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<p>Soil erosion (SE) has emerged as a critical environmental issue in recent times, severely affecting soil fertility, crop productivity, soil quality, infiltration rates, water retention capacity, and groundwater dynamics. This study employed the revised universal soil loss equation (RUSLE) in conjunction with Geographic Information System (GIS) capabilities to assess the magnitude and spatial variation of soil loss (SL) and sediment yield (SY) in the lower Betwa River basin. Six sub-basins, identified as 2BL01 through 2BL06, were delineated within the study area. Raster layers of data set relevant to the RUSLE model included average annual rainfall, soil map, digital elevation model (DEM), and land-use land cover (LULC) map of the study area, from which input RUSLE parameters viz. rainfall erosivity (R factor), soil erodibility (K factor), slope length and steepness (LS factor), and crop management and support practices (P and C factors) were determined and superimposed in a GIS framework to estimate SL. The average annual SL in the Betwa basin was estimated at 5.45 t/ha/year. Notably, sub-basins 2BL01, 2BL02, and 2BL03, severely affected by gullies and ravines, exhibited significantly higher soil loss rates of 12.42, 26.36, and 8.54 t/ha/year, respectively. These sub-basins were classified as high to very high priority areas. A novel sediment delivery ratio (SDR) equation was calibrated and integrated with the RUSLE model to calculate SY. The average SY was estimated at 2.45 t/ha/year (3.06&#xa0;m-t/year). The results were validated with a sediment rating curve developed for the Betwa basin, and were found to be in close agreement with the observed data. An empirical relationship between SY and basin area for north Indian rivers was also developed using the data of previous investigators, leveraging existing research. The study findings help decision-makers in identifying areas vulnerable to erosion and implementing the most effective strategies for SE management in high-priority regions. Additionally, the results offer significant understanding for evaluating erosion risks and developing targeted mitigation strategies in critical areas.</p>

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GIS-based sediment yield estimation in lower Betwa river basin, India using integrated RUSLE-SDR approach

  • 期刊论文

  • 发表日期：

    2025年5月14日

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  • Fatimah,
  • Kakoli Gogoi,
  • Saif Said

摘要

Soil erosion (SE) has emerged as a critical environmental issue in recent times, severely affecting soil fertility, crop productivity, soil quality, infiltration rates, water retention capacity, and groundwater dynamics. This study employed the revised universal soil loss equation (RUSLE) in conjunction with Geographic Information System (GIS) capabilities to assess the magnitude and spatial variation of soil loss (SL) and sediment yield (SY) in the lower Betwa River basin. Six sub-basins, identified as 2BL01 through 2BL06, were delineated within the study area. Raster layers of data set relevant to the RUSLE model included average annual rainfall, soil map, digital elevation model (DEM), and land-use land cover (LULC) map of the study area, from which input RUSLE parameters viz. rainfall erosivity (R factor), soil erodibility (K factor), slope length and steepness (LS factor), and crop management and support practices (P and C factors) were determined and superimposed in a GIS framework to estimate SL. The average annual SL in the Betwa basin was estimated at 5.45 t/ha/year. Notably, sub-basins 2BL01, 2BL02, and 2BL03, severely affected by gullies and ravines, exhibited significantly higher soil loss rates of 12.42, 26.36, and 8.54 t/ha/year, respectively. These sub-basins were classified as high to very high priority areas. A novel sediment delivery ratio (SDR) equation was calibrated and integrated with the RUSLE model to calculate SY. The average SY was estimated at 2.45 t/ha/year (3.06 m-t/year). The results were validated with a sediment rating curve developed for the Betwa basin, and were found to be in close agreement with the observed data. An empirical relationship between SY and basin area for north Indian rivers was also developed using the data of previous investigators, leveraging existing research. The study findings help decision-makers in identifying areas vulnerable to erosion and implementing the most effective strategies for SE management in high-priority regions. Additionally, the results offer significant understanding for evaluating erosion risks and developing targeted mitigation strategies in critical areas.