Groundwater vulnerability to nitrate pollution of alluvial aquifers in Slovenia – Lower Savinja Valley case study Ranljivost podzemne vode glede na nitratno onesnaženje v aluvialnih vodonosnikih Slovenije – primer Spodnje Savinjske doline Jože UHAN Agencija Republike Slovenije za okolje, Vojkova 1b, SI-1000 Ljubljana, Slovenija; e–mail: joze.uhan@gov.si Prejeto / Received 29. 9. 2016; Sprejeto / Accepted 24. 4. 2017; Objavljeno na spletu / Published online 9.6.2017 Dedicated to Professor Jože Pezdič on the occasion of his 70th birthday Key words: groundwater vulnerability, nitrate pollution, weights-of-evidence modelling Ključne besede: ranljivost podzemne vode, nitratno onesnaženje, modeliranje teže evidenc Abstract The article introduced an upgraded approach to assessing the groundwater vulnerability to nitrate pollution. By using the results of field measurements and process-based models outputs, author takes into account effects of nitrogen biogeochemical processes, that were hitherto underestimated in the evaluation schemes. The upgraded methodological self-validated approach to vulnerability assessment in Lower Savinja Valley case study increases reliability and thus effectiveness of decision-making in the water management. This was achieved by using the process-based models outputs in the new pattern classification schemes with the predictions of pollution phenomena. Spatial prediction of groundwater nitrate pollution probability and vulnerability classification of the study area in Lower Savinja Valley was assessed by weights-of-evidence model (WofE). The increased degree of probability for the groundwater contamination with nitrates was determined for 62.5 percent of the aquifer area of the Lower Savinja Valley. About 27 percent of the most nitrate vulnerable areas in Lower Savinja Valley need groundwater nitrate mitigation through land-use measures and public sewage system construction. Izvleček Članek predstavlja nadgrajen pristop ocenjevanja ranljivosti na nitratno onesnaženje podzemnih voda. Ob uporabi rezultatov terenskih meritev in izhodov fizikalno zasnovanih modelov avtor upošteva tudi učinke dušikovih biogeokemičnih procesov, ki so bili v dosedanjih ocenjevalnih shemah podcenjeni. Nadgrajen metodološki samopotrditveni pristop ocenjevanja ranljivosti podzemne vode na primeru Spodnje Savinjske doline zvišuje zanesljivost in učinkovitost odločanja pri upravljanju voda. V ta namen so bili izhodi procesno zasnovanih modelov uporabljeni v novih prostorskih klasifikacijskih shemah, ki omogočajo napoved verjetnosti pojava onesnaženja. Z modelom teže evidenc WofE je bila ocenjena verjetnost pojava z nitratom onesnažene podzemne vode v študijsko izbranem aluvialnem vodonosniku. Povišana stopnja verjetnosti onesnažene podzemne vode z nitratom je bila ugotovljena na 62,5 odstotkih območja vodonosnika Spodnje Savinjske doline. Na okoli 27 odstotkih najbolj ranljivih območij Spodnje Savinjske doline so za zmanjšanje onesnaženosti podzemne vode z nitrati potrebni ukrepi na področju rabe prostora in izgradnje sistema odvodnje komunalne odpadne vode. GEOLOGIJA 60/1, 27-35, Ljubljana 2017 https://doi.org/10.5474/geologija.2017.002 © Author(s) 2017. CC Atribution 4.0 License Introduction Groundwater vulnerability maps are an im- portant tool of the water management deci- sion-making process. Information on groundwa- ter vulnerability has been required by the Nitrate Directive (oFFicial journal oF the euroPean coM- Munities, 1991b) and the Urban Waste Water Di- rective (oFFicial journal oF the euroPean coM- Munities, 1991a) for nitrate pollution management and by the Water Framework Directive (oFFicial journal oF the euroPean coMMunities, 2000) for programme-of-measures planning. The Nitrate Directive initiated nitrate vulnerable zones as a land zonation for action plan implementation. The WFD operative programme of measures requires identification of the potentially vulnerable prior- ity areas within groundwater bodies for cost-ef- 28 Jože UHAN fective measures planning. Most of the previous groundwater vulnerability assessments used a variety of parametric point count methods with a relative rating for the potential of groundwater contamination, e.g. the DRASTIC index, devel- oped as a linear combination of some of the in- trinsic properties of aquifers (aller et al., 1987) or the SINTACS index, adapted to conditions in the Mediterranean