Screening and Optimizing the Sensitive Parameters of BTOPMC Model Based on UQ-PyL Software: Case Study of a Flood Event in the Fuji River Basin, Japan
Publication: Journal of Hydrologic Engineering
Volume 25, Issue 9
Abstract
Block-wise use of TOPMODEL with the Muskingum–Cunge method (BTOPMC) is a physically based distributed hydrological model with five parameters that quantitatively reflect basin physical features, including soil type, vegetation, and land use of each grid-cell. In order to determine the sensitive model parameters and related variables more reasonably and efficiently, and to improve the model’s practical applicability and simulation accuracy, BTOPMC was integrated with the Uncertainty Quantification Python Laboratory (UQ-PyL) and used in the Fuji River Basin of Japan, by which qualitative and quantitative sensitivity analysis (SA) of variables related to the BTOPMC parameters was performed, and the sensitive ones were optimized by shuffled complex evolution (SCE-UA). The results showed that optimizing only the sensitive variables related to the three sensitive parameters of BTOPMC can ensure simulation accuracy with higher optimization efficiency, which indicates that the BTOPMC model could be applied more simply while guaranteeing the reliability of modeling.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available in a repository online in accordance with funder data retention policies. All the data used in this study are as follows: (1) The flood in September 1991 was used as a study case in this paper; (2) the DEM of the basin was taken from CD-ROM GLOBE (version 0.5) of NGDC (1997) and the spatial resolution is (roughly ); (3) hourly precipitation data were obtained from the AMeDAS (Automated Meteorological Data Acquisition System), and the average annual precipitation for 1991 was 1,550 mm; and (4) the annual potential evapotranspiration was estimated by the Penman-Monteith method at about 1,800 mm.
Acknowledgments
It is very appreciated, the valuable suggestions and comments from all the reviewers, and for all the contributors of the references cited in this paper. Author contributions: conceptualization, Ling-xue Liu, Tian-qi Ao and Xiao-dong Li; data curation, formal analysis, and software, Ling-xue Liu and Li Zhou; funding acquisition, Tian-qi Ao; methodology, Ling-xue Liu, Tian-qi Ao, Li Zhou and Xiao-dong Li; writing (original draft), Ling-xue Liu; Writing (review and editing), Ling-xue Liu, Li Zhou, Ting Chen, and Tian-qi Ao. This research is supported by: (1) the international cooperation project of the Ministry of Science and Technology of China (Grant No. 2012DFG21780), (2) the international cooperation project of the Sichuan Province of China (Grant No. 2010HH0005), and (3) China Scholarship Council (Grant No. 201806240035).
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Journal of Hydrologic Engineering
Volume 25 • Issue 9 • September 2020
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© 2020 American Society of Civil Engineers.
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Received: Sep 25, 2019
Accepted: Apr 7, 2020
Published online: Jul 11, 2020
Published in print: Sep 1, 2020
Discussion open until: Dec 11, 2020
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