Flash flood simulation based on distributed hydrological model in future scenarios

Extreme rainfall events are frequent, particularly in economically underdeveloped hilly areas, where conventional hydrological models struggle to accurately simulate the formation of flash floods. Therefore, this study focuses on the Daxi River Basin in Guangdong Province. First, CMIP6 precipitation...

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Main Authors: Qi Liu, Nan Zhang, Lingling Wang, Kunxia Yu, Jiayi Wu, Jingqi Wang, Meihong Ma
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Earth Science
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Online Access:https://www.frontiersin.org/articles/10.3389/feart.2024.1537486/full
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author Qi Liu
Nan Zhang
Lingling Wang
Kunxia Yu
Jiayi Wu
Jingqi Wang
Meihong Ma
Meihong Ma
author_facet Qi Liu
Nan Zhang
Lingling Wang
Kunxia Yu
Jiayi Wu
Jingqi Wang
Meihong Ma
Meihong Ma
author_sort Qi Liu
collection DOAJ
description Extreme rainfall events are frequent, particularly in economically underdeveloped hilly areas, where conventional hydrological models struggle to accurately simulate the formation of flash floods. Therefore, this study focuses on the Daxi River Basin in Guangdong Province. First, CMIP6 precipitation data is utilized to analyze the future precipitation variations on interannual and monthly scales. Compared to the baseline period, the annual precipitation increases under all three scenarios. Next, design storms with a return period greater than 2 years are allocated into rainfall patterns. By combining the accumulated precipitation with the soil moisture content, different distributed hydrological models are applied to calculate the corresponding flood discharges for different rainfall events. The results indicate that: 1) Precipitation under the SSP5-8.5 scenario is generally higher than under the SSP1-2.6 and SSP2-4.5 scenarios, with the SSP1-2.6 scenario showing the mildest increase. 2) The peak flood simulated by the CREST model are relatively low, at 235.4 m³/s, with fewer precipitation events covered, which is significantly lower than the simulation accuracy of the CNFF model. 3) The Daxi River Basin has a low probability of experiencing flash flood disasters exceeding the 10-year return period in the period from 2026 to 2070. The above research results will provide important references for flash flood disaster prevention in similar basins.
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issn 2296-6463
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spelling doaj-art-715fe93922e241bf85316aaf559d4c192025-01-14T06:10:20ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632025-01-011210.3389/feart.2024.15374861537486Flash flood simulation based on distributed hydrological model in future scenariosQi Liu0Nan Zhang1Lingling Wang2Kunxia Yu3Jiayi Wu4Jingqi Wang5Meihong Ma6Meihong Ma7Research Center on Flood and Drought Disaster Reduction of the Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing, ChinaFaculty of Geography, Tianjin Normal University, Tianjin, ChinaShaanxi Provincial Department of Water Resources, Shaanxi Flood and Drought Disaster Prevention Center, Xi’an, Shaanxi, ChinaState Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi’an University of Technology, Xi’an, ChinaFaculty of Geography, Tianjin Normal University, Tianjin, ChinaSchool of National Security and Emergency Management, Beijing Normal University, Beijing, ChinaFaculty of Geography, Tianjin Normal University, Tianjin, ChinaState Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, ChinaExtreme rainfall events are frequent, particularly in economically underdeveloped hilly areas, where conventional hydrological models struggle to accurately simulate the formation of flash floods. Therefore, this study focuses on the Daxi River Basin in Guangdong Province. First, CMIP6 precipitation data is utilized to analyze the future precipitation variations on interannual and monthly scales. Compared to the baseline period, the annual precipitation increases under all three scenarios. Next, design storms with a return period greater than 2 years are allocated into rainfall patterns. By combining the accumulated precipitation with the soil moisture content, different distributed hydrological models are applied to calculate the corresponding flood discharges for different rainfall events. The results indicate that: 1) Precipitation under the SSP5-8.5 scenario is generally higher than under the SSP1-2.6 and SSP2-4.5 scenarios, with the SSP1-2.6 scenario showing the mildest increase. 2) The peak flood simulated by the CREST model are relatively low, at 235.4 m³/s, with fewer precipitation events covered, which is significantly lower than the simulation accuracy of the CNFF model. 3) The Daxi River Basin has a low probability of experiencing flash flood disasters exceeding the 10-year return period in the period from 2026 to 2070. The above research results will provide important references for flash flood disaster prevention in similar basins.https://www.frontiersin.org/articles/10.3389/feart.2024.1537486/fullflash floodCRESTCMIP6future scenariodaxi water Basin
spellingShingle Qi Liu
Nan Zhang
Lingling Wang
Kunxia Yu
Jiayi Wu
Jingqi Wang
Meihong Ma
Meihong Ma
Flash flood simulation based on distributed hydrological model in future scenarios
Frontiers in Earth Science
flash flood
CREST
CMIP6
future scenario
daxi water Basin
title Flash flood simulation based on distributed hydrological model in future scenarios
title_full Flash flood simulation based on distributed hydrological model in future scenarios
title_fullStr Flash flood simulation based on distributed hydrological model in future scenarios
title_full_unstemmed Flash flood simulation based on distributed hydrological model in future scenarios
title_short Flash flood simulation based on distributed hydrological model in future scenarios
title_sort flash flood simulation based on distributed hydrological model in future scenarios
topic flash flood
CREST
CMIP6
future scenario
daxi water Basin
url https://www.frontiersin.org/articles/10.3389/feart.2024.1537486/full
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AT linglingwang flashfloodsimulationbasedondistributedhydrologicalmodelinfuturescenarios
AT kunxiayu flashfloodsimulationbasedondistributedhydrologicalmodelinfuturescenarios
AT jiayiwu flashfloodsimulationbasedondistributedhydrologicalmodelinfuturescenarios
AT jingqiwang flashfloodsimulationbasedondistributedhydrologicalmodelinfuturescenarios
AT meihongma flashfloodsimulationbasedondistributedhydrologicalmodelinfuturescenarios
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