An improved SCF‑SWE relationship function with topographic controls for enhanced snowmelt runoff simulation

Study region The Yarlung Zangbo River Basin (YZRB), a representative high‑altitude alpine‑glacial basin in Xizang, southwestern China. Study focus To improve the snowmelt runoff simulation accuracy of the EasyDHM (Easy Distributed Hydrological Model) in the YZRB, this study proposes an improved snow cover fraction (SCF)-snow water equivalent (SWE) relationship function. Different from the baseline model adopting traditional empirical formulas, the new function incorporates the nonlinear Sigmoid-based physical mechanisms of snow evolution. By establishing a differential equation with SWE as the independent variable and integrating elevation and slope as dynamic constraints, the model better captures the spatial heterogeneity of snow distribution in complex alpine terrains. New hydrological insights for the region Multi-section validation demonstrates that the improved model significantly boosts runoff prediction accuracy, with the average Nash-Sutcliffe efficiency (NSE) increasing from 0.763 to 0.899 and the percent bias (PBIAS) dropping from 11.29% to 6.25% during the calibration period. The improved module effectively eliminates the premature runoff peaks in May, as found in the baseline model, ensuring precise phase alignment during the critical snowmelt period (March-June). Overall, the improved SCF-SWE relationship function enhances the model’s applicability, providing a reliable tool for snowmelt runoff simulation, water resource assessment, and hydrological forecasting in cryosphere-dominated basins.

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Publication Details

Journal
Journal of Hydrology Regional Studies
Published
2026-09-12
DOI
https://doi.org/10.1016/j.ejrh.2026.103969
Primary Topic
Cryospheric studies and observations
Type
article
Field-Weighted Citation Impact
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article

An improved SCF‑SWE relationship function with topographic controls for enhanced snowmelt runoff simulation

Yanhong Dou, Liyuan Zheng, Shuqiang Nian, Yunzhong Jiang et al.
Journal of Hydrology Regional Studies
Cryospheric studies and observations
article

An improved SCF‑SWE relationship function with topographic controls for enhanced snowmelt runoff simulation

Yanhong Dou, Liyuan Zheng, Shuqiang Nian, Yunzhong Jiang, Hao Wang, Weihong Liao
article en

Abstract

Study region The Yarlung Zangbo River Basin (YZRB), a representative high‑altitude alpine‑glacial basin in Xizang, southwestern China. Study focus To improve the snowmelt runoff simulation accuracy of the EasyDHM (Easy Distributed Hydrological Model) in the YZRB, this study proposes an improved snow cover fraction (SCF)-snow water equivalent (SWE) relationship function. Different from the baseline model adopting traditional empirical formulas, the new function incorporates the nonlinear Sigmoid-based physical mechanisms of snow evolution. By establishing a differential equation with SWE as the independent variable and integrating elevation and slope as dynamic constraints, the model better captures the spatial heterogeneity of snow distribution in complex alpine terrains. New hydrological insights for the region Multi-section validation demonstrates that the improved model significantly boosts runoff prediction accuracy, with the average Nash-Sutcliffe efficiency (NSE) increasing from 0.763 to 0.899 and the percent bias (PBIAS) dropping from 11.29% to 6.25% during the calibration period. The improved module effectively eliminates the premature runoff peaks in May, as found in the baseline model, ensuring precise phase alignment during the critical snowmelt period (March-June). Overall, the improved SCF-SWE relationship function enhances the model’s applicability, providing a reliable tool for snowmelt runoff simulation, water resource assessment, and hydrological forecasting in cryosphere-dominated basins.

Journal of Hydrology Regional StudiesVol. 68
Tianjin University (CN), Xiamen University (CN), China Institute of Water Resources and Hydropower Research (CN), China National Commission for Disaster Reduction (CN), Ministry of Water Resources of the People's Republic of China (CN)
Clean water and sanitation
Openalex Percentile: Top 15%
Cryospheric studies and observations
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