4.6 Article

Geometric and Material Variability of the Probability of Landward Slope Failure for Homogeneous River Levees

Journal

SUSTAINABILITY
Volume 14, Issue 5, Pages -

Publisher

MDPI
DOI: 10.3390/su14052833

Keywords

flood risk management; risk-based design; variability analysis; levee failure; slope stability

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Holistic flood risk management aims to minimize flood risk in an entire river basin by considering flooding probability and its consequences in planning flood risk management measures. This study quantifies the variability of landside slope failure probability on homogeneous river levees using Monte Carlo simulation for the first time, providing insights for adjusting local failure probability to limit flood risk. The methodology presented may be expanded to include structured cross-sections or additional failure mechanisms in the future for a more comprehensive understanding of landward slope failure.
Holistic flood risk management (FRM) aims at minimizing the flood risk (FR) for an entire river basin. To this end, the probability of flooding and its consequences must also be taken into account in the planning of flood risk management measures. If the FR is to be limited by the flooding probability value (e.g., by changing the structural reliability), knowledge of the variability of the limit state is required. As an example, this study quantifies for the first time the variability of the probability of a landside slope failure on homogeneous river levees, using the Monte Carlo simulation. In the slip circle method developed by Krey that is used for this purpose, four geometric and six material input parameters are included as being uncertain, of which four emerge in the result as being relevant influencing variables of the failure probability. These analyses extend our understanding of landward slope failure by the variability of the limit state; the results allow a targeted adjustment of the local failure probability to limit the flood risk. In the future, the methodology presented is to be supplemented by the integration of parameter dependencies and, once in use, expanded to include structured cross-sections or additional failure mechanisms.

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