Inundación compuesta en el estuario de Santoña: umbrales bivariados y su aplicación en alertas tempranas
Enviado: 12-12-2024
|Aceptado: 30-04-2025
|Publicado: 30-04-2025
Derechos de autor 2025 Ingeniería del Agua

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
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Palabras clave:
Inundación compuesta, Análisis bivariado, Cópulas, Descarga fluvial, Marea meteorológica, Alerta temprana
Agencias de apoyo:
Gobierno de Cantabria a través del Programa Fénix
“FEDER Una manera de hacer Europa”
"info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-096449-B-I00/ES/SERVICIOS CLIMATICOS PARA APLICACIONES COSTERAS SOBRE EVENTOS EXTREMOS DE DINAMICAS SUPERFICIALES MARINAS (EXCEED)/"
Resumen:
Este estudio implementa un marco metodológico bivariado basado en cópulas para caracterizar el potencial de inundación compuesta en el estuario de Santoña (Cantabria, España), evaluar su desempeño frente a metodologías tradicionales y explorar su aplicabilidad en sistemas de alerta temprana. Al analizar la interacción entre la descarga fluvial y la marea meteorológica, se aborda la complejidad de definir escenarios de peligro en un contexto multivariado. A diferencia de los enfoques univariados, que generan un único valor de referencia, el análisis bivariado identifica combinaciones críticas de forzamientos que, aunque no extremas individualmente, pueden generar impactos significativos al actuar conjuntamente. Con base en estos resultados, se propone un esquema escalonado de niveles de alerta (monitoreo activo, alerta temprana, alerta moderada y alerta extrema), vinculado a umbrales multivariados específicos que relacionan probabilidad de ocurrencia y severidad, optimizando la planificación y la respuesta frente a eventos compuestos.
Citas:
Avand, M., Moradi, H., Lasboyee, M.R. 2021. Using machine learning models, remote sensing, and GIS to investigate the effects of changing climates and land uses on flood probability. Journal of Hydrology, 595: 125663. https://doi.org/10.1016/j.jhydrol.2020.125663
Bevacqua, E., Maraun, D., Vousdoukas, M.I., Voukouvalas, E., Vrac, M., Mentaschi, L., Widmann, M. 2019. Higher probability of compound flooding from precipitation and storm surge in Europe under anthropogenic climate change. Science Advances, 5(9): eaaw5531. https://doi.org/10.1126/sciadv.aaw5531
Box, G.E.P., Jenkins, G.M., Reinsel, G.C., Ljung, G.M. 2016. Time series analysis: forecasting and control. Fifth edition. Wiley series in probability and statistics. Hoboken, New Jersey: John Wiley & Sons, Inc.
Brunner, M.I., Seibert, J., Favre, A. 2016. Bivariate return periods and their importance for flood peak and volume estimation. WIREs Water, 3(6): 819–833. https://doi.org/10.1002/wat2.1173
Cao, A., Nakamura, S., Otsuyama, K., Namba, M., Yoshimura, K. 2024. Current status and challenges in operating flood early warning systems at the local level in Japan. International Journal of Disaster Risk Reduction, 112: 104802. https://doi.org/10.1016/j.ijdrr.2024.104802
Carpenter, B., Gelman, A., Hoffman, M.D., Lee, D., Goodrich, B., Betancourt, M., Brubaker, M., Guo, J., Li, P., Riddell, A. 2017. Stan : A Probabilistic Programming Language. Journal of Statistical Software, 76(1). https://doi.org/10.18637/jss.v076.i01
Corbella, S., Stretch, D.D. 2012. Multivariate return periods of sea storms for coastal erosion risk assessment. Natural Hazards and Earth System Sciences, 12(8): 2699–2708. https://doi.org/10.5194/nhess-12-2699-2012
Couasnon, A., Eilander, D., Muis, S., Veldkamp, T.I.E., Haigh, I.D., Wahl, T., Winsemius, H.C., Ward, P.J. 2020. Measuring compound flood potential from river discharge and storm surge extremes at the global scale. Natural Hazards and Earth System Sciences, 20(2): 489–504. https://doi.org/10.5194/nhess-20-489-2020
Czado, C., Nagler, T. 2022. Vine Copula Based Modeling. Annual Review of Statistics and Its Application, 9(1): 453–477. https://doi.org/10.1146/annurev-statistics-040220-101153
De Luca, G., Nai Ruscone, M., Amati, V. 2023. The use of conditional copula for studying the influence of economic sectors. Expert Systems with Applications, 231: 120582. https://doi.org/10.1016/j.eswa.2023.120582
