Critical rainfall for flash flood warning based on rainfall uncertainty
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Abstract:
Mountain flood disasters generally refer to floods, landslides, and debris flows hazards caused by rainfall and snowmelt. They are characterized by their suddenness and devastating impact. Critical rainfall is a commonly used indicator for mountain flood disaster early warning, indicating that when the rainfall reaches a certain threshold within a certain period, the flow at the outlet of the watershed will exceed the warning flow, resulting in disastrous flooding. These disasters have caused severe social problems. It poses a significant threat to people's lives and property. So optimizing mountain flood early warning and addressing the shortcomings in flood control and disaster reduction are crucial steps in social development. Critical rainfall, as the most commonly used indicator for mountain flood early warning, has been studied by numerous scholars both domestically and internationally. However, there is limited research on the comprehensive consideration of the influence of random rainfall patterns and spatial distribution under different antecedent rainfall conditions on the critical rainfall for mountain flood early warning.To address these issues, the Pengfang small watershed is focused on as the research area and random rainfall patterns are generated, based on control conditions such as probability distribution functions. Based on the historical rainfall data from the Pengfang small watershed, the optimal distribution functions for the five sets of random rainfall patterns were as follows: Normal, Normal, Exponential, Normal, Exponential and Gamma distributions. The control conditions for these distribution functions were (0.50, 0.32), (0.50, 0.42), (0.50, 0.52), (0.17, 0.32), and (0.83, 0.32) respectively. The influence of different sets of random rainfall patterns is explored, considering different antecedent rainfall conditions, on the 6-hour critical rainfall for mountain flood early warning. Furthermore, the impact of rainfall spatial distribution on the 6-hour critical rainfall is also analyzed.The results are as follows: (1) Under rainfall patterns with a later peak position and larger peak values, critical rainfall exhibits significant fluctuations, leading to diverse disaster scenarios with higher uncertainty. (2) The influence of rainfall patterns on critical rainfall is smaller compared to the influence of antecedent rainfall. When the soil is relatively dry in the antecedent period and the coefficient of the peak position of the rainfall pattern is small, the critical rainfall value is relatively large. The change in the peak position has a smaller effect on the critical rainfall when the soil is moist in the antecedent period. While the peak value ratio of the rainfall pattern is larger, the critical rainfall value is relatively small, indicating a higher likelihood of causing mountain flood disasters. (3) In terms of rainfall spatial distribution, the rainfall is concentrated downstream, and the critical rainfall value is the smallest, indicating a higher likelihood of reaching the warning flow. However, the impact of rainfall spatial distribution on the critical rainfall is less significant compared to the impact of antecedent precipitation. Furthermore, as antecedent precipitation increases, the impact of rainfall spatial distribution on the critical rainfall gradually diminishes.The findings have significant implications for improving the accuracy of mountain flood disaster early warning and enhancing the early warning system. These research results can provide a scientific basis for the optimization and improvement of the mountain flood early warning system, aiming to better protect people's lives and properties and effectively respond to the challenges posed by mountain flood disasters.
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