Agent-based modelling and flood risk management: A compendious literature review

Zhuo, Lu and Han, Dawei 2020. Agent-based modelling and flood risk management: A compendious literature review. Journal of Hydrology 591 , 125600. 10.1016/j.jhydrol.2020.125600

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Abstract

The use of agent-based modelling (ABM) to tackle flood-related risk challenges is becoming increasingly popular in recent years. This paper reviews the literature at the interface of ABM and flood-related studies in view of understanding the technique’s advantages and limitations to flood risk management, based on a set of 61 representative articles. In particular, to understand how this process-based technique can help to link human (also institutional) decisions and behaviour with flood risks through the whole human-flood systems. Overall, the temporal and spatial distributions demonstrate a growing interest in this research area around the world, especially since 2017. Three topic areas are identified, addressing different research challenges in the field: real-time flood emergency management, long-term flood adaptation planning, and flood hydrological modelling. The review has shown that the potential contribution of ABM to future flood risk management lays in its practical application to decision-making in adaptation policy and strategy planning. The review also critically reveals the limitation of ad hoc implementations of decision-making and behaviour in the ABM models that could make the application less realistic in the field. It is recommended that the future development should be guided/influenced by the continuing development and refinement of ABM modelling framework and theoretical foundations, and enhancement of model testing and documenting capabilities. More importantly, active collaborations between disciplines and sectors such as to involve more social and psychological sciences in ABM decision-making modelling should be encouraged; and knowledge sharing will encourage more effective uses of ABM by wider audiences.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Earth and Environmental Sciences
Publisher:	Elsevier
ISSN:	0022-1694
Date of Acceptance:	29 September 2020
Last Modified:	21 Oct 2022 13:15
URI:	https://orca.cardiff.ac.uk/id/eprint/153240

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