ACTA GEOGRAPHICA GEOGRAFSKI ZBORNIK SLOVENICA 2021 61 2 ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKIZBORNIK 61-2 2021 2 ZNANSTVENORAZISKOVALNI CENTER SLOVENSKE AKADEMIJE ZNANOSTI IN UMETNOSTI GEOGRAFSKI INŠTITUT ANTONA MELIKA • RESEARCH CENTRE OF THE SLOVENIAN ACADEMY OF SCIENCES AND ARTS ANTON MELIK GEOGRAPHICAL INSTITUTE ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKIZBORNIK 61-2 2021 LJUBLJANA 2021 ACTA GEOGRAPHICA SLOVENICA 2021 ISSN: 1581-6613 UDC: 91 © 2021, ZRC SAZU, Geografski inštitut Antona Melika International editorial board/mednarodniuredniškiodbor:ZoltánBátori(Hungary),DavidBole(Slovenia),MarcoBontje(the Netherlands), Mateja Breg Valjavec (Slovenia), Michael Bründl (Switzerland), Rok Ciglic (Slovenia), Lóránt Dénes Dávid (Hungary), Mateja Ferk(Slovenia), Matej Gabrovec (Slovenia), Matjaž Geršic (Slovenia), Maruša Goluža (Slovenia), Mauro Hrvatin (Slovenia), Ioan Ianos (Romania), Peter Jordan (Austria), Drago Kladnik (Slovenia), Blaž Komac (Slovenia), Jani Kozina (Slovenia), Andrej Kranjc (Slovenia), Matej Lipar (Slovenia), Dénes Lóczy (Hungary), Simon McCarthy (United Kingdom), Slobodan B. Markovic (Serbia), Janez Nared(Slovenia), Cecilia Pasquinelli (Italy), Drago Perko (Slovenia), Florentina Popescu (Romania), Garri Raagmaa (Estonia), Ivan Radevski (North Macedonia), Marjan Ravbar (Slovenia), Nika Razpotnik Viskovic (Slovenia), Aleš Smrekar (Slovenia), Vanya Stamenova(Bulgaria), Annett Steinführer (Germany), Mateja Šmid Hribar (Slovenia), Jure Ticar (Slovenia), Jernej Tiran (Slovenia), Radislav Tošic(Bosnia and Herzegovina), Mimi Urbanc (Slovenia), Matija Zorn (Slovenia), Zbigniew Zwolinski (Poland) Editors-in-Chief/glavna urednika: Rok Ciglic; rok.ciglic@zrc-sazu.si, Blaž Komac; blaz.komac@zrc-sazu.si Executive editor/odgovorni urednik: Drago Perko; drago.perko@zrc-sazu.si Chief editors for physical geography/podrocni uredniki za fizicno geografijo: Mateja Ferk; mateja.ferk@zrc-sazu.si, Matej Lipar; matej.lipar@zrc-sazu.si, Matija Zorn; matija.zorn@zrc-sazu.si Chief editors for human geography/podrocni uredniki za humano geografijo: Jani Kozina; jani.kozina@zrc-sazu.si,Mateja Šmid Hribar; mateja.smid@zrc-sazu.si, Mimi Urbanc; mimi.urbanc@zrc-sazu.si Chief editors for regional geography/podrocni uredniki za regionalno geografijo: Matej Gabrovec; matej.gabrovec@zrc-sazu.si,Matjaž Geršic; matjaz.gersic@zrc-sazu.si, Mauro Hrvatin; mauro.hrvatin@zrc-sazu.si Chief editors for regional planning/podrocni uredniki za regionalno planiranje: David Bole; david.bole@zrc-sazu.si, Janez Nared; janez.nared@zrc-sazu.si, Nika Razpotnik Viskovic; nika.razpotnik@zrc-sazu.si Chief editors for environmental protection/podrocni uredniki za varstvo okolja: Mateja Breg Valjavec; mateja.breg@zrc-sazu.si, Jernej Tiran; jernej.tiran@zrc-sazu.si, Aleš Smrekar; ales.smrekar@zrc.sazu.si Editorial assistant/uredniška pomocnica: Maruša Goluža; marusa.goluza@zrc-sazu.si Journal editorial system manager/upravnik uredniškega sistema revije: Jure Ticar; jure.ticar@zrc.sazu.si Issued by/izdajatelj: Geografski inštitut Antona Melika ZRC SAZU Published by/založnik: Založba ZRC Co-published by/sozaložnik: Slovenska akademija znanosti in umetnosti Address/naslov: Geografski inštitut Antona Melika ZRC SAZU, Gosposka ulica 13, p. p. 306, SI – 1000 Ljubljana, Slovenija The article are available on-line/prispevki so dostopni na medmrežju: http://ags.zrc-sazu.si (ISSN: 1581–8314) Ordering/narocanje: Založba ZRC, Novi trg 2, p. p. 306, SI – 1001 Ljubljana, Slovenija; zalozba@zrc-sazu.si Annual subscription/letna narocnina: 20 € for individuals/za posameznike, 28 € for institutions/za ustanove. Single issue/cena posamezne številke: 12,50 € for individuals/za posameznike, 16 € for institutions/za ustanove. Cartography/kartografija: Geografski inštitut Antona Melika ZRC SAZU Translations/prevodi: DEKS, d.o.o. DTP/prelom: SYNCOMP, d.o.o. Printed by/tiskarna: Present, d.o.o. Print run/naklada: 400 copies/izvodov The journal is subsidized by the Slovenian Research Agency and is issued in the framework of the Geography of Slovenia core research pro-gramme (P6-0101)/Revija izhaja s podporo Javne agencije za raziskovalno dejavnost Republike Slovenije in nastaja v okviru raziskovalnega programa Geografija Slovenije (P6-0101). The journal is indexed also in/Revija je vkljucena tudi v: Clarivate Web of Science (SCIE – Science Citation Index Expanded; JCR – Journal Citation Report/Science Edition), Scopus, ERIH PLUS, GEOBASE Journals, Current geographical publications, EBSCOhost, Georef, FRANCIS, SJR (SCImago Journal & Country Rank), OCLC WorldCat, Google scholar, and CrossRef. Design by/Oblikovanje: Matjaž Vipotnik. Front cover photography: Slovenia's longest river, the Sava, bubbles to the surface in the crystal clear emerald waters of the Zelenci Nature Reserve in northwestern Slovenia near the Slovenia-Austria-Italy border triangle (photograph: Matija Komac).Fotografija nanaslovnici:Sava, najdaljša slovenskareka,prihaja na površjekristalnocistesmaragdne vode naravnega rezervataZelenci, kiležijo vseverozahodniSlovenijiblizu slovensko-avstrijsko-italijansketromeje (fotografija: Matija Komac). ISSN: 1581-6613 UDC: 91 Number: 61-2 Year: 2021 Contents Ðordije VASILjEVIc, Milica BEGAN, Miroslav VujIcIc, Thomas HOSE,uglješa STANkOVDoes geosite interpretation lead to conservation? A case study of the Sicevo Gorge (Serbia) 7 Gabrijela POPOVIc, Dragiša STANujkIc, Predrag MIMOVIc,Goran MILOVANOVIc, Darjan kARABAšEVIc, Pavle BRzAkOVIc,Aleksandar BRzAkOVIc An integrated SWOT – extended PIPRECIA model for identifying key determinantsof tourism development: The case of Serbia 23 Robert kALBARCzyk, Eliza kALBARCzykPrecipitation variability, trends and regions in Poland: Temporaland spatial distribution in the years 1951–2018 41 Ivana CRLjENkO, Matjaž GERšIc A comparison of the beginnings of exonym standardization in Croatianand Slovenian 73 Tadej BREzINA, jernej TIRAN, Matej OGRIN, Barbara LAACOVID-19 impact on daily mobility in Slovenia 91 Maruša GOLuŽA, Maruška šuBIC-kOVAc, Drago kOS, David BOLEHow the state legitimizes national development projects: The Third Development Axis case study, Slovenia 109 Tin LukIc, Tanja MICIc PONjIGER, Biljana BASARIN, Dušan SAkuLSkI,Milivoj GAVRILOV, Slobodan MARkOVIc, Matija zORN, Blaž kOMAC,Miško MILANOVIc, Dragoslav PAVIc, Minucer MESAROš, NemanjaMARkOVIc, uroš DuRLEVIc, Cezar MORAR, Aleksandar PETROVIc Application of Angot precipitation index in the assessment of rainfall erosivity:Vojvodina Region case study (North Serbia) 123 5 janij OBLAk, Mira kOBOLD, Mojca šRAjThe influence of climate change on discharge fluctuations in Slovenian rivers 155 Vladimir STOjANOVIc, Dubravka MILIc, Sanja OBRADOVIc,jovana VANOVAC, Dimitrije RADIšIcThe role of ecotourism in community development: The case of the ZasavicaSpecial Nature Reserve, Serbia 171 Marko V. MILOšEVIc, Dragoljub šTRBAC, jelena cALIc,Milan RADOVANOVIc Detection of earthflow dynamics using medium-resolution digital terrain models:Diachronic perspective of the Jovac earthflow, Southern Serbia 187 6 DOES GEOSITE INTERPRETATION LEAD TO CONSERVATION? A CASE STUDY OF THE SICEVO GORGE (SERBIA) Ðordije Vasiljevic, Milica Began, Miroslav Vujicic, Thomas Hose, Uglješa Stankov The landscape of the Sicevo Gorge. DOI: https://doi.org/10.3986/AGS.8753 UDC: 913:551.435.11:502.13(497.11) COBISS: 1.01 Ðordije Vasiljevic,1 Milica Began,1 Miroslav Vujicic,1 Thomas Hose,1,2 Uglješa Stankov1 Does geosite interpretation lead to conservation? A case study of the Sicevo Gorge (Serbia) ABSTRACT: People have appreciated the beauty of natural landscapes, the result of the interplay of dif­ferentnaturalprocesses,foratleastthreehundredyearsinEurope.Manyhavebeeninspiredbythisbeauty topromotesuchplacesforvisitsbyothers.Somehaveunderstoodtheimportanceofindividualplacesvis­ited within the local or regional environmental system. This has led to definitions and the establishment of protected areas with special visitor rules and regulations. This article presents a case study of Sicevo Gorge Nature Park in Serbia and an opportunity to transform it into a geoheritage site, underpinned by developing itsinterpretation basedontheresults of a studyusing theanalytical-hierarchyprocess(AHP) method. KEYWORDS: geoheritage, interpretation, gorges, Sicevo, Serbia Ali interpretacija obmocij geološke dedišcine zagotavlja njihovo ohranjanje? Primer soteske Sicevo v Srbiji POVZETEK: V Evropi ljudje že vec kot 300 let obcudujejo lepoto naravnih pokrajin, ki je rezultat medsebojnegaucinkovanjarazlicnihnaravnihprocesov.Mnogejetalepotaspodbudilaktemu,dasotake kraje promovirali kot prostore,vredne obiska, nekateri pa so razumeli tudipomen posameznih krajev,ki sojihobiskali,vlokalnemaliregionalnemokolju. Natejpodlagisobilaopredeljenainustanovljenazavarovana obmocja s posebnimi pravili in predpisi za obiskovalce. V clanku je obravnavan primer naravnega parka soteske Sicevo v Srbiji in možnost njegove preobrazbe v obmocje geološke dedišcine na podlagi obliko­vanja njegove interpretacije v skladu z izsledki raziskave, v kateri je bila uporabljena metoda analiticnega hierarhicnega procesa (AHP). KLJUCNE BESEDE: geološka dedišcina, interpretacija, soteske, Sicevo, Srbija This article was submitted for publication on July 2nd, 2020. Uredništvo je prejelo prispevek 2. julija 2020. 1 University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism, and Hotel Management, Novi Sad, Serbia dj.vasiljevic@dgt.uns.ac.rs (https://orcid.org/0000-0002-1225-4409), voyageouse@gmail.com (https://orcid.org/0000-0003-2629-2040), miroslav.vujicic@dgt.uns.ac.rs (https://orcid.org/ 0000-0003-0003-7869), t.hose123@btinternet.com (https://orcid.org/0000-0001-5699-7389), ugljesa.stankov@dgt.uns.ac.rs (https://orcid.org/0000-0002-7731-592X) 2 University of Bristol, School of Earth Sciences, Bristol, United Kingdom t.hose123@btinternet.com (https://orcid.org/0000-0001-5699-7389) 1 Introduction Geoconservation,asafairlyrecentlyrecognizeddiscipline(Larwood2016)withintheEarthsciences,pro­vides information useful for solving environmental problems of social relevance, such as inappropriate land-use planning and geo-exploitation (Hose 2011), which might endanger the physical integrity of geo-heritage (Henriques et al. 2011). In addition, it designs suitable and specialized services necessary and appropriate for their mitigation. Geoconservation is an important discipline in conserving abiotic nature and, thanks to its various methods, it can be used as an educational tool. It also can be designed to simul­taneouslypreservenature,educate,andcreateprofit.Itthusdefinesabodyofknowledgecruciallyimportant to the creation of products (interpretative geotrails, geo-reserves, and geoparks) that, in addition to guar­anteeing the protection of abiotic nature, are capable of promoting economic and social development at every scale from local to global – that is, geotourism (Hose 1997; 2011) – extending to current interpreta­tions of sustainable development. Activities undertaken in, and travelers’ journeys into, wild and natural landscapes that would now be subsumed within geotourism can be recognized in Europe (Hose 2016), including Serbia (Vasiljevic, Markovic and Vujicic 2016), since at least the late seventeenth century. This study presents research on three stakeholder groups (visitors, guides, and experts) that use var­ious interpretation tools for different purposes during their visits to the case study area, the Sicevo Gorge ineasternSerbia.Theaimistodiscoverhowvarioususersofnaturalareasperceiveinterpretation,andwhich ofitsinstrumentsandtoolstheyfindmostrelevant.Suchinformationisusefulformanagingprotectedareas and for nature-based tourism (such as geotourism and ecotourism) in creating enjoyable experiences for visitors and satisfying them while ensuring sustainability (in terms of nature conservation). 2 Geoheritage interpretation in brief The use of suitable presentation techniques can make complex and difficult geological and geomorpho­logical phenomena, as elements of geoheritage, both interesting and easier for the public to understand. Generally, there are two reasons why geoheritage needs to be presented. First, it is important in under­pinning well-known landscapes and geodiversity. Despite this, geoheritage is farthest from the public in terms of knowledge, interests, and general presentation in comparison to other more easily identifiable aspectsofnaturalheritage,especiallybiodiversity.However,similartobiodiversity,geoheritageisvulnerable to both human activities and various natural processes that might damage it (Komac, Zorn and Erhartic 2011). The damage is long-term and difficult, often impossible, to remediate. Therefore, only those peo­ple and local communities that are aware of their geoheritage, and can both identify with and relate to it, can contribute to its conservation and sustainable development. Geoheritage presentation has a clear role in establishing real links between biodiversity and geodiversity, and the equal need to preserve them. Second, geoheritagepresentation supports the opportunity that geodiversity offers for tourism devel­opment at the local and national levels. The sound explanation and presentation of geological and geomorphological phenomena will enhance the visitor experience and help boost geotourism potentials(Štrba, Baláž and Lukác 2016). The interpretation of geoheritage is considered the art of explaining the meaning and significance of geosites to visitors (Xu et al. 2015). The modern idea of interpretation was born in the United States, where Tilden (1977) suggested that producing pamphlets could help tourists understandunfamiliaraspectsofnature,includingageologicalphenomenoninYellowstoneNationalPark that was misunderstood by them. After the idea’s success, guided tours by park rangers and concessioners wereoffered,andthefirstnatureinterpretationprogrambytheUnitedStatesNationalParksService(Nunes 1991;Beganetal.2016)wascreated.AccordingtotheWorldTourismOrganization(WTO)andUnitedNations EnvironmentProgramme(UNEP),educationandinterpretationarekeyelementsofvisitorprovisionused by administrators to better manage and provide for tourists (Making…2005) and meet their needs. Environmental interpretation (Pierssene 1999) is part of environmental education (Ballantyne 1998), being the term used to describe communication activities undertaken to better understand the naturalenvironmentinprotectedareas,natureparks,nationalparks,naturalhistorymuseums,andother venues (Vasconcelos 2003). Its provision aims to preserve and conserve natural resources and seeks to increase visitor satisfaction, serving as a management tool. Ham (1992) argues that it is a form of com-munication,alanguagethattranslatestechnicalscience,environmentalscience,andrelatedmattersinto readilyunderstandabletermsandideasforpeoplewithoutscientifictrainingorinclination.Itaimstosen­sitizevisitorstosee,explore,observe,analyze,understand,andengenderfeelingsfornaturalheritage,including geological heritage, that they visit. To reveal the deeper meaning of a historical reality or a landscape, it is essential to carry out research and follow its results. Thus, Werner (1996) explains that visitors should be offered interpretations of heritage,not inventions or distortions. Murta and Albano(2005)suggest that to interpretheritageistopresentplacesandculturestovisitorsandtoenrichtheirexperience.Environmental interpretationis»atechniqueflexibleandmalleabletodifferentsituations«(César et al.2007).Thus, it can and should be performed to the advantage of the geology and geomorphology of an area with significant geoheritage. Generally, such interpretation is particularly necessary for the purposes of geotourism (Hose et al.2011;Vasiljevic et al.2011),ecotourism(Mastrini et al.2018),andsustainabletourism(Moreira 2012;Began et al. 2016). 3 Study area The Sicevo Gorge (Sicevacka klisura) lies along the Nišava River (Figure 1). It connects the Bela Palanka Basin (Belopalancka kotlina) to the east with the lower Nišava Valley (Ponišavlje) to the west. The litho­logicalbasisoftheSicevoGorgeisPaleozoic,Mesozoic,andTertiary–Neogenesandstonesandlimestones (Figure 2). Quaternary rock, primarily alluvial deposits,andscree frequently obscure them as well as cre­atingtheirownlandforms.Locallyknownasthe»SerbianCappadocia«(NationalGeographicSrbija,2016) it is an oasis of rare plants and animals, the setting of various geosites, and an important cultural, histor­ical, and religious location. A Roman military road, the Via Militaris (Figure 3b), was constructed here in the first century AD and was used later during Ottoman rule, from the fourteenth to the early twentieth centuries,intheBalkans.Hence,manydifferentcivilizationshavetraveledthroughthisgorge,underpinning its historical and cultural significance. Kostic (1954) distinguishes three morphological units (Figure 2) in the gorge. The easternmost part, about 7km long, is called the Gradište Canyon (Gradiški kanjon, locally known as Gradištanski kanjon) after the nearby village of Gradište, although this part of the gorge also carries a number of other names: UpperGorge(Gornjaklisura),BigSicevoGorge(Velikasicevackaklisura),OstrovicaGorge(Ostrovickaklisura), Crnce–GradišteCanyon(Crnacko-gradištanskaklisura),andOstrovica–GradišteCanyon(Ostrovicko-gradiš­tanskaklisura).ThesecondunitistheOstrovicaextensionandthethirdistheProsekGorge(Proseckaklisura). Figure 1: Geographical position of the Sicevo Gorge. Figure 2: Geological composition of the Sicevo Gorge (adapted after Began 2019). p Mitic (2006) divided the Sicevo Gorge into two parts: the upper part (the canyon) and the lower part (the gorge). Ciric (2006) distinguished four parts: the Svrljig Mountains (Svrljiške planine), part of the Ploce Plateau (visoravan Ploce) and the Kunovica area (with Mount Oblik and Mount Kusaca), the Ostrovica Basin(Ostrovickakotlina),andtheSicevoGorge.IntheSicevoGorge,thesameauthordistinguishedthree parts: the Gradište Canyon, the passage through the Ostrovica Basin, and again the Sicevo Gorge in the narrow sense (Began et al. 2016). The same author continues description of the study area: »The canyon part of the Sicevo Gorge, Gradište Canyon, cuts between Mount Oblik (901m) to the north and the Svrljig Mountains (Mount Golubnjak, 1,179m; Mount Pleš, 1,267m; and Mount Tupanar, 1,106m) to the south. The canyon consists of steep and vertical, often terraced rocky cliffs. The width of the canyon at the bottom is mainly reduced to the bed of the Nišava River. The height of the rocky canyon walls reaches about 400m on the north side of Mount Oblik, whereas the average direct canyon depth to the valley is about 250m. The southsideofthecanyonextendscontinuously,withtheexceptionofthevalleyofBabicaCreek,wheretheNišava River flows into the gorge. The north side is cut by the valleys of several small intermittent tributaries of the Nišava River, as well as steep longitudinal profiles and hanging valleys« (Began 2019, 92). Downstream from the Gradište Canyon, approximately between the St. Petka Monastery (Figure 3d) and the mouth of Ostrovica Creek (Ostrovicki potok), the Nišava River flows through a basin extension, with a wide bottom and slightly sloping sides, about 2km long. This extension is tectonically predisposed and built in the domain of the small Neogene Ostrovica Basin and St. Petka Basin, and then transformed byfluvialanddenudationprocesses. Thebeltoflowerterrainrunsdeeptowardthesoutheasterncountry-sidearoundthegorgealongthevalleyofOstrovicaCreek,allthewaytothevillageofRavniDo(Mitic2006). Figure 3: Scenery and landmarks of the Sicevo Gorge. (a) The edge of the village of Sicevo; (b) The exit of the gorge toward Niš (part of the Via Militaris is best preserved here, but barely visible); (c) The slopes of the gorge seen from the river; (d) The St. Petka Monastery in the village of Ostrovica. ThepartofthevalleydownstreamfromtheSt.PetkaBasiniscalledtheProsekGorge(Proseckaklisura). It is about 8km long and is morphologically very diverse. The first, most upstream part of it, 1.5km in length,isinthesoutheasternpartofthegorge,nexttoverticalrockycliffsover200mhighandsteep,occa­sionally vertical sections about 150m high on the north (Brljavski kamen ‘Dirty Cliff’). At the end of this narrowedsectorofthevalley,approximatelyatthelineofthevillageofSicevo,theNišavaRivercompletely cuts through the complex limestone rocks and begins to cut into the substrate of Devonian and Permian sandstones,conglomerates,siltstone,andclays.Duetothelesserresistanceoftheserockstoerosionalprocess­es, the bottom parts of the valley lost their typical gorge features; that is, the valley sides are less steep and the valley floor widens. In the limestone rocks that build the upper, higher sections of the valley, the sides form rock sections, both on Mount Jecava to the north and Mount Kusaca to the south. However, those sections away from the river, with the particularly impressive limestone excavations of Mount Kusaca, are lined up in an arched, amphitheatrical series. At the base of these sections there is a belt of steeply sloping screes, and below them slightly gentler slopingterrainconstructedofPaleozoicrocks.Downstreamfromthelineonwhichthelimestonesofboth Mount Kusaca and Mount Jecava end to the west, along the line from Red Hill (Crveno brdo) to the vil­lage of Prosek, in the double bend of the Nišava River, the valley is built of Permian red sandstones and, due to the steeper slopes and slightly narrower bottom, the river cut meanders (Krumin 2006; Mitic 2006; Began 2019). Abovethegorge,thelimestoneplateausarepockmarkedwithdolines(Krumin2006).TheSicevoGorge is rich in underground karst features, mainly caves without speleothems. Most of the caves are preserved intheirnaturalconditionandarehydrographicallydry.TherapidcuttingoftheNišavaRiverintotheSicevo Gorge and the onset of deep karstification did not allow more constant underground flows a given level and thus the development of larger cave channels. The most common Serbian term for these small caves is dupke (Jovanovic 1891). Big Balanica Cave (Velika Balanica, 20m long) and Little Balanica Cave (Mala Balanica, 12m long) are the best known and most explored in the Sicevo Gorge, located near the village of Sicevo. The entrances to both caves are at an elevation of 332m and they are only 7m apart. Pleistocene deposits,mammalianfossils,andPaleolithicworkedflintremainshavebeenfoundinbothcaves.Theremains date to the Middle Pleistocene: nine teeth and seven bones from hands and feet, as well as a human jaw, which has been described as a remnant of archaic Homo sapiens (Roksandic et al. 2011; Cvetkovic and Dimitrijevic2014);cavebearremainswerealsofoundhere(Began2019).Inthegorgeareatherearealarge number of springs with karst water or through which free water discharges in Neogene sediments and Paleozoic rock (Kostic and Martinovic 1967). 4 Methods In order to achieve the study’s goals, the authors employed the analytical-hierarchy process (AHP), a sys-tematicapproachdevelopedbySaaty(1980)andusedinmulti-criteriadecision-making.TheAHPpresents amulti-criteriadecision-makingmethodologythatisnoteworthyforitsacceptanceofthesubjectivenature of the information used in many decision-making contexts (Hsu, Tsai and Wu 2009). Through its oper­ations, the subjectivities and biases given in individual responses can be factored into the model, allowing for the gradual refinement of decision-making criteria, which means that it is particularly relevant in the context of tourism development and planning, in which, for example, decisions about resource allocation and promotion can be contestable and problematic. Withcomplexdecisions,duetodifferentcriteriaandalternatives,thedecision-makingprocessbecomes complex, comprising mutually connected and dependent factors, further influencing the final decision (Jandric and Srdevic 2000). The AHP provides solutions to complex problems and employs hierarchical structuresthroughdevelopingprioritiesfordifferentalternativesdeterminedbythedecision-makers(Brushan and Rai 2004). Its final output is an evaluation model for decision-making, dependent upon weighted cri­teria.Itintegratesdifferentmeasuresintoasingleoverallscoreforrankingdecisionalternatives(Hsu,Tsai and Wu 2009). It is used to simplify multiple criterion problems by deconstructing them into a multilevel hierarchical structure (Harker and Vargas 1987) because it gradually compares alternatives and measures their impact on the final decision-making goal; this helps decision-makers in their choices between com­peting alternatives (Saaty 1980). Givenapairwisecomparison,theAHPanalysisinvolvesthreetasks:1)developingacomparisonmatrix at each level of the hierarchy starting from the second level and working down, 2) computing the relative weights for each element of the hierarchy, and 3) estimating the consistency ratio (CR) to check the con­sistency of the judgment (Božic et al. 2018; Vujicic et al. 2020). If the consistency ratio (CR) is less than 0.10, the result is sufficiently accurate and there is no need for adjustments in comparison or for repeat-ingthecalculation.Iftheratioofconsistencyisgreaterthan0.10,theresultsshouldbereanalyzedtodetermine thereasonsforinconsistenciesandtoremovethembypartialrepetitionofthepairwisecomparison.When repetition of the procedure in several steps does not lead to reduction of the consistency to the tolerable limitof0.10,alltheresultsshouldbediscardedandtheentireprocedureshouldberepeatedfromthebegin­ning(JandricandSrdevic2000).Inordertoevaluatethecriteriaweightforattitudestowardinterpretation means among respondents that have visited, researched, or worked at the Sicevo Gorge, the authors first developedahierarchicallystructuredmodel(Figure4)basedoncertainindicators,adaptedfromVujicicetal. (2011;2018)andPetrovic et al.(2013).TheythenappliedtheAHPmodel,amethodwithincreasingappli-cation in tourism research literature (Scholl et al. 2005). 4.1 Study sample The sampling strategy for the AHP method can be based on a suitably chosen purposeful sample that is appropriateforgeneratingqualitativedata,usefulforresearchfocusingonaspecificissueforwhichalarge sample is not necessary, especially in tightly bounded case studies (Lam and Zhao 1998; Cheng, Li and Ho2002).Purposefulsampling(Coyne1997)wasdeemedappropriateforthisresearchbecauseofthelim­ited need for generalization from the case study (Creswell 2007). Cheng and Li (2002) argue that the AHP method is in fact made impractical in research with a large sample size because »cold-called« non-expert respondents may have a great tendency to provide arbitrary answers, resulting in a very high degree of inconsistency, which invalidates the approach (Wong and Li 2008). The data were collected within a case study,inwhichquestionnairesweredistributedbytheresearchersintoapurposefullyselectedsamplepop­ulation.These were subdivided into three groups: 1) ten guides (tour guides experienced in nature-based tourism); 2) ten experts (tourism experts, geosite experts, geoheritage experts, hikers, and geographers); and 3) ten individuals (respondents that had visited the Sicevo Gorge). Thus, the final sample consisted of thirty respondents of various ages, nationalities, and sexes. 4.2 Questionnaire design and research phases Research design and implementation have been particularly well and concisely covered by the Tourism andRecreationResearchUnit(1983)intheUnitedKingdom;itcoversmanyoftheresearchtermsemployed Figure 4: Scheme of various interpretation and signaling tools presented to respondents. herein.Thefirstphaseoftheresearchincludeda reviewofrelevantpreviousliterature(Vujicic et al.2011, 2018;Petrovic2013;Višnic,SpasojevicandVujicic2016)andtheselectionofallthefactorsdefininginter­pretationtools,thushelpingdefinethefinalmodelbasedonthemodifiedindicatorscreatedbyVujicic et al. (2011). The authors selected eight indicators (Figure 4) to be measured by the AHP model. The indica­tors are formed according to the most relevant factors included in the decision-making process. After the selection of the factors and the design of the questionnaires, the second phase of the research was initiat­ed; this included the interviewed respondents, as well as the entry of the collected data into the statistical computer program Expert Choice 2000 – AHP Software for Decision Making and Risk Assessment (expertchoice.com).Finally,theconsistencyoftheoverallresearchwasdetermined,aswellasthefinalrank­ing of the factors, by calculating the weight coefficients. 4.3 Procedure The research for this case study was conducted in 2018, from March through to June. The respondents participated in the research on a volunteer basis. All of them were thoroughly informed about the pur­poseoftheresearch,aswellastheresearchers’identities.Theywereadvisedthattheircontributionswould berecordedanonymouslyandthatthedatawouldbeusedstrictlyandsolelyforthepurposesoftheresearch. Astructuredinterview,basedonapreprintedquestionnaire,wasemployedinwhichtheinterviewerasked set questions, filling in the answers on the questionnaire. In this way, any possible misunderstandings of the carefully derived questions were eliminated. Respondents were asked to express their attitudes toward interpretation tools when visiting geosites, measuringtheirimportancefactorbyusingSaaty’s(1980)scale(Table1).Theauthorsgavebriefstandardized explanationsofeachcriterion(orfactor)beforeandduringthestructuredinterview.Therespondentswere required to assign a corresponding numerical value (Saaty’s scale) to different factors based on the rela­tive importance they considered the factor had for them. Table 1: Saaty’s scale for pairwise comparisons in AHP. An intermediate numerical value of 2, 4, 6, 8 and 1/2, 1/4, 1/6, 1/8 can be used as well (Saaty 1980). Judgment term (elements A and B) Numerical term Absolute preference (A over B) 9 Very strong preference (A over B) 7 Strong preference (A over B) 5 Weak preference (A over B) 3 Indifference of A and B 1 Weak preference (A over B) 1/3 Strong preference (A over B) 1/5 Very strong preference (A over B) 1/7 Absolute preference (A over B) 1/9 In post–research group decision-making, an aggregation of each respondent’s resulting priorities was computed using the geometric mean, which is more consistent with the meaning of priorities in AHP (Božic et al. 2017; Vujicic et al. 2018). 5 Results The synergy of all responses (Figure 5) from the respondents shows that the most important factor for measuring interpretation tools is guiding services (0.161), followed by tourist signalization (0.144) and interpretative boards (0.138), whereas the least important factors are printed materials (0.102) and mountain signalization (0.106). The consistency ratio (CR) is 0.03, which indicates that the study is reli­able and accurate, and therefore there is no need for adjustments in the comparison of criteria. Figure5showsthesignificanceofguidingservices,whichtherespondentsmarkedasfarmoreimpor­tant than all the other interpretation indicators. Guiding services can improve and bring interpretation toacompletelynewlevel.Irrespectiveoftheavailabletechnologythatcanbeemployed,acompetentguide will always be one of the best interpretation tools. Before taking any action for creating high-value inter-pretationintheSicevoGorge,itisnecessarytoofferappropriategeointerpretationtraining.Thereareasuitable number of tour guides in the city of Niš, but most of them do not have experience in geo-interpretation. There are also mountain guides, who lack experience in working with tourist groups. By setting up prop-ergeo-interpretationtrainingforbothparties,itispossibletocreatehigh-qualitygeo-interpretationservices. Table2showstheweightofthepreferencesforinterpretationtoolsamongthreedifferentgroups.Visitors ratedguidingservices(0.200)themostimportantinterpretationtool,followedbytouristsignaling(0.163) and interpretation boards (0.126), whereas the least important were modern devices (0.084) and hiking signaling (0.088). Experts gave preference to and rated interpretation boards (0.165) as the most important factor, fol­lowed by modern devices (0.147) and hiking signaling (0.141), whereas the least important are printed materials(0.097)andguidingservices(0.100).Theguidesgavethehighestscoretoguidingservices(0.231), Figure 5: Synergy of all responses. Table 2: Weight of preferences for interpretation tools among three different groups. Visitors Experts Guides Guiding services (0.200) Interpretation boards (0.165) Guiding services (0.231) Tourist signaling (0.163) Modern devices (0.147) Modern devices (0.144) Interpretation boards (0.126) Hiking signaling (0.141) Tourist signaling (0.129) Printed materials (0.117) Tourist signaling (0.132) Interpretation boards (0.108) Visitor center (0.113) Traffic signaling (0.115) Visitor center (0.108) Traffic signaling (0.110) Visitor center (0.102) Traffic signaling (0.105) Hiking signaling (0.088) Guiding services (0.100) Printed materials (0.088) Modern devices (0.084) Printed materials (0.097) Hiking signaling (0.086) followed by modern devices (0.144) and tourist signaling (0.129), whereas the least important are hiking signaling (0.086) and printed materials (0.088). The consistency ratio (CR) for the visitors is 0.02, for the experts it is 0.03, and for the guides it is 0.04, which means that this sample, as well as the result, is suffi­ciently reliable and accurate, and therefore there is no need for additional adjustments. 6 Concluding remarks: management implications The interpretation of geoheritage and the dissemination of knowledge about the Earth is accomplished by various means and techniques, both in situ and ex situ and with or without the personal interaction of an interpreter (Hose 1995; 2000). The results of various indicators posed as questions to the respondents are presented in Tables 1 and 2.Afterconsideringthe results,the authors propose various actions in order to improve geoheritage interpretation at the case study location. The tourism-related respondents (visitors and guides) in general gave preference to guiding services andtouristsignalingasimportantfactors.Thisindicatesthattheyconsiderthesetoolsimportantelements ofgeoheritageprotectionandinterpretationinthe SicevoGorge.Highlytrainedandwell-educatedguides can both teach and develop visitors’ positive feelings about the Sicevo Gorge, as well as showing them its best aspects. They can present visitors with geoheritage features and their values in the best way possible because they are in direct contact with the visitors. Because there are currently no specialized tour guides for the Sicevo Gorge, it is necessary to offer appropriate training for such guides and, following the exam­ple of best guiding practice in other geosites in Europe, teach them the skills of high-quality geoheritage guiding.TheaforementionedLittleandBigBalanicaCavesareimportantandattractivearchaeologicalsites, unique in Serbia. They should be evaluated, protected, and opened up to carefully managed visitors. The Balanica Caves’ prehistoric finds have already attracted much attention; a properly developed interpreta­tionschemecanbothbetterpresentthissitetocurrentvisitorsandbringittotheattentionofawideraudience. What might also be useful in justifying interpretation as a tool for geoconservation is the high values assigned to signaling (in general) and interpretation boards by all three groups of respondents. Mountain signalization(eventhoughthisisbasicsignalizationforanyoutdoorspace)isleastimportantfortherespon­dents;thereasonforthismightbethatmostofthevisitorsthatrespondeddonotunderstandthemeaning of this signalization. Tourist signalization and interpretative boards – which make the area more attrac­tive when features that visitors see are explained – are the most important indicators for the respondents. The importance of interpretative boards must be emphasized, and significant attention should be paid to this means of interpretation. The organization and design of interpretation boards needs to be appropri-ateandfollowoneideaandstoryline.Interpretationboards,orevenQRcodesthatlinktoonlineresources as a more cost-effective solution, need to be installed at every attractive spot; however, overt visual intru­sion should be avoided so that there are not so many boards that they become visually dominant in the naturallandscape.Theyshouldinterpretgeologicalandgeomorphologicalfeaturesinsuchawayastopro­vide visitors with interesting information that will engage them in further and future exploration. The information provided on the panels should contain facts of interest to various types of visitors, facts they did not already know, and facts specific to the area. The main idea should be a desire for visitors to leave the place satisfied, energized, more informed, and better aware of the significance of the place they have just visited. Special attention must be paid to this analogue interpretation means. Even though other bet-ter-developedandbetter-organizednaturalsitesrelyonmoderndigitaldevices(Stankov et al.2019)more than on interpretation panels, the respondents’ opinions show the importance of the interpretation pan­els, and this finding cannot be ignored. Before explaining any kind of natural heritage to potential visitors, it is fundamentally necessary to waymark all the paths in the Sicevo Gorge and ensure that appropriate and adequate safety measures are inplace.TheSicevoGorgehasalwaysbeenafavoriteplaceformanyprofessionalandamateurnaturelovers, and so its paths are currently clearly marked with hiking signalization. All the signalization is clear and visible because it is remarked every spring and autumn. It should be noted that the hikers’ signalization is for their specific purposes; this means that all potential visitors must know how to read and understand its specialized markings. However, it is possible to rely on this signalization to create paths for different typesofvisitors.Pathscanbedividedintosections,fromeasiesttohardest.TheKjugekullgeosite(inSkåne county,Sweden)hasestablishedandmarkedpathsthroughouttheentiregeosite(e.g.,yellowforeasy,green formedium,andredfordifficult).Inthisway,itiseasyforvisitorstofollowthepathmostsuitedforthem. At the start of every path, there is an information board with a map of the path, and information about itslengthandtheapproximatetimeneededtocompleteit.ThisideacaneasilybeimplementedintheSicevo Gorge because its terrain allows it to be marked and divided into easy, medium, and hard sections. This type of signage can also be attractive to visitors. The paths should include the most interesting features of the gorge along with interpretation panels that explain the most important and interesting facts about the features. The Sicevo Gorge is rich in cultural and historical heritage, biodiversity, geodiversity, and folk stories; including these within the overall interpretation will make it even more attractive and accessible to a wide range of visitors of different ages and interests. Because the Sicevo Gorge was part of a historical Roman military road, the Via Militaris (Figure 3b), as well as part of the old Stambol road constructed during the Ottoman era, today it is possible to hike thepathsthatwerepartsoftheseroads,wherevisitorscanfeelasenseofhistory.Thisroadalsohasattrac­tive viewpoints and places of historical events that can be highlighted by attractive interpretation panels, maps, and photographs. Whilecreatingandway-markingthewalkingandhikingpaths,onemustbearinmindhealthandsafe­ty precautions and do whatever is necessary to ensure that visitors will not experience any unwanted or serious events. Putting fences in dangerous places, constructing outdoor steps so that visitors can more easilytacklesomeofthehardinclines,andavoidingthemostdangerousareasorconstructingbridgesover someofthesecanhelpvisitorsreachsomeofthepartsthatareattractive,butcurrentlydifficultandpoten­tiallydangerous.However,abalanceneedstobestruckbetweenachievinggreaterandsaferaccessforvisitors other than hikers and avoiding damage to fragile habitats and detracting from the area’s natural beauty with excessive artificial construction and signage; that is, sustainable ecotourism. TheresultsofthisstudyshouldbetakenintoconsiderationwhencreatingplansforprotectingtheSicevo Gorge. Ithas already beenprotected asanaturepark,butitneeds to befurther protected,especiallyforits geoheritageinterest,bycreatingandimplementingadetailedgeoconservationplan.Atthetimeofwriting thisarticle,onlyafewmonthsaftertrafficwasremovedfromthegorgetoanewhighway,thegorgeisalready fuller than in the past, with nature loversusing this new situation to better enjoy this incredible place. Itis importanttoactquicklyandimplementallthegeoconservationmeans,especiallyinterpretation,inallfuture plans to protect this geological and geomorphological phenomenon for the benefit of future generations. All three groups of respondents, with some essentially minor differences, gave preference to similar interpretation tools to raise awarenessabout these somewhat remote and rather fragile but attractive nat­ural assets. In general, the case study results strongly indicate that interpretation tools can greatly assist in the conservation of geoheritage sites – that is, geoconservation. This is very much in keeping with the truismexpressedsometwentyyearsagobytheGreekgeoconservationistIriniTheodossiou-Drandaki(2000) that there is »no conservation without education.« Although she touched upon environmental interpre­tation, she particularly focused on formal education and significantly noted that »listing a site will not guaranteeitsconservationandprotection.Thiscanonlybeaccomplishedbytouchingeverybody’saware­ness and especially that of young people, who, learning of their home’s geological heritage, will appreciate its value and will consequently protect it.« Environmental interpretation, as advocated by Tilden (1977) – withitsemphasisonnotjustprovidingeducationalinformationbutonbuildingempathybyrevealingmean­ings and relationships through illustrative media such as outdoor panels – appears to have been validated by the respondents’ preferences in this case study. 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Karabaševic, P. Brzakovic, A. Brzakovic, An integrated SWOT… DOI: https://doi.org/10.3986/AGS.9271 UDC: 338.486:004.652(497.11) COBISS:1.01 GabrijelaPopovic1,DragišaStanujkic2,PredragMimovic3,GoranMilovanovic4,DarjanKarabaševic1, Pavle Brzakovic1, Aleksandar Brzakovic1 An integrated SWOT – extended PIPRECIA model for identifying key determinants of tourism development: The case of Serbia ABSTRACT: This paper proposes a new integrated model based on SWOT and extended PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA) that offers a systematic approach to strategic plan­ning in tourism. The applicability of the proposed integrated model is demonstrated through a case study defining the main determinants of tourism development in Serbia. The result emphasizes the strategy Improving the organization, management, and enhancement of tourism development as the highest prior­ity for implementation. The model facilitates decision-making in tourism, and its key advantages are its suitability for application in group decision-making and its simplicity. KEY WORDS: extended PIPRECIA method, SWOT, Serbia, strategy, tourism Integrirani model za dolocanje kljucnih determinant turisticnega razvoja, ki temelji na analizi SWOT in razširjeni metodi PIPRECIA: primer Srbije POVZETEK: V clanku avtorji predlagajo nov integrirani model, ki temelji na analizi SWOT in razširjeni metodiPIPRECIA(PIvotPairwiseRElativeCriteriaImportanceAssessment)teromogocasistematicenpristop kstrateškemunacrtovanjuvturizmu.Uporabnostpredlaganegamodelajepredstavljenasštudijoprimera, vkateriavtorjidolocijoglavnedeterminanteturisticnegarazvojavSrbiji.Izsledkikažejo,dajemedrazlicnimi strategijami najpomembnejša tista, ki se osredotoca na izboljšanje organizacije, upravljanja in krepitve turisticnega razvoja. Model omogoca lažje odlocanje v turizmu, njegova kljucna prednost pa je ta, da je primeren za skupinsko odlocanje in preprost za uporabo. KLJUCNE BESEDE: razširjena metoda PIPRECIA, analiza SWOT, Srbija, strategija, turizem This paper was submitted for publication on November 10th, 2020. Uredništvo je prejelo prispevek 10. novembra 2020. 1 University Business Academy in Novi Sad, Faculty of Applied Management, Economics and Finance in Belgrade, Belgrade, Serbia gabrijela.popovic@mef.edu.rs (https://orcid.org/0000-0002-2652-4860), darjan.karabasevic@mef.edu.rs (https://orcid.org/0000-0001-5308-2503), pavle.brzakovic@mef.edu.rs (https://orcid.org/0000-0001­5184-9627), aleksandar.brzakovic@mef.edu.rs 2 University of Belgrade, Technical Faculty in Bor, Bor, Serbia dstanujkic@tfbor.bg.ac.rs (https://orcid.org/0000-0002-6846-3074) 3 University of Kragujevac, Faculty of Economics, Kragujevac, Serbia mimovicp@kg.ac.rs (https://orcid.org/0000-0003-0323-8033) 4 University of Niš, Faculty of Economics, Niš, Serbia goran.milovanovic@eknfak.ni.ac.rs (https://orcid.org/0000-0003-0091-2774) 1 Introduction Serbia is a landlocked Balkan country. Despite not having sea access, it has significant potential for devel­opingandenhancingvariouskindsoftourism.Today,thedevelopmentpotentialofruraltourisminSerbia has attracted the most attention among researchers (Todorovic and Bjeljac 2009; Dimitrovski, Todorovic andValjarevic2012;Petrovicetal.2018).Apartfromruraltourism,othertypesoftourismsuitablefordevel­opmenthavealsobeenstudied(Košic et al. 2011;Vasiljevic et al. 2011;Vujicic et al.2011;Dragicevic et al. 2012; Dragicevic et al. 2013; Blešic et al. 2014; Vujko and Plavša 2014; Božic and Tomic 2016; Pavlukovic, Stankov and Arsenovic 2020). Mulec and Wise (2013) and Armenski, Dwyer and Pavlukovic (2018) have also examined the competitiveness of the Vojvodina region andSerbia as a whole as tourism destinations. ImprovingtourisminSerbiarequiresdeterminingitspositiveandnegativeaspects,whichcoulddrive or hinder further development. In addition to other data on tourism and predictions for the future, the TourismDevelopmentStrategyoftheRepublicofSerbia2016–2025(2016)alsocontainsaSWOT(strengths, weaknesses,opportunities,andthreats)analysis.Itclearlyoutlinestheinternalandexternalfactorsimpor­tantforfurthertourismdevelopment,aswellasstrategiestotakeadvantageofstrengthsandopportunities, avoid threats, and overcome weaknesses. Despite its benefits, the qualitative nature of SWOT analysis is ashortcoming.ThiscanbeovercomebycombiningSWOTanalysiswithappropriatemultiple-criteriadeci-sion-making (MCDM) methods. This article proposes applying the SWOT – extended PIvot Pairwise RElative Criteria Importance Assessment framework, or PIPRECIA (Stanujkic et al. 2017a). PIPRECIA is a newly developed MCDM methodthatisconvenientforapplicationinagroupdecisionenvironment.ThepaperproposestheSWOT – extended PIPRECIA integrated model as a convenient tool for strategic planning in tourism. The applic­abilityofthemodelispresentedthroughacasestudybasedontourismdevelopmentdatafromtheTourism DevelopmentStrategyoftheRepublicofSerbia2016–2025(2016).ThismodeldeterminesthekeySWOT influential factors, and it prioritizes strategies to improve tourism in Serbia. The paper proposes a new modelbasedonSWOTandtherelativelyrecentlyintroducedMCDMmethod,whosepossibilitiesinstrate­gic planning have not been tested yet. 2 Literature review SWOTanalysisiswidelyusedintourismtoappraiseinternal(strengthsandweaknesses)andexternal(oppor­tunities and threats) factors important for assessing the market position of certain destinations, and it is the first phase in strategic planning and creating a strategy. The applicability of this technique has been shown in variousstudies (Abdi and Azadegan-Mehr 2011; Sariisik, Turkay and Akova 2011; Ghazinoory, Reihanian et al. 2012; Cetin 2015; Gürel and Tat 2017; Cetin et al. 2018).Although SWOT analysis is the startingpointinstrategicplanning,itissometimescriticizedforleadingtothecreationofunsuitablestrate­gies (Hill and Westbrook 1997; Kurttila et al. 2000; Helms and Nixon 2010; Vlados 2019). Such criticism mainly addresses its qualitative nature, inability to express factors quantitatively, and inability to deter-minewhichfactorhasadecisiveimpact(Kajanusetal.2012).Theseshortcomingscanberesolvedbyapplying MCDM methods. MCDM methods have become increasingly popular in recent decades, having been applied in many differentresearchareas(ZavadskasandTurskis2011;Gavade2014;Zavadskas,TurskisandKildiene2014; Stojcic et al. 2019). They are especially convenient for application in situations where a greater number of criteria are included, against which the decision-maker (DM) should perform the evaluation process and make the final decision (Stanujkic et al. 2017b; Stanujkic et al. 2017c; Popovic, Stanujkic and Karabasevic 2019). These techniques are useful in facilitating decisions and increasing the reliability of decisions. In addition to resolving various business problems, MCDM methods are also used to facilitate decisions in tourism with regard to policy (Liu, Tzeng and Lee 2012; Michailidou, Vlachokostas and Moussiopoulos 2016),competitiveness(Wu2011;Zhang et al.2011;HuangandPeng2012;Gómez-VegaandPicazo-Tadeo 2019),sustainabletourismandecotourism(Michalena,HillsandAmat2009;Alianietal.2017;Arsic,NikolicandŽivkovic2017),locationanddestinationselection(Chou,HsuandChen2008;Cheng,SuandTan2013; Morteza et al. 2016; Aksoy and Ozbuk 2017; Puška, Stojanovic and Maksimovic 2019), service quality G. Popovic, D. Stanujkic, P. Mimovic, G. Milovanovic, D. Karabaševic, P. Brzakovic, A. Brzakovic, An integrated SWOT… (Rozman et al. 2009; Tseng 2011; Zoraghi et al. 2013; Wu and Wang 2014), and website quality (Hu 2009; Akincilar and Dagdeviren 2014; Stanujkic, Zavadskas and Tamošaitiene 2015; Stanujkic et al. 2017b). Combining one of these methods with SWOT analysis creates a hybrid model, preserving the bene­fits of SWOT analysis and eliminating the shortcomings explained above. The most popular and most frequently used hybrid model is the A’WOT model, based on combining SWOT analysis and the Analytic HierarchyProcessorAHPmethod(Saaty1980).Thismodelisoftenappliedinstrategicplanningintourism (Kajanus, Kangas and Kurttila 2004; Mimovic, Kocic and Milanovic 2012; Akbulak and Cengiz 2014; Nikolic et al.2015;Demir,EsbahandAkgün2016).InadditiontotheA’WOTmodel,othercombinations ofthe MCDM methods and SWOT analysis have also been proposed as a decision-making aid in tourism(Arsic, Nikolic and Živkovic 2017; Ajmera 2017; Abadi et al. 2018; Khan 2018; Popovic, Milovanovic and Stanujkic 2018; Jiskani et al. 2020). The extended PIPRECIA method is an improved version of the Step-Wise Weight Assessment Ratio Analysis or SWARA method (Keršuliene et al. 2010). It retains the benefits of the SWARA method and amelioratesitsshortcomings.TheSWARAmethodisnotsuitableforgroupdecision-makingenvironments, which may be its crucial disadvantage. This unsuitability arises from the fact that every DM should sort criteria according to their significance, which complicates obtaining the results from all DMs. The possi­bility that each DM could sort criteria in a different order makes evaluation more complex. Furthermore, theSWARAmethoddoesnotanticipateconsistencychecking,andsothereliabilityoftheresultsobtained is somewhat questionable. Group decision-making requires a method that facilitates the process and is easy to apply. Extended PIPRECIA almost entirely meets theserequirements. Namely, extended PIPRECIA does not require pre­sortingofcriteria.Thismethodthereforeautomaticallybecomesmoresuitableforgroupdecision-making. Then, the evaluation procedure is more straightforward than in the AHP method (Saaty 1980). The AHP methodrequiresamoredetailedexplanationthanextendedPIPRECIAforDMsinvolvediftheyareunfa­miliar with it. The AHP and extended PIPRECIA methods are similar in requiring consistency checking. For this purpose, consistency checking in extended PIPRECIA is conducted by using Pearson’s or Spearman’scorrelationandbyapplyingthebidirectionalapproach;thatis,top-downandbottom-upeval­uationofcriteria.ThisbidirectionalapproachinconsistencytestingcouldbecomplicatedforDMsbecause they have to change their way of thinking while evaluating criteria from both sides. It requires an analyt­icapproachandmeasuringtheimportancethatoneparticularcriterionhasinrelationtothepreviousand next criterion (depending on the side the evaluation starts from). This manner of estimating criteria sig­nificance, however, contributes to the reliability of the results and the ranking order. Extended PIPRECIA was used to facilitate decision-making in several areas. Plain PIPRECIA, which is an integral part of extended PIPRECIA, is very convenient for criteria weight determination (e.g., Karabasevic etal.2019).ExtendedPIPRECIAwasproposedforevaluatingthequalityofwebsites(Stanujkic, KarabasevicandSava2018)andforassessingconsumersatisfactionwithrestaurantservice(Stanujkic et al. 2019). Stevic et al. (2018) also introduced a fuzzy extension of the PIPRECIA method that is also used in the decision process (Ðalic et al. 2020a; Ðalic et al. 2020b; Memis et al. 2020; Veskovic 2020). Extended PIPRECIA is applied for selecting an adequate mining method (Popovic, Ðordevic and Milanovic 2019). Intourism,extendedPIPRECIAisusedtoprioritizeprojectsfordevelopingaccommodationfacilities(Popovic andMihajlovic2018)andforrankingsustainableindicatorsforculturalheritagesites(Popovic et al.2019). This indicates that there is enough room to further examine and test the possibilities of extended PIPRECIA.Moreover,noexamplesofacombinationofSWOTanalysisandextendedPIPRECIAhavebeen found in tourism. 