水資源工程通常依據用水需求及歷史水文進行符合設計標準的規劃與設
計，歷史資料之趨勢與變動量直接影響所需的構造物規模，而用水需求時間序列中出現的資料缺失、錯誤與異常值更會影響分析模式之建立與推估成果，其資料中的異常變動往往來自災害與人為政策等的干擾，若能釐清干擾原因與其可能的影響程度，將有助於改進預估結果。
為瞭解影響售水量之因子與干擾因素，本研究結合時間序列之層級模式與介入分析，推估受到災害等干擾因素影響之售水量，有助瞭解災害事件對生活售水量之量化影響。本研究先對台南市的生活售水量紀錄進行探討，顯示近年來受到節約用水政策、停水等影響，售水量有下降特性，但也在受到淹水、登革熱疫情爆發或其他人為干擾因素時而有所增加。
應用本研究所建置之生活售水量模式擬合歷史售水量時，最大誤差為2.74%，平均誤差小於1%。驗證結果也顯示納入介入分析所得之介入量可以更精確推估未來售水量，有加入介入參數之模式擬合歷史售水量的成果比未加入介入參數之模式為佳，在月售水量誤差上平均可修正約13%，而在年誤差則平均可修正39%。但若多起介入事件同時發生時，會受到介入事件彼此互相影響，影響程度較小的介入事件則不易分析出其精準的介入量。
本研究成果可供檢視節約用水政策下的可能節水量，對災害事件的介入影響可以有更深入的瞭解，可提供未來水資源規劃與歷史需求資料修正之參考。

The planning of water resource projects usually refers to the historical data for model construction. However, the intervention events in time series data such as natural disasters and policies are not often considered in the general model but have a significant influence on the estimation and forecasting result of the model. In order to
understand and forecast the impacts of intervention events, we take domestic water use in Tainan as a study case, exploring the composition of domestic water use and the reason for abnormal data occurred.
In this study, the cascade model combined with intervention analysis is used to estimate the amount of water affected by intervention events. The result indicates that domestic water use declined from 2007 by the influence of water-saving policy and water outage, but also increase when the people suffering from flood events, dengue fever occurred and other man-made intervention events. The intervention analysis can improve the model fitting error by 13% in monthly data, and 39% in yearly data compare to the model without intervention analysis.
The intervention analysis can not only improve the forecasting result but also examine the actual water saving of the water policies, providing a reference to the water sector for the future design of the water supply system.

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