137Cs-Based Assessment of Soil Erosion Rates in a Morphologically Diverse Catchment with Varying Soil Types and Vegetation Cover: Relationship with Soil Properties and RUSLE Model Predictions

This study assessed soil erosion intensity and soil properties across the Crveni Potok catchment in Serbia, a region of diverse morphology, geology, pedology, and vegetation. Soil samples were collected using a regular grid approach to identify the underlying factors contributing to erosion and the most vulnerable areas. Based on 137Cs activities and the profile distribution (PD) model, severe erosion (>10 t ha−1 y−1) was predicted at nearly 60% of the studied locations. The highest mean erosion rates were detected for the lowest altitude range (300–450 m), Rendzic Leptosol soil, and grass-covered areas. A significant negative correlation was found between the erosion rates, soil organic matter, and indicators of soil structural stability (OC/clay ratio and St), indicating that the PD model successfully identifies vulnerable sites. The PD and RUSLE (revised universal soil loss equation) models provide relatively similar mean erosion rates (14.7 t ha⁻1 y⁻1 vs. 12.7 t ha⁻1 y⁻1) but significantly different median values (13.1 t ha−1 y−1 vs. 5.5 t ha−1 y−1). The model comparison revealed a positive trend. The observed inconsistencies were interpreted by the models’ spatiotemporal frameworks and RUSLE’s sensitivity to input data quality. Land use stands out as a significant factor modifying the variance of erosion rate, highlighting the importance of land management practices in mitigating erosion.

Authors

Institutions

Publication Details

Journal
Water
Published
2025-02-12
DOI
https://doi.org/10.3390/w17040526
Citations
7
Primary Topic
Soil erosion and sediment transport
Type
article
Field-Weighted Citation Impact
8.30

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

137Cs-Based Assessment of Soil Erosion Rates in a Morphologically Diverse Catchment with Varying Soil Types and Vegetation Cover: Relationship with Soil Properties and RUSLE Model Predictions

Ivana Smičiklas, Ranko Dragović, Aleksandar Čupić, Mihajlo Jović et al.
7 citations
Water
Soil erosion and sediment transport
8.30
article

137Cs-Based Assessment of Soil Erosion Rates in a Morphologically Diverse Catchment with Varying Soil Types and Vegetation Cover: Relationship with Soil Properties and RUSLE Model Predictions

Ivana Smičiklas, Ranko Dragović, Aleksandar Čupić, Mihajlo Jović, Milan Đorđević, Snežana Dragović, Mrđan Đokić, Milena Gocić, Boško Gajić, Dušan Topalović, Miloš Manić
article en
7 citations

Abstract

This study assessed soil erosion intensity and soil properties across the Crveni Potok catchment in Serbia, a region of diverse morphology, geology, pedology, and vegetation. Soil samples were collected using a regular grid approach to identify the underlying factors contributing to erosion and the most vulnerable areas. Based on 137Cs activities and the profile distribution (PD) model, severe erosion (>10 t ha−1 y−1) was predicted at nearly 60% of the studied locations. The highest mean erosion rates were detected for the lowest altitude range (300–450 m), Rendzic Leptosol soil, and grass-covered areas. A significant negative correlation was found between the erosion rates, soil organic matter, and indicators of soil structural stability (OC/clay ratio and St), indicating that the PD model successfully identifies vulnerable sites. The PD and RUSLE (revised universal soil loss equation) models provide relatively similar mean erosion rates (14.7 t ha⁻1 y⁻1 vs. 12.7 t ha⁻1 y⁻1) but significantly different median values (13.1 t ha−1 y−1 vs. 5.5 t ha−1 y−1). The model comparison revealed a positive trend. The observed inconsistencies were interpreted by the models’ spatiotemporal frameworks and RUSLE’s sensitivity to input data quality. Land use stands out as a significant factor modifying the variance of erosion rate, highlighting the importance of land management practices in mitigating erosion.

WaterVol. 17(4)
University of Nis (RS), University of Belgrade (RS)
Science Fund of the Republic of Serbia
Openalex Percentile: Top 3%
Soil erosion and sediment transport
8.30
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.