Statistical modeling and dependence analysis for tide level via multivariate extreme value distribution method

This paper presents a statistical modeling approach to explore the dependence of extreme values in multi-site tidal water levels (TL) using hourly data from six tidal stations in the Kansai region, Japan. The proposed method utilizes a multi-site conditional extreme value model (CEVM) and a peak over threshold (POT) model with yearly order grouping (YOG) to handle extreme value dependence and marginal modeling of tidal CEVM, respectively. The results demonstrate the effectiveness of the proposed approach in analyzing extreme value dependence among multiple sites, with the YOG method yielding favorable results for extreme value dependence analysis. The extreme dependence effect of TL and the probability of exceedance at multiple sites under extreme conditions are investigated. The paper concludes that the extreme dependence effect should be captured through a multivariate CEVM and provides a more accurate basis for engineering construction and disaster prevention. The novelty of this work lies in its statistical modeling approach that enables accurate multi-site extreme value analysis and provides a more comprehensive understanding of the extreme value dependence of the TLs, which has significant implications for disaster management and prevention.