Articles | Volume 30, issue 16
https://doi.org/10.5194/hess-30-5343-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-5343-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Process diagnostics of snowmelt runoff in global hydrological and land surface models – Part 1: A systematic evaluation across basins of increasing complexity
Xiangyong Lei
Institute of Remote Sensing and Geographic Information Systems, School of Earth and Space Sciences, Peking University, Beijing, 100871, China
Haomei Lin
Institute of Remote Sensing and Geographic Information Systems, School of Earth and Space Sciences, Peking University, Beijing, 100871, China
Kaihao Zheng
Institute of Remote Sensing and Geographic Information Systems, School of Earth and Space Sciences, Peking University, Beijing, 100871, China
Institute of Remote Sensing and Geographic Information Systems, School of Earth and Space Sciences, Peking University, Beijing, 100871, China
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Short summary
Snowmelt runoff is a critical freshwater resource. This study assesses how well 15 large-scale models and runoff products simulate its volume, peak, and timing across 1455 snow-dominated basins, with special attention to model performance in increasingly complex basin environments. Our results reveal common biases and identify model types with relative strengths, providing guidance for water-resource planning and sustainable water management under global warming.
Snowmelt runoff is a critical freshwater resource. This study assesses how well 15 large-scale...