Articles | Volume 25, issue 6
https://doi.org/10.5194/hess-25-3595-2021
https://doi.org/10.5194/hess-25-3595-2021
Research article
 | 
24 Jun 2021
Research article |  | 24 Jun 2021

Statistical modelling and climate variability of compound surge and precipitation events in a managed water system: a case study in the Netherlands

Víctor M. Santos, Mercè Casas-Prat, Benjamin Poschlod, Elisa Ragno, Bart van den Hurk, Zengchao Hao, Tímea Kalmár, Lianhua Zhu, and Husain Najafi

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Cited articles

AghaKouchak, A., Chiang, F., Huning, L. S., Love, C. A., Mallakpour, I., Mazdiyasni, O., Moftakhari, H., Papalexiou, S. M., Ragno, E., and Sadegh, M.: Climate Extremes and Compound Hazards in a Warming World, Annu. Rev. Earth Pl. Sc., 48, 519–548, https://doi.org/10.1146/annurev-earth-071719-055228, 2020. a
Anderson, D., Rueda, A., Cagigal, L., Antolinez, J., Mendez, F., and Ruggiero, P.: Time-Varying Emulator for Short and Long-Term Analysis of Coastal Flood Hazard Potential, J. Geophys. Res.-Oceans, 124, 9209–9234, 2019. a
Baldwin, J. W., Dessy, J. B., Vecchi, G. A., and Oppenheimer, M.: Temporally compound heat wave events and global warming: and emerging hazard, Earths Future, 7, 411–427, https://doi.org/10.1029/2018EF000989, 2019. a
Bartoszek, K.: The main characteristics of atmospheric circulation over East-Central Europe from 1871 to 2010, Meteorol. Atmos. Phys., 129, 113–129, 2017. a
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. a, b, c
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Short summary
We present an application of multivariate statistical models to assess compound flooding events in a managed reservoir. Data (from a previous study) were obtained from a physical-based hydrological model driven by a regional climate model large ensemble, providing a time series expanding up to 800 years in length that ensures stable statistics. The length of the data set allows for a sensitivity assessment of the proposed statistical framework to natural climate variability.