Ranking sources of uncertainty in flood damage modelling: a case study on the cost-benefit analysis of a flood mitigation project in the Orb Delta, France

Cost-benefit analyses (CBA) of flood management plans usually require estimating expected annual flood damages on a study area and rely on a complex modelling chain, including hydrological, hydraulic and economic modelling, as well as geographic information system-based spatial analysis. As most model-based assessments, these CBA are fraught with uncertainty. In this paper, we consider as a case study the CBA of a set of flood control structural measures on the Orb Delta, France. We demonstrate the use of variance-based global sensitivity analysis to (i) propagate uncertainty sources through the modelling chain and assess their overall impact on the outcomes of the CBA, and (ii) rank uncertainty sources according to their contribution to the variance of the CBA outcomes. All uncertainty sources prove to explain a significant share of the overall output variance. Results show that the ranking of uncertainty sources depends not only on the economic sector considered (private housing, agricultural land, other economic activities), but also on a number of averaging-out effects controlled by the number and surface area of the assets considered, the number of land use types or the number of damage functions.