3 Methodology Developing the integrated model is performed in two phases. The first phase involves preliminary eval­uationoftheSWOTfactorsusingthePIPRECIAmethod,determiningthefivemostimportantonesfrom eachgroup,anddefiningtheappropriatestrategies.Themainreasonforselectingfiveistoavoidanexces­siveexamplethatwouldexacerbatetheunderstandingoftheproposedapproach.Thesecondphasedevelops and applies the extended model based on the SWOT technique and extended PIPRECIA. Figure 1 shows the guiding concept of building the integrated SWOT – extended PIPRECIA model. The crucial benefits and main shortcomings of both techniques are examined below. Figure 1: The proposed methodology. 3.1 SWOT analysis SWOT analysis gained popularity because it makes it possible to simultaneously scan internal strengths and weaknesses and external opportunities and threats for proper diagnosis of a current state to develop an appropriate strategy. Although SWOT analysis could be considered an inevitable technique for screening a business situ­ ation and determining convenient strategies, some consider it to have certain flaws (Kurttila et al. 2000; Yüksel and Dagdeviren 2007; Kajanus et al. 2012). In the present case, a SWOT analysis was used in the first phase to evaluate opportunities for tourism development in Serbia. The SWOT analysis is very extensive and contains many SWOT factors. To avoid complexity, the evaluation is divided into two phases. In the first phase, the five most influential factors from each group are determined based on the complete list of SWOT factors. A questionnaire was dis­tributedtosixprivatehotelmanagersandeighttouristboardmanagersforselectedmunicipalities.Complete dataforfurtherprocessingwereobtainedfromfiveDMs(threetouristboardmanagersandtwohotelman-agers), which showed how the model can be used in a group decision environment. The significance of allSWOTfactorswasdeterminedbyapplyingthePIPRECIAmethod.Inthisphase,DMsdefinedthestrate­gies that best meet the advantages and disadvantages of tourism development in Serbia. The five most influential factors from each group and proposed strategies were the entry data for phase two. G. Popovic, D. Stanujkic, P. Mimovic, G. Milovanovic, D. Karabaševic, P. Brzakovic, A. Brzakovic, An integrated SWOT… 3.2 Extended PIPRECIA ExtendedPIPRECIA(Stanujkic et al.2017a),whichincludesthePIPRECIAandinversePIPRECIAmeth­ods,wasusedinthesecondphaseofevaluatingopportunitiesfortourismdevelopmentinSerbia.Thefive DMs assessed the given factors and strategies individually by using extended PIPRECIA. The overall sig­nificance of the factors and strategies were then determined and, by multiplying the results obtained, the importanceofdegreesofstrategiesweredetermined.Thecomputationalprocedure,basedonStanujkicet al. (2017a), is presented below. Step 1. Select the criteria for evaluation. In this case, the criteria are SWOT factors and strategies. Step 2. Determine the relative significance sj starting from the second criterion in the following manner: where sj denotes the significance of criterion j, Cj denotes the importance of criterion j, and Cj-1 denotes the importance of the previous criterion. This means that sj has values greater than 1 when Cj dominates a previous criterion Cj-1; that is, when it is more important than the previous criterion, whereby a higher value of sj means a higher level of domi­nance and si = (1,1.8]. Similarly, sj has a value less than 1 when the criterion Cj is dominated by Cj-1 and then si = (1,0.2]. Finally, sj has a value of 1 when both criteria are of the same importance. where kj denotes the adjusted significance of criterion j. Step 4. Define the relative adjusted significance qj by using Eq. (3): where qj denotes the relative adjusted significance of criterion j. where wj denotes the relative weight of criterion j. Step 6. Compute the inverse relative significance s'j starting from the penultimate criterion as follows: Step 7. Define the inverse adjusted significance k'j in the following manner: Step 8. Determine the inverse relative adjusted significance q'j by using the following equation: Step 9. Detect the inverse relative weights of the evaluated criteria as follows: where w'j denotes the inverse weight of criterion j. Step 10. Confirm the reliability of the results obtained by using Spearman’s rank correlation coefficient: where denotes the correlation coefficient, dj denotes the distance between the ranks of wj and w'j, n is the number of criteria, and . . = (–1,1]. Step 11. The total weight of the criteria is computed by applying the following equation: where w'' denotes the complete weight of criterion j. j Step 12. When the decision process is performed in a group environment, then the final weights of the criteria are obtained in the following manner: wherewnr denotestheweightofcriterionjobtainedfromrespondentr,Risthenumberoftherespondents, j w*j is the group weight of criterion j before adjustment to fulfill the condition , and wj is the final group weight of criterion j. G. Popovic, D. Stanujkic, P. Mimovic, G. Milovanovic, D. Karabaševic, P. Brzakovic, A. Brzakovic, An integrated SWOT… 4 Results This section presents the results of the evaluation procedure. In using the proposed framework, the most influential SWOT factors are determined and strategies that will lead to a better position for Serbia on the global tourism market are emphasized. 4.1 Preliminary evaluation: phase one This preliminary evaluation is performed by using the plain PIPRECIA method, which is part of extend-edPIPRECIA.Thecomputationalprocedureisperformedbyusingequations(1)–(4)andequations(11)–(12). The results obtained, as well as the proposed strategies, are presented in Table 1. Table 1: SWOT matrix for developing tourism in Serbia (Tourism Development Strategy 2016). Internal factors Strengths (S) Weaknesses (W) S1 – Various resources and the tourist attraction structure in Serbia as the W1 – Disrespect for environmental protection measures in protected basis for developing a diversified tourist product portfolio. natural areas, neglecting structures and monuments under state S2 – A modern legal framework for planning tourism destinations. protection, numerous examples of squalor, environment pollution, S3 – A continuous trend of increasing overnight stays by foreign tourists in and space degradation, and insufficient coordination of tourism Serbia, primarily in Belgrade. development and environment protection. S4 – Internationally positioned and professionally organized events that W2 – A low budget for promoting tourism in Serbia. raise tourists’ awareness of Serbia as a tourism destination. W3 – Enterprises operating in tourism and hospitality are insufficiently S5 – Several airfields that could become usable for low-budget air informed about EU funds and do not make use of them. companies by making a small investment. W4 – The inadequate domestic internet platform and information and communications technology (ICT) applications for promoting tourist attractions, virtual guides, and presentations. W5 – Serbia’s competition further lagging behind and losing a potential market. External factors Opportunities (O) O1 – Serbia’s foreign policy: abolishing visas and visa facilitation for some countries; facilitating visa issuance at the border (for Turkey and China). O2 – Changing habits and tourist motivations on the global market and seeking new experiences, attractions, and products, and a preserved environment. O3 – Using resources for social programs for the staff surplus in public administration for work reintegration in tourism. O4 – Dynamic growth and development of air transport and reaching new destinations. O5 – Strengthening regional cooperation and creating regional tourism products for better positioning of tourism and attracting tourists from distant overseas markets. Threats (T) T1 – Political tensions in the Balkans. T2 – Losing the opportunity to use government reforms and abandoning the longstanding policy of exclusively supporting public institutions. T3 – Abandoning the sale or licensing of every unprofitable property whose owner is Serbia or public enterprises in tourism, which could be used for supporting current or new small and medium-sized enterprises. T4 – Lack of management and coordination reforms in developing tourism in Serbia. T5 – Disconnected and uncoordinated activity in implementing the Strategy and Action Plan for the Implementation of the Tourism Development Strategy of the Republic of Serbia 2016–2025. Strategies SO strategy ST strategy SO1 – Improving tourist and traffic infrastructure in Serbia. ST1 – Improving the organization, management, and enhancement of SO2 – Improving tourist products and services in Serbia. tourism development. WO strategy WT strategy WO1 – Improving human resources and the labor market. WT1 – Networking with other sectors. WT2 – Improving the national tourism marketing system. After defining the most influential factors and forming strategies, the final evaluation procedure with extended PIPRECIA is performed in phase two. 4.2 Final evaluation: phase two Table 2 shows the priorities for each SWOT group computed by applying Eqs. (1)–(12). The reliability of theresponsesischeckedwithSpearman’scoefficientand,basedontheresults,theDMs’responsesarefully justified and consistent in all iterations. Table 2: Importance degrees of SWOT groups. w''1 j w''2 j w''3 j w''4 j w''5 j wj S 0.2173 0.2437 0.2689 0.2035 0.3106 0.2459 W 0.3545 0.2437 0.2689 0.1912 0.2535 0.2572 O 0.2508 0.2563 0.2195 0.2937 0.2070 0.2436 T 0.1775 0.2563 0.2427 0.3116 0.2289 0.2394 . 1.00 1.00 1.00 0.80 1.00 The overall results obtained by using equations (11)–(12), however, show that the Weaknesses Group is assigned the highest priority. TheimportancedegreesforthefactorsfromtheStrengthsGrouparedeterminedbyusingEqs.(1)–(12), and the results are presented in Table 3. The equations are used to determine the further results. The importance degrees show that the most significant factor from this group is S5– Several airfields that could become usable for low-budget air companies by making a small investment (Table 3). Table 3: Importance degrees of the Strengths Group. w''1 j w''2 j w''3 j w''4 j w''5 j wj S1 S2 S3 S4 S5 . 0.1193 0.2268 0.1847 0.1351 0.3341 0.80 0.2241 0.1793 0.1793 0.1982 0.2191 1.00 0.2253 0.1840 0.2034 0.2034 0.1840 0.90 0.2881 0.1659 0.1659 0.2191 0.1610 1.00 0.1455 0.1455 0.1981 0.2426 0.2683 1.00 0.1907 0.1784 0.1858 0.1960 0.2254 TheresultsobtainedfortheWeaknessesGrouparepresentedinTable4.Thehighestpriorityinthisgroup is assigned to factor W1, which is connected to disrespect for environmental protection measures in pro­tected nature areas and neglecting state-protected structures and monuments. Table 4: Importance degrees of the Weaknesses Group. w''1 j w''2 j w''3 j w''4 j w''5 j wj W1 W2 W3 W4 W5 . 0.1811 0.1543 0.2053 0.2597 0.1995 0.70 0.2699 0.2116 0.2019 0.1774 0.1392 0.95 0.2122 0.1919 0.1919 0.1919 0.2122 0.90 0.2818 0.1571 0.1813 0.2129 0.1669 1.00 0.2570 0.2098 0.1898 0.1717 0.1717 1.00 0.2372 0.1832 0.1939 0.2004 0.1760 G. Popovic, D. Stanujkic, P. Mimovic, G. Milovanovic, D. Karabaševic, P. Brzakovic, A. Brzakovic, An integrated SWOT… Table 5 shows the results of evaluating factors from the Opportunities Group. In this case, the most influ­ential factor is O4– Dynamic growth and development of air transport and reaching new destinations. Table 5: Importance degrees of the Opportunities Group. w''1 j w''2 j w''3 j w''4 j w''5 j wj O1 O2 O3 O4 O5 . 0.1559 0.1337 0.2013 0.2970 0.2122 0.70 0.2554 0.2004 0.1813 0.1906 0.1724 1.00 0.2164 0.2164 0.1767 0.1953 0.1953 1.00 0.1874 0.2294 0.1621 0.2211 0.2000 0.80 0.1759 0.1945 0.1759 0.2155 0.2382 0.94 0.1953 0.1916 0.1790 0.2209 0.2025 Table 6 shows the local importance degrees for the Threats Group. It shows that the factor with the high­est weight is T4– Lack of management and coordination reforms in developing tourism in Serbia. Table 6: Importance degrees of the Threats Group. w''1 j w''2 j w''3 j w''4 j w''5 j wj T1 T2 T3 T4 T5 . 0.2155 0.1518 0.1994 0.2538 0.1795 0.70 0.2588 0.1898 0.1898 0.1898 0.1717 1.00 0.1659 0.2032 0.2032 0.2032 0.2246 1.00 0.1778 0.2349 0.1918 0.2215 0.1739 0.90 0.2035 0.2249 0.2035 0.1841 0.1841 0.94 0.2018 0.1986 0.1975 0.2090 0.1858 The factor priority within the groups and the overall factor priorities are presented in Table 7. Table 7: Overall priority scores of SWOT factors. SWOT group Group priority SWOT factors Factor priority within group Overall factor priority S 0.2459 S1 0.1907 0.0469 S2 0.1784 0.0439 S3 0.1858 0.0457 S4 0.1960 0.0482 S5 0.2254 0.0554 W 0.2572 W1 0.2372 0.0610 W2 0.1832 0.0471 W3 0.1939 0.0499 W4 0.2004 0.0515 W5 0.1760 0.0453 O 0.2436 O1 0.1953 0.0476 O2 0.1916 0.0467 O3 0.1790 0.0436 O4 0.2209 0.0538 O5 0.2025 0.0493 T 0.2394 T1 0.2018 0.0483 T2 0.1986 0.0476 T3 0.1975 0.0473 T4 0.2090 0.0501 T5 0.1858 0.0445 EachofthesixstrategiesconsideredareevaluatedrelativetoeachSWOTfactorestimatedasthemostimpor­tant in phase one. By multiplying these results by the overall factor priority, the importance degrees of the strategies are defined (Tables 8a and 8b). Table 8a: Importance degrees of strategies according to SWOT factors. SSSSSWWWWW 12345 12345 SO1 0.1880 0.1499 0.1491 0.1421 0.1895 0.1187 0.1437 0.1259 0.1470 0.1632 SO2 0.1874 0.1537 0.1620 0.1599 0.1638 0.1312 0.1600 0.1401 0.1490 0.1739 WO1 0.1427 0.1590 0.1528 0.1522 0.1509 0.1403 0.1598 0.1489 0.1586 0.1601 WT1 0.1373 0.1626 0.1635 0.1507 0.1562 0.1598 0.1645 0.1517 0.1620 0.1446 WT2 0.1630 0.1705 0.1754 0.1956 0.1615 0.1920 0.1805 0.1791 0.1936 0.1743 ST1 0.1816 0.2042 0.1971 0.1995 0.1782 0.2580 0.1915 0.2544 0.1898 0.1839 Table 8b: Priority scores of strategies according to SWOT factors. O1 O2 O3 O4 O5 T1 T2 T3 T4 T5 SO1 SO2 WO1 WT1 WT2 ST1 0.1820 0.1907 0.1725 0.1517 0.1500 0.1531 0.1744 0.1435 0.1434 0.1728 0.1876 0.1782 0.1332 0.1679 0.1945 0.1712 0.1524 0.1809 0.2083 0.1830 0.1469 0.1370 0.1553 0.1695 0.1462 0.1517 0.1516 0.1616 0.1747 0.2141 0.1690 0.1635 0.1689 0.1516 0.1748 0.1722 0.1551 0.1713 0.1738 0.1634 0.1673 0.1691 0.1528 0.1397 0.1636 0.1548 0.1771 0.2120 0.1646 0.1519 0.1672 0.1583 0.1702 0.1877 0.1890 0.1585 0.1584 0.1673 0.1611 0.1657 Table9showstheoverallpriorityofthestrategiesconsidered.Figure2showsthefinalrankingorderofthe strategies evaluated. Table 9: Overall priority of the strategies. Strategy Overall priority Rank SO1 Improving tourist and traffic infrastructure in Serbia 0.1553 4 SO2 Improving tourist products and services in Serbia 0.1556 3 WO1 Improvement human resources and the labor market 0.1537 5 WT1 Networking with other sectors 0.1528 6 WT2 Improving the national tourism marketing system 0.1685 2 ST1 Improving the organization, management, and enhancement of tourism development 0.1879 1 Figure 2 shows that the highest overall priority is assigned to strategy ST1– Improving the organization, management, and enhancement of tourism development. This result is fully justified, especially when tak­ingintoaccountthemostinfluentialfactorfromtheThreatsGroup,T4–Lackofmanagementandcoordination reforms in developing tourism in Serbia. There is a need to seriously improve tourism management, mod­ernize tourism organizations, and renovate tourism infrastructure. Based on the results, the strategy that should be implemented last is WT1– Networking with other sectors. This does not mean that this strategy is the least important, but that the appropriate conditions must be created that will allow the coordinated action of all sectors. G. Popovic, D. Stanujkic, P. Mimovic, G. Milovanovic, D. Karabaševic, P. Brzakovic, A. Brzakovic, An integrated SWOT… 02 . 01. 8 0.16 0.14 0.12 01 . 00. 8 00. 6 004 . 002 . 0 SOSOWOWTWTST 4th 3rd 5th 6th 2nd 1st 12 1121 Figure 2: Final ranking order of strategies. 5 Discussion The reason for proposing a model based on the SWOT and PIPRECIA methods is that, although SWOT analysis is a proven strategic tool, it has certain flaws. SWOT analysis has a qualitative nature and cannot reveal the importance of factors or their impact on the final decision (Yüksel and Dagdeviren 2007; Kajanus et al. 2012; Vlados 2019). This is resolved by combining the SWOT technique with extended PIPRECIA.ThisnewintegratedmodelclearlyshowsthesignificanceoftheSWOTfactorsaswellaswhich of them is the most influential. Compared to the A’WOT model, which is often used for prioritizing strategies (Kajanus, Kangas and Kurttila 2004; Akbulak and Cengiz 2014; Kisi 2019; Bottero, D’Alpaos and Marello 2020), the proposed integratedmodelhascertainadvantages.Theproposedapproachusesadecision-makingprocedureadjust-ed for a group decision environment and, although extended PIPRECIA is somewhat complicated, it is easy for respondents to understand. The proposed model has certain benefits relative to the SWARA method, which is also used in com-binationwithSWOTanalysis(Popovic,MilovanovicandStanujkic2018).AlthoughtheSWARAmethod, which represents the core of extended PIPRECIA, has a computational procedure that is much easier, it isnotsuitableforagroupdecisionenvironment.ThisismainlybecausetheSWARAmethodrequirespre­sortingofthecriteriaconsidered,andsoallDMscangivetheirrankingorders,whichcomplicatesobtaining theresults.ExtendedPIPRECIAdoesnotinvolvepre-sortingthecriteriaintheevaluationprocedure,which facilitates gathering and calculating the results from a greater number of DMs. Furthermore, extended PIPRECIA predicts verifying the reliability of the results, which is not the case with the SWARA method. Theproposedmodelwasappliedtoacasestudyexaminingtheadvantagesanddisadvantagesoftourism in Serbia. The SWOT analysis used in this work is taken from the Tourism Development Strategy of the RepublicofSerbia2016–2025(2016).Becausethisanalysiscontainsmanyfactors,theevaluationwascon­ductedintwophases.Inphaseone,thefivemostimportantfactorsfromeachSWOTgroupweredetermined by using the PIPRECIA method and group decision-making. In phase two, the final priorityscores of the factors and the final ranking of the strategies relative to the given factors were calculated. The evaluation process in both phases was entrusted to tourism experts, who are familiar with the tourism situation in Serbia. The strategy assigned priority under current conditions is strategy ST1–Improving the organiza-tion,management,andenhancementoftourismdevelopment.Thisisjustifiedbecause,althoughSerbiahas greattourismpotential,itshouldimproveorganizationandmanagementintourismandimproveitsposi­tion on the world tourism market. Comparingtheresultswiththoseobtainedbyotherresearchersshowsacertaindisparityamongcoun­tries regarding the priority of strategies for tourism development. For example, Ajmera (2017) inferred that the SOstrategy is the best choice formedical tourism development in India. Büyüközkan, Mukul and Kongar(2020)alsoemphasizetheSOstrategyforhealthtourismdevelopmentinIstanbul,Turkey.Abadietal. (2018)definedtheWOstrategyasthebestformedicaltourisminIran.ForecotourisminDjerdapNational Park in Serbia, the most important strategy is ST, as in our case (Arsic, Nikolic and Živkovic 2017). The factthatthesestudiesfocusondifferenttypesoftourismdoesnotinfluencetheconclusionthatthemethod­ology used does not affect the result but depends on the tourism situation in a given country. As stated, there are many issues to resolve in Serbian tourism, which leads to the result presented here. In this particular case, decision-making is performed by five DMs. By involving a greater number of DMsfromdifferenttourismstructures,theresultsaremorereliable.Itwouldbedesirabletoperformanew SWOTanalysistakingintoaccountthecurrentsituationcausedbytheCOVID-19pandemic.Adisadvantage oftheproposedmodelistheuseofprecisenumbers.Decision-makingisconductedinanenvironmentchar­acterized by uncertainty and vagueness, and so it is important to include this incertitude in the decision process.Byintroducingfuzzysets(Atanassov1986),graysystems(Deng1982),orneutrosophicnumbers (Smarandache 2005), the reliability of the analysis and the decisions will increase because the vagueness and uncertainty of the environment will be better included. 6 Conclusion Decision-making in tourism and other research areas requires a methodical approach to achieve appro­priatedecisions.MathematicaltoolssuchasMCDMmethodsareoftenusedtoincreasethelevelofcertainty ofthe decisions. As stated previously, this article proposes applying an integrated model based on SWOT analysis and extended PIPRECIA as a decision-making aid for strategic planning in tourism. The possi­bilities of the integrated model are tested using a case study to identify the key determinants for tourism developmentinSerbia.TheresultsareappropriateandinlinewithcurrentpositionsontourisminSerbia. By introducing the new integrated SWOT – extended PIPRECIA model, the theoretical and practi­cal dimensions of MCDM are enhanced and the possibilities of its application are clearly outlined. The crucial advantages of the model lie in its suitability for application in a group-decision environment, its relatively simple and understandable procedure, and the systematic approach for DMs in identifying and implementingstrategiesfortourismdevelopment.ApplyingtheintegratedmodeltotourisminSerbiaoffers a completely different perspective from one based only on SWOT analysis. 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DOI: https://doi.org/10.1016/j.tourman.2010.02.007 Zoraghi, N., Amiri,M., Talebi, G., Zowghi, M. 2013: Afuzzy MCDM model with objectiveand subjective weightsforevaluatingservicequalityinhotelindustries.JournalofIndustrialEngineeringInternational 9. DOI: https://doi.org/10.1186/2251-712X-9-38 PRECIPITATION VARIABILITY,TRENDS AND REGIONS IN POLAND: TEMPORAL AND SPATIAL DISTRIBUTION IN THE YEARS 1951–2018 Robert Kalbarczyk, Eliza Kalbarczyk Crowns of Scots pine trees in the clouds. DOI: https://doi.org/10.3986/AGS.8846 UDC: 913:551.435.11:502.13(497.11) COBISS: 1.01 Robert Kalbarczyk1, Eliza Kalbarczyk2 Precipitation variability, trends and regions in Poland: Temporal and spatial distribution in the years 1951–2018 ABSTRACT:Thegoalsofthisworkweretoassessdifferencesinprecipitationtotals(Pr)inPolandinboth time and space and to distinguish regions based on precipitation variability in the years 1951–2018. To assessprecipitationconditions,thestudyusedstatisticalandspatialanalysesimplementedinArcGISDesktop and STATISTICA software. The largest number of significant, positive correlations describing the linear Pr trend were found for March. The lowest monthly Pr, which represents only approximately 6% of the multi-year precipitation totals, was recorded in October 1951; the highest monthly Pr, which represents as much as approximately 355% of the multi-year precipitation totals, was recorded in October 1974. The study distinguished three precipitation regions of Poland. KEY WORDS: climate change, precipitation conditions, number of days with precipitation, precipitation regions, Poland. Spremenljivost, trendi in obmocja padavin na Poljskem: casovna in prostorska porazdelitev med letoma 1951 in 2018 POVZETEK: V clanku so proucene razlike v skupni kolicini padavin na Poljskem v casu in prostoru, na podlagi cesar so dolocena glavna padavinska obmocja med letoma 1951 in 2018. Padavinske razmere so ocenjene na podlagi statisticne in prostorske analize, opravljene v programskih orodjih ArcGIS Desktop inSTATISTICA.Najvecstatisticnoznacilnihkorelacij,kinakazujejolinearnitrendvskupnikolicinipadavin, jebiloodkritihzamesecmarec.Najmanjšamesecnaskupnakolicinapadavin(samopribližno6%vecletnega mesecnega povprecja) je bila zabeležena oktobra 1951, najvišja (približno 355% vecletnega mesecnega povprecja) pa oktobra 1974. Dolocena so tri padavinska obmocja na Poljskem. KLJUCNE BESEDE: podnebne spremembe, padavinske razmere, število dni s padavinami, padavinska obmocja, Poljska The paper was submitted for publication on August 3rd, 2020. Uredništvo je prejelo prispevek 3. avgusta 2020. 1 Wroclaw University of Environmental and Life Sciences, Institute of Landscape Architecture, Wroclaw, Poland robert.kalbarczyk@upwr.edu.pl (https://orcid.org/0000-0002-0564-8653) 2 Adam Mickiewicz University in Poznan, Faculty of Human Geography and Planning, Poznan, Poland ekalb@amu.edu.pl (https://orcid.org/0000-0002-4871-2483) 1 Introduction Despite many years of research on climate change, there are no clear indications as to the direction and intensificationofprecipitationvariability.Thescenarios andmodels presentedintheliteratureall assume a global, albeit varied, increase in air temperature. On the other hand, research results on the direction andrangeofprecipitation(Pr)variabilityinthefuture(including inPoland)remainburdenedwithmuch higher uncertainty (Kundzewicz and Kozyra 2011; IPCC 2014; Kalbarczyk et al. 2018). Analyses of historical data that contains precipitation totals and the number of days with precipita­tion or extreme precipitation values indicate that in the 20th century and at the turn of the 21st century there were no clear regularities in their patterns (Halimatou, Kalifa and Kyei-Baffour 2017; Pathak et al. 2018;Caloiero,CaloieroandFrustaci2018).Manyreportsfrequentlypointtothelackofasignificanttrend of precipitation totals in Europe; however, regional occurrences of both positive and negative Pr trends havebeenreported(Kundzewicz,RadziejewskiandPinskwar2006;Labudová,FaškoandIvanáková2015; Lupikasza 2017). Also, previous research on the multi-year variability of Pr conducted for various regions of Poland did not produce any unambiguous results so it is not certain how it will develop in the future (Majewski,PrzewozniczukandKleniewska2010;Zarski et al.2014;Ilnicki et al.2015;Ziernicka-Wojtaszek andKopcinska2020).PrecipitationvariabilityoccurringinCentralEuropeismostlyexplainedbyitsdepen­denceonatmosphericcirculation,whichdeterminestheprevalenceofcontinentaloroceanicweathertrends andshapes the global and regional climates (Degirmendžic, Kozuchowski and Zmudzka 2004; Twardosz, NiedzwiedzandLupikasza2011;Mlynski,CebulskaandWalega2018).Outoftheremainingfactorsshap­ing precipitation variability in Poland research studies included e.g. the importance of cloud cover and terrain(BokwaandSkowera2008;Zmudzka2009).Knowledgeofprecipitationvariabilityisvitalformany sectors of the economy. The sum of precipitation and its temporal distribution affect the functioning and development of, for example, agriculture, fisheries, forestry, water transport, hydropower generation and tourism,therebyinfluencingthequalityoflifeinagivencountry(Kalbarczyk,KalbarczykandRaszka2011; Marcinkowski and Piniewski 2018; Radzka, Jankowski and Jankowska 2019). Recognizing the degree of Prvariabilityisessentialforclimateriskmanagement(Markovic et al.2014;Šebenik,BrillyandŠraj2017; Mlynski,CebulskaandWalega2018;Stefanovaetal.2019;Ziernicka-WojtaszekandKopcinska2020).Floods resulting from sudden atmospheric precipitation are one of the biggest climatic threats to cities (Pedrozo-Acuña etal.2017;Szewranski etal.2018;Olsson etal.2019),thereforedeterminationofprecipitationtrends canbeusefulwhenplanningadaptationmeasurestoclimatechangeforurbanandruralareas(Hardoy et al. 2014; Reckien et al. 2015; Chu, Anguelovski and Roberts 2017). Knowledge of precipitation variability in amulti-yearandspatialperspectiverequirescontinuousupdating,soresearchstudiesareconductedanew for the changing climatic conditions in various regions of the world. The aims of this paper were to determine the temporal and spatial variability of precipitation and to distinguish regions of Poland based on specific variability of precipitation totals. 2 Materials and methods The paper used daily precipitation totals which were collected at 74 meteorological stations located across Poland(Figure1).Precipitationtotals(Pr,mm)werecalculatedforeachyearintheanalyzedperiodbetween 1951and2018foreachindividualmonthineachoftheseyears.Theinitialdataweremadeaccessiblebythe Polish Institute of Meteorology and Water Management which is responsible for systematic measurements andobservationswiththeuseoftheirbasicnetworkofstationsandspecial-purposemeasurementnetworks. Singlemissingdailyprecipitationtotalswereaddedonthebasisofcompletemeasurementseriesfrom theneareststations.Longerseriesofmissingdailytotals(atleast10dayslong)weredeterminedbymeans oflinearornon-linearregressionequationswhosecalculateddeterminationcoefficientsdescribedatleast a 64% fit of the empirical data to the regression function. Precipitationpatternsweredescribedwiththefollowingindices:themean(x¯ ),standarddeviation(SD), variation coefficient (V), and extreme values, i.e. the minimum (MIN) and the maximum (MAX) calcu­lated on the basis of all the analyzed annual periods and months during the entire analyzed 1951–2018 period (further accepted also as the norm). Spearman’s coefficient (r) was used to describe thelinear pre­cipitationtrend.Precipitationconditionsforchosen2yearsandthe24monthswiththelowestandhighest precipitation totals were characterized by an index that expressed extreme values as a percentage of the sum of multi-year precipitation and the average number of days without precipitation (0.0) and with pre­cipitationinthefollowingranges:0.1–1,>1,>2,>5,>10,>20and>50mm(Olechnowicz-Bobrowska1970; Bochenek 2020). Maps presenting statistical characteristics of precipitation conditions in Poland in various time func­tions with a borders of the 16 administrative provinces were prepared using inverse distance weighting in ArcGIS Desktop 10.6.1 software. Due to the fact that very high precipitation variability occurs in only one region of Poland, some maps were supplemented witha legend which does not use the same range of val­ues in all intervals. Therefore, on the color scale the last two ranges of values were marked with grey and black. The legend showing the linear trend of precipitation totals gives critical values of Spearman’s coef­ficient for a=0.1 and a=0.01, which amount to 0.201 and 0.311, respectively. The regions in Poland with a similar variability of precipitation were determined on the basis of hier­archicalclusteringin3multi-yearperiods:1951–1984(thefirsthalfoftheentireexaminedmulti-yearperiod), 1985–2018 (the second half of the entire examined multi-year period), and 1951–2018 (the whole exam-inedmulti-yearperiod).Theanalysistookintoconsideration24variables:averagemulti-yearprecipitation totalsandtheiraveragemulti-yearstandarddeviationvalues,bothofwhichwerecalculatedseparatelyfor each month for each meteorological station and each analyzed multi-year period. Before the analysis, the values of all variables (Z) were standardized according to the equation: (xi–x¯ ) Z= SD where xi is the observed value of a variable from a given station in a given month and multi-year period, x¯ is the arithmetic mean for all stations in a given month and multi-year period, and SD is the standard deviation from all stations in a given month and multi-year period. The study used an agglomerative method of clustering to classify meteorological stations into groups so that the degree of correlation of a given station with stations from the same group would be possibly the strongest, and with stations from the remaining groups possibly the weakest. Distances between sta­tionsinmultidimensionalspacewerecalculatedbymeansofthecityblockdistance(Manhattandistance), thankstowhichtheeffectofoutliersisreduced.DistancesbetweennewclustersweredeterminedbyWard’s method. The accepted measure of the linkage amounted to 110. The method aims to minimize the sum of the squared deviations of any two clusters which may be formed at any stage. Regression and cluster analysis were carried out in STATISTICA 13.3 software. 3 Results 3.1 Precipitation distribution In 1951–2018, the average precipitation total (Pr) for the whole of Poland was approximately 634mm (Table1).Insomemonths,Prfluctuatedfromapproximately31mminFebruarytoapproximately90mm in July. Pr of up to 40mm was also recorded in January and March, and Pr of over 70mm was recorded inJuneandAugust.Theannualstandarddeviationformulti-yearprecipitationtotalsamountedto~82mm, but in February it was only ~13mm, and in July as much as 34mm. A high standard deviation of Pr, i.e. >25mm,wascalculatedforAugustandOctober.Thehighestvariabilityofprecipitation,expressedbyvari­ation coefficient V, was characteristic of precipitation in October (60.5%), and the lowest – precipitation in June (27.3%), with the variability of annual precipitation sums at a level of 13%. A significant positive increase in Pr for the whole country was found only for March (r=0.25, a=0.05). InPoland,thespatialdistributionofaveragemulti-yearprecipitationtotalswasveryvaried(Figure2). The lowest Pr was observed in the central strip of Poland and amounted to <550mm. Precipitation increased latitudinally northwards and southwards, where the observed totals were the highest, namely >1300mm. In some months, the spatial structure of Pr was slightly different than for the entire year (Figure 3). Table 1: Characteristics of precipitation totals variability in Poland, 1951–2018. Characteristics Period / month x¯±SD r V January–December 634.1±82.3 0.17ns 13.0 January 36.3±15.0 0.15ns 41.3 February March 31.3±13.1 35.4±13.5 0.04ns 0.251 41.9 38.1 April 41.0±14.4 –0.11ns 35.1 May 62.5±20.3 0.03ns 32.5 June 75.8±20.7 –0.07ns 27.3 July 89.6±34.0 0.05ns 37.9 August 72.0±25.1 –0.09ns 34.8 September 56.3±23.7 0.11ns 42.1 October 46.1±27.9 0.13ns 60.5 November 44.9±16.4 0.01ns 36.5 December 42.7±16.3 0.04ns 38.2 Notes: x¯ – arithmetic mean (mm), SD – standard deviation (mm), r – Spearman’s correlation coefficient for a linear trend, V – coefficient of variation (%), 1 – significant at a=0.05, ns– non-significant at a=0.1 Figure 3: Spatial distribution of average multi-year precipitation [mm] totals by months in Poland, 1951–2018. p p. 48–49 FromJanuarytoMarch,thelowestvalueofprecipitation(<30mm)occurredmainlyincentral-eastPoland; thehighest,i.e.>80–90mm,occurredinthesouthernpartofthecountry.FromApriltoJune,thelowestPr wasobservedinthePolishPlains(from<40mminAprilto<60mminMay),andthehighestwasinthesouth (from >105mm in April to >170mm in June). In July, Pr oscillated from <80mm to >180mm, with the lowestvaluesinthecentral-westandcentral-eastparts;inAugustProscillatedfrom<60to>150mm,with the lowest values in central-west Poland; in September Pr oscillated from <50 to >110mm, with the low­est values in the central-west part. In October in the central strip of Poland, which stretches horizontally, precipitation amounted to <40mm; in the north and south it amounted to >85mm. Finally, in November andDecember,aProf<40mmoccurredincentral-eastPoland,andaProf>90–95mmoccurredinthesouth. 3.2 Variability and precipitation trend In 1951–2018, theannual standard deviation of Pr for whole of Poland fluctuated from <100 to >210mm (Figure 4). In the areas with the highest annual precipitation totals, the calculated standard deviation values (SD) werealsothehighest.Inparticularmonths,thestandarddeviationofProscillatedfrom<15mminJanuary to >90mm in July (Figure 5). Figure 5: Spatial distribution of the standard deviation for monthly precipitation [mm] totals in Poland, 1951–2018. p p. 50–51 The lowest SD was calculated for precipitation in 3 months: January, in some stations located in cen­tral Poland; February, in north-east and central Poland; March, in central Poland. The highest SD in all months was calculated for precipitation in the southern part of the country, i.e. in high-mountain areas, and also in October in the northern part of Poland. In the analyzed multi-year period, annual precipita­tion totals clearly decreased or increased only in some parts of Poland (Figure 6). Figure 4: Spatial distribution of the standard deviation for annual precipitation totals in Poland, 1951–2018. < 30 30–40 < 30 40–50 30–40 50–60 40–50 60–90 50–80 > 90 January > 80 February < 30 < 40 30–40 40–50 40–50 50–60 50–60 60–70 60–90 > 90 FebruaryMarch 70–105 > 105 April < 50 50–60 < 60 60–70 60–80 70–80 80–100 80–90 100–120 90–135 120–170 > 135 May > 120 June < 80 < 60 80–100 60–80 100–120 80–100 120–140 100–120 140–180 120–150 > 180 July > 150 August < 50 50–60 < 40 60–70 40–50 70–80 50–60 80–110 60–85 > 110 September > 85 October < 40 < 40 40–50 40–50 50–60 50–60 60–90 60–95 > 90 November > 95 December < 15 < 15 15–20 15–20 20–25 20–25 25–30 25–30 30–45 30–45 > 45 January > 45 February < 15 15–20 20–25 25–30 30–40 > 40 < 25 25–30 30–35 35–40 40–55 > 55 March May < 20 20–25 25–30 30–45 > 45 < 30 30–35 35–40 40–45 45–65 > 65 April June <40 40–45 45–50 50–55 55–60 < 35 35–40 40–45 45–50 60–90 50–70 >90 mm July > 70 August < 30 30–35 < 30 35–40 30–35 40–45 35–40 45–60 40–50 > 60 September > 50 October < 20 20–25 < 20 25–30 20–25 30–35 25–30 35–45 30–45 > 45 November > 45 December –0.201–0.0 –0.311– –0.201 0.0–0.201 –0.201–0.0 0.201–0.311 0.0–0.201 > 0.311 January 0.201–0.311 Februar –0.201–0.0 < –0.311 0.0–0.201 –0.311– –0.201 0.201–0.311 –0.201–0.0 > 0.311 March 0.0–0.201 April < –0.311 –0.311– –0.201 < –0.311 –0.201–0 –0.311– –0.201 0–0.201 –0.201–0.0 0.201–0.311 May 0.0–0.201 June –0.201–0.0 0.0–0.201 0.201–0.311 –0.311– –0.201 –0.201–0.0 0.0–0.201 0.201–0.311 July September –0.311– –0.201 –0.201–0.0 0.0–0.201 0.201–0.311 August –0.201–0.0 0.0–0.201 0.201–0.311 > 0.311 October –0.311– –0.201 –0.201–0.0 –0.311– –0.201 0.0–0.201 –0.201–0.0 0.0–0.201 0.201–0.311 November December A significant (at least at a level of a=0.1) positive Spearman’s coefficient of =0.201 that was calculat­ed for Pr was found, for example, in Masovia region (central-east), Roztocze region (south-east) and the central part of the Slovincian Coast (north-east). A significant negative Spearman’s coefficient was found in small areas of south-west Poland. In March, a significant positive increase in Pr was found in northern and central Poland (Figure 7). AnincreaseinPrwasfoundfor8months,mainlyinnorthernandeasternPoland:January,February,May, July, August, September, October and December. A significant decrease in Pr in 1951–2018 was proved in a small area of the country, mainly in western and southern Poland, also in 8 months: February, April, May, June, August, September, November and December. 3.3 The lowest and highest precipitation The lowest and highest annual precipitation totals in the entire analyzed multi-year period were respec­tively recorded in 1982 and 2010, amounting to approximately 454 and 852mm (Figure 8). In subsequent months of the year (Figure 9), the highest Pr values in some months occurred in dif­ferent years than the lowest totals. The lowest annual precipitation total in Poland, which was recorded in 1982, constituted ~72% of the multi-year precipitation average (Table 2). Inthatdryyear,precipitationwasnotrecordedon~233days.For~53days,Prvalueswerewithinarange of 0.1–1mm, and for ~79 days they were >1mm. In 1982, the average number of days with precipitation of >5, >10, >20 and >50mm amounted to 27.9, 10.0, 2.4 and 0.1 days, respectively. In some months, Figure 8: Temporal distribution of annual (January–December) precipitation totals in Poland, 1951–2018. Figure 9: Temporal distribution of monthly precipitation totals in Poland, 1951–2018. p p. 55–57 Pr (mm) Pr (mm) 40 60 40 60 20 20 0 0 Year Year mean the lowest the lowest the highestmean the highest MarchApril 100 100 80 80 20 20 0 0 1951 1954 1957 1960 1963 1966 1969 1951 1954 1957 1960 1963 1966 1969 1972 1972 1975 1975 1978 1978 1981 1981 1984 1984 1987 1987 1990 1990 1993 1993 1996 1996 1999 1999 2002 2002 2005 2005 2008 2008 2011 2011 2014 2014 2017 2017 Pr (mm) Pr (mm) 40 January February 100 100 80 80 Year Year mean the lowest the highest mean the lowest the highest 60 40 60 1951 1954 1957 1960 1963 1966 1969 1951 1954 1957 1960 1963 1966 1969 1972 1972 1975 1975 1978 1978 1981 1981 1984 1984 1987 1987 1990 1990 1993 1993 1996 1996 1999 1999 2002 2002 2005 2005 2008 2008 2011 2011 2014 2014 2017 2017 Pr (mm) Pr (mm) 40 60 40 60 20 20 0 0 Year Year mean the lowest the lowest the highestmean the highest JulyAugust 100 100 80 80 20 20 0 0 1951 1954 1957 1960 1963 1966 1969 1951 1954 1957 1960 1963 1966 1969 1972 1972 1975 1975 1978 1978 1981 1981 1984 1984 1987 1987 1990 1990 1993 1993 1996 1996 1999 1999 2002 2002 2005 2005 2008 2008 2011 2011 2014 2014 2017 2017 Pr (mm) Pr (mm) 40 May June 100 100 80 80 Year Year mean the lowest the highest mean the lowest the highest 60 40 60 1951 1954 1957 1960 1963 1966 1969 1951 1954 1957 1960 1963 1966 1969 1972 1972 1975 1975 1978 1978 1981 1981 1984 1984 1987 1987 1990 1990 1993 1993 1996 1996 1999 1999 2002 2002 2005 2005 2008 2008 2011 2011 2014 2014 2017 2017 57 Pr constituted only about 6% of the norm in October (in 1951) to about 51% of the norm in June (1976). In the months of the lowest Pr, the average number of days without precipitation fluctuated from 22 days inJune(1976)to29daysinOctober(1951). Theaveragenumberofdayswithprecipitationwithinarange of 0.1–1mm oscillated from 1.2 days in October (1951) to 6.6 days in January (1997). On the other hand, theaverage numberofdays withprecipitationof >1mm fluctuated from 0.8 daysin October (1951)to 5.6 daysinJune(1976);theaveragenumberofdayswithprecipitationof>2mmvariedfrom0.3to4.7daysin October (1951) and June (1976), respectively. Higher Pr values, i.e. >5mm, in dry months were observed muchmorerarelyastheaveragenumberofdayswithsuchprecipitationoscillatedbetween0.1and2.8days. The spatial distribution of the lowest annual and monthly precipitation totals in Poland is presented in Figures 10 and 11. In 1982, the totals fluctuated from <400mm in central-west and central-east Poland to >1200mm in the south (Figure 10). The lowest Pr values, which were recorded in 1982, were on aver­age 150mm lower than in the multi-year period of 1951–2018 (Figure 2). In particular dry months, Pr values oscillated from <5mm to >105mm (Figure 11). Depending on the month, precipitation of <5mm was recorded mainly in the cold half of the year in various parts of Poland, namely in the strip stretching from the north-west to the central-east (January 1997), in the east (February 1976), in the south-east (March 1974), in the central strip stretching from the north to the south (April 2009), in most of the country (October 1951), in the south and the central strip situated along the west-east axis (November (2011) and mainly in central-east Poland (December 1972). On the other hand, Pr of>105mm occurred in May(1956) and June (1976) in the southof Poland. In otherdrymonths,thehighestPrwasrecordedindifferentpartsofPoland,e.g.>15mminFebruary(1976) incentral-westPoland,>25mminApril(2009)inthesouth-east,>60mminSeptember(1959)inthenorth, and >70mm in November (2011) in the north-west. The highest annual Pr in Poland was registered in 2010 and constituted ~135% of the norm (Table 3). Figure 10: Spatial distribution of the lowest annual precipitation totals in Poland in all the analyzed years, 1951–2018. Figure 11: Spatial distribution of the lowest monthly precipitation [mm] totals in Poland in all the analyzed months, 1951–2018. p p. 60–61 Table 2: Characteristics of the structure of the lowest precipitation totals in Poland, 1951–2018. Period / month Year with the lowest % of multi-year Average number of days without precipitation and with precipitationprecipitation totals precipitation total 0.0 0.1–1 >1 >2 >5 >10 >20 >50 (mm) January–December 1982 71.6 232.5 53.4 79.1 57.8 27.9 10.0 2.4 0.1 January 1997 20.5 22.7 6.6 1.7 1.0 0.3 0.1 0.0 0.0 February 1976 15.2 24.5 3.0 1.5 0.8 0.1 0.0 0.0 0.0 March 1974 21.4 26.7 2.4 1.9 1.3 0.4 0.0 0.0 0.0 April 2009 15.9 27.3 1.4 1.3 0.9 0.3 0.2 0.0 0.0 May 1956 44.7 22.3 3.4 5.3 3.8 1.4 0.6 0.1 0.0 June 1976 50.5 22.0 2.4 5.6 4.7 2.8 1.2 0.1 0.0 July 2006 28.6 25.4 2.3 3.3 2.7 1.5 0.8 0.2 0.0 August 2015 22.5 25.3 2.6 3.1 2.2 0.9 0.3 0.1 0.0 September 1959 25.6 22.6 3.6 3.8 2.3 0.6 0.1 0.0 0.0 October 1951 6.4 29.0 1.2 0.8 0.3 0.1 0.0 0.0 0.0 November 2011 11.1 25.7 3.4 0.9 0.5 0.1 0.0 0.0 0.0 December 1972 15.8 24.0 5.0 2.0 1.0 0.1 0.0 0.0 0.0 Table 3: Characteristics of the structure of the highest precipitation totals in Poland, 1951–2018. Period / month Year with the highest % of multi-year Average number of days without precipitation and with precipitationprecipitation totals precipitation total 0.0 0.1–1 >1 >2 >5 >10 >20 >50 (mm) January–December 2010 134.4 180.7 66.6 117.7 91.5 50.3 22.1 7.2 0.9 January 2007 245.3 6.0 8.2 16.8 12.1 5.6 2.0 0.3 0.0 February 2002 184.1 10.6 5.5 11.9 8.5 4.0 1.0 0.1 0.0 March 1994 207.2 8.6 6.9 15.5 11.6 4.7 1.2 0.0 0.0 April 1970 190.1 10.7 6.7 12.6 9.6 5.6 2.3 0.3 0.0 May 2010 246.0 8.8 4.9 17.3 14.7 9.3 4.4 1.6 0.2 June 2009 160.7 9.2 5.8 15.0 12.2 7.8 4.1 1.0 0.1 July 2011 200.3 10.8 4.8 15.4 13.5 9.9 6.2 2.5 0.2 August 2006 220.1 9.8 5.2 16.0 13.7 8.9 5.2 2.1 0.2 September 2001 203.4 10.0 5.3 14.7 12.2 7.3 3.7 1.0 0.0 October 1974 354.9 7.5 6.2 17.3 14.8 10.1 5.7 1.8 0.1 November 2010 201.4 9.5 6.5 14.0 11.3 6.4 2.6 0.3 0.0 December 2005 186.3 8.4 7.8 14.8 11.3 5.2 1.9 0.2 0.0 < 5 5–10 10–15 15–20 20–25 > 25 < 5 5–10 10–15 15–20 20–25 > 25 < 20 20–40 40–60 60–80 80–105 > 105 January 1997 March 1974 < 5 5–10 10–15 > 15 < 5 5–10 10–15 15–20 20–25 > 25 < 20 20–40 40–60 60–80 80–105 > 105 February 1976 April 2009 May 1956 June 1976 < 15 15–30 30–45 45–60 60–75 > 75 < 10 10–20 20–30 30–40 40–60 > 60 July 2006 September 1959 < 10 10–20 20–30 30–40 40–55 > 55 < 5 5–10 > 10 August 2015 October 1951 < 5 5–10 10–15 15–20 < 5 20–70 5–10 > 70 November 2011 > 15 December 1972 In wet 2010 year, no precipitation was registered on ~181 days. In 2010, the average number of days onwhichprecipitationwasregisteredinPolandwasthefollowing:>1mm(~118days),>2mm(~92days), >5mm (~50 days), >10mm (~22 days), >20mm (~7 days), and >50mm (~1 day). The highest monthly Pr ranged from about 164% of the multi-year precipitation in June (2009) to as much as approximately 355%inOctober(1974).Inboththesemonths,therewasnorainonlyfor8–9days.Precipitationof>1mm per day was observed on about 15 and 17 days in June and October, respectively: >5mm – about 8 and 10 days, >10mm – about 4 and 6 days, and >20mm – about 1 and 2 days. In 2010, which has the highest Pr in the multi-year period, precipitation fluctuated from <750mm in the central strip and the north to >1700mm in the south of Poland (Figure 12). The highest Pr in consecutive months of the year was observed in various parts of Poland, most fre­quentlyinthesouth(Figure13).Highprecipitationvaluesalsooccurredinthenorth(e.g.inJanuary2007 andOctober1974),inthenorth-west(e.g.inFebruary2002andApril1970),inthenorth-east(e.g.inAugust 2006 and October 1974) and in the east (e.g. in August 2006 and October 1974). The biggest differences in Pr occurred in May, when the totals oscillated from <100 to >375mm, and July when the totals oscil­latedfrom<100to>320mm;thehighesttotalswererecordedinthesouthernandeasternpartsofthecountry. 