Water temperature (WT) is a critical control for various physical and biochemical processes in riverine systems. Although the prediction of river water temperature has been the subject of extensive research, very few studies have examined the relative importance of elements affecting WT and how to accurately estimate WT under the effects of cascaded dams. In this study, a series of potential influencing variables, such as air temperature, dew temperature, river discharge, day of year, wind speed and precipitation, were used to forecast daily river water temperature downstream of cascaded dams. First, the permutation importance of the influencing variables was ranked in six different machine learning models, including decision tree (DT), random forest (RF), gradient boosting (GB), adaptive boosting (AB), support vector regression (SVR) and multilayer perceptron neural network (MLPNN) models. The results showed that day of year (DOY) plays the most important role in each model for the prediction of WT, followed by flow and temperature, which are two commonly important factors in unregulated rivers. Then, combinations of the three most important inputs were used to develop the most parsimonious model based on the six machine learning models, where their performance was compared according to statistical metrics. The results demonstrated that GB3 and RF3 gave the most accurate forecasts for the training dataset and the test dataset, respectively. Overall, the results showed that the machine learning model could be effectively applied to predict river water temperature under the regulation of cascaded dams.

The vertical slot fishway (VSF) is one of the most common types of fishway facilitating migratory fish movement past obstacles in rivers, such as dams. The uniform vertical distribution of velocity is friendly to fishes with different depth preferences, but unfriendly to fishes with different swimming capacities. For an established VSF, the insertion of an additional structure is a more convenient and effective way to change the flow field rather than altering the original elements. Numerical experiments were carried out using large-eddy simulation (LES) to optimize a typical VSF with supplementary cylinders for fishes with low swimming capacity. The computational domain of the original design is idealized as a box including two pairs of baffles with the periodic boundary condition used in the streamwise direction. The numerical model is well validated by comparison of time-averaged velocity and turbulence kinetic energy with the ADV measurements at gauging points and lines. Two arrangements of cylinders with different numbers and diameters were investigated and compared with the original design based on the first and second-order hydrodynamic statistics at the half height of the VSF. The insertion of cylinders significantly alters the flow field by introducing a branch path of relatively low-speed current. The arrangement of four slim cylinders slightly outperformed that of one thick cylinder against velocity homogeneity along the minor migration path. Although the turbulence intensity is enhanced due to the additional cylinders, the perturbation on fishes is not significant due to the small size of these vortices.

Lateral cavities along coastlines strongly influence sedimentary morphology and ecological processes by modifying local flow dynamics. This study employed high-resolution large-eddy simulation to investigate flow structures and momentum exchange mechanisms in a semi-circular lateral cavity driven by longshore currents. Model validation against experimental data confirmed the LES’s capability to capture both recirculating flow and turbulent structures accurately. The impact of Reynolds number was examined across three cases ($Re$ = 12,000, 17,000, and 22,000). From $Re$ = 12,000 to 17,000, a significant upstream shift of the primary vortex core occurred, accompanied by stronger shear layer turbulence and intensified secondary vortices. Between $Re$ = 17,000 and 22,000, the flow features stabilized, indicating a transition toward quasi-equilibrium. These changes enhanced vertical momentum transfer and turbulence production within the cavity. Spectral analysis revealed dominant KH frequencies governing periodic momentum exchange and indicating a transition from viscosity-damped upstream turbulence to fully developed shedding downstream.