Abstract. We present a new method to generate spatially coherent river discharge peaks over multiple river basins, which can be used for continental event-based probabilistic flood risk assessment. We first extract extreme events from river discharge time series data over a large set of locations by applying new peak identification and peak-matching methods. Then we describe these events using the discharge peak at each location while accounting for the fact that the events do not affect all locations. Lastly we fit the state-of-the-art multivariate extreme value distribution to the discharge peaks and generate from the fitted model a large catalogue of spatially coherent synthetic event descriptors. We demonstrate the capability of this approach in capturing the statistical dependence over all considered locations. We also discuss the limitations of this approach and investigate the sensitivity of the outcome to various model parameters.

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With the ongoing development of distributed hydrological models, flood risk analysis calls for synthetic, gridded precipitation data sets. The availability of large, coherent, gridded re-analysis data sets in combination with the increase in computational power, accommodates the development of new methodology to generate such synthetic data. We tracked moving precipitation fields and classified them using self-organising maps. For each class, we fitted a multivariate mixture model and generated a large set of synthetic, coherent descriptors, which we used to reconstruct moving synthetic precipitation fields. We introduced randomness in the original data set by replacing the observed precipitation fields in the original data set with the synthetic precipitation fields. The output is a continuous, gridded, hourly precipitation data set of a much longer duration, containing physically plausible and spatio-temporally coherent precipitation events. The proposed methodology implicitly provides an important improvement in the spatial coherence of precipitation extremes. We investigate the issue of unrealistic, sudden changes on the grid and demonstrate how a dynamic spatio-temporal generator can provide spatial smoothness in the probability distribution parameters and hence in the return level estimates.

We present a new method to generate spatially coherent river discharge peaks over multiple river basins, which can be used for continental event-based probabilistic flood risk assessment. We first extract extreme events from river discharge time series data over a large set of locations by applying new peak identification and peak-matching methods. Then we describe these events using the discharge peak at each location while accounting for the fact that the events do not affect all locations. Lastly we fit the state-of-the-art multivariate extreme value distribution to the discharge peaks and generate from the fitted model a large catalogue of spatially coherent synthetic event descriptors. We demonstrate the capability of this approach in capturing the statistical dependence over all considered locations. We also discuss the limitations of this approach and investigate the sensitivity of the outcome to various model parameters.

Abstract. We present a new equation describing the hydrodynamics in infinitely long tidal channels (i.e., no reflection) under the influence of oceanic forcing. The proposed equation is a simple relationship between partial derivatives of water level and velocity. It is formally derived for a progressive wave in a frictionless, prismatic, tidal channel with a horizontal bed. Assessment of a large number of numerical simulations, where an open boundary condition is posed at a certain distance landward, suggests that it can also be considered accurate in the more natural case of converging estuaries with nonlinear friction and a bed slope. The equation follows from the open boundary condition and is therefore a part of the problem formulation for an infinite tidal channel. This finding provides a practical tool for evaluating tidal wave dynamics, by reconstructing the temporal variation of the velocity based on local observations of the water level, providing a fully local open boundary condition and allowing for local friction calibration.