Modelling flood risk can help to inform policymakers, communities and disaster response agencies seeking to minimise property damage, injury and death from natural hazards. At present, the flood risk indices available for developing countries do not provide adequate information for this purpose due to two key limitations:
- Data sets are too coarse to make valid projections of the potential impact of hazard events for individual settlements.
- The vulnerability component of these risk models generally consists of a single, problematic variable: average income per person distributed evenly across the population.
Consequently, existing models don’t provide sufficient nuance to accurately estimate the potential impacts of environmental hazards at city level, let alone at neighbourhood level.
This project aims to substantially improve urban risk modelling for developing countries by integrating data and insights from physical and human geography. This proof-of-concept project will focus on modelling urban flood risk in two developing countries, combining world-leading hydraulic models developed at Bristol with remote sensing data, social indicators and political-administrative data that reflect the quality of urban governance in our case study countries. These models will then be compared against those currently used by major international development agencies such as the World Bank.
This project is being run by Sean Fox (Human Geography) and Jeff Neal (Geographical Science).