region (civita, 1990). These methods require validation with field measure- ments, such as a tracer test, groundwater resi- dence studies or investigation of actual pollution incidents. Gogu and Dassargues (2000) identified the integration of results from process-based models in vulnerability mapping techniques as a new research challenge in groundwater vulnera- bility assessment. Groundwater nitrate pollution in Slovenian al- luvial aquifers has been a major concern in recent years, and about 37 percent of the groundwater in these aquifers has poor chemical status according to WFD criteria, most frequently due to a high concentration of nitrate (cviTanič et al., 2010). Process-based modelling outputs of groundwater recharge, groundwater flow velocity and nitrate leached from the soil profile in the Lower Sav- inja Valley aquifer with poor chemical status are available. With the use of statistical probabilistic classification methods, field-verified groundwater nitrate vulnerability was defined and interpreted with the help of surface-water and groundwater isotopic composition. The aim of this study was to assess the spatial prediction of the probability for increased groundwater nitrate concentration in order to plan the groundwater nitrate reduction measures and optimize the programme for moni- toring the effects of these measures. Study area The Lower Savinja Valley, an area of about 80 square kilometres in Central Slovenia, was se- lected for this study of groundwater vulnerabili- ty to nitrate pollution. The area is situated in the tectonic trench between Kamnik-Savinja Alps on the north and “Posavje fault” tectonic system on the south. Lower Savinja Valley is a tectonic depression, filled with alluvial sediments from Pliocene, Pleistocene and Holocene period. The shallow unconfined Lower Savinja Valley aquifer consists of low permeable Pliocene sediments fill- ing a Miocene depression. On top of the Pliocene sediments are deposited Pleistocene and Holo- cene layers (Buser, 1979), mainly gravel and sand with some interbedded conglomerate and clay intercalations (uhan, 2011). The average thick- ness of middle- to low-permeable Pleistocene (K = 2.0·10-5 m/s to 2.0·10-4 m/s) and high-permeable Holocene sediments (K = 1.1∙10- 3 to 1.1·10-2 m/s) is up to 30 metres (Käss et al., 1976). Shallow eu- tric fluvisoils are prevalent on the sandy-gravely alluvium of the lowest terrace along the Savinja River (Fig. 1). Further away from the river, high- er terraces on both sides are covered by variously deep eutric cambisoil. The northern part of the valley is covered with low-permeable eutric gley- soil (PKS, 2007). The Lower Savinja Valley aqui- Fig. 1. a) Location of the Lower Savinja Valley study area and b) map of quaternary alluvial ter- races with measurements points. 29Groundwater vulnerability to nitrate pollution of alluvial aquifers in Slovenia – Lower Savinja Valley case study fer is alluvial lowland area, mainly recharged di- rectly by precipitation from surface, and locally by infiltration from surface streams. The average annual precipitation is about 1100 mm and the surface runoff coefficient is very low. The ground- water table in the Lower Savinja Valley aquifer is shallow. According to the national groundwa- ter monitoring network during the period 1986 - 2005, average depth to the groundwater is from 0.7 to 7.3 metres. Amplitude of the groundwater level is in the range of 1.4 m to 7.5 m. The Lower Savinja Valley aquifer provides about five percent of the total renewable ground- water quantities of all Slovenian alluvial aq- uifers (anDjelov, 2009). An important part of Lower Savinja Valley regional water demand is covered by pumping groundwater from the allu- vial aquifers of the plain, where, even a decade ago, conflicts of interest occurred among the lo- cal population due to agricultural activities. The region of Lower Savinja Valley is primarily re- nowned as the “valley of hops”, with intensive hops production. One half of the Lower Savinja Valley aquifer area (50.4 %) is in use for agricul- tural purposes (20.9 % is pastures, 18.5 % fields and gardens, 8.5 % hops etc.), and 34 percent of the total area is urbanized (CEC, 1994). The sew- age system is still in the process of construction in areas with highly dispersed urbanisation. Recent analysis of national groundwater mon- itoring data from Lower Savinja Valley in the