EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Disaster Risk Financing systems for fluvial flood risk in Democratic Republic of Congo and Pakistan

John Bevington1, Heather Forbes1, Kay Shelton1, Richard Smith1, Elizabeth Wood1, Paul Maisey2, and Sophie Ludlam2
John Bevington et al.
  • 1JBA Consulting, Skipton, United Kingdom
  • 2JBA Risk Management Ltd, Skipton, United Kingdom

Flood Foresight is JBA’s strategic flood forecasting system, providing flood inundation and depth estimates at 30m resolution up to 10-days ahead of fluvial flood events.  The system is globally scalable and recent projects have seen the Forecasting module provide forecast flood footprints in Democratic Republic of Congo, Myanmar and the Indus River basin in Pakistan.  Data produced by these systems are being used for a variety of purposes including informing humanitarian anticipatory actions, parametric insurance and disaster risk financing.  This presentation will explore the use of Flood Foresight in Democratic Republic of Congo and Pakistan for the purposes of humanitarian disaster risk financing and demonstrate the benefits to this user community in otherwise data sparse regions. 

Disaster Risk Financing (DRF) programmes are being developed for the Democratic Republic of Congo and Pakistan and are designed to allow civil society actors in country to proactively manage disaster risks. By quantifying risks in advance of disasters, pre-positioning funds, and releasing them according to pre-agreed plans, the user community are better placed to enable early disaster relief actions to help reduce the human and economic costs of disasters.  In both Democratic Republic of Congo and Pakistan, JBA were tasked with developing an operational fluvial flood forecasting model which can, at lead times of 0 – 10 days ahead, predict the number of people who will be inundated by fluvial flooding.

For forecasting population impacts, JBA’s Flood Foresight system couples the Copernicus Global Flood Awareness System (GloFAS) with the Flood Foresight technology to generate daily probabilistic forecasts of flood inundation extents and depths.  From the maps generated, the system then generates estimates of the population at risk.  This fully automated early warning system is providing humanitarian organisations with daily forecasts of flood conditions to inform rapid financing for anticipatory actions designed to reduce overall humanitarian impact.  To help inform the definition of risk and subsequently set appropriate financing triggers, a probabilistic flood risk assessment was also developed using JBA’s Global Flood Model, providing national, province and territory level risk profiles of population affected by fluvial flooding.

How to cite: Bevington, J., Forbes, H., Shelton, K., Smith, R., Wood, E., Maisey, P., and Ludlam, S.: Disaster Risk Financing systems for fluvial flood risk in Democratic Republic of Congo and Pakistan, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8204,, 2022.