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Flood Risks Across Spatial Scales

Related Event

  • 2012 Understanding Risk Forum

Related Topics

  • Flood
  • Risk Assessment
  • Risk Finance and Insurance

Related Regions

  • Global
  • Sub-Saharan Africa

Event Summary

Session Leads

  • Hessel Winsemius, Deltares
  • Jaap Kwadijk, Deltares
  • Zuzana Stanton-Geddes, World Bank
  • Brenden Jongman, VU University of Amsterdam

Description

Flooding of river systems and deltas is the most frequent and costly natural hazard, affecting the majority of the world’s countries on a regular basis. To minimize the impact of floods, adaptation measures, mitigation strategies and financing schemes are developed at spatial scales ranging from local to global. The information needed for risk analysis and decision making varies with the scale. At a local scale, high-resolution risk assessment using specific inundation patterns is required to decide upon evacuation and mitigation plans. At a river basin scale, a more generic basin-wide assessment may be used to assist land-use planning and formulate adaptation pathways. At the global scale, international re-insurance and development organizations require a consistent risk framework for cross-continental resource allocation.

In this session, we seek to clarify what information needs on flood risks may arise at different spatial scales and what solutions are available. In particular we focus on applications in the African context. We are looking forward to contributions about, for instance:

Information needs:

  • flood risk assessment requirements
  • flood forecasting requirements
  • temporal and spatial resolution

Solutions:

  • Methodologies to provide flood risk assessments (hazard, exposure, vulnerability)
  • Flood forecasting tools / examples
  • Software solutions for flood forecasting / risk assessments

Session Resources

  • Understanding the Scale of Flood Risk: Size matters!
  • Cities and Flooding Urban Flood Risk Management
  • The Benefits of Rapid Flood Modeling
  • Dynamic Flood Risk Assessment Using Globally Available Data: An African example
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