period 2006 - 2008 shows poor chemical status of groundwater (cviTanič et al., 2010). The trend of nitrate concentration is statistically insig- nificant, showing no groundwater quality im- provement. The nitrate concentration is higher than the EU maximum allowable concentration 50 mg/l for the drinking water limit value (oFFi- cial journal oF the euroPean coMMunities, 1980) in many wells and boreholes, including the main drinking water pumping station. A growing need exists for a more detailed delineation of the aq- uifer, and for spatial prediction of the probability for increased groundwater nitrate concentration in order to optimize the groundwater monitoring programme and the programme of measures. Data and methods A campaign of field measurements on a month- ly basis was carried out in the period between 2008 and 2009. Multiprobe ion-specific elec- trodes with ±2 mg/l-N were controlled by a set of groundwater samples for laboratory nitrate deter- mination using ion chromatography (ISO 10304- 1:2007). Accuracy for the in-situ measurements of groundwater temperature, electrical conductivi- ty, dissolved oxygen, pH and redox potential was ±0.1°C, ±0.001 mS/cm, ±0.2 mg/l, ±0.2 and ±20 mV respectively. Isotope information as interpreta- tive support in the delineation of nitrate vulnera- ble zones was collected by seasonal sampling and determination of δ15N, δ15N-NO3 - and δ13C-DIC in selected surface flows and groundwaters during the period 2008 - 2009 (uhan, 2011). Monthly measurements of groundwater tem- perature averaged at 11.9 °C with the range of 9.7 and standard deviation of 2 °C. Electrical con- ductivity was in the range of 719 mS/cm with the 704.4 and 139.8 mS/cm as the average and the standard deviation respectively. The average of groundwater pH value was 7.2 with the range of 5.3 and standard deviation of 0.3. The ground- water nitrate concentration varied considerably from 0.8 to 119.9 mg/l with average of 46.4 and standard deviation of 25.8 mg/l. According to our analysis of variance (uhan et al., 2009), most of the variance in nitrate concentrations in ground- water of Lower Savinja Valley was due to spatial variation. Hence, the field measurements have been extended to 224 randomly chosen ground- water nitrate monitoring locations (Fig. 1b). Monitoring sites have been classified for fur- ther analysis into two groups on the basis of dis- tribution of groundwater nitrate concentration with 20 mg/l as a threshold value. The threshold value to separate background and anomalous ni- trate concentrations is necessary to be selected on the basis of distribution characteristics and not after the pre-established values, such as the EU threshold value or trigger value for uprising trends. The threshold value for groundwater ni- trate vulnerability assessment in Lower Savinja Valley has been identified from the cumulative probability plot as the inflection point value (Pan- no et al., 2006; Masetti et al., 2009). The threshold value, adjusted to 20 mg/l in Lower Savinja Val- ley case study, defined as the cumulative proba- bility plot inflection point, is interpreted to rep- resent “anthropogenic impact” concentration of nitrate in groundwater (uhan, 2011). Among the different statistical approach- es for pattern classification, including artificial neural networks and neuro-fuzzy classification systems, weights-of-evidence (WofE) was select- ed as the method with the highest prediction ac- curacy in the Lower Savinja Valley groundwater nitrate vulnerability case study. The WofE mod- elling technique (BonhaM-carter et al., 1988), as a part of the Arc Spatial Data Modeller exten- sion (KeMP et al., 2001) implemented in ArcView GIS, is a data-driven method which combines known occurrences of phenomenon (training points) with available spatial data (predictor evidence) in a predictive response (phenomena occurrences conditional probability map). The WofE technique is based on the Bayesian idea of phenomena occurrences probability before (prior probability) and after consideration of any pre- dictor evidence (posterior probability). The prior probability of the phenomena P(D) is the relation between the number of unit cells containing an occurrence (D) and total number of unit cells in the study area (T): . , expressed as odds by: The probability of new phenomena on the ba- sis of predictor evidence present (B) or absent (B) is, after