Digital Twin for effective flood response at Dolo Ado District, Somali Region of Ethiopia - Haile, Alemseged Tamiru; da Silva, Paulo Alexandre Rodrigues; Bekele, T. W.; McTough, Mitchell; Retief, H.; Garcia Andarcia, Mariangel; Wegderes, A.; Seid, Abdulkarim H. (International Water Management Institute, 2025)
Collaboration between CGIAR and the World Food Programme (WFP) has enabled more proactive, data-driven interventions to protect people against the impacts of conflict and climate shocks. This collaboration has been extended to digital innovations for flood preparedness and early warning in a fragile environment in Ethiopia through this study. Flood preparedness and early warning can be improved by providing timely, accurate warnings to all stakeholders. However, several challenges affect flood preparedness and early warning, particularly in fragile and conflict-affected environments. This project aims to overcome these challenges by scaling a Digital Twin (DT) for flood early warning in these environments. DT is a virtual replica of a physical object. It helps to monitor what is happening in real time, issue accurate, timely flood warnings and share relevant flood-related information so that stakeholders act before a flood occurs. It also brings together information from multiple data sources, including ground-based data sensors and satellites, detailed elevation data for the study site and flood forecasting models. It is the future aim of the DT to serve as a convening tool, fostering conversations and negotiations for stakeholder collaboration, the integration of humanitarian development strategies, disaster preparedness, planning and response and a strategic tool for climate adaptation and sustainable land-use planning.