3.4 Precipitation regions In Poland, the area of each of the three regions (separated based on precipitation totals and precipitation variability) changed depending on the analyzed multi-year period (Figure 14). In the first half of the examined multi-year period, i.e. in 1951–1984, the region with the lowest Pr (Cluster I) mostly covered the central-east part of Poland; the second Pr region (Cluster II) covered a bigger part of the country, namely the north, west and partly the south of Poland; the third Pr region Figure 12: Spatial distribution of the highest annual precipitation totals in Poland in all the analyzed years, 1951–2018. Figure 13: Spatial distribution of the highest monthly precipitation [mm] totals in Poland in all the analyzed months, 1951–2018. p p. 64–65 (Cluster III) encompassed a small area in the south and the south-west of Poland. In the second half of the considered multi-year period, i.e. in 1985–2018, regions with a characteristic precipitation variabili­tycoveredslightlydifferentareasofPoland.In1985–2018,thefirstPrregionwasapproximately50%larger than in 1951–1984 and covered the entire central strip of Poland up to the north-western and north-east­ern parts of the country. The second Pr region shrank at the cost of the first region and covered areas only in the north and the south of the country; the third region, on the other hand, slightly shrank at the cost of the second region. As expected, in the whole analyzed multi-year period (1951–2018) the distribution of the distinguished precipitation regions was similar to the distributions in the first and second halves of the entire multi-year period. In 1951–2018, the first and second Pr regions covered almost the same area intermsofsize.ThefirstPrregioncoveredcentralPoland,whilethesecondonecoveredthenorthernand southernparts.ThethirdPrregionwassituatedinthesouthandthesouth-westofPolandanditsareawas slightly smaller than in 1951–1984. Inallthethreeanalyzedmulti-yearperiods,thestationsofthelowestprecipitationtotalswereclassified as the first Pr region,while the stations of the highest totals were classified as the third Pr region (Table 4). In 1951–1984, average precipitation totals were ~550mm in the first region, ~650mm in the second and ~1310mm in the third; in 1985–2018 these values were ~577, ~713 and ~1237mm, respectively. In all the separated regions, lower Pr values in 1951–1984, in comparison with 1985–2018, occurred only in three months: March, May and September. Comparing the two examined sub-periods, a higher average standarddeviationofPrwascalculatedin1985–2018inRegionIandRegionIIIandin1951–1984inRegion II. In particular months, Pr variability determined on the basis of the standard deviation was lower in as many as 10 months in 1951–1984 in Region II, 8 months in Region I, 6 months in Region III, and in 5 months, i.e. March, April, May, July and September, in all regions. Inthemulti-yearperiodof1951–2018,averageannualProscillatedfrom567mminRegionItoabout 1272mm in Region III (Table 4). In Region I, i.e. in central Poland, average monthly Pr values fluctuated fromabout28to82mm;inRegionIItheyfluctuatedfromabout33to95mm,andinRegionIIItheyfluc­tuatedfrom about 73 to 172mm; the lowest totals occurred in February and the highest were in July. The highest variability of Pr in 1951–2018, as in the years 1951–1984 and 1985–2018, was noted in Region III. Table 4: Characteristics (x¯±SD) of precipitation totals in Poland by regions (I, II, III) in 1951–1984, 1985–2018, 1951–2018. Period / 1951–1984 1985–2018 1951–2018 month Region Region Region Figure 14: Regions (I, II, III) of Poland of similar precipitation totals and precipitation variability in 1951–1984, 1985–2018 and 1951–2018. p p. 66 < 70 70–100 100–130 130–175 > 175 < 60 60–80 80–100 100–145 > 145 < 100 100–150 150–200 200–250 250–375 > 375 January March 1994 < 40 40–60 60–80 80–125 > 125 < 60 60–80 80–100 100–130 > 130 < 80 80–110 110–140 140–170 170–210 > 210 February 2002 April 1970 May 2010 June 2009 < 100 100–150 < 120 150–200 120–160 200–250 160–200 250–320 200–245 > 320 July 2011 > 245 August 2006 < 80 < 120 80–120 120–160 120–160 160–200 160–240 200–240 > 240 September 2001 > 240 October 1974 < 60 < 60 60–80 60–90 80–100 90–120 100–120 120–150 120–165 > 150 November 2010 > 165 December 2005 a) 1951–1984 1985–2018 b) c) 1951–2018 Region I II III Scale: 1:10,000,000 Content and map by: Robert Kalbarczyk0 55 110 Source: IMWM (Poland), 2020km © 2020, Robert Kalbarczyk Inautumnandwintermonths,thestandardprecipitationdeviationwashigherthaninthespringandsum­mermonthsandfluctuatedfromapproximately15to46mminRegionI,fromapproximately18to52mm in Region II, with the lowest values in February and the highest in July; in Region III it oscillated from ~38mm in March to ~93mm in July. 4 Discussion In Polandin themulti-yearperiodtheannual precipitation totalshavechangedsignificantly only in some areas of the country. In the south-east, central-east and north-west Poland, precipitation increased sig­nificantly, while the sum of precipitation was only locally reduced in south-west Poland. An increase in precipitationtotalswasconfirmedonlyregionally.TheobservedsignificantpositiveincreaseinPrinMarch had the biggest spatial range. The high increase in precipitation in March and the slight increase in annu­al precipitation totals in Poland in 1951–2013 were also confirmed by Szwed (2018). Adecreaseinmonthlyprecipitationtotalswasalsofrequentinsomeregions.Regionaldifferencesrelat-ed to the trends of precipitation totals and the number of days with precipitation are a very common phenomenon. In Slovakia, regional differences in the temporal distribution of precipitation were shown by Labudová, Faško and Ivanáková (2015); in Czechia, some regional differentiation in annual precipita­tion totals of daily maxima was also found (Kveton and Žák 2008). Some examples of regional differences in precipitation variability can also be found in studies by, for example, Skowera, Kopcinska and Kopec (2014), Tošic et al. (2016), Kivinen et al. (2017) and Pathak et al. (2018). In the examined 1951–2018 period, differences between the lowest and highest values of annual and monthly precipitation totals and the long-term average (norm) were very high. The highest annual pre­cipitation total in Poland was recorded in 2010 and constituted ~135% of the norm. The highest monthly precipitationtotalconstitutedfromabout164%inJune(2009)toasmuchasabout355%inOctober(1974) of the multi-year monthly values. The lowest annual precipitation total in Poland, which was recorded in 1982, constituted ~72% of the multi-year annual precipitation. In particular months, precipitation totals constituted from as little as about 6% of the monthly norm in October 1951 to about 51% of the norm in June 1976. Although undertaken quiteoften, studies on values that deviate from the norm are still a chal­lengeforresearchers(HundechaandBárdossy2005;Mlynski,CebulskaandWalega2018;Kalbarczykand Kalbarczyk 2020b). Differences in the extent of atmospheric precipitation in Poland are primarily explained by the effect of certain types of atmospheric circulation; high importance is attributed to cloud cover (Degirmendžic, Kozuchowski and Zmudzka 2004; Zmudzka 2009; Twardosz, Niedzwiedz and Lupikasza 2011; Mlynski, Cebulska and Walegaet 2018). For extreme phenomena it is difficult to prove the significance of a trend and regularities in the development of a given phenomenon (Pfeifer et al. 2015; Zeyaeyan et al. 2017). The observed differences in temporal distribution of precipitation totals between particular years result in irregular periods of drought and excessive precipitation, whose negative social and economic effects cannot be prevented (Kundzewicz, Radziejewski and Pinskwar 2006; Dumrul and Kilicarslan 2017; Brázdil et al. 2019). According to some researchers, the frequency of droughts in Poland isincreasingandwillcontinueriseuntiltheendofthecentury(Kalbarczyk2010;KucharandIwanski2013; Somorowska2016).Similarpredictionsconcerningtheincreasedintensificationofdroughtconditionsuntil 2100 have been made for, among others, California (Pathak et al. 2018), South Europe and North Africa (Caloiero,CaloieroandFrustaci2018),andThuringiainsummer(KrauseandHanisch2007).Ontheother hand,NorthEuropeisexpectedtoexperienceincreasedprecipitation(Szwed et al.2010).Itisalsoreport-ed that in spring Poland may expect an increase in precipitation (Mezghani et al. 2017). Spatial distribution of annual precipitation totals in Poland shows a clear regularity. The lowest pre­cipitation is characteristic of the central part of the country and increases northwards and southwards, withmaximumvaluesinthesouthernmostmountainareas.Thedeterminedprecipitationregionsdisplay a fairly close similarity to the pluviothermal regions of Poland presented in Schmuck’s (1965) as well as in Ziernicka-Wojtaszek and Zawora’s (2008); the fundamental difference is the range of the lowest pre­cipitationregionreachingalsothenorth-eastofthecountry.IntheKöppen’sclassificationnearlythewhole Poland is located in the Dfb zone, only a small fragment in the south is included in the climatic zone Dfc (Beck et al. 2018). Thus, the present regionalization provides additional information about spatial differ-encesofprecipitationinPoland.Inparticularmonthsandseasons,spatialdistributionofprecipitationtotals slightly diverge from this regularity; however, the areaswith thelowest precipitation totals are continually located in the strip of central lowlands with a shift to the west or east of the country. The highest month­ly Pr values in the examined multi-year period occurred in various parts of the country, most frequently in the south of Poland. This kind of spatial distribution of precipitation in Poland is consistent with pre­vious research studies conducted on the basis of different multi-year periods, as well as research on the early decades of the 20th century (Twaróg 2016; Szwejkowski et al. 2017; Szwed 2018); this indicates sta­ble regularities of Poland’s spatial distribution of precipitation. The determined precipitation regions may be useful for climatic risk management and preparation of regionalandlocaladaptationplansaimedatbalancingtheeffectsofclimatechange(Twaróg2016;Kalbarczyk and Kalbarczyk 2020a). 5 Conclusion InPoland,averageannualprecipitationtotalsin1951–2018wereonly~634mmandfluctuatedfrom<550mm inthecentralpartofthecountryto>1300mminthesouth.Thelowestaveragemonthlyprecipitation(Pr), was observed in February and was about 2.9 times as low as the highest average values observed in July. The highest variability of Pr, both annual and monthly, usually occurred in the areas of the highest pre­cipitation totals, primarily in the south of Poland. In1951–2018,inmostpartsofPolandapartfromthesouth-west,annualprecipitationtotalsroseyear by year, but a significant increase of at least at a level of a=0.1 was found only in small areas in the north-west,central-westandsouth-east.ThisincreasewascausedbytherisingPrinMarchwhichoccurredmainly in northern and central Poland. ExtremeannualprecipitationtotalsinPolandoccurredin1982and2010.Theyconstitutedabout72% and 134% of the norm, respectively. The lowest monthly Pr, which constituted only ~6% of the norm, was recorded in October 1951; the highest monthly Pr, which constituted as much as ~355% of the norm, was recorded in October 1974. In the months of the lowest Pr (dry months), the average number of days without precipitation var-iedfromabout22daysinJune1976to29daysinOctober1951;inthemonthsofthehighestPr(wetmonths), itvariedfrom6daysinJanuary2007to11daysinJuly2011,April1970andFebruary2002.Inthemonths withthelowestprecipitation,theaveragenumberofdayswithprecipitationof>5mmandtheaveragenum­ber of days with precipitation of >10mm were mostly observed in June and amounted to 2.8 and 1.2 days, respectively. Spatial distribution of the lowest and highest Pr in particular months of the year in compar­isonwithaveragemulti-yearvaluesdifferednotonlyinprecipitationtotalsbutalsoinspatialdistribution, which mostly resembled a latitudinal arrangement in the case of dry months or an irregular arrangement in wet months. Three precipitation regions were distinguished in Poland on the basis of precipitation variability in eachofthedifferentmulti-yearperiods:1951–1984,1985–2018,and1951–2018.Thelowestandleastvari­ablePrvalueswereclassedasRegionI,whichin1951–1984coveredthecentral-eastpartofPoland,whereas in 1985–2018 it was in the central, north-west and north-east parts of the country. The highest and most variable Pr was classed as Region III, which in all the analyzed multi-year periods was in the south-west and south Poland. The results may prove useful while planning water management measures, as well as in the management of flood risks and prevention of drought effects. 6 References Beck, H. 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A COMPARISON OF THE BEGINNINGS OF EXONYM STANDARDIZATION IN CROATIAN AND SLOVENIAN Ivana Crljenko, Matjaž Geršic The exonym Jakin ‘Ancona’, formerly established in both Croatian and Slovenian, in Cigale’s Atlant (Atlas), the first world atlas in Slovenian. DOI: https://doi.org/10.3986/AGS.9678 UDC: 811.163.6’373.21 811.163.42’373.21 COBISS: 1.01 Ivana Crljenko1, Matjaž Geršic2 AcomparisonofthebeginningsofexonymstandardizationinCroatianandSlovenian ABSTRACT: This paper compares the beginnings of exonym standardization and some characteristics of the oldest exonyms in two similar Slavic languages, Croatian and Slovenian. It uses the comparative and exemplar methods. It is found that these processes were influenced by the sociopolitical environment of thetime,especiallylanguagepolicies.Itisshownthatthenineteenthcenturywasfavorablyinclinedtoward exonyms.Theywereoftenwritteninconsistentlyandunsystematicallybecausetherewerenospellingnorms for their writing and use. For some, the influences of foreign languages (German, Italian, etc.) are obvi­ous. Numerous transitional forms also appeared, which did not become established. KEY WORDS: exonyms, exonym standardization, geographical names, geography, linguistics, Croatian, Slovenian Primerjava zacetkov standardizacije eksonimov v hrvaškem in slovenskem jeziku POVZETEK:Clanekobravnavazacetkestandardizacijeeksonimovinidentifikacijonajstarejšiheksonimov vdvehpodobnihslovanskihjezikih,hrvaškeminslovenskem,sprimerjalnoinvzorcnometodo.Ugotavlja, da je bila standardizacija eksonimov plod družbeno-politicnih okolišcin, še posebej jezikovnih politik, in da je bilo 19. stoletje naklonjeno eksonimom. Pogosto so jih zapisovali neenotno in nesistematicno, saj pravopisna pravila za njihovo rabo še niso bila izoblikovana. Pri nekaterih so ocitni vplivi tujih jezikov (nemškega,italijanskegaindrugih).Pojavljalesosetudištevilneprehodneoblikeeksonimov,kipaseniso uveljavile. KLJUCNE BESEDE: eksonimi, standardizacija eksonimov, zemljepisna imena, geografija, jezikoslovje, hrvašcina, slovenšcina The paper was submitted for publication on February 24th, 2021. Uredništvo je prejelo prispevek 24. februarja 2021. 1 The Miroslav Krleža Institute of Lexicography, Zagreb, Croatia ivana.crljenko@lzmk.hr (https://orcid.org/0000-0002-1315-0644) 2 Research Centre of the Slovenian Academy of Sciences and Arts, Anton Melik Geographical Institute, Ljubljana, Slovenia matjaz.gersic@zrc-sazu.si (https://orcid.org/0000-0001-9640-6037) 1 Introduction Exonymstandardizationistheprocessofadapting(i.e.,nativizing)originalgeographicalnamesfromadonor language (i.e., endonyms) to a changed (or adapted or nativized) form in a recipient language. Because it takes place within a particular language, exonym standardization reflects the characteristics and devel­opment trends of that language in a certain period (Kladnik 2007a; 2009; Kladnik et al. 2017). This is also thecaseinCroatianandSlovenian,twosimilarSlaviclanguagesthatwereinfluencedbyexternalsociopo­litical factors and different language policies during the Austro-Hungarian period (Kladnik et al. 2017). In both languages, certain exonyms were used long before the first half of the nineteenth century – per­hapsassoonascertainplacesbecamerelevantforpeoplespeakingCroatianandSlovenian–butuntilthen were not standardized in any way. The first half of the nineteenth century was a period marked by nation-alawakening,stateformation,thebuildingofnationalidentities,andintenseadvocacyfortheestablishment of distinct languages and standard orthographies. Exonyms were used more and more frequently in dif­ferentpublications,andthereforethefirstattemptsofexonymstandardizationappeared.Thispapercompares exonymstandardizationandsomecharacteristicsoftheoldestexonymsinbothlanguagesduringthenine­teenthcentury.Itisestablishedhowthebroadersociopoliticalcontext,especiallynormativepolicy,influenced exonym standardization in both languages, what the similarities and differences were in these processes, and why they exist. Croatian and Slovenian researchers have discussed exonyms, mostly addressing modern usage (e.g., Kladnik2007c;KladnikandBole2012;PerkoandKladnik2017;Crljenko2018;2019;2020;Kladnik,Geršic andPerko2020),generalissues(e.g.,Kladnik2006;Kladnik2007d;Kladnik et al.2013;Perko,Jordanand Komac2017;Kladnik,GeršicandPerko2020),relationshipsbetweenendonymsandexonyms(e.g.,Kladnik 2009), and sometimes also their use in literature (e.g., Geršic 2019). Researchontheoldestexonymsismainlyfoundin(top)onomastics,andlessoftenincartographyand historical geography. Toponymic papers focus on specific language problems supported by a small num­ber of examples, not systematically. Dinu Moscal (2018) deals with the complete or partial translation of foreign toponyms into Romanian at the beginning of the nineteenth century. In an analysis of translated toponymsinthreehistoricaltextsfromtheRomanianpremodernperiod(1780–1830),Ana-MariaGînsac and Madalina Ungureanu note that translation was influenced by different language systems, differences inpronunciationandwritingbetweenRomanianandthedonorlanguageofthenames,differencesamong the donor languages (French, German, Italian, etc.), the variety of proper names, translators’ knowledge, andsoon.Thesameauthors(2020)alsodealtwiththeadaptationofforeigntoponymstoRomanianthrough an intermediate language (Greek or Latin) during that period. The oldest sources of Hungarian exonyms werestudiedbyBélaPokoly(2006),whocitessomeexamples.InananalysisofthefirstDutchschoolatlases toexplorehowGreecewasdepictedinthem,FerjanOrmeling(2015)alsoreferstothewritingofexonyms in the nineteenth century. The most extensive collections of exonyms are found in world atlases and geographical textbooks, as wellasinorthographicmanuals.Theyalsoappearinencyclopedicpublications,monographsongeography, newspapers,andjournals;thefirstCroatianexonymsappearintranslationsofthemedievalbookLucidarius, andthefirstSlovenianonesintheworksofProtestantwritersinthesixteenthcentury(Kapetanovic2005; Kladnik,GeršicandPerko2020).Systematicresearchongeographicalnamesinvariouspublicationsfrom this period is relatively modest. The first world atlas in Slovenian was published between 1869 and 1877. It was called Atlant (Atlas), and the Slovenian text for it was edited by Matej Cigale (Fridl et al. 2005; Kladnik et al. 2006; Urbanc et al. 2006). The names in it were carefully analyzed by Drago Kladnik, and thefindingswerepublishedinseveralplaces(e.g.,Kladnik2005;Kladnik2007b;KladnikandGeršic2016). The names in the oldest world atlases by Blaž Kocen from the end of the nineteenth century (starting in 1887) thatwere prepared for Croatian users have not been analyzed so far. Although Marcel Kušar briefly refers to the basic principles of exonym standardization in his Science of the Orthography of the Croatian or Serbian Language (photenic and etymologic; Kušar 1889), the third edition of Ivan Broz’s 1904 Hrvatski pravopis (CroatianOrthography, edited by Dragutin Boranic) can be considered the first Croatian ortho­graphic manual with rules on adapting names from other languages. Ankica Cilaš Šimpraga and Ivana Crljenko (2017) reviewed the rules of exonym standardization in it, as well as in other Croatian ortho­graphic manuals. The first Slovenian orthographic manual in Slovenian, which also contains a section on theSlovenianizationofgeographicalnames,waspublishedin1899inViennabyFranLevec(Figure1;right). TheexonymsinthismanualwereanalyzedbyMatjažGeršic(2020).Somefeaturesofexonymsinthemul­tidisciplinary geographical work Images from General Geography (Hoic 1888–1900) were addressed by Crljenko(2014).ThelargenumberofexonymsinthegeographicaltextbookZemljepisnazacetnicazagim­nazije in realke (Basic Geography for High Schools; Jesenko 1865; Figure 2; right) have not yet received scholarly analysis. The writing of selected exonyms (e.g., Great Britain, Ireland, Scotland, and England) in Croatian newspapers from the first half of the nineteenth century was studied by Dora Riffer-Macek (1962). Inasimilarmanner,IrenaOrel(2004)comparedtheuseofgeographicalnamesinthenewspapers Ljubljanske novice (Ljubljana News, 1797) and Kmetijske in rokodelske novice (Farmers’ and Craftsmen’s News, 1797 and 1850). Her research is based on bachelor’s theses by Breda Bernetic (1990) and Mojca Podobnikar (2004) and on her own research. Interestingly, the author states in a footnote that compari­sonwithcontemporaryforeignnewspaperswouldbenecessary.MarkoJesenšek(2013)studiedthewriting ofgeographical names, as well as exonyms, in the first Prekmurje newspaper Prijatel (The Friend), which was published from 1875 to 1879 (and appeared from 1877 onward in the Gaj alphabet). Based on the literature reviewed, it was determined that there are many discussions about the topi­calityoftheuseofexonyms,butresearchersrarelyfocusontheverybeginningsofexonymstandardization– and, if they do, they focus on sources in their own language. This paper aims to fill the research gap in thisareaandcomparetheprocessofexonymformationintwodifferentbutcloselyrelatedSlaviclanguages. Comparing exonyms in historical sources helps in determining what their development was and in the application of typology of exonymization. Thisstudyisadirectresultofbilateraltwo-yearcooperationbetweenSlovenianandCroatianresearchers, the objective of which was, among other things, to compare Croatian and Slovenian exonyms and social, political, and linguistic influences on their formation (Kladnik et al. 2017). Figure 1: Title pages of the first orthographic manuals in Croatian (1892; left) and Slovenian (1899; right). 2 Methodology A comparative method is used to compare exonyms in Slovenian and Croatian sources, and an exemplar methodisusedtosubstantiateclaims(examplesofexonyms).Exonymsselectedfromtheoldestgeographical sources (atlases, textbooks, and monographs), linguistic sources (orthographic manuals), and old news­papers are analyzed. A set of exonyms for further analysis was compiled in two phases. Inthe first phase, we identified 422 exonyms from various Croatian sources, which various authors used to name 285 topographic features. CroatianexonymswereidentifiedinseveralgeographytextbooksbyBradaška(1867),Marik(1868;1870), Klaic (1875; 1881), Hoic (1888–1900), and Rožic (1842), and in Kocen's atlases (1887; 1900; 1911; 1919), inthenewspapersIlRegioDalmata/KraglskiDalmatin(RoyalDalmatian,1807;1808)andNarodnenovine (ThePeople’sNewspaper,1843),inthebookletNaukaopravopisujezikahrvackogailisrpskoga(fonetickom ietimologijskom)(Kušar1889),andinBroz’sorthographicmanual(1892;1904;1906).Inthesecondphase, SlovenianexonymsweresoughtinselectedSloveniansourcesthatwouldcorrespondtotheCroatianones. The Slovenian set of sources is less numerous, but at least one source was selected for each type of source. The choices were Cigale’s atlas Atlant (1868–1877), Jesenko’s textbook Zemljepisna zacetnica za gimnaz­ije in realke (1865), the first Slovenian orthographic manual, prepared by Franc Levec (1899), and the newspapersKmetijskeinrokodelskenovice,editedbyJanezBleiweis,andLjubljanskenovice,editedbyValentin Vodnik. In the selected Slovenian sources, exonyms were identified for 161 topographic features, which were identified in the first phase in the Croatian sources. The final set for the name corpus, which was the sub­ject of further analysis, included 232 Croatian exonyms and 250 Slovenian exonyms for 161 topographic features. Based on their comparison, the individual characteristics were determined for the beginning of exonym standardization in the two languages. 3 The emergence of exonyms At the beginning of the nineteenth century, the most accessible source of exonyms for the Croatian pub­lic was Croatian newspapers. Although they were just being established and their reach was limited, their spreadcertainlycontributedtotheuseofexonyms.ThefirstbilingualItalian–Croatiannewspaper,IlRegio Dalmata / Kraglski Dalmatin, was published from 1806 to 1810 once a week in Zadar. Although this was thefirstnewspaperinCroatian,thegeographicalnameswritteninthenewspaper’sCroatiancolumnwere clearly strongly influenced by other languages, Italian as well: either Italian names were used verbatim or (semi-) Croatianized forms were written based on Italian (Pragha – Italian Praga ‘Prague’, Parigi ‘Paris’, Nizza‘Nice’,Napuli–ItalianNapoli‘Naples’,Italia‘Italy’).In1823,thefirstgeographicaltextbookinCroatian was published by Antun Rožic, Kratki zavjetek zemelyzkoga-izpiszavanya Horvatzke y Vugerzke zemlye (AShortManualonGeographyofCroatianandHungarianLands;Figure2;left),inwhichtheoldestexonyms ingeographicalliteraturecanbefound;forexample,Europa‘Europe’,TurzkoCzeszarztvo‘OttomanEmpire’, Franczuzko Kralyeztvo ‘Kingdom of France’, and Stajerzka ‘Styria’. The authors of newspaper and geographical texts adapted exonyms in different ways. The reason for thisisthefactthatseveralgraphicallydifferent,nonstandardorthographieswereused,whichwerenotuni­fiedintermsofthelettersusedinthespelling,letaloneindeterminingthewritinganduseofgeographical names for foreign features. In 1830, Ljudevit Gaj’s orthographic manual Kratka osnova horvatsko-slaven­skoga pravopisana (Brief Basics of Croatian-Slavic Orthography) was published, which at least partially overcame the previous particularisms. It standardized Croatian Latin script, but there were still problems with spelling rules, which were often applied intuitively or following customary use (e.g., capitalization; Badurina 2012). ExonymstandardizationincreasedinCroatiastartinginthe1830s,whichisassociatedwiththebegin­ningoftheCroatiannationalrevival–anational,cultural,andpoliticalmovementthatsupportednational awakening,integrationofCroatianterritories,affirmingCroatianidentity,andthusstrengtheningtherole of the Croatian language. The official beginning of the movement is considered 1835, when Ljudevit Gaj received permission to publish a political newspaper, Novine horvatzke (Croatian Newspaper) with the literarysupplementDaniczahorvatzka,slavonzkaydalmatinzka(TheCroatian,Slavonian,andDalmatian Daystar). The idea of »linguistic and orthographic unification of all Croatian regions – along with that of Slavic reciprocity« (Badurina 2012) was one of the fundamental components of this (Illyrian) movement. Afterpartialunityinlanguagepolicywasachieved,theCroatiannationalrevivalwasfurtherstrength­ened by ideas about the importance of knowing and using Croatian. Therefore, after initial resistance to its use in the 1830s, Croatian finally became the official language in general use in 1847. It began to be usedinschools,intheCroatianparliament,andinpublicservices,andbooks,newspapers,textbooks,and geographical literature began to be published in it. Consequently, exonym standardization became more intense, and reception of exonyms became more favorable at the expense of endonyms. Not only were Croatian names created and used for familiar, nearby geographical features, but the names of more dis-tant,non-European,lesser-knowngeographicalfeatureswerealsoincreasinglyadapted(e.g.,inthenewspaper Narodnenovineof1843onefindstheexonyms:Antiliban‘Anti-LebanonMountains’,ZapadnaIndia‘West Indies’, Tibet, Tatarska ‘Tatarstan’, Kairo ‘Cairo’, and Hindostan ‘Hindustan’). Inthesecondhalfofthenineteenthcentury,severaldifferentorthographicmanualsandvariousgram­marswerestillused.However,theygenerallydonotmentiontheproblemofwritingexonyms,andsothere are no corresponding rules for their writing and use. If these do appear,they cite exonyms with only a few examples. Thus, in the booklet Nauka o pravopisu jezika hrvackoga ili srpskoga (fonetickom i etimologi­jskom) from 1889, Marcel Kušar mentions only a few exonyms (Azija ‘Asia’, Evropa ‘Europe’, Kavkaz ‘the Caucasus’;Kušar1889;CilašŠimpragaandCrljenko2017).Theuseofmultipleorthographicmanualswith-out clear rules led to the appearance of inconsistent names in various publications (Crljenko 2008; 2014). Whentheboardofeducationdeterminedthat»oneorthographicmanualshouldbeused«(Broz1892) in Croatian schools for the first time in 1862, and then again in 1864, 1877, and 1889, Ivan Broz was given the task of putting it together. Thus, in 1892, the first graphically standard Croatian orthographic manu­al, Hrvatski pravopis, was created, which finally »standardized the Croatian phonological-morphological orthographicnorm«forthefirsttime(Badurina2012,66;Figure1;left).WithlatercomplementbyDragutin Boranic,it went through six editions and was used until the 1920s.In it,however,even Broz does not state therulesforadaptingnamesfromforeignlanguages,andinthedictionarysectiononlyafewexonymsare recommended (e.g., Mletci, not Venecija ‘Venice’; and Njemadija or Njemcadija,not Njemacka ‘Germany’; Broz 1892; Cilaš Šimpraga and Crljenko 2017). Onlyinthethird(1904)andunchangedfourthedition(1906)ofBroz’sorthographicmanual,prepared by Dragutin Boranic, were the rules on adapting names from other languages adopted. It is pointed out thatwordsthatenteredCroatianlongagoarewrittenlikedomesticCroatiannames,andthosethatentered more recently either completely retain their foreign form or are adapted to Croatian. However, it warned that historical exonyms such as »Monakov for München ‘Munich’, Draždani for Dresden, and Kopenhagen for Kjöbenhavn ‘Copenhagen’… should not be used because these names are not pronounced this way bythe people they belong to« (Broz 1906, 51; Cilaš Šimpraga and Crljenko 2017), from which it follows that asearlyasthebeginningofthetwentiethcenturyitwascautiouslyrecommendedtoreducetheuseof(his­torical) exonyms in favor of endonyms. Althoughtherewasstillnolanguagestandardfromthe1860stothe1880s,thehistoricalmomentrequired geographerstocreateand/ortranslateschooltextbooksandatlasesintoCroatian.Severalgeographerspre­paredschooltextbooksongeneral(i.e.,world)andonregional(theAustro-HungarianMonarchy)geography: FranjoBradaška(1867),VjenceslavZabojMarik(1868;1870),PetarMatkovic(1875),VjekoslavKlaic(1875; 1881), and Ivan Hoic (1888–1900). In 1887, the first edition of the first atlas translated into Croatian was published: Kozenov geografijski atlaszasrednješkole (Kozen’sGeographicalAtlasforSecondarySchools),adaptedbyAugustinDobrilovic and Petar Matkovic. Blaž Kocen was a Slovenian geographer and cartographer that published geograph­ical atlases in German, Czech, Polish, Croatian, Hungarian, and Italian. His atlases in Croatian began to appear in the late 1880s (Bratec Mrvar 2007; Bratec Mrvar et al. 2011). With its thirty-seven maps, it is therichestsourceofadaptednamesfromthatperiod.AlthoughDobrilovicandMatkovic,likeotherauthors, hadtocomeupwith»correct«waysofwritingalargenumberofexonyms,manycharacteristicsofexonyms of that time, which have been confirmed in other sources, can be detected from this atlas. Compared to some later periods, the second half of the nineteenth century was very inclined toward Croatian exonyms, which means that exonyms enjoyed good reception and rather frequent use. This is also reflected in the fact that in most sources endonyms do not stand next to exonyms, not even in paren­theses. In Slovenia, exonym standardization can be more systematically observed with the appearance of the firstnewspapersinSlovenian.ThefirstonewaspublishedonApril1st,1797,andwascalledLublanskenovize od v.ih Krajov zeliga .vejta (Ljubljana News from All Parts of the Whole World). The title itself promises the appearance of foreign geographical names, and indeed many appear in the first issue,includingDunej ‘Vienna’,Shpania‘Spain’,Madrit‘Madrid’,Franzo.kadeshela‘France’,Paris,andSdrusheneholendor.kedeshele ‘United Provinces of the Netherlands’. At that time, the Bohoric alphabet (hence Lublanske novize, 1797) wasstillestablishedastheorthographyforwritingSlovenian.ThenextSloveniannewspaperwasKmetijske in rokodelske novice, which was launched in 1843. An increase in the use of exonyms began, similarly to Croatian,withtheSloveniannationalmovementanditsspreadinthelateeighteenthandearlynineteenth centuries. An important change that took place in the nineteenth century and also affected the writing of geo­graphicalnameswasthechangeofSlovenianorthographyin1848,whenpeoplebeganusingtheGajalphabet instead of the Bohoric alphabet. Illyrianism,whichwasstronglypresentinCroatia,didnotexperiencesuchstrongsympathiesinSlovenia. The key factor in this resistance was the idea or demand to abandon Slovenian as a language and adopta South Slavic language, which would be based on Štokavian dialect. Even Stanko Vraz, the main propo­nentofIllyrianisminSlovenia,primarilysawculturalintegrationinabroadersenseinthemovement,and somehowhewasnotreadytogiveupSlovenian.Thereweremoresympathizersmainlyonthenortheastern edgeofSlovenianethnicterritory,wherethepressureofGermanizationwasstrongestandIllyrianismrep­resented a kind of defense against Germanization (Cvirn 2000). The first geography textbook in Slovenian that systematically contains a large number of foreign geo­graphicalnamesisZemljepisnazacetnicazagimnazijeinrealke(Figure2;left).ItwaswrittenbyJanezJesenko and was self-published in 1865 (Kladnik 2005; Kladnik and Bratec Mrvar 2008). The work already uses Figure 2: Title pages of the oldest geography textbooks in Croatian (left) and Slovenian (right). Table 1: Comparison of milestones in exonym standardization in Croatian and Slovenian. Croatia Slovenia First orthographic manual First geography textbook First world atlas First newspaper Official language status 1892 (Hrvatski pravopis) 1823 (Kratki zavjetek zemelyzkoga-izpiszavanya Horvatzke y Vugerzke zemlye) 1887 (Kozennov geografijski atlas za srednje škole) 1806 (Il Regio Dalmata=Kraglski Dalmatin) 1847 1899 (Slovenski pravopis) 1865 (Zemljepisna zacetnica za gimnazije in realke) 1869–1877 (Atlant) 1797 (Lublanske novize od v.ih Krajov zeliga .vejta) 1849 many Slovenianized names in its text, and at the end the author added several tables containing names of towns.Thefirsttableliststowns»inAustria«(i.e.,Austro-Hungarianterritory),followedbyEuropeantowns andfinallytownsonothercontinents.TheauthordoesnotpresenttheissueofSlovenianizinggeographical names,butheaddsSloveniannamestosomenamesoftownsinAustria-Hungary(e.g.,Gjur=Raab‘Gyor’) whereashewritesnameselsewhereinEuropeandtheworldwithasinglename,usingeithertheendonym (e.g., Birmingham) or a Slovenianized name (e.g., Kodanj ‘Copenhagen’). The only exception is the name Konstantinopel ‘Constantinople’, to which he adds the Slovenianized form Carjigrad. 4 Results The comparison of the beginnings of exonym standardization is based on the name corpus, which con­tains a total of 482 names, of which 232 are from Croatian sources and 250 from Slovenian ones (Table 1). The collected names designate 161 different topographic features (Figure 3). Table 2: List of geographical names used in the analysis. List contains Croatian and Slovenian exonyms, as well as exonyms and endonyms of other languages when used interchangeably with the corresponding Croatian or Slovenian exonyms, rarely without them. If different name forms appear for a certain geographical feature, they are separated by a comma. Toponyms are listed in the same way they appear in the sources – sometimes with a small initial letter. The names are listed in alphabetical order in the left column. Names identified in Croatian sources Names identified in Slovenian sources Current endonyms Abruzi Abruzzo Abruzzo Adiža, Eca, Ecava Adiža Adige Adžmir Adžmir Ajmer aegejsko more, Egejsko more Egejsko morje Egeo pélagos/Ege Denizi Afrika Afrika Africa/Afrique* Akaba Akaba Al-’Aqabah Amerika Amerika America/Amérique* arabski zalev, cèrveno more, perzijski zalev, Arabski zaliv, Persijski zaliv, Perzijski zaliv, al-Bahr al-Ahmar/Badda Cas/QeyH baHri/ Perzijski zaljev Rdece Morje Yam Suf/Red Sea Arapsko more Arabsko morje Bahr al-’Arab Asia, Azija Asia, Azija, Azia Asia/Asie* Astrakan Astrahan Astrahan’/Ästerxan Atena, Atina Atene, Atine Athína atlanticki ocean, Atlantski ocean Atlanško morje, Atlantsko morje Atlantic Ocean/Océan Atlantique Attersko jezero Attersko jezero Kammersee Australija, Nova Holandija Avstralija, Nova Holandija Australia Austrija Avstrija, Estrajh Österreich Names identified in Croatian sources Names identified in Slovenian sources Current endonyms azovsko more Azovsko morje Azovskoe more/Azovs’ke more/Azaq deñizi Balaton, Blatno jezero Blatno jezero Balaton Bec, Beç Bec, Dunaj, Dunej Wien Becko Novo Mjesto Dunajsko novo mesto Wiener Neustadt Belak, Beliak, Beljak Belak Villach belo more, bielo more, Bielo more, Bijelo more Belo morje, Marmarsko morje Marmara Denizi/Propontis Benares Benares Varanasi Bengalski zalev Bengalski zaliv Bay of Bengal Bitolj Bitelj, Bitolja, Monastir Bitola Bodansko jezero Bodensko jezero Bodensee Bolonja Bolonja Bologna Brašov Braševo Brasov Brazilija Brazilija Brasil Bruselj Bruselj Brussel/Bruxelles Bukarešt, Bukurešt Bukreš Bucuresti Carigrad, Czarrigrad Carjigrad, Konstantinopel, Zargrad Istanbul Celovac, Celovac, Cjelovac Celovec, Zelovez Klagenfurt am Wörthersee Cernagora, Cherna Gora, Czerna gora, Crna gora Crna Gora Czerna Gora, Cerna Gora Cerno more, Cerno morje, crno more, Crno morje Cërnoe more/Chorne more/Marea Neagra/ Crno more Cerno more/Karadeniz/Shavi zghva Dnjestar, Dnyeztar Dnester, Dnestr Dnister/Nistru Draždjani, Draždani Draždane Dresden Drinopolje Adrianopel, Drenopolje Edirne Dunav Donava, Dunaj, Dunava Donau/Dunaj/Duna/Dunav/Dunarea/Dunay Englezka Angleško, Angležko, Anglia, Britania, England England Erdelj, Sedmogradska Erdelj, Erdeljsko Transilvania/Ardeal/Erdély/Siebenbürgen Eufrat Evfrat, Furat al-Furat/Firat Europa, Evropa Evropa, Europa Europe* Falacka Palatinat Pfalz Filippini Filipinski otoci Pilipinas/Philippines Fiorencija, Firenca, Florenc, Florencija Fiorenza, Florenca, Florensa, Florenz Firenze Francezka, Francuska, Franczuzko Kralyeztvo Francija, Francosko, Franzo..ka deshela, Franzosko France Gadames Ghadames Ghadamis/ghdams Galicija Galicia, Galicija Halychyna/Galicja Gardsko jezero Gardsko Jezero Lago di Garda/Benàco Gercka Grško Elláda/Hellás Gjur Gjur Györ glavina Dobre nade Nos dobre nade, Nos Dobre Nade Kaap die Goeie Hoop/Cape of Good Hope Gradac Gradec Graz Habeš Abisinija, Habeš Ityop· p ·ya Irska Irland, Irlandija, Irrland Éire/Ireland Islandija Izlandija Ísland Italia, Italija, Talijanska Italia, Italija, La. hko, Laška, Laško Italia Names identified in Croatian sources Names identified in Slovenian sources Current endonyms Iztocno kitjasko more Vzhodno-kitajsko Morje Zhongguó Dong Ha.i/Higashi­Shina-Kai/Dongjungguk-hae Jakin Jakin Ancona Jaš Jaš Iasi Jedrene Jadrene Edirne Jenizaj Jenisej Enisej jonsko more Jonsko morje Iónio pélagos/Mar Ionio/Deti Jon Južna Karolina Južna Karolina South Carolina Južni Sporadi Južne Sporade Nóties Sporádes južno kitajsko more južno Kitajsko morje Nán Zhongguó Ha.i/Nán Ha.i/Dagat Timog Tsina/Bieˆn Ðông/Laut Cina Selatan Kadiz Kadix Cádiz Kairo Kairo al-Qahira Kalifornija Kalifornija California Kališ Kališ Kalisz Kitajska China, Kina, Kitaj Zhongguó Kološvar Kološvar Kolozsvár Kolumbija Kolumbija Colombia Kopenhagen Kodanj København Krf Krf Kérkyra Lavov Levov L’viv Linac Linc Linz Lipsko Lipsko Leipzig Majna Men Main Marijanska kupelj Marijanske toplice Mariánské Lázne Mekhong Majkoung, Mekhong Láncang Jiang/Mae Khaung/Mae Nam Khong/ Mènam Khong/Tonle Mékôngk/Sông Mê Kông Mexicki zaljev, mexikanski zalev, zaljev Mehikanski zaliv, Mexikanski zaliv Gulf of Mexico/Golfo de México Meksicki, Zaton Mejicki, Zaton Mexicki Mexika, Mexiko Mehikanska, Mexico, Mexiko México Mleci, Mletci, Mljetci, Venecija Benedke, Benetke Venezia Moldavska Moldavija, Moldavska, Moldavski, Multanija Moldova Monakov Mnihov München Moriš Moriš Mures/Maros Moriški Novi Tèrg Moriški Novi trg Târgu Mure. Moza Maza, Moza Meuse/Maas Mozela Mozela Moselle/Mosel Muhac Muhac Mohács Napolj, Napuli, Napulj Napoli, Neapol, Neapolj, Neapel, Neapoli Napoli Nemachka, Nemacka, Nemacka, nimaçka Nemcija, nem. hki Rajh, nem. hko, Nemške Deutschland zemglia, Njemacka, Njemadija, Njemcadija države, Nemško Nil Nil an-Nil/Nile/Phiaro/iteru Nizza Nizza Nice Norveška, Norvežka Norvegija Norge/Noreg Names identified in Croatian sources Names identified in Slovenian sources Current endonyms Nova Foundlandija Nova Fundlandija Newfoundland Nova Kaledonija Nova Kaledonija Nouvelle-Calédonie Nova Seelandija Nova Zelandija New Zealand/Aotearoa Novi Hebridi Nove Hebride New Hebrides/Nouvélles-Hebrides* Novi Jork Novi Jork, Novi York New York Odra Odra Odra/Oder Olomuc Olomouc Olomouc Oporto Oporto Porto Orijaško gorje Krkonoši Krkonoše/Karkonosze Pad Pad Po Parigi, Pariz Paris, Pariz Paris Pasov Pasov Passau Pecuh, Pecuj Pecuh Pécs Persia, Perzia Iran, Persia, Persija, Perzija Iran Petrograd Petrograd, Petrovburg Sankt-Peterburg Pirej Pirej Peiraiás Piza Pisa Pisa Plzanj Pelzenj Plzen Poljsko Kraljevstvo, Polyzko Kralyeztvo Poljsko Polska Požun Požunj Požun Prag, Pragha Prag, Praga Praha Pruska Praj. oviko, Prusko Preußen Rajna Rajna Rhein/Rhin/Rijn reticke Alpe, Rhaetske Alpe Retiske Alpe, Retiske Planine, Retiške Planine Alpi Retiche/Rätische Alpen Rim Rim Roma Robsko jezero Sužniško Jezero, Veliko Sužniško Jezero Great Slave Lake Rodos Otok Rod, Otok Rodos, Rod, Rodos Ródos/Rhódos Ruska Rusija, Rusko, Rusko cesarstvo, Ru. sia Rossija Sala Salla Saale Saska Sasko Sachsen/Sakska Siget Siget Szigetvár Sileska, Szlezia Sleško Slask/Slezsko/Schlesien Smirna Smirna Izmir Solnograd Solnimgrad Salzburg Spanyolzko Kralyeztvo, Španjolsko Kraljevstvo Shpanija, Španija España sredozemno more, Sredozemno more Srednje morje, Sredozemsko morje Mediterranean Sea/Mer Méditerranée/ Mar Mediterráneo/Mar Mediterrània/ Mar Mediterraneo/Sredozemno more/ Deti Mesdhe/Mesogeios Thalassa/Akdeniz/ ha-Yam ha-Tikhon/al-Bah.r al-Abyad. al­Mutawassit./Ilel Agrakal Stajerzka, Štajerska Štajersko Steiermark Stokholm, Štockholm, Štokholm Stockholm Stockholm Stolni Biograd Stolni Belgrad Székesfehérvár Names identified in Croatian sources Names identified in Slovenian sources Current endonyms Syrija Sirija, Sirsko Suriyya/Surya Šopronj Šopronj Sopron Štrasburg Strassburg Strasbourg Švedska Švedija Sverige Tamiš Tamiš Timis/Tamiš Temišvar Temišvar Timisoara Tèrst, Trst Terst, Ter. t, Trst Trieste Thirrensko more, Tirensko more, Tirensko morje, Toskansko Morje Mar Tirreno/Mer Tyrrhénienne Tirrensko more, Tirrhensko more Tiber Tibera Tevere Tibet Tibet Xizàng zìzhìqu/Xizàng/ Bod-rang-skyong-ljongs/Bod Tiflis Tiflis T’bilisi Tirolska Tirolska, Tirolsko Tirol Turska, Turzko Czeszarztvo Turcia, Turcija, Turške dežele, Turzhija Türkiye Varsciovia, Varšava Varšava Warszawa Velika Britania, velika Britanija, Velika Brittania Velika Britanija Great Britain/Breatainn Mhòr/Prydain Fawr Velika Kaniža Velika Kaniža Nagykanizsa Veliki Varadin Veliki Varad, Veliki Varadin, Veliki Vardin Oradea Veliko medvedje jezero Medvedje Jezero Great Bear Lake Vezera Vezera, Vezra, Wezra Weser visoke Ture Visoke Ture Hohe Tauern Volinj Volinj Volyn’ Vorarlberžka Predarelsko Vorarlberg Zalev sv. Lovrinca Svetega Lovrencija zaliv Gulf of Saint Lawrence/Golfe du Saint Laurent zelena glavina Zeleni Nos Cap Vert Žuto more Rumeno morje Huáng Ha.i/Hwang-Hae *English and French name 4.1 Comparison In comparing the oldest exonyms in Croatian and Slovenian, the use of an identical exonym in both lan­guages was found for forty-five topographic features. These are cases in which only one exonym form was identified for a single language (the exception is ‘Europe’, for which two identical ones were identified in both languages). Such examples are Jakin ‘Ancona’, Krf ‘Corfu’, and Nizza ‘Nice’. A match was also found in at least one exonym form in twenty-two named topographic features, where the use is not uniform in either Croatian or Slovenian. Such examples are Bec ‘Vienna’, Habeš ‘Abyssinia, Ethiopia’, Persija ‘Persia, Iran’, and Varšava ‘Warsaw’. Six cases involved differences only in the generic part of the name. These are mostly the names of bays and seas, such as Cro. Azovsko more and Sln. Azovsko morje ‘Sea of Azov’, Cro. Bengalski zalev and Sln. Bengalski zaliv ‘Bay of Bengal’, and Cro. Jonsko moreand Sln. Jonsko morje ‘Ionian Sea’. However, only three examples of names have a single Croatian or Slovenian exonym form and these forms are obviously different from each other. These are Cro. Kopenhagen and Sln. Kodanj ‘Copenhagen’, Cro. Mleci, Mletciand Sln. Benetke, Benedke‘Venice’, and Cro. Becko Novo Mjesto and Sln. Dunajsko Novo mesto ‘Wiener Neustadt’. When comparing exonyms in the two languages, some characteristic differences were also found. In some cases, there is a difference between exonyms in the languages examined regarding the letters e and a (e.g., Cro. Bodansko jezero and Sln. Bodensko jezero ‘Lake Constance’) and when using the diphthongs au and av (e.g., Cro. Austria and Sln. Avstrija ‘Austria’). There is also a characteristic difference in the suf­fixes of some modern or historical countries and administrative units, with the Croatian suffix -ska and the Slovenian suffix -sko(e.g., Cro. Pruskaand Sln. Prusko‘Prussia’). Two more examplesofthe use of the SlovenianexonymsinsteadofGermanendonymsinCroatianformodernAustriaarenoteworthy:forVillach (Sln. Beljak) the Croatian exonym variants Belak, Beliak, and Beljak were used, and for Klagenfurt (Sln. Celovec) the Croatian exonym variants Celovac, Celovac, and Cjelovac. Some principles of exonym standardization were also seen in individual semantic types of geograph­ical names. The exonyms for seas and lakes in both languages are usually formed with the adjective endings-skoand-škoplusacommonnoun;forexample,Cro.ArapskomoreandSln.Arabskomorje‘Arabian Sea’,Cro.BodanskojezeroandSln.Bodenskojezero‘LakeConstance’,andSln.Atlanškomorje‘AtlanticOcean’. For adapting the names of European rivers from the German-speaking area, adding the suffix -a pre­vailed;thatis,convertingthenameintoafemininenoun(whichagreeswiththegenderofCro.rijeka‘river’ or Sln. reka ‘river’; for example, Cro./Sln. Rajna ‘Rhine’. The use of the name form Ren later dominated in Slovenian. The names of continents, many countries, and important or large towns gained exonyms in Croatian andSlovenianearlyon.Namesofcontinentswereadaptedtofacilitatepronunciation.Aninterestingexample is Cro. Europa ‘Europe’, which is cited in the oldest sources in this form (only Klaic uses the form Evropa, buthealsosometimesreplacesitwiththeformEuropa). AsimilarsituationisfoundinSlovenian,inwhich theuseisinconsistentintheoldestnewspapersources(bothEuropaandEvropa‘Europe’),buttheformEvropa laterbecameestablished.Namesofcountriesweremostoftennativizedbytheadditionofthesuffixes-s(z)ka inCroatianand-s(z)koinSlovenian,and-ijainbothlanguages;forexample,Cro.AustralijaandSln.Avstralia 600 500 400 300 200 100 0 482 250 232 161 45 44 52 30 22 Complete exonym corpus Exonyms identified in Croatian sources Exonyms identified in Slovenian sources Same topographic features identified as exonyms in both languages (see Table 1) Identical exonyms in both languages for all exonym variants Correspondence of at least one exonym variant in both languages Multiple exonym variants identified for a single topographic feature in Croatian Multiple exonym variants identified for a single topographic feature in Slovenian Multiple exonym variants identified in both languages Figure 3: Number of exonyms analyzed by individual sources and types. ‘Australia’,Cro.Francezka(laterFrancuska)andSln.Francija‘France’,andCro./Sln.Pers(z)ija‘Persia,Iran’. FortheCroatsandSlovenians,prominenttownsoftenalreadyhadtraditionalCroatianorSloveniannames. A comparison of the number of different exonyms for individual topographic features showed that therearefifteensuchcasesonlyinCroatian,nineteenonlyinSlovenian,andtwenty-twoinbothlanguages. This indicates rather inconsistent use of exonyms in the oldest sources. Unsystematicusecanalsobefoundwithinanindividualissueofanewspaper,whendifferentexonym formsappearforthesamegeographicalfeature.AgoodexampleisfoundintheCroatianliterarysupplement Daniczahorvatzka,slavonzkaydalmatinzkafrom1835,wherethefollowingformsarefoundfor‘Montenegro’: Cherna Gora, Czerna Gora, and Czerna gora (issue 19), Cerna Gora (issue 32), and Cernagora (issue 50). Comparing the exonyms identified in both languages, there are forty-four that appear in different forms in Croatian, and fifty-two in Slovenian. 4.2 Typology When comparing Croatian and Slovenian exonyms in the oldest sources, it was found that roughly four most frequent patterns of adapting a toponym (i.e., type of exonymization) appear: The first pattern is the translation of all or part of the endonym. For example, Cro. Belo/Bijelo more and Sln. Belo morje ‘White Sea’, Cro. Cerno/Crno more and Sln. Crno morje ‘Black Sea’, Cro./Sln. Nova Holandija ‘New Holland’, and Cro. Becko Novo Mjesto and Sln. Dunajsko Novo mesto ‘Wiener Neustadt’. ThesecondpatternistheadditionofSlavicsuffixes:Cro./Sln.-ija,Cro.-ska,-ška,-cka(inoldestsources -zka), and Sln. -sko, -ško, -žko; for example, Cro. Australija and Sln. Avstralija‘Australia’, Cro. Austrija and Sln.Avstrija‘Austria’,Cro.Moldavska‘Moldova’,Cro.Norveška‘Norway’,Cro.GerckaandSln.Grško‘Greece’, Cro. Francezka and Sln. Francosko ‘France’, and Cro. Englezka and Sln. Angležko ‘England’. Thethirdpatternisthesimplificationofpronunciationandtheomissionofspecialcharactersandlet­ters that do not exist in either Croatian or Slovenian; for example, Cro. Atina/Atena and Sln. Atene/Atine ‘Athens’, Cro. Bukarešt/Bukurešt and Sln. Bukreš ‘Bucharest’, Cro. Eufrat and Sln. Evfrat/Furat ‘Euphrates’, Cro./Sln.Gjur‘Gyor’,Cro./Sln.Olomuc‘Olomouc’,Cro./Sln.Pasov‘Passau’,andCro./Sln.Varšava‘Warsaw’. The fourth pattern is the use of old Croatian and Slovenian names, which can be described as »typi­cal« exonyms; for example, Cro. Bec/Beç and Sln. Dunaj/Dunej/Bec ‘Vienna’, Cro./Sln. Bruselj ‘Brussels’, Cro. Carigrad/Czarrigrad and Sln. Carjigrad/Konstantinopel/Zargrad ‘Istanbul’, Cro. Draždjani/Draždani and Sln. Draždane ‘Dresden’, Cro. Erdelj and Sln. Erdelj/Erdeljsko ‘Transylvania’, Cro./Sln. Jakin ‘Ancona’, Cro. Jedrene and Sln. Jadrene/Adrianopel/Drenopolje ‘Edirne’, Cro./Sln. Krf ‘Corfu’, Cro./Sln. Lipsko ‘Leipzig’, Cro. Mleci/Mletci and Sln. Benetke/Benedke ‘Venice’, Cro. Napulj/Napolj and Sln. Neapolj/Neapel ‘Naples’,Cro./Sln.Pad‘Po’,Cro.Pecuh/PecujandSln.Pecuh‘Pécs’,Cro.PragandSln.Praga‘Prague’,Cro./Sln. Rim ‘Rome’, Cro. Tiber and Sln. Tibera ‘Tiber’, and Cro./Sln. Trst ‘Trieste’. 