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Abstrato

GIS-based Framework for the Simulation of the Impacts of Sea Level Rise and Coastal Flooding on Oman

Al-Buloshi A, Al-Hatrushi S and Charabi Y

The Sultanate of Oman has a shoreline of 3,165 km and offers a diverse range of natural resources and promising circumstances for social and economic development According to the Oman general census of 2010, 80% of the Omani population lives in low-lying areas such as coastal plains and could be threatened by Sea Level Rise (SLR). During the last five years the country witnessed two strong tropical cyclones, Gonu 2007 and Phet 2010 revealed the extreme vulnerability of the populated Omani coast to storm surge and flooding. The impact of SLR on the entire Omani coastal zone was assessed to develop estimates of inundated land area relative to a set of SLR scenarios. The impact of SLR was evaluated through the use of a GIS framework. A total of 7 SLR scenarios were considered: 0.2 meters, 0.5 meters, 1 meter, 2 meters, 3 meters, 4 meters and 5 meters. The sea level scenarios were overlain on land use/elevation datasets to estimate the inundation risk among all land use categories. All the grid cells that would be inundated based on a user-defined horizontal spatial resolution of 0.5 meters for the entire coastline. The results of the assessment show that Oman is highly vulnerable to climate change-induced SLR. At the national scale, nearly 400 km2 of total land area is projected to be inundated under the smallest SLR scenario. Under the highest SLR scenario, over 900 km2 is potentially inundated. An assessment of the vulnerability of productive land use shows that the Al-Batinah and Muscat governorates are the most vulnerable under all SLR scenarios. The findings of this study, shows that an urgent need to develop a strategic coastal management plan to face the challenges of the climate change, and to provide a clear outlook of the Omani coastal areas for better adaptive resilience and responses.

Isenção de responsabilidade: Este resumo foi traduzido usando ferramentas de inteligência artificial e ainda não foi revisado ou verificado.