GEOSPATIAL ASSESSMENT OF RUSLE MODELING FOR SOIL EROSION RISK IN NUWARA ELIYA, SRI LANKA

Abstract

In the tropical highlands of Sri Lanka, especially in the Nuwara Eliya District, steep slopes, intensive agriculture, and heavy rainfall contribute to the accelerated degradation of the land, and soil erosion is one of the major environmental issues prevalent in this area. Although the occurrence of soil erosion in Sri Lanka has been investigated in earlier studies, the present study is an attempt to carry out a detailed soil erosion assessment on the Nuwara Eliya Highlands using GIS techniques, and the Revised Universal Soil Loss Equation (RUSLE) has received less attention in the local context for mapping and spatial prioritization of soil erosion conservation practices. The objectives of this study are to evaluate the potential soil erosion on Nuwara Eliya Highlands and to map the soil erosion risk by using the RUSLE model in combination with GIS techniques. The CHIRPS rainfall dataset, SoilGrids and ESDAC datasets, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) data, Landsat 9 imagery, and land use data were used to derive Rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management (C), and conservation practice (P) factors in Google Earth Engine and ArcGIS 10.8. These RUSLE factors were combined to calculate soil loss in a year and provide an erosion risk map at a spatial level. The model output shows that 546 km² (32%) of the district experienced moderate erosion, 460.62 km2 (30%) experienced high erosion, and 307.08 km2 (20%) experienced severe erosion, which indicates that a significant area of the district is highly prone to soil erosion. The spatial distribution of erosion risk was further analysed by comparing it with topographic conditions, land cover characteristics, and documented erosion-prone locations, where erosion hotspots were identified, thereby offering qualitative validation of the hotspots. The study provides a localised soil erosion assessment using GIS data, which can support evidence-based land management and conservation planning in the Nuwara Eliya Highlands.