4.3 Discussion Exonyms have been relatively well studied in central Europe (Hajciková and Kovácová 1997; Hornanský 2000;Jordan2000),buttherearedifferencesbetweenlanguages.Somelanguages(e.g.,FinnishandPolish) have a decades-long tradition of gazetteers with exonyms (e.g., Hakulinen and Paikkala 2012; Wolnicz­Pawlowska2013),whereasothershaveonlyindividualpartialstudies.Sloveniandoesnothavesuchalong tradition,butithasadictionaryorlistofexonymsinbothdigitalandbookform(Kladniketal.2013;Kladnik andPerko2013).Inaddition,Slovenianexonymsarealsoconsideredfromsomeotherpointsofview.Two separategazetteersofexonymshavealsobeenpublishedinCroatianinrecentyears(Crljenko2016;2018), but some aspects have not yet been addressed. All these works mostly focus on the current situation, and in neither language has there yet been a fundamental discussion of the beginnings of exonym standard­ization. This gap has been addressed with the bilateral project A Comparative Analysis of Croatian and Slovenian Exonyms, based on which several studies have been published (e.g., Kladnik et al. 2017). AcomparisonofthebeginningsofexonymstandardizationinCroatianandSlovenianconfirmssome basic assumptions about this process in both languages; however, some differences between the two lan­guagesarealsoapparent.Althoughsomeexonymsappearveryearly,inbothlanguagestheirnumberincreased considerablyinthesecondhalfofthenineteenthcentury.Namely,thiswasthetimeofnationalmovements, whichwereinitiallyalso(ormainly)assertedwithanationallanguage.Thiswasalsothetimeofthelarge­scalepress,especiallynewspapers,whichalsocarriednewsfromareaswhereforeignlanguageswerespoken. A key characteristic of the use of exonyms in this period is especially their lack of systematicity. Thereareseveralreasonsfortheunsystematicuseofexonyms.Themostimportantofthese,whichapplies to both languages, is the absence of orthographic manuals in the languages, which began to appear in the lastdecadeofthenineteenthcentury(in1892inCroatianand1899inSlovenian). Thedifferencebetween theSlovenianandCroatianorthographicmanualsisthattheSlovenianonecontainedrulesforwritingfor-eigngeographicalnamesassoonasitwaspublishedin1899,andtheCroatianoneonlyinitseditionpublished in 1904. An additional circumstance in Croatian is the existence of multiple standards at the same time. UpuntiltheIllyrianmovementinthefirsthalfofthenineteenthcentury,thenorthernCroatswroteusing anadaptedHungarianLatinscript,andthesouthernCroatsusedanadaptedItalianscript.Inaddition,some writers often changed their Latin script orthography from one occasion to another. The Croatian linguist Ljudevit Gaj, following the example of the Czech alphabet, created a Roman-alphabet system (known asgajica ‘the Gaj alphabet’), using a distinct set of letters. The Gaj alphabet also replaced the Bohoric alpha-betinSlovenian.However,theSlovenianGajalphabetissomewhatmodifiedand,incontrasttotheCroatian version,hasonlytwenty-fiveletters. Anotherdifferencebetweenthetwolanguagesortheirscriptsisasso­ciatedwith LjudevitGaj –that is,Illyrianism,whichdidnotwin asmuchsympathyamong theSlovenians asamongtheCroats.FortheSlovenians,thismeant,aboveall,adeparturefromtheGermanpoliticalframe-work, but in no way did they accept Štokavian dialect as the standard norm for all South Slavs. Aninteresting difference in the use of geographical names in both languages is also reflected in some Slovenian names in territory that lies outside Slovenia. For settlements near today’s Slovenian–Austrian border, the Croats used Slovenian-(based) forms (e.g., Beljak, Celovac)while they were in common coun­trieswiththeSlovenes–and,asdistancetothenorthincreases,thiskindofsharedusedecreases.Forexample, forthe highest Austrian peak,Mount Großglockner, the Croats use the German name (and in older usage also the form Gros Glokner), whereas in Slovenian the name Veliki Klek has become established. A shared characteristic is also the fact that some exonyms in both languages were taken from other languages, especially Slavic ones. Thelackofuniformityinbothlanguageswasalsocontributedtobythefactthatsomebasicgeographical andcartographic works were published before the first orthographic manuals, for example, textbooks (in 1823 in Croatian and 1865 in Slovenian) and atlases (in 1887 in Croatian and between 1869 and 1877 in Slovenian); among all publications, these certainly contain the most adapted foreign geographical names. Becausethespellingnormonwritingnameswasnotestablishedbeforethis,thelackofuniformityisreal­ly not surprising. Comparing the findings of this study with some other related studies in European languages (Pokoly 2006;GînsacandUngureanu2018;Moscal2018)revealssomesimilarities.Thetimewhenexonymsarose is similar in Romanian, around 1800, and in Hungarian the oldest systematic sources are from the begin-ningoftheeighteenthcentury(thenameBees‘Vienna’appearsasearlyas1356).Inclassifyingthesenames by their manner of adaptation, three types are roughly shown in related research: complete translation, partialtranslation,andadditionofsuffixes.Interestingly,atleastintheRomaniancase,thisdoesnotinvolve exonyms, but translated names. The use of exonyms was also inconsistent because in the same source an individual name may appear in different forms. The role of individual languages, which acted as media­tors in the adaption of some foreign geographical names, is also evident. Thisdiscussion,whichisbasedonalimitedamountofmaterial,partiallyfillstheresearchgapregard­ingthebeginningsoftheappearanceofexonymsintworelatedlanguages,CroatianandSlovenian.Anupdated corpus of names would clearly contribute to even better results. In the case of Croatian, the appearance of exonyms in the first atlases should be treated more systematically, and in Slovenian especially their use in newspapers. In thisway, individual typesofmaterial couldbe compared, not only the materialasawhole. 5 Conclusion The first exonyms in Croatian and Slovenian appeared in large numbers at the end of the eighteenth cen­tury with the first newspapers. Their number increased in the nineteenth century because the first orthographic manuals, atlases, and geographical textbooks containing foreign geographical names also appeared in the second half of the century. A comparison of the beginnings of exonym standardization in Croatian and Slovenian shows that the emergence of exonyms in both languages was mainly influenced by historical and political circumstances and the language policy of the time. A similar language, immediate proximity, and a partly common past fostered many similar and identical exonyms in both languages, and some differences are mainly due to spelling differences and some differences in grammatical rules. In the analysis of exonyms, four groups were highlighted: partly or entirely translated names, names with a Slavic suffix added, names with sim­plified writing based on pronunciation, and old or »typical« exonyms. ACKNOWLEDGEMENTS: The authors acknowledge financial support from the Croatian Ministry of Science, Education, and Sports and from the Slovenian Research Agency for funding the bilateral project A Comparative Analysis of Croatian and Slovenian Exonyms, and from the Slovenian Research Agency corefundingGeographyofSlovenia(P6-0101).SpecialthankstoIrenaOrelforsharingdataaboutSlovenian exonyms from old newspapers. 6 References Atlant 1868–1877. Ljubljana. Badurina, L. 2012: Hrvatski slovopis i pravopis u predstandardizacijskome razdoblju. Povijest hrvatskoga jezika / Književnost i kultura devedesetih, Zbornik radova 40. seminara Zagrebacke slavisticke škole. Zagreb. Bernetic,B.1990:ZemljepisnaimenaizVodnikovihLN.Diplomskodelo,UniverzavLjubljani,Filozofska fakulteta. Ljublajana. Bradaška, F. 1867: Sravnjivajuci zemljopis za više razrede srednjih ucionah. Zagreb.Bratec Mrvar, R. 2007: Blaž Kocen: Življenje in delo. Šentjur. 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(ed.) 2013: Urzedowy wykaz polskich nazw geograficznych swiata. Warszawa. COVID-19 IMPACT ON DAILY MOBILITY IN SLOVENIA Tadej Brezina, Jernej Tiran, Matej Ogrin, Barbara Laa Bus stop Dovje-Mojstrana. DOI: https://doi.org/10.3986/AGS.9390 UDC: 913:331.556:616-036.22(497.4) COBISS: 1.01 Tadej Brezina,1 Jernej Tiran,2 Matej Ogrin,3 Barbara Laa1 COVID-19 impact on daily mobility in Slovenia The Slovenian subsample (n=415) of an international online survey about changes in daily mobility dur­ingtheCOVID-19outbreakinthespringof2020wasanalysedfroma geographicalperspective.Thedataset was split into three spatial classes (urban, transitional and rural) according to the respondents’ place of residence. People’s behaviour before and during the COVID-19 lockdown was compared and analysed in terms of commuting frequency, changes in mode choice for commuting and style of grocery shopping. The results show that commuting was reduced drastically during the lockdown while the car remained the main transportmode both for commuting and shopping, especially in rural areas. The study provides an unprecedented insight in travel behaviour changes due to the pandemic and congruously argues for improved transport policies to meet climate change and public health challenges. KEY WORDS: travel behaviour, modal share, level of urbanization, lockdown, pandemic, Slovenia Vpliv epidemije covida-19 na dnevno mobilnost v Sloveniji POVZETEK: Z geografskega vidika smo analizirali slovenski podvzorec (n=415) mednarodne anketne raziskave o spremembah dnevne mobilnosti, ki je bila izvedena med prvim valom epidemije covida-19 spomladi2020.Podatkovnobazosmonajprejrazdelilivtriskupinegledenakrajbivanjaanketirancev(urbani, prehodniinruralni),natopaprimerjalimobilnostljudipredinmedzaprtjemdržaveterjoanaliziralizvidi­kapogostnostipotinadelo,izboranacinapotovanjainnakupovalnihnavad.Ugotovilismo,dasobilapotovanja nadelomedzaprtjemdržaveizrazitookrnjena,pritempajeosebniavtomobiltakozapotnadelokotnakupo­vanjeostalprevladujocpotovalninacin,zlastinapodeželju.Raziskavanudiedinstvenvpogledvspremembe potovalnihnavadmedepidemijoinpodkrepljujepotrebopoboljtrajnostnihprometnihpolitikahzaomilitev podnebne krize in izboljšanje javnega zdravja. KLJUCNE BESEDE: potovalne navade, modalni delež, stopnja urbanizacije, zaprtje države, pandemija, Slovenija The article was submitted for publication on January 6th, 2021. Uredništvo je prejelo prispevek 6. januarja 2021. 1 Vienna University of Technology, Institute of Transportation, Research Center of Transport Planning and Traffic Engineering; Vienna, Austria tadej.brezina@tuwien.ac.at (https://orcid.org/0000-0003-4865-9472); barbara.laa@tuwien.ac.at (https://orcid.org/0000-0001-5053-2097) 2 Research Centre of the Slovenian Academy of Sciences and Arts, Anton Melik Geographical Institute; Ljubljana, Slovenia jernej.tiran@zrc-sazu.si (https://orcid.org/0000-0001-9839-720X) 3 University of Ljubljana, Faculty of Arts, Department of Geography; Ljubljana, Slovenia matej.ogrin@ff.uni-lj.si (https://orcid.org/0000-0002-4742-3890) 1 Introduction TheCOVID-19pandemichasbeenaffectingtheWorldinanunprecedentedmanner.WhentheSARS-CoV-2 virusspreadinEuropeinearlyspringof2020,adiversityofreactions–frompharmaceuticaltonon-phar­maceutical–ensued.Amongthenon-pharmaceuticalinterventions(NPI)enactedbynationaland/orregional authorities were measures to reduce virus transmission by restricting socializing and public life and lim­iting human movement (Flaxman et al. 2020) – also called lockdown. TheSARS-CoV-2viruswasalsodetectedinSlovenia.InthefirsthalfofMarch2020,thespreadofinfec­tions accelerated and on March 12th, the Government of the Republic of Slovenia declared an epidemic (Odredbaorazglasitvi…2020).Interventionsfollowedquickly:onMarch16th,gatheringofpeopleinedu­cationalinstitutionswasprohibitedandtheprohibitionofpublictransportwasissuedaswell.Inaddition, all restaurants and many shops were closed. On March 30th, any movement outside municipalities of resi­dence was also prohibited (with certain exceptions). The total lockdown of public life and many activities lasted about a month, as the first measures to lift the lockdown took effect on April 17th (Odlok o zacasni prepovediinomejitvah…2020;Odlokospremembi…2020;Odlokozacasniprepovedi,omejitvah…2020). WhilemanyEUcountriesintroducedrestrictionsonpublictransport(Internet1;Internet2;Internet3),Slovenia wasoneoftheveryfewcountriesthatdecidedtoshut-downpublictransportcompletely.Internationalroad andrail-boundpublictransport was reinstatedonJune 13th (Odloko nacinuizvajanja…2020). With such anapproachtofightingtheepidemic,somesourcesciteSloveniarankedhighamongcountriesonthestrin­gencyindexinthefirstwave(Hale et al. 2020),whileothers(Hans et al.2020)citeingenerallessstringent measures. The same study (Hans et al. 2020) argues that around April 1st 2020 Slovenia’s measures during lockdownwereamongthemoststringentinEU,howeverthisphaselastedlessthanamonth.Therefore,the generalassessmentisthatSloveniafacedmediumexposuretopotentialnegativeimpactofCOVID-19lock­down, a medium sensitivity in the eastern and central parts and a low sensitivity in the western part of the country(Hansetal.2020).ThismakesSloveniainterestingforresearchonpotentialconsequencesofCOVID­19 on human behaviour such as mobility. After the first COVID-19 wave, many scholars evaluated the worldwide effect of lockdown on human mobility. While some research collectives fathomed the global impact by interviewing transport scholars and professionals (Zhang and Hayashi 2020), other scholars conducted surveys of mobility changes due to COVID-19 for different countries. A team of researchers from TUWien –with the aid ofinternational colleagues – designed, translated, launchedanddistributedanonlinequestionnairein21languagestostudytheimpactofthevariousinten­sities of NPI measures on people’s daily mobility patterns. An analysis of the obtained international data focusesonthecommonalitiesanddiscrepanciesincommutingbehaviourforasubsampleoffourteencoun­tries (Shibayama et al. 2021). As Austrians were the most represented participants in this survey, country-specific results were highlighted particularly by Brezina et al. (2020b). Their findings show sub­stantialchangesintransportdemandandingeneraladrasticdecreaseoftransportvolumesduringlockdown. A major branch of research focused on analysing traffic flows and all reported significant decrease. Onesuchanalysis(Internet4)showsthatcongestionlevelsinmanycitiesdroppedto10%duringthelock­down,whereastheynormallyreacharound30–60%.InChina,duringtheSpringFestivalrushfromJanuary 10th toFebruary 13th,commercial passengertrafficfell by 46.6%andrail,road,waterway andcivil airtraf­ficfellby50.3%comparedtothesameperiodofthepreviousyear(Zhou,WangandHuscroft2020).InJapan, forexamplethemajorTokaidoShinkansenlinereporteda59%dropinpassengernumbersinMarch.Astudy by Zhang (2020) estimates that between January and March 2020, Japanese domestic intercity rail travel declinedby30%.InIndia,afterthenationwidelockdownonMarch25th,asimilardecreaseofdailymobil­itywasdetectedwithonlyaslowrecovery(Dandapat et al.2020).InSweden,forthreeregions(Stockholm, VästraGötalandandSkane)thenumberofdailytripsfromMarch1st toApril1st decreasedbyabout40–60% relativetothesameperiodin2019(JeneliusandCebecauer2020).InthecityofSantander,Spain,Aloi et al. (2020) report significant decrease in public transport and reduction of transport related emissions of pol­lutants, with emissions of NO2 reduced by 60%. Arellana, Márquez and Cantillo (2020) made an analysis ofofficialandsecondarydataoftransportsystemsinsevenurbanareaswithinColombia.Inthefirstthree monthsofthepandemic,freight transportwasthemost resilient transport component. AGerman survey studied the effects on the travel behaviour by means of an online survey while distinguishing areas with different levels of lockdown intensity. Results reveal a shift away from public transport and increases in car usage, walking and cycling (Anke et al. 2021). Fromthegeographicalperspective,alsostudiesonmodellingtheinfluenceofmobilityonthespreadof SARS-CoV-2shouldbenoted,forexamplebyChangetal.(2021).WhilemanystudiesfocusedonCOVID-19 impactduringthepandemic,somearealreadytryingtoforeseehowcitieswillchangeinordertolivewith a permanent COVID-19 threat (Florida, Rodriguez-Pose and Storper 2020). Slovenia represents a good example of polycentric urban development (Nared et al. 2017) and is one of the European countries with the most dispersed settlement system. According to the degree of urban­ization (DEGURBA) classification, 44.5% of people are living in thinly populated areas, also classified as »rural« (Local Administrative Units 2021). Trends in daily mobility in recent decades have been associ­atedwithanincreaseininter-regionaltrafficflowstowardsmajorcentres,aweakeningofpublictransport and an increase in car-dependent mobility patterns (Bole 2004; 2011). Travel behaviour changes among the youth show a similar trend: between 1991 and 2016 in primary schools in Novo mesto, the share of pupils who come to school by car increased from 4 to 53% (Plevnik, Balant and Mladenovic 2017). However, only few studies have been conducted on the impact of the COVID-19 pandemic on trav-elbehaviourinSloveniasofar.AsurveybytheSlovenianCarAssociation(AMZS)questionedalmost500 peopleaboutthechangeoftheirmobilityhabits,indicatingsomesubstantialchanges(Poženel2020).While thesurveyoftheEuropeanConsumerOrganizationshowsthatoccasionalworkathomeinSloveniaincreased from27to63%ofthepopulationduringthelockdowncomparedtobeforelockdown,56%ofrespondents were still occasionally working from home in October 2020 (Okorn 2020). Some»pre-COVID-19«mobilitystudiestookspatialdifferencesintransportbehaviourintoconsidera­tion,suchasbetweenruralandurbanareas.Ingeneral,themobilityoftheurban-ruralcontinuumischaracterizedbythefactthatasruralityincreases,theprivatecargainsinvalueandpublictransportloses(PucherandRenne 2005; Bouwman and Voogd 2005). Studies from theNetherlandshave also shown that the number ofshort distance trips in rural areas decreases and the number of medium distance trips increases (Bouwman and Voogd2005).Connectionsbetweenmobilitypatternandlifestyleacrosstheurban-ruralcontinuumwerealso studied in Slovenia by Drozg (2012). Inhabitants of towns and suburbs were found to be more mobile than ruraldwellers,whilethelatterusuallytraveloverlongerdistances.Hisstudyconfirmsthegapbetweenurban­ization of inhabitants (urbanwayof life) andurbanization ofspace (accessibilityof urban activities). OurreviewofexistingresearchandliteratureshowsthatageographicapproachtostudyingtheimpactoftheCOVID-19epidemicondailymobilityhasnotbeenusedyet.ThusthispaperexaminestheSlovenian subsample of the openly available dataset »International survey on COVID-19 lockdowns and mobility behaviour«(Brezina et al.2020a)fromageographicallydifferentiatedviewpoint.Previousanalysisofthis available dataset has examined differences and commonalities between 14 countries, Slovenia included, but did not specify geographic differences (Shibayama et al. 2021). Their research also indicates that the Sloveniansubsampleappearswellsuitedforadetailedgeographicalanalysis,asitshowsthebestbalanced distributionbetweenurbanandrurallocations.ApartfromSlovenia,countriesshowpredominantlyurban respondent locations. In this paper, we analyse the replies of respondents from Slovenia, distinguishingby their residential location along the urban-rural continuum. Here we study the changes in daily travel behaviour of the subsample for work commuters and for grocery shopping due to NPIs during the first wave of the COVID-19 pandemic compared to the pre-pandemic period. These types of trips were the only ones allowed during the lockdown, except for emergency trips. 2 Methods and data 2.1 Questionnaire We utilise the openly accessible dataset of an international online survey in 21 languages on changes in everydaymobility,carriedoutduringtheCOVID-19outbreakinspringof2020(Brezina et al.2020a).The online questionnaire was available with its first language versions from March 24th until May 12th, 2020. TheSloveneversionwasavailablefromMarch25th on.Intotal,thedatasetcontainsmorethan11,000respons­esfromover100countries.Thequestionnaireisreported(Shibayama et al.2021)tohavebeendistributed with the snowball method using email and social media and comprised of 33 total questions with pre­dominantly closed-ended questions. Replies included the option »other« to specify a divergent answer. The survey gathered information from respondents on: • the specifics of workplace; • the specifics of place of education; • the specifics of grocery shopping; • thetransportmeans,durationandfrequencyoftripsforthesepurposesbeforeandduringtheCOVID-19 triggered lockdown; • the way of and motivation for changing one’s behaviour; • and the COVID-19 triggered changes in child-care. Inadditiontoageclass,gender,educationandoccupation,householdtypeandcountryofliving,thepost­codewasalsoaskedtoidentifythelocationoftherespondents.Weusethepostcodeforspatialclassification ofresponses.Themetadataofthedatasetgivesdetailsonquestionsandansweringoptions(Brezinaetal.2020a). 2.2 Sample The Slovenian subsample encompasses 415 total replies of which 244 stated to be female, 167 to be male and4peoplechosediverseorleftitunanswered.Asforthegenderandageclassoftherespondents,Table 1 shows the age distribution of the sample. Table 1: Age distribution of the survey participants. Sample (n=411) Age class Male [%] Female [%] 0–18 0.5 0.5 19–29 4.1 11.2 30–39 11.7 18.0 40–49 11.9 18.0 50–59 6.1 8.3 60–69 5.1 2.4 70 or older 1.2 1.0 Total 40.5 59.2 Outof415totalparticipants,337(307+20+10inFigure1)statedtobeofworkingoccupation.Table 2 gives the number of participants answering to questions being relevant in the course of this analysis. Table 2: Subsample sizes. Subsample n Reference to Working occupation 337 Figure 1 Commuting before lockdown 290 Figure 2 Commuting under lockdown 310 Figure 3 Work commute 289 Figure 4 Grocery shopping 351 Figure 5 Workplace type 313 Figure 6 Grocery shopping style before lockdown 387 Figure 7 Grocery shopping style under lockdown 384 Figure 8 As for the respondents’ occupational status, 74% were employees, 7.5% were retired, 6.8% were stu­dents (working and non-working) and 4.8% were self-employed (see Figure 1). Therefore, occupational status deviates from the national distribution as persons in employment, which account for around 43% of the national population, are overrepresented in the sample on the account of other population groups (Cuk 2020; Razpotnik 2020). 100 Share (%) 90 80 70 60 50 40 30 20 10 0 307 31 20 19 18 10 4 3 2 n = 415 1 Employee Pensioner/retired Self employed – Student, notworking Unemployed Student, working School (12. level)Volunteering, CivilService/MilitaryNo answer Trainee Figure 1: Share of survey respondents by occupation with absolute respondent number over each column. 2.3 Spatial classification The geographic classification for Slovenia regarding the level of urbanization is also available at the set­tlementlevel(n=5,994)andconsistsofsixtypes:S1=city/town,S2=suburbanizedsettlement,S3=urbanized settlement, S4=strongly urbanized rural settlement, S5=urbanized rural settlement and S6=rural set-tlement(Ravbar1997;Cigale2005).Asindividualsurveydatarecordswereavailableonthenationalpostal district level, the data from the survey (available with much smaller granularity) needed to be aggregated toahigherlevel.Forthistaskweappliedthefollowingcriteriafordeterminingthreepostcodetypesalong the urban-rural continuum: 1. Urban area – predominant share (minimum 50%) of urban population (type S1) AND 75% of popu­lation together with suburbs (types S1+S2) AND maximum 10% of rural population (types S5+S6). 2. Transitional area – mixed, urban-rural area; does not meet the criteria either for urban or rural areas. 3. Ruralarea–aminimumof50%ofthepopulationlivesinruralorurbanizedruralsettlements(typeS5+S6). AsthetypeS1intheoriginalclassificationofsettlementswasbasedontheoutdatedlistoftownsfrom1981, weslightlyrevised it andidentifiedcitiesand townsaccordingtothe classification oftheSlovenian statistical office’s (SURS) criteria numbers one (= 3,000 inhabitants) and four (suburban settlements, graduallyspa­tiallyandfunctionallyintegratedwithanurbansettlementwith5,000inhabitantsormore)(Pavlinetal.2004). Theresultsshowthat268respondentsarelocatedindistrictsdefinedasurban(64.6%),92intransitional (22.2%)and35inrural(8.4%),while20participants(4.8%)providednon-assignablepostcodedata(Table3). Participants from a total of 110 postal districts (out of 466) have been recorded. The distribution along the rural-urbancontinuumisthereforeslightlybiasedwithoverrepresentedurbandwellers(around50%ofthe Slovenepopulationlivesinurbanareas)and underrepresentedruraldwellers(theiractualshareinthenation­al population is around 25%). The share of respondents in transitional areas is comparable to the national average (Cigale 2005). Figure 2shows the distribution of participants by postcode types over Slovenia. Postcode types Sample size Sample share [%] Urban 268 64.6 Transitional 92 22.2 Rural 35 8.4 None 20 4.8 Total 415 100.0 3 Results ThegeographicaldistinctionofcommutingfrequencybeforeCOVID-19lockdown(Figure3)showsaclear picture, as 81% (transitional) to 92% (rural) of the respondents were commuting five days a week. Under COVID-19 lockdown, the situation changed drastically (Figure 4): around half report that they were not commuting,butwereunderamandatoryhomeofficeregime.Whenaddingthosepersonswhoseworkwas closed(rural3.4%tourban10.0%)andthosewhoworkedathomevoluntarily(rural6.9%tourban13.9%), no actual commuting was taking place for a portion of between 62.1% (rural) and 72.2% (urban) of the sample. Only around 10% of respondents commuted the same number of times. Figure5showsthemodechoiceforworkcommute(leftcolumn)andforgroceryshopping(rightcolumn) in Sankey (flow) diagrams. The left hand side of each diagram shows the mode choice before COVID-19 lockdown and the right hand side during lockdown. Urban (n =209) Transitional (n =72) Rural (n = 2 )9 Figure 4: How commuting behaviour changed under COVID-19 lockdown in comparison to before. 98 Share %) ( 60 50 40 30 20 10 0 Urban (n = 197) Transitional (n = 67) Rural (n = 26) Figure 3: Commuting frequency distribution before COVID-19 lockdown. 100 90 80 70 Share (%) No answer Yes, moreoften Yes, the ame s number of times Yes, at other times Yes, butless often No, workclosedOnce/weekor less Twice/week 3 days/week 4 days/week 5 days/week No, voluntary home office No, mandatoryhome office No, taken offto care for others 6 days/week 7 days/week No, as usual 100 90 80 70 60 50 40 30 20 10 0 Figure 5: Sankey diagram matrix of changes in commuting mode choice before (left hand side) and during lockdown (right hand side) for workers (left column)andchangesinmodechoiceforgroceryshopping(right column)according to thespatialclassification urban(top row),transitional(centrerow) and rural (bottom row). Thereareobviousdifferencesinthemodechoiceresultsofthesurveyforcommutingbetweenthespa­tialclassesbeforetheCOVID-19lockdown.Inurbanareas,weseehighersharesinactivemodes(walking and cycling) and lower levels of private car use than in transitional ones. Especially in rural areas with no shareof active modes at all, a very high car share of 96.2% is evident. With 9.0%, the shareof public trans­port was higher in transitional and urban areas (8.2%) than in rural areas (3.8%). During the COVID-19 lockdown, the percentage of people who were not commuting for work was quite similar in all three areas. Between 59.7% (transitional areas) and 62.8% (urban areas) were in home officeand7.7%(ruralareas)to11.9%(transitionalareas)werenotworking.Aspublictransportwasceased nationwide, its share dropped to zero in all areas. The total shut-down of public transport did not signif­icantlyincreasecartrafficastheshareofpublictransportuserswasalreadylowbefore,whileitsusersmostly workedfromhome.Inurbanareastherewasstillaconsiderableshareofactivemodesincommutingdur­ing lockdown with 2.6% of walking and 7.7% of cycling, while in transitional areas only 1.5% walked or cycledtoworkandevennobodyinruralareas.There,carsweretheonlytransportmodeusedbythecom­muters. A similar pattern can be seen for the grocery shopping mode choice. However, before the COVID-19 lockdown,carusewasmoreprevalentinurbanareasforshoppingthanforcommutingcomparedtotran­sitional and rural areas, where it was high for both purposes. During lockdown, the modal share of cars forshoppingincreasedinallthreespatialclasses.Thecessationofpublictransportdidnotaffectthemodal share as public transport use for shopping before the lockdown was extremely rare. In contrast to work commuting,thedominanceofthecarforshoppingpurposespersisted,whileforworkcommutingthecar’s shareshrunkinurbanareas.Forruralareasonecaneasilystatethatthecarisbasicallytheonlycommuting mode. ThequestionnairealsosurveyedawidevarietyofmainworkplacetypesbeforeCOVID-19(Figure 6). In our sample, a clear trend is visible with the changing perspective from urban to rural settings: ‘Office’ workplaces decrease from almost 55% to almost 38%, while simultaneously ‘Classrooms / lecture hall / stage’ increase from 11% to almost 35%. Workplacetypesdifferintheirsuitabilityforswitchingtoworkingfromhome.Wedifferentiatebetween ‘homeofficepossible’,‘presenceessential’and‘undetermined’.Forthiscategorization,wedefineworkplace types‘Home’,‘Office’and‘Classroom/lecturehall/stage’tobe‘homeofficepossible’andworkplacetypes ‘Mobile(customervisits)’,‘Customertraffic’,‘Hospital,nursinghome’and‘Atcustomersite(e.g.construction site)’ to be ‘presence essential’. ‘Customer traffic’ denotes working places with stationary customer con­tact, while service-oriented visits to customers are named ‘At customer site’. Results are shown in Table 5. Twotrendssurface:‘homeofficepossible’increasesbyagood10percent-pointswhenswitchingfromurban (72.6%)torural(82.8%)settings,while‘presenceessential’decreasesfrom17.5%(urban)to13.8%(rural). The workplace types that we consider as ‘undetermined’ decrease from 9.9% to 3.4% with reduced spa­tial density. When it comes to the style of grocery shopping before COVID-19 lockdown (Figure 7), the distinc­tion that urban people tend to shop for groceries more often than rural dwellers is notable, as 38.5% of urban respondents do it many times per week, which is 5.5 percentage-points more than for transitional and 9.1 percentage-points more than for rural respondents. Interestingly, twice as many people let others do the shopping in rural areas than they do in urban or transitional ones. COVID-19relatedmobilitychangescouldbeexplainedbychangedgroceryshoppingbehaviourdur­ing lockdown, depicted in Figure 8. Irrespective of spatial classification, a combined share of 50 to 60% of responses report buying ‘larger quantities at once’ (18.6 to 21.8%), buying ‘long-lasting products’ (8.1 to 11.5%) and ‘shopping less often’ (29.3 to 30.8%). In urban settings 12% of respondents report to ‘eat out less often’, while in rural settings 10.3% go to ‘stores nearby’. Table 4: Share of workplace types in subsample by spatial classification and distinction between ‘home office possible’ and ‘presence essential’. Shares [%] Home office possible Presence essential Undetermined Urban 72.6 17.5 9.9 Transitional 80.6 15.3 4.2 Rural 82.8 13.8 3.4 Share %) ( 100 90 19. 42. 19. 14. 09. 56. 14. 14. 14. 34. 10.3 83. 80 137. 70 11.3 194. 34.5 60 50 40 30 547. 542. 379. 20 10 66. 69. 103. 0 33. 14. 34. Urban (n = 212) Transitional (n = 72) Rural (n = 29) Hospital, nursing home Civil protection facility Production, warehouse Outdoors (e.g. field) At Customer Site (e.g. construction site) Mobile (customer visits) Customer traffic Classroom / lecture hall / stage Office No answer Home Figure 6: Workplace type before COVID-19 lockdown by spatial classification. 100 34. 44. 88. 90 80 70 53 1 . 58 2. 60 Share %) ( 58.8 50 40 30 20 38.5 33 0. 29 4. 10 0 Urban (n = 262) Transitional (n = 91) Rural (n = 34) None of these Someone else does Most meals delivered Mostly eat out Ad hoc delivery– 1 2 times/week– Many times/week Figure 7: Style of grocery shopping before COVID-19 lockdown by spatial classification. 4 Discussion The changes in travel behaviour during the COVID-19 lockdown (comprising of limitations for travel-ling,closedservicesandworkplacesetc.)canbeviewedasasocialresponsetothethreatofvirustransmission. On one hand, the mobility in Slovenia was reduced due to quite stringent measures, and a large propor­tion of people working from home and going shopping less often, which is similar to other parts of the world (Aloi et al. 2020; Jenelius and Cebecauer 2020; Dandapat et al. 2020). On the other hand, the pri­vatecarevenreinforceditsstatusasthemajortransportmode.However,therearesomeimportantdifferences alongtheurban-ruralnexus.Slovenianruralareasareverydependentoncarmobilityandinthelastdecades, cardependencyhasevenreinforced(BoleandGabrovec2012).Whileworkcommutersshowaverystrong affinity with private cars in transitional and rural areas pre-lockdown as well as during lockdown, the pic­ture looks more diverse in urban settings. There, car-dependency is not as pronounced and is balanced by walking, cycling and the use of public transport. The higher share of non-car users in urban areas in pre-lockdown can be explained with better service of public transport, especially in bigger urban areas (OgrinandDovecar2014)andwithshorterdistancesofdailytrips.Whilemorethan30%ofurbandwellers still use alternatives to cars for grocery shopping, in transitional and rural areas, the travel behaviour for shopping, as well as for commuting is distinctively dominated by car use. Very few alternatives are used and the situation did not improve during the lockdown. These findings confirm a notion that built envi­ronmentinfluencesthetravelbehaviourandfrequencythroughpromotingsustainabletravelmodes(Jiao, Vernez Moudon and Drewnowski 2011; 2016). ThesurveyofAMZS(Poženel2020)ontravelbehaviourchangesinSloveniaduetothelockdownshows somehow different results: only 24% used the car about the same, while about 69% of respondents used thecarless,and3%usedthecarmorethanpriortothepandemic.Theshareofbicycleandwalkingincreased: 18% used the bicycle more often, 31% used it the same and 15% used it less, while 31% walked more, 53% walked the same and only 8% walked less. Their findings are not strictly in line with ours, as trips were notseparatedbytrippurposeandBrezina et al.(2020a)didnotexplicitlyaskforfrequencychanges.AMZS’ survey as well as our inquiry suggest that shopping behaviour changed by shifting from higher frequen­cies and smaller quantities to lower frequencies and higher quantities – and did so by increasingly using cars for this purpose. Incontrasttopreviousrecent(Shibayama et al.2021)research,basedonthesurvey’scompletedataset, we also studied the spatial distribution of workplace types. The respondents who can work from home haveahighshareinoursampleirrespectiveofthespatialsetting.Regardingchangesinlockdown-induced commuting, the scene is set with 82.8% of jobs in rural areas being ‘home office possible’ and 62.1% of respondents reporting no commute. On the urban end of the spectrum, 72.6% reported to have ‘home office possible’ jobs and 72.2% had no commute. While in the urban surrounding possibilities and actu­al behaviour almost coincided, the rural settings saw a discrepancy of about 20 percentage-points. The location of ‘presence essential’ workplaces in relation to dwelling areas appears to be a crucial perspective in terms of crisis resilient and environmentally friendly transport supplies. With 17.5% the share of such workplaceswashighestinurbansettingsinourcase.Ingeneral,wesuggestthatthecloser‘presenceessen­tial’ workplaces are located to dwellings (preferably of their workers), the more attractive it will appear to workers to choose walking and/or cycling as a transport mode for commuting. However, this cannot be always the case due to recent trends of decentralized spatial development (Rebernik 2010), current model ofthereimbursement of travel expenses, which favours long-distance commuting by car (Gabrovec et al. 2021), and the lack of infrastructure for sustainable mobility due to allocating funds mostly to road infra­structure in the past (Bole and Gabrovec 2012). In both cases, safe and attractive infrastructures for public transport and active mobility need to be provided.Consequentially,fromaplanningperspective,theprovisionofsuchinfrastructuresthusnotonly asks to be appraised from an ecological perspective but also from the viewpoint of providing resilience in a major health crisis – as was shown by research on pop-up infrastructures (Kraus and Koch 2021). The lack of public transport use due to measures taken by the government is apparent in all settings and was reflected also in its lower usage after the first wave was over (Campa et al. 2020). As suggested before, this sector had a remarkable position: Even though its services were cut down by the government, nonoteworthyprotestsfromthepublicopposedthismove.Thereasonsforthatappeartoberootedinthe ongoingdecliningrelevanceofpublictransportanditslowusage(GabrovecandBole2009;Halilovic et al. 2020). On first sight, additional reduction of passengers in public transport may lead to an increase in the level of service (ceteris paribus): less crowded vehicles offer more comfort, are more COVID-safe and are expected to run more punctually. But on a systemic level, this passenger reduction has led (and may also do so in the future) to a decrease in cost-recovery rates for un-/tendered public transport services on state andcity levels. Other research suggests that urban transport as one of the crucial urban systems will need tointroducepandemic-proofinfrastructureandtransportmanagement(touchlesssolutions,capacitymon­itoring, floor markings,…) (Florida, Rodriguez-Pose and Storper 2020). Replacement of public transport for individual motorised mobility to avoid COVID-19 disease is not an option. Not onlywould air quality deteriorate in many urban areas and have a negative impact on pub­lichealth,thegrowthoftrafficinurbanareaswouldincreasethetrafficloadsonroadinfrastructures,leading toarapidincreaseincongestionandadeteriorationinaccessibility.StudiesfromSlovenia’scapitalLjubljana confirmed poor air quality in major city roads within the period 2005 to 2013 (Ogrin and Vintar Mally 2013; Vintar Mally and Ogrin 2015). Since then, some streets in the centre of Ljubljana have been closed to motorized individual traffic and remained open to public transport, and air quality in these areas has improved. A return of individual traffic in the city centre would do much more harm than good. But the regional challenges for substantial shifts from non-sustainable to sustainable modes remain persistent in a policy culture that on the one hand eases all matters car and on the other highlights alleged difficulties in providing better public transport (Brezina and Lokar 2020). Thestudyalsohascertainmethodologicallimitations.Asthedatawascollectedwithanonlinesurvey, non-probability sampling was used. Even though the sample is not representative of the total population, weinsinuatethatthesnowballmethodofsurveyengagementprovedfunctionalforquicklyharvestingsocial reactions under a rapidly evolving situation at least among employees, which were the most represented populationgroupinthesample.Wealsofoundthesampletobenottoospatiallybiased,althoughtherural dwellers were a bit underrepresented. One might also question the accuracy of determining the location of the respondents as it was only available at the postal district level and not at a lowerspatialscale, which may be more appropriate for a country with such a disperse settlement system. We are aware that classi­fying respondents along the urban-rural spectrum may lead to certain generalizations and errors. Onmattersofshortcomings,weneedtoadmitthatsimilartochangesinmodesandcommutingdura­tion, an inquiry of commuting distances would have deemed promising. Commuting distance was asked in the survey, but unfortunately the subsample of valid responses was too small (n=8 altogether for all three spatial classes) for useful evaluation. 5 Conclusion InourresearchweaddresstheCOVID-19pandemicandthecorrespondingmobilityresponsesinSlovenia fromageographicperspective.Emanatingfromaworldwidesurvey,westudythechangesineverydaytrav-elbehaviourwithfocusonworkingcommutersandgroceryshoppingoftheSlovenesubsample,forwhich we differentiate responses by three spatial classes: urban, transitional and rural. Depicting the changes in travelbehaviourfromregulartolockdownshowsthepersistingandevenincreasingdominanceofthecar for shopping purposes, while for work commuting the car’s share shrunk due to a high portion of people workingfromhome.Takingintoaccountthespatialperspective,ourstudyconfirmedthenotionthatrural areas remain very car-oriented, while modal share of the urban dwellers is more diverse. Ourresultsposeachallengingpictureforthelong-termfuturewhichrequeststransportpolicytoswitch shares of trips from non-sustainable to sustainable modes. Such transport policy does not only need to implement measures which are effective from a sustainability perspective, but – as we may have learned from the COVID-19 pandemic – needs to meet these demands under public health requirements. Congruously, this also opens avenues for future research on the design and implementation of trans­ portpoliciesthatwillenablepeopletomovesustainablyandinapandemicdampeningwayinlessdensely populated areas – not only in Slovenia but in all European countries. ACKNOWLEDGMENTS:Wethankthereviewersfortheirvaluablecommentsthathelpedtofinalizethepaper. We thank Takeru Shibayama, Fabian Sandholzer, Melissa Kapfenberger, Ulrich Leth, Helmut Lemmerer and Günter Emberger who co-designed and co-implemented the survey. We thank Miha Lokar for the translation of the initial survey into Slovene language. We thank many colleagues who helped in distrib­uting the survey among their peers. The authors also acknowledge receiving financial support from the Slovenian Research Agency, research core funding Geography of Slovenia (P6-0101). CONTRIBUTIONS:Conceptualizationofresearch:T.B.,J. T.,M. O.;geographicalanalysis:J. T.;dataanaly-sis:T. B., B. L.; literature review: M. O.; paper writing: T. B., J.T., M. 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Internet: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3679662 (23. 7. 2021). DOI: https://doi.org/10.2139/ssrn.3679662 HOW THE STATE LEGITIMIZES NATIONAL DEVELOPMENT PROJECTS: THE THIRD DEVELOPMENT AXIS CASE STUDY, SLOVENIA Maruša Goluža, Maruška Šubic-Kovac, Drago Kos, David Bole Public participation in a decision-making processes. DOI: https://doi.org/10.3986/AGS.9572 UDC: 711.122:711.7(497.4) COBISS: 1.01 Maruša Goluža1, Maruška Šubic-Kovac2, Drago Kos3, David Bole1 How the state legitimizes national development projects: The Third Development Axis case study, Slovenia ABSTRACT: We analyzed planning mechanisms and evaluated their performance in achieving legitima­cy in infrastructure planning in Slovenia. Planning mechanisms were divided according to the concept of input, throughput and output legitimacy. We conducted a document analysis and interviews to assess theireffectivenessinachievinglegitimatedecisions.Althoughtheanalyzeddecision-makingprocessdeclar­atively promoted democratic principles, themechanisms failed to satisfactorily enhance the legitimacy of decisions. The study revealed inadequate communication approaches, both in the decision-makers’ rela­tionship with the public and within the expert discourse. Accordingly, the study argues for more genuine communicationwiththepublicandwithinacademiatoaddresslegitimacychallengesinincreasinglycon­flictual decision-making processes. KEY WORDS: deliberative governance, post-political spatial planning, qualitative research, citizen par­ticipation, transportation planning Kako država legitimira nacionalne razvojne projekte: primer tretje razvojne osi, Slovenija POVZETEK: V prispevku smo analizirali postopek nacrtovanja infrastrukturnega projekta v Sloveniji in ocenili uspešnost uporabljenih pristopov za doseganje legitimnosti odlocitev. Pristopi k nacrtovanju so bili razdeljeni v tri sklope, glede na uveljavljen koncept vhodne, postopkovne in izhodne legitimnosti. Legitimnostuporabljenihprostorsko-nacrtovalskihpristopovsmougotavljalispomocjokvalitativnihmetod, natancnejezanalizodokumentovinintervjuji.Raziskavajepokazala,dajenajvecjilegitimacijskiprimanjkljaj na podrocju komunikacije, ne le med odlocevalci in javnostjo temvec tudi med posameznimi strokami. Iz tega sledi, da bi morali za vecjo družbeno sprejemljivost v bodocih, cedalje bolj konfliktnih postopkih odlocanja,prostorskinacrtovalcinamenitivecpozornostikakovostikomunikacijeinsporazumevanjumed akterji. KLJUCNEBESEDE:deliberativnoupravljanje,post-politicnoprostorskonacrtovanje,kvalitativnemetode, participacija civilne družbe, prometno nacrtovanje The article was submitted for publication on February 9th, 2021. Uredništvo je prejelo prispevek 9. februarja 2021. 1 Research Centre of the Slovenian Academy of Sciences and Arts, Anton Melik Geographical Institute marusa.goluza@zrc-sazu.si (https://orcid.org/0000-0002-2011-1547), david.bole@zrc-sazu.si (https://orcid.org/0000-0003-2773-0583) 2 University of Ljubljana, Faculty of Civil and Geodetic Engineering, Ljubljana, Slovenia maruska.subic-kovac@fgg.uni-lj.si 3 University of Ljubljana, Faculty of Social Sciences, Ljubljana, Slovenia drago.koss@gmail.com 1 Introduction: The necessary legitimacy of national spatial planning system Modern societies increasingly face a crisis of legitimacy in spatial planning and other public policies due toconflicts,theemergenceofcitizens’ initiativesandanoveralldeclineinsocialacceptanceofpublicpoli­cies (Sager 1999; Kos 2002; Inch 2015). Decision-making is often value-based and requires trade-offs and long-termsolutions(RittelandWebber1973;InnesandBooher2010).Differentiatedsectoralpolicies,sci­ence, and the division of labour between different levels tires of government often overlap spatially and substantively.Policydecisionsarethereforeincreasinglydifficulttomakeandjustify(Healey1997;Kos2002). As a resultofthelegitimacycrisis,thecorequestion of modernnation-states todayis how thestate issup­posedtojustifyandmaintainitspositionofcontrolandresponsibilityfortheimplementationofpublicpolicies infrontofthepublic–thepeoplewhoaredirectlyaffectedbythesepolicies.Habermasaddressedthisissue asearlyasthe1970s,claimingthatthestatemustintervenetolimitadverseeffectsoftheliberalmarketecon­omywhileallowingtheeconomytofunction(Plant1982).Theneedfortrustworthyplanningisparticularly relevant in the formulation of long-term development plans where outcomes cannot be expected imme­diately.Inthiscontext,Tyler(2001)arguesthatlegitimategovernmentinstitutionsandtheirpublicpolicies are moreefficientand less likely to generatepublic opposition. Public policies that are perceived asillegit­imatearegenerallymoreconflictual,lessfeasibleandalsomoreexpensiveforthestate.Legitimacyhastherefore always been one of the central concerns of planning theorists and practitioners. Theconceptoflegitimacyinspatialplanningtheoryiscloselyrelatedtothebalancebetweenindividual and public interests. It reflects the extent to which national policies and spatial plans (that are supposed tobeinthepublicinterest)areconsistentwithindividualinterestsandopinions(Alexander2002).Legitimacy is thus a powerful means of achieving efficiency in the implementation of national policies and develop-mentplans(Tyler2001).Itreferstosubstantiveandproceduraldimensionsofdecision-makingprocesses. Substantively, it depends on the legitimacy and conformity to established norms, rules and processes rel-evanttothematterathand.Inproceduralterms,legitimacydependsonwhetherandhowthedecision-making process enables relevant actors to participate. Legitimacy thus signifies shared beliefs about how a coun­try should be governed as a political community. It concerns the rights of citizens as well as the rights and duties of the state (or those who govern). Legitimacy in this sense is closely related to the notion of justi­fication. Decisions of the state are legitimate insofar as they are properly justified. In other words, policies and decisions of the state are legitimate if the decision-makers can demonstrate that the powers they have and use are just, right and reasonable (Bekkers, Dijkstra and Fenger 2007). Despitevariouscritiquesthatparticipatoryprocessescannotliveuptotheirtheoreticalidealsinprac­tice (e.g., Flyvbjerg 1998; Forester 1999; 2009; Flyvbjerg, Bruzelius, and Rothengatter 2003; Flyvbjerg and Richardson 2003; Hillier 2003; Innes and Booher 2010; Sager 2013), there remains a general consensus amongtheoristsandpractitionersthatparticipatoryplanningapproachesarecrucialforlegitimizingdevel-opmentprojects(e.g.., Forester1993;Healey1996;1997;2003;Innes1996;MaregaandKos2002).However, empirical studies have shown that in practice it is often carried out superficially (Nared et al. 2015) and perceivedasahindranceindecision-makingprocesses.Tokenisticparticipationisparticularlycharacteristic ofpost-socialistcountries(HafnerFink2012;Pop-ElechesandTucker2013;PoljakIstenicandKozina2020). Stable power relations and the strategic functioning of actors in decision-making processes also prevent genuine collaboration and consensus-building (Flyvbjerg 1998; Flyvbjerg and Richardson 2003). Nevertheless, little is known about the actual performance of spatial planning and its mechanisms for legitimizing national development projects in Slovenia (e.g. Nared et al. 2015; Goluža 2020). Several con-flictualandprotracteddecision-makingprocesses,especiallyinthefieldoftransportandenergyinfrastructures in the past decades, have shown that legitimation processes in Slovenia have obviously failed. In addition, Slovenianspatialplanninglegislationhasbeenamendedseveraltimesafterindependence,withclearattempts to optimize the preparation of national spatial plans, also by limiting public participation. We therefore hypothesize that the Slovenian attitude towards public participation in spatial planning is a legacy of the formerYugoslavsocialisteconomicandpoliticalsystemofself-government.Thesystem,whichwasdemo­cratic in theory and granted considerable decision-making powers to the working population, proved to be inefficient in practice. Decision-making processes were still heavily influenced by politics and market relationsandwerealsoverytime-consumingandunproductive(Centrih2014).Thus,theself-governance system did not contribute to more democratic decision-making processes. On the contrary, the experi­encewiththeself-governmentsystemprobablylefttracesofdistrustinparticipatorydecision-makingthat persistedevenafterSloveniadeclaredindependencein1991andtransitionedtoliberaldemocracy.Although Slovenia has adopted the Aarhus Convention (Zakon o ratifikaciji…2004) and, as an EU member state, declares the idea of participation as necessary for the legitimacy of public decision-making, its planning laws require only a minimum of public participation. The purpose of this study is to examine how the Slovenianspatialplanningsystemrelatestolegitimacyandhowtheadoptionofdemocraticnormsaffects legitimacyprocessesinpractice.Therearetwomainobjectivesofthisstudy.Thefirstistooutlinetheplan­ningmechanismsusedinthedecision-makingprocesstolegitimizethenationaldevelopmentproject(the northern part of the Third Development Axis, hereafter Third Development Axis) and the national spa­tial plan as the basis for its implementation. Secondly, the legitimacy of the applied mechanisms will be assessed through a qualitative analysis.The research will contribute to a better understanding of the plan­ning mechanisms and their contribution to the legitimacy of national development projects. With a specific focus on the Slovenian case study, the research will in particular deepen the understanding of key legitimacy problems in spatial planning that Slovenia as a young democracy is facing today. 