A River Network‐Based Hierarchical Model for Deriving Flood Frequency Distributions and Its Application to the Upper Yangtze Basin

In flood frequency analysis, expanding the additional information with hydrological reasoning beyond local at‐site flood samples can be very useful for improving the accuracy of flood frequency distribution (FFD) estimation as well as reflecting a better understanding of flood characteristics. In th...

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Veröffentlicht in:Water resources research 2021-08, Vol.57 (8), p.n/a, Article 2020
Hauptverfasser: Jiang, Cong, Xiong, Lihua, Xu, Chong‐Yu, Yan, Lei
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Xiong, Lihua
Xu, Chong‐Yu
Yan, Lei
description In flood frequency analysis, expanding the additional information with hydrological reasoning beyond local at‐site flood samples can be very useful for improving the accuracy of flood frequency distribution (FFD) estimation as well as reflecting a better understanding of flood characteristics. In this study, a river network‐based hierarchical model is developed to estimate the FFDs in the Upper Yangtze basin by making full use of the hydrological reasoning information of both the flood dependence within the river network and reservoir regulation. Under this hierarchical model, a covariate analysis based on the generalized additive model for location, scale and shape is performed to obtain the conditional distribution of the interested flood variable given both its upstream flood variables and the reservoir index quantifying reservoir regulation; and then, the FFD of the interested flood variable is derived by combining its conditional distribution with the probability distribution of the upstream flood variables. The application to the Upper Yangtze basin indicates that the proposed hierarchical model suggests a satisfactory performance in FFD estimation. It is also found that the reservoir regulation, especially that of the Three Gorges Reservoir, is of great significance in reducing the flood magnitude in the basin. Compared to the conventional FFD estimation method that directly fits the assumed theoretical probability distributions to the at‐site flood samples, the hierarchical model incorporating the flood dependence within the river network exhibits an advantage in capturing the effect of reservoir regulation on the floods as well as in reducing the uncertainty in flood quantile estimation. Key Points A river network‐based hierarchical model is developed to derive flood frequency distributions in the Upper Yangtze basin The reservoir regulation especially that of the Three Gorges Reservoir remarkably reduces the flood magnitude in the Upper Yangtze basin The hierarchical model incorporating the flood dependence within river network improves estimation quality of flood frequency distributions
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In this study, a river network‐based hierarchical model is developed to estimate the FFDs in the Upper Yangtze basin by making full use of the hydrological reasoning information of both the flood dependence within the river network and reservoir regulation. Under this hierarchical model, a covariate analysis based on the generalized additive model for location, scale and shape is performed to obtain the conditional distribution of the interested flood variable given both its upstream flood variables and the reservoir index quantifying reservoir regulation; and then, the FFD of the interested flood variable is derived by combining its conditional distribution with the probability distribution of the upstream flood variables. The application to the Upper Yangtze basin indicates that the proposed hierarchical model suggests a satisfactory performance in FFD estimation. It is also found that the reservoir regulation, especially that of the Three Gorges Reservoir, is of great significance in reducing the flood magnitude in the basin. Compared to the conventional FFD estimation method that directly fits the assumed theoretical probability distributions to the at‐site flood samples, the hierarchical model incorporating the flood dependence within the river network exhibits an advantage in capturing the effect of reservoir regulation on the floods as well as in reducing the uncertainty in flood quantile estimation. Key Points A river network‐based hierarchical model is developed to derive flood frequency distributions in the Upper Yangtze basin The reservoir regulation especially that of the Three Gorges Reservoir remarkably reduces the flood magnitude in the Upper Yangtze basin The hierarchical model incorporating the flood dependence within river network improves estimation quality of flood frequency distributions</description><identifier>ISSN: 0043-1397</identifier><identifier>EISSN: 1944-7973</identifier><identifier>DOI: 10.1029/2020WR029374</identifier><language>eng</language><publisher>WASHINGTON: Amer Geophysical Union</publisher><subject>Additives ; Canyons ; Distribution ; Environmental Sciences ; Environmental Sciences &amp; Ecology ; Flood frequency ; Flood frequency analysis ; flood frequency distribution ; Flood magnitude ; Floods ; Frequency analysis ; Frequency distribution ; hierarchical model ; Hydrology ; Life Sciences &amp; Biomedicine ; Limnology ; Marine &amp; Freshwater Biology ; Modelling ; Physical Sciences ; Probability distribution ; Probability theory ; Reasoning ; reservoir effect ; Reservoirs ; River discharge ; River networks ; Rivers ; Science &amp; Technology ; Upstream ; Water Resources ; Yangtze River</subject><ispartof>Water resources research, 2021-08, Vol.57 (8), p.n/a, Article 2020</ispartof><rights>2021. 