the Bayesian theorem, expressed as a posterior probability: 30 Jože UHAN Prior and posterior probability of the j-th pre- dictor map can be measured by positive (W+) and negative weights (W-), which indicate the associa- tion between a phenomena and a prediction pattern: The difference between weights defines the contrast (C=W+-W-), which is the overall measure of spatial association between the training points and evidential theme. The contrast was used as a parameter for assessment of the pattern as a predictor. Absolute weights values under 0.5 are mildly predictive; between 0.5 and 1 are moder- ately predictive; and values above 1 are strongly predictive (KeMP et al., 2001). Weights-of-Evidence modelling After extensive sensitivity analysis of the available evidential themes, the outputs of three empirical/numerical models have been used as evidential themes for prediction of groundwater nitrate pollution probability and vulnerability classification of the study area: long-term groundwater recharge (Fig. 2a), nitrogen load in seepage water (Fig. 2b) and groundwater flow velocity (Fig. 2c). , , ( ) TDDP = ( ) ( )( ) DT D DP DPDO − = − = 1 ( ) ( ) ( )( )BP DBP DPBDP = ( ) ( ) ( )( )BP DBP DPBDP = )( )( DBP DBP nlW j j j = + )( )( DBP DBP nlW j j j = −  Fig. 2. a) Groundwater long-term recharge (anDjelov, 2009), b) nitrogen load in seepage water (uhan, 2011) and c) groundwater flow velocity (viŽinTin, 2009). 31Groundwater vulnerability to nitrate pollution of alluvial aquifers in Slovenia – Lower Savinja Valley case study The long-term groundwater recharge of the Lower Savinja Valley aquifer has been modelled with the GROWA water-balance model (KunKel & wenDlanD, 2002) using high-resolution digital data of geology, topography, soil, land use, surface waters and climate. Real evapotranspiration was calculated according to the method of renGer and wessoleK (1996), using the national meteorolog- ical monitoring database. In order to determine groundwater recharge, a runoff separation was performed. The model was validated using the national hydrological monitoring database, and the Nash-Sutcliff model efficiency coefficient 0.79 indicated good simulation (anDjelov, 2009). The 2008 annual average of groundwater recharge in Lower Savinja Valley was about 320 millimetres. The nitrogen load in seepage water in Low- er Savinja Valley was modelled with the De- Nitrification-DeComposition biogeochemical model (DNDC), developed as a field-scale, pro- cess-based, mechanistic model of N and C dy- namics in agroecosystems (li et al., 1992). DNDC consists of the six sub-models for soil climate, crop growth, decomposition, nitrification, deni- trification, and fermentation. The six interacting sub-models include the fundamental factors and reactions, which integrate carbon and nitrogen cycles into a computing system. Using the data of climate, soil and use lande of Lower Savinja Valley, nine simulations for 2008 were performed based on the different scenario and combinations of soils and crops. Nitrogen leaching rates for the year 2008 modelled by DNDC in Lower Savin- ja Valley are in range from 1.7 to 36.9 kilograms of nitrogen per hectare. The comparison of the DNDC / GLEAMS model results for Latkova vas field experiment from year 2000 indicate the ade- quacy of DNDC model use in further vulnerabil- ity studies of shallow alluvial aquifers. Groundwater flow velocity has been calculat- ed through hydraulic potentials with the numer- ical solution of the diffusion equation, estimat- ed with the finite element subsurface flow and transport simulation system FEFLOW (Diersch, 2009). The groundwater model of Lower Savinja Valley modelled a two-layer aquifer with one wa- ter table (viŽinTin, 2009). The values of hydraulic conductivity of Holocene sediments range from 8·10-3 m/s to 5·10-2 m/s and the values of hydrau- lic conductivity of Pleistocene sediments are to be found around 10-4 m/s. A structural palaeo- depression is taken into consideration north of the present bed of the river Savinja, which rep- resents its former riverbed with increased hy- draulic conductivity. Modelled groundwater flow velocity was in the range of up to 25 metres per day in the major part of the aquifer, increasing to 100 metres a day in the zones of preferential groundwater flows (viŽinTin, 2009). The output data layers of the above mentioned models have been generalized and