本研究評估了臺灣高雄市的經濟洪水損失，利用高解析度淹水圖增強洪水風險管理和城市韌性。其目標是量化多個部門的損失，並為緩解措施提供可行見解。研究方法將 QGIS 處理的高解析度淹水圖與住宅、工業、農業和公共資產的空間資料相結合。分析了洪水場景—八個重現期 (T)，有/無風暴潮 (SS)，十二種降水量 (P)，以及三種持續時間 (6、12、24 小時)—使用深度-損失曲線 (DDC) 在 Excel 中估計損失。
結果顯示，獨立房屋的損失是公寓的兩倍以上，製造業主導工業損失，養殖業推動農業損失。短暫而強烈的 6 小時風暴造成的損失遠高於 24 小時事件，而風暴潮加劇了住宅和車輛的損失。預期年度損失 (EAD) 凸顯了持續的經濟負擔，敦促採取主動防禦措施。
研究得出結論，將高解析度淹水圖與經濟模型相結合，為洪水評估提供了一個可複製的框架，這對高雄市易受颱風影響的環境至關重要。它為有針對性的緩解措施提供了部門特定的資料，但局限性包括簡化的模型可能低估損失以及未考慮長期社會經濟影響。未來的研究應通過額外的洪水動態和更廣泛的影響來精煉模型。

This study evaluates economic flood losses in Kaohsiung, Taiwan, leveraging high-resolution inundation maps to enhance flood risk management and urban resilience. Its objectives are to quantify damages across multiple sectors and provide actionable insights for mitigation. The methodology integrates QGIS-processed high-resolution inundation maps with spatial data on residential, industrial, agricultural, and public assets. Flood scenarios—eight return periods (T), with/without storm surge (SS), twelve precipitation amounts (P), and three durations (6, 12, 24 hours)—were analyzed using depth-damage curves (DDC) to estimate losses in Excel.
Results show individual houses incur over twice the losses of apartments, manufacturing dominates industrial damage, and aquaculture drives agricultural losses. Short, intense 6-hour storms cause significantly higher damages than 24-hour events, while SS amplifies residential and vehicle losses. Expected annual damage (EAD) underscores a persistent economic burden, urging proactive defenses.
The study concludes that combining high-resolution inundation maps with economic models offers a replicable framework for flood assessment, critical for Kaohsiung’s typhoon-prone context. It provides sector-specific data for targeted mitigation, though limitations include potential underestimation from simplified models and omission of long-term socio-economic impacts. Future research should refine models with additional flood dynamics and broader impacts.

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