Scholarlink

<p>Hydrological modelling is essential for understanding runoff dynamics and water potential in river basins, based on rainfall, land use, and soil properties. Among various models, HEC-HMS has been widely applied for rainfall-runoff simulations. In this study, a rainfall-runoff model for the Lower Sub-Basin of the Tapi River was developed using HEC-HMS. Daily rainfall and streamflow data from 2005 to 2015 were used for model development. Hydrological parameters, along with land use/land cover (LULC), soil, and slope maps, were prepared using ArcGIS to compute curve numbers for model input. Daily, monthly, and monsoonal rainfall-runoff models were developed and evaluated using statistical performance indices including the coefficient of determination (R²), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), and RMSE-observation standard deviation ratio (RSR). The results indicate that all models generally perform well, with R² and NSE values exceeding 0.75 and PBIAS below 10%, except for the daily model where NSE was slightly lower than 0.75. Among the models, showed superior performance in reproducing observed streamflow, highlighting its suitability for water resources planning and management in the Lower Tapi River Basin.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Hydrological modeling for flood inundation assessment using HEC-HMS in the lower sub-basin of the Tapi River India

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月16日

查看全文
  • Pradeep Kumar Rajput

摘要

Hydrological modelling is essential for understanding runoff dynamics and water potential in river basins, based on rainfall, land use, and soil properties. Among various models, HEC-HMS has been widely applied for rainfall-runoff simulations. In this study, a rainfall-runoff model for the Lower Sub-Basin of the Tapi River was developed using HEC-HMS. Daily rainfall and streamflow data from 2005 to 2015 were used for model development. Hydrological parameters, along with land use/land cover (LULC), soil, and slope maps, were prepared using ArcGIS to compute curve numbers for model input. Daily, monthly, and monsoonal rainfall-runoff models were developed and evaluated using statistical performance indices including the coefficient of determination (R²), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), and RMSE-observation standard deviation ratio (RSR). The results indicate that all models generally perform well, with R² and NSE values exceeding 0.75 and PBIAS below 10%, except for the daily model where NSE was slightly lower than 0.75. Among the models, showed superior performance in reproducing observed streamflow, highlighting its suitability for water resources planning and management in the Lower Tapi River Basin.