A test of Snowmelt Runoff Model （SRM） for the Gongnaisi River basin in the western Tianshan Mountains, China

The Snowmelt Runoff Model (SRM) is one of a very few models in the world today that requires remote sensing derived snow cover as model input. Owing to its simple data requirements and use of remote sensing to provide snow cover information, SRM is ideal for use in data sparse regions, particularly in remote and inaccessible high mountain watersheds. In order to verify the applicability of SRM in an environment of continental climate, a test of SRM is performed for the Gongnaisi River basin in the western Tianshan Mountains, the results show that two SRM average goodness-of-fit statistics for simulations, Nash-Sutcliff coeffident (R2) and volume difference (Dv), are 0.87 and 0.90%,respectively. As compared with the application results over 80 basins in 25 different countries around the world, SRM performs well in the Gongnaisi River basin. The results also show that SRM can be a validated snowmelt runoff model capable of being applied in the western Tianshan Mountains.On the basis of snowmelt runoff simulation, together with a set of simplified hypothetical climate scenarios, SRM is also used to simulate the effects of climate change on snow cover and the consecutive snowmelt runoff. For a given hypothetical temperature increase of 4℃, the snow coverage and snowmelt season shift towards earlier dates, and the snowmelt runoff, as a result, is changed significantly at the same time. The simulation results show that the snow cover is sensitive to changes of climate, especially to the increase of temperature, the major effect of climate change will be a time shifting of snowmelt runoff to early spring months, resulting in a redistribution of seasonally runoff throughout the whole snowmelt season.

A test of Snowmelt Runoff Model (SRM) for the Gongnaisi River basin in the western Tianshan Mountains,China

The Snowmelt Runoff Model (SRM) is one of a very few models in the world today that requires remote sensing derived snow cover as model input. Owing to its simple data requirements and use of remote sensing to provide snow cover information, SRM is ideal for use in data sparse regions, particularly in remote and inaccessible high mountain watersheds. In order to verify the applicability of SRM in an environment of continental climate, a test of SRM is performed for the Gongnaisi River basin in the western Tianshan Mountains, the results show that two SRM average goodness-of-fit statistics for simulations, Nash-Sutcliff coefficient (R2) and volume difference (DV), are 0.87 and 0.90%, respectively. As compared with the application results over 80 basins in 25 different countries around the world, SRM performs well in the Gongnaisi River basin. The results also show that SRM can be a validated snowmelt runoff model capable of being applied in the western Tianshan Mountains. On the basis of snowmelt runoff simulation, together with a set of simplified hypothetical climate scenarios, SRM is also used to simulate the effects of climate change on snow cover and the consecutive snowmelt runoff. For a given hypothetical temperature increase of 4℃, the snow coverage and snowmelt season shift towards earlier dates, and the snowmelt runoff, as a result, is changed significantly at the same time. The simulation results show that the snow cover is sensitive to changes of climate, especially to the increase of temperature, the major effect of climate change will be a time shifting of snowmelt runoff to early spring months, resulting in a redistribution of seasonally runoff throughout the whole snowmelt season.