Abstract Understanding flow behavior in compound channels with floodplain vegetation is essential for modeling river hydraulics and ecohydraulics processes. This study conducted a controlled large-scale flume experiment in an asymmetric trapezoidal compound channel to examine the effects of emergent rigid cylindrical vegetation on mean flow, turbulence, momentum exchange, and coherent structures. Vegetated and nonvegetated sections were compared using water-level measurements and three-dimensional acoustic Doppler velocimetry. Floodplain vegetation intensified the velocity gradient at the main channel–floodplain interface, increasing turbulent kinetic energy and streamwise and lateral Reynolds stresses in the transition zone. The vegetated section developed a broader mixing layer and stronger coherent structures, as indicated by larger autocorrelation time scales and peaks in the lateral velocity spectra. Although normalized turbulence statics were consistent with laboratory-scale studies, the spatial and temporal scales of coherent structures were notably larger in the present large-scale experiment. These scale-dependent differences highlight that the need for scale-aware interpretation when using laboratory-derived turbulence and resistance parameters in compound-channel modeling. The data set provides a useful resource for validating numerical models and upscaling laboratory findings to field-relevant two-stage channel configurations.
Abstract A piano key weir (PKW) is a hydraulic control structure that offers significantly higher discharge capacity than its linear counterpart, primarily due to the extended effective spillway crest. When operated as in-channel applications, rising downstream water levels can interfere with free-flow conditions, causing submergence of the weir and reducing its hydraulic performance. Moreover, variations in tailwater levels as well as the weir geometry can significantly influence the hydraulics and flow patterns in the downstream reach of the weir. This study investigated the impact of tailwater on the downstream flow regime of an A-type trapezoidal PKW within an experimental model. By comparing flow velocities and flow depths with those observed downstream of a linear weir under similar boundary conditions, the influence of the weir geometry on downstream flow behavior was evaluated. Results indicate that the PKW generates a complex, three-dimensional flow field directly downstream of the weir, characterized by free-falling nappes and jet formations, whereas the linear weir induces a more two-dimensional flow structure. As tailwater levels increase, the visual complexity of the PKW flow diminishes, and both weir types exhibit reduced air entrainment due to decreased drop height. Energy dissipation at the PKW occurs more locally, driven by plunging jets and submerging nappes, whereas the linear weir promotes supercritical flow at low tailwater levels, followed by a hydraulic jump farther downstream. This shift in the dissipation zone may enhance the potential for sediment transport processes in the vicinity of the weir structure. Farther downstream, beyond the aerated region, velocity profiles evolve from logarithmic to irregular shapes, with decreasing boundary layer thickness at higher flow depths. This trend is less pronounced at the linear weir, for which profiles remain in a narrower range of profile development. However, the PKW has more distinct secondary flow effects, such as the velocity dip phenomenon, which intensifies with rising tailwater levels and across the channel width. Additionally, elevated bed shear stress and Reynolds numbers suggest increased turbulence relative to that of the linear weir, implying a greater potential for sediment transport. These findings highlight the importance of weir design and flow depth in influencing downstream flow behavior and hydraulic characteristics.
Abstract This study investigates the hydrodynamic and sediment-transport dynamics during a flash flood that occurred on February 23, 2024, in the San Antonio River, a tributary of the San Roque Reservoir in Córdoba, Argentina. Such events pose a significant hazard in urban and recreational rivers; however, their transient processes remain poorly understood, particularly regarding the onset of bed-load transport and the vulnerability of exposed individuals. High-resolution, stationary measurements were collected using an Acoustic Doppler Current Profiler (ADCP), generating time series of flow depth, velocity, and energy slope during the passage of the flood wave front. Sediment mobilization was assessed through the Shields–Parker diagram, and flow conditions were compared against human body stability criteria for both adults and children. Results indicate that the velocity rise preceded the increase in flow depth, reflecting an initial adjustment of the wave-front slope. During the flood arrival, during a 22-min interval, flow depth increased from 0.40 to 1.47 m, and velocity rose from 0.20 to 2.00 m / s . Bed-load transport initiated given higher velocities with nearly constant depth, followed by sustained transport and a sharp increase in suspended sediment presence. Regarding human safety, the applied body stability criteria indicate that instability thresholds were exceeded rapidly: within only 2 min for children and 3 min for adults after the onset of the rising limb, highlighting the high vulnerability of recreational areas. These findings emphasize the value of direct, high-resolution observations to better understand unsteady processes in flash floods and to provide key insights for risk management in urban and touristic river systems.
Abstract Although the classical steady and quasi-steady friction term often overestimates hydraulic head, it remains widely used in water hammer equations to simulate hydraulic transients in piping systems. Its popularity stems from its simple mathematical form and ease of implementation compared to unsteady friction models, particularly in complex networks. Within the method of characteristics (MOC) framework, this classical friction term for turbulent flows is typically integrated using explicit numerical schemes, producing linear finite difference equations that are straightforward and computationally efficient to solve. In contrast, more accurate implicit methods are often avoided due to the perceived need for nonlinear iterative schemes to resolve the resulting equations. This work introduces a unique closed-form analytical solution to the nonlinear algebraic recurrence equation governing discharge in the water hammer problem derived using the Crank–Nicolson approximation of classical turbulent friction. The proposed approach not only delivers second-order accuracy, which is unattainable with conventional explicit approximations, but also remains computationally efficient and robust, offering a superior alternative to existing methods. By evaluating a global normalized absolute error as a function of step size across multiple methods and a representative dimensionless governing parameter, we demonstrate that the improved accuracy offsets the modest increase in central processing unit (CPU) time. Specifically, the proposed methodology consistently reduces global mean errors by up to an order of magnitude compared with other second-order explicit methods, with only approximately a 60% increase in computational cost.
Abstract Traditional two-dimensional (2D) hydraulic models face significant computational challenges (e.g., long computing times) that limit their use in applications that are time-sensitive or require many model evaluations. This study presents a physics-informed deep-operator network (DeepONet) framework for computational hydraulics modeling that learns the solution operator of the 2D shallow water equations (SWEs) to create fast surrogate models. The framework can operate in two modes: a purely data-driven SWE-DeepONet that learns from a numerical solver such as Sedimentation and River Hydraulics–Two-Dimension (SRH-2D), and a physics-informed shallow water equations DeepONet (PI-SWE-DeepONet) that additionally incorporates the continuous SWEs as constraints during training. Based on a real-world case, steady flows in a reach of the Sacramento River in California, it is demonstrated that PI-SWE-DeepONet possesses much enhanced prediction capability than SWE-DeepONet when applied to out-of-distribution scenarios. The physics-informed model is shown to exhibit slower error growth and larger breakdown distances in the normalized inlet-discharge parameter space (the distance between an out-of-distribution case and the closest training sample) in comparison with SWE-DeepONet. The gain of the physics-informed training, however, comes with costs, chief among which is that the simulated results have slightly higher errors for in-distribution cases. It reflects the existence of a tension between the two competing training objectives: fitting the results from the traditional hydraulic model and satisfying the continuous governing equations. In this study, guidelines are developed for selecting the appropriate approach based on a real-world case: PI-SWE-DeepONet is preferred for out-of-distribution predictions, uncertain training data, or when physical consistency is a priority, while SWE-DeepONet is recommended if the modeling objective is to replicate faithfully the traditional hydraulic model results within the training distribution. Once trained, both surrogates evaluate a new scenario in less than one second on a single graphics processing unit (GPU), more than two orders of magnitude faster than a fresh SRH-2D run on the same case, which makes them suitable for applications requiring many model evaluations. Other challenges are also discussed, such as the loss weighting approach.
