Improvement of snowmelt runoff simulation and analysis of key driving factors in alpine river basins

Abstract

[Objective] To address the issue of insufficient physical mechanisms in the distributed hydrological model SPHY for snowmelt runoff simulation in cold regions(specifically the neglect of solar radiation and the use of static degree-day factors), the snowmelt module is optimized and enhanced to improve the accuracy of snowmelt runoff simulation in cold regions. [Methods]Three improvements were made:(1) constructing a radiation-coupled potential snowmelt energy term;(2) proposing a seasonal dynamic degree-day factor based on the snow depth-solar radiation relationship; and(3) quantifying the importance of different factors during the snowmelt process based on random forest. Taking the Niyang River Basin in the southeastern Qinghai-Xizang Plateau as the study area, the simulation performance of the improved model was verified based on meteorological, hydrological, and remote sensing data from 2010 to 2015. The contribution rates of different meteorological factors to snowmelt runoff were quantified through trend analysis, correlation analysis, and random forest models. [Results] The model simulation result showed that during the calibration and validation periods, the average Nash-Sutcliffe efficiency(NSE) of the improved model during the snowmelt period increased by 8%, the root mean square error(RMSE) reduced by 17%, and the overall Percent bias(PBIAS) was optimized from-14. 77% to-0. 05%. Driving factor analysis showed that air temperature was the dominant factor for snowmelt runoff(contribution rate of 41. 79%), and the wind speed contribution rate reached 25. 58%. The total contribution rate of energy factors(air temperature and radiation) reached 61. 08%. [Conclusion] The improved scheme coupling solar radiation with the seasonal dynamic degree-day factor effectively enhances the runoff simulation capability of the SPHY model in cold regions. The findings provide references for runoff simulation in other alpine river basins, and offer scientific support for runoff forecasting and water resource management under climate change.

Keywords

SPHY model / snowmelt runoff / dynamic degree-day factor / radiation coupling / Niyang River Basin / alpine watershed / driving factor analysis / Random Forest(RF)