本研究以高雄市典寶溪流域為研究區域，探討防洪抽水機組於降雨事件中隨機失效對淹水殘餘風險之影響。典寶溪流域下游及中下游地區地勢低平，且鄰近都市計畫區與工商業發展區，於強降雨事件下易受內水排除不及與下游邊界條件影響而產生淹水。雖然抽水機可協助降低區域積淹水風險，但抽水機於洪峰期間可能長時間高負荷運轉，若發生設備失效，將可能改變流域之排水能力與淹水空間分布，形成防洪工程正常設計外仍存在之殘餘風險。
本研究首先利用Delft3D FM模式模擬10年及25年重現期降雨事件下，流域內7組防洪抽水機之128種全時失效情境，並萃取淹水面積與最大水體積作為主要淹水指標。接著，依據各抽水機於正常運轉情境下之流量歷線，透過非齊次卜瓦松過程(Non-Homogeneous Poisson Process, NHPP)建立動態失效機率，結合蒙地卡羅方法產製5000場抽水機隨機失效事件。為降低大量數值模擬所需之計算成本，本研究進一步應用排容原理(Principle of Inclusion–Exclusion)分析，將128種全時失效情境之淹水指標分解為基準項、主效應及各階交互效應係數，建立可快速推估不同失效時間與失效組合下淹水影響之快速估算模型。
為進一步探討抽水機失效對流域內各區域之影響，將模擬結果之各項淹水指標依照流域中之位置分別進行分析，分別為沿海(Area A)、下游(Area B)、中游(Area C)及上游(Area D)。研究結果顯示，典寶溪流域之淹水主要集中於中下游及下游沿岸低窪地區，且25年重現期降雨事件下淹水範圍與最大水體積均較10年重現期明顯增加。由128場全時失效情境可知，最嚴重之抽水機失效情境對下游及中游區域影響最為明顯；其中25年重現期下，Area B之最大淹水面積較正常運轉情境增加25,288 m²，最大水體積增加34,908.01 m³，Area C之最大淹水面積增加61,202 m²，最大水體積增加52,299.29 m³，顯示中下游區域為抽水機組失效下較敏感之空間位置。進一步納入非齊次卜瓦松過程與蒙地卡羅抽樣後，由於多數抽水機於降雨事件中仍維持正常運轉，且失效時間多發生於事件後段，因此全流域期望值與正常運轉情境差異有限；然而分區結果仍顯示殘餘風險具有明顯空間差異。以25年重現期為例，全流域淹水面積與最大水體積分別僅變化-182 m²及-629.88 m³，但Area B仍增加652 m²及759.55 m³，Area C則增加6,429 m²及5,788.26 m³；相對地，Area A幾乎無變化，Area D則分別減少3,200 m²及1,487.30 m³。此結果表示，抽水機失效並非使全流域淹水量均勻增加，而是使淹水風險由影響較小或略為減少之沿海與上游區域，轉而集中於下游及中游區域，尤其25年重現期下Area C為殘餘風險增加最明顯之區域。研究成果可作為防洪抽水機組維護管理、區域防災規劃及殘餘風險評估之參考。

Flood-control pumping stations are essential for reducing inundation in low-lying urban basins; however, prolonged high-load operation during extreme rainfall may lead to random equipment failures. Conventional flood-risk assessments often assume either normal pump operation or predefined full-failure scenarios, which may overlook the timing and probability of pump failures and fail to capture residual flood risk. This study proposes a probabilistic framework to evaluate residual flood risk caused by random failures of flood-control pumps in the Dianbao River Basin, Kaohsiung City, Taiwan. Delft3D FM was used to simulate inundation under different pump-failure scenarios, while a non-homogeneous Poisson process (NHPP) was applied to estimate time-dependent failure probabilities based on pump discharge hydrographs. Monte Carlo simulation was then used to generate stochastic failure events, and a rapid estimation model based on the principle of inclusion–exclusion was developed to efficiently estimate inundation indicators. The results show that although basin-wide expected inundation differs only slightly from normal operation, residual flood risk becomes concentrated in specific subregions, especially under higher rainfall return periods. The proposed framework can support pump maintenance prioritization and risk-informed flood management.

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