De Waal, D.J., Van Gelder, P.H.A.J.M. 2005. Modelling of extreme wave heights and periods through copulas. Extremes, 8(4): 345–356. https://doi.org/10.1007/s10687-006-0006-y
Didier, D., Baudry, J., Bernatchez, P., Dumont, D., Sadegh, M., Bismuth, E., Bandet, M., Dugas, S., Sévigny, C. 2019. Multihazard simulation for coastal flood mapping: Bathtub versus numerical modelling in an open estuary, Eastern Canada. Journal of Flood Risk Management, 12(S1): e12505. https://doi.org/10.1111/jfr3.12505
Galván, C., Puente, A., Juanes, J.A. 2021. Nested Socio-Ecological Maps as a Spatial Planning Instrument for Estuary Conservation and Ecosystem-Based Management. Frontiers in Marine Science, 8: 730762. https://doi.org/10.3389/fmars.2021.730762
Hao, Z., Singh, V.P. 2020. Compound Events under Global Warming: A Dependence Perspective. Journal of Hydrologic Engineering, 25(9): 03120001. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001991
Heinrich, P., Hagemann, S., Weisse, R., Schrum, C., Daewel, U., Gaslikova, L. 2023. Compound flood events: analysing the joint occurrence of extreme river discharge events and storm surges in northern and central Europe. Natural Hazards and Earth System Sciences, 23(5): 1967–1985. https://doi.org/10.5194/nhess-23-1967-2023
Hua, L., Joe, H. 2011. Tail order and intermediate tail dependence of multivariate copulas. Journal of Multivariate Analysis, 102(10): 1454–1471. https://doi.org/10.1016/j.jmva.2011.05.011
IHCantabria. Instituto de Hidráulica Ambiental de la Universidad de Cantabria. 2018. Informe técnico: Subida del nivel del mar en futuros escenarios de cambio climático en estuarios cantábricos.
Jalili Pirani, F., Najafi, M.R. 2023. Nonstationary frequency analysis of compound flooding in Canada’s coastal zones. Coastal Engineering, 182: 104292. https://doi.org/10.1016/j.coastaleng.2023.104292
Jonkman, S.N., Curran, A., Bouwer, L.M. 2024. Floods have become less deadly: an analysis of global flood fatalities 1975–2022. Natural Hazards, 120(7): 6327–6342. https://doi.org/10.1007/s11069-024-06444-0
Láng-Ritter, J., Berenguer, M., Dottori, F., Kalas, M., Sempere-Torres, D. 2022. Compound flood impact forecasting: integrating fluvial and flash flood impact assessments into a unified system. Hydrology and Earth System Sciences, 26(3): 689–709. https://doi.org/10.5194/hess-26-689-2022
Latif, S., Simonovic, S.P. 2022. Parametric Vine Copula Framework in the Trivariate Probability Analysis of Compound Flooding Events. Water, 14(14): 2214. https://doi.org/10.3390/w14142214
Lucey, J.T.D., Gallien, T.W. 2022. Characterizing multivariate coastal flooding events in a semi-arid region: the implications of copula choice, sampling, and infrastructure. Natural Hazards and Earth System Sciences, 22(6): 2145–2167. https://doi.org/10.5194/nhess-22-2145-2022
Lyddon, C., Chien, N., Vasilopoulos, G., Ridgill, M., Moradian, S., Olbert, A., Coulthard, T., Barkwith, A., Robins, P. 2024. Thresholds for estuarine compound flooding using a combined hydrodynamic–statistical modelling approach. Natural Hazards and Earth System Sciences, 24(3): 973–997. https://doi.org/10.5194/nhess-24-973-2024
Maduwantha, P., Wahl, T., Santamaria-Aguilar, S., Jane, R., Booth, J.F., Kim, H., Villarini, G. 2024. A multivariate statistical framework for mixed storm types in compound flood analysis. Natural Hazards and Earth System Sciences, 24(11): 4091–4107. https://doi.org/10.5194/nhess-24-4091-2024
Mazas, F., Hamm, L. 2017. An event-based approach for extreme joint probabilities of waves and sea levels. Coastal Engineering, 122: 44–59. https://doi.org/10.1016/j.coastaleng.2017.02.003
Ming, X., Liang, Q., Dawson, R., Xia, X., Hou, J. 2022. A quantitative multi-hazard risk assessment framework for compound flooding considering hazard inter-dependencies and interactions. Journal of Hydrology, 607: 127477. https://doi.org/10.1016/j.jhydrol.2022.127477
Moftakhari, H.R., Salvadori, G., AghaKouchak, A., Sanders, B.F., Matthew, R.A. 2017. Compounding effects of sea level rise and fluvial flooding. Proceedings of the National Academy of Sciences, 114(37): 9785–9790. https://doi.org/10.1073/pnas.1620325114
