Issue |
E3S Web Conf.
Volume 7, 2016
3rd European Conference on Flood Risk Management (FLOODrisk 2016)
|
|
---|---|---|
Article Number | 04014 | |
Number of page(s) | 5 | |
Section | Hazard analysis and modelling | |
DOI | https://doi.org/10.1051/e3sconf/20160704014 | |
Published online | 20 October 2016 |
The RMS US inland flood model
1 Risk Management Solutions, Inc., 7575 Gateway Boulevard, Newark, CA 95355, USA
2 Risk Management Solutions, Inc., Peninsular House, 30 Monument Street, London EC3R 8NB, UK
3 Risk Management Solutions, Inc., Stampfenbachstrasse 85, 8006 Zuerich, Switzerland
a Corresponding author: sonja.jankowfsky@rms.com
The RMS US inland flood model provides flood hazard data of up to 10×10m resolution for the Contiguous United States for different return periods. The flood maps were developed using a series of physically based models. First, several thousand years of precipitation were simulated using principal component analysis coupled to a tropical cyclone precipitation model. Then, discharge and runoff were calculated using a semi-distributed rainfall runoff and routing model based on the TOPMODEL approach run at an hourly time step. This in turn forms the input to the fluvial and pluvial inundation models, which uses the shallow water equation to simulate flood propagation. Each of the individual model components such as precipitation, discharge and flood extent and depth were validated individually. The model generally performed very well compared to available flood maps, especially in the high exposure areas, even if it has some difficulties in the dry low exposure areas of the United States, which are heavily influenced by water management. The flood maps will be the base for the fully probabilistic loss model including a financial model. Via the simulated Hurricane track data set the flood model will be coupled to the RMS North Atlantic Hurricane model.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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