The effect of sediment transport models on simulating river dune dynamics

River dunes, dynamic bedforms in the river bed, limit navigable depths during low flows and increase bed roughness. To predict the navigable depth or where maintenance dredging is needed, a numerical dune development model can be a powerful tool. To study the effect of sediment transport on dune shape and propagation, four different sediment transport models were applied in an existing dune development model. Each sediment transport model was able to simulate dune propagation, while only sediment transport models based on the shear stress reshaped the river dunes. The tested sediment transport models can simulate dune celerity similar to observations and realistic, though different, dune shapes for low and median discharges. Implementation of a gravitational bed slope effect combined with a critical shear stress results in low angle dunes, which are representative for river dunes during low river flows. Sediment transport models with spatial relaxation, also result in low angle dunes. However, the relaxation parameters need to be redefined for low flow situation to prevent transition to upper stage plane bed at too low flow velocities. Further analysis of the resulting dune shapes shows that the sediment transport model determines the dune shape in terms of slope angles, while the dune height is related to the total transport capacity

Identification and quantification of uncertainties in a hydrodynamic river model using expert opinions

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. \u

Coping with Uncertainty in River Management:Challenges and Ways Forward

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