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It is also found that the reservoir regulation, especially that of the Three Gorges Reservoir, is of great significance in reducing the flood magnitude in the basin. Compared to the conventional FFD estimation method that directly fits the assumed theoretical probability distributions to the at‐site flood samples, the hierarchical model incorporating the flood dependence within the river network exhibits an advantage in capturing the effect of reservoir regulation on the floods as well as in reducing the uncertainty in flood quantile estimation. 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Freshwater Biology</subject><subject>Modelling</subject><subject>Physical Sciences</subject><subject>Probability distribution</subject><subject>Probability theory</subject><subject>Reasoning</subject><subject>reservoir effect</subject><subject>Reservoirs</subject><subject>River discharge</subject><subject>River networks</subject><subject>Rivers</subject><subject>Science &amp; Technology</subject><subject>Upstream</subject><subject>Water Resources</subject><subject>Yangtze River</subject><issn>0043-1397</issn><issn>1944-7973</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>HGBXW</sourceid><sourceid>3HK</sourceid><recordid>eNqNkc9u1DAQxi0EEkvhxh1LHCEw_pv4uKQsrVRAWhVVnCwncVqXYKe2t9Vy4sAD8Iw8CV62IE6Ik0fWb77vmxmEHhN4QYCqlxQonK1LxWp-By2I4ryqVc3uogUAZxVhqr6PHqR0CUC4kPUCfVvitbu2Eb-z-SbETz--fn9lkh3wkbPRxP7C9WbCb8NgJzyGiA9tdNfOn-PVFMKAV9Febazvt_jQpRxdt8ku-ISNH_BxTng5z1NR2H3iHHC-sPjDPBe7j8af5y8WFzPnH6J7o5mSfXT7HqDT1evT9qg6ef_muF2eVIYpSirGJYFaNET0w8CNlU3XkYEzEJ3oRsIMUNGMxqq-o2QUUg4SqJU1YY1iAOwAPdnL9rGEdV77EI0m0AiqFVW0LsTTPTHHUOZKWV-GTfQlk6ZCciJpcSjU8986IaVoRz1H99nEbdHSu0Povw9R8Gd7_MZ2YUy9K_uyf1oAQDYNBcF31S5k8_906_Kv3bZh43NpZbetbrLbf4bSZ-t2TQUXhP0EqOWp7w</recordid><startdate>202108</startdate><enddate>202108</enddate><creator>Jiang, Cong</creator><creator>Xiong, Lihua</creator><creator>Xu, Chong‐Yu</creator><creator>Yan, Lei</creator><general>Amer Geophysical Union</general><general>John Wiley &amp; 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In this study, a river network‐based hierarchical model is developed to estimate the FFDs in the Upper Yangtze basin by making full use of the hydrological reasoning information of both the flood dependence within the river network and reservoir regulation. Under this hierarchical model, a covariate analysis based on the generalized additive model for location, scale and shape is performed to obtain the conditional distribution of the interested flood variable given both its upstream flood variables and the reservoir index quantifying reservoir regulation; and then, the FFD of the interested flood variable is derived by combining its conditional distribution with the probability distribution of the upstream flood variables. The application to the Upper Yangtze basin indicates that the proposed hierarchical model suggests a satisfactory performance in FFD estimation. It is also found that the reservoir regulation, especially that of the Three Gorges Reservoir, is of great significance in reducing the flood magnitude in the basin. Compared to the conventional FFD estimation method that directly fits the assumed theoretical probability distributions to the at‐site flood samples, the hierarchical model incorporating the flood dependence within the river network exhibits an advantage in capturing the effect of reservoir regulation on the floods as well as in reducing the uncertainty in flood quantile estimation. Key Points A river network‐based hierarchical model is developed to derive flood frequency distributions in the Upper Yangtze basin The reservoir regulation especially that of the Three Gorges Reservoir remarkably reduces the flood magnitude in the Upper Yangtze basin The hierarchical model incorporating the flood dependence within river network improves estimation quality of flood frequency distributions</abstract><cop>WASHINGTON</cop><pub>Amer Geophysical Union</pub><doi>10.1029/2020WR029374</doi><tpages>21</tpages><orcidid>https://orcid.org/0000-0002-6390-5646</orcidid><orcidid>https://orcid.org/0000-0003-4826-5350</orcidid><orcidid>https://orcid.org/0000-0001-6990-2414</orcidid><oa>free_for_read</oa></addata></record>
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subjects Additives
Canyons
Distribution
Environmental Sciences
Environmental Sciences & Ecology
Flood frequency
Flood frequency analysis
flood frequency distribution
Flood magnitude
Floods
Frequency analysis
Frequency distribution
hierarchical model
Hydrology
Life Sciences & Biomedicine
Limnology
Marine & Freshwater Biology
Modelling
Physical Sciences
Probability distribution
Probability theory
Reasoning
reservoir effect
Reservoirs
River discharge
River networks
Rivers
Science & Technology
Upstream
Water Resources
Yangtze River
title A River Network‐Based Hierarchical Model for Deriving Flood Frequency Distributions and Its Application to the Upper Yangtze Basin
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