2 Conceptual framework for assessing legitimacy of decision-making process: Input, throughput and output legitimacy Spatialplanningisincreasinglyfacingacrisisoflegitimacyduetoconflictingscientificviewpoints,uncer­tainties,timeandfinancialconstraints,andmanyothervalue-based,institutional,andworldviewdifferences among actorsthataredifficulttobridge(Forester1984;Wheeler2020). Legitimacy,then,isanelusive and context-dependent concept that cannot easily be guaranteed by a universal approach to planning. Since there is no absolutely correct planning approach that would ensure intrinsically legitimate decisions, researchershavenochoicebuttoanalyseandlearnfromindividualcasestudies.Inordertoevaluateplan­ning approaches in terms of legitimacy, some authors propose to decompose the concept of legitimacy intothreepillars:Input,ThroughputandOutputLegitimacy(e.g.Bekkers,DijkstraandFenger2007;Schmidt 2012; Lieberherr and Thomann 2020), which are summarised in Table 1. The concept of input, through­putandoutputlegitimacyisalsousedinthispaperasitprovidesasystematicanalyticalmeanstoevaluate decision-making processes. Table 1: Norms for assessing democratic legitimacy in decision-making processes (adapted from Bekkers, Dijkstra and Fenger 2007). Input legitimacy Throughput legitimacy Output legitimacy • Equal opportunities for participation in • Realization of collective decision-making • How decisions taken tackle collective problems; decision-making process and influencing (e.g., voting, deliberation, etc.); • Effectiveness and efficiency of decision-making the decisions; • Who participate in decision-making process; • Representation of relevant interests; (e.g., public, experts, representatives • Accountability of decisions. • Openness of the governance practices of public sector); to respond to specific needs in society. • Transparency; • Balanced power relations. Inputlegitimacyreferstoaqualityofpolicymaking(LieberherrandThomann2020). Itconcernspolit­ical equality, active citizenship and popular sovereignty in shaping spatial policies or plans. It depends on theopportunitiesgivento citizenstoparticipate,expresstheirinterests,engage and influence the decision-making process. When citizen participation is only indirect, input legitimacy depends on the quality of representationofinterestsandpreferencesbypoliticalintermediaries.Inputlegitimacyalsoreferstotheopen­ness of the agenda-setting process to citizens’ demands and concerns. In this sense, it means the openness ofgovernancepracticestorespondto(locally)specificneedsinsociety(Bekkers,DijkstraandFenger2007). Throughput legitimacyrefers to the quality of a governance process (Lieberherr and Thomann 2020), to rules and processes that define decision-making processes (Bekkers, Dijkstra and Fenger 2007). Since societalproblemsandconflictsrequirecollectiveaction,throughputlegitimacyisrelatedtotheimplementation of collective decision-making. Throughput legitimacy is related to the quality of participation of all rele­vant actors. According to Habermas, communication between all relevant actors should lead to a shared learningprocessthatpromotesmutualunderstandingandconfrontsandtransformsthepowerofthestate andcapital(Healey1996).Itshouldbetransparentandinformativeandbalancethepowerrelationsbetween actors. With these prerequisites, throughput legitimacy comes closest to participatory democracy and the goals of the Aarhus Convention (Bekkers, Dijkstra and Fenger 2007). The third aspect of legitimacy in the decision-making process is output legitimacy, which represents the government’s ability to produce outcomes from decision-making processes that solve collective prob­lems (Bekkers, Dijkstra and Fenger 2007). Output legitimacy focuses on whether the outcomes of the decision-making process are legitimate in terms of acceptability, rather than the process itself (Lieberherr and Thomann 2020). Output legitimacy refers to the efficiency and effectiveness of the outputs and out-comesoftheimplementedpolicyorplan.Itisconcernedwithhowthedecisionsmademeettheoriginally stated goals of the policy or plan and how they respond to the expressed desires of the population. Output legitimacyalsoreferstotheaccountabilityofdecisionmakers,bothforthedecisionsandfortheoutcomes of those decisions. Therefore, decisions and their impacts should be based on a fully transparent provi­sion of information (Bekkers, Dijkstra and Fenger 2007). 3 Methodology 3.1 Case study selection The study is based on a case study approach. For our analysis, we chose the planning process fora motor­way along the Third Development Axis that will extend from the Slovenian-Austrian border in the north to the Slovenian-Croatian border in the south. We focused specifically on Section F, which refers to the area between the existing A1 motorway and the town of Velenje (see Figure 1). The selection of the case studywasbasedoninformation-orientedsampling(Flyvbjerg2006),whichwasmotivatedbyseveralrea-sons: 1) the Third Development Axis is one of the few major Slovenian infrastructure projects of the last decades and also one of the most notorious ones due to multiple problems of legitimacy and conflicts; 2) the process of preparing the national development plan for Section F was one of the most conflictual and lengthydecision-makingprocessesinSlovenia;and3)thecaseinvolvedactorsfromdifferentsocialspheres, e. g., from civil society, the public sector and experts. 3.2 Methods Sincelegitimacyisaratherambiguoustheoreticalconceptthatcannotbefullymeasuredorquantifiedobjec­tively, we have adopted a qualitative approach for our study, i.e. a document analysis. Documents related tothe preparation of the national spatial plan,such as expert evaluationsofalternatives,revisions,reports andminutes,arepubliclyavailableuponrequestfromtheMinistryoftheEnvironmentandSpatialPlanning, which is also responsible for the implementation of the decision-making process. These documents were used to identify the applied planning mechanisms used by the State to legitimise the development project under study, the Third Development Axis. We have presented the applied mechanisms according to the conceptofinput,throughputandoutputlegitimacydiscussedinChapter2inTable2).Finally,weassessed the overall legitimacy of the observed decision-making process. 4 Results: The analysis of decision-making process’s legitimacy 4.1 Overview of the planning process and outline of the applied legitimizing planning mechanisms The motorway along the Third Development Axis is a national infrastructure project defined as one of thedevelopmentprioritiesinthenationalSpatialdevelopmentstrategyofSlovenia(Odlokostrategiji…2004). Figure 1: Alternative variants of the Third Development Axis on the Section F. p p. 114 114 The main purpose of the motorway is to increase the economic competitiveness of the regions and cities (suchasSlovenjGradec,Dravograd,Velenje,Novomesto)alongtheplannedroute,improvetheiraccessi­bility and strengthen the institutional and economic links between them. In short, it is an instrument for strengtheningeconomic,socialandterritorialcohesion(Projekt…2007).Themotorwaylink,whichwould connect five Slovenian regions with the Austrian transport system in the north and the Croatian one in the south, should be implemented by 2013 (Resolucija…2004). As this is a major national infrastructure project, the state has a key role in legitimizing and implementing the planning process. Following the launch of the project in 2004, the first spatial planning conference was organizedby the Ministry of the Environment and Spatial Planning. This was a formally prescribed mechanism (Spatial Management Act 2002) aimed at soliciting and harmonizing the recommendations, guidelines and legit­imate interests of local communities, the business community, interest groups and the organized public with regardtothepreparation of thenational spatial plan.In accordancewith theinterests expresseddur­ing the spatial planning conference, the preliminary expert analysis of the Third Development Axis was conducted. The analysis took into account various development scenarios, forecasts of traffic flows and various spatial, environmental and economic indicators. Suitable motorway alignment alternatives were identified for further analysis and review (Predhodne…2008). Theproposedmotorwayalternativeswerefurtheranalysedandreviewedbasedonfourgroupsofindi­cators:spatial,functional,environmental,andeconomic.Theexpertanalysisendedin2007withtheproposal of the most suitable variant for the Third Development Axis. For Section F, two alternatives received the highest score. Finally, the so-called F2 was selected as the most suitable because it was a better fit withthe highestscoringalternativeontheabove-lyingsection(seeFigure1).However,F2hadtwomajordrawbacks.Itwasrelativelysteepandwouldresultinasignificantlossofhigh-qualityagriculturalland(Študija…2008). In 2008, the proposals for the best evaluated sections were presented to the ministries and represen­tatives of the municipalities that would be affected by the new motorway. They were able to comment on the proposed motorway route and suggest optimizations, some of which were later included in the pub­lic displays and public hearings. During the public displays and hearings, fierce opposition arose from the local communities in the municipalities that would be affected by Section F, especially in the small rural municipality of Braslovce. They argued that the motorway would unjustifiably damage and cause loss of high-value and other agricultural land in the area typically used for agriculture. The decision-making process was also reviewed at this stage by experts, as is customary for national development projects. The review revealed several shortcomings, such as that the objective of the whole project and its importance for regional development were not clear enough. They also emphasized that theprojectneglectedanticipateddemographictrendsandtheincreasingimportanceofpublictransportation, which would reduce automobile use and the need for new motorway. The reviewers also pointed out the ambiguityandinconsistencyintheuseofvariousindicators.Theyclaimedthattheindicatorsusedineval­uating the alternatives did not include an examination of the social acceptability of each alternative. The lackofclearexplanationsastowhyonealternativeisbetterthanotherswasparticularlyevidentinSection F, where two alternatives received the same score in the expert evaluation. As the preparation of the national spatial plan as a whole proved to be very challenging due to sever­al conflicts, the Ministry of Infrastructure arranged for the projectto be divided into four separate spatial plans. One of these was the spatial plan for Section F. Sectoral ministries were asked to supplement their guidelines for the preparation of new spatial plans. In 2010, a draft of the national spatial plan for Section F was presented to the ministries and mayors, as well as to the public in the municipalities. The partially optimized version of F2 again provokedoppo­sition from the Ministry of Agriculture, Forestry and Food. It issued three negative opinions in relation withtheenvironmentalreport.TheMinistryofAgriculture,ForestryandFoodopposedtheconstruction ofthemotorwayonlegallyprotected,highvalueagriculturallandandpointedoutsomeproceduralincon­sistencies. They claimed that the chosen alternative was enforced without considering other alternatives. ThepreparationofthenationalspatialplanforSectionFcontinuedwiththeinter-sectoralexpertgroup thatthenationalgovernmenthadestablishedin2011toevaluatethedecision-makingprocess.Theexpert group found similar inconsistencies as the reviewers. They highlighted the lack of justification of the pro-ject(intermsofexpectedtrafficscenarios,financialresources,etc.),thevagueexplanationsofthedecisions onthealternatives,andtheinadequatemethodologyforassessingimpactsonagriculturalland.Themethod­ologyallowedanytypeofconstructiononagriculturallandaslongasitwasplannedwithmitigationmeasures. Thus, in the environmental report, any construction could be assessed as having an insignificant impact on agricultural land (Porocilo…2011). In 2012, due to conflicts, the national government initiated the study of other possible alternatives for the motorway on Section F, but all of them were discarded due to the crossing of Natura 2000 sites and other protected areas (Študija…2012). The preparation of the national spatial plan for Section F was therefore continued for the optimized alternative F2. The proposal for the plan was put on public display in 2015. Three public hearings wereheld in three municipalities, Velenje, Šmartno ob Paki and Polzela. In Šmartno ob Paki, the public hear­ing was disrupted by local civic initiatives because they objected to the decision-making process and the selectionofthefinalalternativeitself.Despitetheobjections,theMinistryoftheEnvironmentandSpatial Planning continued the preparation of the National Spatial Plan, which was adopted by the national gov-ernmentin2017.ThemunicipalitiesofBraslovce,PolzelaandŠmartnoobPakithereforefiledaconstitutional review of the national spatial plan for the motorway (Decree…2017). They argued that the procedure for thepreparationofthenationalspatialplanforSectionFviolatedseverallegallyprotectedrightsandlegal­ly binding procedures. For example, they relied on the Slovenian Constitution, which grants citizens the righttoparticipateindecision-makingprocesses,theAarhusConvention(Conventionon…1998),which protects the right to access to information, public participation in decision-making and access to justice in environmental matters, as well as several other directives dealing with the impact of projects, plans and programs on the environment (Directive…2001; Directive…2011). In 2019, the Constitutional Court found that the Decree (2017) was not in conflict with the Slovenian Constitution (Odlocba…2019). 4.2 The evaluation of legitimacy of applied planning mechanisms Intheprevioussubsection,wesummarizedtheprocessofpreparingthenationalspatialplanfortheThird Development Axis, in Section F. Here we will assess the mechanisms that state actors used to legitimize the national development project. They have been presented chronologically and in line with the concept of input, throughput and output legitimacy in Table 2 below. On paper, in the case of the Third Development Axis, the planning process began with mechanisms that promised high input legitimacy, such as the Spatial Planning Conference, which was a legally bind-ingmechanismandaimedtoharmonizetheinterestsofactors,includingcivilsociety(SpatialManagement Act 2002). A preliminary expert analysis was also carried out to define possible alternative variants and a coordination meeting was held with the mayors of the potentially affected municipalities. Local com­munities and experts were given the opportunity to influence decision-making by providing guidance, information and expertise (Pravilnik…2007). However, as the project became more concrete, conflicts between stakeholders increased, while the receptiveness of decision-makers to the plurality of interests and proposals from experts and civil society seemed to diminish. The subsequent process was essential­ly indifferent to the arguments of the opponents of alternative F2, which came from both experts and the local population in the area concerned. Decision-makers relied exclusively on seemingly rational expert assessments,eventhoughseveralexternalexperts(includingreviewers,aninter-ministerialexpertgroup, and agronomists) argued that these assessments were not entirely appropriate. Throughputlegitimacyreferstothecommunicationaspectofthedecision-makingprocessandcollective actioninrespondingtoproblemsandconflicts.Thecasestudyfoundthatthedecision-makingprocessfol­lowedlegallybindingmechanisms,suchasinformingministriesandmunicipalitiesofdecisionsmadeand publicdisplaysof(propositional)spatialplanswithpublichearings.TheMinistryoftheEnvironmentand Spatial Planning, which carried out the preparation of the national spatial plan, organized even more pub-licdisplaysandhearings,asrequired.Thispartlycontributedtomoretransparency,andresidentswerealso better informed about the project. However, it did little to improve the legitimacy of the decision-making process. The arguments of the opposing actors remained virtually the same throughout the decision-mak­ingprocess.Therelocationofthemotorwaytoanareaofhigh-qualityagriculturallandwasthebiggeststumbling block, both for agronomists and for local farmers whodepend on hop production and agriculture in gen­eral (Študija…2012). Conflicts between decision-makers and local residents opposed to the F2 variant reached their peak in 2015, when local citizens’ groups violently disrupted the public hearing. Public dis-playsandhearingscouldhavefacilitatedconsultation,butinpracticetheydidnotimprovecommunication between actors. Table 2: The timeline of legitimizing planning mechanisms applied in the preparation of national spatial plan for Section F, according to input, throughput and output legitimacy. Year Input legitimacy Throughput legitimacy Output legitimacy 2006 Spatial conference Preliminary expert analysis of alternatives 2007 Coordination meeting with mayors of affected municipalities Expert evaluation of alternatives 2008 Ministries supplement their guidelines for national spatial plan Display of the proposed route for ministries and municipalities Public display of the proposed variants and public hearing Revision of the expert evaluation Opposition in local communities National spatial plan divided into four sections 2010 Draft national spatial plan for F2 presented to ministries and municipalities Public display of draft national spatial plan for F2 and public hearing Negative opinion of the Ministry of Agriculture, Forestry and Food Opposition of civic initiative in Braslovce 2011 Inter-sectoral expert group assessed decision-making process 2012 Expert evaluation of other alternatives on the Section F National government requires expert analysis of other alternatives on the Section F Ministry of the Environment and Spatial Planning proceeds with optimisation of alternative F2 2015 Public display of draft spatial plan for optimized F2 and public hearing Ministry of Agriculture, Forestry and Food opposed to the proposed spatial plan 2016 Public display of national spatial plan for optimized F2 and public hearing 2017 National government adopted spatial plan for Section F Spatial plan for Section F was submitted for constitutional review 2019 The constitutional court rejected alleged irregularities Output legitimacy refers to the efficiency and accountability of decisions and is thus closely related to the reliability of the expert knowledge that supports the decisions. In the case of the Third Development Axis,thenationalgovernmentreviewedthelegitimacyandefficiencyofthedecision-makingprocessmul­tipletimes,forexamplethroughindependentreviewsandtheestablishmentofaninter-sectoralexpertgroup. Thesemechanismsuncoveredmultipleproblemsoflegitimacyduetoinconsistencies(e.g. inthejustifica­tion of how the Third Development Axis would improve regional development, why it should be built as afour-lanemotorway,or why onagriculturalland),ambiguities (e.g. in theuse and interpretationofindi-cators),andshortcomings(e.g.innotassessingthesocialacceptabilityoftheproject)inthedecision-making process. There was also opposition from the Ministry of Agriculture, Forestry and Food because the pro­posed motorway conflicted with sectoral (agricultural) legislation that protects agricultural land. Inanefforttoincreasethelegitimacyofthemotorwayandfacilitateconflictresolution,decision-mak­ers decided to split the Third Development Axis project into four separate spatial plans (Študija…2012). However, Section F remains controversial and illegitimate even after the government adopted the spatial development plan. The municipalities affected by the planned motorway submitted the Decree (2017) for constitutional review in 2017, but the Constitutional Court rejected the alleged irregularities in 2019 (Odlocba…2019).Astheconflictsremainedunresolvedandtheadoptedspatialplandidnotachievesocial acceptance, expert consent or the approval of the Ministry of Agriculture, Forestry and Food, the overall legitimacy in this regard proved weak. 4.3 Discussion: The role of the state in providing legitimate decision-making The case study showed that the procedural measures used to legitimize the project were not sufficient to increase the legitimacy of the decision-making process as a whole. With the exception of the spatial con­ference and the preliminary expert analysis, which allowed for deliberation and co-decision-making in the initial phase of the project, the other mechanisms did not contribute to achieving a consensual and legitimatedecision.Thecommunicationaspectofdecision-makingwaslimitedtopublicdisplaysandhear-ings,whichdidnotallowforargumentationbetweentheactorsbutformutualpersuasion.Publicdisplays and hearings are commonly known as mechanisms that aim to inform citizens while allowing minimal citizeninfluenceondecisions.AccordingtoArnstein(1969),theyfallintothecategoryoftokenisticapproach topublicparticipationandgivethefalseimpressionthatdecisionsaremadewithpublicconsent(Naredetal. 2015). Thecasestudyrevealedaninherentlyconflictualnatureofspatialplanningthatresultedinaprotracted and erratic decision-making process. The state, represented by ministries, the government and munici­palities, did not act together and there was a lack of long-term political commitment to the project. The casestudyshowedthattherewasnogenuinecommunicationnotonlybetweenstateactors,butalsobetween experts and civil society. Weak input and throughput pillars of legitimacy also led to erodedlegitimacy of the final decision. The constitutional review of the decision-making process, several expert opinions, and opposition from the Ministry of Agriculture, Forestry and Food made it clear that the adopted motorway route was considered illegitimate not only by local communities, but also by experts and politicians. The decision-making process revealed that some of the claims questioned by experts and civil society (espe­cially those related to the environment and sustainable transport planning) were not intended for wider publicandexpertorscientificdiscourse.Moreover,governmentdecision-makersdidlittletoincreaseaccount-ability for the outcomes of decision-making processes. Similar to the findings of Flyvbjerg (1998), the decision-making process analysed demonstrates how power relations and taken-for-granted discourses between certain groups of actors prevent the ideas and demands of others from coming to fruition or at least opening public debate and consideration. The case study examined in this paper shows a vicious circle of stable power relations that have not fundamentallychangedwiththetransitiontoliberaldemocracy,theratificationoftheAarhusConvention or the accession to the EU. Central decision-making power over the motorway project has remained in the hands of narrow circle of decision-makers and experts. On the contrary, there has been little room to reconcilethepluralityofinterestsandopinionsamongstakeholders,whetherfromthepublicsector,wider circle of experts and academia, or civil society. Low level of trust in public institutionsandtokenistic par-ticipatoryapproaches,typicalofcountriesintheCentralandEasternEurope(Marinova2011),areobviously alsopresentinSlovenia.InSlovenia,publictrustinthegovernmentismarkedlylow(Public…2018),which meansthatthestateshouldmakeevenmoreeffortstolegitimizeprojectsthroughparticipatoryapproaches. Theparticipatoryapproachtoplanningwasrecognizedasimportantinlegitimizingnationalpolicies.The decision-making process even went beyond the number of formally required public displays and hear­ings. Nevertheless, these measures did not strengthen mutual trust between actors or bring them closer toacommon,accountableandlegitimatesolution.Inthisrespect,thetransitioninSloveniahassofarbeen only partially successful. Awareness of the importance of public participation for legitimate public poli­cies has certainly increased, but there is an apparent lack of will on the part of actors to put this principle into practice and participate in a genuine decision-making process. Theconceptofinput,throughput,andoutputlegitimacyprovidesausefulandsystematictoolnotonly for analysis but also for raising awareness of the various aspects of acquiring legitimacy. As such, it is very informative for spatial planners and decision-makers who, in most cases, represent ‘the state’ in decision-making processes. It argues for more open, transparent and adaptive spatial planning processes to achieve greaterlegitimacyinfuturedecision-makingprocesses,notonlyininfrastructureplanningbutinspatialplan­ningingeneral.Thecase studysuggeststhatthemechanismsformallyprescribedbythestatetolegitimize projects facilitate participation (input legitimacy) and shows that the Slovenian national spatial planning system is relatively open to plurality of interests. Nevertheless, communication between actors appeared rather symbolic and remained on the lower rungs of the participation ladder (Arnstein 1969). The adher­ence to formalistic decision-making processes rather than the promotion of an adaptiveand deliberative approach may be the legacy of the earlier system of self-government. Indeed, state decision-makers’ fear of losing control if too many decision-making powers are distributed among different actors, even the lay public, is understandable. This may lead to uncritical, unproductive and time-consuming decision-mak­ingprocesses(Centrih2014),aswasthecaseintheformerYugoslavia’sself-governmentsystem.Scientific input(notlimitedtoformallyselectedfourdomainsofexpertanalyses)shouldthereforebecrucialtojus­tifywhyoneoptionisbetterthantheother.Toincreasethelegitimacyofthroughput,thestateshouldmake much more effort to balance power relations and adapt to possible (unexpected) conflicts. Certain con­cerns of actors, especially in cases where similar criticisms of the project are voiced by both citizens and experts, should be discussed more transparently (e.g., environmental concerns). Any decision or exclu­sion of a particular option should be publicly deliberated and justified with the broadest possible (expert and public) consensus. Adjusting the formally prescribed decision-making process in such cases should not be seen as an obstacle, but as a moral obligation of the state in changing the environment for present and future generations. Only when the decision-making process allows different voices to be heard, and when collective decisions are based on deliberation and soundly justified (rather than being the result of tokenisticpersuasion),candecision-makersmakemorelegitimateandaccountabledecisions(outputlegit­imacy). 5 Conclusion The case study analyzed has highlighted several legitimacy problems, which do not depend not only on compliance with formal, procedural mechanisms to facilitate participation, but above all require a change in actors’ attitudes towards co-decision. Since legitimacy is a context-dependent and rather ambiguous concept that cannot be easily determined and achieved, the ideal decision-making processcannot be pre­scribed or formalized. However, being aware of the legitimacy deficits of past decision-making processes istheonlywaytograduallyimprovethelegitimacyoffutureprocesses.Thedecision-makingprocessana­lyzed in this paper showed rigidity and adherence to legally binding planning mechanisms that did not significantlyenhancethelegitimacyoftheproject.Theprinciplesofparticipatoryplanning,whichencom-pass the concept of legitimacy, have remained untapped and represent potential that could enhance the legitimacy of national development projects and government agencies themselves. However, the imple­mentation of the principles of participatory planning would inevitably require the allocation of decision-making powers. ACKNOWLEDGEMENTS: The authors thank the Slovenian Research Agency for funding the core pro­gram Geography of Slovenia (P6-0101) and the junior researchers postgraduate research program. Both funds provided support for publishing these findings. 6 References Alexander, E. 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APPLICATIONOFANGOTPRECIPITATION INDEX IN THE ASSESSMENT OF RAINFALL EROSIVITY: VOJVODINA REGION CASE STUDY (NORTH SERBIA) Tin Lukic, Tanja Micic Ponjiger, Biljana Basarin, Dušan Sakulski, Milivoj Gavrilov, Slobodan Markovic, Matija Zorn, Blaž Komac, Miško Milanovic, Dragoslav Pavic, Minucer Mesaroš, Nemanja Markovic, Uroš Durlevic, Cezar Morar, Aleksandar Petrovic Rainfall erosivity in Vojvodina (North Serbia). DOI: https://doi.org/10.3986/AGS.8754 UDC: 911.2:556.12:504.121(497.113) COBISS: 1.01 Tin Lukic1, Tanja Micic Ponjiger1, Biljana Basarin1, Dušan Sakulski2, Milivoj Gavrilov1, Slobodan Markovic1, Matija Zorn3, Blaž Komac3, Miško Milanovic4, Dragoslav Pavic1, Minucer Mesaroš1, Nemanja Markovic1, Uroš Durlevic4, Cezar Morar5, Aleksandar Petrovic6 Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia) ABSTRACT: The paper aims to provide an overview of the most important parameters (the occurrence, frequency and magnitude) in Vojvodina Region (North Serbia). Monthly and annual mean precipitation values in the period 1946–2014, for the 12 selected meteorological stations were used. Relevant parame-ters(precipitationamounts,Angotprecipitationindex)wereusedasindicatorsofrainfallerosivity.Rainfall erosivity index was calculated and classified throughout precipitation susceptibility classes liable of trig-geringsoilerosion.Precipitationtrendswereobtainedandanalysedbythreedifferentstatisticalapproaches. Results indicate that various susceptibility classes are identified within the observed period, with a higher presenceofverysevererainfall erosionin June and July. This study could haveimplicationsfor mitigation strategies oriented towards reduction of soil erosion by water. KEY WORDS: climate change, precipitation, rainfall erosivity, soil erosion, Angot precipitation index, Vojvodina, Serbia. 1 University of Novi Sad, Department of Geography, Tourism and Hotel Management; Novi Sad, Serbia lukic021@gmail.com (https://orcid.org/0000-0001-5398-0928), tanja.micic91@gmail.com (https://orcid.org/0000-0002-5549-2693), biljana.basarin@gmail.com(https://orcid.org/0000-0002-2546­3728), gavrilov.milivoj@gmail.com, baca.markovic@gmail.com(https://orcid.org/0000-0002-4977-634X), dragoslav.pavic@dgt.uns.ac.rs (https://orcid.org/0000-0002-7113-0887), minucher@gmail.com (https://orcid.org/0000-0003-2505-5633), nemanja123markovic@gmail.com 2 University of Novi Sad, BioSense Institute; Novi Sad, Serbia dsakulski2@gmail.com (https://orcid.org/0000-0002-4926-2824) 3 Research centre of the Slovenian academy of sciences and arts, Anton Melik Geographical Institute; Ljubljana, Slovenia matija.zorn@zrc-sazu.si (https://orcid.org/0000-0002-5788-018X), blaz.komac@zrc-sazu.si (https://orcid.org/0000-0003-4205-5790) 4 University of Belgrade, Faculty of Geography, Department of Geospatial Bases of Environment; Belgrade, Serbia misko@gef.bg.ac.rs (https://orcid.org/0000-0002-7245-0700), durlevicuros@gmail.com (https://orcid.org/0000-0003-3497-5239) 5 University of Oradea, Department of Geography, Tourism and Territorial Planning; Oradea, Romania cezarmorar@yahoo.com (https://orcid.org/0000-0003-0211-5883) 6 University of Belgrade, Faculty of Geography, Department of Physical Geography; Belgrade, Serbia bebek2005@gmail.com (https://orcid.org/0000-0002-1172-3875) Uporaba padavinski indeksa Angot za oceno erozivnosti padavin: na primeru Vojvodine (severna Srbija) POVZETEK: Prispevek podaja pregled najpomembnejših padavinskih parametrov (pojavnost, pogostost invelikost)vVojvodini(severnaSrbija).Za12izbranihmeteorološkihpostajsobileuporabljenemesecne inletnepovprecnevrednostipadavinvobdobju1946–2014.Kotkazalnikeerozivnostipadavinsmoupora­bili ustrezne padavinske parametre (kolicina padavin, padavinski indeks Angot). Izracunali smo indeks erozivnostipadaviningarazvrstilivrazredegledenamožnostpojavljanjaerozijeprsti.Trendesmopreucili s tremi razlicnimi statisticnimi pristopi. V preucevanem obdobju smo prepoznali razlicne razrede indek­sa,zzelomocnopadavinerozijojunijainjulija.Raziskavajedobertemeljzaoblikovanjestrategij,usmerjenih v zmanjšanje vodne erozije prsti. KLJUCNEBESEDE:podnebnespremembe,padavine,erozivnostpadavin,erozijaprsti,padavinskiindeks Angot, Vojvodina, Srbija The article was submitted for publication on May 31st, 2020. Uredništvo je prejelo prispevek 31. maja 2020. 1 Introduction Oneofthemostprominentcausesoflanddegradationiswatererosion(BoardmanandPoesen2006;Bosco et al. 2015). »Erosion is a geomorphic process that detaches and removes material (soil, rock debris, and associated organic matter) from its primary location by some natural erosive agents or through human or animal activity« (Zorn and Komac 2013a, 288). Soil erosion is an important process connected to sev­eralerosiveagents,suchaswater,wind,ice,andsnow(Morgan2005;Blinkov2015a;Blinkov2015b).Panagos etal.(2015a;2015b)pointedoutthatinEurope,soilerosionbywateraccountsforthegreatestsoillosscom­pared to other erosion processes (e.g., Boardman and Poesen 2006). Water erosion may be accelerated by humanactivity,buthumanactivitymayalsopreventrunoffsandsoilremovalbybuildingretentionponds(Ferk et al. 2020) or terraces (Šmid Hribar et al. 2017). Watererosionhasmanyon-siteandoff-siteeffects(SantosTelles,deFátimaGuimarãesandFalciDechen 2011), whereby off-site effects may have greater social, economic and environmental concern (Boardman et al. 2019). Soil erosion affects land resources and increases the risk posed by the blockage of rivers and causes degradation of water quality through pesticides, fertilizers and nutrients carried with the sediment (Lukic et al. 2019). Although soils represent a vital resource, research on soil erosion has not gained as muchattentionas degradationof waterand airquality(Blinkov2015a). The reasoncanbefoundinmuch morecomplexandextensivenaturalfactorsthatledtothistypeoferosion,whicharealmostimpossibleto explainwithamodelthatwouldconsistofeveryvariableandfactorincludedintheprocess. Nevertheless, land degradation is recognized as a major environmental threat in many parts of Europe (e.g., de Luis, González-HidalgoandLongares2010;deLuisetal.2011;Blinkov2015a;Blinkov2015b;Lukicetal.2013, 2016, 2018, 2019; Zorn and Komac 2013b). Soilerosionmaybequantifiedusingfieldmeasurement(Stroosnijder2005)orerosionmodels(Borrelli et al. 2021). Globally the most widely used erosion models belong to Universal Soil Loss Equation family (USLE/RUSLE (Wischmeier and Smith 1978; Renard et al. 1997)), whereas on the territory of former YugoslaviaandinsomeneighbouringcountriestheGavrilovicequationhaspredominated(Gavrilovic1972; Hrvatinetal.2019).Besidesthese,therearemorethan600othermodelsthatcanbedividedintotwobasic groups: those extracted from the USLE and RUSLE equations, while others employ qualitative approach­es (Auerswald et al. 2014). Precipitationisthemostimportantnaturalagentwithregardtowatersoilerosion,hencerepresenting oneofthedeterminingfactorsintheUSLE equation(WischmeierandSmith1978;Morgan2005;Melloet al. 2013). Thecapabilityofrainfalltocausesoillossiscalledrainfallerosivity(Nearingetal. 2017;Panagos et al. 2017) and represents a climatological component in the overall erosion processes by water (da Silva 2004;Yu1998).Itisfundamentalfortheunderstandingoftheclimaticvulnerabilityregardingsoilerosion ina givenregion(Panagosetal. 2015a). Severalmeasuresofrainfallerosivityhavebeen proposed(Yuand Neil 2000; Morgan 2005): • R-factor in the USLE/RUSLE (Wischmeier and Smith 1978; Renard et al. 1997), • Fournier’s Index (Fournier 1960), • Modified Fournier Index (Arnoldus 1980), • Lal’s AIm index (Lal 1976), • Hudson’s KE >1 Index (Hudson 1976), and • Onchev’s Universal Erosivity Index (Onchev 1985). Rainfallerosivitypresentsthepotentialofraindropstotriggersoilerosionanditsestimationisfunda­mental for the understanding of the climatic vulnerability of a given region (Mello et al. 2013). Thereby, respective authors (e.g., Kirkby and Neale 1987; de Luis, González-Hidalgo and Longares 2010; de Luis et al. 2011) investigated the relationship between the intensity of precipitation and its distribution in time, since there is no exact relationship between the total amount of precipitation and soil erosion. Different approacheshavebeendevelopedwhenestimatingsoilerosion,namelyindicesbasedonprecipitationdata, and indices based on kinetic energy and precipitation intensity (e.g., Lukic et al. 2016; 2019). The most recognizedindicesdescribing kineticenergy andprecipitationintensity are EI30 (WeischmeierandSmith, 1978),AIm(Lal1976),KE>1(Hudson1976)andP/vt(Onchev1985).Theseparametersrequiredailypre­cipitationdataseriesover20years,andsincethereisnosuchdataformostpartsoftheworld,itwasnecessary to create a simpler approach. The most utilized indices based on available rainfall data are the Fournier Index (FI) and the Modified Fournier Index (MFI) (Morgan 2005; Arnoldus 1980) which are extracted from the R – rainfall erosivity factor in the USLE equation (Renard and Freimund 1994; Gabriels 2001; LoureiroandCoutinho2001;DiodatoandBellocchi2007).Theywereusedinnumerousstudieswithscarce precipitationdatabases(e.g.,LujanandGabriels2005;BoardmanandPoesen2006;deLuis,González-Hidalgo andLongares 2010; Ufoegbune et al. 2011; Costea 2012; Lukic et al. 2016; 2018; 2019). It was also in com-parisonsofseveralrainfallerosivityindices(e.g.,Oduro-Afriyie1996;daSilva2004;Bayramin,Erpuland Erdogan2006;Angulo-MartínezandBeguería2009;Alipouretal.2012;Melloetal.2013;Sanchez-Moreno, Mannaerts and Jetten 2014). Fournier indices require mean monthly data averages and are based on tem­poralprecipitationdistributionobtainedthroughPrecipitationConcentrationIndex(PCI)(Arnoldus1980). BesidearticlesthatwerebasedonMFIandFIparameters(e.g.,Oduro-Afriyie1996;LujanandGabriels2005; Apaydin et al. 2006; Costea 2012; Yue, Shi and Fang 2014; Hernando and Romana 2015), PCI was also usedinnumerousstudiesconcerningprecipitationdistributionandconcentration(Martínez-Casasnovas, Ramos and Ribes-Dasi 2002; de Luis et al. 2011; Iskander, Rajib and Rahman 2014; Lukic et al. 2019). According to Dumitrascu et al. (2017), besides soil type, topography, and land use, the amount and intensityofprecipitationisanimportantfactorinestimatingtherateofsoilerosionbywater.Theclimatic factors can lead to the intensification of erosion when they register high intensities and occurrence after a prolonged drought period. Forthispurpose,anindicatorfortheassessmentofpluvialaggressiveness(Angot–Kindex)(Dragota, MicuandMicu2008)canbeappliedinassessingrainfallerosivityinSoutheasternEurope–ahotspotregion with the highest number of severely affected sectors (Dragota, Micu and Micu 2008; Dragota et al. 2014; Dumitrascu et al. 2017; Lung and Hilden 2017; Lukic et al. 2019; Milanovic et al. 2019). So far, rainfall erosivity assessment in the Vojvodina Region has been carried out in the Backa and Zemun loess plateaus (Lukic et al. 2016, 2018) and in the Pannonian Basin (Lukic et al. 2019). The study found that the amount andtheintensityofprecipitationareincreasing.AccordingtoMarkovicetal.(2008;2012;2015),thelargest part of Vojvodina is covered with loess and loess-like sediments (> 60%), which are extremely suscepti­bletotheerosionprocessesduetohighporosity,carbonateandclaycontentasaboundingmaterial(Lukic et al. 2009; Vasiljevic et al. 2011; Hrnjak et al. 2014). Therefore, it is very important to point out the most vulnerable areas for mitigation and prevention (Leger 1990; Lukic et al. 2016; 2019). The publicly available precipitation database of the Vojvodina Region record more than 70 years of continuousobservations.However,thedataisbasedonmonthlyvalues.Accordingly,theaforementioned Angot – K index, which was used in similar studies (in the neighbouring countries), is one of the com­patible methodological approaches for assessing the potential vulnerability of the investigated area from the rainfall erosivity (e.g., Dragota, Micu and Micu 2008; Dragota et al. 2014; Dumitrascu et al. 2017). So far, rainfall erosivity assessment in the Vojvodina Region has been carried out for the case study of Kulasettlement(southernpartoftheBackaloessplateau)andZemunareainthevicinityofBelgrade(Zemun loessplateau),whereLukicetal.(2016;2018)studiedtherelationshipbetweenrecurringlandslidesandrain­fall erosivity. In a later study, Lukic et al. (2019) showed an increase in the amount and the intensity of precipitationaswellasinrainfallerosivityformostpartsofthePannonianBasin,includingVojvodinaregion. InthispaperclimatologicalparametersfromtheVojvodinaRegion(NorthSerbia)areprocessed.Weused theAngotprecipitationindex(Dragota,MicuandMicu2008),whichistheratioofthedailyaveragevolume of precipitation in a month and the annual daily average precipitation volume (Constantin and Vatamanu 2015)andwaspreviouslyalreadyusedinthewiderstudyregionbyDragotaetal.(2014)andDumitrascuet al.(2017).InordertoassesstheerosionvulnerabilityforthesouthernpartofthePannonianBasin,theoccur­rence,frequencyandmagnitudeof some ofthe most significant precipitationparameterswere studied. 2 Study area The Autonomous Province of Vojvodina (21,533km2) is located in the southern part of the Pannonian Basin and the northern part of the Republic of Serbia (Figure 1). It is divided into three regions: Banat, Backa, and Srem with Novi Sad as the capital (Basarin et al. 2018; Gavrilov et al. 2020). Thelargestpartoftheregioniscoveredwithloessandloess-likesediments(>60%).Astheloessmate-rial possesses several properties which make it highly susceptible to water erosion, it is very important to pointoutthemostvulnerableareasformitigationandprevention(Leger1990;Lukicetal.2009;2016;2019). TheVojvodinaRegionispredominantlyalowlandarea,andthehighestpartsareFruškagoraMountain (539m) in the northern part of the Srem Region, and the Vršacke Mountains (641m) in the southeastern partoftheBanatRegion.However,thelargestgeomorphologicalstructuresareformedonloessandloess­like material, and present loess plateaus, terraces and microrelief forms (Markovic et al. 2008; 2012; 2015; Lukic et al. 2009; Vasiljevic et al. 2011; Gavrilov et al. 2020). The climate of the Vojvodina Region is controlled by the geographical position in the southern part of the Pannonian Basin. According to the Köppen climate classification it is moderately continental due totheweakerimpactofwesternaircurrents,andthegreaterimpactofaEurasiancontinentalclimate.Winter seasons are cold (averageJanuary temperatures range from <0.0°C to 1.0°C), while summers are hot and humid (average July temperatureof between 21.0°C and 23.0°C),with a huge temperaturerange,reaching ~70°C and very irregular distribution of monthly rainfall (extremely rainy early summer and low precipi­tationin November and March) (Malinovic-Milicevic et al. 2018). Climate is influenced by NW cold and humid wind, and the warm and dry SE wind. Hence, the main characteristic of the rainfall regime in Vojvodina is reflected in the pronounced variability in both space and time. The average annual precipi­tation is 606mm, with the highest amounts in June, and lowest in February (Gavrilov et al. 2015; 2016). During the summer the total monthly precipitation can fall within a single day. The lowest average annual rainfallofabout540mmis recordedin thenorth,while thehighestaverage precipitation valuesare recorded in the southwest of Vojvodina (Hrnjak et al. 2014; Tošic et al. 2014; Gavrilov et al. 2019). 3 Data and methods The precipitation data for the rainfall erosivity assessment was obtained from the database of the Hydro-meteorological Service of the Republic of Serbia for the period 1946–2014 for 12 meteorological stations (Meteorološki godišnjak 1946–2014) (Table 1), selected based on the completeness of the time series and spatialdistribution(Figure1).Datafortheanalysedperiodcoverstwothirty-yearcycles,whichisinaccor-dance with the WMO standards. Datasetsforeachofthestationswereanalysedandprocessedforthecalculationofthemeanmonthlyamount ofprecipitation. Thus,a database wascreatedwith a timeseries of monthly andannualprecipitationvalues. The homogeneity of the precipitation series was confirmed by the Alexandersson (1986) test. Precipitation trendswereexaminedusingthreedifferentstatisticalapproaches.Inthefirstapproach,asimplelinearregres­sionwasusedtodeterminetheexistenceofacertaintendencyinthedataseries,whichgivesinformationon thestagnation,growthordeclineoftheobservedphenomenon(Cohen1988;GocicandTrajkovic2013).Using Figure 1: Map of Vojvodina (North Serbia) with meteorological stations used in this study. p p. 128 19°0'0"E 20°0'0"E 21°0'0"E HUN Palic ¯ ( !Legend!Meteorological station ( Inland water Senta ! ( ROU Bac ka loess plateau Kikinda River net A.P. Vojvodina ! ( Sombor ! ( National border km 0 20 40 Backi Bac Rimski !PetrovacZrenjanin ( !Šancevi ! ( ( ! ( Tite lloess HRV plateau Vršac Banatski!( SremskaKarlovac ! ( Mitrovica ! ( BelaCrkva ! ( BIH Scale: 1:900.000Content and map by: Tanja Micic PonjigerSource: DEM (Copernicus data and information funded by EU, EU-DEM layers);National border (GADM database (www.gadm.org), version 3.4, April 2018.); Hydrography (Copernicus Land Monitoring Service–Local Component: EU–Hydro).© 2020 DGTH, Faculty of Sciences, UNS 45°0'0"N 46°0'0"N 45°0'0"N 46°0'0"N 19°0'0"E 20°0'0"E 21°0'0"E Table 1: Geographical coordinates and altitudes of selected meteorological stations. Region Meteorological stations Latitude (N) Longitude (E) Altitude (m) this method, the trend equation for yearly data was obtained for 69 years. The precipitation trend was also investigatedusingthenonparametricMann-Kendalltest,whichiswidelyappliedinenvironmentalsciences foritssimplicityandprecision(Gilbert1987;Gavrilovetal.2011,2013;Hrnjaketal.2014;Lukicetal.2017). Third, Kendall’s tau (t) (Kendall 1938, 1975) was calculated to gain a trend over a fully observed period of 69 years. Then, two hypotheses were tested: 1) Nullhypothesis(H0)–withtheassertionthatthereisnotrendintheobservedtimeseriesforadefined level of significance of 95% (a= 0.05); 2) Alternativehypothesis(Ha)–withtheassertionthatthereisatrendinagiventimeseriesforadefined level of significance of 95% (a= 0.05). Statistical data processing was performed using the Wolfram Mathematica 11.3 software. Due to the presence of a positive correlation in data sets that can influence the increase in the number of false-pos­itive trend outcomes, the Yue-Pilon method was performed (Yue et al. 2002). Rainfallerosivitycanbeassessedusingseveralmethods(Costea2012),ofwhichwechooseAngotpre­cipitationindex(K)(Dragota,MicuandMicu2008;Dragotaetal.2014;Dumitrascuetal.2017).According toDumitrascuetal.(2017),destructiveheavyrainfallsmostlydependontheintensity,durationandwater quantityoftheprecipitation,andparticularsurfacefeatures,suchaslithology,vegetationcover,andslope. Insuchconditions,heavyprecipitationcantriggerfloods,erosionandslopefailures(Lukicetal.2016,2018). Hence, the main components of the precipitation regime that have the strongest impact on the environ­mentintheVojvodinaRegionhavebeenanalysedusingaspecificerodibilityKindex.AccordingtoDumitrascu et al. (2017), this index has the benefit of relying on easily accessible input data (precipitation), where the quantification and ranking of precipitation aggressiveness is made using already established value class-es.TheAngotprecipitationindex(K)wasinitiallyaimedatdeterminingthecharacteristictypesofmonthly and annual variation of precipitation based on regional and local comparisons. The index was quantified according to equations 1 and 2 (Dragota, Micu and Micu 2008; Dumitrascu et al. 2017): p K = (1) P where p = q/n, q being the monthly precipitation amounts, and n being the number of days/months, and Q P = 365 (2) where Q is the multiannual precipitation amounts. The resulted index values were used to determine the susceptibility classes of precipitation liable for triggering soil erosion (Table 2). Table 2: Susceptibility classes of precipitation liable to triggering soil erosion based on Angot precipitation index (K) (Dragota, Micu and Micu 2008; Dumitrascu et al. 2017). Precipitation attributes Very dry Dry Normal Rainy Very rainy Precipitation erodibility classes Very low Low Moderate Severe Very severe Angot index values (K) <0.99 1.00–1.49 1.50–1.99 2.00–2.49 > 2.50 In order to examine the relationship between precipitation data, K and potential climate drivers, lin-earcorrelationswereutilized.Theselectedlarge-scalephenomenon,NorthAtlanticOscillation(NAO)and Multivariate ENSO Index (MEI) were used following the approach by Malinovic-Milicevic et al. (2018) and Lukic et al. (2019). NAO is characterized as the difference between sea-level pressure observed over IcelandandPortugal.WhenthevaluesofNAOarenegativestormtracksshifttothesouth,inducingmore winterprecipitationintheregionssouthofthePyrenean-AlpineMountains,includingthePannonianBasin (and the Vojvodina Region). On the other hand, positive values of the NAO lead to shifting storm tracks to the north, exposing the area south of the Pyrenean-Alpine Mountains to relatively dry conditions in the winter (Hurrell et al. 2003; Trigo et al. 2004). The station-based NAO time series were obtained from the Climatic Research Unit of the University of East Anglia (Internet 1). Ocean–atmosphere interactions in the Pacific realm El Niño-Southern Oscillation (ENSO) is one of the most important climate drivers whose influence extends across the globe. MEI is an appropriate and arathercomplexparameter,whichintegratescompleteinformationofsixoceanicandmeteorologicalvari­ablesindicatingtheinfluenceofsouthernoscillation(Pompa-GarcíaandNémiga2015).TheENSO(MEI) record was obtained from the NOAA Physical Sciences Laboratory (Internet 2). 4 Results and discussion Thetemporalevolutionofthemovingaverage(withasizewindowequalto12months)indicatesthatthere arenosignificantvariationsordeviationsregardingtheprecipitationdistributioninthestudyarea(Figure2). This observation corresponds wellwith the resultsof Lukicetal. (2019)whopointed out thatprecipitation concentration values (PCI) in northern Serbia belong to the group of moderately distributed precipitation (a statistically significant trend was not observed). According to the authors, seasonal values of precipita­tionconcentrationfortheVojvodinaRegiongenerallydisplayuniformvalues,wherethewinterseasonexhibits higher values than other seasons for all investigated stations during the period 1961–2014. AsshownbyBjelajacetal.