Colin David Rennie

Riverine fish conservation in eco‐hydraulics is often based on restoring or regulating river habitat to a semi‐natural state. For example, ecohydraulic projects support fish populations by increasing river connectivity through fishways, and by maintaining or restoring natural flow variance to enhance habitat quality and availability. However, the application of these concepts is challenging due to climate change and human perturbations that can modify the riverine environment in unpredictable ways. To address these challenges, we propose broadening eco‐hydraulics to eco‐evo‐hydraulics by incorporating the evolutionary dynamics of fish populations into eco‐hydraulics. We argue that this may improve the resilience and resistance of fish populations to future climate and human perturbation. Moreover, the evolutionary response of fishes to perturbations also alters their capability to “zoogeomorphically engineer” their physical environment, with associated feedbacks such as changes in sediment mobilization. Thus, understanding such hydro‐evolutionary feedbacks can improve the long‐term prediction of river hydraulics. In this position paper, we explore the interactions between hydraulics, hydrology, and rapid evolution based on a literature review to identify gaps and opportunities that need joint efforts from water resources engineers and evolutionary biologists. We propose the concept of eco‐evo‐hydraulics with hydro‐evolutionary feedbacks to encapsulate the interactions between the three disciplines, and suggest research avenues for the future. Finally, we suggest potential managerial strategies based on the eco‐evo‐hydraulic concept for local and basin‐wide fish conservation. We aim to fill the gap between water resources management and evolutionary biology to provide a new theory for fish conservation.

Ice-cover roughness perturbs velocity and momentum distributions, leading to secondary flow redistribution within river channels. Particle image velocimetry measurements examined the effects of ice roughness on secondary flow at the apex of a 135° bend under two different simulated ice covers. Both flows produced a two-layer flow structure, with roughness strongly influencing cell position and intensity. Under rough ice, the top-layer inner-bank cell (IBC) observed in the smooth ice case merged with the primary vortex, forming a single dominant vortex that was shifted toward the inner bank. While the total circulation in the ice-layer decreased, the bottom-layer vortex circulation increased with roughness. A three-dimensional (3D) momentum analysis showed vertical momentum with intensified downward flux from the ice layer and enhanced upward flux from the bed. Cross-stream momentum was characterized by concentrated high-intensity zones near the inner bank, indicating roughness-induced lateral redistribution. Roughness had a greater effect on the vertical and cross-stream components of momentum than on the streamwise momentum. The rough ice cover induced greater turbulence across the cross section from outer to inner bank, with a localized decrease near the bed layer adjacent to the inner bank. Increased turbulence under rough ice facilitated the observed merging in the ice layer of the IBC with the primary circulation cell. Momentum and turbulence responses suggest that IBC formation and stability are shaped by boundary morphology and, under rough ice, involve structural reorganization and integration into the primary circulation.

Eco-hydraulics traditionally aims at managing riverine systems in a semi-natural state while meeting human demands, assuming aquatic species are static. However, evidence of rapid evolution suggests that ignoring evolutionary dynamics of fish species might limit long-term effectiveness of eco-hydraulics frameworks. It remains unclear how freshwater fish adapt to human perturbation. Why are some fish populations more resilient to human perturbation than others? What are the genetic mechanisms behind it? To answer these questions, we genotyped eleven populations of three-spined stickleback in a regulated river system and collected data on river morphology, connectivity, flow regimes, physico-chemistry and parasite abundance through a combination of field surveys and modelling. Gene-environment association analysis detected strong signals of genetic divergence associated with hydraulic features. Gene ontology analysis revealed evolutionary responses that primarily involve functions in the nervous and sensory systems. These findings demonstrate that fish can evolve in response to river regulation, highlighting the need to transition from eco-hydraulics toward eco-evo-hydraulics.

