Probability Estimation of Shallow Landslide Considering Uncertainty of Rainfall and Soil Parameter
碩士 === 國立嘉義大學 === 土木與水資源工程學系研究所 === 105 === Neglecting the uncertainty of rainfall and soil parameter could misestimate shallow landslide because the rainfall and soil parameter are highly random. In this study, the historical precipitation data of Zhuokou river basin was collected and classified in...
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ndltd-TW-105NCYU57310152019-05-15T23:53:45Z http://ndltd.ncl.edu.tw/handle/8q44p7 Probability Estimation of Shallow Landslide Considering Uncertainty of Rainfall and Soil Parameter 考量降雨及土壤參數不確定性之坡地淺崩塌機率評估 顏嘉宏 碩士 國立嘉義大學 土木與水資源工程學系研究所 105 Neglecting the uncertainty of rainfall and soil parameter could misestimate shallow landslide because the rainfall and soil parameter are highly random. In this study, the historical precipitation data of Zhuokou river basin was collected and classified into the central, advanced, uniform, and delayed patterns using the cluster analysis. The rainfall time series of four rainfall patterns were then generated using a stochastic rainfall series generation model. Based on the rainfall time series and the sampling of soil parameter, the probability estimation of shallow landslide considering the uncertainty of rainfall and soil parameter was conducted by using the rainfall-induced variably saturated infinite slope failure model together with the Monte Carlo simulation method. The simulation results show that both uncertainties of soil parameter and rainfall affect the shallow landslide probability estimation. Only considering the rainfall uncertainty may severely underestimate the shallow landslide probability. Therefore, a reliable estimation of shallow landslide probability needs to simultaneously consider both uncertainties of rainfall and soil parameter. 蔡東霖 學位論文 ; thesis 42 zh-TW |
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碩士 === 國立嘉義大學 === 土木與水資源工程學系研究所 === 105 === Neglecting the uncertainty of rainfall and soil parameter could misestimate shallow landslide because the rainfall and soil parameter are highly random. In this study, the historical precipitation data of Zhuokou river basin was collected and classified into the central, advanced, uniform, and delayed patterns using the cluster analysis. The rainfall time series of four rainfall patterns were then generated using a stochastic rainfall series generation model. Based on the rainfall time series and the sampling of soil parameter, the probability estimation of shallow landslide considering the uncertainty of rainfall and soil parameter was conducted by using the rainfall-induced variably saturated infinite slope failure model together with the Monte Carlo simulation method. The simulation results show that both uncertainties of soil parameter and rainfall affect the shallow landslide probability estimation. Only considering the rainfall uncertainty may severely underestimate the shallow landslide probability. Therefore, a reliable estimation of shallow landslide probability needs to simultaneously consider both uncertainties of rainfall and soil parameter.
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蔡東霖 |
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蔡東霖 顏嘉宏 |
author |
顏嘉宏 |
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顏嘉宏 Probability Estimation of Shallow Landslide Considering Uncertainty of Rainfall and Soil Parameter |
author_sort |
顏嘉宏 |
title |
Probability Estimation of Shallow Landslide Considering Uncertainty of Rainfall and Soil Parameter |
title_short |
Probability Estimation of Shallow Landslide Considering Uncertainty of Rainfall and Soil Parameter |
title_full |
Probability Estimation of Shallow Landslide Considering Uncertainty of Rainfall and Soil Parameter |
title_fullStr |
Probability Estimation of Shallow Landslide Considering Uncertainty of Rainfall and Soil Parameter |
title_full_unstemmed |
Probability Estimation of Shallow Landslide Considering Uncertainty of Rainfall and Soil Parameter |
title_sort |
probability estimation of shallow landslide considering uncertainty of rainfall and soil parameter |
url |
http://ndltd.ncl.edu.tw/handle/8q44p7 |
work_keys_str_mv |
AT yánjiāhóng probabilityestimationofshallowlandslideconsideringuncertaintyofrainfallandsoilparameter AT yánjiāhóng kǎoliàngjiàngyǔjítǔrǎngcānshùbùquèdìngxìngzhīpōdeqiǎnbēngtājīlǜpínggū |
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