To assess mitigation measures for habitat loss, it is important to understand the function of artificial wetlands as alternative wader habitat. In the Netherlands since 2016, a 1,000-ha freshwater archipelago called Marker Wadden has been constructed 3 km offshore in lake Markermeer. This artificial ecosystem provided a unique opportunity to study the impacts of construction designs and development of habitats on waders. Over a seven-year period, we studied Pied Avocets Recurvirostra avosetta because they used habitats in the constructed basins right from the start for feeding, and they are of conservation concern in the Netherlands. Between 2017 and 2023 we counted staging Pied Avocets and monitored habitat development in basins that varied in the time of construction (age) and design (closed or open, i.e. with breached levees connecting to the surrounding lake). Annual habitat changes were assessed with satellite images, and with pictures taken monthly at 20 fixed locations. With negative binomial zero-inflated models, we tested the effects of habitat characteristics, basin age, size and design, and raptor presence on bird numbers. The maximum number of Pied Avocets declined from >500 in 2017 to <100 in 2023. Basin age captured all habitat variation caused by natural succession and had the strongest negative effect on bird numbers. Open basins, allowing permanent flooding, were used less than closed basins. Avocet numbers remained highest in basins containing a mosaic of water and mud, with no or sparse vegetation. We concluded that Pied Avocets decreased due to two reinforcing processes: vegetation succession and breaching of levees leading to a rise in water level. Future developments targeting Pied Avocet conservation in freshwater wetlands should create and maintain shallow and muddy habitats with the closed basin and size concept as guidelines.

This work proposes a data-driven explicit algebraic stress-based detached-eddy simulation (DES) method. Despite the widespread use of data-driven methods in model development for both Reynolds-averaged Navier–Stokes (RANS) and large-eddy simulations (LES), their applications to DES remain limited. The challenge mainly lies in the absence of modelled stress data, the requirement for proper length scales in RANS and LES branches, and the maintenance of a reasonable switching behaviour. The data-driven DES method is constructed based on the algebraic stress equation. The control of RANS/LES switching is achieved through the eddy viscosity in the linear part of the modelled stress, under the $\ell ^2-\omega$ DES framework. Three model coefficients associated with the pressure–strain terms and the LES length scale are represented by a neural network as functions of scalar invariants of velocity gradient. The neural network is trained using velocity data with the ensemble Kalman method, thereby circumventing the requirement for modelled stress data. Moreover, the baseline coefficient values are incorporated as additional reference data to ensure reasonable switching behaviour. The proposed approach is evaluated on two challenging turbulent flows, i.e. the secondary flow in a square duct and the separated flow over a bump. The trained model achieves significant improvements in predicting mean flow statistics compared with the baseline model. This is attributed to improved predictions of the modelled stress. The trained model also exhibits reasonable switching behaviour, enlarging the LES region to resolve more turbulent structures. Furthermore, the model shows satisfactory generalization capabilities for both cases in similar flow configurations.

By generating drag and turbulence away from the bed, aquatic vegetation shapes the mean and turbulent velocity profile. However, the near-bed velocity distribution in vegetated flows has received little theoretical or experimental attention. This study investigated the near-bed velocity profile and bed shear stress using a coupled particle image velocimetry and particle tracking velocimetry system, which enabled the acquisition of flow-field measurements at very high spatial and temporal resolution. A viscous sublayer with a linear velocity profile was present, but this sublayer thickness was much smaller in vegetated flows than in bare flows with the same channel velocity. However, the dimensionless viscous sublayer thickness was the same in vegetated and bare flows, $z_v^+ = z_v \langle u_*\rangle / \nu = 6.1 \pm 0.7$. In addition, in vegetated flow, the horizontally averaged velocity profile above the viscous sublayer did not follow the classic logarithmic law found for bare beds. This deviation was attributed to the violation of two key assumptions in the classic Prandtl mixing length theory. By modifying the mixing length theory for vegetated conditions, a new theoretical power law profile for near-bed velocity was derived and validated with velocity data from both the present and previous studies, with mean percent errors of 4.9 % and 7.8 %, respectively. Using the new velocity law, the spatially averaged bed shear stress (and friction velocity) can be predicted from channel-average velocity, vegetation density and stem diameter, all of which are conveniently measured in the field.

We present an experimental study of convection–evaporation of a pool of water evaporating into a quiescent atmosphere. The temperature difference between the bottom of the pool and the surrounding air, as well as the water layer’s aspect ratio $\varGamma$, are systematically varied. Compared with classical Rayleigh–Bénard convection (RBC), this configuration involves a free-surface mechanical upper boundary and a mixed thermal upper boundary in contact with a poorly conducting air layer: evaporation extracts latent heat from the liquid and injects lighter vapour into the air, while radiation adds further cooling. As a result, neither temperature nor heat flux is fixed at the water–air interface, but they are instead strongly coupled. To characterise the respective contributions of convection, evaporation and radiation, we perform three sets of experiments: convection–evaporation, evaporation without bottom heating and convection without evaporation. High-resolution infrared imaging reveals multiple scales of convection at the surface: small hot plumes, cold sheet-like plumes and a large-scale circulation. The latter is constrained by the tank geometry for $\varGamma \lesssim 12$, but several turbulent superstructures develop for larger $\varGamma$. This is reminiscent of RBC but with different temperature statistics, due to the mixed boundary condition. Scaling laws are derived for interfacial transfers and mean surface temperature. Evaporation dominates heat extraction, accounting for 60 %–70 % of the flux, while radiation contributes 15 %–20 %. The release of vapour further enhances coupling between the liquid and air layers. When evaporation is blocked, radiation becomes dominant (70 %–80 %).These results have important implications for industrial and natural systems.

A time-domain model of an ice shelf interacting with ocean water in a finite domain is developed, which combines Kirchhoff–Love plate theory with the shallow-water wave equations. In particular, the domain is divided into an open-water region and a region in which the ocean is covered by an ice shelf. Boundary conditions, together with continuity conditions at the ice–water interface, lead to a nonlinear matrix eigenvalue problem, which is solved numerically to obtain the natural modes and frequencies of the system. These form the basis for reconstructing the transient response to wave forcing using a spectral method. Simulations show how wave packets excite multiple modes and generate interference patterns through boundary reflections. Since the method solves the initial value problem in a geometry containing both an open-ocean region and an ice-shelf-covered region, it provides a foundation for simulating sequential break-up of ice shelves due to wave-induced mechanical stresses, and contributes to broader efforts to model ice shelf disintegration under ocean forcing.