uniformly used as input in weights-of-evidence modelling for de- lineation of relative groundwater nitrate vulnera- ble zones as a response theme map (Fig. 3). Results and discussion The training data set in the Lower Savinja Val- ley aquifer consists of data from 170 groundwater wells and piezometers with a concentration of nitrate above the threshold value. The measure- ment locations with a concentration higher than 20 mg NO3 - per litre of groundwater have been considered as training points. The spatial asso- ciation between the training data points and the evidential theme classes has been initially calcu- lated as contrast (C), which combines the effects of the positive and negative weights (C=W+-W-). Due to a relatively small number of wells and pie- zometers with nitrate pollution, evidential themes with many classes result in noisy and unreliable estimates of weights. It is these advantageous to generalize and simplify themes in these cases (BonhaM-carter et al., 1989). Evidential themes in Lower Savinja Valley have been generalized with the maximization of the contrasts, which re- sulted in: six classes for groundwater recharge, four classes for nitrogen load and five classes for groundwater flow velocity. According to the cal- culated confidence value, the most important con- tribution to the final response theme was assessed for the groundwater recharge evidential theme, followed by the nitrogen load evidential theme. High values (> 95 %) of the ratio between the posterior probability and its standard deviation in the 97 % of the modeled area indicate that the uncertainty is relatively small compared to the probability value itself. Conditional independence among the evidential themes used in the model, as an important assumption of the WofE model was calculated at 0.93, being within the range 1±0.15 that generally indicates no dependence amongst evidential themes (BaKer et al., 2007). Evidential themes, representing groundwater recharge, nitrogen load and groundwater flow velocity, were applied to generate the response 32 Jože UHAN theme with posterior probability values rang- ing from 0.00135 to 0.0997. The response theme values describe the relative probability that a 100×100 metre spatial unit will have a groundwa- ter nitrate concentration higher than the training points threshold value of 20 mg/l with regard to the prior probability value of 0.0216. Based on the definition of the training point, higher posterior probability values correspond with more ground- water vulnerable cells and lower posterior proba- bility values correspond to less vulnerable areas. The highest probability of groundwater nitrate vulnerability zones has been found to be general- ly in the southeastern part of the Lower Savinja Valley aquifer. The WofE posterior probability response theme of the Lower Savinja Valley aquifer was separated into three classes of relative nitrate vulnerability based on the distinction in a chart of the cumulative study area vs. posterior proba- bility values. The vulnerability class breaks were defined by selecting discontinuity in the graph of posterior probability vs. cumulative percent of the modelled area, where was a significant in- crease in probability detected: 0.022 and 0.034. Higher posterior probability values correspond with more vulnerable areas, based on the defini- tion of training. The most sensitive area has been mostly designated within the lower and middle alluvial terrace of Lower Savinja Valley. A sig- nificant part of the drinking water protection areas is most vulnerable to groundwater nitrate pollution with high risk due to groundwater ni- trate transport in the saturated zone from up- stream sites of the aquifer. The parametric point count methods are gen- erally not able to describe and analyse important physical processes, such as nitrification/denitrifi- cation and nitrate dilution in the aquifer (DeBer- narDi et al., 2008). The knowledge of geochemical processes and pollution sources is necessary for interpretation of the groundwater vulnerability results and the isotopic signature of nitrate in groundwater is valuable evidence (uhan, 2011). Correlation between the groundwater nitrate concentrations and isotope δ15N in groundwater nitrate suggested that part of the aquifer was influenced by denitrification, especially at meas- urement points in the northern heavy soils area of the aquifer. In