Soil erosion risk assessment and spatial mapping using LANDSAT-7 ETM+, RUSLE, and GIS—a case study

This paper discusses the application of the Revised Universal Soil Loss Equation (RUSLE) in conjunction with LANDSAT-7 ETM+ remote sensing data, and geographical information system (GIS) to the spatial mapping of soil erosion risk in Jhagrabaria Watershed Allahabad, U.P., India. Soil map and topographical data were used to develop the soil erodibility factor (K), and a digital elevation model (DEM) image was used to generate the topographic factor (LS). The cover-management factor (C) was developed based on vegetation, shade, and soil fraction images derived from spectral mixture analysis of a LANDSAT Enhanced Thematic Mapper Plus (LANDSAT-7 ETM+) image, and support practice factor (P) was developed by crossing operation between land use/land cover classification map and slope map. Assuming the same climatic conditions in the study area, the rainfall-runoff erosivity (R) factor was not used. The value of K for the study area lies between 0.25 and 0.485, LS values were less than 1.4, and C and P values were less than 1. A soil erosion risk map with five classes (very low, low, medium, medium high, and high) was produced based on the simplified RUSLE within the GIS environment and was linked to land use/land cover (LULC) image to explore the relationships between soil erosion risk (SER) and LULC distribution. The results indicated that the land use/land cover (LULC) having the most succession and mature vegetation are in low-erosion-risk areas, while the barren and fallow lands are usually associated with high- to medium-erosion-risk areas. The spatial maps of the SER has been generated that can be utilized in the policy matter and planning for the watershed studied. This research also implied that the remote sensing and GIS tools and techniques provide the highly promising and important tools for evaluating and mapping soil erosion risk in the Jhagrabaria Watershed.