Sea-Level Rise Insight assesses and visualize potential impact of sea-level rise (SLR) across the coastal zone of West Africa, covering countries from Senegal to Nigeria. The tool is designed to simulate inundation by SLR under different SLR scenarios, thus offering insight into areas at risk based on elevation, proximity to the coast, and hydrological connectivity.

Data Sources and Preprocessing

The main dataset used for the modelling was the 30-meter resolution Shuttle Radar Topography Mission (SRTM) derived from a Digital Elevation Model (DEM). This dataset was accessed and downloaded via Google Earth Engine (GEE). This elevation data was preprocessed in ArcGIS Pro V3.5 to correct voids, fill sinks, and remove anomalies in flat terrain.

Terrain below 20 meters elevation was extracted for focused analysis, as this zone represents the most vulnerable to near-term sea-level rise.

Modelling Approach

The modelling approach followed a modified bathtub method, where sea-level rise was simulated by comparing future water surfaces to current land elevations. This approach involves creating synthetic water surfaces by adding projected sea-level rise increments to the baseline tidal level, which was approximated using regional mean higher high water (MHHW) levels from tide gauges and literature sources.

The tool evaluates scenarios of 0.5, 1.0, 1.5, and 2.0 meters of sea-level rise based on global climate projections, including those from the IPCC Sixth Assessment Report (AR6).

Inundation Mapping Process

Inundation mapping was performed by calculating the difference between the SLR water surface and the DEM. Areas where the water level exceeds the elevation were marked as potentially inundated.

However, not all low-lying areas are directly connected to the ocean; therefore, the analysis incorporated a hydrological connectivity assessment using the Region Group function in ArcGIS Pro. This ensured that only hydrologically connected zones (those continuously linked to the ocean or tidal systems) were identified as inundated.

Low-lying, disconnected depressions larger than one acre were still retained in the analysis but symbolized separately to avoid overestimating risk. Lastly inundation depths were also mapped to show the extent of flooding across each scenario. A land-water mask was applied to focus visual outputs on terrestrial areas only.

Technical Implementation

The final raster and vector layers were then published to the organization's ArcGIS Server environment as dynamic map services and feature services. An API endpoint was automatically generated for each service through ArcGIS Server. These APIs allowed the services to be accessed programmatically and integrated into web-based applications.

Through Esri Leaflet and the API endpoints, dynamic maps were embedded into The ROC Datahub interface, supporting interactive features such as layer toggling, scenario switching, zoom and pan, and pop-up information windows.