Abstract. The derivation of flood risk maps requires an estimation of maximum inundation extent for a flood with a given return period, e.g. 100 or 500 yr. The results of numerical simulations of flood wave propagation are used to overcome the lack of relevant observations. In practice, deterministic 1-D models are used for flow routing, giving a simplified image of flood wave propagation. The solution of a 1-D model depends on the initial and boundary conditions and estimates of model parameters which are usually identified using the inverse problem based on the available noisy observations. Therefore, there is a large uncertainty involved in the derivation of flood risk maps. Bayesian conditioning based on multiple model simulations can be used to quantify this uncertainty; however, it is too computer-time demanding to be applied in flood risk assessment in practice, without further flow routing model simplifications. In order to speed up the computation times the assumption of a gradually varied flow and the application of a steady state flow routing model may be introduced. The aim of this work is an analysis of the influence of those simplifying model assumptions and uncertainty of observations and modelling errors on flood inundation mapping and a quantitative comparison with deterministic flood extent maps. Apart from the uncertainty related to the model structure and its parameters, the uncertainty of the estimated flood wave with a specified probability of return period (so-called 1-in-10 yr, or 1-in-100 yr flood) is also taken into account. In order to derive the uncertainty of inundation extent conditioned on the design flood wave, the probabilities related to the design wave and flow model uncertainties are integrated. In the present paper we take into account the dependence of roughness coefficients on discharge. The roughness is parameterised based on the available observed historical flood waves. The approach presented allows for the relationship between flood extent and flow values to be derived thus giving a cumulative assessment of flood risk. The methods are illustrated using the Warsaw reach of the River Vistula as a case study. The results indicate that the uncertainties have a substantial influence on flood risk assessment.
Maximizing the usefulness of flood risk assessment for the River Vistula in Warsaw
