Articles | Volume 20, issue 9
Hydrol. Earth Syst. Sci., 20, 3549–3560, 2016
Hydrol. Earth Syst. Sci., 20, 3549–3560, 2016

Research article 05 Sep 2016

Research article | 05 Sep 2016

Action-based flood forecasting for triggering humanitarian action

Erin Coughlan de Perez1,2,3, Bart van den Hurk2,4, Maarten K. van Aalst1,3,14, Irene Amuron5, Deus Bamanya6, Tristan Hauser7, Brenden Jongma2,8, Ana Lopez9, Simon Mason3, Janot Mendler de Suarez1,10, Florian Pappenberger11, Alexandra Rueth12, Elisabeth Stephens13, Pablo Suarez1,14, Jurjen Wagemaker15, and Ervin Zsoter11 Erin Coughlan de Perez et al.
  • 1Red Cross Red Crescent Climate Centre, The Hague, 2521 CV, the Netherlands
  • 2Institute for Environmental Studies, VU University Amsterdam, 1081 HV, Amsterdam, the Netherlands
  • 3International Research Institute for Climate and Society, Columbia University, Palisades, NY 10964, USA
  • 4Royal Netherlands Meteorological Institute (KNMI), De Bilt, 3731 GA, the Netherlands
  • 5Uganda Red Cross Society, Kampala, Uganda
  • 6Uganda National Meteorological Authority, Kampala, Uganda
  • 7Climate System Analysis Group, Department of Environmental and Geographical Science, University of Cape Town, Cape Town, South Africa
  • 8Global Facility for Disaster Reduction and Recovery (GFDRR), World Bank, Washington DC, USA
  • 9Atmospheric Oceanic & Planetary Physics Department, Oxford University, Oxford, OX1 3PU, UK
  • 10Frederick S. Pardee Center for the Study of the Longer-Range Future, Boston University, Boston, Massachusetts, USA
  • 11European Centre for Medium-Range Weather Forecasts, Reading, RG2 9AX, UK
  • 12German Red Cross, 12205 Berlin, Germany
  • 13School of Archaeology, Geography and Environmental Science, University of Reading, Reading, RG6 6AH, UK
  • 14Department of Science, Technology, Engineering and Public Policy, University College London, London, UK
  • 15Floodtags, The Hague 2516 BE, the Netherlands

Abstract. Too often, credible scientific early warning information of increased disaster risk does not result in humanitarian action. With financial resources tilted heavily towards response after a disaster, disaster managers have limited incentive and ability to process complex scientific data, including uncertainties. These incentives are beginning to change, with the advent of several new forecast-based financing systems that provide funding based on a forecast of an extreme event. Given the changing landscape, here we demonstrate a method to select and use appropriate forecasts for specific humanitarian disaster prevention actions, even in a data-scarce location. This action-based forecasting methodology takes into account the parameters of each action, such as action lifetime, when verifying a forecast. Forecasts are linked with action based on an understanding of (1) the magnitude of previous flooding events and (2) the willingness to act "in vain" for specific actions. This is applied in the context of the Uganda Red Cross Society forecast-based financing pilot project, with forecasts from the Global Flood Awareness System (GloFAS). Using this method, we define the "danger level" of flooding, and we select the probabilistic forecast triggers that are appropriate for specific actions. Results from this methodology can be applied globally across hazards and fed into a financing system that ensures that automatic, pre-funded early action will be triggered by forecasts.

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Short summary
Many flood disaster impacts could be avoided by preventative action; however, early action is not guaranteed. This article demonstrates the design of a new system of forecast-based financing, which automatically triggers action when a flood forecast arrives, before a potential disaster. We establish "action triggers" for northern Uganda based on a global flood forecasting system, verifying these forecasts and assessing the uncertainties inherent in setting a trigger in a data-scarce location.