Abstract

In this paper, the performance of the classic snowmelt runoff model (SRM) is evaluated in a daily discharge simulation with two different melt models, the empirical temperature-index melt model and the energy-based radiation melt model, through a case study from the data-sparse mountainous watershed of the Urumqi River basin in Xinjiang Uyghur Autonomous Region of China. Theclassic SRM, which uses the empirical temperature-index method, and a radiation-based SRM, incorporating shortwave solar radiation and snow albedo, were developed to simulate daily runoff for the spring and summer snowmelt seasons from 2005 to 2012, respectively. Dailymeteorological and hydrological data were collected from three stations located in the watershed. Snowcover area (SCA) was extracted from satellite images. Solarradiation inputs were estimated based on a digital elevation model (DEM). Theresults showed that the overall accuracy of the classic SRM and radiation-based SRM for simulating snowmelt discharge was relatively high. Theclassic SRM outperformed the radiation-based SRM due to the robust performance of the temperature-index model in the watershed snowmelt computation. Nosignificant improvement was achieved by employing solar radiation and snow albedo in the snowmelt runoff simulation due to the inclusion of solar radiation as a temperature-dependent energy source and the local pattern of snowmelt behavior throughout the melting season. Ourresults suggest that the classic SRM simulates daily runoff with favorable accuracy and that the performance of the radiation-based SRM needs to be further improved by more ground-measured data for snowmelt energy input.

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