Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Probabilistic hazard analysis of rainfall-induced landslides at a specific slope considering rainfall uncertainty and soil spatial variability
https://orcid.org/0000-0003-1796-3578
https://orcid.org/0000-0003-4635-7059
Abstract A key index for assessing landslide risk quantitatively is annual slope failure probability, PFA, induced by rainfalls at a specific slope. Although PFA is expected to be significantly influenced by both spatial variability of soil properties and rainfall uncertainty, previous studies seldom estimate PFA with simultaneous consideration of both soil spatial variability and rainfall uncertainty. Most previous studies focused on the effect of soil spatial variability and ignored rainfall uncertainty, and the estimated slope failure probability is not associated with a reference time period (e.g., a year for PFA). This study aims to assess PFA considering both soil spatial variability and rainfall uncertainty by developing a fully Monte Carlo simulation (MCS)-based method. To bypass the high-dimensional integration in estimation of PFA and high computational costs of MCS, a semi-analytical method is further developed for enhancing computational efficiency in estimating a small failure probability. Results show that the semi-analytical and fully MCS-based methods produce consistent PFA. Using the proposed semi-analytical method, a small number (e.g., 30) of random samples is sufficient for estimating a small failure probability (e.g., 10−4) accurately. When the variability of soil properties is negligible, PFA is dominated by rainfall uncertainty and converges to a constant failure probability.
Probabilistic hazard analysis of rainfall-induced landslides at a specific slope considering rainfall uncertainty and soil spatial variability
https://orcid.org/0000-0003-1796-3578
https://orcid.org/0000-0003-4635-7059
Abstract A key index for assessing landslide risk quantitatively is annual slope failure probability, PFA, induced by rainfalls at a specific slope. Although PFA is expected to be significantly influenced by both spatial variability of soil properties and rainfall uncertainty, previous studies seldom estimate PFA with simultaneous consideration of both soil spatial variability and rainfall uncertainty. Most previous studies focused on the effect of soil spatial variability and ignored rainfall uncertainty, and the estimated slope failure probability is not associated with a reference time period (e.g., a year for PFA). This study aims to assess PFA considering both soil spatial variability and rainfall uncertainty by developing a fully Monte Carlo simulation (MCS)-based method. To bypass the high-dimensional integration in estimation of PFA and high computational costs of MCS, a semi-analytical method is further developed for enhancing computational efficiency in estimating a small failure probability. Results show that the semi-analytical and fully MCS-based methods produce consistent PFA. Using the proposed semi-analytical method, a small number (e.g., 30) of random samples is sufficient for estimating a small failure probability (e.g., 10−4) accurately. When the variability of soil properties is negligible, PFA is dominated by rainfall uncertainty and converges to a constant failure probability.
Probabilistic hazard analysis of rainfall-induced landslides at a specific slope considering rainfall uncertainty and soil spatial variability
https://orcid.org/0000-0003-1796-3578
https://orcid.org/0000-0003-4635-7059
Abstract A key index for assessing landslide risk quantitatively is annual slope failure probability, PFA, induced by rainfalls at a specific slope. Although PFA is expected to be significantly influenced by both spatial variability of soil properties and rainfall uncertainty, previous studies seldom estimate PFA with simultaneous consideration of both soil spatial variability and rainfall uncertainty. Most previous studies focused on the effect of soil spatial variability and ignored rainfall uncertainty, and the estimated slope failure probability is not associated with a reference time period (e.g., a year for PFA). This study aims to assess PFA considering both soil spatial variability and rainfall uncertainty by developing a fully Monte Carlo simulation (MCS)-based method. To bypass the high-dimensional integration in estimation of PFA and high computational costs of MCS, a semi-analytical method is further developed for enhancing computational efficiency in estimating a small failure probability. Results show that the semi-analytical and fully MCS-based methods produce consistent PFA. Using the proposed semi-analytical method, a small number (e.g., 30) of random samples is sufficient for estimating a small failure probability (e.g., 10−4) accurately. When the variability of soil properties is negligible, PFA is dominated by rainfall uncertainty and converges to a constant failure probability.
Probabilistic hazard analysis of rainfall-induced landslides at a specific slope considering rainfall uncertainty and soil spatial variability
29.07.2023
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Uncertainty of rainfall-induced landslides considering spatial variability of parameters
| British Library Online Contents | 2017
Uncertainty of rainfall-induced landslides considering spatial variability of parameters
| Online Contents | 2017
Uncertainty of rainfall-induced landslides considering spatial variability of parameters
| British Library Online Contents | 2017