Distributed calibrating snow models using remotely sensed snow cover information

Abstract:

Distributed calibrating snow models using remotely sensed snow cover information

Hongyi Li¹, Tao Che¹, Xin Li¹, Jian Wang¹

1. Cold and Arid Regions Environmental and Engineering Research Institute,
Chinese Academy of Sciences, Lanzhou 730000, China

For improving the simulation accuracy of snow model, remotely sensed snow cover data are used to calibrate spatial parameters of snow model. A physically based snow model is developed and snow parameters including snow surface roughness, new snow density and critical threshold temperature distinguishing snowfall from precipitation, are spatially calibrated in this study. The study region, Babaohe basin, located in northwestern China, have seasonal snow cover and with complex terrain. The results indicates that the spatially calibration of snow model parameters make the simulation results more reasonable, and the simulated snow accumulation days, plot-scale snow depth are more better than lumped calibration.