Artificial intelligence techniques for flood risk management in urban environments
Published under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) licence: http://creativecommons.org/licenses/by-nc-nd/3.0/
Urban flooding is estimated to cause £270 million pounds worth of damage each year in England and Wales alone. There has, therefore, been a clear need to develop improved methods of identifying intervention strategies to reduce flood risk in urban environments. This paper describes ground-work performed towards evaluating the relative suitability of several algorithms applied to multi-objective optimisation of flood risk intervention strategies in an urban drainage network. An effective methodology is described for reducing an array of return period/duration rainfall files to a minimum, and it is described how this methodology makes possible comparisons of optimisation algorithms. This work has been undertaken as part of a STREAM-IDC EngD project which is a collaborative effort between the University of Exeter, and HR Wallingford.
Open Access journal
Copyright © 2013 The Authors. Published by Elsevier Ltd.
12th International Conference on Computing and Control for the Water Industry, CCWI2013
Vol. 70, pp. 1505 - 1512