A methodology for deriving extreme nearshore sea conditions for structural design and flood risk analysis |
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| Institution: | 1. Environmental Hydraulics Institute “IH Cantabria”, Universidad de Cantabria, C/Isabel Torres 15, Parque Científico y Tecnológico de Cantabria, 39011 Santander, Spain;2. HR Wallingford Ltd., Howbery Park, Wallingford, Oxfordshire OX10 8BA, UK;3. IFREMER, Technopolis, 40-155 Rue Jean-Jacques Rousseau, 92138 Issy-les-Moulineaux, France;1. Faculty of Civil Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia;2. Coastal and Offshore Engineering Institute (COEI), Universiti Teknologi Malaysia Kuala Lumpur, Jalan Semarak, 54100 Kuala Lumpur, Malaysia;3. School of Marine Science and Technology (Faculty of Science and Technology), University of Plymouth, Drake Circus, PL4 8AA Plymouth, United Kingdom;4. Centro de Investigación Científica y Educación Superior de Ensenada (CICESE), Carretera Ensenada-Tijuana No. 3918, Zona Playitas, C.P. 22860 Ensenada, B.C. México;1. Middlesex University, Flood Hazard Research Centre, The Burroughs, London NW4 4BT, United Kingdom;2. Infram, PO Box 16, 8316 ZG Marknesse, The Netherlands;3. University of Bologna, Dept. of Civil, Environmental and Materials Eng., Viale Risorgimento 2, 40136 Bologna, Italy;4. University of Plymouth, Coastal Engineering Research Group, Drake Circus, Plymouth PL4 8AA, United Kingdom;5. Bulgarian Academy of Sciences, Institute of Oceanology, 1, 15 Noemvri Str., 1040 Sofia, Bulgaria;6. Centre d''Etudes Techniques Maritimes et Fluviales, 2, Boulevard Gambetta, BP 60039, 60321 Compiegne, Cedex, France;7. Katholieke Universiteit Leuven, Depart. Burgerlijke Bouwkunde, Laboratorium voor Hydraulica, Oude Markt 13, 3000 Leuven, Belgium;8. Institute of Meteorology and Water Management, Ul. Podlesna 61, 01-673 Warszawa, Poland;9. Hamburg Port Authority, Neuer Wandrahm 4, 20457 Hamburg, Germany;10. University of Cantabria, Facultad de Ciencias Económicas y Empresariales, Avda. de las Castros, s/n 39005 Santander, Spain;11. Royal Netherlands Institute for Sea Research, NIOZ Yerseke, Department of Spatial Ecology, P.O. Box 140, 4400 AC Yerseke, The Netherlands |
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| Abstract: | Extreme sea conditions in the nearshore zone are required for coastal flood risk analysis and structural design. Many multivariate extreme value methods that have been applied in the past have been limited by assumptions relating to the dependence structure in the extremes. A conditional extremes statistical model overcomes a number of these previous limitations. To apply the method in practice, a Monte Carlo sampling procedure is required whereby large samples of synthetically generated events are simulated. The use of Monte Carlo approaches, in combination with computationally intensive physical process models, can raise significant practical challenges in terms of computation. To overcome these challenges there has been extensive research into the use of meta-models. Meta-models are approximations of computationally intensive physical process models (simulators). They are derived by fitting functions to the outputs from simulators. Due to their simplified representation they are computationally more efficient than the simulators they approximate.Here, a methodology for deriving a large Monte Carlo sample of extreme nearshore sea states is described. The methodology comprises the generation of a large sample of offshore sea conditions using the conditional extremes model. A meta-model of the wave transformation process is then constructed. A clustering algorithm is used to aid the development of the meta-model. The large sample of offshore data is then transformed through to the nearshore using the meta-model. The resulting nearshore sea states can be used for the probabilistic design of structures or flood risk analysis. The application of the methodology to a case study site on the North Coast of Spain is described. |
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