Nagler, T., Schepsmeier, U., Stoeber, J., Brechmann, E. C., Graeler, B., Erhardt, T., ..., Killiches, M. 2024. Package ‘VineCopula,’. https://cran.r-project.org/web/packages/VineCopula/VineCopula.pdf
Nelsen, R.B. 2006. An Introduction to Copulas. Second Edition. Springer Series in Statistics. New York, NY: Springer Science+Business Media, Inc. https://doi.org/10.1007/0-387-28678-0
Núñez, P., García, A., Mazarrasa, I., Juanes, J.A., Abascal, A.J., Méndez, F., Castanedo, S., Medina, R. 2019. A methodology to assess the probability of marine litter accumulation in estuaries. Marine Pollution Bulletin, 144: 309–324. https://doi.org/10.1016/j.marpolbul.2019.04.077
Papadimitriou, A.G., Metallinos, A.S., Chondros, M.K., Tsoukala, V.K. 2024. A Novel Input Schematization Method for Coastal Flooding Early Warning Systems Incorporating Climate Change Impacts. Climate, 12(11): 178. https://doi.org/10.3390/cli12110178
Paprotny, D., Vousdoukas, M.I., Morales-Nápoles, O., Jonkman, S.N., Feyen, L. 2018. Compound flood potential in EuropeHydrometeorology/Mathematical applications, 19 April 2018. https://doi.org/10.5194/hess-2018-132
Sadegh, M., Moftakhari, H., Gupta, H.V., Ragno, E., Mazdiyasni, O., Sanders, B., Matthew, R., AghaKouchak, A. 2018. Multihazard Scenarios for Analysis of Compound Extreme Events. Geophysical Research Letters, 45(11): 5470–5480. https://doi.org/10.1029/2018GL077317
Salvadori, G., Durante, F., De Michele, C. 2013. Multivariate return period calculation via survival functions. Water Resources Research, 49(4): 2308–2311. https://doi.org/10.1002/wrcr.20204
Salvadori, G., Durante, F., De Michele, C., Bernardi, M., Petrella, L. 2016. A multivariate copula-based framework for dealing with hazard scenarios and failure probabilities. Water Resources Research, 52(5): 3701–3721. https://doi.org/10.1002/2015WR017225
Santos, V.M., Wahl, T., Jane, R., Misra, S.K., White, K.D. 2021. Assessing compound flooding potential with multivariate statistical models in a complex estuarine system under data constraints. Journal of Flood Risk Management, 14(4): e12749. https://doi.org/10.1111/jfr3.12749
Serinaldi, F. 2015. Dismissing return periods! Stochastic Environmental Research and Risk Assessment, 29(4): 1179–1189. https://doi.org/10.1007/s00477-014-0916-1
Tootoonchi, F., Sadegh, M., Haerter, J.O., Räty, O., Grabs, T., Teutschbein, C. 2022. Copulas for hydroclimatic analysis: A practiceoriented overview. WIREs Water, 9(2): e1579. https://doi.org/10.1002/wat2.1579
Wahl, T. 2017. Compound flooding: examples, methods, and challenges 2017: EP11A-1550.
Wahl, T., Jain, S., Bender, J., Meyers, S.D., Luther, M.E. 2015. Increasing risk of compound flooding from storm surge and rainfall for major US cities. Nature Climate Change, 5(12): 1093–1097. https://doi.org/10.1038/nclimate2736
Wu, W., Westra, S., Leonard, M. 2021. Estimating the probability of compound floods in estuarine regions. Hydrology and Earth System Sciences, 25(5): 2821–2841. https://doi.org/10.5194/hess-25-2821-2021
Xu, H., Xu, K., Lian, J., Ma, C. 2019. Compound effects of rainfall and storm tides on coastal flooding risk. Stochastic Environmental Research and Risk Assessment, 33(7): 1249–1261. https://doi.org/10.1007/s00477-019-01695-x
Yang, X., Wang, J., Weng, S. 2020. Joint Probability Study of Destructive Factors Related to the “Triad” Phenomenon during Typhoon Events in the Coastal Regions: Taking Jiangsu Province as an Example. Journal of Hydrologic Engineering, 25(11): 05020038. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002007
Zhu, Z., Zhang, W., Zhu, W. 2024. Compound Impact of Storm Surge and Flood Characteristics in Coastal Area Based on Copula. Water, 16(2): 270. https://doi.org/10.3390/w16020270
Zscheischler, J., Martius, O., Westra, S., Bevacqua, E., Raymond, C., Horton, R.M., Van Den Hurk, B., AghaKouchak, A., Jézéquel, A., Mahecha, M.D., Maraun, D., Ramos, A.M., Ridder, N.N., Thiery, W., Vignotto, E. 2020. A typology of compound weather and climate events. Nature Reviews Earth & Environment, 1(7): 333–347. https://doi.org/10.1038/s43017-020-0060-z




