Use of artificial intelligence to improve resilience and preparedness against adverse flood events

Journal article


Saravi, Sara, Kalawsky, Roy, Joannou, Demetrios, Rivas Casado, Monica, Fu, Guangtao and Meng, Fanlin 2019. Use of artificial intelligence to improve resilience and preparedness against adverse flood events. Water. 11 (5), p. 973. https://doi.org/10.3390/w11050973
AuthorsSaravi, Sara, Kalawsky, Roy, Joannou, Demetrios, Rivas Casado, Monica, Fu, Guangtao and Meng, Fanlin
Abstract

The main focus of this paper is the novel use of Artificial Intelligence (AI) in natural disaster, more specifically flooding, to improve flood resilience and preparedness. Different types of flood have varying consequences and are followed by a specific pattern. For example, a flash flood can be a result of snow or ice melt and can occur in specific geographic places and certain season. The motivation behind this research has been raised from the Building Resilience into Risk Management (BRIM) project, looking at resilience in water systems. This research uses the application of the state-of-the-art techniques i.e., AI, more specifically Machin Learning (ML) approaches on big data, collected from previous flood events to learn from the past to extract patterns and information and understand flood behaviours in order to improve resilience, prevent damage, and save lives. In this paper, various ML models have been developed and evaluated for classifying floods, i.e., flash flood, lakeshore flood, etc. using current information i.e., weather forecast in different locations. The analytical results show that the Random Forest technique provides the highest accuracy of classification, followed by J48 decision tree and Lazy methods. The classification results can lead to better decision-making on what measures can be taken for prevention and preparedness and thus improve flood resilience.

KeywordsArtificial Intelligence; machine learning; flood; preparedness; resilience; flood resilience
Year2019
JournalWater
Journal citation11 (5), p. 973
PublisherMDPI AG
ISSN2073-4441
Digital Object Identifier (DOI)https://doi.org/10.3390/w11050973
Web address (URL)http://hdl.handle.net/10545/624221
hdl:10545/624221
Publication dates09 May 2019
Publication process dates
Deposited18 Oct 2019, 15:29
Accepted06 May 2019
ContributorsLoughborough University
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File Access Level
Open
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File Access Level
Open
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https://repository.derby.ac.uk/item/9337y/use-of-artificial-intelligence-to-improve-resilience-and-preparedness-against-adverse-flood-events

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