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Geospatial modelling of floods: a literature review

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A Correction to this article was published on 16 September 2023

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Abstract

Floods are one of the most frequent, dangerous natural disasters globally. During the period from 1990 to 2020, more than 50% of the world's recorded disasters were related to floods. This problem stems largely from the inadequate planning and economic circumstances of human settlements in flood-prone plains. Geospatial modelling can be a powerful tool for large-scale flood modelling. The hydrological and hydraulic models theory, GIS-based multi-criteria evaluation techniques, and machine learning algorithms for flood simulation are presented. The most used techniques and methodologies for the geospatial simulation of floods in the last decade are presented. This paper also shows the input data requirements and the algorithms used for each geospatial technique and a description of the tools and some relevant examples of geospatial flood studies are given. A comprehensive assessment of the characteristics of the flood models is presented based on its modelling approach, either for flood susceptibility, hazard, vulnerability, or risk.

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Source: modified from (López S. 2005)

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Acknowledgements

The authors thank the Faculty of Earth and Space Sciences, Autonomous University of Sinaloa, and CONAHCYT.

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This research received no external funding.

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Conceptualization, EA-A, WP-R and SAM-A; methodology, EA-A and WP-R; validation, EA-A, WP-R, SAM-A and JGR-P; formal analysis, EA-A, WP-R, SAM-A and JGR-P; investigation, EA-A, WP-R and SAM-A; resources, EA-A, WP-R, SAM-A and JGR-P; data curation, EA-A, WP-R and SAM-A writing—original draft preparation, EA-A, WP-R, SAM-A and JGR-P; writing—review and editing, EA-A, WP-R, SAM-A and JGR-P; visualization, WP-R, SAM-A and JGR-P; supervision, WP-R and SAM-A; project administration, EA-A, WP-R and SAM-A; funding acquisition, EA-A, WP-R, SAM-A and JGR-P. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Wenseslao Plata-Rocha or Sergio Alberto Monjardin-Armenta.

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The original online version of this article was revised due to one of the corresponding author’s name spelling error.

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Avila-Aceves, E., Plata-Rocha, W., Monjardin-Armenta, S.A. et al. Geospatial modelling of floods: a literature review. Stoch Environ Res Risk Assess 37, 4109–4128 (2023). https://doi.org/10.1007/s00477-023-02505-1

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