E3S Web Conf.
Volume 7, 20163rd European Conference on Flood Risk Management (FLOODrisk 2016)
|Number of page(s)||12|
|Published online||20 October 2016|
- Cabanes C., Cazenave A. and Le Provost C. (2001). Sea level rise during past 40 years determined from satellite and in situ observations. Science, 294, 840- 842. [CrossRef]
- Marcos M. and Tsimplis M.N. (2008). Coastal sea level trends in Southern Europe. Geophysical Journal International, 175(1), 70–82. [CrossRef]
- WASA- Group. (1998). Changing waves and storms in the Northeast Atlantic? Bulletin of the American Meteorological Society, 79, 741–760. [CrossRef]
- Weisse, R. von Storch, H. and Feser, F. (2005). Northeast Atlantic and North Sea storminess as simulated by a regional climate model. Journal of Climate, 18, 465–479. [CrossRef]
- Wang X. and Swail V. (2006). Climate change signal and uncertainty in projections of ocean wave heights. Climate Dynamics, 26, 109–126. [CrossRef]
- Debernard J. and Roed L. (2008). Future wind, wave and storm surge climate in the Northern Seas: a revisit. Tellus, 60, 427–438. [CrossRef]
- Woth, K., Weisse, R. and Storch, H. (2006). Climate change and North Sea storm surge extremes: an ensemble study of storm surge extremes expected in a changed climate projected by four different regional climate models. Ocean Dynamics, 56(1), 3–15. [CrossRef]
- De Winter R.C., Sterl A., de Vries J.W., Weber S.L. and Ruessink G. (2012). The effect of climate change on extreme waves in front of the Dutch coast. Ocean Dynamics, 62(8), 1139–1152. [CrossRef]
- Weisse R., von Storch H., Niemeyer H.D. and Knaack H. (2012). Changing North Sea storm surge climate: An increasing hazard? Ocean and Coastal Management, 68, 58–68. [CrossRef]
- Μéndez F.J., Menéndez Μ., Luceño Α. and Losada Ι.J. (2006). Estimation of the long-term variability of extreme significant wave height using a timedependent Peak Over Threshold (POT) model. Journal of Geophysical Research, 111(7), C07024. [CrossRef]
- Lionello P., Cogo S., Galati M.B. and Sanna A. (2008). The Mediterranean surface wave climate inferred from future scenario simulations. Global and Planetary Change, 63, 152–162. [CrossRef]
- Casas-Prat M. and Sierra J.P. (2011). Future scenario simulations of wave climate in the NW Mediterranean Sea. Journal of Coastal Research, SI 64, 200–204.
- Gaertner M.A., Jacob D., Gil V., Dominguez M., Padorno E., Sanchez E. and Castro M. (2007). Tropical cyclones over the Mediterranean Sea in climate change simulations. Geophysical Research Letters, 34(14), L14711. [CrossRef]
- Martucci G., Carniel S., Chiggiato J., Sclavo M., Lionello P. and Galati M. B. (2010). Statistical trend analysis and extreme distribution of significant wave height from 1958 to 1999–an application to the Italian Seas. Ocean Science, 6(2), 525–538. [CrossRef]
- Galiatsatou P. and Prinos P. (2014). Analysing the effects of climate change on wave height extremes in the Greek Seas, Proceedings of the 11th International Conference on Hydroscience & Engineering (ICHE 2014), Hamburg - Lehfeldt & Kopmann (eds) - © 2014 Bundesanstalt für Wasserbau ISBN 978-3- 939230-32-8, 773–781.
- Galiatsatou P. and Prinos P. (2015). Estimating the effects of climate change on storm surge extremes in the Greek Seas, 36th IAHR World Congress, 28 June - 3 July, The Hague, The Netherlands
- Sánchez-Arcilla A., Gomez-Aguar J., Egozcue J. J., Ortego M. I., Galiatsatou P. and Prinos P. (2008). Extremes from scarce data. The role of Bayesian and scaling techniques in reducing uncertainty. Journal of Hydraulic Research, 46(2), 224–234. [CrossRef]
- van Gelder P.H.A.J.M. and Mai C. (2008). Distribution functions of extreme sea waves and river discharges. Journal of Hydraulic Research, 46(2), 280–291. [CrossRef]
- Bulteau T., Lecacheux S., Lerma A. N. and Paris F. (2013). Spatial extreme value analysis of significant wave heights along the French coast. In International short conference on advances in extreme value analysis and application to natural hazards: EVAN 2013.
- Coles S. and Tawn J. (2005). Bayesian modelling extreme surges on the UK east coast. Philosophical Transactions of the Royal Society of London (A: Mathematical, Physical and Engineering Sciences), 363, 1387–1406. [CrossRef]
- van Gelder P.H.A.J.M. (1999). Risk-based design of civil structures. PhD-Thesis, University of Technology, Delft, The Netherlands.
- Galiatsatou P. and Prinos P. (2008). Non-stationary point process models for extreme storm surges, Flood Risk Management Research into Practice, Oxford, 1045–1054.
