A novel dynamic flash flood early warning framework based on distributed hydrologic modeling

• Proposed a novel dynamic flash flood early warning framework based on a distributed hydrological model. • Identified multi-level warning flow and the percentage of multi-level risk areas. • Coupling disaster risk levels with critical rainfall thresholds enables dynamic early warning for flash floods. Flash flood disaster prevention urgently requires high-precision hydrological models. However, extreme weather increases the uncertainty of flash flood risks, making it difficult for existing hydrological models to accurately simulate the flash flood processes. This study focuses on the Daxi River watershed in Guangdong Province. Based on verifying the applicability of the China Flash Flood Hydrological Modeling System (CNFF), the Manning formula is introduced to invert the calculation of the critical rainfall threshold for flash floods. The flash flood-inducing factors were then qualitatively analyzed using multiple indicators to determine their risk levels, thereby proposing a dynamic early warning framework for flash flood disasters. Results indicate that: 1) the CNFF demonstrated relatively high simulation accuracy, with the average Nash-Sutcliffe Efficiency (NSE) during the calibration and validation periods being 0.79 and 0.89, respectively; 2) dynamic rainfall warning indicators for 1-hour intervals were obtained under different soil moisture conditions. The warning, danger, and extreme danger flow rates were determined to be 176.3 m 3 /s, 308 m 3 /s, and 483.6 m 3 /s, respectively; 3) utilizing flood disaster risk assessment indicators, the risk distribution of flash floods has been evaluated, with the relatively high-risk areas, high-risk areas, and low-risk areas accounting for 31.1 %, 7.26 %, and 6.42 %, respectively; 4) the delay times for issuing warnings in different risk zones were determined, achieving dynamic early warning for flash flood disasters. The above research results will provide theoretical references for improving the flash flood defense methods.

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Publication Details

Journal
Ecological Indicators
Published
2025-03-01
DOI
https://doi.org/10.1016/j.ecolind.2025.113247
Citations
5
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
5.53

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article

A novel dynamic flash flood early warning framework based on distributed hydrologic modeling

Guangpeng Wang, Yiru Chen, Xiaolei Zhang, Nan Zhang et al.
5 citations
Ecological Indicators
Flood Risk Assessment and Management
5.53
article

A novel dynamic flash flood early warning framework based on distributed hydrologic modeling

Guangpeng Wang, Yiru Chen, Xiaolei Zhang, Nan Zhang, Yun Wang, Meihong Ma, Ronghua Liu
article en
5 citations

Abstract

• Proposed a novel dynamic flash flood early warning framework based on a distributed hydrological model. • Identified multi-level warning flow and the percentage of multi-level risk areas. • Coupling disaster risk levels with critical rainfall thresholds enables dynamic early warning for flash floods. Flash flood disaster prevention urgently requires high-precision hydrological models. However, extreme weather increases the uncertainty of flash flood risks, making it difficult for existing hydrological models to accurately simulate the flash flood processes. This study focuses on the Daxi River watershed in Guangdong Province. Based on verifying the applicability of the China Flash Flood Hydrological Modeling System (CNFF), the Manning formula is introduced to invert the calculation of the critical rainfall threshold for flash floods. The flash flood-inducing factors were then qualitatively analyzed using multiple indicators to determine their risk levels, thereby proposing a dynamic early warning framework for flash flood disasters. Results indicate that: 1) the CNFF demonstrated relatively high simulation accuracy, with the average Nash-Sutcliffe Efficiency (NSE) during the calibration and validation periods being 0.79 and 0.89, respectively; 2) dynamic rainfall warning indicators for 1-hour intervals were obtained under different soil moisture conditions. The warning, danger, and extreme danger flow rates were determined to be 176.3 m 3 /s, 308 m 3 /s, and 483.6 m 3 /s, respectively; 3) utilizing flood disaster risk assessment indicators, the risk distribution of flash floods has been evaluated, with the relatively high-risk areas, high-risk areas, and low-risk areas accounting for 31.1 %, 7.26 %, and 6.42 %, respectively; 4) the delay times for issuing warnings in different risk zones were determined, achieving dynamic early warning for flash flood disasters. The above research results will provide theoretical references for improving the flash flood defense methods.

Ecological IndicatorsVol. 172
Tianjin Normal University (CN), Tianjin Academy of Fine Arts (CN), China Institute of Water Resources and Hydropower Research (CN), Ministry of Water Resources of the People's Republic of China (CN)
National Natural Science Foundation of China, China Institute of Water Resources and Hydropower Research, Applied Basic Research Key Project of Yunnan
Climate action
Openalex Percentile: Top 5%
Flood Risk Assessment and Management
5.53
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