The transition towards a new risk approach for the Dutch national safety assessment of primary flood defences has been taken as an opportunity to improve the dealings with uncertainties. The probabilistic models for the new safety assessment (WBI2017) not only deal with the natural variability, but also with so-called epistemological uncertainties. One class of epistemological uncertainties is the model uncertainty in the hydrodynamic models used. The quantification of the water level uncertainty depends on the dominant hydraulic processes in each water system and is chosen to be independent of the return period. However, water level frequency lines derived including model uncertainty sometimes conflict with the physics. A comparative analysis is carried out to assess the performance of Hydra-NL w.r.t. observations and to analyse if physical processes that play an important role in each fresh water system are represented correctly after the inclusion of model uncertainty with the WBI2017 method. This study showed that the estimated exceedance probability of actual water levels in the tidal river area and lake area are often overestimated by the Hydra-model even without model uncertainty. When model uncertainties are included the overestimations become even larger. Furthermore, the inclusion of model uncertainty sometimes gives an incorrect representation of the underlying physical processes. The effect of the model uncertainty gets larger when the water level frequency line becomes flatter. This is e.g. the case at locations where the water levels are influenced by the closure of the Europoortkering and upstream of the flood channel near Veessen-Wapenveld. It can be argued that water level uncertainties are likely to decrease in these situations, because a reservoir is more predictable than a flowing river and the operation of the flood channel results in an enlarged conveyance that is less sensitive than an average river profile. The hypothesis that the inclusion of model uncertainty according to WBI2017 results in an incorrect representation of the underlying physical processes is further analysed for several case studies in the upper river area and the lake area. Varying river schematisations and two river interventions (flood channel and retention area) are modelled to compare the WBI2017 method with a more physics-based approach. In this physics-based approach the hydraulic roughness of the main channel and/or floodplains is incorporated as additional stochastic variable for the derivation of water level frequency lines. It is shown that the water level uncertainty becomes smaller for wide rivers where the water level frequency line becomes flatter. The cases where river interventions are present the water level uncertainty is bounded, because of the environment/geometry that influences the water levels. According to the physics-based method the water level uncertainties are location and discharge dependent, which are both not integrated in the WBI2017 method. For the lake area the focus is on locations where high water levels are predominantly determined by the wind that is causing a set-up on the lake. By considering an empirical parameter of the "capped Wu" formula as additional stochastic variable the uncertainty of the drag coefficient is modelled for the physics-based method. The physics-based method demonstrates that the water level uncertainty is larger for higher decimate heights and vice versa. It can be concluded that it is not valid to choose one uniform standard deviation of the water level for all wind-dominated locations, as it is done for WBI2017. It is recommended to include the model uncertainty by considering a model parameter in the hydrodynamic model for the upper river area and lake area as additional stochastic variable in the Hydra-models, to model uncertainty in the water level. In other water systems it becomes more complex, because several equally important sources of uncertainty are present. Still, the most important model uncertainty sources could considered stochastically, but computational effort would become the limiting factor

The direct measurement of discharges in rivers can be time-consuming and costly. The discharge is commonly estimated indirectly by means of a curve, relating water level to discharge. This so-called rating curve is traditionally determined by fitting a curve to a number of observations, which induces several uncertainties and difficulties: 1) the curve is approximated by a function type, 2) in general there are no observations for high flow conditions and 3) it needs to updated regularly due to cross sectional changes. In this research a physics-based rating curve is developed and evaluated that is more reliable and easy to update. By the use of a photogrammetry techtnique 3D surface maps of river banks are generated by pictures obtained from an Unmanned Aerial Vehicle (UAV). The topography of the main channel is determined by using an Acoustic Doppler Current Profiler (ADCP) or it is approximated by the making use of expert judgement and the method developed by Lane (relates the water depth of the channel to the width and natural angle of repose). By knowing the geometric profile of a river reach, only the roughness coefficient and water surface slope are the unknown parameters to derive the rating curve, where the Manning’s formula acts as the basis of the rating curve. In this way, the rating curves can be made physically substantiated and the calibration parameter is the combination of roughness and water surface slope. Instead of using the power law function as a approximate function of the rating curve, it is used as approximation of the conveyance-water level relationship. Therefore, the exponents in the power law function are physical substantiated and reduce uncertainties in the extrapolation zone of the traditional method, because the profile during high flow conditions is also known. Further more, the local invariabilities that are specific to single cross-section analyses are minimized by analysing river reaches. It is demonstrated that local invariabilities arises easily in natural rivers that are causing non-uniform flows, which make in general the the open-channel flow analysis much more complex. However, the average conveyance of a reach may led to the a valid assumption of a uniform flow (which is part of the assumption in the Manning’s formula), depending on how the local variabilities behave. The calibration of rating curves are much easier compared with the traditional way. Instead of collecting new discharge measurements during dispersed flows, you just have to visit the area ones with a drone and surveying equipment. During this visit, the new new geometric profile can be captured and the rating curve can be updated, assuming that the roughness and water surface slope remains constant.