Strategies are proposed to cope with uncertainties in a way that all possible kinds of uncertainty are named, recognized, statistically quantified as far as possible and utilized in efficient decision-making in flood risk management (FRM). We elaborated on the metaphor of uncertainty as a monster. We recommend two strategies to cope with the uncertainty monster to support efficient decision-making in FRM: monster adaptation and monster assimilation. We present three cases to illustrate these strategies. We argue that these strategies benefit from improving the structure and reducing the complexity of decision problems. We discuss ways to involve decision-makers in FRM, and how communication strategies can be responsive to their informational needs.

Climate change and human-modified landscapes have led to an increase in global flood and drought risks, while biodiversity has declined. The concept of using nature-based solutions (NbS) to improve the water retention capacity at the landscape scale, also known as ‘sponge functioning of catchments,’ has been recognised to help reduce and delay peak flows and stimulate infiltration to the groundwater, thus reducing flood and drought risks. Although various effects of NbS have been demonstrated, there is limited evaluation of the combined multiple benefits for flood risk reduction, drought risk reduction, and biodiversity. To address this gap, we analysed various online databases on NbS and additional literature on the evaluated combined effects of NbS. We found that the quantitative evaluation of NbS is fragmented and not standard practice in many projects. Although many successfully implemented NbS have been reported in different environments globally, most cases lack evidence for their response to the combined impacts of floods, droughts, and biodiversity. Therefore, we propose four components to facilitate planning, design, implementation, and monitoring of NbS that improve sponge functioning for floods and droughts. First, we suggest increased understanding of how NbS affects the hydrological processes of both flood and drought events along the full range of potential conditions. Second, we recommend evaluating the effect of potential NbS measures at a landscape scale. Third, we propose that integrated modelling and upscaling techniques should be improved to quantify the impacts of NbS. Finally, we suggest using a consistent and socially relevant set of indicators to evaluate the NbS and communicate this with stakeholders. In conclusion, our analysis demonstrates a need for more comprehensive and standardised evaluation of NbS, particularly in relation to their combined impacts on floods, droughts, and biodiversity.

The move towards unlimited financial penalties in the UK for sewerage systems that do not operate in line with their discharge permits (and the even more extreme suggestion that there should be a financial penalty every time an overflow spills) sets a challenge to whether our existing sewerage models are accurate enough to provide certainty of avoiding those penalties. This article sets out proposed improved practice in the preparation of urban drainage models to improve their accuracy and usefulness and identifies areas where research, particularly into machine learning techniques, could deliver further improvements.

Traditional cost-benefit analyses (CBAs) of flood risk reduction measures usually ignore distributions of damages over populations, which disadvantages the poor. Instead, a CBA based on social welfare includes individual social vulnerability through relative impacts on consumption. If vulnerabilities are high, floods are catastrophic and cause poverty, migration or indirect deaths, and risk reductions have high social welfare values. For non-catastrophic risks, social welfare values of risks are relatively higher for vulnerable low-income households. We present a framework to integrate social vulnerability into CBAs, and show how financial protection reduces social flood vulnerability and provides welfare benefits. A case study illustrates that traditional CBAs underestimate the social welfare value of flood risk reduction measures, up to a factor of 30. Data on financial protection is however scarce, which hampers estimation of the social welfare value in practice. A solution is to increase financial protection of individuals, in addition to offering physical flood protection.