Acta geographica Slovenica, 61-2, 2021, 123–153
APPLICATION OF ANGOT PRECIPITATION
INDEX IN THE ASSESSMENT OF
RAINFALL EROSIVITY: VOJVODINA
REGION CASE STUDY (NORTH SERBIA)
Tin Lukić, Tanja Micić Ponjiger, Biljana Basarin, Dušan Sakulski, Milivoj Gavrilov,
Slobodan Marković, Matija Zorn, Blaž Komac, Miško Milanović, Dragoslav Pavić,
Minučer Mesaroš, Nemanja Marković, Uroš Durlević, Cezar Morar, Aleksandar Petrović
Rainfall erosivity in Vojvodina (North Serbia).

Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia)
DOI: https://doi.org/10.3986/AGS.8754
UDC: 911.2:556.12:504.121(497.113)
COBISS: 1.01
Tin Lukić
1
, Tanja Micić Ponjiger
1
, Biljana Basarin
1
, Dušan Sakulski
2
, Milivoj Gavrilov
1
, Slobodan
Marković
1
, Matija Zorn
3
, Blaž Komac
3
, Miško Milanović
4
, Dragoslav Pavić
1
, Minučer Mesaroš
1
,
Nemanja Marković
1
, Uroš Durlević
4
, Cezar Morar
5
, Aleksandar Petrović
6
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 (precipitation amounts, Angot precipitation index) were used as indicators of rainfall erosivity. Rainfall
erosivity index was calculated and classified throughout precipitation susceptibility classes liable of trig-
gering soil erosion. Precipitation trends were obtained and analysed by three different statistical approaches.
Results indicate that various susceptibility classes are identified within the observed period, with a higher
presence of very severe rainfall erosion in June and July. This study could have implications for mitigation
strategies oriented towards reduction of soil erosion by water.
KEY WORDS: climate change, precipitation, rainfall erosivity, soil erosion, Angot precipitation index,
Vojvodina, Serbia.
124
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/0000-0002-2546-
3728), 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)

1 Introduction
One of the most prominent causes of land degradation is water erosion (Boardman and Poesen 2006; 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 sev-
eral erosive agents, such as water, wind, ice, and snow (Morgan 2005; Blinkov 2015a; Blinkov 2015b). Panagos
et al. (2015a; 2015b) pointed out that in Europe, soil erosion by water accounts for the greatest soil loss com-
pared to other erosion processes (e.g., Boardman and Poesen 2006). Water erosion may be accelerated by
human activity, but human activity may also prevent runoffs and soil removal by building retention ponds
(Ferk et al. 2020) or terraces (Šmid Hribar et al. 2017).
W ater erosion has many on-site and off-site effects (Santos T elles, de Fátima Guimarães and Falci Dechen
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
(Lukić et al. 2019). Although soils represent a vital resource, research on soil erosion has not gained as
much attention as degradation of water and air quality (Blinkov 2015a). The reason can be found in much
more complex and extensive natural factors that led to this type of erosion, which are almost impossible to
explain with a model that would consist of every variable and factor included in the process. Nevertheless,
land degradation is recognized as a major environmental threat in many parts of Europe (e.g., de Luis,
González-Hidalgo and Longares 2010; de Luis et al. 2011; Blinkov 2015a; Blinkov 2015b; Lukić et al. 2013,
2016, 2018, 2019; Zorn and Komac 2013b). 
Soil erosion may be quantified using field measurement (Stroosnijder 2005) or erosion models (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
Yugoslavia and in some neighbouring countries the Gavrilović equation has predominated (Gavrilović 1972;
Hrvatin et al. 2019). Besides these, there are more than 600 other models that can be divided into two basic
groups: those extracted from the USLE and RUSLE equations, while others employ qualitative approach-
es (Auerswald et al. 2014).
Precipitation is the most important natural agent with regard to water soil erosion, hence representing
one of the determining factors in the USLE equation (Wischmeier and Smith 1978; Morgan 2005; Mello et
al. 2013). The capability of rainfall to cause soil loss is called rainfall erosivity (Nearing et al. 2017; Panagos
et al. 2017) and represents a climatological component in the overall erosion processes by water (da Silva
2004; Yu 1998). It is fundamental for the understanding of the climatic vulnerability regarding soil erosion
Acta geographica Slovenica, 61-2, 2021
125
Uporaba padavinski indeksa Angot za oceno erozivnosti padavin: na primeru
Vojvodine (severna Srbija)
POVZETEK: Prispevek podaja pregled najpomembnejših padavinskih parametrov (pojavnost, pogostost
in velikost) v Vojvodini (severna Srbija). Za 12 izbranih meteoroloških postaj so bile uporabljene mesečne
in letne povprečne vrednosti padavin v obdobju 1946–2014. Kot kazalnike erozivnosti padavin smo upora-
bili ustrezne padavinske parametre (količina padavin, padavinski indeks Angot). Izračunali smo indeks
erozivnosti padavin in ga razvrstili v razrede glede na možnost pojavljanja erozije prsti. Trende smo preučili
s tremi različnimi statističnimi pristopi. V preučevanem obdobju smo prepoznali različne razrede indek-
sa, z zelo močno padavin erozijo junija in julija. Raziskava je dober temelj za oblikovanje strategij, usmerjenih
v zmanjšanje vodne erozije prsti.
KLJUČNE BESEDE: podnebne spremembe, padavine, erozivnost padavin, erozija prsti, padavinski indeks
Angot, Vojvodina, Srbija
The article was submitted for publication on May 31
st
, 2020.
Uredništvo je prejelo prispevek 31. maja 2020.

Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia)
in a given region (Panagos et al. 2015a). Several measures of rainfall erosivity have been proposed (Yu and
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 AI
m
index (Lal 1976),
• Hudson’s KE>1Index (Hudson 1976), and
• Onchev’s Universal Erosivity Index (Onchev 1985).
Rainfall erosivity presents the potential of raindrops to trigger soil erosion and its estimation is funda-
mental 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
approaches have been developed when estimating soil erosion, namely indices based on precipitation data,
and indices based on kinetic energy and precipitation intensity (e.g., Lukić et al. 2016; 2019). The most
recognized indices describing kinetic energy and precipitation intensity are EI
30
(Weischmeier and Smith,
1978), AI
m
(Lal 1976), KE > 1 (Hudson 1976) and P/√t (Onchev 1985). These parameters require daily pre-
cipitation data series over 20 years, and since there is no such data for most parts of the world, it was necessary
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;
Loureiro and Coutinho 2001; Diodato and Bellocchi 2007). They were used in numerous studies with scarce
precipitation databases (e.g., Lujan and Gabriels 2005; Boardman and Poesen 2006; de Luis, González-Hidalgo
and Longares 2010; Ufoegbune et al. 2011; Costea 2012; Lukić et al. 2016, 2018, 2019). It was also in com-
parisons of several rainfall erosivity indices (e.g., Oduro-Afriyie 1996; da Silva 2004; Bayramin, Erpul and
Erdogan 2006; Angulo-Martínez and Beguería 2009; Alipour et al. 2012; Mello et al. 2013; Sanchez-Moreno,
Mannaerts and Jetten 2014). Fournier indices require mean monthly data averages and are based on tem-
poral precipitation distribution obtained through Precipitation Concentration Index (PCI) (Arnoldus 1980).
Beside articles that were based on MFI and FI parameters (e.g., Oduro-Afriyie 1996; Lujan and Gabriels 2005;
Apaydin et al. 2006; Costea 2012; Yue, Shi and Fang 2014; Hernando and Romana 2015), PCI was also
used in numerous studies concerning precipitation distribution and concentration (Martínez-Casasnovas,
Ramos and Ribes-Dasi 2002; de Luis et al. 2011; Iskander, Rajib and Rahman 2014; Lukić et al. 2019).
According to Dumitrascu et al. (2017), besides soil type, topography, and land use, the amount and
intensity of precipitation is an important factor in estimating the rate of soil erosion by water. The climatic
factors can lead to the intensification of erosion when they register high intensities and occurrence after
a prolonged drought period.
For this purpose, an indicator for the assessment of pluvial aggressiveness (Angot – K index) (Dragotă,
Micu and Micu 2008) can be applied in assessing rainfall erosivity in Southeastern Europe – a hotspot region
with the highest number of severely affected sectors (Dragotă, Micu and Micu 2008; Dragotă et al. 2014;
Dumitrascu et al. 2017; Lung and Hilden 2017; Lukić et al. 2019; Milanović et al. 2019). So far, rainfall
erosivity assessment in the Vojvodina Region has been carried out in the Bačka and Zemun loess plateaus
(Lukić et al. 2016, 2018) and in the Pannonian Basin (Lukić et al. 2019). The study found that the amount
and the intensity of precipitation are increasing. According to Marković et al. (2008, 2012, 2015), the largest
part of Vojvodina is covered with loess and loess-like sediments (> 60%), which are extremely suscepti-
ble to the erosion processes due to high porosity, carbonate and clay content as abounding material (Lukić
et al. 2009; Vasiljević 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; Lukić et al. 2016, 2019).
The publicly available precipitation database of the Vojvodina Region record more than 70 years of
continuous observations. However, the data is based on monthly values. Accordingly, the aforementioned
Angot – K index, which was used in similar studies (in the neighbouring countries), is one of the com-
patible methodological approaches for assessing the potential vulnerability of the investigated area from
the rainfall erosivity (e.g., Dragotă, Micu and Micu 2008; Dragotă 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
Kula settlement (southern part of the Bačka loess plateau) and Zemun area in the vicinity of Belgrade (Zemun
126

