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Numerical Study on Fish Collection and Transportation Facility with Water Temperature Compensation

Power China Huadong Engineering Corporation Limited, Hangzhou 311122, China
College of Environment, Hohai University, Nanjing 210098, China
Author to whom correspondence should be addressed.
Water 2023, 15(18), 3185;
Submission received: 10 July 2023 / Revised: 16 August 2023 / Accepted: 4 September 2023 / Published: 7 September 2023
(This article belongs to the Section Hydraulics and Hydrodynamics)


Fish collection and transportation facilities have been widely constructed as man-made passages that allow fish to bypass dams. These facilities usually provide proper conditions that attract and gather fish inside, and then transport them upstream over the dam. A novel design that includes water temperature compensation was presented, and the velocity, temperature distribution, and turbulent kinetic energy inside the fish collecting channel were studied using numerical tools. The facility mixes the warm cooling water from the electrical transformer with the tailwater in order to reduce the negative ecological effect of the low-temperature discharge. It can operate under a 2 m water level range in the tailrace channel. The numerical results show that the temperature inside the fish collecting channel increased by about 2 °C and settled within the suitable range of the target fish species. The water body maintained a relatively uniform and steady temperature. The velocity and the turbulence kinetic energy (TKE) field near the fish entrance were distinct from those of the background and were beneficial for fish migration. This study could potentially motivate ecological engineers to mitigate the negative impacts of low-temperature tailwater from hydropower plants when designing fish collection and transportation facilities.

1. Introduction

Fish are the most dynamic components of aquatic ecosystems. Their life cycles and populations are disrupted by the presence of dams and locks that interrupt their natural habitats and migration patterns. Fishways and fish collection and transportation facilities are common structures used to restore the connectivity of rivers for fish migration. A fishway is an open channel that is convex inside or contains baffles or orifices [1]. The water cascades dissipate the kinetic energy and slow down the water velocity, making them suitable for the swimming capacity of fish. Fishways are usually applied to low dams and locks. The longer the fishway is, the harder it is for the fish to swim upstream. Fish collection and transportation facilities overcome the limits of fishways, as they use machinery to aid fish in their migration, so that a fish does not consume its own energy.
There are different types of fish collection and transportation facilities. The collection facility can be a floating platform, a near-shore fixed platform, a fishway, a fish collecting channel, etc. The transportation facility can be a light truck, a track trolley, a cable car, an elevator, etc. The fish collection and transportation facility is very flexible in its potential to fit different dams and terrains, and it is sometimes an economical solution. Fish collection and transportation facilities have been applied to many projects all around the world. A juvenile fish collection, transportation, and bypass facility was applied at Little Goose Dam, US, in 1971 and rebuilt in 1990 [2,3]. The new facility comprises a collection channel, a dewatering machine, a bypass flume, and other assistant parts. It is able to handle 3 to 3.5 million juvenile salmonids and over 3000 adult salmonids annually, according to estimations. There are detailed records from the St. Stephen fish lift in the US, spanning the period from 1987 to 2014, which show that the number of bypassing fish varied between 0.2 and 0.6 million annually between 2010 and 2014. The dominant species observed were American shad (Alosa sapidissima) and blueback herring (Alosa aestivalis), which accounted for over 98% of the bypassing fish. A fish lift was also built in the tailrace of the Golfech–Malause hydroelectric complex in France [4]. This fish lift lifts the holding tank from the tailrace up to a transfer canal. Its efficiency for returning Atlantic salmon was studied using the radio-tag telemetry method, which 9 out of 19 individuals succeeded in passing. The successful individuals spent most of their time near the V-shaped entrance of the downstream guidance flume, which suggested that the flow there was less attractive. Two fish lifts were built at the Holyoke Dam, located in the tailrace and spillway [5]. The attraction of adult American shad to fish lifts was studied using the radio telemetry method. During 1980 and 1981, 18 out of 34 tagged individuals returned to the study area after their release; 9 out of 18 returnees were lifted upstream—7 via the tailrace lift, and 2 via the spillway lift. Other returnees were repelled by the turbulent flow in the tailrace or somehow became lost and could not find the entrance to the lift. The overall success rate of the two fish lifts was 26.5%. A trap-and-truck fish bypass system was applied in the Santa Clara Dam, Brazil [6,7]. In one reproductive season, 67,841 individuals of 32 species passed the lift. The efficiency rate, estimated using the mark recapture method, ranged from 0.2% to 16.1% for various species. The average was 7% for migratory species. The applicability of fish lifts for Palaemonidae shrimp was also studied, since the fish lift could be an alternative for Palaemonidae migration, but for a lack of pertinence to the shrimp. As mentioned above, the attraction of the entrance is vital to the whole facility, and the basic formation is a flume with a vertical V-shaped metal trap. The attraction water is supplied via a pipe and a syphon. Some have an auxiliary attraction flow [8]. In addition to hydrodynamics, other attraction and avoidance factors (e.g., light [9], sound [10,11,12], temperature, bubbles, chemicals, dissolved gas, electricity [13], etc.) are also studied systematically; however, only a limited number of these factors were considered or applied to the considered fish collection and transportation facilities, some for economic reasons and others due to negative side effects.
Indeed, temperature can play a significant role in determining the effectiveness of these systems. Fish are poikilothermic animals, meaning their body temperature changes in response to the ambient temperature. They are naturally inclined to migrate towards waters with specific temperature conditions that are ideal for their survival and reproduction. For many species, warmer waters can trigger spawning behaviors, while cooler waters may suggest a rich food environment. Therefore, adjusting the temperature of the water at the entrances to fish lifts could make them more appealing to fish, subsequently increasing the number of fish that utilize the lift. This could potentially optimize the efficacy of fish protection facilities and contribute to the conservation of various fish species. Observing and understanding the temperature preferences of different fish species could play a crucial role in these conservation efforts.
Many fish species are reported to move towards their preferred temperature. The proper temperature for inanga is 20 degrees centigrade, but fish held in cooler temperatures prefer warmer temperatures [14]. When a fish was acclimatized to 15, 17, and 20 degrees centigrade, it showed total avoidance at 29.5, 31, and 31.5 degrees centigrade, respectively. A higher temperature improves the low-dissolved-oxygen tolerance of red drum under experimental conditions [15]. The temperature is also a criterion for spawning behavior [16,17,18]. On the other hand, tailwater changes the natural seasonal temperature rhythm of a river [19,20], which may lead to physiological disorders in fish [21,22]. According to a numerical study, the Three Gorges Reservoir and the reservoirs upstream in the Yangtze River significantly delay the temperature-changing process, especially in spring and autumn and, therefore, may delay the spawning date of Chinese sturgeon. Some operational regulations were proposed in order to reduce low-temperature discharge [23].
Taking into consideration the temperature for fish collection and transportation holds theoretical applicability, with the potential to attract and retain fish more effectively. In this context, a new design for a fish collection facility specific to a particular hydropower dam is proposed. The effectiveness of this design in targeting the intended fish species is analyzed through numerical and theoretical approaches. This investigation aims to provide a comprehensive understanding of the facility’s potential performance under various circumstances, aiding in the anticipation of potential challenges and subsequent design improvements. The successful implementation of this design could present significant advancements in fish conservation.

