Non-stationary evolutionary characteristic analysis of coastal extreme water levels under sea level rise

Abstract

[Objective] The rising global sea level has undermined the stationary assumption in coastal water level observations, [Results] ing in significant alterations in the return period and return level of extreme water levels in coastal regions. Hence, it is imperative to assess the impact of sea level rise on extreme water levels under a non-stationary framework, offering scientific insights for coastal protection engineering design in these areas. [Methods] Tidal observation from the tide gauges in Wenzhou and Taizhou in Zhejiang Province was analyzed. Non-stationary assumption was validated via trend analysis. Non-stationary Generalized Extreme Value(GEV) and Generalized Pareto Distribution(GPD) models were constructed with time-dependent parameters, and Bayesian Markov Chain Monte Carlo(MCMC) sampling was applied for posterior parameter estimation. Model performance was evaluated using Akaike(AIC) and Bayesian(BIC) information criteria, while risk dynamics were quantified through effective return levels(ERL) and expected waiting time(EWT). [Results] Distinct trends were detected in all three stations, making the adoption of non-stationary extreme value theory models more appropriate. The GPD model outperformed GEV. Under non-stationary, the return period of the 100-year extreme water level is projected to reduce dramatically. [Conclusion] The GPD model is more suitable for non-stationary risk prediction due to its sensitivity to high-frequency extremes. The estimation result of extreme water levels are impacted by the selection of model thresholds. With the rise in sea level, the frequency and intensity of flood disaster risks in coastal areas will significantly increase, necessitating dynamic updates of coastal defense standards. The findings advances the method ological application of non-stationary extreme value theory in climate change adaptation and serves as a reference for coastal defense engineering design.

Keywords

extreme value theory / return period / non-stationary / return level / extreme sea level / climate change / flood