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Development of real-time shallow landslide warning system
|Authors: ||Jui-Yi Ho|
|Contributors: ||NTOU:Department of Harbor and River Engineering|
shallow landslide;modified version of TOPMODEL;soil depth estimation;grey rainfall forecasting model
|Issue Date: ||2011-06-30T08:03:20Z
|Abstract: ||臺灣地區地形陡峻、降雨強度集中，往往產生淺層地滑或土石流，進而造成人員傷亡與鉅額財產損失。隨著數值高程資料精度的增加，使得工程師能依照集水區地文特性，進而建構淺層地滑分析模式，藉以預測淺層地滑發生之時間與位置。本研究利用修正地形指數模式模擬降雨期間集水區表層土壤飽和水位變化，而後將集水區中各格點之表層土壤飽和水位配合淺層地滑模式，計算次集水區之平均安全係數與不穩定格點百分比，以評估淺層地滑發生的可能性。研究中並考量集水區中地文與水文因子之不確定性，利用第一階不確定性分析理論與風險分析理論，以計算淺層地滑發生機率。 本研究蒐集2010年梅姬颱風與2000年象神颱風期間，宜蘭縣與新北市曾發生淺層地滑資料之地文與水文紀錄資料。研究中利用數值高程模式推求修正地形指數模式與邊坡穩定分析所需之地文因子，並分別藉由四種不同土壤厚度推求方法，以估計研究區域中土壤厚度的空間分佈。研究結果顯示，淺層地滑發生機率與集水區不穩定格點百分比之時間變化與降雨趨勢大致相符，而平均安全係數則與降雨趨勢成反比之關係。分析過程中並且發現，當集水區之平均安全係數小於1或不穩定格點超過50%時，將會產生淺層地滑。研究中並發展灰色降雨預測模式，以結合淺層地滑即時預警模式，期能減少人員傷亡與財產損失。|
Shallow landslides usually occur in Taiwan to result in casualties and property losses due to steep topography and concentrated rainfall intensity. By using high resolution digital elevation data, current engineers are able to develop analytical model for shallow landslide prediction only based on watershed geomorphologic characteristics. In this study, variation of the saturated water table on hillslope was simulated by using a modified version of TOPMODEL, and then the temporal water level at each grid was used to estimate the average value of the safety factors and the percentage of unstable grids in a subwatershed for shallow landslide prediction. In order to consider the uncertainty of geomorphologic and hydrological factors in the watersheds, a first-order uncertainty analysis and a risk analysis were also employed to calculate the probability of shallow landslide occurrence. Geomorphologic and hydrological records from landslide-prone areas in Yilan County during 2010 Megi Typhoon and in New Taipei City during 2000 Xangsane Typhoon were collected. Digital elevation model was used to calculate the geomorphologic factors required in performing the modified version of TOPMODEL and in estimating the instability of the slopes, in which four different ways were also applied to determine the spatial distribution of soil depth. Results show that the temporal variation of the probability for shallow landslide occurrence and the percentage of unstable grids in the study watersheds basically followed the variation of rainfall hyetographs, and the average value of safety factor shows an inverse relationship with the variation of rainfall hyetographs. The results also reveal that shallow landslide might occur if the safety factor is less than 1 or more than 50% of the grids show unstable in the subwatershed. Furthermore, a grey rainfall forecasting model was also developed to connect with the real-time shallow landslide warning system to decrease the magnitude of the loss of lives and properties.
|Appears in Collections:||[河海工程學系] 博碩士論文|
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