(2016),theaverageannualprecipitation(calculatedforaperiodof69years) for11outof12stationsindicateapositivelineartrend,ofwhichmostpronouncedtrendsareobservedfor theBackaRegion–RimskiŠancevimeteorologicalstation(y=1.8309x+550.89).Thehighestaveragepre­cipitationamountisrecordedfortheBelaCrkvameteorologicalstation(659.1mm)inthesoutheast,while thelowestvaluesarerecordedinthenorthandnortheast(Palicstation555mmandKikindastation555.5mm) (Figure3).AccordingtotheMann-Kendalltest,basedoncalculatedpvalues,Sombor(p=0.020)andPalic (p = 0.021) stations confirm the Ha hypothesis, i.e. there is a noticeable positive trend at the significance level p < 0.05. Therefore, on the annual basis, Sombor and Palic stations (for the study period) display an increase in the amount of precipitation by 1.46mm and 1.68mm, respectively (Figure 3). Other meteoro­logical stations do not show statistically significant trend of precipitation variability for the study period. Theusedmeteorologicaldatabasecoversthewarmperiodoftheyear(whenpositivevaluesofKindex prevail).Themostfavourableconditionsfortheoccurrenceofwatererosionprocessesaredistributedwith­inAprilandSeptember(whenthehighestrainfallamountsarerecordedforallinvestigatedstations;Figure4). Table 3 summarizes monthly susceptibility of the Angot precipitation index classes (in%) for the selected stations during the period 1946–2014. Figure 2: The 12-month moving average of precipitation distribution (for the study period) for the Vojvodina Region. p p. 131 Figure 3: Spatial distribution of the mean annual precipitation for the study period in the study area. p p. 132 Figure 4: Mean monthly multiannual precipitation amounts (mm) for the selected stations and regions. p p. 133–134 200 150 100 50 0 Precipitation (mm) 1946 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 Year 132 Banatski Karlovac (Banat region) Bela Crkva (Banat region) 80 Precipitation (mm) Precipitation (mm) Precipitation (mm) Precipitation (mm) Precipitation (mm) Precipitation (mm) Precipitation (mm) Precipitation (mm) 60 40 20 20 0 0 I II III IV V VI VIIVIII IX X XI XII I II III IV V VI VIIVIII IX X XI XII Month Month Vršac (Banat region) Zrenjanin (Banat region) 80 80 60 40 60 40 20 20 0 0 I II III IV V VI VIIVIII IX X XI XII I II III IV V VI VIIVIII IX X XI XII Month Month Kikinda (Banat region) Senta (Banat region) 70 70 60 60 50 40 30 20 20 10 10 0 0 I II III IV V VI VIIVIII IX X XI XII I II III IV V VI VIIVIII IX X XI XII Month Month Bac (Backa region) Backi Petrovac (Backa region) 80 80 60 40 20 0 0 I II III IV V VI VIIVIII IX X XI XII I II III IV V VI VIIVIII IX X XI XII Month Month 133 134 Table 3: Monthly susceptibility of Angot precipitation index classes (1946–2014). Susceptibility class/Angot index values Month (%) April May June July August September Very low (< 1.0) 56.5 52.2 20.3 53.6 59.4 62.3 Low (1.0–1.5) 31.9 17.4 26.1 13.4 18.8 20.3 Moderate (1.6–2.0) 8.7 14.5 27.5 14.5 14.5 13.1 Severe (2.1–2.5) 2.9 7.2 17.4 11.6 1.5 0 Very severe (> 2.5) 0.0 8.7 8.7 7.2 5.8 4.4 Very low (< 1.0) 57.9 42.1 26.1 46.4 55.1 59.4 Low (1.0–1.5) 28.9 26.1 17.4 18.8 21.7 24.6 Moderate (1.6–2.0) 8.7 11.6 30.4 14.5 11.6 13.1 Severe (2.1–2.5) 4.3 10.1 10.1 8.7 7.2 0 Very severe (> 2.5) 0.0 10.1 15.9 11.6 4.3 2.9 Very low (< 1.0) 53.6 44.9 23.2 47.8 53.6 63.8 Low (1.0–1.5) 31.9 28.9 27.5 18.8 15.9 18.8 Moderate (1.6–2.0) 10.1 14.5 20.3 13.1 14.5 8.7 Severe (2.1–2.5) 4.3 4.3 17.4 8.7 5.8 5.8 Very severe (> 2.5) 0.0 7.2 11.6 11.6 10.1 2.9 Very low (< 1.0) 59.4 53.6 17.4 53.6 66.6 62.3 Low (1.0–1.5) 28.9 17.4 26.1 18.8 14.5 23.2 Moderate (1.6–2.0) 10.1 15.9 27.5 10.1 10.1 8.7 Severe (2.1–2.5) 1.4 7.2 13.1 7.2 4.3 1.4 Very severe (> 2.5) 0.0 5.8 15.9 10.1 4.3 4.4 Very low (< 1.0) 56.5 49.3 30.4 47.8 53.6 56.5 Low (1.0–1.5) 28.9 18.8 23.2 21.7 23.2 28.9 Moderate (1.6–2.0) 5.8 17.4 15.9 14.5 11.6 8.7 Severe (2.1–2.5) 5.8 11.6 15.9 10.1 5.8 2.9 Very severe (> 2.5) 2.9 2.9 14.5 5.8 5.8 2.9 Very low (< 1.0) 69.6 46.4 24.6 59.4 50.7 57.9 Low (1.0–1.5) 18.8 21.7 27.5 20.3 27.5 24.6 Moderate (1.6–2.0) 8.7 15.9 24.6 8.7 13.1 11.6 Severe (2.1–2.5) 1.4 7.2 8.7 7.2 5.8 2.9 Very severe (> 2.5) 1.4 8.7 14.5 4.4 2.9 2.9 Very low (< 1.0) 57.9 43.5 26.1 47.8 57.9 65.2 Low (1.0–1.5) 30.4 30.4 24.6 28.9 20.3 14.5 Moderate (1.6–2.0) 10.1 13.1 24.6 14.5 11.6 8.7 Severe (2.1–2.5) 0 8.7 14.5 5.8 4.3 8.7 Very severe (> 2.5) 1.4 4.3 10.1 2.9 5.8 2.9 Very low (< 1.0) 65.2 47.8 21.7 53.6 59.4 59.4 Low (1.0–1.5) 23.2 24.6 28.9 21.7 20.3 18.8 Moderate (1.6–2.0) 8.7 17.4 17.4 8.7 10.1 13.1 Severe (2.1–2.5) 2.9 4.3 17.4 8.7 5.8 5.8 Very severe (> 2.5) 0.0 5.8 14.5 7.2 4.4 2.9 Susceptibility class/Angot index values Month (%) April May June July August September Very low (< 1.0) 63.8 42.1 26.1 39.1 44.9 57.9 Low (1.0–1.5) 24.6 28.9 26.1 31.9 33.3 24.6 Moderate (1.6–2.0) 5.8 13.1 15.9 15.9 15.9 8.7 Severe (2.1–2.5) 4.4 10.1 20.3 8.7 1.4 4.3 Very severe (> 2.5) 1.4 5.8 11.6 4.3 4.4 4.3 Very low (< 1.0) 59.4 47.8 23.2 52.2 57.9 66.7 Low (1.0–1.5) 31.9 26.1 23.2 18.8 18.8 15.9 Moderate (1.6–2.0) 5.8 14.5 23.2 10.1 8.7 11.6 Severe (2.1–2.5) 1.4 7.2 14.5 11.6 10.1 4.3 Very severe (> 2.5) 1.4 4.3 15.9 7.2 4.3 1.4 Very low (< 1.0) 56.2 49.3 26.1 40.6 59.4 65.2 Low (1.0–1.5) 33.3 23.2 24.6 21.7 23.2 18.8 Moderate (1.6–2.0) 5.8 11.6 27.5 26.1 8.7 5.8 Severe (2.1–2.5) 2.9 7.2 13.1 4.3 2.9 5.8 Very severe (> 2.5) 1.4 8.7 8.7 7.2 5.8 4.3 Very low (< 1.0) 52.2 49.3 21.7 44.9 60.9 63.8 Low (1.0–1.5) 37.7 23.2 27.5 34.8 18.8 18.8 Moderate (1.6–2.0) 7.2 17.4 24.6 7.2 11.6 11.6 Severe (2.1–2.5) 2.9 4.3 15.9 7.2 4.3 2.9 Very severe (> 2.5) 0.0 5.8 10.1 5.8 4.3 2.9 Very low (< 1.0) 56.5 44.9 21.7 46.4 55.1 63.8 Low (1.0–1.5) 34.8 31.9 27.5 27.5 21.7 20.3 Moderate (1.6–2.0) 7.2 10.1 27.5 14.5 14.5 11.6 Severe (2.1–2.5) 1.4 8.7 14.5 5.8 5.8 1.4 Very severe (> 2.5) 0.0 4.3 8.7 5.8 2.9 2.9 AccordingtotheKindexvaluesfortheBanatRegion,BanatskiKarlovacmeteorologicalstationrecords, the presence of very severe rainfall erosivity occurred in 1975 and 2014. On the other hand, the presence ofmoderateerosionclassesisevenlydistributedduringthetwothirty-yearcyclesinthestudyperiod.Bela Crkvastationfollowsasimilarpattern.After1975,anincreaseofverysevereprecipitationclasseshasbeen observed during the studied six-month interval. The most pronounced very severe precipitation erosion classes have been observed for the Vršac station in 1995. During the study period, this station does not record the presence of severe erosion classes except in 2014 (during May, August and September). This observation corresponds with the results of Lukic et al. (2019), who pointed out that the weather station Vršac (MFI – 149.16) and its surroundings have the highest erosivity value for 2014. The Zrenjanin sta­tion records very severe rainfall erosivity classes in 2010 and 2014. The number of precipitation months classified as severe and very severe erosion have been increasing since 1999 (Figure 5). The weather sta­tionKikindadoesnotdisplayextremerainfallerosivity,duringtheinvestigatedperiod.2001ishighlighted as a year where severe erosion occurred in April, June and September. Extreme precipitation sums (reg­istered in 2014) for the weather station of Senta indicate the presence of very severe erosion during May, JulyandSeptember.Yearswiththedistinguishedpresenceofverysevereerosionclasses(33.3%ofthestud­iedprecipitationinterval)are1974,1978,1999,2001and2004.ThisimpliesthattheareasurroundingSenta weather station is somewhat more prone to rainfall erosivity. Figure 5: Mean multiannual values of K Index during the warm part of the year for Banat weather stations. p p. 137–139 137 138 139 According to the K index values for the Backa Region, the Bac weather station in the western part ofVojvodinaRegion,registers severalyears with the two-month precipitationintervalpresence of very severe erosion classes (2001, 2005 and 2014). The presence of low values of the K index corresponds well with the observations provided by Bjelajac et al. (2016). The Backi Petrovac station does not dis­play a higher presence of severe erosion classes during the study period. The years with the presence of severe erosion classes within the 33.3% of the precipitation interval are 1975, 2005 and 2014. On the otherhand,thePalicweatherstationinthenorthoftheVojvodinaprovincegenerallydisplaysanabsence of periods with intensive rainfall erosivity classes. These observations fit well withthe finding of Lukic etal.(2019),thatPalicarearecordsthelowesterosivityvalueintheVojvodinaRegionduring1983(MFI – 8.60). Results for the Rimski Šancevi weather station in the southern parts of Backa Region indicate that an increase of rainfall erosivity can be seen from 1995, with the presence of three-month precip­itation intervals of very severe erosion in 2001. Lukic et al. (2019) indicate that this part of the Pannonian Basin is characterized by periods of irregular precipitation concentration and an increase of MFI values on an annual basis. These features suggest a rather wetter conditions in this part of Vojvodina Region. The Sombor weather station generally registers weaker rainfall erosivity, with an exception of extreme rainy years (Figure 6). According to the K index values forthe Srem Region, the Sremska Mitrovica weather station does not identify higher three-month precipitation intervals of severe and very severe erosion classes. The years 1972, 2001 and 2014 record two-month precipitation intervals of very severe erosion. Three-month pre­cipitation intervals of very severe erosion classes were only present during the extremely rainy 2014. The years of 1975 and 2001 record two-month precipitation intervals of the highest erosion classes. During the period 1946–2014, the highest presence of very low and low rainfall erosivity classes can be observed (Figure 7). Similar approach related to the hydro-meteorological hazard assessment has been performed by Dumitrascu et al. (2017) for the south-western part of Romania. Previously, Dragota et al. (2014) point­edoutthattheDanubeFloodplaindisplaysmoderatetoexcessiverainfallerosivityregime.Authorsemphasize that due to relief configuration, reduced declivity and soil types, moderate, low and very low susceptibil­ityclassesprevailinthestudyarea.Ontheotherhand,Dumitrascuetal.(2017)showedthatmountainous and hilly areas display the highest susceptibility to rainfall erosivity, as it can be observed for south-east­ern parts of the Vojvodina Region (Banat Region with Vršac weather station) (Figure 8). As the altitude drops,severeandverysevereclassvaluesareapproximatelyequallydistributedonamultiannualbasiscor-respondingtothefindingsinaneighbouringcountry.AsobservedfortheRomanianplainandtheDanube valley, very low and low classes dominate, especially in April, August and September, which is in accor­dance with the obtained mean K values for the Vojvodina Region (Figure 8). On the other hand, Lukic et al. (2019) suggest that both the amount and the intensity of precipitation are increasing and varying in some areas of the Pannonian Basin. The trends generally indicate a progressive increase in the values of the erosion by precipitation at the annual level,which in future may lead to the transition to a higher ero­siveclassandincreasethevulnerabilitytothistypeoferosioninthePannonianBasinandVojvodinaRegion. Also, the relief properties and the interaction with the general atmospheric circulation in the study area greatlycontributetothespatialpatternofrainfallerodibilitypotentialintermsofintensity,frequencyand spatial distribution (Figures 3 and 8). These spatial features correspond with the RUSLE soil loss results, presented by Borrelli et al. (2017). In agricultural areas, evaluation of the vulnerability associated with the high impact of rainfall ero­sivityisofutmostimportanceinthecontextofsustainableagriculturalpracticesandspecificlocalorregional climateconditions(KomacandZorn2005;Maracchi,SirotenkoandBindi2005).Accordingly,agoodunder­standingofclimatevariabilityandmainprecipitationfeaturesisofgreatimportance,especiallywhendealing with rainfall erosivity in agricultural areas such as Vojvodina Region. Figure 6: Mean multiannual values of K Index during the warm part of the year for Backa weather stations. p p. 141–143 Figure 7: Mean multiannual values of K Index during the warm part of the year for Srem weather station and the Vojvodina Region. p p. 144 Figure 8: Distribution of the mean K Index classes for the observed period and comparison with the RUSLE soil loss values (adapted after Borrelli et al. 2017). p p. 145 141 142 143 144 In order to protect areas that are potentially endangered by rainfall erosion, it is necessary to assess the intensity of these processes, and then evaluate the negative impact of social structures. As pointed out byPanagosetal.(2015a),rainfallerosivityinEuropeisakeyparameterforestimatingsoilerosionlossand risk in various regions. Authors outline that the European continental climatic zone is characterized by warm summers and cold winters, and thus highly susceptible to the variability of rainfall erosivity. The meanrainfallerosivityfactorforthePannonianzone(centralDanubianbasin)is660.1..mmha-1 h-1 yr-1 and corresponds well with the findings of Mezosi and Bata (2016) and Lukic et al. (2019). The results of NAO and MEI indices were correlated with the mean annual precipitation data for the study area and K index values. Correlation between the teleconnection patterns and precipitation para­meters was estimated in order to investigate the possible relationships between rainfall erosivity and atmospheric variability by applying Pearson’s correlation analysis at the 5% (p < 0.05) significance level. AcorrelationbetweentheNAOindexandprecipitation(–0.19),aswellastheKindex(–0.20),ispresented in Figure 9. The negative correlation coefficient indicates the wetting effect on the K index. Based on con-temporaryfindingsitcanbepointedoutthatNAOconsiderablyaffectsrainfallinthispartofEurope(e.g., Tošic et al. 2014; Lukovic et al. 2015; Radakovic et al. 2018), and since the K index is based on precipita-tionamounts,NAOhasacertaininfluenceonitaswell.AspointedoutbyBiceetal.(2012),NAOgenerally has a strong influence on winter precipitation in the Pannonian Basin, with negative NAO phases corre­sponding to periods of high precipitation. Results of Malinovic-Milicevic et al. (2018) indicate that the amount and intensity of precipitation in Serbia had a statistically significant increase during autumn, and weremostpronouncedinthenorthern(Vojvodina)andwesternpartsofthecountry.Theauthorsshowed that»dry«regimesdominateover»wet«,withanincreasingtrendof»warm«regimesanddecreasingtrend of »cold« regimes. The correlation between the examined extreme indices and the large-scale circulation patterns showed that East Atlantic (EA) and NAO patterns had a significant influence on the duration of winterwarmperiods,whiletheirinfluenceonthedurationofcoldperiodscannotbeconfirmedwithcer­tainty.TheEastAtlantic/WestRussia(EAWR)patternaffectsstatisticallysignificantpositiveautumntrends ofallintensityandfrequencyindices.Inwinter,ithasanimpactonthefrequencyof»dry«and»wet«con­ditionsandtheintensityoftheprecipitation.Ontheotherhand,thecorrelationbetweenMEI andprecipitation (0.006) cannot be confirmed for the given significance level (p <0.05). Hence, no significant correlations were detected between observed precipitation parameters, NAO and MEI, thus generally indicating the absenceofstronglinearitybetweentheK,andthesetwolarge-scaleprocessesofclimatevariability.Asshown by Dehghani et al. (2020), large-scale circulation drivers have a considerable impact on precipitation in different regions, where various climate indices in different phases may decrease the seasonal precipita-tion(evenupto100%).Ontheotherhand,seasonalprecipitationmayincreasemorethan100%indifferent seasons due to the impact of these indices. 5 Conclusion Soil erosion by water has often been overlooked (Zorn 2015) as an important land degradation (Zorn and Komac 2013b) and environmental problem. In the Soil Thematic Strategy of the European Commission (Communication…2006) it is listened among the eight main threats to soil in the EU (Panagos 2015b). In this study the K index was used to determinate the characteristic types of monthly and annual variation of precipitation based on regional and local comparisons. Results of this study indicate that theVojvodinaRegionhasexperiencedthepresenceofvarioussusceptibilityclassesofprecipitationliable fortriggeringsoilerosionfromApriluntilSeptember.JuneandJulyarethemonthswithhigherfrequency ofverysevereerodibilityclasses,withthedistributionof 8.70%and 5.80%,respectively. Mostofthe dis­tributed erodibility classes observed for the study area belong to moderate, varying from7.25% (in April) up to 27.54% (in June). On the other hand, a progressive increase in the values of the rainfall erosiv­ity atthe annual level (induced by climatevariability), in the futurecan leadto thetransition toa higher erosive class and increase the vulnerability to rainfall erosion in the Pannonian continental climatic zone. Figure 9: Correlation between NAO and precipitation (a), NAO and K Index (b), and MEI and precipitation (c). p p. 147 a) NAO (x)–Precipitation (y) correlation 2 –2 –1 1 2 3 –2 –4 b) NAO (x)–Angdot index (y) correlation 2 –2 –1 1 2 3 –2 –4 c) MEI (x)–Precipitation (y) correlation 2 -2 -1 1 2 3 -2 -4 As precipitation is seen as one of the main triggering factors for flash floods, landslides, and soil ero­sion, future extreme weather events are likely to have seriously damaging effects on crops and pastures, thus changing the land use and land cover. In the further research it is necessary to look more into the relationship between NAO and its impact onchangesinseasonalprecipitation.ForSerbia,thesechangesshouldbeinvestigatedindetailusingawet seasonconceptbetweenOctoberandMarch,aspreviouslydiscussedbyLukovicetal.(2015).Thisapproach maybesuitablesinceitcouldinvestigatetheprobabilityofanincreaseordecreaseinprecipitationamounts associated with the above-mentioned indices and seasonal rainfall erosivity rates as well. ACKNOWLEDGEMENTS:TheauthorsacknowledgethefinancialsupportoftheMinistryofEducation, ScienceandTechnologicalDevelopmentoftheRepublicofSerbia(GrantNo.451-03-68/2020-14/200125). ApartoftheresearchwassupportedbytheH2020WIDESPREAD-05-2020–Twinning:ExtremeClimTwin that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952384, and the Slovenian Research Agency research programme Geography of Slovenia (grant No. P6-0101). 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DOI: https://doi.org/10.1007/978-1-4020-4399-4_207 THE INFLUENCE OF CLIMATE CHANGE ON DISCHARGE FLUCTUATIONS IN SLOVENIAN RIVERS Janij Oblak, Mira Kobold, Mojca Šraj High waters of the Kamniška Bistrica River in 2007. DOI: https://doi.org/10.3986/AGS.9942 UDC: 556.16:551.583(497.4) COBISS: 1.01 Janij Oblak1, Mira Kobold1,2, Mojca Šraj1 The influence of climate change on discharge fluctuations in Slovenian rivers ABSTRACT:Inrecentdecades,anincreaseinthenumberofextremefloodeventsaswellasextremedrought eventshasbeenobservedinSlovenia.Thisrisetheneedforacomprehensiveanalysisoftrendsindischarge data series. In the study, statistical trends in seasonal and annual mean, maximum, extreme and low dis­charge values were investigated using the Mann Kendall test. The results show a temporal and spatial variabilityoftrendsindischarge.Ingeneral,adecreasingtrendinwaterquantitiesintheriverswasobserved. However, results at some gauging stations indicate statistically significant increasing trends, especially for maximumandextremedischarges.Additionalanalysesshowthatthedischargetrendsdependontheloca­tion of the gauging station. KEY WORDS: hydrology, geography, trend analysis, Mann Kendall test, discharges, Slovenia Vpliv podnebnih sprememb na nihanja pretokov v slovenskih rekah POVZETEK: V zadnjih desetletjih v Sloveniji opažamo povecanje števila tako ekstremnih poplavnih kot tudi ekstremnih sušnih dogodkov. To kaže na potrebo po kompleksni analizi trendov v serijah podatkov opretokih.VraziskavismospomocjotestaMannKendallanaliziralistatisticnetrendesezonskihinletnih povprecnih, najvecjih, ekstremnih in nizkih vrednosti pretokov. Rezultati kažejo casovno in prostorsko spremenljivosttrendovpretokov.Vsplošnemsmozaznalitrendzmanjševanjakolicinvodevrekah.Rezultati nekaterih vodomernih postaj pa kažejo na statisticno znacilno narašcajoce trende, zlasti za najvecje in ekstremne pretoke. Dodatne analize kažejo, da so trendi pretokov odvisni od lokacije vodomerne postaje. KLJUCNE BESEDE: hidrologija, geografija, analiza trenda, Mann Kendallov test, pretoki, Slovenija The article was submitted for publication on May 4th, 2021. Uredništvo je prejelo prispevek 4. maja 2021. 1 University of Ljubljana, Faculty of Civil and Geodetic Engineering, Ljubljana, Slovenia janij.oblak@gmail.com, mira.kobold@gov.si, mojca.sraj@fgg.uni-lj.si (https://orcid.org/0000-0001-7796-5618) 2 Slovenian Environment Agency, Ljubljana, Slovenia mira.kobold@gov.si 1 Introduction A recent study by Blöschl et al. (2019) demonstrated that no uniform pattern in trends of flood discharge seriescanbefoundinEuropeinthepastfivedecades.Theyidentifiedthreeregionalpatternsofbothincreas­ing and decreasing trends in flood discharges in Europe. Floods are becoming increasingly severe in northwesternEurope,whiletheirintensityisdecreasinginsouthernandeasternEurope.Increasingfloods in northwestern Europe are the result of increasing autumn and winter precipitation, while the decreas­ing trend of flood events in southern Europe is the result of decreasing precipitation and increasing evaporation. However, the decreasing snow cover due to global warming is the reason for the decrease in flooding in Eastern Europe. The average increasing trend of floods in Europe is up to 11% and decreas­ing by up to 23% per decade (Blöschl et al. 2019). Similarly, Mediero et al. (2015) found a mixed pattern of changes in flood frequency and few significant changes in the flood timing at a pan-European scale by usingthelongeststreamflowrecords.Theyidentifiedastrongerfield-significantdecreasingtrendsinflood magnitude in the Atlantic region comparing the periods 1920–1999 and 1956–1995 as well as in the Continentalregioncomparingtheperiods1900–1999and1939–1998.Anuncleartrendpatternwasfound intermsofannualnumberoffloodsaboveathreshold,apartfromadecreasingtrendintheAlpineregion for all the periods considered. No clear trend patterns were found with respect to the timing of floods, apartfromfield-significantincreasingtrendsinthecontinentalregionanddecreasingtrendsintheAlpine region in the period 1900–1999 (Mediero et al. 2015). In neighbouring Austria, annual maximum floods for the period 1976–2007 showed increasing trends in 17% of the catchments with a general tendency for increasing trends in the north, decreasing trends in the south, increasing trends in winter floods in the west and decreasingtrends in the southeast (Hall et al. 2014). The majority of the stations showed no sig­nificant change. For the Alpine region of France, Switzerland, Germany, Italy, Austria and Slovenia, an increasing trend in spring floods associated with snowmelt is found during 1961–2005 (Hall et al. 2014). In Slovenia, due to high climatic diversity, the magnitude and frequency of flood events is expectedto increase at some gauging stations and decrease in others (Bezak, Brilly and Šraj 2016; Kovacic 2016;Šrajetal.2016;Šraj,MenihandBezak2016;HrvatinandZorn2017a;ŠrajandBezak2020).Furthermore, an increase in torrential flooding is expected due to the increase in local convective precipitation (Blöschl et al. 2019). Indeed, Slovenia has faced an increasing number of flood events causing high damage and even fatalities (Zorn and Komac 2011; Komac and Zorn 2020). Analyses show that extreme flood events haveoccurredmorefrequentlysince1990thanbefore(Kobold,DolinarandFrantar2012).Tonameafew,theŽeleznikifloodin2007claimedsixlives(Kobold2008),in2010partofLjubljanawasflooded(Strojan et al. 2010), and in 2012 Drava River flooded due to increased runoff from neighbouring Austria (Klanecek2013).Furthermore,in2014,Sloveniaexperiencedatotalof83dayswithhighhydrologicalcon­ditionsinatleastonerivercatchment(GolobandPolajnar2016),floodingkarstpoljes(FrantarandUlaga 2015), part of the capital was flooded again (Fazarinc 2014), and the Bolska stream with two fatalities and the Mislinja River with one fatality showed their strength again. On the other hand, temperature changes and uneven temporal and spatial distribution of precipita­tion(HrvatinandZorn2017b;Ocenatveganjazasušo2017;Cunja,KoboldandŠraj2019)areincreasingly causingwaterscarcityanddroughtsinSloveniaaswell(Kajfež-BogatajandBergant2005;Sušniketal.2013;Šebenik,BrillyandŠraj2017;Cunja,KoboldandŠraj2020;Jelen,MikošandBezak2020).After1990,agri­cultural drought was declared 11 times in Slovenia, 9 of since 2000 (2000, 2001, 2003, 2006, 2007, 2009, 2012, 2013, 2017). In most of these years, the drought reached the level of a natural disaster, which means that the estimated direct damage exceeded 0.3‰ of the planned state budget revenue (Ocena tveganja za sušo 2017). Giventhatanincreasednumberofbothextremefloodevents(Kobold,DolinarandFrantar2012)and extreme drought events (Sušnik et al. 2013; Ocena tveganja za sušo 2017) have been observed in Slovenia inrecentdecades,theneedforcomprehensiveanalysesoftrendsindifferenttypesofdischargedataseries arose.Therefore,themainobjectivesofthestudyweretoinvestigatetrendsin(i)seasonalandannualmean discharge values (Qs), (ii) seasonal and annual maximum mean daily discharge values Qvp, (iii) extreme seasonal and annual flood discharge values defined by the peak-over-threshold method with an average ofone(POT1)andthree(POT3)peaksperyearand(iv)seasonalandannuallowdischargeindicesdescrib­ing the 7- and 30-day duration of low flows (Qmin7 and Qmin30). 2 Data and methods Analyseswereperformedbasedondailydischargedataseries(Arhivhidrološkihpodatkov2017)at40gaug­ing stations in Slovenia (Table 1 and Figure 1). The criteria for inclusion of individual gauging station into thestudywereasfollows:(1)atleast52yearsofdata(1961–2013),(2)nogapsinthedataseries,(3)uniform Table 1: List of gauging stations studied with associated catchment area (Arhiv hidroloških podatkov 2017). Station code Main catchment Gauging station River Catchment area [km2] 1060 Mura River Gornja Radgona Mura 10,197.2 1140 Pristava Šcavnica 272.5 1220 Polana Ledava 208.2 2250 Drava River Otiški Vrh Meža 550.9 2650 Videm Dravinja 763.8 2750 Tržec Polskava 187.8 2900 Zamušani Pesnica 477.8 3200 Sava River Sveti Janez Sava Bohinjka 94.0 3420 Radovljica Sava 908.0 3570 Šenjakob Sava 2,284.8 3650 Litija Sava 4,821.4 3840 Catež Sava 10,185.8 4120 Kokra Kokra 112.3 4480 Nevlje Nevljica 82.0 4670 Martinja vas Mirna 164.6 4820 Kolpa River Petrina Kolpa 460.0 4850 Radenci Kolpa 1,191.0 4860 Metlika Kolpa 2,002.0 4970 Gradac Lahinja 221.3 5030 Ljubljanica River Vrhnika Ljubljanica 1,135.1 5080 Moste Ljubljanica 1,762.5 5540 Razori Šujica 46.9 5880 Hasberg Unica Karst 6060 Savinja River Nazarje Savinja 457.3 6200 Laško Savinja 1,663.6 6240 Kraše Dreta 100.8 7030 Krka River Podbukovje Krka 321.4 7160 Podbocje Krka 2,238.1 7340 Precna Precna 294.2 7380 Škocjan Radulja 108.0 8060 Soca River Log Cezsoški Soca 324.7 8080 Kobarid Soca 437.0 8270 Žaga Ucja 50.2 8350 Podroteja Idrijca 112.8 8450 Hotešk Idrijca 442.8 8500 Baca pri Modreju Baca 142.3 8590 Dornberk Vipava 468.5 8600 Miren Vipava 590.0 8630 Ajdovšcina Hubelj 93.2 9050 Coastal Rivers Cerkvenikov mlin Reka 377.9 Figure 1: Location of the considered gauging stations coloured according to the associated river catchment. p spatial distribution of stations covering different flow regimes, and (4) data from the catchments with the least possible anthropogenic influence or where the influence of human activities, such as deforestation, urbanization,constructionofreservoirs,waterabstractionisminimal(Kundzewiczetal.2005).Thechoice of the end of the time period under consideration is related to the missing data. Slovenian Environment AgencycarriedouttherenovationofSloveniangaugingstationswithintheBOBERproject(Roškar2015) in 2014–2016 and there was a data outage (semi-annual and more) at most gauging stations during these years. Statistical trends were investigated using seasonal and annual mean discharge values (Qs), seasonal andannualmaximummeandailydischargevaluesQvp,extremeseasonalandannualflooddischargeval-uesdefinedbypeak-over-thresholdmethod(POT)withanaverageofone(POT1)andthree(POT3)peaks peryear,andseasonalandannuallowdischargeindicesdescribingthe7-and30-daysdurationoflowdis-charges (Qmin7 and Qmin30). POT samples were defined using Hydrospect software (Radziejewski 2011). More details about thePOT method can be found in (Bezak, Brilly and Šraj 2014). In order to detect trends in aforementioned datasamplesnon-parametricMannKendall(MK)testwasapplied(Kendall1975)(Equations1-3),which isoneofthemostcommonlyusedtestsfordetectingtrendsinhydro-meteorologicaldata.Itsgreatestadvan­tage is that it is robust against missing values and ties in the data and does not require normality of thedata (e.g., Douglas, Vogel and Kroll 2000; Strupczewski, Singh and Feluch 2001; Šraj et al. 2016). The null hypothesis of the MK test is that there is no trend in the series and the alternative hypothesis is that thereis either positive or negative trend in the tested series (Bezak, Brilly and Šraj 2016). The MK test statistic t is defined as follows (Douglas, Vogel and Kroll 2000): (1) (2) (3) where x is the discharge value at time i and j, and n is the sample length. Kendall package (McLeod 2011) implemented in R software (R Core Team 2013) was used for the trend analyses. The significance levels of0.05and0.1wereappliedtoidentifythestatisticalsignificanceofthetrendsinthedataseries.Additionally, the presence of serial correlation in the data series was investigated in order to avoid incorrectly reject­ing the null hypothesis of no trend in the time series (Yue, Pilon and Cavadias 2002; Šraj et al. 2016). 3 Results and discussion 3.1 Trend analysis The results of the trend analyses for all considered data series are presented in Figure 2. The analysis of the mean discharge values (Qs) shows that the mean annual discharges decreased during the period 1961–2013atalltheconsideredstations,statisticallysignificantatmostofthem(25atthesignificantlevel of 0.05 and 6 at the significant level of 0.1). This finding is consistent with the results of Frantar, Kobold andUlaga(2008),whoanalysedthetrendsofmeandischargesatthe22gaugingstationsinSloveniausing the data for the whole observations period up to and including the year 2005. Obviously, the decreasing trend of mean discharges continues 10 years later. Further analysis by season shows that the decrease in mean discharge in the summer and spring seasons is statistically significant for the majority of the gaug­ingstationsconsidered.Infact,theriversoftheAdriaticcatchmenthaveastatisticallysignificant decrease inmeandischargeinthesummerseasonandtheriversoftheBlackSeacatchmentinthesummerandspring seasons.Themeandischargesinwinterandautumnmostlydonotshowstatisticallysignificanttrends.The decreaseinmeandischargesismostlytheconsequenceofthedecreaseinprecipitationandtheincreasein temperature,whichinturnincreasesevapotranspirationinrecentdecades(Frantar,KoboldandUlaga2008; Figure 2: Results of trend analyses for the period 1961–2013. p Ocena tveganja za sušo 2017; Macek et al. 2018; Šraj, Mikoš and Bezak 2019). The results are consistent with those published by Stahl et al. (2010), who came to a regionally coherent picture of annual discharge trendswithnegativetrendsidentifiedmainlyintheheadwatercatchmentsofthelargerrivers(e.g.Danube River) of Austria and Germany, Czechia and Slovakia, while positive trends were identified for the main streams of the larger rivers. The annual maximum mean daily discharges (Qvp) do not show such a uniform trend as the meanannual discharges (Figure 2). Two gauging stations, Precna (7340) and Škocjan (7380) in the Krka River catchmentshowastatisticallysignificantincreasingtrend(atthesignificantlevelof0.1)intheannualmax­imum discharge series. Previous studies have shown also that some gauging stations in Slovenia have statisticallysignificanttrendsintheannualmaximumfloodseries(Kobold,DolinarandFrantar2012;Bezak,Brilly and Šraj 2016; Šraj, Menih and Bezak 2016). For example, Škocjan gauging station (7380) on the Radulja River with a statistically increasing trend in annual maximum discharges is one of the stations, that have been investigated in detail in some other studies investigating the impact of variable climate onfloods in Slovenia (Šraj, Menih and Bezak 2016; Šraj and Bezak 2020). A detailed study of the relation­shipbetweenannualmaximumdischargesandannualprecipitationhavedemonstratedagoodcorrelationbetween high annual precipitation and high discharges for Škocjan at the Radulja River (Šraj, Menih and Bezak2016).Ontheotherhand,10gaugingstationsshowstatisticallysignificantdecreasingtrendsinannu­al maximum discharge series (7 at the significant level of 0.05 and 3 at the significant level of 0.1). Stations with a decreasing trend are located in various river catchments; however, most of them in the Soca River catchment. TheriversoftheAdriaticSeacatchmentmostlydemonstrateastatisticallysignificantdecreas-ingtrendinthemaximumdischargesinthespringandsummerseasons,whilewecannotgiveunambiguous conclusions for the rivers of the Black Sea catchment. We can only state that we have quite a few stations in the Ljubljanica and Kolpa river catchments with a statistically significant decrease in the annual max-imumdischargesinsummer.Wecanmakeageneralstatementthattheresultsofthetrendsofthemaximum annual discharges (Qvp) indicate regional diversity with a predominantly decreasing trend, which is in agreement with the results of Frantar, Kobold and Ulaga (2008). Theresultsofthetrendanalysisoftheextremeannualdischargevaluesdefinedbythepeak-over-thresh­oldmethod(POT)withanaverageofone(POT1)andthree(POT3)peaksperyearalsoshownouniform trend. However, compared to the trends in the annual maximum discharges, even more gauging stations demonstratethestatistically increasingtrendintheextremedischargeseries.8 gaugingstations showsta­tistically significant increasing trends in POT3 data series (4 at the significant level of 0.05 and 4 at the significant level of 0.1) and 6 gauging statins in POT1 data series (5 at the significant level of 0.05 and 1 at the significant level of 0.1). Most of them are located in the Ljubljanica and the Krka River catchments (Figure 2). Among 40 stations considered, only station Kraše (6240) at the Dreta River shows a statisti­cally significant decreasing trend for POT3 data series. Seasonal analysis show that the increasing trend ofextremedischargesisstatisticallysignificant,especiallyintheautumnfollowedbyspring.Frantar,Kobold and Ulaga (2008), who analysed trends of discharges at the 22 gauging stations in Slovenia using the data for the whole observation period until 2005, reported an increasing trend for the POT1 data series onlyfortheŠcavnicaRiver.However,theyreportedthatthenumberofgaugingstationswithanincreasingtrend increasedincaseofthePOT3dataseries.Thus,itseemsthatthenumberofextremefloodeventshasincreased in recent years. Annual low discharges with a duration of 7 days (Qmin7) decrease statistically significantly for the rivers of the Black Sea catchment (Figure 2). The Kolpa, Ljubljanica and Savinja rivers show statistically significantdecreasingtrendforallanalysedgaugingstations,whiletheMura,Drava,Sava,andKrkarivers showastatisticallysignificantdecreasingtrendformostoftheconsideredstations.TheriversoftheAdriatic Sea catchment show no uniform trends as 5 gauging stations in the Soca River catchment demonstrate statistically significant decreasing trend and 4 stations do not show any statistically significant trend. All together 30 out of 40 gauging stations show a statistically significant decreasing trend (27 at the signifi­cant level of 0.05 and 3 at the significant level of 0.1). Qmin7 discharges decrease at most of the stations in the summer, while in the Kolpa, Ljubljanica and Krka catchments also in the autumn season and in the Drava, Sava, Kolpa, Ljubljanica, KrkaandSoca catchments also in the spring season. Frantar, Kobold and Ulaga (2008) reported an increasing trend of low discharges in the karstic and eastern areas of Slovenia usingthedataforthewholeobservationperiodupto2005.However,theyarguedthatthenumberofgaug­ing stations with an increasing trend is getting smaller, while the number of those with a decreasing trend increase. The results of this study demonstrate that for the period 1961–2013 none of the considered sta­tions has a statistically significant increasing trend in data series of annual low discharges with a duration of7days(Qmin7)anymore.IncomparisonwithotherEuropeancountries,thestudybyStahletal.(2010) showedthatlowdischargeshavedecreasedinmostregions,wherethelowestmeanmonthlydischargeoccurs insummer,butvaryforcatchments,whichhavedischargeminimainthewinterseasonandsecondarylow discharge in summer. In most of western and central Europe, the lowest discharge occurs in late summer, between July and September. In the Alps and northern Europe, the annual minima occur in January and February (Stahl et al. 2010). Very similar results are observed in the trend analysis of annual low discharges with a duration of 30 days(Qmin30).Overall,together31outof40gaugingstationsdemonstratestatisticallysignificantdecreas­ing trend (28 at the significant level of 0.05 and 2 at the significant level of 0.1) (Figure 2). Additionally, seasonaltrendanalysisindicatesthatsummerlowdischarges(Qmin30)showastatisticallysignificantdecreas­ing trend for 36 stations considered. 3.2 Analysis of station location influence Since precipitation in Slovenia typically decreases in the direction from west to east, we performed addi­tionalanalysesoftheinfluenceofthewatergaugingstationlocationontheresultsofthecalculateddischarge trends. The analysis was performed using annual and seasonal values for all selected data series, namely Qs, Qvp, POT3, POT1, Qmin7 and Qmin30. The analysis shows that the mean annual discharges (Qs) are decreasing across the country regard-lessofthelocation,mostofthemstatisticallysignificantly(Figure3).Aswenotedearlier,theannualmaximum mean daily discharges (Qvp) do not show as consistent trends as the mean annual discharges. Statistically significantdecreasingtrendsofQvpmostlyoccurinthewesternandcentralpartofSlovenia,whilestatis­tically significant increasing trends mostly occur in the eastern and central part of the country (Figure 3). Furthermore, the extreme annual flood discharge values (POT1 and POT3) do not show statistically sig­nificant decreasing trends, with the exception of the POT3 data series at Kraše gauging station at Dreta River. Statistically significant increasing trends of the POT3 data series were found mainly in the east of the country, while in case of POT1 data series statistically significant increasing trends occur regardless ofthelocation.Annuallowdischargeswithadurationof7days(Qmin7)and30days(Qmin30)haveasta­tisticallysignificantdecreasingtrendatmostoftheconsideredstationsregardlessofthelocation(Figure 3). Analysis by season shows that mean summer discharges (Qs) have a statistically significant decreas­ingtrendthroughoutthecountrywiththeexceptionoftheeasternpart,wheredecreasingtrendsaremostly not statistically significant (Figure 4). In addition, the largest summer discharges (Qvp) in Slovenia are mostly statistically significantly decreasing, with the exception of some stations in the eastern part of the country, where the trends are increasing, but not statistically significant. The same is true for the summer lowdischarges(Qmin7andQmin30),whichmostlyshowstatisticallysignificantdecreasingtrendsacross the country regardless of the location (Figure 4). Mean autumn discharges (Qs) are mostly decreasing; however, the trend is statistically significant for two stations. Location does not appear to affect these results (Figure 5). The same can be concluded for the largest autumn discharges (Qvp). Stations with statistically significant decreasing trends are found in the eastern, western and central parts of the country. On the other hand, the extreme autumn flood dis­charges are mostly increasing, especially the POT1 data series. Stations with the statistically significant increasing trend in the POT1 and POT3 values are mainly located in the central part of Slovenia. Autumn low discharges (Qmin7 and Qmin30) mostly show decreasing trends (Figure 5). However, they are not as pronounced as for the summer low discharges, especially in the eastern and western part of Slovenia. Statistically significant decreasing trends in mean winter discharges (Qs) are characteristic mainlyfor theeasternpartofthecountry.Thesameistrueforthelargestwinterdischarges(Qvp).Theextremewin­terdischargesshowdecreasingandincreasingtrends.Stationswithstatisticallysignificantincreasingtrends Figure 3: Trends in annual values of discharge data series for the period 1961–2013, plotted in west-east direction. p p. 164 Figure 4: Trends in summer values of discharge data series for the period 1961–2013, plotted in west-east direction. p p. 165 Figure 5: Trends in autumn values of discharge data series for the period 1961–2013, plotted in west-east direction. p p. 166 in POT3 values are located in the eastern and central parts of the country, while stations with statistical­lysignificantincreasingtrendsinPOT1valuesarelocatedinthewesternpartofthecountry.Furthermore, threestationsshowingstatisticallysignificantdecreasingtrendsinPOT1dataseriesarelocatedinthecen­tralpartofthecountry.Winterlowdischarges(Qmin7andQmin30)showmostlydecreasingtrends,which are less pronounced in the western part of the country. Theresultsforthespringdischargedataseriesareverysimilartothesummerresults,butlesspronounced. Meanspringdischarges(Qs)aredecreasingthroughoutthecountry.Mostofthemarestatisticallysignificant, except in the western part where the trend is not statistically significant. Furthermore, the largest spring discharges(Qvp)havemostlystatisticallysignificantdecreasingtrend,exceptforsomestationsintheeast­ern part of the country, where the trends are increasing, but not statistically significant. Extreme spring discharge values (POT1 and POT3) do not show consistent trends as they increase at some stations and decreaseatothers.Statisticallysignificantdecreasingtrendsinextremedischargeswerefoundatsomesta­tionsinthewesternandcentralpartsofthecountry,whereasstatisticallysignificantincreasingtrendswere found in the eastern and central parts of the country. Location does not appear to have the influence on trends of the spring low discharges. 4 Conclusion Theresultsofthestudyshowthatclimatevariabilityduringtheconsideredperiod(1961–2013)influences the temporal and spatial variability of discharges and associated floods and droughts in Slovenia. In gen-eral,adecreaseinwaterquantitiesintheriverswasobserved.SimilarconclusionsweredrawnalsobyFrantar, Kobold and Ulaga (2008) using the data for the whole observation period until 2005. Thus, it seems that similar trends continue also a decade later. Meanannualdischargesaredecreasingatallstationsconsidered,statisticallysignificantatmostofthem. Furthermore, the rivers of the Adriatic catchment demonstrate a statistically significant decrease in mean discharges in the summer season and the rivers of the Black Sea catchment in the summer and springsea-sons. On the other hand, the maximum mean daily discharges do not show such uniform trends as the mean discharges as some gauging stations exhibit statistically significant trends in annual maximum dis­charge series. However, despite the fact that the results of the trends of the maximum annual discharges indicate regional differences, a predominantly decreasing trend was observed. The rivers of the Adriatic Sea catchment mostly demonstrate a statistically significant decreasing trend in the maximum discharges inthespringandsummerseasons,whiletheriversoftheBlackSeacatchmentdonotshowuniformtrends. The extreme annual discharge values also do not show a uniform trend; however, even more gauging sta­tions show a statistically increasing trend compared to the trends in maximum discharges. Most of them are located in the Ljubljanica and the Krka River catchments. Furthermore, the results of the trend analy­sisoflowdischargesdemonstratestatisticallysignificantdecreasefortheriversoftheBlackSeacatchment, whilefortheriversoftheAdriaticSeacatchmentsomestationsdonotshowstatisticallysignificantchanges. Lowdischargesdecreaseinsummeratmoststations,whileinsomecatchmentstheyalsodecreaseinautumn and spring. The results show that the discharge trends depend to some extent on the location of the gauging sta­tion. This was to be expected due to the great climatic and landscape diversity in Slovenia. The findings of the study related to the trends of different types of discharge data series should be taken into account in practice, e.g. for effective water management, flood protection, granting permits for water abstraction, designing of irrigation systems. 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DOI: https://doi.org/10.3986/AGS51101 THE ROLE OF ECOTOURISM IN COMMUNITY DEVELOPMENT: THE CASE OF THE ZASAVICA SPECIAL NATURE RESERVE, SERBIA Vladimir Stojanovic, Dubravka Milic, Sanja Obradovic, Jovana Vanovac, Dimitrije Radišic Visitor center in the Zasavica Special Nature Reserve. DOI: https://doi.org/10.3986/AGS.9411 UDC: 91:338.48-6:502/504(497.11) COBISS: 1.01 Vladimir Stojanovic1, Dubravka Milic2, Sanja Obradovic1, Jovana Vanovac2, Dimitrije Radišic1,2 The role of ecotourism in community development: The case of the Zasavica Special Nature Reserve, Serbia ABSTRACT: This study explores local community attitudes toward ecotourism as a form of sustainable tourismintheZasavicaSpecialNatureReserveinSerbiausingtheSustainableTourismAttitudeScale(SUS-TAS).ResidentsoftheZasavicaSpecialNatureReserveacknowledgethesocioculturalandeconomicbenefits of ecotourism development while recognizing the negative impacts of development on the natural envi­ronment. Low awareness of non-charismatic species among residents contrasts with strong awareness of them among large communities of scientists and naturalists in Serbia. This study shows the importance of local community support for ecotourism and conservation development. Moreover, the study revealed that the SUS-TAS scale can be successfully applied in ecotourism research. KEY WORDS: ecotourism, sustainable development, local community, local residents, attitude, protected areas, Sustainable Tourism Attitude Scale Vloga ekoturizma pri razvoju skupnosti: Primer posebnega naravnega rezervata Zasavica, Srbija POVZETEK:Vclankuraziskujemoodnoslokalneskupnostidoekoturizmakotobliketrajnostnegaturiz­ma v posebnem naravnem rezervatu Zasavica v Srbiji z lestvico odnosa trajnostnega turizma. Prebivalci posebneganaravnegarezervataZasavicapriznavajodružbeno-kulturneingospodarskekoristirazvojaeko­turizma, hkrati pa prepoznavajo negativne vplive razvoja na naravno okolje. Med prebivalci zaznavamo nizko ozavešcenost o pomenu nekarizmaticnih rastlinskih vrst, kar je v nasprotju s stališci velike skup­nostiznanstvenikovinnaravoslovcevvSrbiji.Clanekkaženapomenpodporelokalneskupnostizarazvoj ekoturizma in ohranjanja narave. Poleg tega je študija pokazala, da je mogoce lestvico SUS-TAS uspešno uporabiti pri raziskavah ekoturizma. KLJUCNE BESEDE: ekoturizem, trajnostni razvoj, lokalna skupnost, lokalni prebivalci, odnos, zašcitena obmocja, Lestvica odnosa do trajnostnega turizma The article was submitted for publication on March 17th, 2021. Uredništvo je prejelo prispevek 17. marca 2021. 1 University of Novi Sad, FacultyofSciences,Department of Geography, Tourism andHotel Management, Novi Sad, Serbia vladimir.stojanovic@dgt.uns.ac.rs (https://orcid.org/0000-0001-6792-2841), sanjaobradovic992@gmail.com (https://orcid.org/0000-0001-9339-1570), dimitrije.radisic@dbe.uns.ac.rs (https://orcid.org/0000-0003-2716-9829) 2 University of Novi Sad, Faculty of Sciences, Department of Biology and Ecology, Novi Sad, Serbia Novi Sad, Serbia dubravka.milic@dbe.uns.ac.rs (https://orcid.org/0000-0002-8828-1489), jovanavanovac@yahoo.com, dimitrije.radisic@dbe.uns.ac.rs (https://orcid.org/0000-0003-2716-9829) 1 Introduction Sustainabledevelopmentandsustainabletourismarecomplementary(Stojanovicetal.2014;Espiner,Orchiston andHigham2017).Sustainabledevelopmentisadevelopmentconceptthatemphasizesthebalanceofeco­nomic, environmental, and social approaches. The main assumption is that preserving the environment will lead to an increase in tourist visits. Accordingly, it can be argued that a protected nature resort can provetobeapopulartouristdestinationandeventuallydeveloptowardecotourism(Diamantis1999;Hermon 2016; Putra et al. 2018). Ecotourism is growing rapidly worldwide and is predicted to be one of the main growth areas in the coming years (Arlym and Hermon 2019). Using the Zasavica Special Nature Reserve (SNR) in Serbia as an example, this article identifies local residents’ attitudes toward sustainable tourism development.WeappliedtheSustainableTourismAttitudeScale(SUS-TAS)developedbyChoiandSirakaya (2005)toassesslocalperceptionsofconservation.Itisimportanttoemphasizethatecotourismdiffersfrom otherformsoftourismbyitsobjectives.Itaimstoformcloselinksbetweennaturalandculturalenvironments, which makes it the most valuable form of sustainable tourism (Stefanica and Vlavian-Gurmeza 2010; Burgoyne and Mearns 2020). Education and awareness raising among residents about the importance of ecosystems is crucial and can help local communities better appreciate the importance of protected areas. One way in which pro­tected areas can have a positive social impact is by ensuring that the costs and benefits of conservation are shared equitably. If this is achieved, local communities can more readily recognize protected areas as important resources that can improve their livelihoods and contribute to the development of their com­munities – for example, through the development of ecotourism (Abukari and Mwalyosi 2020). This article analyzes 1) local residents’ attitudes about the importance of involving residents in eco­tourismdevelopment,2)whetherrespondents’socio-demographiccharacteristicsinfluencetheirattitudes toward ecotourism as a form of sustainable tourism development, and 3) the extent to which the com­munity has a positive attitude toward ecotourism development and residents’ willingness to be involved in tourism planning and decision-making processes. 2 Theoretical background Many researchers claim that ecotourism seems to meet most of the objectives set out in the definition of sustainabletourismbecauseitisatoolforbothsocialempowermentandlong-termeconomicdevelopment oflocalcommunities(WeaverandLawton2007;Caric2018;Ramón-Hidalgoetal.2018;Gracietal.2019). The involvement of local communities in ecotourism is one of its core rules (Senko et al. 2011; Kihima and Musila 2019; Albu 2020). There is an ethical dimension to the collaboration of these communities in ecotourism projects because local communities should benefit from such a relationship (Abdullah, Weng and Som2011; Eshun and Tichaawa 2020). Local residents need to be involved in the planning and devel­opment of ecotourism projects from the early stages to maximize the positive effects of ecotourism. To fullyparticipateintheplanningprocess,theyneedtobeawareoftheimpactsandsupportiveofthedevel­opment.Itisalsoimportantthatthelocalcommunityhave»abasiclevelofawarenessofthepotentialbenefits andcostsoftourism«tosuccessfullyparticipateintheplanningprocess(KhoalenyaneandEzeuduji2016; Thetsane2019).Assessmentofecotourismawarenesscanbemeasuredbyunderstandingthehostcommunity’s attitudestowardthepositiveandnegativeenvironmental,economic,andsocialimpactsofecotourism(Adetola and Adediran 2014; Milheiras 2019). Community involvement is a process of working together (McCloskey et al. 2013). It has been found that the involvement and active participation of local residents plays a vital role in implementing conser­vation programs and helps conserve national heritage and take good care of protected areas (Jaafar, Noor and Rasoolimanesh 2015). Moreover, lack of resident participation reduces the value of heritage sites and protected areas (Buta, Holland and Kaplanidou 2014; Majid et al. 2019). During the last decade, studies on residents’ attitudes toward tourism development have increased (McGeheeandAndereck2004;DiedrichandGarcía-Buades2009;SoldicFrletaandSmolcicJurdana2020), and conceptual models and theories have sought to explain the relationship between residents’ attitudes toward tourism development (Mohammadi and Khalifah 2014; Hsu, Chen and Yang 2019; Biju and Biju 2020). Protected areas managed as ecotourism sites play an important role in generating much-needed revenue to finance biodiversity conservation and improve the income of local communities (Belete and Assefa2005;Abeli2017).Whenitcomestoecotourismplanningandmanagement,becauselocalresidents that interact directly with tourists are indirectly the most important stakeholders, it is essential to ensure their positive perceptions and attitudes toward tourism (Lee 2013; Bhat and Mishra 2020). Previous studies on this topic have suggested that ecotourism and other types of sustainable tourism development initiatives would not succeed without the cooperation, support, goodwill, and participation of local residents (Chen, Li and Li 2017; Eusébio, Vieira and Lima 2018; McCaughey, Mao and Dowling 2018). In light of this, the involvement of local residents in decision-making and their positive attitude towardtourismisessentialfortourismsustainability(Canalejoetal.2015;Panyik2015).Empoweredcom­munities are able to benefit more from tourism development opportunities and use these opportunities more constructively (Chen, Li and Li 2017; Bittar Rodrigues and Prideaux 2018). 