Efficient joint-probability methods for hurricane surge frequency analysis |
| |
Authors: | Gabriel R. Toro Donald T. Resio Alan Wm. Niedoroda |
| |
Affiliation: | a Risk Engineering Inc.—William Lettis and Associates, 3 Farmers Row, Acton, MA 01720, USA b US Army Corps of Engineers, ERDC-CHL, 3909 Halls Ferry Road, Vicksburg, MS 39180, USA c Watershed Concepts, AECOM Water, 1360 Peachtree Street NE, Suite 500, Atlanta, GA 30309, USA d URS Corporation, 1625 Summit Lake Drive, Suite 200, Tallahassee, FL 32317, USA |
| |
Abstract: | The Joint-Probability Method (JPM) was adopted by federal agencies for critical post-Katrina determinations of hurricane surge frequencies. In standard JPM implementations, it is necessary to consider a very large number of combinations of storm parameters, and each such combination (or synthetic storm) requires the simulation of wind, waves, and surge. The tools used to model the wave and surge phenomena have improved greatly in recent years, but this improvement and the use of very large high-resolution grids have made the computations both time-consuming and expensive. In order to ease the computational burden, two independent approaches have been developed to reduce the number of storm surge simulations that are required. Both of these so-called JPM-OS (JPM-Optimal Sampling) methods seek to accurately cover the entire storm parameter space through optimum selection of a small number of parameter values so as to minimize the number of required storm simulations. Tests done for the Mississippi coast showed that the accuracy of the two methods is comparable to that of a full JPM analysis, with a reduction of an order of magnitude or more in the computational effort. |
| |
Keywords: | Hurricane Katrina Storm surge Joint-probability method Probabilistic methods Flood insurance maps Numerical methods |
本文献已被 ScienceDirect 等数据库收录! |
|