Reasearch Of Spatial Distributed Snowmelt Runoff Model With Double Layer In The Arid Area

Snowmelt runoff is the main fresh water resource in the middle and high latitude region. And it also could cause large damage in the form of flood. Thus, analysis the mechanism of snowmelt runoff formation could provide decision-making basis for flood control, fight with the drought, water resource management and utilization and so on. And hydrologic model is the main way to simulate the formulation of snowmelt runoff and predict the flood and drought. Consider the snowmelt runoff mainly impacted by snow characteristics, hydrological and meteorological factors, this paper constructs a double layer snowmelt runoff mode l based on the physical mechanism and applied the model in the Juntanghu river basin at the north tianshan mountain, combining with mesoscale numerical prediction model WRF, RS and GIS.This article first extracte the watershed information through the digital elevation model. Next retrieve the soil, vegetation information based on the Harmonized World Soil Database and the national land-use data set with resolution of 250 meters. Then get the snow characteristic based on GIS and RS and simulate the meteorological elements using the numerical weather forecast model WRF. Then coupled them with the snowmelt model.According to the analysis of the WRF simulations in 2010 year, the meteorological data such as temperature, solar radiation, relative humidity, soil temperature and humidity fit the measured data well and could support the further use in the snowmelt runoff model. Although the dominant factors inflouncing the formulation of snowmelt runoff are temperatures and solar radiation, it also control by the melt rate of frozen soil later period of the snow melt. Simulation of snowmelt runoff process are consistent with the observed at 2009, 2010. The whole deterministic coefficient is over 80% and the change of the snow depth in the basin fit the MODIS data well. Promising results indicate the possible use of runoff forecasting driven by numerical weather prediction data for flood mitigation and water resource management.