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The runoff estimation is essential for managing water resources, assessing flood risks, and planning environmental strategies. This chapter explores a comprehensive methodology to estimate surface runoff in Satluj River Basin in parts of Bilaspur District of Himachal Pradesh. The total area of study is approx. 1098.77 km2. The RS and GIS technologies were used for calculating surface runoff. The rainfall data (daily and monthly) of required area (from June 2023 to September 2023) was collected from India-WRIS website and used to predict the runoff using the soil conservation service-curve number (SCS-CN) method, advanced by the USDA Natural Resources Conservation Service (NRCS). The curve number (CN) is calculated using Antecedent Moisture Condition II (AMC-II) by integrating hydrologic soil groups (HSGs) and LULC categories. For that, satellite imagery, digital elevation models (DEMs), hydrological soil data, and precipitation data are merged with geospatial technologies. These tools are used to classify LULC, extract drainage networks, delineate basins, and estimate surface runoff in the area of interest. The surface runoff map has been generated with low and high of 865.75 mm and 1344.86 mm, respectively, for the monsoon season in the area of interest. This information can be used to develop required water and soil conservation plans.

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Estimation of Surface Runoff of Satluj Sub-basin of Bilaspur and Parts of Mandi, Shimla, Solan, Himachal Pradesh, India

  • 章节

  • 发表日期：

    2025年

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  • Saloni Bauddh,
  • Roshan Mahto,
  • Neha G. Paswan

摘要

The runoff estimation is essential for managing water resources, assessing flood risks, and planning environmental strategies. This chapter explores a comprehensive methodology to estimate surface runoff in Satluj River Basin in parts of Bilaspur District of Himachal Pradesh. The total area of study is approx. 1098.77 km2. The RS and GIS technologies were used for calculating surface runoff. The rainfall data (daily and monthly) of required area (from June 2023 to September 2023) was collected from India-WRIS website and used to predict the runoff using the soil conservation service-curve number (SCS-CN) method, advanced by the USDA Natural Resources Conservation Service (NRCS). The curve number (CN) is calculated using Antecedent Moisture Condition II (AMC-II) by integrating hydrologic soil groups (HSGs) and LULC categories. For that, satellite imagery, digital elevation models (DEMs), hydrological soil data, and precipitation data are merged with geospatial technologies. These tools are used to classify LULC, extract drainage networks, delineate basins, and estimate surface runoff in the area of interest. The surface runoff map has been generated with low and high of 865.75 mm and 1344.86 mm, respectively, for the monsoon season in the area of interest. This information can be used to develop required water and soil conservation plans.