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Snow depth plays a significant role in the regional water balance, for which snowfall is usually determined by a fixed temperature threshold in regional snow research. This study developed a regional hydrological process-based snow depth model in the Upper Yangtze River Basin by using spatially distributed critical temperature data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data and station data. Based on meteorological station and remotely sensed data, daily snow hydrological components from 1 August 2003 to 31 July 2015 were simulated. Results show that the simulated snow depth patterns agreed with those of the observed snow depth. The multi-year average of the starting date and ending date of snow duration was 16 October and 6 June, respectively, and that of maximum annual snowfall was approximately 455 mm, of which canopy interception comprised 10%, with a maximum value of 50 mm. The proportion of snow sublimation was less than 20%, which was contributed by interception sublimation (40%), snow surface sublimation (40%) and sublimation underneath the canopy (20%). The maximum annual snow sublimation was 29 mm. Snow melting was the primary snow consumption pathway, and approximately 70% of snowfall melted. This research is significant for the assessment and management of water resources in this region.

A simple regional snow hydrological process-based snow depth model and its application in the Upper Yangtze River Basin