- Bardet L., Duluc C. M., Rebour V. and L’Her J. (2011). Regional frequency analysis of extreme storm surges along the French coast. Natural Hazards and Earth System Sciences, 11(6), 1627–1639. [CrossRef]
- Galiatsatou P. and Prinos P. (2005). Analysis of dependence in a bivariate process of extreme waves and surges, Proceedings of the 1st International Conference on Coastal Zone Management and Engineering in the Middle East, Dubai, 221–225
- Morton I. D. and Bowers J. (1996). Extreme value analysis in a multivariate offshore environment. Applied Ocean Research, 8, 303–317. [CrossRef]
- De Haan L. and De Ronde J. (1998). Sea and wind: multivariate extremes at work. Extremes, 1, 7–45. [CrossRef]
- Ferreira J.A. and Guedes Soares C. (2002). Modelling bivariate distributions of significant wave height and mean period. Applied Ocean Research, 24, 31–45. [CrossRef]
- Repko A., Van Gelder P.H.A.J.M., Voortman H.G. and Vrijling J.K. (2004). Bivariate description of offshore wave conditions with physics-based extreme value statistics, Applied Ocean Research, 26, 162–170. [CrossRef]
- Yeh S.P., Ou S.P., Doong D.J., Kao C.C. and Hsieh D.W. (2006). Joint probability analysis of waves and water level during typhoons. In Proceedings of the Third Chinese-German Joint Symposium on Coastal and Ocean Engineering.
- Galiatsatou P. (2007). Joint exceedance probabilities of extreme waves and storm surges. XXXIII Congress of IAHR, pp 780 (abstract), (JFK Competition).
- Wahl T., Mudersbach C. and Jensen J. (2012). Assessing the hydrodynamic boundary conditions for risk analyses in coastal areas: a multivariate statistical approach based on copula functions, Natural Hazards and Earth System Sciences, 12, 495–510.
- Corbella A. and Stretch D. D. (2013). Simulating a multivariate sea storm using Archimedean copulas. Coastal Engineering, 76, 68–78. [CrossRef]
- Masina M., Lamberti A. and Archetti R. (2015). Coastal flooding: A copula based approach for estimating the joint probability of water levels and waves. Coastal Engineering, 97, 37–52. [CrossRef]
- Grimaldi S. and Serinaldi F. (2006). Design hyetographs analysis with 3-copula function. Hydrological Sciences Journal, 51(2), 223–238. [CrossRef]
- Shiau JT. (2006). Fitting drought duration and severity with two dimensional copulas. Water Resources Management, 20(5), 795–815. [CrossRef]
- Zhong H., van Overloop P.-J. and van Gelder P. (2013). A joint probability approach using a 1-D hydrodynamic model for estimating high water level frequencies in the Dutch Lower Rhine Delta. Natural Hazards and Earth System Sciences, 13, 1841–1852. [CrossRef]
- Zhang L. (2005). Multivariate hydrological frequency analysis and risk mapping. Doctoral dissertation, Beijing Normal University.
- Chebana F., Ouarda T.B.M.J. and Duong T.C. (2013). Testing for multivariate trends in hydrologic frequency analysis. Journal of Hydrology, 486, 519- 530. [CrossRef]
- Bender J., Wahl T. and Jensen J. (2014). Multivariate design in the presence of nonstationarity. Journal of Hydrology, 514, 123–130. [CrossRef]
- Coles S. (2001). An introduction to statistical modelling of extreme values. Springer Series in Statistics, Springer, Berlin. [CrossRef]
- Hosking J.R.M. (1990). L-moments: analysis and estimation of distributions using linear combinations of order statistics. Journal of the Royal Statistical Society (Series B), 52, 105–124.
- De Kort J. (2007). Modeling tail dependence using copulas-literature review, http://ta.twi.tudelft.nl/nw/users/vuik/numanal/kort_scriptie.pdf [accessed 29 February 2016]
- Joe H. and Xu J.J. (1996). The Estimation Method of Inference Functions for Margins for Multivariate Models. Working paper, Department of Statistics, University of British Columbia.
- Genest C., Ghoudi K. and Rivest L. P. (1995). A semiparametric estimation procedure of dependence parameters in multivariate families of distributions. Biometrika, 82, 543–552. [CrossRef]
- Salvadori G., De Michele C and Durante F. (2011) Multivariate design via copulas, Hydrology & Earth System Sciences Discussions, 8(3), 5523–5558. [CrossRef]
- Gräler B., van den Berg M.J., Vandenberghe S., Petroselli A., Grimaldi S., De Baets B. and Verhoest N.E.C. (2013). Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation. Hydrology and Earth System Sciences, 17, 1281–1296. [CrossRef]
- Stockdon H. F., Holman R. A., Howd P. A. and Sallenger A. H. (2006). Empirical parameterization of setup, swash, and runup. Coastal Engineering, 53, 573–588. [CrossRef]
- Booij N., Ris R.C., and Holthuijsen L.H. (1999). A Third-Generation Wave Model for Coastal Regions. 1. Model Description and Validation. Journal of Geophysical Research, 104, 7649–7666. [CrossRef]
- Androulidakis Y.S., Kombiadou K.D., Makris C.V., Baltikas V.N. and Krestenitis Y.N. (2015). Storm surges in the Mediterranean Sea: Variability and trends under future climatic conditions. Dynamics of Atmospheres and Oceans. 71, 56–82. [CrossRef]
- Dickinson R, Errico R., Giorgi F. and Bates G. (1989). A regional climate model for the western United States. Climate Change, 15(3), 383–422.
- Hosking J.R.M., Wallis J.R. (1997). Regional Frequency Analysis: An Approach based on LMoments. Cambridge University Press, 238 p.
- Hipel K.W. and McLeod A.I. (2005). Time Series Modelling of Water Resources and Environmental Systems. Electronic reprint of the book originally published in 1994, http://www.stats.uwo.ca/faculty/aim/1994Book/ [accessed 29 February 2016]
- Chambers, J. M. (1992). Linear models. Chapter 4 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole.
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