these areas, decreased dissolved oxygen was measured and the model assessed the lowest groundwater nitrate posterior probability. According to KenDall (1998) ranges of δ15N val- ues for the major sources of nitrogen in the hy- drosphere, the isotope δ15N in Lower Savinja Val- ley groundwater nitrate suggests predominant soil (cultivation sources) and/or manure/septic waste nitrate sources. The range of δ15N-NO3 - iso- tope values in the groundwater of Lower Savinja Valley is between +5.11 ‰ and + 21.90 ‰, which falls inside the range, found in areas with com- parable hydrogeological setting and land use in the northeastern part of Slovenia (Pintar, 1996; Pezdič, 1999). The δ15N-NO3 - isotope values in samples from rivers in Lower Savinja Valley were ranged between +3 ‰ and +13 ‰ and grouped to- gether with some groundwater samples from lo- cations where the hydrological impact of the sur- face water on the groundwater flow regime was significant. The δ15N-NO3 - and δ13C-DIC relation reflects the importance of internal and external Fig. 3. Map of relative gro- undwater nitrate vulne- rability assessed by WofE probability approach. 33Groundwater vulnerability to nitrate pollution of alluvial aquifers in Slovenia – Lower Savinja Valley case study sources of dissolved carbon and nitrogen and the degree of processes in the aquifer. The shift in δ13C-DIC toward more negative values was in- dicative of an isotopically light carbon source as oxidation of organic carbon. The isotope infor- mation of predominant soil and manure/septic waste nitrate origin, associated with other local physical and chemical boundary conditions and land use data, offers an interpretative support in the delineation of nitrate vulnerable zones (uhan, 2011; uhan et al., 2011a; 2011b). Conclusions The model outputs of long-term groundwa- ter recharge, nitrogen load in seepage water and groundwater flow velocity were found to be the most relevant evidential themes for the ground- water nitrate vulnerability study of the Lower Savinja Valley aquifer. Through the application of these process-based model results and ground- water field measurements, the efficiency of prob- ability classification weights-of-evidence (WofE) approach to provide verified groundwater nitrate vulnerable maps was tested. The study highlights the superiority of the WofE model over the par- ametric point count relative rating approaches. The WofE model results show the highest predic- tion accuracy and the response theme very well illustrates groundwater vulnerability potential as a posterior probability for increased ground- water nitrate concentration. WofE model gener- ation is dependent upon a training dataset and the results in the self-validation model output as a probability map, displayed in classes of rela- tive vulnerability. About 27 percent of the most nitrate vulnerable areas in Lower Savinja Val- ley need groundwater nitrate mitigation through land-use measures and public sewage system construction. The lowest probability of groundwater ni- trate vulnerability was determined in the are- as with indicated denitrification processes. Field measurements and isotope analysis of ground- water in these parts of Lower Savinja Valley aq- uifer revealed anoxic conditions. The isotope in- formation of predominant soil and manure/septic waste nitrate origin, associated with other local physical and chemical boundary conditions and land use data, offered interpretative support in the delineation of nitrate vulnerable zones. To achieve a more precise nitrate source or mixing sources determination, more complex isotopic composition would be needed. The methodology outlined in this study for ni- trate contaminant vulnerability analysis, using process-based models and the statistical classifi- cation method, can be applied to other areas with a similar hydrogeological setting to get a better characterization of the nature of the contami- nation. The present study again underlines the importance of redox conditions and denitirifica- tion processes for regional groundwater nitrate distribution. The results, obtained in this case study, lead us to envisage additional monitor- ing programs, focused on a field measurements technique and water sampling for isotopes. In the future, an extensive field groundwater pro- file measurement program will be of great im- portance in order to be able to identify