FloodScan: Near Real-Time and Historical Flood Mapping

Flood risk and hazard zone data for Ethiopia showing areas prone to flooding and inundation. Use this layer for disaster risk reduction planning, infrastructure siting, climate adaptation, and emergency preparedness.

This layer contains information about the flood risk - by second-level administrative area - estimated during the Integrated Context Analysis (ICA) run in Sudan in 2018. Data sources: UNEP/UNISDR, GAR 2013. The main indicators used for the analysis were the percentage of district surface at flood risk and the maximum expected frequency of flood events with a 100-year return period.

This dataset is the output from the Global Flood Model intercomparison project undertaken on behalf of the Global Flood Partnership. The methodology is described in Trigg et al., 2016, "The credibility challenge for global fluvial flood risk analysis," published in the Environmental Research Letters Journal. Each file is a geospatial, WGS84, 1/1200 decimal degrees resolution (~90m) GeoTIFF raster with a classified integer value representing how many out of the 6 models agree that a cell is wet (note 0 - dry/no data)

This dataset is the output from the Global Flood Model intercomparison project undertaken on behalf of the Global Flood Partnership. The methodology is described in Trigg et al., 2016, "The credibility challenge for global fluvial flood risk analysis," published in the Environmental Research Letters Journal. Each file is a geospatial, WGS84, 1/1200 decimal degrees resolution (~90m) GeoTIFF raster with a classified integer value representing how many out of the 6 models agree that a cell is wet (note 0 - dry/no data)

Flood risk and hazard zone data for Kenya showing areas prone to flooding and inundation. Use this layer for disaster risk reduction planning, infrastructure siting, climate adaptation, and emergency preparedness.

This map illustrates satellite-detected flood water extent in Somali Region, Ethiopia. The analysis was conducted by analysing a Sentinel-1 image acquired on the 1 May 2018. As observed from the satellite radar image, a total of 9,200 ha of land were inundated in the area of interest. By using WorldPop data, we estimate that at least 12,000 people are potentially affected or living close to the flooded area. This corresponds to about 7% of the population living in the area of interest. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.