Integrating RUSLE Model with Geographic Information System for Prediction of Soil Erosion in Baitarani River Basin of Odisha, India
DOI:
https://doi.org/10.52151/jae2025622.1925Keywords:
digital elevation model, rainfall erosivity, satellite imagery, slope length and steepness, soil erodibilityAbstract
The deteriorating soil conditions in the Odisha state of India pose a serious environmental challenge, particularly in the drought-prone central region of the state. This study was conducted to predict the soil erosion in Baitarani River basin of Odisha by using the revised universal soil loss equation (RUSLE) model on geographic information system (GIS) platform along with a digital elevation model, satellite imagery, and different soil datasets. The key factors affecting soil erosion such as rainfall erosivity, soil erodibility, slope length and steepness, management practice, and crop cover were analyzed to estimate soil erosion rate. Results indicated that RUSLE-GIS integration effectively identified erosion hotspots, within the river basin. The study revealed that 94.4% of the area experiences low to moderate soil erosion (2-10 t ha-1 yr-1), while 5.6% area faces high to severe erosion (10-30 t ha-1 yr-1), particularly in Keonjhar and Mayurbhanj districts. The findings emphasize the critical need for soil conservation measures in the high erosion-risk zone especially under the scenario of intense rainfall and changing land-use pattern. This study emphasizes that the integration of RUSLE model with GIS is a crucial tool for developing effective soil conservation strategies to mitigate land degradation in the area.
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