3 Methods 3.1 Case study area The Zasavica Special Nature Reserve (SNR) is located in the southern part of the province of Vojvodina, Serbia. It extends across the territories of the municipalities of Sremska Mitrovica and Bogatic and cov­ers an area of 671 hectares, and the protected zone covers an area of 1,150 hectares (Decree…1997). The Zasavica area is a remnant of a once large wetland area in the Sava and Drina basins (Stankovic 2014). In 2012, wider boundaries of the reserve were proposed, toward a total area of 1,128 hectares, with a pro­tected zone of 3,462 hectares (Dobretic et al. 2012). The Zasavica SNR is also an area of international importance, considering that it has the following listings: a Ramsar site (wetland of international importance), an IBA (Important Bird Area) as a patch-workandthebest-preservedhabitatofmarshbirdsinnorthwesternSerbia,anIPA(ImportantPlantArea) due to its floristic and vegetation value and its inclusion in the botanically important areas of central and eastern Europe (Stevanovic 2005), a PBA (Prime Butterfly Area) as one of four in Vojvodina (Jakšic and Nahiranic 2011), an Emerald Network Area of Special Conservation Importance (ASCI) due to the pres-enceofwetland,forest,andmeadowhabitatsofthePannonianlandscapethatareapriorityforconservation, anda proposed NATURA 2000 area with twenty-three types of habitat priority for conservation recorded (Lazic et al. 2008). The Zasavica SNR is also part of the international networks Sava Parks and Dinarides Parks (Puzovic et al. 2015). Finally, due to its good conservation and accessibility, it offers excellent con­ditions for the development of ecotourism. 3.2 Research design, instrument, and data collection To achieve the objectives of the research, a survey in a form of a questionnaire was developed. It explores localresidents’attitudestowardsustainabletourismdevelopment.Thequestionnaireconsistsofthreeparts. The first part contains demographic data about the participants. Inthesecondpart,participantswereaskedtorespondto42statementsaboutsustainabletourismdevel­ opmentusingtheSUS-TASscale(ChoiandSirakaya2005).ChoiandSirakaya(2005)developedtheSustainable Tourism Development Scale (SUS-TAS) to measure residents’ attitudes toward the current sustainability statusoftourismdevelopmentandtheexpectedlevelofsustainability.ThisstudyadoptstheSUS-TASwith onlyminormodificationinwording.Forthequestionnaire,theSUS-TASscalewastranslatedintoSerbian. Responses in the second part were measured using a five-point Likert scale (1 = absolutely disagree, 2 = partially disagree, 3 = neutral, 4 = partially agree, and 5 = absolutely agree) as in several previous studies onsustainabletourismdevelopment(ChoiandSirakaya2005;Gidebo2019;RathnayakeandDarshi2020). Inthethirdpart,participantswereaskedaboutnatureconservationintheareastudied.Weaskedpar­ticipants the following questions: • Do you know any plant species in the Zasavica SNR? • Do you know any animal species in the Zasavica SNR? • In your opinion, are there any problems related to nature protection in the Zasavica SNR? • Are you involved in any programs connected with nature protection in the Zasavica SNR? • Would you like to contribute as a volunteer to nature protection in the Zasavica SNR? Figure 1: Map of the Zasavica SNR. p 175 The data were collected in August 2020. The study sample consisted of 399 respondents. Part of the respondents(seventy-sixparticipants)weresurveyedthroughanonlinequestionnaire(atGoogleForms), which was distributed through social media (Facebook). The rest of the responses were collected through a face-to-face interview. For this portion, a pen-and-paper questionnaire was conducted by giving paper questionnaires to individuals in person and asking them to complete them by hand and return them to the researcher. Respondents were informed that the survey was anonymous, that participation was vol­untary, and that the results of the survey would be used for research purposes only. 3.3 Sampling procedure ThesampleincludesresidentsfromtownsandvillagessurroundingtheZasavicaSNR.Datawerecollected in eight cadastral municipalities (total population 14,437). A representative targeted sampling was used toselectrespondentsineachcadastralmunicipality:Ravnje(population1,142),Radenkovic(946),Zasavica Ravnje(1,142),Radenkovic(946),Zasavica(1,330),Nocaj(1,866),SalašNocajski(1,751),MacvanskaMitrovica (4,116), Crna Bara (1,924), and Banovo Polje (1,362). The total sample numbered 399, which is 2.76% of the total population. 3.4 Data analysis techniques Fordataanalyses,IBMSPSS25.0.Statisticswasused.Thestatisticalmethodsusedinthisresearchinclude descriptive statistical analysis to determine the sociodemographic profiles of the respondents, principal componentanalysis(PCA)todeterminethedimensionsoftheSUS-TAS,Cronbach’salphatotesttheinter­nalconsistencyoftheitemsmeasuringeachfactor,andcorrelationtodetermineassociationsbetweenthe responses of respondents belonging to different age groups based on the SUS-TAS factors. An ANOVA testwasconductedtodeterminethedifferencesintherespondents’answersintermsoftheiremployment, education, type of settlement, and nationality, and a t-test was performed to compare the data reported by respondents of different sexes in terms of sustainable tourism development factors. 4 Results 4.1 Respondents’ sociodemographic pro.les A total of 399 questionnaires were submitted. A descriptive summary of the respondents (Table 1) shows that females (55.39%) slightly outnumbered males (44.61%). The majority of the respondents were under 30 (age=19:26.06%; 20–29 years: 29.57%) and had a high-school education (55.39%) or above(universi­tyeducation:37.09%).ThehouseholdsizeintheareastudiedisabovetheSerbianaverage,2.88(according to the 2019 census). About half of the respondents (49.37%) earn more than the average monthly income in Serbia (€450). In terms of duration of residence, the majority of respondents had lived locally between 10 and 19 years (38.34%) and between 20 and 29 years (20.81%). 4.2 Factoranalysisoflocalcommunities’attitudestowardsustainabletourismdevelopment Fist, a principal component analysis (PCA) was conducted with a varimax rotation on forty-two items to delineate the dimensions of the SUS-TAS, and it loaded within seven domains. Almost all communalities wereabove0.300,furtherconfirmingthateachitemsharessomecommonvariancewithotheritems.Only the statements »Sometimes it is acceptable to exclude a residents of a community from tourism develop­ment« and »Residents of a community should have an opportunity to participate in tourism development andmanagement«were0.120and0.285,respectively,andtheywerenotincludedinfurtheranalysis.Given these overall indicators, the factor analysis was considered appropriate for 40 out of the 42 items. Table 1: Socio-demographic characteristics of respondents (n = 399). Category n % Sex: Male 178 44.61 Female 221 55.39 Age (years): = 19 104 26.06 20–29 118 29.57 30–39 79 19.80 40–49 57 14.29 50–59 22 5.52 = 60 19 4.76 Education: Elementary school 30 7.52 High school 221 55.39 University and above 148 37.09 Household size: < 3 78 19.55 3–5 258 64.66 >5 61 15.29 Monthly income (€): < 250 67 16.80 250–450 132 33.08 > 450 197 49.37 No response 3 0.75 Residence (years): = 9 40 10.02 10–19 153 38.34 20–29 83 20.81 30–39 49 12.28 40–49 26 6.52 = 50 48 12.03 TheKaiser–Meyer–Olkinmeasureofsamplingadequacywas0.87,abovethegenerallyrecommended valueof0.6 required for valid factor analysis (Kaiser 1970;1974;Tabachnick andFidell 1989;2007), and Bartlett’s test of sphericity was significant (.² (780) = 10,582.367, p = 0.000). Using the eigenvalue crite­rion (greater than 1), we confirmed seven significant factors totaling 65.68% of the explained variance (Table 2). Inthisstudy,Cronbach’salphacoefficientsforeachSUS-TASdomainrangedfrom0.603to0.884with an overall scale reliability of 0.871, indicating that the variables had strong to moderate correlation with their factor grouping and were internally consistent. Thehighestlevelofagreementwasforenvironmentalsustainability(90%),followedbyvisitorsatisfaction (85.8%) and community-centered economy (85.2%), and the lowest level of agreement was for perceived social cost (42.2%). 4.3 ANOVA test: respondents’ age, education status, and correlation analysis Respondents over 19 (Table 4) are more likely to consider environmental sustainability than the youngest respondents(F=5.813;p=0.000),whereastheyoungestrespondentsaremoreconcernedaboutperceived social costs than other groups (F = 4.956; p= 0.000). Significant differences were found based on the edu­cational status of the respondents regarding six factors of sustainable tourism development, except in the case of community participation. Educational status correlated significantly (mostly positively) with almost all SUS-TAS factors except community participation (Table 5). Residents’ age and length of residence also showed a significant posi­tivecorrelationwithenvironmentalsustainabilityaswellascommunity-orientedmanagement.Furthermore, a significantly negative correlation was found between perceived social costs and age, educational status, and length of residence. Table 2: Factor analysis for host community attitudes toward sustainable tourism development. Factors and statements Value Environmental sustainability (a = 0.869) 1. The community’s environment should be protected now and for the future 0.825 2. The diversity of nature must be valued and protected 0.819 3. The development of tourism should increase efforts to protect the environment 0.744 4. Tourism must protect the community environment 0.732 5. Tourism must be developed in harmony with the natural and cultural environment 0.709 6. Appropriate tourism development requires wildlife and natural habitat protection at all times 0.642 7. Tourism development must promote positive environmental ethics for all tourism stakeholders 0.562 8. Regulatory environmental standards are needed to reduce impacts of tourism development 0.301 9. Tourism must improve the environment for future generations 0.312 Perceived social costs (a = 0.884) 10. Tourists in my community are disrupting my quality of life 0.831 11. My quality of life has deteriorated because of tourism 0.820 12. I often feel irritated because of tourism in the community 0.818 13. The community’s recreational resources are overused by tourists 0.739 14. My community is overcrowded because of tourism development 0.734 15. I do not feel comfortable or welcome in local tourism businesses 0.664 16. Tourism is growing too fast 0.651 17. The quality of social interaction in my community has deteriorated because of tourism 0.551 Perceived economic benefits (a = 0.884) 18. I like tourism because it brings new income into our community 0.760 19. Tourism makes a strong economic contribution to the community 0.721 20. Tourism generates significant tax revenue for local government 0.681 21. Tourism is good for our economy 0.666 22. Tourism creates new markets for local products 0.626 23. Tourism diversifies the local economy 0.554 24. Tourism is beneficial to other industries in the community 0.512 Community participation (a = 0.603) 25. Tourism decisions need to be made by everyone in my community regardless of background 0.864 26. The whole community must participate in decisions for successful tourism development 0.837 Long-term planning (a = 0.703) 29. The tourism industry must plan for the future 0.616 30. Successful management of tourism requires an advanced planning strategy 0.839 31. We need to take a long-term perspective when planning tourism development 0.811 32. Residents must be encouraged to take a leadership role on tourism planning committees 0.686 33. Tourism development needs well-coordinated planning 0.641 34. Tourism development plans should be continuously improved 0.601 Visitor satisfaction (a = 0.782) 35. Tourism businesses have a responsibility to provide for visitors’ needs 0.777 36. Community attractiveness is the core element of environmental attractiveness to visitors 0.750 37. Tourism enterprises need to monitor visitor satisfaction 0.614 38. The tourism industry must ensure high-quality tourism experiences for future visitors 0.604 Community-centered economy (a = 0.837) 39. The tourism industry should obtain at least half its goods and services locally 0.749 40. Tourism should hire at least half its employees from the local community 0.687 41. Local community residents should receive a fair share of the benefits from tourism 0.686 42. The tourism industry must contribute to community improvement funds 0.467 Table 3: Respondents’ attitudes to sustainable tourism development. Sustainable tourism development factors Mean SD Agreement level (%) Environmental sustainability 4.50 0.54 90 Perceived social cost 2.11 0.84 42.2 Perceived economic benefits 3.97 0.74 79.6 Community participation 3.77 0.66 75.4 Long-term planning 4.07 0.72 81.4 Visitor satisfaction 4.29 0.65 85.8 Community-centered economy 4.26 0.68 85.2 Table 4: ANOVA test: Factors of sustainable tourism development by respondents’ age and education. Factors F-value LSD post-hoc test By age Environmental sustainability 5.813* 2, 3, 4, 5, 6 > 1 Perceived social cost 4.956* 1 > 2, 3, 4, 5, 6 Perceived economic benefits 3.042 / Community participation 0.241 / Long-term planning 2.675 / Visitor satisfaction 1.691 / Community-centered economy 4.225* 3 > 1, 2, 5; 4 > 1 By education Environmental sustainability 12.295* 3 > 1, 2; 2 > 1 Perceived social cost 3.955* 1 > 3 Perceived economic benefits 10.400* 3 > 1, 2; 2 > 1 Community participation 0.105 / Long-term planning 10.403* 3 > 1, 2; 2 > 1 Visitor satisfaction 5.274* 3 > 1, 2; Community-centered economy 4.000* *p < 0.01; F > 3.32 Table 5. Correlation analysis: age of respondents, educational status, household size, and sustainable tourism development factors. Pearson correlation coefficient (r) Factors Age Education status Length of residence Environmental sustainability 0.202** 0.240** 0.163** Perceived social costs -1.810** -0.126* -0.147** Perceived economic benefits 0.048 0.218** 0.006 Community participation -0.013 -0.009 -0.062 Long-term planning 0.046 0.219** -0.070 Visitor satisfaction 0.052 0.150** 0.015 Community-centered economy 0.101** 0.140** 0.023 *Correlation significant at p = 0.05, **Correlation significant at p = 0.01 4.4 Respondents’ attitudes toward nature protection Ingeneral,respondentsexpressedaverypositiveattitudetowardnatureprotectioninthestudyarea.Two­thirdsoftherespondents(68%)statedthattheyknewsomeplantspecies,andsimilarresponseswerefound forrespondents’knowledgeofanimalspecies.Althoughmanagersofthenaturereservesinformedthepub­licabouttheimportanceofthepresenceofendangeredplantspecies,localsmainlyrecognizedyellowand white water lilies and reeds. Unfortunately, 91% of the respondents indicated that the most popular ani­mal species in the study area was the domestic donkey, and only 0.5% of the respondents knew about the European mudminnow (Umbra krameri), an endangered fish species. Asignificantnumber(75%)oftherespondentsareawarethatthereareproblemsrelatedtonaturepro­tection,butnoonenamedthem.Also,only8.5%oftherespondentsansweredthattheyhavebeeninvolved in some programs related to nature protection – but, again, without specific answers regarding the capac­ity to which they are involved in such programs. Fortunately, half of the people surveyed (55%) would be happy to contribute to nature protection and tourism development in the Zasavica SNR without receiv­ing any compensation. 5 Discussion TheresultsobtainedshowthatinhabitantsoftheZasavicaSNRhaveapositiveattitudetowardsustainable tourismdevelopment,ecotourism,socioculturalandeconomicimpactsofecotourism,andnatureconser­vationintheareastudied. Furthermore,ourfindingsreinforcepreviousresearchandsupporttheposition that SUS-TAS is also a reliable and valid instrument for measuring residents’ attitudes toward sustainable tourism development in ecotourism research (Nunnally and Bernstein 1994; Gidebo 2019). In this study, the SUS-TAS scale wasapplied in the Zasavica SNR, where tourism is underdeveloped, whereas previous studies were conducted in tourist destinations and in countries where tourism is one of the most impor­tanteconomicsectors;forexample,inIzmir,Turkey(Sirakaya-Turk,EkinciandKaya2007;Sirakaya-Turk, IngramandHarill2008),Cyprus(Kvasova2011),andtheUnitedStates(Hawaii,Indiana,SouthCarolina, Texas, andrural counties in the Midwest; Choi and Sirakaya 2005; Yu et al. 2011; Assante, Wen and Lottig 2012; Sirakaya-Turk and Gursoy 2013; Zhang, Cole and Chancellor 2015). SUS-TAShasalsobeenappliedtohotels(Prayag,Dookhony-RamphulandMaryeven2010),andsome studies have been conducted in national parks (Gidebo 2019) and outstanding natural landscapes (Obradovic and Stojanovic 2021), which are also protected natural areas. In the study by Obradovic and Stojanovic (2021), it was confirmed that this scale can be used in different cross-cultural settings (con­firmatory factor analysis, or CFA, was used) and in municipalities and protected areas where tourism has not yet emerged as a significant economic area of activity. This study seeks to promote the development of ecotourism in communities and raise awareness of theneedtocreateprogramsthatengagelocalcommunities.Sofar,educationalprogramshavemostlybeen periodic and related to specific projects, but there is a need to ensure their continuity. Their goal should be continuous education and promotion of awareness of the potential of the Zasavica SNR to protect and preserve it through ecotourism as a form of sustainable tourism development. The development of such aformoftourismrequirestheparticipationofthreegroupsofstakeholders:thelocalcommunity,theman­agementoftheprotectedarea,andthetourismindustry.Ifthelocalcommunityisinformedandeducated, thiswillleadtoincreasedinvestmentinthetourismindustry.Thisapproachcanincreasetheinvolvement of local residents as entrepreneurs and employees in tourism development and encourage young people to remain in the area. This can in turn lead to the creation of employment opportunities for local people, reduceunemployment,andimprovelivingstandards,makingtheresidentsmuchmoresupportiveoftourism development. In general, community members show agreement with seven factors of sustainable tourism develop­ment,withtheexceptionofperceivedsocialcosts,whichisconsistentwithpreviousstudies(Gidebo2019; Rathnayake and Darshi 2020). Our presumption is that the community in the study area has experienced lower social costs associated with tourism development at this time, which mitigates the negative impacts on the local community. This would explain the lowest level of agreement in the case of perceived social costs.Furthermore,theresultsobtainedshowapredominantlypositivecorrelationbetweenresidents’edu­cationalstatusandalmostallSUS-TASfactors.Thepositivecorrelationofhigheducationlevelwithsupport fortourismdevelopmentisconsistentwiththeliteratureconsulted(Teye,SirakayaandSönmez2002;Chen and Qui 2017). The group of respondents with completed high school education is more likely to con­sider environmental sustainability, perceived economic benefits, and long-term planning than the group with only primary school education.Perceived social costs as a factor of sustainable tourism development are more thoroughly considered by locals with completed primary school. Older respondents with high­er levels of education were found to have more positive attitudes toward environmental sustainability and acommunity-basedeconomy.Theresultsofthisstudyareconsistentwithpreviousresearch(Teye,Sirakaya and Sönmez 2002; Chen and Qui 2017), which suggests that people with higher levels of education are moreawareofthepotentialbenefitsoftourismthanpeoplewithlowerlevelsofeducation.Furthermore,the surveyresults showthatrespondentswith higherlevelsofeducationstrongly believethattourismdevelop­ment needs well-coordinated planning, similar to a study conducted in Sri Lanka (Rathnayake and Darshi 2020). On the other hand, younger respondents with lower educational status were more likely to perceive social costs than older ones, which is associated with a critical attitude toward the negative environmental impactcausedbytourismdevelopment,whichwasconfirmedinastudyconductedbyKuvanandAkan(2005). According to a number of researchers, length of residence in a geographic location may be a better predictorofresidents’attitudestowardtourismimpacts(Walpoleand Goodwin2001;GuandRyan2008). In this study, length of residence was positively correlated with attitudes toward environmental sustain­ability, which is consistent with similar research (Khoshkam, Marzuki and Al-Mulal 2016). Furthermore, some previous studies confirmed that length of residency was positively correlated with attitudes toward the economic impacts of tourism development (Liu and Var 1986; Haralambopoulos and Pizam1996; Khoshkam, Marzuki and Al-Mulal 2016). General public awareness about nature and environmental protection is still insufficient in Serbia (Tomicevic, Shannon and Milovanovic 2010). To our knowledge, this is the first time that this type of sur­veyhasbeenusedinnatureprotectiontoinvestigatethelevelofknowledgeofthelocalpopulation.Although respondents expressed a very positive attitude toward nature protection, key species for conservation of theZasavicaSNRarepoorlyrecognizedbythelocalpopulation.Forthegloballythreatenedaquaticwater­wheelplant(Aldrovandavesiculosa),ZasavicaistheonlyremaininghabitatinSerbia(Tomovicetal.2009). This species has the status of a globally threatened species (EN; Cross and Adamec 2020), and in Serbia itisdesignatedascriticallyendangered(IUCN2001).ExtantpopulationsofA.vesiculosaarerareinEurope, and only a few sites remain in the Balkans. A. vesiculosa was promoted as one of the »flagship species« of thereserve(Stankovic2014).However,onlythestaffoftheZasavicaSNRknewabouttheexistenceofthis species. The low level of knowledge about non-charismatic plant species among residents contrasts with the awareness of large communities of scientists and naturalists from Serbia, who recognize A. vesiculosa as one of the most important species in the reserve. Moreover, only 0.5% of respondents knew about the endangeredEuropeanmudminnow(Umbrakrameri).Thisspeciesisarelict,anditistheonlynativespecies in the genus Umbra in Europe. In particular, the Zasavica SNR is one of two remaining habitats in Serbia (Sekulic et al. 2013). Previousstudiesshowthatthemostattractiveandsecurespeciesreceivethehighestpublicsupportcom-paredtolessattractiveandmorethreateningones(dePinhoetal. 2014;Liordosetal. 2017). Furthermore, physicalsize(MetrickandWeitzman1998)andphylogeneticsimilaritytohumans(Tisdell,WilsonandSwarna Nantha 2006) also increase support in efforts to save threatened species. In our study, A. vesiculosa and U. krameri donotmeettheseparameters,andthisisprobablywhytheyarenotrecognizedbythelocals. One ofthesolutionscouldbefound,forexample,in Greece,wherecampaignstoincreasepublicinterestinthe lesscharismaticspecies,conductedbytheWWFandNGOshavesofarpromotedsuccessfulmanagement and conservation of the black vulture for more than twenty-five years (Liordos et al. 2017). Moreover,intheareastudied,oneofthefamousattractionsisdonkeys,togetherwithliqueurandsoap made from donkey milk. This is the only place in the region where people can see and buy such products. Thisisprobablywhytherespondentssaidthatthemostpopularanimalinthereserveisthedomesticdon­key. The Zasavica SNR is involved in a genetic resources conservation program, and the donkeys are part of the breeding stock of a special native Balkan breed. The Zasavica SNR hosts a population of a few hun­dredBalkandonkeys,Podoliancattle,andMangalitsapigs,whichroamfreelyinlargepasturesinthecentral part of the reserve, and they contribute to the management of grasslands and wetlands. Although kept as domestic animals, these are perceived as valuable representatives of local biodiversity and part of native ecosystems. On the other hand, the examples of U. krameri and A. vesiculosa show that, despite intensive promo­tion and education campaigns (e.g., the tourist boat on the Zasavica River is named Umbra after the endangered fish), managers have not succeeded in raising awareness of non-charismatic wildlife among local people, most of whom recognize the Zasavica SNR as a preserved natural habitat with traditional livestock management. Similar results on local perception toward conservation have been found in other parts of the world (de Albuquerque and de Albuquerque 2005; Abukari and Mwalyosi 2020). Therefore, it would be good to investigate how locals learn about biodiversity and conservation in other protected areas. The results of the survey suggest that long-term educational programs on conservation should be devised for locals. Over time, their knowledge will accumulate, multiply, and spread to eventually achieve a better balance with nature. The large number of respondents that want to contribute to nature protection and sustainable devel­opment is important because of the scope of tourism development in the Zasavica SNR. This protected area is one of the most frequently visited in northern Serbia. The Zasavica SNR stands out for its level of tourism development and tourist services (a visitors’ center, educational and eco-trails, restaurants, and a camp), and it has strategies and plans according to which it is developing as a destination (Stojanovic, Lazic and Dunjic 2018). Revenue from tourist visits from tickets alone is about €21,000 a year. The prof-itfromcateringservicesisalsosignificant,andfromthesaleofsouvenirsandethnicfood:goatmilk,cheeses, and processed meat from Mangalitsa pigs (Jovanovic et al. 2019). On the whole, the residents are aware of the importance of nature and protecting it even if they dif­fer in material status or education level. Interestingly, Tomicevic, Shannon and Milovanovic (2010) came toasimilarconclusioninTaraNationalParkinSerbia.Moreover,ourresultsshowthatasignificantnum­berofrespondentswouldliketocontributetonatureconservationandtourismdevelopmentintheZasavica SNR. In conclusion, as indicated in a study conducted by Tomicevic, Shannon, and Milovanovic (2010), acomprehensive,participatorymanagementprogramisundoubtedlynecessarytoreachpeoplethatalready feelconnectedtoaprotectedareatodeveloptailoredplansandincreasecommunityparticipationinman­agement of the protected area. 6 Conclusion Accordingtotheliteratureinthisarea,sustainabletourismreliesheavilyonstakeholderparticipation,and efforts must be made to improve the links between conservation, local community development, and the tourism industry (Wearing and Neil 2009). This study emphasized the importance of local community support and participation. The results of this case study reinforce the findings of similar previous studies (Lundberg 2017; Wang 2019) and show that SUS-TAS can be used to measure residents’ attitudes toward sustainabletourismdevelopmentincommunitiesandprotectedareaswheretourismhasnotyetemerged as a significant economic activity. According to the study by Jaafar, Noor, and Rasoolimanesh (2015), local residents’ involvement and active participation plays avital role in implementing conservation programs that contribute to preserving heritage sites and protected areas. This study shows that half of those surveyed would like to contribute to natureconservationandtourismdevelopmentintheZasavicaSNR.Lackoflocalparticipationdiminishes thevalue of heritage sites and protected areas (Buta, Holland and Kaplanidou 2014; Majid et al. 2019), but thisresearchhasconfirmedthatcommunityparticipationandactiveinvolvementarenecessaryfornature protection and tourism development. Attitudes toward tourism development and protecting nature vary among individuals in the Zasavica SNR. Moreover, the results of this study have a practical application for the local authorities in designing and planning future tourism development and nature protection in the Zasavica SNR as well as in other protected areas in Serbia and the wider region. Finally, it is impor­tanttoemphasizethattheresidentsoftheareastudiedrecognizethebenefitsofsocioculturalandeconomic impacts of development, while acknowledging the negative impacts of development on the natural envi­ronment. 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The case study is the Jovac mega-landslide – the largest landslide to occur in Serbia in the last 100 years,active for three days in February 1977.The indicators used todetermine the volume and move­mentmechanismwerethespatialdistributionofelevationdifferenceswithinthetwodigitalterrainmodels (DTM), and the analysis of geomorphological features before the landslide. The obtained elevation dif­ferences allowed the definition of the approximate landslide volume: 11.6×106m3. All the data obtained indicate that the movement mechanism falls into the category of earthflow. KEY WORDS: landslide, earthflow, GIS analysis, Jovac, Serbia Zaznavanje dinamike premikanja zemeljskih gmot z uporabo digitalnih modelov višin srednje locljivosti: Diakronicna perspektiva plazu Jovac, južna Srbija POVZETEK: Prispevek predstavlja in obravnava postopek raziskovanja zemeljskih plazov, ki se nanaša na topografijo pred nastankom procesa in po njem, s primerjalno analizo dveh digitalnih modelov tere­nasrednjelocljivosti.ŠtudijaprimerajemegazemeljskiplazJovac,kijenajvecjiplazvSrbijizgodilvzadnjem stoletju in je bil aktiven tri dni februarja 1977. Kazalniki, ki dolocajo prostornino in mehanizem gibanja, so prostorska porazdelitev višinskih razlik v obeh digitalni modeli terena (DTM), pa tudi analiza pred­hodnihgeomorfološkihznacilnosti.Dobljenevišinskerazlikesoomogociledolocitevpribližneprostornine plazu:11,6×106m3.Vsipridobljenipodatkikažejo,damehanizemgibanjaspadavkategorijozemljinskih tokov. KLJUCNE BESEDE: zemeljski plaz, drobirski tok, analiza DMR, Jovac, Srbija The article was submitted for publication on March 22nd, 2021. Uredništvo je prejelo prispevek 22. marca 2021. 1 Serbian Academy of Sciences and Arts, Geographical Institute Jovan Cvijic, Belgrade, Serbia m.milosevic@gi.sanu.ac.rs (https://orcid.org/ 0000-0001-5188-7260), d.strbac@gi.sanu.ac.rs (https://orcid.org/0000-0001-9946-7978),j.calic@gi.sanu.ac.rs ( https://orcid.org/0000-0002-7271-5561), m.radovanovic@gi.sanu.ac.rs (https://orcid.org/0000-0002-9702-3879) 2 South Ural State University, Institute of Sports, Tourism and Service, Chelyabinsk, Russia m.radovanovic@gi.sanu.ac.rs (https://orcid.org/0000-0002-9702-3879) 1 Introduction The article deals with earthflow as a specific form/process of landslides from the perspective of changing topography, within a case study of the Jovac earthflow in south-eastern Serbia. Landslides, as one of the mostdynamicprocesses,havebeenthoroughlystudiedinthelastdecades,especiallywiththerapiddevel­opmentofgeomorphometrictools.AmongthemostcitedandimportantreferencesaretheworksofVarnes (1978; 1984) on landslide hazard zonation, Cruden (1991), Cruden and Varnes (1996) on landslide types, and Hungr, Leroueil and Picarelli (2014) on landslide typification. Cruden’s (1991) definition is accepted bytheinstitutionswhichdefinedtheinternationalstandardsinlandslideresearch,suchasTheinternational geotechnicalsocieties’UNESCOworkingpartyforworldlandslideInventory(1993),andtheInternational AssociationforEngineeringGeologyandtheEnvironment(IAEG)(UNESCOworking…1993).Furthermore, the above-mentioned references indicate a high degree of diversification of landslides depending on the type of movement and the type of material. Within this typology, the combination of relatively high water content within the small-grained material indicates the landslide category of earthflow, as a subgroup in thelandslideclassificationsystem.Hungr,LeroueilandPicarelli(2014)defineearthflowmaterialasacohe­sive, plastic, clayey soil material, often mixed and remoulded with the Liquidity Index below 0.5. Keefer andJohnson(1983)statethatmanyearthflowscontainfragmentsofmaterialinvariousstagesofremould­ing and may carry granular clasts. The IGS Multilingual Landslide Glossary (1993) recognizes the term »flow« (not earthflow) and explains that the distribution of velocities in the displacing mass is similar to thatinaviscousfluid.ValuabletheoreticalbackgroundforearthflowsisprovidedbyUrciuolietal.(2016), whoexplaintherelationshipbetweenmorphologicalaspects,kinematicbehaviourandslopestabilitycon­ditions. Digitalterrainmodels(DTMs)arearesourceofhighimportancewithinlandslidedetectionandresearch. (Mahalingam and Olsen 2016). Jaboyedoff et al. (2012) see the role of DTM in: • mass movement detection and characterization, • hazard assessment and susceptibility mapping, • modelling, and • monitoring. The resolution of a DTM is one of the crucial properties affecting the quality of research results (Lee et al. 2004; Hrvatin and Perko 2005; Santini et al. 2009). In the early period of DTM development, it was assumedthathigherresolutionwouldautomaticallyleadtobetterresults(DietrichandMontgomery1998). However,recentstudiesshowthatresolutionsof2m,5mand10mdonotnecessarily providemoreaccu-rate results (Mahalingam and Olsen 2016; Chen et al. 2020). In some caseswithquite high resolution, the DTM may also contain irrelevant data (Tarolli and Tarboton 2006). These can blur the key influencing factors related to sliding during further processing. Examples of this are microtopographic details creat­ed by subsequent denudation of the landslide body or small-scale rockfalls in the scarp zone. Therefore, the selection of the optimal DTM resolution must consider the dimensions of the landslide, as well as the context of the analysis (McKean and Roering 2004; Claessens et al. 2005). Landslide detection using DTM was one of the main aims of our research which was conducted in several time frames. A time frame refers to a state of the topographic surface at the time of the analysis. Performing two or more analyses (assuming that the intervening period included an observable change) provided the insight into the temporal dynamics of the process (Table 1). Table 1: Landslide detection methods using a Digital Terrain Models (DTM). Time frame Detection method Detected features DTM One time frame More time frames Visual interpretation of DTM Automated interpretation of DTM Detection of elevation differences before and after the landslide (two DTMs) Landslide outlines and morphometric features of the landslide topographic surface Landslide outlines, dimensions, morphometric features of the landslide topographic surface, depletion zone, accumulation zone, movement mechanism, monitoring Within a time frame, the detection process can be done by two methods: visual interpretation and/or automated recognition. In our case, the visual method combined with fieldwork was the starting point fordetermininglandslideoutline(Ardizzoneetal.2007;Amundsenetal.2010;Guzzettietal.2012).Visual interpretation of DTMs relies on hillshade, the generated contours, and the slope of the topographic sur­face (Van Den Eeckhaut et al. 2007; Schulz 2007; Ðomlija 2018). This method of landslide determination is very subjective. In contrast, an objective landslide identification method is based on statistical analyses of DTM-generated morphometric parameters (curvature, surface roughness), which can be used to auto­matically determine landslide contours (Tarolli, Sofia and Dalla Fontana 2012). Two or more time-frames recorded within the DTMs allow the application of quantitative methods indefiningtheoutline(boundaries),approximatevolumeestimation,identificationofdepletionandaccu­mulation zones, and monitoring of landslide dynamics. The spatial distribution of colluvium canindicate the mechanism of movement (Corsini .t .l. 2009; Fernández et al. 2011; 2017; Giordan et al. 2013). The workofConoscentietal.(2015)isanexampleoftheuseofmultipletime-framesinDTManalyses.Apoten­tialdrawbackofDTMasamethodoflandslidedetectioningeneralisthattheDTMresolutionintheanalysis phase is usually limited by the pre-sliding input data. In our case, lower data resolution can be expected because the topographic data acquisition took place about 10 years before the landslide event, when map­ping methods were not sophisticated as today. Theaimofthisarticleistodeterminewhetheramedium-resolutionDTM(sensu,Gigovic2010;Table 2) canbeareliabledatasourceforlandslidestudies,giventhecurrenteraofLiDARdominance.Ourhypoth­esis is that a medium-resolution DTM can prove to be sensitive enough to determine landslide outlines, areas and volumes, as well as reconstruct their movement mechanisms. In this study, two DTMs of the same area are analysed – one is before and one after a landslide, created by applying two different meth-ods.Thearticledescribesthedetailsofthesuperpositionprocedureappliedinordertoavoidthesystematic errorsindeterminingtheelevationdifferences.Inthesubsequentanalysis,itispossibletodefinethemove­ment mechanism based on the comparison of the paleo-topography and the present topography of the Jovac landslide. Table 2: DTM resolutions (after Gigovic 2010). Resolution Horizontal distance of elevation points In meters In arc seconds Low 900–90 30–3 Medium 90–30 30–1 High 30–10 1–0.3 Very high 10–1 0.3–0.03 2 Study area and basic geological setting The Jovac landslideis located in the villages of Jovac and Ostrovica (Vladicin Han municipality) in south­easternSerbia(N44.64°,E22.003°).Themountainousareawithinthealtituderange400–800mhoststhe catchment area of the Jovacka Reka River, the left tributary of the Južna Morava River (Figure 1).Thecur-rent average precipitation average is about 740mm, with the peaks in June and May. Geologically, the study area is located on the southwestern edge of the Eurasian Plate. According to Prelevic et al. (2005), the closure of the Neotethys basin and the collision of the Eurasian Plate with theAfrican Plate triggered large-scale volcanism in early Cenozoic (Cvetkovic, Šaric and Mladenovic 2019). One of the eruption points was located in the zone of the Grot and Oblik peaks (Vukanovic et al. 1970), 7kmwestofthepresentlandslide(Figure1).Pyroclasticmaterialwasdepositedintheareawithinthedacite lava eruption. During the Miocene, the lower parts of the drainage area were part of a lacustrine basin where terrigenous sediments were deposited (Vukanovic et al. 1970; Babovic et al. 1977; Jovanovic and Novkovic1988).Thecombinationoftheselithologicalcomponentscreatedalandslide-pronesettinginthe area. Landslide activation occurred in February 1977 and destroyed 70 households in the villages of Jovac and Ostrovica (Petrovic and Stankovic 1981). Figure 1: Situation map of the study area (profiles refer to figures 10 and 11). 2.1 Previous research Twopapershavealreadybeenpublishedonthegenesisandmorphometryofthislandslide(Lazarevic1977; Petrovic and Stankovic 1981), giving dimensions of 3km2 area, 50m average width and 150×106m3 vol­ume. Both described the movement mechanism as a typical landslide, using the visual observation and fieldmapping.ReviewpapersmentioningtheJovaclandslidemostlyrefertotheprimaryreferencesmen­tioned(Jevremovic,SunaricandKostic2011;Pavlovicetal.2012).Lazarevic(1977)definedtheJovaclandslide astranslationalanddetermineditsareatobe1.52km2.Interestinglyhefoundthattherewasnosynchronized movement of the entire landslide body, but rather that the upper part moved first, while the middle and lower parts moved subsequently. Petrovic and Stankovic (1981) estimate the average depth of 50m and the volume of 150×106m3. They do not explicitly mention the mechanism of movement but their figure shows a translational landslide character (see Figure 11A). 3 Data sources and methods The aim of the research was to determine the precise outline (boundaries), area, volume and movement type of the Jovac landslide by analysing the topographic data from both, thepre-activation period and the resulting landform after the landslide process was complete. The most accurate data source available for the period before the landslide are the classical topographical maps at 1:25,000 published in 1971. The contourlinesofthe1:25Kmapsweredigitizedindetail(contourinterval10m,additional5mand2.5m) tosubsequentlycreatea30×30mDTMreferringtotheyear1971,inUTM34N.Theaccuracyoftheobtained DTMbased on digital contour lines from the cartographic records is 2.2m for TIN interpolation method (GovedaricaandBorisov2011).Accordingtothe1971map,forestvegetationcoveredonly12%ofthestud­ied area (in total), in 13 separate fragments; therefore, we do not consider that it affected the accuracy of the data obtained by the photogrammetric method. Forthepost-slideperiod,weusedanSRTMDTM30×30mrasterreferringtotheyear2000.Toallow thecomparisonbetweenthetwodatasets,thefinalresolutionof30×30mrastercell(pixel)resolutionwas accepted for the analysis 3.1 Calculation and analysis of elevation differences Rasterarithmeticwasusedtocalculatetheelevationdifferences.InthefirstoverlapoftwoDTMs,the1971 elevations were subtracted from the 2000 elevations. The analysis of the elevation differences allowed the Figure 2: Workflow. distinction between the sliding and non-sliding (stable) parts of the studied area, which led to the deter­mination of the exact boundary of the landslide. The non-sliding area was subjected only to statistical analysis of elevation differences, while the slid­ingareawassubjectedtogeomorphologicalanalysis.Thepreliminarydelineationbetweenthesetwounits was based on cartographic sources, literature, and fieldwork. The size ratio between the units is approxi­mately 1:3 (sliding area 1770 pixels; non-sliding area 4878 pixels). The objective of the statistical analysis oftheelevationdifferencesofthenon-slidingareawastodeterminethequalityoftheoverlapoftwoDTMs used,whilethetaskofthegeomorphologicalanalysiswastodeterminethecharacteristicsandconsequences of the sliding process. 3.2 Test of the overlap quality of DTMs It is assumed that the non-sliding area was not subject to any influences that would significantly change itselevation.Consequently,thecomparisonofpre-andpost-elevationvaluesshouldbepossible.Thechar­acteristics and spatial distribution of the differences would indicate whether there are systematic errors in the overlap of two DTMs obtained using the different data sources. The total number of pixels (in the non-sliding area) for which the elevation differences were analysed is 4878, i.e. 146,340m2. The distribution of the obtained elevation differences is shown in Figure 3. – ThearithmeticmeanoftheelevationdifferencesbetweenthetwoDTMsisx =3.940m,whilethestan­ darddeviationiss=4.331m.Thestandarddeviationisameasureofthequalityoftheoverlap(i.e.agreement of the data). Two tests of overlap of two DTMs were performed in the following way: One of the models was shift­ed by one pixel (30m) with respect to the other model. The displacement had four directions – N, E, S, W. The data on the mean (x –) and standard deviation (s) of the elevation differences for each movement are given in Table 3. Comparison of the standard deviation values of vertical differences shows that the deviation for the initial model is the smallest, which means that the overlap was correct. Figure 3: Distribution of elevation differences for the non-sliding (stable) area. Table 3: Arithmetic means and standard deviations of the elevation differences during the overlap test. – Pixel movement direction x s North 8.356 5.734 East 0.748 5.082 South –0.490 6.454 West 7.091 6.567 Initial value 3.940 4.331 Definitevaluesofelevationdifferenceswereobtainedbysubtractingthevalueof4minthepost-sliding – DTMinrelationtothepre-slidingDTM.Asmentionedabove,thevalueof4m(x =3.940)wastakenasthe value of the systematic error. 4 Results 4.1 Paleotopography Analysis of the pre-slide topographic surface (1971 topographic map) revealed colluvial (slope) and flu-vialmorphogeneticrelieftypes,determinedbylithologicalcomposition.Theindicatorfortherecognition ofcolluvialformsarethecontourdistanceswhichatsomeplacesdonotregularlyfollowthecontourinter­vals. Rogers and Chung (2016) suggest that the heterogeneous contour intervals on narrow and elongate surfaces may indicate earthflows. In the case of Jovac, the colluvial traces were present only in the zone of volcanoclastic sediments, mainly in the middle and upper part of the slope (Figure 4). Lazarevic (1977) pointed out the signs of former sliding by noting that the pond at the Jezero locality (meaning »lake« in Serbian language) is located in a depression formed during an earlier sliding phase. This former hydrological feature with a size of 2345m2 (45×50m in SW–NE direction), is visible on the1971topographicmap.OurfieldresearchresultsshowthattherewasanotherpondinthehamletDeda Dorinci, called Cekino Jezero or Cekina Bara (pond / swamp). Petrovic and Stankovic (1981) indirectly confirm this by listing the morphological elements of the slope that were present before the activation of theJovaclandslide.Theynotethatthe»middlepartofthepresentlandslidewassubjecttodynamicchanges, inversely inclined, with microdepressions, rounded hillocks and steep sides,« – features typical for land-slides.Inthecentralpartoftheslopetherewerehillocksofupto10mrelativeheight,depressionsandlandslide terraces of different heights. FluviallandformswerepresentonlyinthecatchmentareaofManastirskiPotok,whichextendedfrom themouthtotheJovackaRiver(at400km2.ThelowercourseoftheManastirskiPotok,carveda40mdeep gorge in pyroclastics. The valleys of the upstream tributaries are carved in volcanoclastic material with morphological traces of sliding processes. Thelongitudinalprofileofastreamisoneoftheindicatorsofitsmorphologicalstageofdevelopment. In the case of Manastirski Potok, the profile is not parabolic (as it would be in a balanced state), but uni­formly sloping (Figure 5), indicating an early morphogenetic phase and a possible imprinting by a paleo-(colluvial)-relief. The lateral tributary valleys were relatively shallow, with maximum depths up to10m,withinheritedcolluviallandforms–hillocks,depressions,slidingterraces.Thehydrographicnet-work consisted only of occasional streams, with a total length of 2910m. 4.2 Predispositions for the development of landslides TherewerethreemainpredispositionsforthelandslideprocessontherightvalleysideoftheJovackaReka River: • lithological composition, • morpho-hydrographic conditions: a) surface runoff areas and b) endorheic areas, and • human impact. Figure 4: Paleo-earthflows on the right side of the valley of the Jovacka River (1971 situation), where the 1977 landslide was later formed. Altitude (m) 680 630 580 530 480 430 380 Manastirski potok stream 0 500 1000 102000 50 Distance (m) Figure 5: Longitudinal profile of the stream Manastirski Potok. Through thepalaeogeographic evolution of thearea duringtheTertiary,it is possibletoidentify some ofthelithologicalpredispositionsfortheformationoftheJovaclandslide.Asmentionedabove,synchronous depositionofterrigenousandvolcanoclasticsedimentstookplaceduringtheMiddleMiocene(Jovanovic and Novkovic 1988). This sedimentary-volcanogenic unit represented by clays, sands, pebbles, volcanic ash, lapilli, tuff, volcanic agglomerates and volcanic blocks subsequently becomes an ideal environment for the formation of the Jovac landslide. Lithologically, the southwestern hinterland of the landslide con-sistsofdacites(theGradišteandOstrovicapeaks)(Vukanovicetal.1970),whilepyroclastitessuchasvolcanic breccias and agglomerates, as well as tuff sandstones and tuffs (Kremen Ridge) are located to the east and southeast (Babovicet al. 1977). The contact of these lithological units with the sedimentary-volcanogenic unit determined the boundaries of the subsequent Jovac landslide. Thehydrogeologicalcharacteristicsofpyroclastites,whichtopographicallygravitatetowardstheland-slide, are different than those of the dacites. Their permeability is extremely lowand the regolith is rather thin. Considering the morpho-hydrological criteria, there are two significant topographic units. The first is the surface catchment area of the Jovac landslide and the second is the endorheic area within it. The landslide catchment area includes not only the landslide body and hinterland of the scar, but also the lat­eral areas that morphologically gravitate towards the main landslide body (Figure 6). Regardingthehydrogeologicalcharacteristicsofthelithologicalunits,twozonescanbedistinguished: feedingzoneandcollectionzone.Thefeedingzoneisthelandslidebody(Miocenesedimentary-volcanogenic Figure 6: Predispositions for the development of the Jovac landslide. unit), whichhastheroleof hydrocollector(reservoir)andisfedby infiltrationofatmosphericandsurface water.Waterflowedfromtheimpermeableareasofthedacitesandpyroclastitestowardsthelandslidebody. This was an additional factor in increasing the amount of water received by the topographic surface. The total catchment area of the Jovac landslide was 3.06km2, of which 52% was the area of landslide itself. Another morpho-hydrographic feature is the occurrence of endorheic areas, which were detected on 48% of the catchment area (Table 4). This means that the water of 1.47km2did not drain superficially but infiltrated into the ground. The endorheic areas were divided into two areas. The first (1.07km2; of which 0.519km2 on the landslide) included the upper part of the slope, immediately below the Ostrovica peak, while another of 0.4km2 (of which 0.107km2 on the landslide) included the area around a palaeolake, to the northwest from the Manastirski Potok Gorge. Table 4: Hydrographic characteristics of the catchment area. Hydrography Catchment area Jovac landslide km2 % km2 % Exorheic 1.59 52 0.96 60 Endorheic 1.47 48 0.62 40 SUM 2.84 100 1.58 100 InthecaseoftheJovaclandslide,humanimpactisassociatedwiththeincreaseoftheslopecatchment area.Inotherwords,thetotalamountofwaterthatagivenareareceivescomesnotonlyfromitstopographic catchment, but also from other catchments. The inhabitants of the village of Ostrovica built a water-sup-plysystemthatdirectedthewaterfrombelowtheOštraCuka(1040m)(Figure6).Despitethefactthatthis areaisnotmorphologicallydirectedtothefuturelandslidebody,thehumanactivityadditionallyincreased thewaterbalanceoftheslope. Thewatersupplysystemwasofgravitationalandflow-throughtype, which resulted in water consumption exceeding the actual needs of the population (Lazarevic 2000). This was certainly not the main, but only an additional factor in triggering the landslide. The main anthropogenic factor was the permanent humidification of the ground in the built area zone, due to the water supply sys­tem which transferred the water from the neighboring catchment, area thus increasing the water input. 