Turbulences in liquids caused by jets can be of interest for numerous applications. For one, it concerns flood spillway structures within civil engineering but also is key in any area where turbulent mixing is present. The numerical simulations of jets that impinge into plunge pools are still in an early phase of their development. This paper verifies the accuracy of the Flow-3D software package in regards to simulating 3D scouring processes generated by turbulent water jets impinging on a sediment bed. Scour calculations are performed based on previously examined laboratory experiments. The results of the numerical model compare well with the experimental results in terms of the scour depth and the ridge height which accumulates downstream of the scour hole. The impact angle of the jet is identified as a driving parameter for the establishment of steady state conditions of scour depth and ridge height.

Sediment traps with partially open check dams are crucial elements for flood protection in alpine regions. The trapping of sediment is necessary when intense sediment transport occurs during floods that may endanger urban areas at downstream river reaches. In turn, the unwanted permanent trapping of sediment during small, non-hazardous floods can result in the ecological and morphological degradation of downstream reaches. This study experimentally analyses a novel concept for permeable sediment traps. For ensuring the sediment transfer up to small floods, a guiding channel implemented in the deposition area of a sediment trap was systematically studied. The bankfull discharge of the guiding channel corresponds to a dominant morphological discharge. At the downstream end of the guiding channel, a permeable barrier (check dam) triggers sediment retention and deposition. The permeable barrier consists of a bar screen for mechanical deposition control, superposed to a flow constriction for the hydraulic control. The barrier obstructs hazardous sediment transport for discharges that are higher than the bankfull discharge of the guiding channel without the risk of unwanted sediment flushing (massive self-cleaning).

Three‐dimensional (3d) numerical models are state‐of‐the‐art for investigating complex hydrodynamic flow patterns in reservoirs and lakes. Such full‐complexity models are computationally demanding and their calibration is challenging regarding time, subjective decision‐making, and measurement data availability. In addition, physically unrealistic model assumptions or combinations of calibration parameters may remain undetected and lead to overfitting. In this study, we investigate if and how so‐called Bayesian calibration aids in characterizing faulty model setups driven by measurement data and calibration parameter combinations. Bayesian calibration builds on recent developments in machine learning and uses a Gaussian process emulator as a surrogate model, which runs considerably faster than a 3d numerical model. We Bayesian‐calibrate a Delft3D‐FLOW model of a pump‐storage reservoir as a function of the background horizontal eddy viscosity and diffusivity, and initial water temperature profile. We consider three scenarios with varying degrees of faulty assumptions and different uses of flow velocity and water temperature measurements. One of the scenarios forces completely unrealistic, rapid lake stratification and still yields similarly good calibration accuracy as more correct scenarios regarding global statistics, such as the root‐mean‐square error. An uncertainty assessment resulting from the Bayesian calibration indicates that the completely unrealistic scenario forces fast lake stratification through highly uncertain mixing‐related model parameters. Thus, Bayesian calibration describes the quality of calibration and correctness of model assumptions through geometric characteristics of posterior distributions. For instance, most likely calibration parameter values (posterior distribution maxima) at the calibration range limit or with widespread uncertainty characterize poor model assumptions and calibration.