在全球氣候變遷的影響下，極端降雨及河川水位的發生日益頻繁，颱風與短延時強降雨常導致河川溪水暴漲，進而引發複合淹水災害。因此，如何建立具備統計可靠性與實務應用價值的淹水潛勢圖資，已成為當前重要的研究課題。
本研究以筏子溪為示範區域，選用三變量Copula聯結函數建立總降雨量(R)、降雨總延時(D)及河川最大水位(W)之間的相依結構，並利用蒙地卡羅取樣法產製大量邊界條件組合，作為TELEMAC-2D模式的輸入條件，進行複合淹水模擬與風險量化。同時，為探討未來氣候變遷對於淹水風險的影響，選用台灣氣候變遷推估資訊與調適知識平台(TCCIP)提供之五種全球環流模式(GCM)於世紀末的網格化日雨量資料，推估三變量於未來的變化趨勢，並建構各GCM模式所對應的聯合機率模型。另於模式模擬中加入非工程滯洪措施，包括低衝擊開發設施(LID)與在地滯洪措施，評估逕流分擔策略對於減災效益的貢獻。
研究結果顯示，Clayton Copula能夠良好描述降雨、延時與水位三個變量間的相依關係，將聯合機率模型所推估的聯合重現期與實際發生淹水的重現期進行比較後，顯示同時超過特定降雨、延時、水位門檻值的複合淹水事件重現期(AND重現期)會低估實際淹水風險，單一變量超越門檻值事件的重現期(OR重現期)則較為保守估計。複合淹水模擬結果則顯示，五種GCM模式中，平均淹水深度與淹水面積在各個模式中皆呈現增加趨勢，MIROC6的期望變化量最大，平均淹水深度增加9.77%，淹水面積則增加14.12%；僅MPI-ESM1-2-LR小幅減少，平均淹水深度的期望變化量減少3.62%；淹水面積平均減少5.78%。非工程滯洪設施之減災效益方面，整體可減少1%至3%的淹水面積，具備一定的減災潛力。
綜上所述，本研究建立一套融合統計建模、氣候變遷情境推估與模式模擬的複合淹水風險評估流程，成果可作為未來都市區域防洪構造物規劃與防災策略擬定之參考依據。

Under global climate change, extreme rainfall and river stage events have become more frequent, increasing the risk of compound flooding. Therefore, developing flood inundation mapping that are both statistically reliable and practically applicable has become an important research challenge. This study focuses on the Fazi River Basin and employs a trivariate Copula model to capture dependencies among rainfall(R), duration(D), and river stage(W). Monte Carlo sampling was used to generate boundary conditions for TELEMAC-2D simulations to quantify flood risk. To assess future flood risk under climate change, gridded daily rainfall data from five GCMs provided by TCCIP were used to rebuild joint probability models for each scenario. In addition, runoff distribution strategies, including Low Impact Development and flood retention measures, were integrated into the model to evaluate the effectiveness of runoff management strategies. The results show that the Clayton Copula best describes the relationship between the rainfall, duration, and river stage data. By comparing with the realistic flood risk, the AND-type joint return period tends to underestimate flood risk, while OR-type return period is more conservative. Simulation results show that, both average flood depth and flooded area tend to increase in the future. MIROC6 shows the highest increase, expected change in average flood depth increases 9.77% and flooded area increases 14.12%. Only MPI-ESM1-2-LR shows decrease, with flood depth down 3.62% and area down 5.78%. Meanwhile, applying runoff distribution strategies reduces flooded area by 1% to 3%, demonstrating their potential for flood reduction. In summary, this study establishes a compound flood risk assessment framework that combines statistical modeling, climate change scenarios, and flood simulations. The results can serve as a reference for urban flood protection structure design and disaster mitigation strategy development in the future.

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