4.3 Morphometric characteristics of the Jovac landslide The landslide boundary was determined based on the spatial distribution of elevations of the topograph­ic surface, as explained in the Chapter 3. The topographic surface with no or with minimal differences wasdeclaredasthelandslideboundary.Thus,apolygonsimilartotheonedefinedbyPetrovicandStankovic (1981) was formed. The boundaries outline the elongated area with an area of 1.58×106m2. The maxi­mumlengthofthelandslideis3,000m,whilethewidthevariesfrom490mto670m.Twodistinctcontinuous areasarevisible,representingthevaluesoftheelevationchangedifferences.Thesmallerarea(0.62×106m2) islocatedinthehighestpartofthelandslide.Itischaracterisedbytheloweringoftheprevioustopographic surfaceintheintervalfrom–1to–45m.Inthemiddleandhypsometricallylowestpartoftheslope(0.96×106m2) (Figure 8A), the changes indicatethe increased elevation of the topographic surface. The values are in the interval from +1 to +51m. The boundary between these two areas is a narrow belt where the elevation change was not detected or is negligible (Figure 7). In the area of lowering of the previous topographic surface, the differences are positioned concentri­cally, and increase towards the interior. In the central part the highest extent of the topographic surface lowering was –45m. The distribution of the differences in elevation is very uneven. The greatest change isrecordedattheformergorgeoftheManastirskiPotokStream.Thevaluesoftopographicelevationsincrease fall in the interval from +31 to +51m. Outside this zone, the accumulation reaches +30m only in some places. Other values of topographic increase are distributed in various locations. By analysing the topographic elevation difference for each DTM cell (30×30m), the volume of land­slide was determined. The estimated volume of the depleted ground, where the surface was lowered is 12.45×106m3.Thevolumeofcolluviuminthezoneoftopographicsurfaceelevationincreaseis11.6×106m3, which is 4% less than the volume of depleted ground (Figure 8B). Figure 7: Elevation differences of the topographic surface of the Jovac landslide (contours refer to the present topographical surface). As a result of large denivelation of the topographic surface on the landslide body, several small lake basins have formed. They are permanently filled with water. Of the six lakes, five are located on the land-slidebody–twointhedepletionzoneandthreeintheaccumulationzone(Figure7).Thesixthandlargest lake is the Jovac Lake, formed by the landslide dam of the Jovacka Reka River. Table 5: Extreme and average morphometric characteristics of pre-sliding and post-sliding topographic surfaces. Elevation (m) Slope (°) Curvature Aspect (°) Pre-sliding Min Max 380 807 0.0 87.0 –5.046 5.046 Post-sliding Average Min Max 568 390 793 11.0 0.0 43.0 0.015 –0.342 0.361 110 Average 567 9.6 0.014 101 a) 80.000 Erosion Deposition 70.000 61% 39% 60.000 50.000 32 Volume (m)Area (m) 40.000 30.000 20.000 10.000 0 –46 –23 0 Elevation difference (m) 27 54 b) 1,000.000 Erosion Deposition 800.000 48% 52% 600.000 400.000 200.000 0 –200.000 –400.000 –600.000 –800.000 –46 –23 0 Elevation difference (m) 27 54 Figure 8: Distribution of elevation differences on the topographic surface (A) and distribution of volumes (B). 5 Discussion AlthoughthedescriptionsofJovacthemechanismsofmovementoftheJovaclandslidebyLazarevic(1977) andPetrovicandStankovic(1981)fitintothecategoryof»flow«,theauthorsexplicitlyreferredtothemove­ment as sliding. The analysis of the planar form of the Jovac landslide, where the length is much greater than the width, according to the nomenclature of Varnes, modified by Hungr et al. (2014) and the inter­national classification of landslides according to the movement mechanism IAEG (1991–1992), indicate that the flow-associated elements are also present. This statement can be analysed by three indicators based on the analysis of two DTMs, and related to the elevation differences of the situations before and after the slide. The first indicator is runoff. It shows how many cells (30×30m pixels) gravitate to an observed cell, i.e. how large is the »catchment area« of each cell. For this analysis, only the values obtained from the pre­slidingDTMwereconsidered.ThesecondindicatoristheelevationdifferenceoftwoDTMsforeachselected cell (negative or positive, indicating depletion or accumulation). The third indicator is the current eleva­tion of a cell, the elevation after the sliding process. Comparative analysis of these indicators was a valuable tool in geomorphological reconstruction of the area. The cross-section in the depletion zone (with lowering of the topographic surface) showed that the depletion peaks do not follow the peaks of the runoff capacity. The runoff peaks are directly propor­tional to the drainage lines. This indicates that the sliding process in the upper part of the landslide was independentofthemorphologyofthetopographicalsurface(profileB–BointheFigure10A).Thedeple­tion zone almost completely overlaps with the endorheic area and conditions for water saturation of soil and rock are favourable (Lollino, Giordan and Allasia 2014). The cross sections in the accumulation zone show a clearly different situation. Profile C–Co shows amatchingoftherunoffpeaks,butnotsomanyconspicuouspeaksintheincreaseofthetopographicval­ues(Figure10B).ThesameisseenontheD–Doprofile,withslightlybettervisiblepeakscomparedtoC–Co, thanks to its lower position on the slope (Figure 10C). This feature may indicate that the highest accu­mulationofthematerialoccurredalongthedrainagelines.Inotherwords,themorphologyofthepre-sliding surface determined the movement of colluvial material from the depletion zone (upper slope) through the accumulation zone (middle and lower zones). To prove the assumption that in the lower part of the landslide the flow followed the stable palaeoto­pographic surface, it was necessary to include the third indicator, the elevation of the cells after the slide (Figure 11D). Figure 11D shows that the convex portions of the current topographic surface overlap with the peaks of runoff and accumulation. A convex profile of the topographic surface in the earthflow accu­mulationzoneswasalsopointedbySoetersandvanWesten(1996).Thisundoubtedlyprovesthatthecolluvial material from the depletion zone continued to move downwards following the pre-existing morphology of the middle and lower parts of the slope. The underlying rock was certainly stable, thanks to the pyro­clastitezoneonthenortheastside.Thistypeofmovementwasaconsequenceofsupersaturationbywater, which decreased the viscosity of the colluvium and allowed it to follow the slope morphology. This also explains the asymmetry in the colluvium thickness, which is greatest in the zone of the former gorge of Manastirski Potok. Basedonthepresentedrelationshipsbetweenthecolluviumandtopographicsurfaceweconcludethat the Jovac landslide has elements of earthflow movement. According to the ICL classification (Internet 1), the Jovac earthflow is in the category of large landslides (=106m3). In Serbia, landslides with similar volume and lithology usually occur along the banks of large rivers and their movement mechanisms are rotational and planar. The right bank of the Danube River hosts the Bocke landslide, Krcedin landslide (Mészáros 2013), Cigansko Brdo (Janjic 1996), Rujište (Lazarevic 1957; Janjic 1996), Provalija (Lukovic 1951), while the Umka and Duboko landslides are located on the right bank of the Sava River (Abolmasov et al. 2014). Figure 10: Relationship between discharge and elevation differences along cross sections (see also Figure 1). p p. 202 Figure 11: Model of the Jovac landslide adapted from Petrovic and Stankovic (1981) (A); longitudinal profile of the Jovac landslide (B); cross section in the topographic decrease zone (C); cross section in the increase zone of Manastirski Potok Gorge (D) (see also Figure 1). p p. 203 a) 90 10 80 –0 70 Number of pixels –10 50 60 –20 40 30 –30 20 –40 10 0 –50 B Bo Distance in pixels Pixel catchment area Elevation difference (m) b) 1000 30 25 20 Number of pixels 100 15 10 10 5 0 1 –5 C Co Distance in pixels Pixel catchment area Elevation difference (m) c) 1000 60 50 Number of pixels 100 40 30 10 20 10 mmm D Do Distance in pixels Pixel catchment area Elevation difference (m) 6 Conclusion According to the systematization of Varnes (1978) and Cruden and Varnes (1996), the mechanism of the Jovaclandslidecolluviummovementcanbedeterminedasflowing.Intermsofmaterial(criteriaofVarnes 1978),itbelongstothecategoryofearth,containinghighproportionofparticlesabout2mminsize.Using themodifiedVarnes(1978)classificationoflandslides(Hungr,LeroueilandPicarelli2014),theJovacland-slidebelongstothecategoryofearthflow.Itsestimatedvolumeis11.6×106m3,whichisasignificantdifference compared to the earlier estimates of 150×106m3(Lazarevic 1977; Petrovic and Stankovic 1981). The rea­son for such a difference lies is that the earlier researchers had rather poor spatial data, mostly collected by fieldwork observations. We believe that the exceptional size of the landslide and the degree of damage may have influenced the earlier researchers to somewhat subjective conclusions. In determining the landslide contour, two DTMs were used, one with the situation before the land-slideandonewiththesituationafterthelandslide.Inordertoexplainthattheelevationdifferencesbetween them are the consequences of the sliding process, it was necessary to define the procedure to avoid tech­nical errors. Possible errors could be related to the incorrect overlapping of two DTMs and to the possible presenceofsystematicerrorsduetodifferenttypesofelevationdataacquisition.Aftercompletingthetest­ing, we obtained the exact elevation differences between two DTMs caused by the sliding process. The use of small- and medium-resolution DTMs, in this case 30×30m (Corsini et al. 2009; Hu et al. 2019), can be a relevant data source for landslide studies, provided that the dimensions of the landslide are large enough to be visible in a DTM. The DTM resolution used makes the study comparable world-wide,asbothEUandglobalDTMsusethisresolution.InthecaseoftheJovaclandslide,thepre-slidedata wereobtainedfromthetopographicmap1:25,000.Theinputdatadeterminedtheresolutionof30×30m. Judgingby thearea oftheJovacearthflow(1.58km2) andthevolume(11.6×106m3),weconcludethat the DTMatthisresolutioncontainstheinformationrelevanttotheearthflowformationprocess.Wealsocon­cludethattheanalysisoftheelevationdifferencesofthetopographicsurfacebeforeandafterthelandslide is an appropriate method to study earthflows (Fernández et al. 2011; Giordan et al. 2013). 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Washington.Cvetkovic,V.;Šaric,K.,Mladenovic,A.2019:Magmatizamimetamorfizam.Geohemijsko-geodinamicka perspektiva. Beograd. Dietrich,W.E.andMontgomery,D.R1998:SHALSTAB:Adigitalterrainmodelformappingshallowland­slidepotential.NCASI–Nationalcouncilofthepaperindustryforairandstreamimprovement,1998. Ðomlija, P. 2018: Identification and classification of landslides and erosion phenomena using the visual interpretation of the Vinodol valley digital elevation model. Ph.D. thesis, University of Zagreb. Zagreb. Fernández,T.,Pérez,J.L.,Cardenal,F.J.,Delgado,J.,Irigaray,C.,Chacón,J.2011:Evolutionofadiachron­iclandslidebycomparisonbetweendifferentDEMsobtainedfromdigitalphotogrammetrytechniques inLasAlpujarras(Granada,SouthernSpain).Internet:https://www.isprs.org/proceedings/2011/gi4dm/ PDF/OP69.pdf (18.10.2020). Fernández, T., Pérez, J. L., Colomo, C., Cardenal, J., Delgado, J., Palenzuela, J. A., Irigaray, C., Chacón, J. 2017:Assessmentoftheevolutionofalandslideusingdigital photogrammetryandLiDARtechniques intheAlpujarrasRegion(Granada,SoutheasternSpain).Geosciences7-2.DOI:https://doi.org/10.3390/ geosciences7020032 Gigovic, L. J. 2010: Digitalni modeli visina i njihova primena u vojnoj analizi terena. Vojnotehnicki glas­nik 58-2. Giordan, D., Allasia, P., Manconi, A., Baldo, M., Santangelo, M., Cardinali, M., Corazza, A. et al. 2013: Morphologicalandkinematicevolutionofalargeearthflow:TheMontagutolandslide,southernItaly. Geomorphology 187. DOI: https://doi.org/10.1016/j.geomorph.2012.12.035 Govedarica, M., Borisov, M. 2011: The Analysis of data quality on topographic maps. Geodetski vestnik 55-4. Guzzetti,F.,Mondini,A.C.,Cardinali,M.,Fiorucci,F.,Santangelo,M.,ChangK.T.2012:Landslideinven-torymaps:Newtoolsforanoldproblem.Earth-ScienceReviews112-1,2.DOI:https://doi.org/10.1016/ j.earscirev.2012.02.001 Hrvatin,M.,Perko,D.2005:Differencesbetween100-meterand25-meterdigitalelevationmodelsaccord­ingtotypesofreliefinSlovenia.ActageographicaSlovenica45-1.DOI:https://doi.org/10.3986/AGS45101 Hu,S.,Qiu,H.,Pei,Y.,Cui,Y., Xie, W., Wang,X.;Yang,D. etal. 2019:Digitalterrainanalysisofa landslide on the loess tableland using high-resolution topography data. Landslides 16. DOI: https://doi.org/ 10.1007/s10346-018-1103-0 Hungr,O.,Leroueil,S.,Picarelli,L.2014:TheVarnesclassificationoflandslidetypes,anupdate.Landslides 11. DOI: https://doi.org/10.1007/s10346-013-0436-y Internet 1: http://iplhq.org/ (29. 9. 2021). Jaboyedoff, M., Oppikofer, T., Abellán, A., Derron, M. H., Loye, A. Metzger, R., Pedrazzini, A. 2012: Use of LIDAR in landslide investigations: A review. Natural Hazards 61-1. DOI: https://doi.org/10.1007/ s11069-010-9634-2 Janjic,I.1996:GenezaisvojstvaklizištauneogenimsedimentimajužnogobodaPanonskogbasena.M.Sc. thesis, University of Belgrade. Belgrade. Jevremovic, D., Sunaric, D., Kostic, S. 2011: Landslide and rockfall induced lakes in Serbia. Tehnika 66-5. Jovanovic, O., Novakovic, M. 1988: Litološke odlike tercijarnih naslaga Vranjsko-pcinjskog basena. Vesnik geološkog zavoda 44. Keefer, D. K., Johnson, A. M. 1983: Earth flows: Morphology, mobilization and movement. Washington. Lazarevic, R. 1957: The relief of the immediate Danube basin between Grocka and Smederevo. Journal of the Geographical Institute »Jovan Cvijic« SASA 13. Lazarevic, R. 1977: Jovacko kliziste . Erozija 8. Lazarevic, R. 2000: Klizišta. Beograd. Lee, S., Ryu, J. H., Won, J. S., Park, H. J. 2004: Determination and application of the weights for landslide susceptibility mapping using an artificial neural network. Engineering Geology 71-3,4. DOI: https://doi.org/10.1016/S0013-7952(03)00142-X Lollino,P.,Giordan,D.,Allasia,P.2014:TheMontagutoearthflow:Aback-analysisoftheprocessofland-slide propagation. Engineering Geology 170. DOI: https://doi.org/10.1016/j.enggeo.2013.12.011 Lukovic, T. M. 1951: Važniji tipovi naših klizišta i mogucnosti njihovog saniranja. Geološki Vesnik 9. Mahalingam, R., Olsen, M. J. 2016: Evaluation of the influence of source and spatial resolution of DEMs on derivative products used in landslide mapping. Geomatics, Natural Hazards and Risk 7-6. DOI: https://doi.org/10.1080/19475705.2015.1115431 McKean, J., Roering, J. 2004: Objective landslide detection and surface morphology mapping using high-resolution airborne laser altimetry. Geomorphology 57-3,4. DOI: https://doi.org/10.1016/ S0169-555X(03)00164-8 Mészáros, .. 2013: Spatial analysis of geohazard on the Fruška Gora mountain. Ph.D. thesis, University of Szeged. Szeged. Pavlovic, R., Calic, J., Djurovic, P., Trivic, B., Jemcov, I. 2012: Recent landform evolution in Serbia. Recent Landform Evolution. The Carpatho-Balkan-Dinaric Region. Dordrecht. Petrovic,V.,Stankovic,S.1981:VelikoklizišteuseluJovac.Simpozijumistraživanjeisanacijaklizišta.Beograd. Prelevic, D., Foley, S. F., Romer, R. L., Cvetkovic, V., Downes, H. 2005: Tertiary ultrapotassic volcanism in Serbia:Constraintsonpetrogenesisandmantlesourcecharacteristics.JournalofPetrology46-7.DOI: https://doi.org/10.1093/petrology/egi022 Pre-processing algorithms and landslide modelling on remotely sensed DEMs. Geomorphology 113-1,2. DOI: https://doi.org/10.1016/j.geomorph.2009.03.023 Rogers, D. J., Chung, J. 2016: Mapping earthflows and earthflow complexes using topographic indicators. Engineering Geology 208. DOI: https://doi.org/10.1016/j.enggeo.2016.04.025 Santini, M., Grimaldi, S., Nardi, F., Petroselli, A., Rulli, M. C. 2010: Schulz, W. H. 2007: Landslide susceptibility revealed by LIDAR imagery and historical records, Seattle, Washington. Engineering Geology 89-1,2. DOI: https://doi.org/10.1016/j.enggeo.2006.09.019 Soeters, R., van Westen, C. J. 1996: Slope instability recognition, analysis and zonation. Landslides. Investigation and Mitigation. Washington D. C. Tarolli, P., Sofia, G., Dalla Fontana, G. 2012: Geomorphic features extraction from high resolution topog­raphy: Landslide crowns and bank erosion. Natural Hazards 61-1. DOI: https://doi.org/10.1007/ s11069-010-9695-2 Tarolli,P.,Tarboton,D.G.2006:Anewmethodfordeterminationofmostlikelylandslideinitiationpoints andtheevaluationofdigitalterrainmodelscaleinterrainstabilitymapping.HydrologyandEarthSystem Sciences 10. DOI: https://doi.org/10.5194/hess-10-663-2006 The international geotechnical societies’ UNESCO working party for world landslide Inventory: Multilingual landslide glossary. Richmond, 1993. UNESCO working party on world landslide inventory: A suggested method for describing the activity of a landslide. Bulletin of the International Association of Engineering Geology 47. Urciuoli,G.,Comegna,L.,DiMaio,C.,Picarelli,L.2016:TheBasentovalley:Anaturallaboratorytounder-stand the mechanics of earthflow. Rivista Italiana di Geotecnica 50-1. Van Den Eeckhaut, M., Poesen, J., Verstraeten, G., Vanacker, V., Nyssen, J., Moeyersons, J., van Beek, L. P. H., Vandekerckhove, L. 2007: Use of LIDAR-derived images for mapping old landslides under for­ est. Earth Surface Processes and Landforms 32–5. DOI: https://doi.org/10.1002/esp.1417 Varnes,D.J.1978:Slopemovementtypesandprocesses.Landslides,AnalysisandControl.SpecialReport 176. Washington, D. C. Varnes,D.J.1984Landslidehazardzonation:Areviewofprinciplesandpractice.NaturalHazards3.Paris. Vukanovic,M.,Dimitrijevic,M.,Dimitrijevic,M.N.,Karajicic,Lj.,Rakic,M.O.1970:TumaczaOsnovnu geološku kartu 1:100,000, list Vranje. Savezni geološki zavod. Beograd. Guidelines for contributing authors in Acta geographica Slovenica EDITORIAL POLICIES 1 Focus and scope TheActageographicaSlovenicajournalisissuedbytheZRCSAZUAntonMelikGeographicalInstitute,pub­lishedbythe ZRC SAZU Založba ZRC,and co-published by the Slovenian Academy of Sciencesand Arts. Acta geographica Slovenica publishes original research articles from all fields of geography and relat­ed disciplines, and provides a forum for discussing new aspects of theory, methods, issues, and research findings, especially in Central, Eastern and Southeastern Europe. Thejournalacceptsoriginalresearcharticlesandreviewarticles.Articlespresentingnewdevelopments andinnovativemethodsingeographyarewelcome.Submissionsshouldaddresscurrentresearchgapsand explorestate-of-the-artissues.Research-basedoncasestudiesshouldhavetheaddedvalueoftransnational comparison and should be integrated into established or new theoretical and conceptual frameworks. The target readership is researchers, policymakers, students, and others who are studying or applying geography at various levels. Thejournalisindexedinthefollowingbibliographicdatabases:ClarivateWebofScience(SCIE–Science CitationIndexExpanded;JCR–JournalCitationReport/ScienceEdition),Scopus,ERIHPLUS,GEOBASE Journals, Current Geographical Publications, EBSCOhost, Georef, FRANCIS, SJR (SCImago Journal & Country Rank), OCLC WorldCat, Google Scholar, and CrossRef. 2 Types of articles Unsolicited or invited original research articles and review articles are accepted. Articles and materials or sections of them should not have been previously published or under consideration for publication else­where. The articles should cover subjects of current interest within the journal’s scope. 3 Special issues The journal also publishes special issues (thematic supplements). Special issues usually consist of invited articles and present a special topic, with an introduction by the (guest) editors. The introduction briefly presents the topic, summarizes the articles, and provides important implications. 4 Peer-review process Allarticles are examinedby the editor-in-chief. This includes fact-checking thecontent, spelling and gram­mar, writing style, and figures. Articles that appear to be plagiarized, are badly or ghost-written, have been publishedelsewhere,areoutsidethe scope ofthejournal,orareoflittle interest toreadersof Acta geograph­icaSlovenicamayberejected.Ifthearticleexceedsthemaximumlength,theauthor(s)mustshortenitbefore the article is reviewed. The article is then sent to responsible editors, who check the relevance, significance, originality, clarity, and quality of the article. If accepted for consideration, the articles are then sent to peer reviewer(s) for double-blind review. Articles arerejectedoracceptedbasedon thepeerreviewsand editori­alboard’sdecision. 5 Publication frequency Acta geographica Slovenica is published three times a year. 6 Open-access policy This journal provides immediate open access to the full-text of articles at no cost on the principle of open science,thatmakesresearchfreelyavailabletothepublic.Thereisnoarticleprocessingfee(ArticleProcessing Charge) charged to authors. Digital copies of the journal are stored by the repository of ZRC SAZU and the digital department of Slovenian national library NUK, dLib. The author(s) receive a free print copy. The journal’s publication ethics and publication malpractice statement is available online, as well as information on subscriptions and prices for print copies. AUTHOR GUIDELINES Beforesubmittinganarticle,pleasereadthedetailsonthejournal’sfocusandscope,publicationfrequency, privacystatement,history,peer-reviewprocess,open-accesspolicy,dutiesofparticipants,andpublication ethics (all available at https://ags.zrc-sazu.si). 1 Types of articles Unsolicited or invited original research articles and review articles are accepted. Articles and materials or sections of them should not have been previously published or under consideration for publication else­where. The articles should cover subjects of current interest within the journal’s scope. 2 Special issues The journal also publishes special issues (thematic supplements). Special issues usually consist of invited articles and present a special topic, with an introduction by the (guest) editors. The introduction briefly presents the topic, summarizes the articles, and provides important implications. 3 The articles Researcharticlesmustbepreparedusingthejournal’stemplate(availableathttps://ags.zrc-sazu.si)andcon­tain the following elements: – Title: this should be clear, short, and simple. – Informationaboutauthor(s):submitnames(withoutacademictitles),affiliations,ORCiDs,ande-mail addresses through the online submission system (available at https://ags.zrc-sazu.si). – Highlights: authors must provide 3–5 highlights. This section must not exceed 400 characters, includ­ing spaces. – Abstract: introduce the topic clearly so that readers can relate it to other work by presenting the back­ground, why the topic was selected, how it was studied, and what was discovered. It should contain one or two sentences about each section (introduction, methods, results, discussion, and conclusions). The maximum length is 800 characters including spaces. – Key words: include up to seven informative key words. Start with the research field and end with the place and country. – Maintext:Themaintextmustnotexceed30,000characters,includingspaces(withoutthetitle,affiliation, abstract, key words, highlights, reference list, and tables). Do not use footnotes or endnotes. Divide the articleintosectionswithshort,cleartitlesmarkedwithnumberswithoutfinaldots:1 Sectiontitle.Use only one level of subsections: 1.1 Subsection title. Research articles should have the following structure: • Introduction: present thebackgroundof the researchproblem (trendsandnewperspectives),stateof theart(currentinternationaldiscussioninthefield),researchgap,motivation,aim,andresearchquestions. • Methods:describe the studyarea, equipment, tools, models, programs, data collection, and analysis, define the variables, and justify the methods. • Results:followtheresearchquestionsaspresentedintheintroductionandbrieflypresenttheresults. • Discussion: interpret the results, generalize from them, and present related broader principles and relationships between the study and previous research. Critically assess the methods and their limita­tions,anddiscussimportantimplicationsoftheresults.Clarifyunexpectedresultsorlackingcorrelations. • Conclusion:presentthemainimplicationsofthefindings,yourinterpretations,andunresolvedques­tions, offering a short take-home message. Review articles (narratives, best-practice examples, systematic approaches, etc.) should have the following structure: • Introduction:include1)thebackground;2)theproblem:trends,newperspectives,gaps,andconflicts; and 3) the motivation/justification. • Materialandmethods:provideinformationsuchasdatasources(e.g.,bibliographicdatabases),search terms and search strategies, selection criteria (inclusion/exclusion of studies), the number of studies screened and included, and statistical methods of meta-analysis. • Literaturereview:usesubheadingstoindicatethecontentofthevarioussubsections.Possiblestruc­ture: methodological approaches, models or theories, the extent of support for a given thesis, studies thatagreewithoneanotherversusstudiesthatdisagree,chronologicalorder,andgeographicallocation. • Conclusions:provideimplicationsofthefindingsandyourinterpretations(separatefromfacts),iden­tify unresolved questions, summarize, and draw conclusions. – Acknowledgments:usewhenrelevant.Inthissection,authorscanspecifythecontributionofeachauthor. – Reference list: see the guidelines below. 4 Article submission 4.1 Open journal system Author(s) must submit their contributions through the Acta geographica Slovenica Open Journal System (OJS;availableathttps://ags.zrc.sazu.si)usingtheWorddocumenttemplate(availableathttps://ags.zrc.sazu.si). Enter all necessary information into the OJS. Any addition, deletion, or rearrangement of names of the author(s) in the authorship list should be made andconfirmed by all coauthors before the manuscript has been accepted, and is only possible if approved by the journal editor. Tomakeanonymouspeerreviewpossible,thearticletextandfiguresshouldnotincludenamesofauthor(s). Do not use contractions or excessive abbreviations. Use plain text, with sparing use of bold and italics (e.g. for non-English words). Do not use auto-formatting, such as section or list numbering and bullets. If atext is unsatisfactory, the editorial board mayreturn it to the author(s) for professional copyediting orrejectthearticle.Seethesectiononthepeer-reviewprocess(availableathttps//ags.zrc-sazu.si)fordetails. Author(s) may suggest reviewers when submitting an article. 4.2 Language Articles are published in English. Articles can be submitted in English or Slovenian. Authors must take care of high-quality English text. In the case of poor language, the article is copy- edited/translatedafteracceptancebyaprofessionalchosenbytheeditorialboard.Insuchacase,thetranslation or copyediting costs are borne by the author(s) and must be paid before layout editing. All articles should have English and Slovenian abstracts. 4.3 Supplementary file submission Supplementary files (figures) can be submitted to the OJS packed in one zip file not exceeding 50 MB. 4.4 Submission date The journal publishes the submission date of articles. Please contact the editorial board (ags@zrc-sazu.si) with any questions. 5 Citations Examples for citing publications are given below. Citing »grey literature« is strongly discouraged. 5.1 Citing articles • Bole,D.2004:DailymobilityofworkersinSlovenia.ActageographicaSlovenica44-1.DOI:https://doi.org/ 10.3986/AGS44102 • Fridl, J., Urbanc, M., Pipan, P. 2009: The importance of teachers’ perception of space in education. Acta geographica Slovenica 49-2. DOI: https://doi.org/10.3986/AGS49205 • Gams, I. 1994a: Types of contact karst. Geografia Fisica e Dinamica Quaternaria 17. • Gams, I. 1994b: Changes of the Triglav glacier in the 1955-94 period in the light of climatic indicators. Geografski zbornik 34. • Van Hall, R. L., Cammeraat, L. H., Keesstra, S. D., Zorn, M. 2016: Impact of secondary vegetation suc­cessiononsoilqualityinahumidMediterraneanlandscape.Catena,Inpress.DOI:https://doi.org/10.1016/ j.catena.2016.05.021 (25. 11. 2016). • De Kerk, G. V., Manuel, A. R. 2008: a comprehensive index for a sustainable society: The SSI – The SustainableSocietyIndex.EcologicalEconomics66-2,3.DOI:https://doi.org/10.1016/j.ecolecon.2008.01.029 • Perko, D. 1998: The regionalization of Slovenia. Geografski zbornik 38. • Urry, J. 2004: The ‘system’ of automobility. Theory, Culture and Society 21-4,5. DOI: https://doi.org/ 10.1177%2F0263276404046059 • Yang, D. H., Goerge, R., Mullner, R. 2006: Comparing GIS-based methods of measuring spatial acces­sibilitytohealthservices.JournalofMedicalSystems30-1.DOI:https://doi.org/10.1007/s10916-006-7400-5 5.2 Citing books • Cohen, J. 1988: Statistical power analysis for the behavioral sciences. New York. • Fridl, J., Kladnik, D., Perko, D., Orožen Adamic, M. (eds.) 1998: Geografski atlas Slovenije. Ljubljana. • Hall, T., Barrett, H. 2018: Urban geography. London. DOI: https://doi.org/10.4324/9781315652597 • Hall, C. M., Page, S. J. 2014: The geography of tourism and recreation: Environment, place and space. New York. DOI: https://doi.org/10.4324/9780203796092 • Luc,M.,Somorowska,U.,Szmanda,J.B.(eds.)2015:Landscapeanalysisandplanning,SpringerGeography. Heidelberg. DOI: https://doi.org/10.1007/978-3-319-13527-4 • Nared, J., Razpotnik Viskovic, N. (eds.) 2014: Managing cultural heritage sites in southeastern Europe. Ljubljana. DOI: https://doi.org/10.3986/9789610503675 5.3 Citing chapters of books or proceedings • Gams,I.1987:AcontributiontotheknowledgeofthepatternofwallsintheMediterraneankarst:Acase study on the N. island Hvar, Yugoslavia. Karst and Man, Proceedings of the International Symposium on Human Influence in Karst. Ljubljana. • Hrvatin, M., Perko, D., Komac, B., Zorn, M. 2006: Slovenia. Soil Erosion in Europe. Chichester. DOI: https://doi.org/10.1002/0470859202.ch25 • Komac, B., Zorn, M. 2010: Statisticno modeliranje plazovitosti v državnem merilu. Od razumevanja do upravljanja. Naravne nesrece 1. Ljubljana. • Zorn, M., Komac, B. 2013: Land degradation. Encyclopedia of Natural Hazards. Dordrecht. DOI: https://doi.org/10.1007/978-1-4020-4399-4_207 5.4 Citing expert reports, theses, dissertations and institutional reports • BregValjavec,M.2012:Geoinformaticmethodsforthedetectionofformerwastedisposalsitesinkarstic and nonkarstic regions (case study of dolines and gravel pits). Ph.D. thesis, University of Nova Gorica. Nova Gorica. • Holmes,R.L.,Adams,R.K.,Fritts,H.C.1986:Tree-ringchronologiesofNorthAmerica:California,Eastern OregonandNorthernGreatBasinwithproceduresusedinthechronology developmentworkincluding usermanualforcomputerprogramCOFECHAandARSTAN.ChronologySeries6.UniversityofArizona, Laboratory of tree-ring research. Tucson. • Hrvatin, M. 2016: Morfometricne znacilnosti površja na razlicnih kamninah v Sloveniji. Ph.D. thesis, Univerza na Primorskem. Koper. • Šifrer, M. 1997: Površje v Sloveniji. Elaborat, Geografski inštitut Antona Melika ZRC SAZU. Ljubljana. • World commission on environmental and development 1987: Our common future: Brundtland report. Oxford. 5.5 Citing online materials with authors • Tiran,J.2021:Slovenijasejevcelotiodelavmodro.Metinalista.Internet:https://metinalista.si/sloveni­ja-se-je-v-celoti-odela-v-modro/ (3. 11. 2021). • Davies, G. 2017: The place of data papers: Producing data for geography and the geography of data pro­duction.Geo:GeographyandEnvironment.Internet:https://blog.geographyandenvironment.com/2017/09/27/ the-place-of-data-papers-producing-data-for-geography-and-the-geography-of-data-production/(8.11.2021). 5.6 Citing websites without authors (e.g. websites of projects and institutions) Use in-text citations only. It is not necessary to include a citation in the reference list. The in-text citation should include the URL. 5.7 Citing publicly archived data (e.g. statistical data) Use in-text citations only. It is not necessary to include publicly archived datasets in the reference list. The in-textcitationshouldincludethenameofthedataset,theinstitutionprovidingthedataandthetimeframe of the data used. Whenthedatayoucitedwerepublishedasareport,addittothereferencelistandusethefollowingformat: • Popisprebivalstva,gospodinjstev,stanovanjinkmeckihgospodarstevvRepublikiSloveniji,1991–koncni podatki. Zavod Republike Slovenije za statistiko. Ljubljana, 1993. • Agriculture, forestry and fishery statistics. 2020 edition. Publications Office of the European Union. Luxembourg, 2020. 5.8 Citing geospatial data and cartographic materials Geospatialdatausedinmapsshouldbecitedinthecolophononthemap(seetheTableandFiguressection of the Authors’ Guidelines). It is not necessary to include geospatial data in the reference list. When cartographic materials are published as anindependent monograph, add it to the reference list and use the following format: • Buser, S. 1986: Osnovna geološka karta SFRJ 1 : 100.000, list Tolmin in Videm (Udine). Savezni geološki zavod. Beograd. • Državna topografska karta Republike Slovenije 1 : 25.000, list Brežice. Geodetska uprava Republike Slovenije. Ljubljana, 1998. • FranciscejskikatasterzaKranjsko,k.o.Sv.Agata,listA02.ArhivRepublikeSlovenije.Ljubljana,1823–1869. • The vegetation map of forest communities of Slovenia 1:400,000. Biološki inštitut Jovana Hadžija ZRC SAZU. Ljubljana, 2002. 5.9 Citing legal sources Usein-textcitation.Itisnotnecessarytoincludeacitationinthereferencelist.Thein-textcitationshould include the title of legal document and the year. 5.10 In-text citation examples All references in the reference list are cited in the text. In-text citations should include the last name of the author(s) or the name of the institution, and the year of publication. Separate individual citations by semicolons, arrange citations by year of publication, and separate the page information from author(s)’ namesandyearsbyacomma;forexample:(Melik1955),(Melik,IlešicandVrišer1963;Gams1982a;Gams 1982b;WorldCommissiononEnvironmentandDevelopment1987).Forreferenceswithmorethanthree authors,citeonlythefirst,followedbyetal.:(Meliketal.1956).Givepagenumbersonlyfordirectquotations. Narrativecitations:Perko(2016, 25)states:»Hotspotsare…«orparentheticalcitation(Kokole1974,7–8). Whencitingonlinematerialswithoutauthors,suchasprojectorinstitutionalwebsites,theURLshould be included, for example: »The aim of the LABELSCAPE project is to develop mechanisms for integrat­ ing sustainability labels into tourism policy (https://labelscape.interreg-med.eu).« Whencitingpubliclyarchiveddata,suchasstatisticaldata,informthereaderinthetextwiththename ofdataset,thetimeframe,andtheinstitutionthatprovidesthedata:»The2000–2020populationdataused in the analysis were provided by the Eurostat«. If the statistical data were published as a report, cite the document, e.g. (Popis prebivalstva…1993). When citing legal sources such as legislative acts, white papers, etc., you should provide (short for- mal)titleandtheyear,forexample:»…TheEuropeanCommission’sWhitepaperontransport(2011)sets out ten strategic goals for a competitive and resource-efficient transport system:…« 5.11 Reference list Arrange references alphabetically and then chronologically if necessary. Identify more than one reference by the same author(s) in the same year with the letters a, b, c, etc., after the year of publication: (1999a; 1999b). Use this format for indirect citations: (Gunn 2002, cited in Matei et al. 2014). Include the Digital Object Identifier (DOI) in the reference if available. Format the DOI as follows: https://doi.org/… (for example: https://doi.org/10.3986/AGS.1812). 6 Tables and figures Number all tables in the article uniformly with their own titles. The number and the text are separated by a colon, and the caption ends with a period. Example: Table 1: Number of inhabitants of Ljubljana. Table 2: Changes in average air temperature in Ljubljana (Velkavrh 2009). Tablesshouldcontainnoformattingandshouldnotbetoolarge;itisrecommendedthattablesnotexceed one page. Upload figures to the OJS as separate supplementary files in digital form. If the graphic supplements preparedcannotbeuploadedusingtheseprograms,consulttheeditorialboard(ags@zrc-sazu.si)inadvance. Numberallfigures(maps,graphs,photographs)inthearticleuniformlywiththeirowntitles.Example: Figure 1: Location of measurement points along the glacier. All graphic materials must be adapted to the journal’s format. Illustrations should be exactly 134mm wide (one page) or 64mm wide (half page, one column), and the height limit is 200mm. To makeanonymouspeer review possible, include the name of the author(s) with the title of the illus­tration in the supplementary file metadata, but not in the article text. MapsshouldbemadeindigitalvectorformwithCorelDraw,AdobeIllustrator,orasimilarprogram,espe­cially if they contain text. They can exceptionally be produced in digital raster form with at least 300 dpi resolution, preferably in TIFF or JPG format. For maps made with CorelDraw or Adobe Illustrator, two separate files should be prepared; the original file (.cdr or .ai format) and an image file (.jpg format). For maps made with ArcGIS with raster layers used next to vector layers (e.g., .tif of relief, airborne or satellite image), three files should be submitted: the first with a vector image without transparency together with a legend and colophon (export in .ai format), the second with a raster background (export in .tif for­mat), and the third with all of the content (vector and raster elements) together showing the final version of the map (export in .jpg format). Do not print titles on maps; they should appear in a caption. Save colors in CMYK, not in RGB or other formats. Use Times New Roman for the legend (size 8) and colophon (size 6). List the author(s), scale, source, and copyright in the colophon. Write the colophon in English (and Slovenian, if applicable). Example: Scale: 1:1,000,000 Content by: Drago Perko Map by: Jerneja Fridl Source: Statistical Office of the Republic of Slovenia 2002 © 2005, ZRC SAZU Anton Melik Geographical Institute Graphs should be made in digital form using Excel on separate sheets and accompanied by data. Photos must be in raster format with a resolution of 240 dots per cm or 600 dpi, preferably in .tif or .jpg formats; that is, about 3,200 dots per page width of the journal. Figures containing a screenshot should be prepared at the highest possible screen resolution (Control Panel\AllControlPanelItems\Display\ScreenResolution).ThefigureismadeusingPrintScreen,andthe capturedscreenispastedtotheselectedgraphicprogram(e.g.,Paint)andsavedas.tif.Thesizeoftheimage or its resolution must not be changed. Examplesofappropriate graphicdataformats: see the templates of maps in cdr and mxd files (available at https://ags.zrc.sazu.si) for a full-page map in landscape layout and an example of the correct file struc­ture (available at https://ags.zrc.sazu.si) for submitting a map created with ESRI ArcGIS. SUBMISSION PREPARATION CHECKLIST Aspart ofthesubmissionprocess, authorsarerequired to checkofftheirsubmission’s compliancewith all ofthefollowingitems,andsubmissionsmaybereturnedtoauthorsthatdonotadheretotheseguidelines. • I, the corresponding author, declare that this manuscript is original, and is therefore based on original research, done exclusively by the authors. All information and data used in the manuscript were pre­paredbytheauthorsortheauthorshaveproperlyacknowledgedothersourcesofideas,materials,methods, and results. • Authors confirm that they are the authors of the submitting article, which is under consideration to be published (print and online) in the journal Acta geographica Slovenica by Založba ZRC, ZRC SAZU. • All authors have seen and approved the article being submitted. • The submission has not been previously published, nor it is under consideration in another journal (or an explanation has been provided in Comments to the Editor). Authors have disclosed any prior post­ing, publication or distribution of all or part of the manuscript to the Editor. • Upon publishing an article in a journal the authors agree to license non-exclusive copyrights to ZRC SAZU (Založba ZRC): they retain the copyright in the scope that enables them to continue to use their work, even by publishing it in one of the personal or institutional repositories before the publication of the article in the journal. • AuthorsconsenttothepublicationoftheirworksunderCreativeCommonsAttribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0). • Permissionhasbeenobtainedfortheuse(inprintedandelectronicformat)ofcopyrightedmaterialfrom other sources, including online sources. Restrictions on the transfer of copyright on this material have been clearly indicated. • All the necessary permits to work with people have been obtained in the research related to the article (in accordance withthe applicable laws and institutional guidelines and approved by the relevant insti­tutions). • The journal policies and guidelines have been reviewed and followed. • Themetadata(title,abstract,keywords,authors,affiliation,ORCiD,etc.)areprovidedinEnglish(Slovenian authors must provide the metadata also in Slovenian language). • The list of authors is complete. Failure to do so may result in co-authors not being listed on the article at publication. • The submission is in Microsoft Word format and the document templatewas used (single-spaced text, 12-point font, no formatting except italics and bold). • The article has been checked for spelling and grammar. • FiguresarenotembeddedintheWordfileandareprovidedasasupplementaryfile:editablevectorformat (e.g., cdr, ai) for maps and illustrations; tif for photographs; xlsx for graphs. The Word file includes only figure captions. • Tables are placed in the Word file with text at the appropriate place. • The reference list was prepared following the guidelines. • All references in the reference list are cited in the text. • Where available, URLs and DOI numbers for references are provided. • Supplementary files are in one .zip file. • Authors agree that any costs of English proofreading are borne by the author(s). No additional costs are associated with the submission. • The instructions for ensuring a double-blind review have been followed. ACTA GEOGRAPHICA SLOVENICA EDITORIAL REVIEW FORM This is a review form for editorial review (version 14) of an article submitted to the AGS journal. This is an original scientific article. (The articleis originalandthe firstpresentation of research results withthefocuson methods, theoretical aspects or a case study.) • Yes • No The article follows the standard IMRAD/ILRAD scheme. • Yes • No The article’s content is suitable for reviewing in the AGS journal. (The article is from the field of geography or related fields of interest, the presented topic is interesting for thereadersofActageographicaSlovenicaandwellpresented.Incaseofnegativeansweraddcommentsbelow.) • Yes • No Editorial notes regarding the article’s content. The reference list is suitable (the author cites previously published articles with similar topics from other relevant geographic scientific journals). • Yes, the author cited previously published articles on a similar topic. • No, the author did not cite previously published articles on a similar topic. Notes to editor-in-chief regarding previously published scientific work. Is the language of the article appropriate and understandable? RECOMMENDATION OF THE EDITOR • The article is accepted and can be sent to the review process. • Reconsider after a major revision (see notes). • The article is rejected. ACTA GEOGRAPHICA SLOVENICA REVIEW FORM This is Acta geographica Slovenica review form (version 7). 1 RELEVANCE Are the findings original and the article is therefore a significant one? • yes • no • partly Is the article suitable for the subject focus of the AGS journal? • yes • no 2 SIGNIFICANCE Does the article discuss an important problem in geography or related fields? • yes • no • partly Does it bring relevant results for contemporary geography? • yes • no • partly What is the level of the novelty of research presented in the article? • high • middle • low 3 ORIGINALITY Has the article been already published or is too similar to work already published? • yes • no Does the article discuss a new issue? • yes • no Are the methods presented sound and adequate? • yes • no • partly Do the presented data support the conclusions? • yes • no • partly 4 CLARITY Is the article clear, logical and understandable? • yes • no If necessary, add comments and recommendations to improve the clarity of the title, abstract, keywords, introduction, methods or conclusion: 5 QUALITY Isthearticletechnicallysound?(Ifnot,theauthorshoulddiscusswiththeEditorialBoard[ags@zrc-sazu.si] for assistance.) • yes • no Does the article take into account relevant current and past research on the topic? • yes • no Propose amendments, if no is selected: Is the references list at the end of the article adequate? • yes • no Propose amendments, if no is selected: Is the quoting in the text appropriate? • yes • no • partly Propose amendments, if no is selected: Which tables are not necessary? Which figures are not necessary? COMMENTS OF THE REVIEWER Comments of the reviewer on the contents of the article: Comments of the reviewer on the methods used in the article: RECOMMENDATION OF THE REVIEWER TO THE EDITOR-IN-CHIEF Please rate the article from 1 [low] to 100 [high] (this will NOT be presented to the author): Personal notes of the reviewer to the editor-in-chief (this will NOT be presented to the authors): COPYRIGHT NOTICE TheActageographicaSlovenicaeditorialboardandthepublisher,theZRCSAZUAntonMelikGeographical Institute, are committed to ensuring ethics in publication and the quality of published books and journals by following the Acta Geographica Slovenica Publication Ethics and Publication Malpractice Statement. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. Authorsmustrespectthecopyrightrulesofdataowners;forexample,therulesoftheSlovenianSurveying and Mapping Authority are available at its webpage. ForthearticlesenttoActageographicaSlovenica,authorsagreethatallmoralrightsoftheauthorsremain with the authors; material rights to reproduction and distribution in Slovenia and other countries are exclusively ceded to the publisher for no fee, for all time, for all cases, for unlimited editions, and for all media; and material rights to the article figures (maps, photos, graphs, etc.) are ceded to the publisher on a non-exclusive basis. Authors allow publication of the article or its components on the internet. Authors give permission to the publisher to modify the article to conform to its guidelines. Authors shall provide a professional translation of articles not originally in English. The name of the translator must be reported to the editor. No honoraria are paid for articles in Acta geographica Slovenica or for the reviews. The first author of the article shall receive one free copy of the publication. PRIVACY STATEMENT Bysubmittingtheirarticlesorothercontributionstheauthorsandreviewersconsenttocollectionandpro­cessingoftheirpersonaldata(likename,surnameandemailaddress)whichenableeffectivecommunication, editing and publication of articles or other contributions. The names and e-mail addresses provided to this journal site will be used exclusively for the stated purposes of this journal and will not be made available for any other purpose or to any other party. PUBLISHER Anton Melik Geographical Institute Research Center of the Slovenian Academy of Sciences and Arts PO Box 306 SI–1001 Ljubljana Slovenia SOURCES OF SUPPORT ThejournalissubsidizedbytheSlovenianResearchAgencyandisissuedintheframeworkoftheGeography ofSlovenialong-termcoreresearchprogramme(P6-0101).ThejournalisalsosupportedbytheSlovenian Academy of Sciences and Arts. JOURNAL HISTORY Acta geographica Slovenica (print version: ISSN: 1581-6613, digitalversion: ISSN: 1581-8314) was founded in1952.ItwasoriginallynamedGeografskizbornik/Actageographica(printISSN0373-4498,digitalISSN: 1408-8711). Altogether42volumeswerepublished. In2002 GeographicaSlovenica (ISSN0351-1731,founded in 1971, 35 volumes) was merged with the journal. Since2003(fromvolume43onward)thenameofthejointjournalhasbeenActageographicaSlovenica. The journal continues the numbering system of the journal Geografski zbornik / Acta geographica. Until 1976, the journal was published periodically, then once a year, from 2003 twice a year and from 2019 three times a year. The online version of the journal has been available since 1995. In 2013, all volumes of the magazine were digitized from the beginning of its publication to 1994 inclusive. Allarticlesofthejournalareavailablefreeofchargeindigitalformonthejournalwebsitehttp://ags.zrc­sazu.si. Thoseinterestedinthehistoryofthejournalareinvitedtoreadthearticle»TheHistoryofActageographica Slovenica« in volume 50-1. ISSN: 1581-6613 UDC – UDK: 91 ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKI ZBORNIK 61-2 2021 © 2021, ZRC SAZU, Geografski inštitut Antona MelikaPrint/tisk: Present, d.o.o. Ljubljana 2021 ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKI ZBORNIK 61-2 • 2021 Contents Ðordije VasiljeVic, Milica Began, Miroslav Vujicic, Thomas Hose, uglješa sTankoVDoesgeositeinterpretationleadtoconservation?A casestudyoftheSicevoGorge(Serbia) 7 gabrijela PoPoVic, Dragiša sTanujkic, Predrag MiMoVic, goran MiloVanoVic,Darjan karaBašeVic, Pavle BrzakoVic, aleksandar BrzakoVicAnintegratedSWOT –extendedPIPRECIAmodelforidentifyingkeydeterminantsoftourism development:ThecaseofSerbia 23 robert kalBarczyk, eliza kalBarczyk Precipitationvariability,trendsandregionsinPoland:Temporalandspatialdistributionintheyears1951–2018 41 ivana crljenko, Matjaž geršic A comparisonofthebeginningsofexonymstandardizationinCroatianandSlovenian 73 Tadej Brezina, jernej Tiran, Matej ogrin, Barbara laaCOVID-19impactondailymobilityinSlovenia 91 Maruša goluŽa, Maruška šuBic-koVac, Drago kos, David BoleHowthestatelegitimizesnationaldevelopmentprojects:TheThirdDevelopmentAxis casestudy,Slovenia 109 Tin lukic, Tanja Micic Ponjiger, Biljana Basarin, Dušan sakulski,Milivoj gaVriloV, slobodan MarkoVic, Matija zorn, Blaž koMac,Miško MilanoVic, Dragoslav PaVic, Minucer Mesaroš, nemanjaMarkoVic, uroš DurleVic, cezar Morar, aleksandar PeTroVic ApplicationofAngotprecipitationindexintheassessmentofrainfallerosivity:VojvodinaRegioncasestudy(NorthSerbia) 123 janij oBlak, Mira koBolD, Mojca šraj TheinfluenceofclimatechangeondischargefluctuationsinSlovenianrivers 155 Vladimir sTojanoVic, Dubravka Milic, sanja oBraDoVic, jovana VanoVac,Dimitrije raDišic Theroleofecotourismincommunitydevelopment:ThecaseoftheZasavicaSpecialNature Reserve,Serbia 171 Marko V. MilošeVic, Dragoljub šTrBac, jelena calic, Milan raDoVanoVicDetectionofearthflowdynamicsusingmedium-resolutiondigitalterrainmodels:Diachronic perspectiveoftheJovacearthflow,SouthernSerbia 187 ISSN 1581-6613 9 771581 661010