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<p>Accurate flash flood warning is crucial for hazard risk management. Rainfall threshold is one of the most effective approaches for flash flood early warning. However, the capability of different rainfall-threshold methods has been insufficiently&#xa0;evaluated and validated, and the influence of data limitations on the model performance still needs to be explored. In this work, we comprehensively evaluate and compare three rainfall-threshold methods (empirical, hydrological, and probabilistic) based on soil moisture conditions for flash flood warnings in two small mountainous catchments with different data features. Results show that all three methods obtain good accuracy (Hit Rate (HR) &gt; 0.80, False Alarm Rate (FAR) &lt; 0.20) in both catchments, indicating that rainfall threshold is an efficient warning approach for flash flood management. Especially, the hydrological method shows the best predictive performance, with the highest Critical Success Index (CSI) (0.61 and 0.41, respectively in the two study catchments) and the lowest FAR (0.07 and 0.12), suggesting it is the most appropriate method for catchments where the hydrological model can be properly calibrated. Empirical and probabilistic methods are not far behind, showing comparable performance (CSI = 0.53 and 0.53, respectively for the Qingxi River (QXH) catchment). Catchment data availability, which reflects the representativeness of the relevant flash flood process conditions, greatly impacts the forecasting and model application. The results of this work improve our understanding of the applicability and reliability of these methods under various conditions, and aid in selecting or establishing a robust rainfall-threshold&#xa0;method for flash flood warning under complex environments.</p>

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Evaluation of rainfall‑threshold methods for flash flood warnings based on soil moisture conditions

  • 期刊论文

  • 发表日期：

    2025年5月16日

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  • Yuting Zhao,
  • Xuemei Wu,
  • Li Guo,
  • Guanghua Qin,
  • Xiaodong Li,
  • Hongxia Li

摘要

Accurate flash flood warning is crucial for hazard risk management. Rainfall threshold is one of the most effective approaches for flash flood early warning. However, the capability of different rainfall-threshold methods has been insufficiently evaluated and validated, and the influence of data limitations on the model performance still needs to be explored. In this work, we comprehensively evaluate and compare three rainfall-threshold methods (empirical, hydrological, and probabilistic) based on soil moisture conditions for flash flood warnings in two small mountainous catchments with different data features. Results show that all three methods obtain good accuracy (Hit Rate (HR) > 0.80, False Alarm Rate (FAR) < 0.20) in both catchments, indicating that rainfall threshold is an efficient warning approach for flash flood management. Especially, the hydrological method shows the best predictive performance, with the highest Critical Success Index (CSI) (0.61 and 0.41, respectively in the two study catchments) and the lowest FAR (0.07 and 0.12), suggesting it is the most appropriate method for catchments where the hydrological model can be properly calibrated. Empirical and probabilistic methods are not far behind, showing comparable performance (CSI = 0.53 and 0.53, respectively for the Qingxi River (QXH) catchment). Catchment data availability, which reflects the representativeness of the relevant flash flood process conditions, greatly impacts the forecasting and model application. The results of this work improve our understanding of the applicability and reliability of these methods under various conditions, and aid in selecting or establishing a robust rainfall-threshold method for flash flood warning under complex environments.