Nonstationary Extreme Value Analysis of Nearshore Sea-State Parameters under the Effects of Climate Change: Application to the Greek Coastal Zone and Port Structures

Abstract

In the present work, a methodological framework, based on nonstationary extreme value analysis of nearshore sea-state parameters, is proposed for the identification of climate change impacts on coastal zone and port defense structures. The applications refer to the estimation of coastal hazards on characteristic Mediterranean microtidal littoral zones and the calculation of failure probabilities of typical rubble mound breakwaters in Greek ports. The proposed methodology hinges on the extraction of extreme wave characteristics and sea levels due to storm events affecting the coast, a nonstationary extreme value analysis of sea-state parameters and coastal responses using moving time windows, a fitting of parametric trends to nonstationary parameter estimates of the extreme value models, and an assessment of nonstationary failure probabilities on engineered port protection. The analysis includes estimation of extreme total water level (TWL) on several Greek coasts to approximate the projected coastal flooding hazard under climate change conditions in the 21st century. The TWL calculation considers the wave characteristics, sea level height due to storm surges, mean sea level (MSL) rise, and astronomical tidal ranges of the study areas. Moreover, the failure probabilities of a typical coastal defense structure are assessed for several failure mechanisms, considering variations in MSL, extreme wave climates, and storm surges in the vicinity of ports, within the framework of reliability analysis based on the nonstationary generalized extreme value (GEV) distribution. The methodology supports the investigation of future safety levels and possible periods of increased vulnerability of the studied structure to different ultimate limit states under extreme marine weather conditions associated with climate change, aiming at the development of appropriate upgrading solutions. The analysis suggests that the assumption of stationarity might underestimate the total failure probability of coastal structures under future extreme marine conditions.

Intensity-Duration-Frequency Curves at Ungauged Sites in a Changing Climate for Sustainable Stormwater Networks

“…In the present work the nonstationary model of Equation ( 2) has been fitted using a 30-year moving time window shifted by one year each time [59,60]. Therefore, nonstationary GEV (or Gumbel) parameters for the annual maximum rainfall can be assessed for each one of these windows.…”

“…Linear and nonlinear parametric trends are then fitted to the extracted GEV (or Gumbel) parameter estimates. The Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) [60], as well as tests for statistical significance of the coefficients of the fitted trends, are utilised here to select parametric trends representing the GEV parameters' variability in the best possible way. Nonlinear trends include polynomials of order lower than or equal to five.…”

“…The ordinary least squares method has been used to fit linear and polynomial trends to all GEV/Gumbel parameters, to examine their variability in the studied period. The statistical significance of all trends has been judged using the t-test [60]. An analysis of variance (ANOVA), as well as the AIC and the BIC (see Section 2.1) of all statistically significant (at a 5% significance level) fitted models were then computed to identify the simplest trend in each parameter.…”

CoastFLOOD: A High-Resolution Model for the Simulation of Coastal Inundation Due to Storm Surges

“…These conditions should last for at least a few hours and up to 3 days, given that the storm-induced sea level does not abruptly change in time but follows the slow smooth variation of the tidal constituent. Furthermore, this approach is ideal for particular scenarios of long-term MSLR or Total Water Level (TWL) on the coastline [104,105].…”

“…The model has been applied in operational forecast mode for short-term marine weather predictions and has been thoroughly validated, during the past 15 years, in the Mediterranean region against field data from in situ tide-gauge observations of storminduced episodic SSH due to severe weather conditions or the derived Sea Level Anomaly (SLA; SLA = SSH−MSL) in inter-annual tidal cycles [2,17,20,21]. Its climatic mode counterpart, MeCSS, has also been evaluated for long-term historical simulations of mean and extreme storm surge patterns in the Mediterranean basin during (>30-year) reference periods [9,18,[22][23][24]104,105]. Furthermore, the HiReSS model is the official numerical tool of the Operational Forecast Platform (OFP) Wave4Us, recently incorporated into the METEO.GR node managed by the National Observatory of Athens [109][110][111].…”