Open AccessThe use of wave propagation and reduced complexity inundation models and metamodels for coastal flood risk assessment
Author(s) -
Rueda A.,
Gouldby B.,
Méndez F.J.,
Tomás A.,
Losada I.J.,
Lara J.L.,
DíazSimal P.
Publication year - 2016
Publication title -
journal of flood risk management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.049
H-Index - 36
ISSN - 1753-318X
DOI - 10.1111/jfr3.12204
Subject(s) - computer science , flood myth , function (biology) , probability density function , environmental science , marine engineering , mathematical optimization , statistics , geography , mathematics , engineering , archaeology , evolutionary biology , biology
To estimate coastal risk it is necessary to integrate the joint probability density function, including extremes, of the sea condition variables over a function that defines the consequences, typically economic damage. The use of M onte C arlo methods is common practice to undertake this integration; however, it can introduce a high computational burden for use in practical applications. Hence, a simplifying assumption of full dependence between the sea condition variables is often made. This paper describes a method that overcomes this simplifying assumption through the use of two techniques. A hybrid emulator of the simulating waves nearshore model is used to increase the computational efficiency associated with the wave transformations. In addition, a computationally efficient dynamic inundation model has been incorporated to further reduce the computational burden. To demonstrate the system, it has been applied to an urban coastal area located in northern S pain.