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.
Abstract Detailed measurements of motions, including turbulence structures, in high-concentration sediment flows are difficult, and their dynamics remain poorly understood. Interface-resolved large eddy simulation (IRLES) is a numerical simulation method that uses computational grids smaller than individual particles to resolve the flow using large eddy simulation and simultaneously solves the particle–fluid coupled motions. In this study, the turbulence structure of sediment flows was analyzed using IRLES. The IRLES simulations using gravel-shaped particles were conducted for uniform flows of sediment–water mixtures with uniform grain size under three different flume slope conditions: 6.4°, 10.5°, and 14.4°. The simulated particle volume concentrations of 0.086 (6.4°), 0.173 (10.5°), and 0.298 (14.4°) showed good agreement with predictions of the equilibrium sediment concentration equation, with a maximum error E c of 13%. Turbulence energy spectra of sediment flows were obtained at different heights to analyze turbulent structures. The simulations indicated that, in the steep-slope case, the peak of the turbulence energy for high-concentration sediment flows occurred closer to the free surface than in low-concentration flows. To clarify the characteristics of the turbulent energy spectra of sediment flows in comparison with those of water-only flows, an additional simulation was conducted for the 6.4° slope condition in which the bed particles were fixed. In the water-only simulation, the energy spectra, when nondimensionalized by the local turbulent kinetic energy, collapsed onto nearly the same curve at all heights. In contrast, in sediment flows, the decay of the energy spectrum at high wavenumbers became less pronounced with increasing particle concentration near the bottom of the flow. In high-concentration flows, this trend of reduced spectral decay at high wavenumbers persisted even near the free surface, indicating coexistence of vortices across different scales and complex vortex dynamics near the surface.
Abstract This work investigates the key scour protection techniques for bridge foundations of an inland river bridge—Chongqing Jiangjin Highway Yangtze River Bridge in China. It incorporates a water retaining wall, gabion cofferdam, geotextile, and solidified soil. The gabion cofferdam, in conjunction with the geotextile, is engineered to minimize the loss rate of the solidified soil during the infill process. Unidirectional flow of water surrounding the inland river bridge group pile foundation, with high vortex energy, renders the gabion susceptible to being swept away. To mitigate this risk, a water retaining wall was constructed upstream of the bridge abutment. The utilization of solidification technology to enhance the quality of waste material fosters a circular economy. The integration of solidified soil and the bridge pier foundation can restore the coordination of the riverbed’s stiffness and the bridge pier structure, thereby ensuring optimal stability and functionality of pier. In this case study, through numerical simulation analysis, a low-velocity environment is formed around the bridge piers with a water retaining wall height exceeding the water depth. The techniques of gabion placement and solidified soil grouting were explored. Through on-site measurement, the combined protection method effectively reduces the average flow velocity from 2.44 to 0.06 m / s , with a solidified soil loss rate of 9.92% during construction. Compared to riprap protection, the proposed method offers lower costs and superior protective performance in this case. This indicates that the proposed combined method holds broad application prospects for large-scale inland river bridges subjected to high-velocity unidirectional flow.
