With heavy storms increasing and sea level rise taking over significant portions of habitable land, small island states are among the most impacted by climate change. From coastal and fluvial flooding to landslides and unpredictable drought, climate change is posing an existential threat to inhabitants of these islands.
Lobelia provided a comprehensive approach to climate risk assessment involving past and future flood modelling, historical satellite and earth observation data, and regional CORDEX projections. The analysis was used to inform adaptation investment by the World Bank to safeguard vulnerable coastal island transport infrastructure.
Sao Tomé, the largest and most populous island in the small island archipelago Sao Tomé and Principe off the coast of West Africa, maintains a vulnerable coastal road network that encircles the island and is a vital means of transport for commerce and the community. This network often runs perilously close to the sea and crosses multiple rivers.
Coastal roads are impacted by river and coastal flooding triggered by changes in precipitation, sea level rise, changes in wave patterns and coastal erosion.
To assess flood risk to specific sections of the coastal road in Sao Tome, an in depth approach to climate risk including high resolution flood modelling was needed.
The high resolution flood model enabled Lobelia’s partner, Royal HaskonyDHV, to provide the World Bank with suitable adaptation strategies to specific road sections involving nature based approaches to design better drainage above and below the road, stabilize erosion prone slopes, build higher retaining walls, and reduce the risk of landslides.
Long-term precipitation data is scarce in remote regions. To address this in Sao Tome, sparse field data was compared with global climatological products to identify the most accurate dataset. This dataset was then used for further analysis with satellite data.
Optical and radar satellite imagery identified hazard footprints of past flooding events.
These footprints were compared to precipitation from the same time period. This analysis served to calibrate the flood model simulating past extreme flood events.
Sao Tome is projected to experience a 10% increase in extreme rain events. Lobelia modelled the future projected path of flood extent, identifying areas at risk, and the likely path and depth of the water, depending on local geography including slope, soil, and the shape of the river.
Not only the road, but surrounding areas at risk can be analysed for future impacts.
Flood modelling was just one piece of the comprehensive climate risk assessment delivered for Sao Tomé.
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