TY  - JOUR
PY  - 2020//
TI  - A framework for comparing permanent and forecast-based flood risk-reduction strategies
JO  - Science of the total environment
A1  - Bischiniotis, Konstantinos
A1  - de Moel, Hans
A1  - van den Homberg, Marc
A1  - Couasnon, Anaïs
A1  - Aerts, Jeroen
A1  - Guimarães Nobre, Gabriela
A1  - Zsoter, Ervin
A1  - van den Hurk, Bart
SP  - 137572
EP  - 137572
VL  - 720
IS  - 
N2  - 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.<br><br>Copyright © 2020. Published by Elsevier B.V.<p />  <p>Language: en</p>
LA  - en
SN  - 0048-9697
UR  - http://dx.doi.org/10.1016/j.scitotenv.2020.137572
ID  - ref1
ER  -