contam- ination sensitivity of the aquifer throughout its vertical extent and to optimize the groundwater protection management strategy. Acknowledgements Author gratefully dedicates this article to his PhD advisor, Full Professor Jože Pezdič, PhD, who greatly contributed to the successful completion of this rese- arch study through both his scientific as well as peda- gogical dimensions. This study was supported by the Slovenian Environment Agency and represents part of the Ph.D. research work. The author would like to thank Vlado Savić, Janja Turšič and Mišo Andjelov for their es- sential support during this study. Many thanks to Katherine Artzner for language review. References anDjelov, M. 2009: Modeliranje napajanja vodo- nosnikov za oceno količinskega stanja podze- mnih voda v Sloveniji v letu 2006. 20. Mišičev vodarski dan – zbornik referatov, 126-130. aller, l., Bennet, t., lehr, j.h., Petty, r.j. & hacKett, G. 1987: DRASTIC: A Standardized System for Evaluating Ground Water Pollution Potential Using Hydrogeological Settings. U.S. Environmental Protection Agency, Washington: 622 p. BaKer, a.e., wooD, a.r & cichon, j.r. 2007: The Marion County Aquifer Vulnerability as- sessment. Marion County Project No. SS06- 01: 42 p. BonhaM-carter, G.F., aGterBerG, F.P. & wriGht, D.F. 1988: Integration of geological data- sets for gold exploration in Nova Scotia. Photogrammetry and Remote Sensing, 54: 1585-1592. 34 Jože UHAN BonhaM-carter, G.F., aGterBerG, F.P. & wriGht, D.F. 1989: Weights of evidence modelling: a new approach to mapping mineral potenci- al. In: aGterBerG, F.P. & BonhaM-carter, G.F. (eds.): Statistical application in the earth sci- ences. Geological Survey of Canada: 171-183. Buser, s. 1979: Osnovna geološka karta SFRJ = Basic geological map of SFRY 1:100.000. Tolmač lista Celje – Explanatory Book to the sheet Celje: L 33-67. Zvezni geološki zavod, Beograd: 72 p. civita, M. 1990: La valutazione della vulnerabilitŕ degli acquiferiall’inquinamento - Assessment of aquifer vulnerability to contamination. Proc 1st Conv. Naz. Protezione e Gestione delle Acqe Sotterranee: Metodologie, Technologie e Obiettivi, Marano sul Panaro, 3: 39-86. CLC 2000: Geografski informacijski sistem ARSO – Geographic information system ARSO. Internet: http://gis.arso.gov.si/geopor- tal (6. 11. 2010) cviTanič, i., dObniKar TehOvniK, m., Gacin, m., GrbOvić, J., JeSenOvec, b., KOzaK-leGiša, š., Krajnc, M., Kuhar, u., MihorKo, P., Poje, M., reMec-reKar, š., rotar, B., sever, M., SOdJa, e., andJelOv, m., miKulič, z., Pavlič, u., Savić, v., SOuvenT, P., Trišič, n. & uhan, j. 2010: Vode v Sloveniji: ocena stanja voda za obdobje 2006-2008 po določilih okvir- ne direktive o vodah – Waters in Slovenia: Status assessment for the period 2006-2008 according to the Water Framework Directive. Ministrstvo za okolje in prostor, Agencija RS za okolje, Ljubljana: 62 p. DeBernarDi, l., Deluca, D.a. & lasaGna, M. 2008: Correlation between nitrate concentration in groundwater and parameters affecting aqu- ifer intrinsic vulnerability. Environmental Geology, 55/3: 539–558, doi:10.1007/ s00254-007-1006-1. Diersch, h-j. 2009: FEFLOW 5.4 Finite ele- ment subsurface flow and transport simula- tion system. Users manual, WASY Software, Berlin: 202 p. GoGu, c. & DassarGues, a. 2000: Current trends and future challenges in groundwater vulne- rability assesment using overlay and index methods. Environmental Geology, 39/6: 549- 559, doi:10.1007/s002540050466. ISO 10304-1 2007: Water quality - Determination of dissolved anions by liquid chromatography of ions - Part 1: Determination of bromide, chloride, fluoride, nitrate, nitrite, phosphate and sulfate. ISO 10304-1:2007. KäSS, W., drObne, F. & buKvič, b. 1976: Markierung unterirdischer Wässer Untersuchungen in Slowenien 1972-1975. B. Markierung von Porengrund-wässer, 1. Untersuchungen im Quartär des Savinja Tals. Third International Symposium of Underground Water Tracing. Graz: 219-238. KeMP, l.D., BonhaM-carter, G.F., raines, G.l. & looney, c.G. 2001: Arc-SDM: Arcview extension for spatial data modelling using weights of evidence, logistic regression, fuzzy logic and neural network analysis. Internet: http://www.ige.unicamp.br/sdm/ (10. 2. 