A hybrid method for the incompressible Navier-Stokes equations is presented. The method inherits the attractive stabilizing mechanism of upwinded discontinuous Galerkin methods when momentum advection becomes significant, equal-order interpolations can be used for the velocity and pressure fields, and mass can be conserved locally. Using continuous Lagrange multiplier spaces to enforce flux continuity across cell facets, the number of global degrees of freedom is the same as for a continuous Galerkin method on the same mesh. Different from our earlier investigations on the approach for the Navier-Stokes equations, the pressure field in this work is discontinuous across cell boundaries. It is shown that this leads to very good local mass conservation and, for an appropriate choice of finite element spaces, momentum conservation. Also, a new form of the momentum transport terms for the method is constructed such that global energy stability is guaranteed, even in the absence of a point-wise solenoidal velocity field. Mass conservation, momentum conservation and global energy stability are proved for the time-continuous case, and for a fully discrete scheme. The presented analysis results are supported by a range of numerical simulations.

We hindcast a 110 year period (1860–1970) of morphodynamic behavior of the Western Scheldt estuary by means of a 2‐D, high‐resolution, process‐based model and compare results to a historically unique bathymetric data set. Initially, the model skill decreases for a few decades. Against common perception, the model skill increases after that to become excellent after 110 years. We attribute this to the self‐organization of the morphological system which is reproduced correctly by the numerical model. On time scales exceeding decades, the interaction between the major tidal forcing and the confinement of the estuary overrules other uncertainties. Both measured and modeled bathymetries reflect a trend of decreasing energy dissipation, less morphodynamic activity, and thus a more stable morphology over time, albeit that the estuarine adaptation time is long (approximately centuries). Process‐based models applied in confined environments and under constant forcing conditions may perform well especially on long (greater than decades) time scales.

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An engineered alluvial river (i.e., a fixed‐width channel) has constrained planform but is free to adjust channel slope and bed surface texture. These features are subject to controls: the hydrograph, sediment flux, and downstream base level. If the controls are sustained (or change slowly relative to the timescale of channel response), the channel ultimately achieves an equilibrium (or quasi‐equilibrium) state. For brevity, we use the term “quasi‐equilibrium” as a shorthand for both states. This quasi‐equilibrium state is characterized by quasi‐static and dynamic components, which define the characteristic timescale at which the dynamics of bed level average out. Although analytical models of quasi‐equilibrium channel geometry in quasi‐normal flow segments exist, rapid methods for determining the quasi‐equilibrium geometry in backwater‐dominated segments are still lacking. We show that, irrespective of its dynamics, the bed slope of a backwater or quasi‐normal flow segment can be approximated as quasi‐static (i.e., the static slope approximation). This approximation enables us to derive a rapid numerical space‐marching solution of the quasi‐static component for quasi‐equilibrium channel geometry in both backwater and quasi‐normal flow segments. A space‐marching method means that the solution is found by stepping through space without the necessity of computing the transient phase. An additional numerical time stepping model describes the dynamic component of the quasi‐equilibrium channel geometry. Tests of the two models against a backwater‐Exner model confirm their validity. Our analysis validates previous studies in showing that the flow duration curve determines the quasi‐static equilibrium profile, whereas the flow rate sequence governs the dynamic fluctuations.