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Nonstationary joint probability analysis of extreme marine variables to assess design water levels at the shoreline in a changing climate

Author

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  • Panagiota Galiatsatou

    (Aristotle University Of Thessaloniki)

  • Christos Makris

    (Aristotle University Of Thessaloniki)

  • Panayotis Prinos

    (Aristotle University Of Thessaloniki)

  • Dimitrios Kokkinos

    (Aristotle University Of Thessaloniki)

Abstract

In the present study, a recently developed novel approach (Bender et al. in J Hydrol 514:123–130, 2014) has been further extended to investigate the changes in the joint probabilities of extreme offshore and nearshore marine variables with time and to assess design the total water level (TWL) at the shoreline under the effects of climate change. The nonstationary generalised extreme value (GEV) distribution has been utilised to model the marginal distribution functions of marine variables (wave characteristics and sea levels), within a 40-year moving window. All parameters of the GEV were tested for statistically significant linear and polynomial trends over time, and best-fitted trends have been detected. Different copula functions were fitted at the 40-year moving windows, to model the dependence structure of extreme offshore significant wave heights and peak spectral periods, and of wave-induced sea levels on the shoreline and nearshore sea levels due to storm surges. The most appropriate bivariate models were then selected. Statistically significant polynomial trends were detected in the dependence parameters of the selected copulas, and time-dependent most likely bivariate events were extracted to be used in the estimation of the TWL at the shoreline. The methods of the present work were implemented in three selected Greek coastal areas in the Aegean Sea. The analysis revealed different variations in the most likely estimates of the offshore wave characteristics and nearshore storm surges in the three study areas, as well as in the time-dependent estimates of TWL at the shoreline. The approach combines nonstationarity and bivariate analysis, blends coastal and offshore marine features and finally provides non-trivial alterations in the response of coastal sea level dynamics to climate change signals, compared to former work on the subject. The methodology produces reasonable estimates of design quantities for coastal structures and boundary conditions for the assessment of flood hazard and risk in coastal areas.

Suggested Citation

  • Panagiota Galiatsatou & Christos Makris & Panayotis Prinos & Dimitrios Kokkinos, 2019. "Nonstationary joint probability analysis of extreme marine variables to assess design water levels at the shoreline in a changing climate," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 98(3), pages 1051-1089, September.
    • Handle: RePEc:spr:nathaz:v:98:y:2019:i:3:d:10.1007_s11069-019-03645-w
    DOI: 10.1007/s11069-019-03645-w
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    References listed on IDEAS

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    Cited by:

    1. Ivan D. Haigh & Thomas Wahl, 2019. "Advances in extreme value analysis and application to natural hazards," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 98(3), pages 819-822, September.
    2. Goyal, Manish Kumar & Gupta, Anil Kumar & Jha, Srinidhi & Rakkasagi, Shivukumar & Jain, Vijay, 2022. "Climate change impact on precipitation extremes over Indian cities: Non-stationary analysis," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    3. Déborah Idier & Jérémy Rohmer & Rodrigo Pedreros & Sylvestre Roy & Jérome Lambert & Jessie Louisor & Gonéri Cozannet & Erwan Cornec, 2020. "Coastal flood: a composite method for past events characterisation providing insights in past, present and future hazards—joining historical, statistical and modelling approaches," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 101(2), pages 465-501, March.

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