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Advances in Meteorology
Volume 2016, Article ID 6408319, 8 pages
http://dx.doi.org/10.1155/2016/6408319
Research Article

A Method to Assess Localized Impact of Better Floodplain Topography on Flood Risk Prediction

1Remote Sensing Solutions, Inc., Monrovia, CA 91016, USA
2School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK
3NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA

Received 23 January 2016; Revised 3 May 2016; Accepted 17 May 2016

Academic Editor: Maoyi Huang

Copyright © 2016 Guy J.-P. Schumann and Konstantinos M. Andreadis. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Many studies have highlighted the need for a higher accuracy global digital elevation model (DEM), mainly in river floodplains and deltas and along coastlines. In this paper, we present a method to infer the impact of a better DEM on applications and science using the Lower Zambezi basin as a use case. We propose an analysis based on a targeted observation algorithm to evaluate potential data acquisition subregions in terms of their impact on the prediction of flood risk over the entire study area. Consequently, it becomes trivial to rank these subregions in terms of their contribution to the overall accuracy of flood prediction. The improvement from better topography data may be expressed in terms of economic output and population affected, providing a multifaceted assessment of the value of acquiring better elevation data. Our results highlight the notion that having higher resolution measurements would improve our current large-scale flood inundation prediction capabilities in the Lower Zambezi by at least 30% and significantly reduce the number of people affected as well as the economic loss associated with high magnitude flooding. We believe this procedure to be simple enough to be applied to other regions where high quality topographic and hydrodynamic data are currently unavailable.