With increasing climate change impacts, Mozambique faces a rising threat of floods and storms. Gathering crucial information for territorial planning, resource management, and protecting coastal communities during natural disasters is now imperative. Our goal was to identify flood and storm-prone areas along the Mozambique coast using the InVEST Coastal Vulnerability Model. This innovative technology, applied at the state level for the first time, produces informative maps for adaptive coastal management, benefiting diverse stakeholders. Multiple bio-geophysical variables, such as elevation, natural habitats (mangroves, coral reefs, seagrass), wind and wave exposure, landmasses, coastline points, and human population density, were integrated into the Coastal Vulnerability Model (InVEST). Combining the ranks of these variables yielded an Exposure Index (EI) calculated at a spatial distance of 100 meters along the entire Mozambican coastline. The outputs comprise detailed maps of the Exposure Index (EI) along the Mozambican coast, delineating high- risk areas requiring strict management. Of the examined 2,700 km length of coastline, 43% were deemed low risk (1.0 ≤ EI ≤ 2.3), 54% medium risk (2.4 ≤ EI ≤ 3.6), and 3% high-risk (3.7 ≤ EI ≤ 5.0). Provinces with the highest storm exposure were Inhambane, followed by Nampula, Zambezia, Maputo, Maputo City, Cabo Delgado, Gaza, and Sofala. Additionally, our results highlight the role of natural ecosystems in protecting coastal areas and communities, serving as a tool to prioritize conservation and restoration areas. The model's outputs represent a significant advancement in understanding coastal vulnerability, offering essential tools for policy formulation in territorial management and disaster preparedness programs.

(ICMS) Coastal Vulnerability Model for Informative Management of Coastal Areas in Mozambique / Foggia, C., Malatesta, L., Candeago, E., Bourgeois, C., Ramoni-Perazzi, P., Attorre, F.. - (2024), pp. 74-74. (2nd International Conference on Mangroves for Sustainability Kalutara,Sri Lanka ).

(ICMS) Coastal Vulnerability Model for Informative Management of Coastal Areas in Mozambique

Camilla Foggia
Primo
Methodology
;
Luca Malatesta
Visualization
;
Elisabetta Candeago
Writing – Original Draft Preparation
;
Fabio Attorre
Ultimo
Supervision
2024

Abstract

With increasing climate change impacts, Mozambique faces a rising threat of floods and storms. Gathering crucial information for territorial planning, resource management, and protecting coastal communities during natural disasters is now imperative. Our goal was to identify flood and storm-prone areas along the Mozambique coast using the InVEST Coastal Vulnerability Model. This innovative technology, applied at the state level for the first time, produces informative maps for adaptive coastal management, benefiting diverse stakeholders. Multiple bio-geophysical variables, such as elevation, natural habitats (mangroves, coral reefs, seagrass), wind and wave exposure, landmasses, coastline points, and human population density, were integrated into the Coastal Vulnerability Model (InVEST). Combining the ranks of these variables yielded an Exposure Index (EI) calculated at a spatial distance of 100 meters along the entire Mozambican coastline. The outputs comprise detailed maps of the Exposure Index (EI) along the Mozambican coast, delineating high- risk areas requiring strict management. Of the examined 2,700 km length of coastline, 43% were deemed low risk (1.0 ≤ EI ≤ 2.3), 54% medium risk (2.4 ≤ EI ≤ 3.6), and 3% high-risk (3.7 ≤ EI ≤ 5.0). Provinces with the highest storm exposure were Inhambane, followed by Nampula, Zambezia, Maputo, Maputo City, Cabo Delgado, Gaza, and Sofala. Additionally, our results highlight the role of natural ecosystems in protecting coastal areas and communities, serving as a tool to prioritize conservation and restoration areas. The model's outputs represent a significant advancement in understanding coastal vulnerability, offering essential tools for policy formulation in territorial management and disaster preparedness programs.
2024
2nd International Conference on Mangroves for Sustainability
coastal vulnerability; models; gis; climate change; flood risk; ecosystem conservation
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
(ICMS) Coastal Vulnerability Model for Informative Management of Coastal Areas in Mozambique / Foggia, C., Malatesta, L., Candeago, E., Bourgeois, C., Ramoni-Perazzi, P., Attorre, F.. - (2024), pp. 74-74. (2nd International Conference on Mangroves for Sustainability Kalutara,Sri Lanka ).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1776995
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