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Research Article

Geostatistical strategy to build spatial coastal-flooding models

ORCID Icon, , ORCID Icon, , &
Pages 395-409 | Received 30 May 2021, Accepted 20 Dec 2021, Published online: 31 Dec 2021
 

ABSTRACT

The intensification of flooding events and the management of ecosystems became global issues. The combination of statistical modelling techniques and geospatial analysis represents a promising strategy to provide a holistic representation of the systems. This paper aimed to develop a strategy to build Spatial Coastal-Flooding Models based on evidence of flooding points and environmental and artificial characteristics of the area. The procedure combines statistical techniques, such as PCA, Cluster analysis, ANOVA, OLS regression, and geospatial data obtained from open databases. The geostatistical strategy was applied in Florianópolis city – Brazil. 108 photographic records of flooding were inventoried. The OLS regression analysis constructed three Spatial Coastal-Flooding Models considering eight factors. The analysis specifies the ability of models to explain the flooding in C1, C2, and C3 sub-regions through calculus (76, 68, and 40%). The results find that relationships between environmental and artificial variables and flooding events are not homogeneous over space.

Acknowledgements

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001. The authors are very grateful still to PMF (Prefeitura Municipal de Florianópolis) for supporting research activities.

Disclosure statement

All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.

Supplementary material

Supplemental data for this article can be accessed https://doi.org/10.1080/1573062X.2021.2022720

Additional information

Funding

No funds, grants, or other support were received by organizations that may gain or lose financially through the publication of this manuscript.

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