A framework for comparing permanent and forecast-based flood risk-reduction strategies

Konstantinos Bischiniotis*, Hans de Moel, Marc van den Homberg, Anaïs Couasnon, Jeroen Aerts, Gabriela Guimarães Nobre, Ervin Zsoter, Bart van den Hurk

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Flood risk can be reduced at various stages of the disaster management cycle. Traditionally, permanent infrastructure is used for flood prevention, while residual risk is managed with emergency measures that are triggered by forecasts. Advances in flood forecasting hold promise for a more prominent role to forecast-based measures. In this study, we present a methodology that compares permanent with forecast-based flood-prevention measures. On the basis of this methodology, we demonstrate how operational decision-makers can select between acting against frequent low-impact, and rare high-impact events. Through a hypothetical example, we describe a number of decision scenarios using flood risk indicators for Chikwawa, Malawi, and modelled and forecasted discharge data from 1997 to 2018. The results indicate that the choice between permanent and temporary measures is affected by the cost of measures, climatological flood risk, and forecast ability to produce accurate flood warnings. Temporary measures are likely to be more cost-effective than permanent measures when the probability of flooding is low. Furthermore, a combination of the two types of measures can be the most cost-effective solution, particularly when the forecast is more skillful in capturing low-frequency events. Finally, we show that action against frequent low-impact events could more cost-effective than action against rare high-impact ones. We conclude that forecast-based measures could be used as an alternative to some of the permanent measures rather than being used only to cover the residual risk, and thus, should be taken into consideration when identifying the optimal flood risk strategy.

Original languageEnglish
Article number137572
Pages (from-to)1-16
Number of pages16
JournalScience of the Total Environment
Volume720
Early online date26 Feb 2020
DOIs
Publication statusE-pub ahead of print - 26 Feb 2020

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Keywords

  • And early action
  • Early warning
  • Flood prevention
  • Flood risk management
  • Forecast quality
  • Forecast-based financing

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