This study examines the effects of combined ship-generated waves and wind-driven waves on sediment dynamics in the upper St. Lawrence River, focusing on two sites at Mariatown and Jacobs Island in Ontario, Canada. Six loggers installed at the two study sites recorded wave and turbidity data over a period of 300 days to distinguish the influences of natural versus ship-induced waves on sediment resuspension. The findings indicate that wind-driven waves regularly resuspend sediment, establishing a baseline turbidity level, while ship-generated waves cause short-lived but intense turbidity spikes, particularly in shallow zones with fine sediment. Spectral signal analyses, including synthetic natural wave modeling and frequency-based filtering, are used to isolate the frequency characteristics of primary and secondary ship-generated waves from those of natural wind waves, enabling a focused assessment of each wave type’s impact on sediment dynamics. Wavelet analysis is applied as a validation tool to confirm the spectral localization of separated wave components. The study demonstrates that factors such as water depth, sediment type, and proximity to the navigation channel strongly influence local turbidity responses. While historical shoreline imagery is used to provide spatial context, shoreline change was not formally analyzed in this study. Overall, the results offer a replicable framework for isolating wave contributions to sediment resuspension and support future efforts in sustainable sediment and shoreline management in modified river environments.

Landscape scale bedrock erosion is the integration of bedrock erosion at the reach scale, which is driven by particle impacts from sediment transport caused by near‐bed hydraulics. Plunging flow hydraulics have been identified in bedrock canyons and cause velocity profile inversions, which enhance near‐bed velocities, sediment transport, and the potential for bedrock erosion. Observations of plunging flows are limited, and the frequency and statistical properties of this hydraulic phenomenon have not been investigated. Here, we define metrics to identify velocity inversions and use them to detect instances of plunging flows through a 375 km reach of the Fraser River where channel morphology is controlled by bedrock. Isolated plunging flows are identified as well as plunging flow complexes where a series of plunges cause the core of maximum velocity to remain depressed in the water column for a prolonged distance. A significant relationship between plunging flows and bedrock exposure is identified, and plunging flows occupy more than half of the bedrock confined reaches. Stronger plunging flows are correlated with deeper and narrower channels with higher maximum shear stresses. Plunging flows are also concentrated in steeper reaches, which likely represent knickzones in the river profile. We use particle abrasion‐based bedrock erosion models to show that plunging flows drive reach‐scale incisions in bedrock rivers, creating deep bedrock pools. These pools dominate the incision into the bedrock, which sets the base level for their drainage areas and in turn sets the pace of landscape evolution.

Tailings dam breach modelling studies have received considerable attention recently due to the rise in the number of tailings dam failures and catastrophic consequences caused by downstream flooding. Numerical models are useful tools in risk management for assisting urban planners in planning for the safe evacuation of the vulnerable communities located downstream in the so-called “shadow area” of such dams. Several challenges and uncertainties exist when conducting risk assessments of tailings dam failure. In this study, recent advances in modelling approaches for tailings dam breach analysis and downstream flood wave routing are summarized and critically reviewed. This study evaluates different mudflow modelling studies that involve single-phase, quasi-two-phase, and two-phase modelling approaches; dam breach outflow modelling; tailings rheological characterization; and application of geographic information system (GIS) and remote sensing to tailings dam breach analysis. Recommendations for further research are provided based on the findings. In addition, this study will help dam engineers and practitioners to maintain industry standards and include state-of-the-art practices in their work.

The incapability of processing flow velocities under low tracer density conditions is one of the limitations of the traditional Large-Scale Particle Image Velocimetry (LSPIV). This study developed a new LSPIV algorithm, Time Frequency Analysis (TiFA), to overcome such a limitation, enhance computational efficiency, and improve the accuracy of derived velocities. TiFA investigates the temporal joint distribution pattern of two velocity components at each location. By assuming that the valid velocities follow a quasi-normal distribution in the velocity time series, TiFA can quickly and accurately separate the valid velocities from background noise and outliers. The performance of TiFA was evaluated by comparing with other algorithms including Traditional LSPIV, Ensemble Correlation (EC), Large-Scale Particle Tracking Velocimetry (LSPTV), and Seeding Density Index (SDI) in an experimental hydraulic model and two field cases. TiFA showed the highest overall accuracy and lowest computation cost in data analysis, especially under low tracer density conditions. In addition, TiFA showed its unique ability of automatically filtering out velocity data from low-quality zones such as no-tracer zones and surface glare zones. TiFA also showed its potential in processing turbulent flow. In summary, the newly-developed algorithm, TiFA, has demonstrated strong capability and competence in various flow and tracer scenarios, making it a valuable candidate for future applications.