A model for impact-based flood early warning in Uganda

Lead Research Organisation: University of Reading
Department Name: Geography and Environmental Sciences


The initial Forecast-based Financing pilot project in North Eastern Uganda required considerable human resource to establish danger thresholds for which flood forecasting systems would be required to forecast (Coughlan de Perez et al. 2016). A new approach is therefore needed to establish country-wide danger thresholds for scaling out Forecast-based Financing to all areas of Uganda which have sufficient forecast skill (as being evaluated by the FATHUM postdoc). This research will involve the development of measures of vulnerability and resilience in Uganda, for example, based on an exploration of crop yield and livelihoods data.
This PhD project will work towards a model for national-scale impact-based forecasting of flood risk by answering the following questions:
1. what are the key indicators of flood vulnerability across different parts of Uganda? - Working alongside the Uganda Red Cross Society (URCS) and the FATHUM project team to determine the criteria for flood vulnerability which can be addressed using anticipatory measures, to include the Vulnerability and Capacity Assessment (VCA) carried out by URCS and analysis of historical disaster impacts (e.g. through Red Cross Disaster Relief Emergency Fund (DREF) reports).
2. How can a GIS tool be developed that integrates all components of risk: hazard, exposure, and vulnerability, which would support Forecast-based Financing action planning? - Identify the criteria for spatially explicit flood vulnerability and capacity assessment - Identifying key datasets for mapping flood vulnerability across Uganda - Building national-scale flood hazard maps from locally and globally available resources - Linking flood inundation mapping with population and settlement information, administrative areas and vulnerability classifications to delineate (an appropriate number of) possible action areas.
3. How can this GIS analysis be linked to forecasts in real-time to enable decision-relevant impact-based probabilistic flood forecasting? - GloFAS, or local hydrological forecasting systems, will be combined with the GIS tool to create a probabilistic decision support tool for Forecast-based Action by the Uganda Red Cross. This tool will highlight in real time the areas that could see impact, and in which early actions would be worth taking.


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