Soil erosion vulnerability analysis of Damodar River Basin, India using Revised Universal Soil Loss Equation (RUSLE) in Google Earth Engine (GEE)
Joy Ghosh, Sukanta Das, Swagata Ghosh, Kousik Midya, Sudipta Das, Varun Narayan Mishra
Abstract
Soil erosion is an important environmental issue worldwide. Therefore, data on spatio-temporal patterns of soil erosion and successive soil loss would be of immense significance for the sustainable management of land and water resources. Despite being coal mining-intensive area, Damodar River Basin of India, suffers with the lack of adequate measurements of soil erosion over the entire basin, which hampers the holistic planning and conservation initiative. Therefore, present study employs the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information System (GIS), massive databases and processing capabilities of Google Earth Engine (GEE) and attempts to estimate the soil loss in the entire basin. To estimate soil loss for the years 2017 and 2024 for the study area, RUSLE considers several factors, including the steepness factor (S), crop/cover management component (C), rainfall erosivity factor (R), soil erodibility factor (K), slope length (L), and conservation support practice factor (P). The mean soil loss in the Damodar River Basin is decreased from 12.86 t ha⁻ 1 yr⁻ 1 in 2017 to 12.06 t ha⁻ 1 yr⁻ 1 in 2024. The present study identifies areas affected by prominent soil loss (> 20 t ha⁻ 1 yr⁻ 1 ) covering 36.47% of the total area in 2017 mostly concentrated on northwestern and central region of the entire basin with extensive mining activities, which slightly declined to 35.07% in 2024. Among all the factors, R factor is the primary reason for such decline which is attributed to the decrease in rainfall in the study area. The findings underscore the urgent need for focused soil conservation measures in the Damodar River Basin, considering its ecological relevance and socioeconomic worth. Due to the limitations in obtaining comprehensive field observations, across such an immense river basin, might affect the accuracy of predictions using the RUSLE model. However, present study estimates soil loss and identify vulnerable zone over two time periods within the expansive and mining-scarred river basin to enhance the reliability of estimations and thus it may contribute to the development of viable strategies for the long-term management of the Damodar River Basin's natural resources.