Acta geographica Slovenica, 61-2, 2021
127
loess plateau), where Lukić et al. (2016, 2018) studied the relationship between recurring landslides and rain-
fall erosivity. In a later study, Lukić et al. (2019) showed an increase in the amount and the intensity of
precipitation as well as in rainfall erosivity for most parts of the Pannonian Basin, including V ojvodina region.
In this paper climatological parameters from the V ojvodina Region (North Serbia) are processed. W e used
the Angot precipitation index (Dragotă, Micu and Micu 2008), which is the ratio of the daily average volume
of precipitation in a month and the annual daily average precipitation volume (Constantin and Vătămanu
2015) and was previously already used in the wider study region by Dragotă et al. (2014) and Dumitraşcu et
al. (2017). In order to assess the erosion vulnerability for the southern part of the Pannonian Basin, the occur-
rence, frequency and magnitude of some of the most significant precipitation parameters were studied.
2 Study area
The Autonomous Province of Vojvodina (21,533 km
2
) 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,
Bačka, and Srem with Novi Sad as the capital (Basarin et al. 2018; Gavrilov et al. 2020).
The largest part of the region is covered with loess and loess-like sediments (> 60%). As the loess mate-
rial possesses several properties which make it highly susceptible to water erosion, it is very important to
point out the most vulnerable areas for mitigation and prevention (Leger 1990; Lukić et al. 2009, 2016, 2019).
The Vojvodina Region is predominantly a lowland area, and the highest parts are Fruška gora Mountain
(539 m) in the northern part of the Srem Region, and the Vršačke Mountains (641 m) in the southeastern
part of the Banat Region. However, the largest geomorphological structures are formed on loess and loess-
like material, and present loess plateaus, terraces and microrelief forms (Marković et al. 2008, 2012, 2015;
Lukić et al. 2009; Vasiljević 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
to the weaker impact of western air currents, and the greater impact of a Eurasian continental climate. Winter
seasons are cold (average January temperatures range from < 0.0 °C to 1.0 °C), while summers are hot and
humid (average July temperature of between 21.0 °C and 23.0 °C), with a huge temperature range, reaching
~70 °C and very irregular distribution of monthly rainfall (extremely rainy early summer and low precipi-
tation in November and March) (Malinović-Milićević 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 precipi-
tation is 606 mm, 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
rainfall of about 540mm is recorded in the north, while the highest average precipitation values are recorded
in the southwest of Vojvodina (Hrnjak et al. 2014; Tošić 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
spatial distribution (Figure 1). Data for the analysed period covers two thirty-year cycles, which is in accor-
dance with the WMO standards.
Datasets for each of the stations were analysed and processed for the calculation of the mean monthly amount
of precipitation. Thus, a database was created with a time series of monthly and annual precipitation values.
The homogeneity of the precipitation series was confirmed by the Alexandersson (1986) test. Precipitation
trends were examined using three different statistical approaches. In the first approach, a simple linear regres-
sion was used to determine the existence of a certain tendency in the data series, which gives information on
the stagnation, growth or decline of the observed phenomenon (Cohen 1988; Gocić and Trajković 2013). Using
Figure 1: Map of Vojvodina (North Serbia) with meteorological stations used in this study.p p. 128

Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia)
128
S R E M
B A N A T
B A Č K A
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Bač
Zrenjanin
Banatski
Karlovac
Bela
Crkva
Vršac
Kikinda
Sombor
Senta
Palić
Bački
Petrovac
Sremska
Mitrovica
Rimski
Šancevi
21°0'0"E
21°0'0"E
20°0'0"E
20°0'0"E
19°0'0"E
19°0'0"E
46°0'0"N
46°0'0"N
45°0'0"N
45°0'0"N
0 20 40
km
Legend
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Meteorological station
Inland water
River net
A.P. V ojvodina
National border
T i t e l
l o e s s
p l a t e a u 
F r u š k a g o r a m t .
D e l i b l a t o s a n d s
V r š a c 
m t .
B ač k a
l o e s s
p l a t e a u  
HUN
HRV
BIH
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Scale: 1:900.000
Content and map by: Tanja Micić Ponjiger
Source: 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
Danube
Danube
Sava
Tisa
S u b o t i c a s a n d s

this method, the trend equation for yearly data was obtained for 69 years. The precipitation trend was also
investigated using the nonparametric Mann-Kendall test, which is widely applied in environmental sciences
for its simplicity and precision (Gilbert 1987; Gavrilov et al. 2011, 2013; Hrnjak et al. 2014; Lukić et al. 2017).
Third, Kendall’s tau (τ) (Kendall 1938, 1975) was calculated to gain a trend over a fully observed period
of 69 years. Then, two hypotheses were tested:
1) Null hypothesis (H
0
) – with the assertion that there is no trend in the observed time series for a defined
level of significance of 95% (α=0.05);
2) Alternative hypothesis (H
a
) – with the assertion that there is a trend in a given time series for a defined
level of significance of 95% (α=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-pos-
itive trend outcomes, the Yue-Pilon method was performed (Yue et al. 2002).
Rainfall erosivity can be assessed using several methods (Costea 2012), of which we choose Angot pre-
cipitation index (K) (Dragotă, Micu and Micu 2008; Dragotă et al. 2014; Dumitraşcu et al. 2017). According
to Dumitraşcu et al. (2017), destructive heavy rainfalls mostly depend on the intensity, duration and water
quantity of the precipitation, and particular surface features, such as lithology, vegetation cover, and slope.
In such conditions, heavy precipitation can trigger floods, erosion and slope failures (Lukić et al. 2016, 2018).
Hence, the main components of the precipitation regime that have the strongest impact on the environ-
ment in the V ojvodina Region have been analysed using a specific erodibility K index. According to Dumitraşcu
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. The Angot precipitation index (K) was initially aimed at determining the characteristic types of monthly
and annual variation of precipitation based on regional and local comparisons. The index was quantified
according to equations 1 and 2 (Dragotă, Micu and Micu 2008; Dumitraşcu et al. 2017):
(1)
where p = q/n, q being the monthly precipitation amounts, and n being the number of days/months, and
(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).
Acta geographica Slovenica, 61-2, 2021
129
Table 1: Geographical coordinates and altitudes of selected meteorological stations.
Region Meteorological stations Latitude (N) Longitude (E) Altitude (m)
Banat Banatski Karlovac 45°03’00’’ 21°02’12’’ 100
Bela Crkva 44°54’00’’ 21°25’12’’ 90
Vršac 45°09’00’’ 21°19’12’’ 83
Zrenjanin 45°22’00’’ 20°25’00’’ 80
Kikinda 45°51’00’’ 20°28’12’’ 81
Senta 45°55’48’’ 20°04’48’’ 80
Bačka Bač 44°54’00’’ 21°25’12’’ 90
Bački Petrovac 45°22’12’’ 19°34’12’’ 85
Palić 46°06’00’’ 19°46’12’’ 102
Rimski Šančevi 45°19’48’’ 19°51’00’’ 86
Sombor 45°46’12’’ 19°09’00’’ 87
Srem Sremska Mitrovica 45°01’00’’ 19°33’00’’ 82
K =
p
P
P =
Q
365

Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia)
130
In order to examine the relationship between precipitation data, K and potential climate drivers, lin-
ear correlations were utilized. The selected large-scale phenomenon, North Atlantic Oscillation (NAO) and
Multivariate ENSO Index (MEI) were used following the approach by Malinović-Milićević et al. (2018)
and Lukić et al. (2019). NAO is characterized as the difference between sea-level pressure observed over
Iceland and Portugal. When the values of NAO are negative storm tracks shift to the south, inducing more
winter precipitation in the regions south of the Pyrenean-Alpine Mountains, including the Pannonian Basin
(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
a rather complex parameter, which integrates complete information of six oceanic and meteorological vari-
ables indicating the influence of southern oscillation (Pompa-García and Némiga 2015). The ENSO (MEI)
record was obtained from the NOAA Physical Sciences Laboratory (Internet 2).
4 Results and discussion
The temporal evolution of the moving average (with a size window equal to 12 months) indicates that there
are no significant variations or deviations regarding the precipitation distribution in the study area (Figure 2).
This observation corresponds well with the results of Lukić et al. (2019) who pointed out that precipitation
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 precipita-
tion concentration for the V ojvodina Region generally display uniform values, where the winter season exhibits
higher values than other seasons for all investigated stations during the period 1961–2014.
As shown by Bjelajac et al. (2016), the average annual precipitation (calculated for a period of 69 years)
for 11 out of 12 stations indicate a positive linear trend, of which most pronounced trends are observed for
the Bačka Region – Rimski Šančevi meteorological station (y = 1.8309x + 550.89). The highest average pre-
cipitation amount is recorded for the Bela Crkva meteorological station (659.1 mm) in the southeast, while
the lowest values are recorded in the north and northeast (Palić station 555mm and Kikinda station 555.5mm)
(Figure 3). According to the Mann-Kendall test, based on calculated p values, Sombor (p = 0.020) and Palić
(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 Palić stations (for the study period) display an
increase in the amount of precipitation by 1.46 mm and 1.68 mm, respectively (Figure 3). Other meteoro-
logical stations do not show statistically significant trend of precipitation variability for the study period.
The used meteorological database covers the warm period of the year (when positive values of K index
prevail). The most favourable conditions for the occurrence of water erosion processes are distributed with-
in April and September (when the highest rainfall amounts are recorded for all investigated stations; Figure 4).
Table 3 summarizes monthly susceptibility of the Angot precipitation index classes (in%) for the selected
stations during the period 1946–2014.
Table 2: Susceptibility classes of precipitation liable to triggering soil erosion based on Angot precipitation index (K) (Dragotă, Micu and Micu 2008;
Dumitraşcu 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
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

Acta geographica Slovenica, 61-2, 2021
131
0
50
100
150
200
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
Y ear
Precipitation (mm)

Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia)
132
#
#
#
#
#
#
#
#
#
#
# *
#
Bač
Zrenjanin
Banatski
Karlovac
Bela
Crkva
Vršac
Kikinda
Sombor
Senta
Palić
Bački
Petrovac
Sremska
Mitrovica
Rimski
Šančevi
0 25 50
km
Legend
Precipitation distribution [mm]
555–565
565–575
575–585
585–595
595–605
605–615
615–625
625–635
635–645
645–659
# *
Positive trend
# *
Negative trend
Scale: 1:1.500.000
Content and map by: Tanja Micić Ponjiger
Source:  National border (GADM database
(www.gadm.org), version 3.4, April 2018.)
© 2020 DGTH, Faculty of Sciences, UNS
* p<0.05
* 
* 
¯

Acta geographica Slovenica, 61-2, 2021
133
II II I II VVV IV I IV I I II XXX IX I I
Month
II II I II VVV IV I IV I I II XXX IX I I
Month
Banatski Karlovac (Banat region) Bela Crkva (Banat region)
0
20
40
60
80
Precipitation(mm)
0
20
40
60
80
Precipitation(mm)
II II I II VVV IV I IV I I II XXX IX I I
Month
Bač (Bačka region)
II II I II VVV IV I IV I I II XXX IX I I
Month
Bački Petrovac (Bačka region)
0
20
40
60
80
Precipitation(mm)
0
20
40
60
80
Precipitation(mm)
II II I II VVV IV I IV I I II XXX IX I I
Month
II II I II VVV IV I IV I I II XXX IX I I
Month
Vršac (Banat region) Zrenjanin (Banat region)
0
20
40
60
80
Precipitation(mm)
0
20
40
60
80
Precipitation(mm)
II II I II VVV IV I IV I I II XXX IX I I
Month
II II I II VVV IV I IV I I II XXX IX I I
Month
10
20
30
40
50
60
70
Palić (Bačka region) RimskiŠančevi (Bačka region)
0
20
40
60
80
Precipitation(mm)
0
Precipitation(mm)
Sombor (Bačka region) Sremska Mitrovica (Srem region)
II II I II VVV IV I IV I I II XXX IX I I
Month
0
20
40
60
80
Precipitation(mm)
II II I II VVV IV I IV I I II XXX IX I I
Month
0
20
40
60
80
Precipitation(mm)
Kikinda (Banat region) Senta (Banat region)
II II I II VVV IV I IV I I II XXX IX I I
Month
10
20
30
40
50
60
70
0
Precipitation(mm)
II II I II VVV IV I IV I I II XXX IX I I
Month
10
20
30
40
50
60
70
0
Precipitation(mm)
The Autonomous Province of Vojvodina
II II I II VVV IV I IV I I II XXX IX I I
Month
0
20
40
60
80
Precipitation(mm)

Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia)
134
II II I II VVV IV I IV I I II XXX IX I I
Month
II II I II VVV IV I IV I I II XXX IX I I
Month
Banatski Karlovac (Banat region) Bela Crkva (Banat region)
0
20
40
60
80
Precipitation(mm)
0
20
40
60
80
Precipitation(mm)
II II I II VVV IV I IV I I II XXX IX I I
Month
Bač (Bačka region)
II II I II VVV IV I IV I I II XXX IX I I
Month
Bački Petrovac (Bačka region)
0
20
40
60
80
Precipitation(mm)
0
20
40
60
80
Precipitation(mm)
II II I II VVV IV I IV I I II XXX IX I I
Month
II II I II VVV IV I IV I I II XXX IX I I
Month
Vršac (Banat region) Zrenjanin (Banat region)
0
20
40
60
80
Precipitation(mm)
0
20
40
60
80
Precipitation(mm)
II II I II VVV IV I IV I I II XXX IX I I
Month
II II I II VVV IV I IV I I II XXX IX I I
Month
10
20
30
40
50
60
70
Palić (Bačka region) RimskiŠančevi (Bačka region)
0
20
40
60
80
Precipitation(mm)
0
Precipitation(mm)
Sombor (Bačka region) Sremska Mitrovica (Srem region)
II II I II VVV IV I IV I I II XXX IX I I
Month
0
20
40
60
80
Precipitation(mm)
II II I II VVV IV I IV I I II XXX IX I I
Month
0
20
40
60
80
Precipitation(mm)
Kikinda (Banat region) Senta (Banat region)
II II I II VVV IV I IV I I II XXX IX I I
Month
10
20
30
40
50
60
70
0
Precipitation(mm)
II II I II VVV IV I IV I I II XXX IX I I
Month
10
20
30
40
50
60
70
0
Precipitation(mm)
The Autonomous Province of Vojvodina
II II I II VVV IV I IV I I II XXX IX I I
Month
0
20
40
60
80
Precipitation(mm)

Acta geographica Slovenica, 61-2, 2021
135
Table 3: Monthly susceptibility of Angot precipitation index classes (1946–2014).
Susceptibility class / Angot index values Month (%)
April May June July August September
Banatski Karlovac (Banat Region)
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
Bela Crkva (Banat Region)
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
Vršac (Banat Region)
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
Zrenjanin (Banat Region)
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
Kikinda (Banat Region)
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
Senta (Banat Region)
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
Bač (Bačka Region)
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
Bački Petrovac (Bačka Region)
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

Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia)
According to the K index values for the Banat Region, Banatski Karlovac meteorological station records,
the presence of very severe rainfall erosivity occurred in 1975 and 2014. On the other hand, the presence
of moderate erosion classes is evenly distributed during the two thirty-year cycles in the study period. Bela
Crkva station follows a similar pattern. After 1975, an increase of very severe precipitation classes has been
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 Lukić 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 sta-
tion 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 sta-
tion Kikinda does not display extreme rainfall erosivity, during the investigated period. 2001 is highlighted
as a year where severe erosion occurred in April, June and September. Extreme precipitation sums (reg-
istered in 2014) for the weather station of Senta indicate the presence of very severe erosion during May,
July and September. Y ears with the distinguished presence of very severe erosion classes (33.3% of the stud-
ied precipitation interval) are 1974, 1978, 1999, 2001 and 2004. This implies that the area surrounding Senta
weather station is somewhat more prone to rainfall erosivity.
136
Susceptibility class / Angot index values Month (%)
April May June July August September
Palić (Bačka Region)
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
Rimski Šančevi (Bačka Region)
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
Sombor (Bačka Region)
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
Sremska Mitrovica (Srem Region)
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
The Autonomous Province of Vojvodina
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
Figure 5: Mean multiannual values of K Index during the warm part of the year for Banat weather stations.p p. 137–139

