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首页> 外文期刊>Stochastic environmental research and risk assessment >Estimation of rainfall threshold for flood warning for small urban watersheds based on the 1D-2D drainage model simulation
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Estimation of rainfall threshold for flood warning for small urban watersheds based on the 1D-2D drainage model simulation

机译:Estimation of rainfall threshold for flood warning for small urban watersheds based on the 1D-2D drainage model simulation

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摘要

Flood warning systems can provide an effective and low-cost solution to protect urban residents especially in developing countries suffering from severe flood damages caused by weak capacity of flood defense structures. Rainfall Threshold for Flood Warning (RTFW) is an essential key of accurate flood warning system. This study proposed an easy-to-use mathematical equation for RTFW for small urban watersheds based on computer simulations. First, a coupled 1D-2D dual-drainage model was used to simulate the flooded area in nine watersheds of Seoul, Korea corresponding to 540 scenarios of various synthetic rainfall events and watershed imperviousness. Then, the results of the 101 simulations that caused the critical flooded depth (0.25 m-0.35 m) were used to develop the equation that relates the value of RTFW to the rainfall event temporal variability (represented as coefficient of variation or CV) and the watershed imperviousness (represented as NRCS Curve Number or CN). The results suggest that (1) RTFW exponentially decreases as the rainfall CV increases; (2) RTFW linearly decreases as the watershed CN increases; and that (3) RTFW is dominated by CV when the rainfall has low temporal variability (e.g., CV 0.2) while RTFW is dominated by CN when the rainfall has high temporal variability (e.g., CV 0.4). For validation, the proposed equation was applied for the flood warning system with two storm events occurred in 2010 and 2011 over 239 watersheds in Seoul. The system showed the hit, false and missed alarm rates at 69 (48), 31 (52) and 6.7 (4.5), respectively for the 2010 (2011) event.

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