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Camila Gaido-Lassarre

Publications and source records attributed to Camila Gaido-Lassarre.

2 recordsLinked to original sources

Hybrid coral reef restoration can be a cost-effective nature-based solution to provide protection to vulnerable coastal populations

Coral reefs can mitigate flood damages by providing protection to tropical coastal communities whose populations are dense, growing fast, and have predominantly lower-middle income. This study provides the first fine-scale, regionally modeled valuations of how flood risk reductions associated with hybrid coral reef restoration could benefit people, property, and economic activity along Florida and Puerto Rico’s 1005 kilometers of reef-lined coasts. Restoration of up to 20% of the regions’ coral reefs could provide flood reduction benefits greater than costs. Reef habitats with the greatest benefits are shallow, nearshore, and fronting low-lying, vulnerable communities, which are often where reef impacts and loss are the greatest. Minorities, children, the elderly, and those below the poverty line could receive more than double the hazard risk reduction benefits of the overall population, demonstrating that reef restoration as a nature-based solution can have positive returns on investment economically and socially by providing protection to the most vulnerable people.

Florida

Improved efficient physics-based computational modeling of regional wave-driven coastal flooding for reef-lined coastlines

Coastal flooding affects low-lying communities worldwide and is expected to increase with climate change, especially along reef-lined coasts, where wave-driven flooding is particularly prevalent. However, current regional modeling approaches are either insufficient or too computationally expensive to accurately assess risks in these complex environments. This study introduces and validates an improved computationally efficient and physics-based approach to compute dynamic wave-driven regional flooding on reef-lined coasts. We coupled a simplified-physics flood model (SFINCS) with a one-dimensional wave transformation model (XBeach-1D). To assess the performance of the proposed approach, we compared its results with results from a fully resolving two-dimensional wave transformation model (XBeach-2D). We applied this approach for a range of storms and sea-level rise scenarios for two contrasting reef-lined coastal geomorphologies: one low relief area and one high relief area. Our findings reveal that SFINCS coupled with XBeach-1D generates flood extents comparable to those produced by XBeach-2D, with a hit rate of 92%. However, this method tends to underpredict the flood extent of weaker, high-frequency storms and overpredict stronger, low-frequency storms. Across scenarios, our approach overpredicted the mean flood water depth, with a positive bias of 7 cm and root mean square difference of 15 cm. Offering approximately 100 times greater computational efficiency than its two-dimensional XBeach counterpart, this flood modeling technique is recommended for wave-driven flood modeling in scenarios with high computational demands, such as modeling numerous scenarios or undertaking detailed regional-scale modeling.

Journal of Marine Science & Engineering