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<p>The Upper Ganga Basin (UGB) in Northern India heavily depends on seasonal snowmelt and glacier-fed runoff, making it highly sensitive to climate change. In this study, we employ WinSRM (version 1.12), a degree-day-based Snowmelt Runoff Model, to simulate current (2000–2015) and future (up to 2099) hydrological responses under RCP 4.5 climate projections from the CCCma_CanESM2 model. Daily precipitation, temperature (bias-corrected), and MODIS 500&#xa0;m snow-cover data serve as the primary inputs. Model calibration yielded a Nash-Sutcliffe Efficiency of 0.78 during 2000–2005 and 0.75 during 2006–2015, demonstrating robust performance. Results indicate a consistent warming trend of 0.03&#xa0;°C/year, earlier snowmelt onset, and a 15% decrease in snowfall duration. Future scenarios project a 10–15% increase in summer snowmelt runoff by 2050 and up to a 40% decline in glacial volume by 2100. However, these findings are subject to uncertainties associated with climate model assumptions, remote sensing resolution (500&#xa0;m), and input data biases, underscoring the need for enhanced local climate modeling and improved glacial monitoring. Our results highlight the vulnerability of the UGB’s water resources and emphasize the importance of adaptive water management strategies for sustaining downstream communities.</p>

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Simulating snowmelt runoff in the Upper Ganga Basin under climate change scenarios

  • 期刊论文

  • 发表日期：

    2025年6月30日

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  • Manish Rawat,
  • Rayees Ahmed,
  • Riyaz Ahmad Mir,
  • Anil Kumar Lohani,
  • Sanjay Kumar Jain

摘要

The Upper Ganga Basin (UGB) in Northern India heavily depends on seasonal snowmelt and glacier-fed runoff, making it highly sensitive to climate change. In this study, we employ WinSRM (version 1.12), a degree-day-based Snowmelt Runoff Model, to simulate current (2000–2015) and future (up to 2099) hydrological responses under RCP 4.5 climate projections from the CCCma_CanESM2 model. Daily precipitation, temperature (bias-corrected), and MODIS 500 m snow-cover data serve as the primary inputs. Model calibration yielded a Nash-Sutcliffe Efficiency of 0.78 during 2000–2005 and 0.75 during 2006–2015, demonstrating robust performance. Results indicate a consistent warming trend of 0.03 °C/year, earlier snowmelt onset, and a 15% decrease in snowfall duration. Future scenarios project a 10–15% increase in summer snowmelt runoff by 2050 and up to a 40% decline in glacial volume by 2100. However, these findings are subject to uncertainties associated with climate model assumptions, remote sensing resolution (500 m), and input data biases, underscoring the need for enhanced local climate modeling and improved glacial monitoring. Our results highlight the vulnerability of the UGB’s water resources and emphasize the importance of adaptive water management strategies for sustaining downstream communities.