Advanced GIS-Based RUSLE Modeling for Soil Erosion Estimation in the Toplica River Basin, Serbia

Among the most serious types of land degradation, soil erosion poses a major threat to agricultural productivity, water quality, and ecosystem stability. Using a multidisciplinary approach, this study aimed to identify the spatial patterns of soil erosion and dominant drivers influencing soil loss in the Toplica River Basin in southern Serbia. Soil properties, including texture and organic matter content, were analyzed in samples collected throughout the study area, accounting for variations in altitude, soil type, and land use, to determine the erodibility factor (K). The rainfall erosivity factor (R), topographic factor (LS), and cover management factor (C) were determined using available inputs on rainfall erosivity, topography, land use, and vegetation cover. The Revised Universal Soil Loss Equation (RUSLE) was used to estimate annual soil erosion rates, and GIS tools and cartographic techniques were used to create spatial layers for each RUSLE factor and to generate a detailed erosion risk map. The results showed a mean annual soil loss of 5.45 t ha−1 year−1, with values ranging from 0 to 397.09 t ha−1 year−1, indicating considerable spatial variability. The regression modeling revealed the dominant roles of factors LS (β = 0.828), C (β = 0.731), and their interaction (LS × C, β = 0.561), followed by rainfall-related interactions (R × C, β = 0.268 and R × LS, β = 0.261). Two dominant erosion regimes were distinguished: topography-controlled erosion in mountainous regions and land-use-controlled erosion in low- to moderately sloping agricultural areas. The maps and analyses presented in this study provide a process-based framework for interpreting spatial erosion patterns, identifying critical hotspots and areas with higher erosion risk, and supporting more focused and context-aware conservation strategies.

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Publication Details

Journal
Geosciences
Published
2026-02-14
DOI
https://doi.org/10.3390/geosciences16020083
Primary Topic
Soil erosion and sediment transport
Type
article
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article

Advanced GIS-Based RUSLE Modeling for Soil Erosion Estimation in the Toplica River Basin, Serbia

Ivana Smičiklas, Ranko Dragović, Snežana Dragović, Miloš Manić et al.
Geosciences
Soil erosion and sediment transport
article

Advanced GIS-Based RUSLE Modeling for Soil Erosion Estimation in the Toplica River Basin, Serbia

Ivana Smičiklas, Ranko Dragović, Snežana Dragović, Miloš Manić, Mrđan M. Đokić, Antonije Onjia, Jelena Vesković, Milan Đorđević
article en

Abstract

Among the most serious types of land degradation, soil erosion poses a major threat to agricultural productivity, water quality, and ecosystem stability. Using a multidisciplinary approach, this study aimed to identify the spatial patterns of soil erosion and dominant drivers influencing soil loss in the Toplica River Basin in southern Serbia. Soil properties, including texture and organic matter content, were analyzed in samples collected throughout the study area, accounting for variations in altitude, soil type, and land use, to determine the erodibility factor (K). The rainfall erosivity factor (R), topographic factor (LS), and cover management factor (C) were determined using available inputs on rainfall erosivity, topography, land use, and vegetation cover. The Revised Universal Soil Loss Equation (RUSLE) was used to estimate annual soil erosion rates, and GIS tools and cartographic techniques were used to create spatial layers for each RUSLE factor and to generate a detailed erosion risk map. The results showed a mean annual soil loss of 5.45 t ha−1 year−1, with values ranging from 0 to 397.09 t ha−1 year−1, indicating considerable spatial variability. The regression modeling revealed the dominant roles of factors LS (β = 0.828), C (β = 0.731), and their interaction (LS × C, β = 0.561), followed by rainfall-related interactions (R × C, β = 0.268 and R × LS, β = 0.261). Two dominant erosion regimes were distinguished: topography-controlled erosion in mountainous regions and land-use-controlled erosion in low- to moderately sloping agricultural areas. The maps and analyses presented in this study provide a process-based framework for interpreting spatial erosion patterns, identifying critical hotspots and areas with higher erosion risk, and supporting more focused and context-aware conservation strategies.

GeosciencesVol. 16(2)
University of Nis (RS), University of Belgrade (RS)
Life in Land
Openalex Percentile: Top 55%
Soil erosion and sediment transport
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