Modeling dependence and coincidence of storm surges and high tide: methodology, discussion and recommendations based on a simplified case study in Le Havre (France)

Abstract

Abstract. Coastal facilities such as nuclear power plants (NPPs) have to be designed to withstand extreme weather conditions and must, in particular, be protected against coastal floods because it is the most important source of coastal lowland inundations. Indeed, considering the combination of tide and extreme storm surges (SSs) is a key issue in the evaluation of the risk associated with coastal flooding hazard. Most existing studies are generally based on the assumption that high tides and extreme SSs are independent. While there are several approaches to analyze and characterize coastal flooding hazard with either extreme SSs or sea levels, only few studies propose and compare several approaches combining the tide density with the SS variable. Thus this study aims to develop a method for modeling dependence and coincidence of SSs and high tide. In this work, we have used existing methods for tide and SS combination and tried to improve the results by proposing a new alternative approach while showing the limitations and advantages of each method. Indeed, in order to estimate extreme sea levels, the classic joint probability method (JPM) is used by making use of a convolution between tide and the skew storm surge (SSS). Another statistical indirect analysis using the maximum instantaneous storm surge (MSS) is proposed in this paper as an alternative to the first method with the SSS variable. A direct frequency analysis using the extreme total sea level is also used as a reference method. The question we are trying to answer in this paper is then the coincidence and dependency essential for a combined tide and SS hazard analysis. The results brought to light a bias in the MSS-based procedure compared to the direct statistics on sea levels, and this bias is more important for high return periods. It was also concluded that an appropriate coincidence probability concept, considering the dependence structure between SSs, is needed for a better assessment of the risk using the MSS. The city of Le Havre in France was used as a case study. Overall, the example has shown that the return level (RL) estimates using the MSS variable are quite different from those obtained with the method using the SSSs, with acceptable uncertainty. Furthermore, the shape parameter is negative from all the methods with a much heavier tail when the SSS and the extreme sea levels (ESLs) are used as variables of interest.

Preface: Advances in extreme value analysis and application to natural hazards

“…Such analysis may include a wide range of approaches, including, most notably, frequentist and Bayesian statistical models derived from historical event data in order to describe the behavior of extreme values. The estimation of the frequency of occurrence of extreme events using probability functions has been a common issue for many decades (e.g., Dalrymple, 1960;Cunnane, 1987;Haigh et al, 2016;Wahl et al, 2017;Hamdi et al, 2019;Parey et al, 2019).…”