Acta geographica Slovenica, 61-2, 2021
137
Bela Crkva
Banatski Karlovac
IX
VIII
VI
V
VII
IV
IX
VIII
VI
V
VII
IV
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
very low low moderate
severe very severe

Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia)
138
Zrenjanin
Vršac
IX
VIII
VI
V
VII
IV
IX
VIII
VI
V
VII
IV
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
very low low moderate
severe very severe

Acta geographica Slovenica, 61-2, 2021
139
Kikinda
Senta
IX
VIII
VI
V
VII
IV
IX
VIII
VI
V
VII
IV
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
very low low moderate
severe very severe

Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia)
140
According to the K index values for the Bačka Region, the Bač weather station in the western part
of Vojvodina Region, registers several years with the two-month precipitation interval presence 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 Bački Petrovac station does not dis-
play 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
other hand, the Palić weather station in the north of the Vojvodina province generally displays an absence
of periods with intensive rainfall erosivity classes. These observations fit well with the finding of Lukić
et al. (2019), that Palić area records the lowest erosivity value in the Vojvodina Region during 1983 (MFI –
8.60). Results for the Rimski Šančevi weather station in the southern parts of Bačka Region indicate
that an increase of rainfall erosivity can be seen from 1995, with the presence of three-month precip-
itation intervals of very severe erosion in 2001. Lukić 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 for the 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 pre-
cipitation 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
Dumitraşcu et al. (2017) for the south-western part of Romania. Previously, Dragotă et al. (2014) point-
ed out that the Danube Floodplain displays moderate to excessive rainfall erosivity regime. Authors emphasize
that due to relief configuration, reduced declivity and soil types, moderate, low and very low susceptibil-
ity classes prevail in the study area. On the other hand, Dumitraşcu et al. (2017) showed that mountainous
and hilly areas display the highest susceptibility to rainfall erosivity, as it can be observed for south-east-
ern parts of the Vojvodina Region (Banat Region with Vršac weather station) (Figure 8). As the altitude
drops, severe and very severe class values are approximately equally distributed on a multiannual basis cor-
responding to the findings in a neighbouring country. As observed for the Romanian plain and the Danube
valley, very low and low classes dominate, especially in April, August and September, which is in accor-
dance with the obtained mean K values for the Vojvodina Region (Figure 8). On the other hand, Lukić 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 ero-
sive class and increase the vulnerability to this type of erosion in the Pannonian Basin and Vojvodina Region.
Also, the relief properties and the interaction with the general atmospheric circulation in the study area
greatly contribute to the spatial pattern of rainfall erodibility potential in terms of intensity, frequency and
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 ero-
sivity is of utmost importance in the context of sustainable agricultural practices and specific local or regional
climate conditions (Komac and Zorn 2005; Maracchi, Sirotenko and Bindi 2005). Accordingly, a good under-
standing of climate variability and main precipitation features is of great importance, especially when dealing
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 Bačka 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

Acta geographica Slovenica, 61-2, 2021
141
Bač
Bački Petrovac
IX
VIII
VI
V
VII
IV
IX
VIII
VI
V
VII
IV
1946 1946
1947 1947
1948 1948
1949 1949
1950 1950
1951 1951
1952 1952
1953 1953
1954 1954
1955 1955
1956 1956
1957 1957
1958 1958
1959 1959
1960 1960
1961 1961
1962 1962
1963 1963
1964 1964
1965 1965
1966 1966
1967 1967
1968 1968
1969 1969
1970 1970
1971 1971
1972 1972
1973 1973
1974 1974
1975 1975
1976 1976
1977 1977
1978 1978
1979 1979
1980 1980
1981 1981
1982 1982
1983 1983
1984 1984
1985 1985
1986 1986
1987 1987
1988 1988
1989 1989
1990 1990
1991 1991
1992 1992
1993 1993
1994 1994
1995 1995
1996 1996
1997 1997
1998 1998
1999 1999
2000 2000
2001 2001
2002 2002
2003 2003
2004 2004
2005 2005
2006 2006
2007 2007
2008 2008
2009 2009
2010 2010
2011 2011
2012 2012
2013 2013
2014 2014
very low low moderate
severe very severe

Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia)
142
Palić
Rimski Šančevi
IX
VIII
VI
V
VII
IV
IX
VIII
VI
V
VII
IV
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
very low low moderate
severe very severe

Acta geographica Slovenica, 61-2, 2021
143
Sombor
IX
VIII
VI
V
VII
IV
1946
1947
1948
1949
1950
1951
1952
1953
1954
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146
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
by Panagos et al. (2015a), rainfall erosivity in Europe is a key parameter for estimating soil erosion loss and
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
mean rainfall erosivity factor for the Pannonian zone (central Danubian basin) is 660.1 МЈ mm ha
−1
h
−1
yr
−1
and corresponds well with the findings of Mezősi and Bata (2016) and Lukić 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 para-
meters 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.
A correlation between the NAO index and precipitation (–0.19), as well as the K index (–0.20), is presented
in Figure 9. The negative correlation coefficient indicates the wetting effect on the K index. Based on con-
temporary findings it can be pointed out that NAO considerably affects rainfall in this part of Europe (e.g.,
Tošić et al. 2014; Luković et al. 2015; Radaković et al. 2018), and since the K index is based on precipita-
tion amounts, NAO has a certain influence on it as well. As pointed out by Bice et al. (2012), NAO generally
has a strong influence on winter precipitation in the Pannonian Basin, with negative NAO phases corre-
sponding to periods of high precipitation. Results of Malinović-Milićević et al. (2018) indicate that the
amount and intensity of precipitation in Serbia had a statistically significant increase during autumn, and
were most pronounced in the northern (Vojvodina) and western parts of the country. The authors showed
that »dry« regimes dominate over »wet«, with an increasing trend of »warm« regimes and decreasing trend
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
winter warm periods, while their influence on the duration of cold periods cannot be confirmed with cer-
tainty. The East Atlantic/West Russia (EA WR) pattern affects statistically significant positive autumn trends
of all intensity and frequency indices. In winter, it has an impact on the frequency of »dry« and »wet« con-
ditions and the intensity of the precipitation. On the other hand, the correlation between MEI and precipitation
(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
absence of strong linearity between the K, and these two large-scale processes of climate variability. As shown
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 (even up to 100%). On the other hand, seasonal precipitation may increase more than 100% in different
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
the Vojvodina Region has experienced the presence of various susceptibility classes of precipitation liable
for triggering soil erosion from April until September. June and July are the months with higher frequency
of very severe erodibility classes, with the distribution of 8.70% and 5.80%, respectively. Most of the dis-
tributed erodibility classes observed for the study area belong to moderate, varying from 7.25% (in April)
up to 27.54% (in June). On the other hand, a progressive increase in the values of the rainfall erosiv-
ity at the annual level (induced by climate variability), in the future can lead to the transition to a 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

Acta geographica Slovenica, 61-2, 2021
147
–2 –1 1 2 3
–4
–2
2
a)
–2 –1 1 2 3
–4
–2
2
b)
-2 -1 1 2 3
-4
-2
2
c)
NAO (x)–Precipitation (y) correlation
NAO (x)–Angdot index (y) correlation
MEI (x)–Precipitation (y) correlation

Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia)
As precipitation is seen as one of the main triggering factors for flash floods, landslides, and soil ero-
sion, 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
on changes in seasonal precipitation. For Serbia, these changes should be investigated in detail using a wet
season concept between October and March, as previously discussed by Luković et al. (2015). This approach
may be suitable since it could investigate the probability of an increase or decrease in precipitation amounts
associated with the above-mentioned indices and seasonal rainfall erosivity rates as well.
ACKNOWLEDGEMENTS: The authors acknowledge the financial support of the Ministry of Education,
Science and Technological Development of the Republic of Serbia (Grant No. 451-03-68/2020-14/ 200125).
A part of the research was supported by the H2020 WIDESPREAD-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). We confirm that all the authors made an equal contribution to the study
and its development. Authors are grateful to the anonymous reviewer’s whose comments and suggestions
greatly improved the manuscript.
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