Volume 5 Issue 2
Jun.  2012
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Article Contents
Shalamu ABUDU, Chun-liang CUI, Muattar SAYDI, James Phillip KING. 2012: Application of snowmelt runoff model (SRM) in mountainous watersheds: A review. Water Science and Engineering, 5(2): 123-136. doi: 10.3882/j.issn.1674-2370.2012.02.001
Citation: Shalamu ABUDU, Chun-liang CUI, Muattar SAYDI, James Phillip KING. 2012: Application of snowmelt runoff model (SRM) in mountainous watersheds: A review. Water Science and Engineering, 5(2): 123-136. doi: 10.3882/j.issn.1674-2370.2012.02.001

Application of snowmelt runoff model (SRM) in mountainous watersheds: A review

doi: 10.3882/j.issn.1674-2370.2012.02.001
Funds:  the National Natural Science Foundation of China (Grant No. 51069017), the Special Fund for Public Welfare Industry of Ministry of Water Resources of China (Grant No. 201001065), the Open-End Fund of Key Laboratory of Oasis Ecology, Xinjiang University (Grant No. XJDX0206-2010-03), and the Open-End Fund of the China Institute of Water Resources and Hydropower Research (Grant No. IWHR-SKL-201104).
More Information
  • Corresponding author: Shalamu ABUDU
  • Received Date: 2011-04-21
  • Rev Recd Date: 2012-02-14
  • The snowmelt runoff model (SRM) has been widely used in simulation and forecast of streamflow in snow-dominated mountainous basins around the world. This paper presents an overall review of worldwide applications of SRM in mountainous watersheds, particularly in data-sparse watersheds of northwestern China. Issues related to proper selection of input climate variables and parameters, and determination of the snow cover area (SCA) using remote sensing data in snowmelt runoff modeling are discussed through extensive review of literature. Preliminary applications of SRM in northwestern China have shown that the model accuracies are relatively acceptable although most of the watersheds lack measured hydro-meteorological data. Future research could explore the feasibility of modeling snowmelt runoff in data-sparse mountainous watersheds in northwestern China by utilizing snow and glacier cover remote sensing data, geographic information system (GIS) tools, field measurements, and innovative ways of model parameterization.


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