Abstract

Soil erosion significantly impacts dam functionality by leading to reservoir siltation, reducing capacity, and heightening flood risks. This study aims to map soil erosion within a Geographic Information Systems (GIS) framework to estimate the siltation of the K'sob dam and compare these estimates with bathymetric observations. Focused on one of the Hodna basin’s sub-basins, the K'sob watershed (1477 km2), the assessment utilizes the Revised Universal Soil Loss Equation (RUSLE) integrated with GIS and remote sensing data to predict the spatial distribution of soil erosion. Remote sensing data were pivotal in updating land cover parameters critical for RUSLE, enhancing the precision of our erosion predictions. Our results indicate an average annual soil erosion rate of 7.83 t/ha, with variations ranging from 0 to 224 t/ha/year. With a typical relative error of about 13% in predictions, these figures confirm the robustness of our methodology. These insights are crucial for crafting mitigation strategies in areas facing high to extreme soil loss and will assist governmental agencies in prioritizing actions and formulating effective soil erosion management policies. Future studies should explore the integration of real-time data and advanced modeling techniques to further refine these predictions and expand their applicability in similar environmental assessments.

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