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Rainfall-triggered slope instabilities under a changing climate: comparative study using historical and projected precipitation extremes
This study aims to quantitatively assess the impact of extreme precipitation events under current and future climate scenarios on landslides. Rainfall-triggered landslides are analyzed primarily using extreme precipitation estimates, derived using the so-called stationary assumption (i.e., statistics of extreme events will not vary significantly over a long period of time). However, extreme precipitation patterns have shown to vary substantially due to climate change, leading to unprecedented changes in the statistics of extremes. In this study, a nonstationary approach, applied to climate model simulations, is adopted to project the upper bound of future precipitation extremes. Future precipitation estimates are obtained from the coupled model intercomparison project phase 5 (CMIP5) simulations. Baseline (historical) and projected (future) precipitation extremes are obtained for a study area near Seattle, Washington. The precipitation patterns are integrated into a series of fully coupled two-dimensional stress – unsaturated flow finite element simulations. The responses of the baseline and projected models at a 7 day rainfall duration obtained for a 50 year recurrence interval are compared in terms of the local strength reduction factor, displacements, matric suctions, and suction stresses. The results indicate that the usage of historical rainfall data can lead to underestimations in the hydromechanical behavior of natural slopes where locally increased transient seepage rates occur from the upper bound of future extreme precipitation estimates.
Rainfall-triggered slope instabilities under a changing climate: comparative study using historical and projected precipitation extremes
This study aims to quantitatively assess the impact of extreme precipitation events under current and future climate scenarios on landslides. Rainfall-triggered landslides are analyzed primarily using extreme precipitation estimates, derived using the so-called stationary assumption (i.e., statistics of extreme events will not vary significantly over a long period of time). However, extreme precipitation patterns have shown to vary substantially due to climate change, leading to unprecedented changes in the statistics of extremes. In this study, a nonstationary approach, applied to climate model simulations, is adopted to project the upper bound of future precipitation extremes. Future precipitation estimates are obtained from the coupled model intercomparison project phase 5 (CMIP5) simulations. Baseline (historical) and projected (future) precipitation extremes are obtained for a study area near Seattle, Washington. The precipitation patterns are integrated into a series of fully coupled two-dimensional stress – unsaturated flow finite element simulations. The responses of the baseline and projected models at a 7 day rainfall duration obtained for a 50 year recurrence interval are compared in terms of the local strength reduction factor, displacements, matric suctions, and suction stresses. The results indicate that the usage of historical rainfall data can lead to underestimations in the hydromechanical behavior of natural slopes where locally increased transient seepage rates occur from the upper bound of future extreme precipitation estimates.
Rainfall-triggered slope instabilities under a changing climate: comparative study using historical and projected precipitation extremes
Vahedifard, Farshid (author) / Robinson, Joe D / AghaKouchak, Amir
2017
Article (Journal)
English
sol insaturé , landslides , hydromechanical coupling , Precipitation , Rain and rainfall , Climate change , précipitation extrême , modélisation numérique , Finite element analysis , climate change , transient seepage , Simulation , glissements de terrain , Research , Landslides , Extreme weather , numerical modeling , Rain , Soil research , Shear strength of soils , United States , couplage hydromécanique , infiltration transitoire , unsaturated soil , extreme precipitation , changement climatique , non stationnaire , nonstationary
| British Library Online Contents | 2017
Rainfall Triggered Slope Instability Analysis with Changing Climate
| Springer Verlag | 2022