台灣地質脆弱加上地形大多以陡峭的山坡為主，河流短且流速急，再因地理位置關係，常受到颱風或梅雨帶來的侵襲，帶來集中性的豪雨，促使集水區區域內災害發生事件之機率不斷提升且日趨嚴重，導致崩塌數量及規模也產生變化。因此針對集水區內因降雨所誘發的崩塌進行研究探討，同時輔以政府每年對集水區域內進行整治工程編列進行後續整治績效評估，以提供相關單位進行區域治理探討等災害預防參考。
本研究以曾文水庫為研究區域，透過歷年衛星影像及文獻資料之蒐集，進行影像判釋分析，以利獲得歷年崩塌地及自然環境資料，同時也蒐集2017年到2019年所發生的豪雨事件資料，進行統整量化分析，並且運用邏輯斯迴歸建立集水區所發生的崩塌潛勢模式，同時，輔以接受者操作特徵曲線(ROC)判斷其準確性，從中探討集水區內致災因子與降雨誘發坡地崩塌間的關係與空間分布情形。此外，為瞭解政府2017年到2019年對集水區區域內所進行的整治工程績效評估，則是先將集水區進行子集水區劃分，接著利用常態化差異植生指標(NDVI)進行植生變遷狀況監測，來獲得長時期有經整治工程治理之下與自然復育下(未整治)之每期影像崩塌地面積，進而計算出整治前後之崩壞比來判斷整治績效。
結果顯示，本研究以高程、坡度、坡向、地質、距水系距離、距斷層距離及雨量作為本次致災因子，並接續進行坡地崩塌模式之降雨誘發坡地崩塌潛勢評估模式建立，其利用邏輯斯迴歸建置後之總體訓練結果皆達到70%以上之正確率及ROC驗證結果有0.8以上，表示本研究之預測結果有有一定的準確性，以及可從中發現本研究三場降雨事件下集水區崩塌空間區位分佈皆在高程345~357m、坡度百分之7~8、距水系距離100~149m、256~331m及地質多是長枝坑層為主。此外，透過2017年~2019年蒐集之整治工程，進行各子集水區崩壞比比較結果，可得已整治區域與未整治區域之崩壞比比較起來各方面地質、地形及植被皆較穩定，加上經有整治工程之集水區，可承受雨量皆有明顯提升，甚至在整治過後皆無發生崩塌。

Taiwan's geological vulnerability, coupled with its predominantly steep terrain characterized by abrupt slopes, short rivers, and swift currents, along with its geographical location, frequently subjects it to the impacts of typhoons or monsoon rains, resulting in concentrated heavy rainfall. This has led to a continuous and increasingly severe rise in the probability of disaster events within the watershed area. Consequently, the occurrence of landslides, both in terms of frequency and magnitude, has undergone variations. Therefore, conducting a study on rainfall-induced landslides within the watershed area, supplemented by the annual allocation of government-driven watershed management projects, is essential for subsequent assessment of the effectiveness of these interventions. This provides pertinent authorities with valuable insights for regional governance discussions and disaster prevention references, making it a necessary endeavor.
This study chosen the Zengwen Reservoir as the research area. Through the collection of historical satellite imagery and literature data, image interpretation analysis is conducted to acquire data on historical landslides and the natural environment. Additionally, data on heavy rainfall events occurring from 2017 to 2019 is gathered for integrated quantitative analysis. The study employs logistic regression to establish a landslide susceptibility model for the watershed. Simultaneously, the study utilizes the Receiver Operating Characteristic (ROC) curve to assess the accuracy of the model, thereby investigating the relationship and spatial distribution between disaster-inducing factors within the watershed and rainfall-triggered slope failures. Furthermore, to understand the performance evaluation of government-led remediation projects within the watershed area from 2017 to 2019, the watershed was subdivided into sub-watersheds. Subsequently, the Normalized Difference Vegetation Index (NDVI) was employed for monitoring vegetation changes, aiming to obtain the area of landslide occurrence in each image before and after prolonged remediation efforts and natural recovery (pre-remediation). This data allowed the calculation of the pre- and post-remediation landslide ratios to assess the effectiveness of the remediation measures.
The results indicate that this study select the elevation, slope, aspect, geology, distance to water system, distance to fault line, and rainfall as the causal factors for the disaster. Subsequently, a rainfall-induced slope landslide susceptibility assessment model was developed using logistic regression. The overall training results after the establishment of the logistic regression model achieved an accuracy of over 70% and the ROC validation results were above 0.8, demonstrating a satisfactory performance. The predictive outcomes of this study exhibit a certain level of accuracy, and it can be inferred that within the context of the three rainfall events studied, the spatial distribution of landslides within the watershed primarily occurs at elevations ranging from 345 to 357 meters, slopes of 7 to 8 percent, distances to water systems between 100 to 149 meters and 256 to 331 meters, with the predominant geological formation being the Changchih-Keng Formation. Furthermore, by examining the results of the landslide ratio comparison among various sub-watersheds based on the collected data from 2017 to 2019 regarding the remediation projects, it can be observed that the areas subjected to remediation exhibit greater stability in terms of geological, topographical, and vegetative factors compared to the untreated regions. Additionally, the watersheds that have undergone remediation have demonstrated an increased capacity to withstand rainfall, with no occurrences of landslides observed after the implementation of the remediation projects.

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Web Rerferences :

Central Geological Survey, Ministry of Economic Affairs (2023)
https://www.moeacgs.gov.tw/

Central Weather Bureau, Ministry of Transportation and Communications (2023)
https://www.cwb.gov.tw/

Esri (2023)
https://www.esri.com/en-us/home

Forestry Bureau, Council of Agriculture, Executive Yuan (2017~2019)
https://www.forest.gov.tw/

Water and Soil Conservation Regulations (2023)
https://law.moj.gov.tw/LawClass/LawAll.aspx?PCode=M0110001

Water Resources Agency, Ministry of Economic Affairs (2023)
https://www.wra.gov.tw/

Wikipedia (2023)
https://www.wikipedia.org/