Artificial Intelligence Techniques for Flood Risk Management in Urban Environments

Sayers, William ORCID: 0000-0003-1677-4409, Savić, D., Kapelan, Z. and Kellagher, R. (2014) Artificial Intelligence Techniques for Flood Risk Management in Urban Environments. Procedia Engineering, 70. pp. 1505-1512. ISSN 1877-7058

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Abstract

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.

Item Type: Article
Article Type: Article
Uncontrolled Keywords: Flooding; Floods; Drainage; Technology; Innovation; Multi-objective; Optimisation; Optimization
Related URLs:
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Schools and Research Institutes > School of Business and Technology > Technical & Applied Computing
Research Priority Areas: Applied Business & Technology
Depositing User: Susan Turner
Date Deposited: 12 Jun 2019 15:53
Last Modified: 12 Jun 2019 16:00
URI: http://eprints.glos.ac.uk/id/eprint/6921

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