Chakraborty Kunal, Saha Snehasish, Mandal Debasish
Department of Geography & Applied Geography, University of North Bengal, Darjeeling, 734013, West Bengal, India.
Environ Sci Pollut Res Int. 2025 Apr;32(16):10258-10278. doi: 10.1007/s11356-024-34385-5. Epub 2024 Jul 20.
Growing concerns over water availability arise from the problems of population growth, rapid industrialization, and human interferences, necessitating accurate streamflow estimation at the river basin scale. It is extremely challenging to access stream flow data of a transboundary river at a spatio-temporal scale due to data unavailability caused by water conflicts for assessing the water availability.Primarily, this estimation is done using rainfall-runoff models. The present study addresses this challenge by applying the soil and water assessment tool (SWAT) for hydrological modelling, utilizing high-resolution geospatial inputs. Hydrological modelling using remote sensing and GIS (Geographic Information System) through this model is initiated to assess the water availability in the Ganga River basin at different locations. The outputs are calibrated and validated using the observed station data from Global Runoff Data Centre (GRDC). To check the performance of the model, Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), coefficient of determination (R), and RSR efficacy measures are initiated in ten stations using the observed and simulated stream flow data. The R values of eight stations range from 0.82 to 0.93, reflecting the efficacy of the model in rainfall-runoff modelling. Moreover, the results obtained from this hydrological modelling can serve as valuable resources for water resource planners and geographers for future reference.
对水资源可用性的日益关注源于人口增长、快速工业化和人类干预等问题，这就需要在流域尺度上进行准确的径流估算。由于水冲突导致数据不可用，在时空尺度上获取跨界河流的径流数据极具挑战性，而这些数据对于评估水资源可用性至关重要。主要而言，这种估算通过降雨径流模型来完成。本研究通过应用土壤和水资源评估工具（SWAT）进行水文建模，并利用高分辨率地理空间输入数据来应对这一挑战。通过该模型利用遥感和地理信息系统（GIS）启动水文建模，以评估恒河流域不同地点的水资源可用性。利用全球径流数据中心（GRDC）的观测站数据对输出结果进行校准和验证。为检验模型的性能，使用观测和模拟的径流数据，在十个站点启动了纳什 - 萨特克利夫效率（NSE）、偏差百分比（PBIAS）、决定系数（R）和RSR效能度量。八个站点的R值范围为0.82至0.93，反映了该模型在降雨径流建模中的效能。此外，从这种水文建模中获得的结果可为水资源规划者和地理学家提供宝贵的资源以供未来参考。
