Zhibang Lv

    Zhibang Lv

    PhD student, Department of Geography and Planning/Centre for Hydrology, University of Saskatchewan (Supervisor: John Pomeroy)

    Thesis Topic: Data assimilation for cold regions hydrological modelling in the Canadian Rocky Mountains

    Snow hydrological modeling and observations are crucial for understanding and simulating hydrological processes in cold regions. However, model simulations and observations each have deficiencies, which make them deviate from nature. Data assimilation (DA) is an accepted approach to improve this situation by combining complementary information from simulation and observation to obtain more objective estimates of the actual hydrological state and/or flux. In this study, remotely sensed data and ground based data will be used as the data assimilation observation resource for the Cold Regions Hydrological Model (CRHM) to achieve the following objectives: 1) discover the possibility of detecting intercepted snow in the coniferous forest by using remotely sensed data; 2) Evaluate the accuracy of SNODAS in Canadian Rockies and develop downscaling and bias correcting methods for its SWE product; 3) Test CRHM performance improvements by assimilating ground based snow data, SCA data obtained from terrestrial photography, albedo and corrected SNODAS data obtained from objectives 1 and 2.. This research is expected to contribute to the better prediction of mountain snow hydrology and to improve the application of CRHM to hydrological prediction in other locations with sparse meteorological information.


    • Zhibang Lv, John W Pomeroy, and Xing Fang, Evaluation of SNODAS Snow Water Equivalent in Western Canada and assimilation into a cold regions hydrological model. Water Resource Research, in press.
    • Zhibang Lv and John W Pomeroy, Detecting intercepted snow in the coniferous forest by using satellite remotely sensed data. In preparation

    Awards and Scholarships

    • PhD scholarship of China Scholarship Council post-graduate study abroad program