Stochastic generation of spatially coherent river discharge peaks forlarge-scale, event-based flood risk assessment

Abstract. Flood risk assessments are required for long-term planning, e.g. for investments in infrastructure and other urban capital. Vorogushyn et al. (2018) call for new methods in large-scale Flood Risk Assessment (FRA) to enable the capturing of system interactions and feedbacks. With the increase of computational power, large-scale, continental FRAs have recently become feasible (Ward et al., 2013; Alfieri et al., 2014; Dottori et al., 2016; Vousdoukas, 2016; Winsemius et al., 2016; Paprotny et al., 2017). Flood events cause large damages worldwide (Desai et al., 2015). Moreover, widespread flooding can potentially cause large damage in a short time window. Therefore, large-scale (e.g. pan-European) events and for instance maximum probable damages are of interest, in particular for the (re)insurance industry, because they want to know the chance of their widespread portfolio of assets getting affected by large-scale events (Jongman et al., 2014). Using a pan-European data set of modelled, gridded river discharge data, we tracked discharge waves in all major European river basins. We synthetically generated a large catalogue of synthetic, pan-European events, consisting of spatially coherent discharge peak sets.