An hourly-scale scenario-neutral flood risk assessment in a mesoscale catchment under climate change

Reliable assessments of flood risks are essential to formulate robust adaptation policies to climate change. Although the scenario-neutral flood assessments have reduced the dependency on uncertain climate predictions, coarse temporal resolutions of rainfall-runoff modelling adopted for the stress tests may introduce appreciable bias to flood risks driven by climatic stresses. To refine the temporal scale of flow estimates, this study proposes to incorporate a multiplicative random cascade (MRC) scheme and a simple catchment model in the bottom-up flood risk assessment. Results showed that use of a daily flow indicator for the stress tests could considerably underestimate the impact of climatic change on flood risks. The non-linearity between daily and hourly peak flows could increasingly amplify flood risks as the mean and variance of daily precipitation become greater in the study catchment. The first-order catchment model combined with the MRC could acceptably estimate hourly peak flows and the catchment recession behaviours at high flows. This study suggests that subdaily flood indicators should be used in the scenario-neutral assessments for small or mesoscale catchments to prevent underprediction of flood risks. To expand the applicability of the bottom-up framework, we also suggest developing efficient tools that can perturb high-resolution weather time series for the stress tests.