Floods are among the most common and devastating natural hazards worldwide. A key challenge is to select and implement efficient measures to reduce the flood risk, within limitations of budget, time, space, and societal acceptance. Interactions between joining rivers in flood plains and cities lead to several challenges in flood risk studies. Typical ‘critical’ events of such river systems may differ as small (large) rivers are affected by short duration-high intensity (long duration large volume) rainfall events. The challenges are 1) to define design flood conditions (design events) for systems on which the flood resistance measures can be based, e.g. dimensions of measures like levees or reservoirs, and 2) to understand and determine the risk and consequences that a flood can cause. A multivariate analysis is needed to account for the interactions and statistical dependencies (Bender et al., 2016). Copula functions have been applied in different fields as a multivariate method. Nevertheless, its application in risk analysis for river confluences still needs further evaluation.
In this thesis, the objective is to develop a methodology to determine design flood events that account for the different statistical dependencies and interactions between joining rivers, and that balances the required simulation time with the required accuracy of the results. For this objective, we evaluated the different statistical dependencies and interactions of joining rivers according to the catchment characteristics for each model domain: meteorological, hydrological, and hydraulic. First, identifying how the extreme precipitation events (meteorological) of neighbouring catchments are correlated, and evaluating the differences whit correlations of extreme river discharge events (hydrological). Second, we performed hydraulic simulations at a confluence to evaluate the hydraulic interactions of the joining rivers and the flood impacts, from which a response function was obtained. Subsequently, we evaluated the flood risk by implementing an approach to sample combinations of discharges of joining rivers, and determining the flood impacts from the response function. The developed approach consists of three main steps: 1) the selection of the extremes sets at the confluence, 2) the estimation of the copula parameters and 3) Monte Carlo simulations where the discharges of joining rivers are sampled from their respective marginal probability distributions, and the flooded area is calculated by using the response function. The dependence between the two joining rivers is taken into consideration by using a copula (Gaussian, Gumbel, or Clayton) to construct the joint distribution of the confluence from the marginal distributions.