Review of Regionalization and Remote Sensing Based Method for Hydrological Model Parameters Calibration in Ungauged Basins

被引：0
|
作者：
Jiang L. [1 ,2 ]
Wu H. [2 ,3 ,4 ]
Alfieri L. [5 ]
Li X. [2 ]
Kimball J.S. [6 ]
Chen X. [1 ]
机构：
[1] Institute of Remote Sensing and Geographical Information System, Peking University, Beijing
[2] School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai
[3] Southern Marine Science and Engineering Laboratory, Zhuhai
[4] Earth System Science Interdisciplinary Center, University of Maryland, College Park
[5] European Commission, Joint Research Centre, Ispra
[6] Numerical Terradynamic Simulation Group, University of Montana, Missoula
来源：
Beijing Daxue Xuebao (Ziran Kexue Ban)/Acta Scientiarum Naturalium Universitatis Pekinensis | 2020年 / 56卷 / 06期
关键词：
Hydrological model; Regionalization; Streamflow prediction; Ungauged basins;
D O I：
10.13209/j.0479-8023.2020.076
中图分类号：
学科分类号：
摘要：
Challenges in calibration of hydrological model parameters in ungauged basins were discussed, and the latest advances in regionalization method and remote sensing based method were summarized. First, the common problems in the hydrological model calibration (derivation of hydrographic parameters, construction of objective function and selection of optimization method) and their influences on the results of parameter optimization) were analyzed and leading-edge solutions were then provided. Next, fundamental principles and study progress of regionalization method were introduced, and the importance of stream gauge network density of donor catchments for the streamflow prediction was emphasized. The advance of remote sensing based hydrological model calibration method was discussed in terms of model spatial domain, model structure, satellite data source, and calibration target. Finally, the advantages and disadvantages and the future development prospect between regionalization method and remote sensing based method were compared and analyzed, and potential practical strategies for continuous streamflow prediction in ungauged basins in China are suggested. © 2020 Peking University.
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页码：1152 / 1164
页数：12
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