Articles | Volume 30, issue 8
https://doi.org/10.5194/hess-30-2301-2026
https://doi.org/10.5194/hess-30-2301-2026
Research article
 | 
22 Apr 2026
Research article |  | 22 Apr 2026

Transformed-stationary EVA 2.0: a generalized framework for non-stationary multivariate extremes analysis

Mohammad Hadi Bahmanpour, Alois Tilloy, Michalis Vousdoukas, Ivan Federico, Giovanni Coppini, Luc Feyen, and Lorenzo Mentaschi

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Cited articles

Acero, F. J., Parey, S., Hoang, T. T. H., Dacunha-Castelle, D., García, J. A., and Gallego, M. C.: Non-stationary future return levels for extreme rainfall over Extremadura (southwestern Iberian Peninsula), Hydrol. Sci. J., 62, 1394–1411, https://doi.org/10.1080/02626667.2017.1328559, 2017. 
Bevacqua, E., Maraun, D., Hobæk Haff, I., Widmann, M., and Vrac, M.: Multivariate statistical modelling of compound events via pair-copula constructions: analysis of floods in Ravenna (Italy), Hydrol. Earth Syst. Sci., 21, 2701–2723, https://doi.org/10.5194/hess-21-2701-2017, 2017. 
Bevacqua, E., Maraun, D., Vousdoukas, M. I., Voukouvalas, E., Vrac, M., Mentaschi, L., and Widmann, M.: Higher probability of compound flooding from precipitation and storm surge in Europe under anthropogenic climate change, Sci. Adv., 5, eaaw5531, https://doi.org/10.1126/sciadv.aaw5531, 2019. 
Bender, J., Wahl, T., and Jensen, J.: Multivariate design in the presence of non-stationarity, J. Hydrol., 514, 123–130, https://doi.org/10.1016/j.jhydrol.2014.04.017, 2014. 
Burek, P. A., van der Knijff, J., and De Roo, A.: LISFLOOD, distributed water balance and flood simulation model: revised user manual 2013, Publications Office of the European Union, https://doi.org/10.2788/24719, 2013. 
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Short summary
As natural hazards evolve, understanding how extreme events interact over time is crucial. While single extremes have been widely studied, joint extremes remain challenging to analyze. We present a framework that combines advanced statistical modeling with copula theory to capture changing dependencies. Applying it to historical data reveals dynamic patterns in extreme events. To support broader use, we provide an open-source tool for improved hazard assessment.
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