Author:
Amores Angel,Marcos Marta,Pedreros Rodrigo,Le Cozannet Gonéri,Lecacheux Sophie,Rohmer Jérémy,Hinkel Jochen,Gussmann Geronimo,van der Pol Thomas,Shareef Ali,Khaleel Zammath
Abstract
The Maldives, with one of the lowest average land elevations above present-day mean sea level, is among the world regions that will be the most impacted by mean sea-level rise and marine extreme events induced by climate change. Yet, the lack of regional and local information on marine drivers is a major drawback that coastal decision-makers face to anticipate the impacts of climate change along the Maldivian coastlines. In this study we focus on wind-waves, the main driver of extremes causing coastal flooding in the region. We dynamically downscale large-scale fields from global wave models, providing a valuable source of climate information along the coastlines with spatial resolution down to 500 m. This dataset serves to characterise the wave climate around the Maldives, with applications in regional development and land reclamation, and is also an essential input for local flood hazard modelling. We illustrate this with a case study of HA Hoarafushi, an atoll island where local topo-bathymetry is available. This island is exposed to the highest incoming waves in the archipelago and recently saw development of an airport island on its reef via land reclamation. Regional waves are propagated toward the shoreline using a phase-resolving model and coastal inundation is simulated under different mean sea-level rise conditions of up to 1 m above present-day mean sea level. The results are represented as risk maps with different hazard levels gathering inundation depth and speed, providing a clear evidence of the impacts of the sea level rise combined with extreme wave events.
Funder
Ministerio de Ciencia, Innovación y Universidades
Ministerio de EconomÃa, Industria y Competitividad, Gobierno de España
Subject
Ocean Engineering,Water Science and Technology,Aquatic Science,Global and Planetary Change,Oceanography
Cited by
18 articles.
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