Influence of Physiographical Conditions on the Debris-Flow Rainfall-Based Warning Index

• Main Authors: Chih-Yu Chang, 張智瑜
• Other Authors: Chyan-Deng Jan
• Format: Others
• Language: zh-TW
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/86773384594270630160

碩士 === 國立成功大學 === 水利及海洋工程學系碩博士班 === 93 === 　Occurrence of debris flow depends on the hydrologic and physiographical conditions of a watershed. The rainfall conditions have been used to judge debris flow occurrence probability, while the physiographical conditions were applied to identify debris-flow- prone stream. In this study, the product of the rainfall intensity and the effective accumulative rainfall is defined as a debris-flow rainfall triggering index (RTI), and the static physiographical factor (Average slope of hillsides)、dynamic physiographical factors (River density and Rate of landslide) and geology engineering factors (Structure of rock stratification、Soil depth and Rock engineering character) are used to build a physiographical synthetic index (GI). At further stage, the product of rainfall trigger index (RTI) and physiographical synthetic index (GI) is defined as a rainfall-physiographical warning index that is used to evaluate debris-flow occurrence (GRTI). 　The study selects Nantou County, central Taiwan as a test site. A new debris-flow warning model is developed in which a diagram is set up with the -data on the ordinate and the order number of gullies on the abscissa in order to determine debris-flow occurrence probability. A method is proposed to calculate the rainfall-physiographical critical warning values for debris-flow occurrence, based on 144 -values of debris-flow event in Nantou County (from 2000 to 2002). The four rainfall-physiographical critical warning values divide the diagram of debris-flow occurrence probability into five parts：extremely low occurrence probability、low occurrence probability、middle occurrence probability、high occurrence probability and extremely high occurrence probability. The proposed model was applied at the Aiyuzi Stream, Nantou County, central Taiwan to evaluate the temporal variations of debris-flow occurrence probabilities caused by two rainfall events. The results show that the proposed model could effectively evaluate the temporal variations of debris-flow occurrence probability during a rainfall event. 　Additionally, using the relationship between debris-flow rainfall triggering index and the physiographical synthetic index, the critical rainfall condition for debris-flow warning for the areas lacking records of historical debris-flow occurrence can be evaluated. The proposed method was applied at Sungho, Taichung County, central Taiwan to evaluate the temporal variations of debris-flow occurrence probabilities caused by Typhoon Mindulle in 2004. The results show that the proposed method could effectively evaluate the temporal variations of debris-flow occurrence probability during the typhoon rain storm.