Soil Erosion Risk Assessment and Spatial Mapping in Jhagrabaria Watershed, Allahabad, U.P. (India) by Using LANDSAT 7ETM+ Remote Sensing Data, Revised Universal Soil Loss Equation (RUSLE) and Geographical Information System (GIS)

Abstract

This article discusses the application of the Revised Universal Soil Loss Equation (RUSLE) in conjunction with LANDSAT 7ETM+ 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 7ETM+) image. Support practice factors (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 study area lies between 0.25 and 0.485, LS values were less than 1.4, 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 relationships between soil erosion risk and LULC distribution. The results indicate that most succession and mature vegetation are in low erosion risk areas, while Barren and Fallow lands are usually associated with medium to high erosion risk areas. This research implies that remote sensing and GIS provide promising tools for evaluating and mapping soil erosion risk in the Jhagrabaria watershed of India.