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Open AccessArticle

Shoreline Solutions: Guiding Efficient Data Selection for Coastal Risk Modeling and the Design of Adaptation Interventions

1
The Nature Conservancy, Caribbean Division, Coral Gables, FL 33134, USA
2
Institute of Marine Sciences, University California, Santa Cruz, CA 95062, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Gary B. Griggs and Borja G. Reguero
Water 2021, 13(6), 875; https://doi.org/10.3390/w13060875
Received: 12 February 2021 / Revised: 17 March 2021 / Accepted: 20 March 2021 / Published: 23 March 2021
(This article belongs to the Special Issue Adaptation to Coastal Climate Change and Sea-Level Rise)
The Caribbean is affected by climate change due to an increase in the variability, frequency, and intensity of extreme weather events. When coupled with sea level rise (SLR), poor urban development design, and loss of habitats, severe flooding often impacts the coastal zone. In order to protect citizens and adapt to a changing climate, national and local governments need to investigate their coastal vulnerability and climate change risks. To assess flood and inundation risk, some of the critical data are topography, bathymetry, and socio-economic. We review the datasets available for these parameters in Jamaica (and specifically Old Harbour Bay) and assess their pros and cons in terms of resolution and costs. We then examine how their use can affect the evaluation of the number of people and the value of infrastructure flooded in a typical sea level rise/flooding assessment. We find that there can be more than a three-fold difference in the estimate of people and property flooded under 3m SLR. We present an inventory of available environmental and economic datasets for modeling storm surge/SLR impacts and ecosystem-based coastal protection benefits at varying scales. We emphasize the importance of the careful selection of the appropriately scaled data for use in models that will inform climate adaptation planning, especially when considering sea level rise, in the coastal zone. Without a proper understanding of data needs and limitations, project developers and decision-makers overvalue investments in adaptation science which do not necessarily translate into effective adaptation implementation. Applying these datasets to estimate sea level rise and storm surge in an adaptation project in Jamaica, we found that less costly and lower resolution data and models provide up to three times lower coastal risk estimates than more expensive data and models, indicating that investments in better resolution digital elevation mapping (DEM) data are needed for targeted local-level decisions. However, we also identify that, with this general rule of thumb in mind, cost-effective, national data can be used by planners in the absence of high-resolution data to support adaptation action planning, possibly saving critical climate adaptation budgets for project implementation. View Full-Text
Keywords: coastal risk assessment; sea level rise and storm surge modeling; Caribbean coastal risk assessment; sea level rise and storm surge modeling; Caribbean
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MDPI and ACS Style

Acosta-Morel, M.; McNulty, V.P.; Lummen, N.; Schill, S.R.; Beck, M.W. Shoreline Solutions: Guiding Efficient Data Selection for Coastal Risk Modeling and the Design of Adaptation Interventions. Water 2021, 13, 875. https://doi.org/10.3390/w13060875

AMA Style

Acosta-Morel M, McNulty VP, Lummen N, Schill SR, Beck MW. Shoreline Solutions: Guiding Efficient Data Selection for Coastal Risk Modeling and the Design of Adaptation Interventions. Water. 2021; 13(6):875. https://doi.org/10.3390/w13060875

Chicago/Turabian Style

Acosta-Morel, Montserrat; McNulty, Valerie P.; Lummen, Natainia; Schill, Steven R.; Beck, Michael W. 2021. "Shoreline Solutions: Guiding Efficient Data Selection for Coastal Risk Modeling and the Design of Adaptation Interventions" Water 13, no. 6: 875. https://doi.org/10.3390/w13060875

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