Estimation of Soil Loss Using Remote Sensing and Geographic Information System Techniques (case Study of Kaliaghai River Basin, Purba & Paschim Medinipur District, West Bengal, India)

Remote Sensing (RS) and Geographic Information Systems (GIS) are useful tools in hydrological analysis and natural resource management. The application of RS and GIS techniques lends to estimate soil loss based on different parameters. RUSLE (Revised Universal Soil Loss Equation) model is used for soil loss estimation. Different parameters, namely the rainfall and runoff factor (R), soil erodibility factor (K), slope length and steepness factor (LS), crop management factor (C) and conservation practice factor (P), that are the mandatory inputs to RUSLE, have been either derived from remote sensing data or through conventional data collection systems. These parameters are obtained from monthly and annual rainfall data, soil map of the region, Digital Elevation Model (DEM), RS techniques (with use of Normalized Difference Vegetation Index) and land use/land cover map, respectively. This experiential study is carried out on the Kaliaghai river basin under Purbo and Paschim Medinipur district of West Bengal. Soil loss is very high in the river basin area, calculated as 1927779 tons/year using RUSLE model. Thus, the RUSLE model integrated with RS and GIS technologies has great potential for producing accurate and inexpensive erosion and sediment yield assessment map in the Kaliaghai river basin.