Soil Erosion and Sediment Yield Assessment of Nilwande Dam Watershed using RUSLE, GIS, and Remote Sensing Techniques

Abstract

Soil erosion and sediments movement have become a serious problem which affects agriculture production, watershed sustainability, and water holding capacity of reservoirs. This study examines to assess soil erosion and sediments yield in Nilwande Dam watershed, Ahilyanagar district of Maharashtra State, India based on Revised Universal Soil Loss Equation (RUSLE) with Remote Sensing (RS) and Geographic Information Systems (GIS). RUSLE is composed of Rainfall Erosivity Factor (R), Soil Erodibility Factor (K), Slope Length and Steepness Factor (LS), Cover Management Factor (C), and Conservation Practice Factor (P) obtained from rainfall, soil, Digital Elevation Model (DEM), and Sentinel-2 land use/land cover data. Soil erosion per year was quantified through a raster-based analysis within ArcGIS software environment, whereas the sediment yield was calculated through the use of the Sediment Delivery Ratio (SDR). Soil erosion varied between almost 0 to 28,720.4 t ha?¹ yr?¹, whereas sediment yield showed differences between 0 to 8,369 t ha?¹ yr?¹. The hilly areas located to the northwest and southwest parts of the study area were found to suffer most erosion and sediment yield as a result of steep slopes, high rainfall erosivity, and sparse vegetation cover. The validation of the developed model based on the receiver operating characteristic (ROC) curve and area under the curve (AUC) showed satisfactory predictive power.

Introduction

This study estimates sediment yield in the Nilwande Dam watershed (Upper Pravara River Basin, Ahilyanagar, Maharashtra) by integrating the Revised Universal Soil Loss Equation (RUSLE) with Remote Sensing (RS) and Geographic Information System (GIS) techniques. Sediment yield is a key indicator of watershed health because excessive sedimentation reduces reservoir storage, affects irrigation and hydropower generation, and degrades water resources. Traditional field-based methods for estimating soil erosion are time-consuming and costly, whereas GIS and satellite-based approaches enable efficient, large-scale spatial analysis.

The methodology uses RUSLE to estimate annual soil loss based on five factors: rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management (C), and conservation practice (P). Spatial datasets including SRTM DEM, Sentinel-2 imagery, FAO soil maps, and PERSIANN rainfall data were processed in ArcGIS to generate thematic layers for each factor. The estimated soil loss was then multiplied by the Sediment Delivery Ratio (SDR) to determine the actual sediment yield reaching the watershed outlet. This integrated approach identifies erosion-prone areas and supports watershed management and soil conservation planning.

The study area covers the catchments of the Nilwande and Bhandardara dams, which are affected by deforestation, land-use change, agriculture, and intense monsoon rainfall associated with the Western Ghats. Results indicate that rainfall erosivity, soil erodibility, and topographic factors vary considerably across the watershed, with the western and northwestern hilly regions exhibiting the highest erosion potential due to steep slopes, high rainfall, and more erodible soils. The generated erosion and sediment yield maps provide valuable information for prioritizing conservation measures, reducing reservoir sedimentation, and promoting sustainable watershed management.

Conclusion

This study shows the efficiency of using RUSLE, Remote Sensing, and GIS approaches in assessing soil erosion and sediment production of the Nilwande Dam Watershed, Maharashtra. Results from spatial analysis have shown that there was significant variation in the erosion susceptibility of the watershed due to factors such as rainfall erosivity, topography, land use/land cover, and soils. The soil loss estimate map shows the large part of the watershed is subject to erosion risks ranging from low to moderate, some localised areas in the north-western and south-western hilly portions of the watershed appear highly prone to serious soil erosion problems. The sediment production evaluation results show important sediment producing regions in relation to sediment delivery downstream and possible sedimentation in the reservoir. The high level of spatial association between soil erosion and sediment production suggests that topography, vegetation, and watershed management are essential factors in determining sediment dynamics. This investigation proves the effectiveness and practicality of using the RUSLE-GIS model in the identification of erodible zones and prioritization of conservation strategies at the watershed level. The resulting maps of soil erosion and sediment production can be effectively used by planners and watershed managers to select suitable measures of soil and water conservation. Implementation of these measures, which include planting of trees, contour cultivation, vegetative cover, and construction of check dams in erodible zones, would help control sediment production and improve watershed conditions.

References

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Copyright

Copyright © 2026 Gauri R. Khedekar, Dr. Ganesh K. Patil. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.