2008). KenDall, c. 1998: Tracing nitrogen sources and cycling in catchments. In: KenDall, c. & McDonnell, j.j. (eds.): Isotope tracers in ca- tchment hydrology. Elsevier: 519-576. KunKel, r. & wenDlanD, F. 2002: The GROWA98 model for water balance analysis in large ri- ver basins – the river Elbe case study. Journal of Hydrology, 259: 152-162. li, c.s., FrolKinG, s. & FrolKinG, a.t. 1992: A Model of Nitrous Oxide Evolution From Soil Driven by Rainfall Events: 1. Model Structure and Sensitivity. Journal of Geophysical Research, 97/D9: 9759-9776. Masetti, M., sterlacchini, s., BallaBio, c., sorichetta, a. & Poli, s. 2009: Influence of threshold value in the use of statistical methods for groundwater vulnerability as- sessment. Science of the Total Environment, 407: 3836-3846. oFFicial journal oF the euroPean coMMunities, 1980: Direktiva Sveta 80/778/EGS z dne 15. julija 1980 o kakovosti vode, namenjene za prehrano ljudi = Council Directive of 15 July 1980 relating to the quality of water intended for human consumption. Official Journal of the European Communities, L 229: 11–29. oFFicial journal oF the euroPean coMMunities, 1991a: Direktiva Sveta ES 91/271/EEC z dne 21. maj 1991 o čiščenju komunalne odpadne vode = Council Directive 91/271/EEC of 21 May 1991 concerning urban wastewater tre- atment. Official Journal of the European Communities, L 135: 40–52. oFFicial journal oF the euroPean coMMunities 1991b: Direktiva Sveta ES 91/676/EEC z dne 12. decembra 1991 o varstvu voda pred onesnaževanjem z nitrati iz kmetijskih vi- rov = Council Directive 91/676/EEC of 12 December 1991 concerning the protection of waters against pollution caused by nitrates from agricultural sources. Official Journal of the European Communities, L 375: 1–8. 35Groundwater vulnerability to nitrate pollution of alluvial aquifers in Slovenia – Lower Savinja Valley case study oFFicial journal oF the euroPean coMMunities 2000: Direktiva Evropskega parlamenta in Sveta ES 2000/60/EEC z dne 23. oktobra 2000 o določitvi okvira za ukrepe Skupnosti na področju vodne politike = Directive 2000/60/ EC of the European Parliament and of the Council of 23 October 2000 establishing a fra- mework for Community action in the field of water policy. Official Journal of the European Communities, L 327: 1–73. Panno, s.v., Kelly, w.r., MartinseK, a.t. & hacKley, K.c. 2006: Estimating background and threshold nitrate concentrations using probability graphs. Ground Water, 44/5: 697- 709, doi:10.1111/j.1745-6584.2006.00240.x Pezdič, J. 1999: Izotopi in geokemijski pro- cesi = Isotopes and gechemical processes. Naravoslovnotehniška fakulteta, Oddelek za geologijo, Ljubljana: 269 p. Pintar, M. 1996: Vpliv kemijske dejavnosti na koncentracijo nitratov in atrazina v vodah Apaškega polja = Impact of agricultural activities on the concentrations of nitrate and atrazine in the waters of Apaško polje. Magistrska naloga. Univerza v Ljubljani, Biotehniška fakulteta, Ljubljana: 106 p. PKS 2007: Pedološka karta Slovenije – Pedological map of Slovenia. Ministrstvo za kmetijstvo, gozdarstvo in prehrano. Internet: http://rkg. gov.si/GERK/ (10. 2. 2008). renGer, M. & wessoleK, G. 1996: Berechnung der Verdunstungsjahressummen einzelner Jahre. DVWK-Merkblätter zur Wasserwirtschaft, 238: 47 p. uhan, J., Pezdič, J., Savić, v., andJelOv, m. & Turšič, J. 2009: Hidrogeološki faktorji pro- storske in časovne porazdelitve nitrata v podzemni vodi Spodnje Savinjske doline. Geološki zbornik, 20: 177-182. uhan, j. 2011: Ranljivost podzemne vode na ni- tratno onesnaženje v aluvialnih vodonosni- kih Slovenije = Groundwater vulnerability to nitrate pollution of alluvial aquifers in Slovenia. Doktorska disertacija. Univerza v Ljubljani, Naravoslovnotehniška fakulteta, Oddelek za geologijo, Ljubljana: 163 p. uhan, J., brilly, m., PinTar, m., viŽinTin, G., TrčeK, b. & Pezdič, J. 2011a: The impact of anoxic conditions on regional groundwater nitrate distribution and vulnerability as- sessment. International conference: 19th to 21st September 2011, South Africa, Pretoria: 1 p. uhan, J., lOJen, S., PinTar, m. & Pezdič, J. 2011b: Groundwater nitrate sources in alluvial aqu- ifers: Isotope case study in Savinja Valley (Slovenia). In: DeMénz, a. & Fóriys, i. (eds.): Isotope Workshop XI, Budapest, Central European Geology, 54/1-2: 29-33, doi:http:// dx.doi.org/10.1556/CEuGeol.54.2011.1-2.4. viŽinTin, G. 2009: Nestacionarni 3D model toka podzemne vode na Spodnjesavinjskem po- lju – Nonstationary 3D groundwater flow model for Lower Savinja Valley. Univerza v Ljubljani, Naravoslovnotehniška fakulteta, Oddelek za geotehnologijo in rudarstvo: 43 p.