Hydrodynamic river models are applied to design and evaluate measures for purposes such as safety against flooding. The modelling of river processes involves numerous uncertainties, resulting in uncertain model outcomes. Knowledge of the type and magnitude of uncertainties is crucial for a meaningful interpretation of the model results and the usefulness of results in decision making processes. The aim of this study is to identify the sources of uncertainty that contribute most to the uncertainties in the model outcomes and quantify their contribution to the uncertainty in the model outcomes. Experts have been selected based on an objective Pedigree analysis. The selected experts are asked to quantify the most important uncertainties for two situations: (1) the computation of design water levels and (2) the computation of the hydraulic effect of a change in the river bed. For the computation of the design water level, the uncertainties are dominated by the sources that do not change between the calibration and the prediction. The experts state that the upstream discharge and the empirical roughness equation for the main channel have the largest influence on the uncertainty in the modeled water levels. For effect studies, the floodplain bathymetry, weir formulation and discretization of floodplain topography contribute most to the uncertainties in model outcomes. Finally, the contribution of the uncertainties to the model outcomes show that the uncertainties have a significant effect on the predicted water levels, especially under design conditions.

Hydrodynamic vegetation density, the sum of the projected plant area per unit volume, is an important parameter for floodplain flow models. This paper compares two novel techniques to quantify this parameter in the field: terrestrial laser scanning (TLS) and digital parallel photography (PP). Separate field reference data were collected for the two methods, which consisted of (1) a stem map of 650 trees, aggregated into 23 plots in a single forest patch, (2) 17 manually measured forest plots in two floodplains. PP consists of a series of digital photographic images of vegetation against a contrasting background. The centre columns of all images were merged into a single composite parallel image. This mosaic was thresholded to determine the fractional coverage of the vegetation, which is converted to vegetation density using the optical point quadrat method. A sensitivity analysis proved that PP is insensitive to small errors on the selected number of centre columns, photograph spacing should not exceed 20 cm, photograph resolution is important and the plot depth should be measured accurately. TLS was carried out using a Leica HDS3000 time‐of‐flight laser scanner. Data processing of TLS data consisted of slicing the points around breast height. In a polar grid the vegetation density was predicted using the optical point quadrat method, corrected for missing points. Both methods were compared to the field reference data. PP (EF = 0.99; bias = 8.4×10⁻⁵ m⁻¹) showed a higher modelling efficiency than the TLS method (EF = 0.63; bias = 0.015 m⁻¹). An advantage of the TLS method is the ability to provide a detailed 2‐dimensional or even 3‐dimensional distribution of vegetation density. PP is cheaper, faster, and data processing is limited. We conclude that TLS and PP are two complementary techniques that show high accuracies for field measurements of vegetation density.

Coping with uncertainties is inherent to river management planning and policymaking. Yet, policymakers often perceive uncertainty as a complicating factor. We examine the challenges faced by policymakers when coping with uncertainties and provide an action perspective on how to best cope with these challenges to inform the policy debate. Integrating social and natural scientist’s perspectives on uncertainties and learning theories, we present a holistic, management perspective for coping with uncertainty. Based on a literature review about uncertainty concepts, strategies and learning, we identify three challenges in current river management: balancing social and technical uncertainties, being conservative and avoiding to end up a lock-in situation. We then provide a step-wise strategy and concrete actions for policymakers, which are illustrated with several examples. We conclude that coping with uncertainty may require paradigm shifts that can only be achieved through organisational learning. This, we claim, requires reflection, learning and flexibility of policymakers and their organisation.

River dunes are wavelike features in sandy riverbeds that move slowly in a downstream direction. These bedforms are shaped by the interaction between flowing water and sand grains at the riverbed. Understanding river dune dynamics is essential to determine sediment transport and optimize river maintenance. Earlier research mainly focused on river dune dynamics during high flows; therefore, low‐flow dune dynamics are hardly understood. In this study, we analyzed dune dynamics in a unique data set of 10 years of biweekly bed elevation profiles of the Rhine River, focusing on low‐flow conditions. Here, we show that dunes migrate and become lower and longer during low flows, while current literature states that dunes should become shorter. This dune migration and lengthening at low flows is a new finding and is linked to diffusive dune migration processes that become more relevant when sediment transport is just above incipient motion.