Sources of uncertainty in a probabilistic flood risk model

Abstract

Flood risk models capture a variety of processes and are associated with large uncertainties. In this paper, the uncertainties due to alternative model assumptions are analysed for various components of a probabilistic flood risk model in the study area of Vorarlberg (Austria). The effect of different model assumptions for five aspects is compared to a reference simulation. This includes: (I, II) the selection of two model thresholds controlling the generation of large sets of possible flood events; (III) the selection of a distribution function for the flood frequency analysis; (IV) the building representation and water level derivation for the exposure analysis and (V) the selection of an appropriate damage function. The analysis shows that each of the tested aspects has the potential to alter the modelling results considerably. The results range from a factor of 1.2 to 3, from the lowest to highest value, whereby the selection of the damage function has the largest effect on the overall modelling results.

Event generation for probabilistic flood risk modelling: multi-site peak flow dependence model vs weather generator based approach

“…The representation of the dependence structure for simulation of extremes needs to be further improved for the weather generator. Nevertheless, the choice of method to generate heterogeneous flood events might have smaller impact than, for example, the choice of the applied damage functions (Winter et al, 2018).…”

“…Nonetheless, by applying and comparing different methods, the plausibility of the results can be checked (Molinari et al, 2019). Furthermore, the uncertainties related to the choice of methods to generate heterogeneous flood events seem to be lower in comparison to other aspects of the probabilistic flood risk model, such as the choice of the applied damage functions (Winter et al, 2018).…”

Multi-hazard risk assessment for roads: Probabilistic versus deterministic approaches

“…listed potential sources of uncertainties in risk assessment models and classified uncertainties into aleatory and epistemic uncertainties. The first is considered as inherent to a system associated to the natural variability over space and time (Winter et al, 2018) and the variability of underlying random or stochastic processes Thieken, 2005, 2009), which cannot be further reduced by an increase in knowledge, information or data. The latter results from incomplete knowledge and can be reduced with an increase of cognition or better information of the system under investigation Thieken, 2004, 2009;Grêt-Regamey and Straub, 2006).…”

“…Therefore, uncertainties should be included in the analysis by their upper and lower credible limits or by integrating confidence intervals reflecting the incertitude of input data, for an in-depth discussion see e.g. Apel et al (2004), Thieken (2004, 2009), Bründl et al (2009) and Winter et al (2018).…”

Flash flood risk assessment in urban arid environment: case study of Taibah and Islamic universities’ campuses, Medina, Kingdom of Saudi Arabia

“…However, the obtained results are useful for planning flood drainage and prevention measures. Winter et al (2018) studied uncertainties in flood risk models. Five variables, within the hydrologic and risk models, were studied.…”