The naked carp (Gymnocypris przewalskii) plays a central role in the ecosystem of the Qinghai Lake, the largest saline-alkaline lake in China. The adult naked carp migrates in large groups with high population density annually from the Qinghai Lake to the upstream freshwater rivers to spawn. Nevertheless, the responsiveness of the fish to local abiotic cues in the form of distribution patterns during migration across the riverine-lacustrine network of the Qinghai Lake region remains unknown. This knowledge gap has reduced efficiency in fish conservation and management efforts in the region. To address this issue, we carried out two field surveys from June to August, 2018, with the aid of unmanned aerial vehicles to a 200-m long back channel characterizing diverse morphological and hydraulic features on the migration route. Combined structure from motion photogrammetry and deep neural network techniques were used to establish a new workflow for detecting and extracting the profiles of fish individuals in large schools. The spatio-temporal distribution pattern of the fish demonstrated that the naked carp was attracted by hydraulic environments with high flow velocity or deep-water during migration. The diurnal variation of temperature and light could alter the preference for hydraulic environments of the fish. Our results highlight the crucial role of the interactions between river morphology and hydraulics, water temperature and light on the migration behaviours of the naked carp.

Structure-from-Motion (SfM) photogrammetry has become a popular solution for three-dimensional topographic data collection in geosciences and can be used for measuring submerged bed surfaces in shallow and clear water systems. However, the performance of through-water SfM photogrammetry has not been fully evaluated for gravel-bed surfaces, which limits its application to the morphodynamics of gravel-bed rivers in both field investigations and flume experiments. In order to evaluate the influence of bed texture, flow rate, ground control point (GCP) layout, and refraction correction (RC) on the measurement quality of through-water SfM photogrammetry, we conducted a series of experiments in a 70 m-long and 7 m-wide flume with a straight artificial channel. Bed surfaces with strongly contrasting textures in two 4 m-long reaches were measured under five constant flow regimes with three GCP layouts, including both dry and underwater GCPs. All the submerged surface models with/without RC were compared with the corresponding dry bed surfaces to quantify their elevation errors. The results illustrated that the poorly sorted gravel-bed led to the better performance of through-water SfM photogrammetry than the bed covered by fine sand. Fine sediment transport caused significant elevation errors, while the static sand dunes and grain clusters did not lead to noticeable errors in the corrected models with dry GCPs. The elevation errors of the submerged models linearly increased with water depth for all the tested conditions of bed textures, GCP layouts, and discharges in the uncorrected models, but the slopes of the increasing relations varied with texture. The use of underwater GCPs made significant improvements to the performance of direct through-water SfM photogrammetry, but counteracted with RC. The corrected models with dry GCPs outperformed the uncorrected ones with underwater GCPs, which could still be used to correct the underestimation in surface elevation caused by RC. Based on the new findings, recommendations for through-water SfM photogrammetry in measuring submerged gravel-bed surfaces were provided.

Step-pool systems are common bedforms in mountain streams and have been utilized in river restoration projects around the world. Step-pool units exhibit highly nonuniform hydraulic characteristics which have been reported to closely interact with the morphological evolution and stability of step-pool features. However, detailed information on the three-dimensional hydraulics for step-pool morphology has been scarce due to the difficulty of measurement. To fill in this knowledge gap, we established a combined approach based on the technologies of structure from motion (SfM) and computational fluid dynamics (CFD). 3D reconstructions of bed surfaces with an artificial step-pool unit built from natural stones at six flow rates were imported to CFD simulations. The combined approach succeeded in visualizing the high-resolution 3D flow structures for the step-pool unit. The results illustrate the segmentation of flow velocity downstream of the step, i.e., the integral recirculation cell at the water surface, streamwise vortices formed at the step toe, and high-speed flow in between. The highly nonuniform distribution of turbulence energy in the pool has been revealed, and two energy dissipaters of comparable magnitude are found to co-exist in the pool. Pool scour development during flow increase leads to the expansion of recirculation cells in the pool, but this expansion stops for the cell near the water surface when flow approaches the critical value for step-pool failure. The micro-bedforms (grain clusters) developed on the negative slope affect the local hydraulics significantly, but this influence is suppressed at the pool bottom. The drag forces on the step stones increase with discharge (before the highest flow value is reached). In comparison, the lift force consistently has a larger magnitude and a more widely varying range. Our results highlight the feasibility and great potential of the approach combining physical and numerical modeling in investigating the complex flow characteristics of step-pool morphology.