Arpana Handique Praduyt Dey Santanu Kumar Patnaik


Soil erosion is a serious issue, causing loss of agricultural productivity, increase in sediment deposit in the riverbeds, and damage to the ecological balance of the affected areas. Proper assessment of the soil erosion rate is essential for managing natural resources. The present study employs a GIS-based RUSLE (Revised Universal Soil Loss Equation) model to estimate annual soil loss in Majuli River Island of Assam, India. Annual average rainfall, soil properties, topographic characteristics, and LULC were taken as inputs to identify the soil erosion susceptible areas. The result revealed that annual soil loss of the study area ranges between 0 to 711 t ha−1 yr−1, with a mean annual soil loss of 23.02 t ha−1 yr−1. The entire region was classified into six soil loss severity classes, around 90 % of the area was found to be very slightly affected (< 5 t ha−1 yr−1) by soil erosion, around 5 % slightly affected (5 – 10 t ha−1 yr−1), roughly 3% moderately affected (10 – 20 t ha−1 yr−1), around 1% moderate high (20 – 40 t ha−1 yr−1), nearly 0.3 % area affected severely (40 -80 t ha−1 yr−1) and very severely affected areas (> 80 t ha−1 yr−1) contributes 0.1 %. A total of six priority levels of conservation were demarcated village-wise; priority level I requires immediate attention, and so on. The research outcome can help effectively implement conservation and management practices to check soil erosion in the study area.





Geographical Information System (GIS), , Majuli Island, Remote Sensing, Revised Universal Soil Loss Equation (RUSLE) , Soil Erosion

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Research Articles

How to Cite

Application of Revised Universal Soil Loss Equation (RUSLE) model for the estimation of soil erosion and prioritization of erosion-prone areas in Majuli Island, Assam, India. (2023). Journal of Applied and Natural Science, 15(4), 1667-1678. https://doi.org/10.31018/jans.v15i4.5176