Ethiopia environment data

**ADAM ID: FL-20231109-ETH-00** Flood covering 205753.0 sq m on Nov 09 2023 in Ethiopia. It impacted 95847 people.

**ADAM ID: FL-20231114-ETH-01** Flood covering 1016365.0 sq m on Nov 14 2023 in Ethiopia. It impacted 534273 people.

**ADAM ID: FL-20231121-ETH-01** Flood covering 418451.0 sq m on Nov 21 2023 in Ethiopia. It impacted 295186 people.

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)

GLIDEnumbers are GLobal unique IDEntifiers for Disasters. Each disaster is registered in a record that contains a GLIDEnumber that uniquely identifies it and allows information to be interoperable across multiple disaster information sources, both structured and textual. Accessing disaster information can be a time consuming and laborious task. Not only is data scattered but frequently identification of the disaster can be confusing in countries with many disaster events and across borders. To address both of these issues, Asian Disaster Reduction Center (ADRC) proposed a globally common Unique ID code for disasters. Among the institutions using actively GLIDEnumbers are UN-OCHA (ReliefWeb, FSCC, HDX), UNDRR, UNDP, WMO, IFRC, FAO, the European Commission and the Centre for Research on the Epidemiology of Disasters (CRED), among many others. Country datasets are only produced for countries with at least one GLIDE event since 1 January 2022. The global dataset contains all events available from the GLIDE API, including those not assigned to a country.