Time Dependent Reliability Assessment of Seawalls Subjected to Stochastic Waves and Sea Level Rise

Abstract

Sea walls play a major role in protecting the coastal regions from the raging waves and floods that can commonly occur due to storms and hurricanes. The rising sea levels and the increased number of storm events demand to re-examine the performance of the sea walls during their lifetime under future scenarios. The uncertainty is pervasive in this process stemming from stochastic nature and time variability of coastal forcing, as well as the various uncertain future scenarios of extreme climate events and sea-level rise (SLR). The objective of this research is to conduct an improved reliability-based assessment of coastal sea walls with the risk of overtopping as its primary failure mode. In our reliability analysis, we consider the uncertainty due to the stochastic nature of waves acting on the structure as well as the sea-level rise. The risk of overtopping failure is evaluated while incorporating the joint probabilistic description of the seawater level, significant wave height, and wave period under future hydraulic conditions. USACE (United States Army Corps of Engineers) SLR scenarios and USGS (United States Geological Survey) wave projections are used to account for the future hydraulic conditions. The uncertainty in the time-evolution of future sea level is quantified and systematically incorporated by constructing a stochastic model based on the inverse Gaussian process using the data from the USACE SLR projection scenarios. A time-dependent reliability-based framework is formulated to propagate different sources of uncertainty into the quantification of the probability of failure of sea walls. Specifically, we used the Galveston sea wall, which is a reinforced concrete curved seawall, as the case study. We explored the sensitivity of the probability of overtopping to different sources of uncertainty. It is identified that wave height plays a crucial role in causing overtopping failure than all the other parameters. The outcome of this research will lead to knowledge and improved modeling framework that helps policymakers and infrastructure operators to characterize the risk of failure and resilience of coastal defense structures under various uncertain future scenarios and identify the adaptation or mitigation strategies that result in maximum resilience gain in the system.