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Review on parallel computing of distributed hydrological models

LIU Junzhi1,2, ZHU A-Xing1,3, QIN Chengzhi1, CHEN Lajiao4, WU Hui1,2, JIANG Jingchao1,2   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
    3. Department of Geography, University ofWisconsin-Madison, Madison WI 53706, USA;
    4. Institute of Remote Sensing and Digital Earth, CAS, Beijing 100094, China
  • Received:2012-12-01 Revised:2013-03-01 Online:2013-04-25 Published:2013-04-25

Abstract: High resolution distributed hydrological simulations over large watersheds require very large amounts of computations, which cannot be provided by sequential computation techniques on which existing hydrological models were developed. So parallel computing of distributed hydrological models is needed. In this paper, we first analyzed the parallelizability of distributed hydrological models from three angles (spatial, temporal and sub-process) and pointed out that spatial domain decomposition is the preferred approach to parallel computing of distributed hydrological models. According to spatial relationships among simulation units, distributed hydrological models, as well as simulation methods for hydrological processes, are classified into different types. Then, current studies on parallel computing of distributed hydrological models were introduced. For most current studies on parallel computing using spatial domain decomposition methods, sub-basin was adopted as the basic scheduling unit for parallel computing. The temporal-spatial discretization method proved the feasibility of parallel computing utilizing parallelization from the temporal angle. Last, the key technologies and future research directions were discussed in the following aspects: 1) parallel algorithms; 2) parallel computing framework for integrated watershed system simulations; 3) high performance input/output for parallel computing of distributed hydrological models.

Key words: distributed hydrological model, parallel computing, review, spatial domain decomposition