2. Materials and Methods

2.1. Project Background

The hydropower plant utilized for this study was built on the Jialing River, SC, China. Its main purposes are flood control, irrigation, water supply, and power generation. The area of the reservoir is 109.2 km2, the total volume of the reservoir is 4.16 × 109 m3, and the installed capacity of the power station is 1100 MW. It had been running for several years when the attached fish collection and transportation facility was proposed and designed.
The fish collection and transportation facility is located at the left side of the river. It consists of 4 main parts, as shown in Figure 1, namely: the fish collecting channel in the tailrace; the downstream slewing crane, near the fish collecting channel; the track along the river side; and the upstream slewing crane.
According to the design, the fish are collected in the channel and driven to the transportation box via a moving net. In the next step, the box is lifted via the downstream slewing crane, put onto the trolley on the track, transported upstream, and lifted via the upstream slewing crane. Then, the upstream slewing crane turns the box over the dam, moves it down, puts it into the water, and releases the fish. Finally, the box and the trolley return to their initial positions, ready for the next run. The transportation process repeats daily during the fish breeding season, from March to July.
The fish collecting channel is vital to the whole facility. It determines the facility’s success rate, as the collecting process presents more uncertainty than the transportation process does.
As shown in Figure 2, the fish collecting channel has 5 entrances for fish beneath the water, and corresponding water inlets above the water’s surface. Each entrance is 1.4 m wide and 0.3 m high inside the channel and enlarges outward so that it is easy for the fish to enter and difficult for them to leave. The tailwater level varies, from 372.5 m to 374.2 m, with an over 90% guarantee rate.
A collecting channel usually provides a suitable flow velocity through which it stimulates the fish to migrate upstream. In some cases, the collecting channel is even a nature-like or a technical fishway. The flow of the channel is compatible with the main flow. In our case, the velocity within the tailrace is suitable for fish migration. According to previous observations with sonic fish detectors, the fish gathered in the tailrace and their migration was blocked due to the dam. Our design utilizes the warm cooling water in order to attract and collect these fish.
The temperature distribution inside of the channel was studied with numerical tools, as detailed in the following sections.

2.2. Numerical Methods

The following meshing, solving, and post-processing were conducted with the tool chain provided by ANSYS® Inc., Canonsburg, PA, USA, including ICEM for unstructured mesh and Fluent for universal computational fluid dynamics based on finite volume method. The ANSYS® Fluent utilizes common fluid dynamics equations and models and has been validated in many open channel flows [24].

2.2.1. Equations

The control equations for the simulation are single-phase, transient, incompressible, constant-density, Newtonian Navier–Stokes equations. The turbulence model is a realizable k-ε double-equation model. The issue of heat transfer was solved using a detached scalar transport solver, i.e., the temperature and momentum are uncoupled.
The mass conservation equation, i.e., the continuum equation, is an applied constant-density assumption, as shown here:
· v = 0
where v is the velocity vector, in m/s.
In the inertial reference frame, the momentum conservation equation is
v t + · v v = 1 ρ p + 1 ρ · [ μ v + v T + g
where p is the pressure, in Pa; ρ is the density, in kg/m3; μ is dynamic viscosity, in Pa·s; and g is gravitational acceleration vector, equal to (0, −9.81, 0) m/s2.
After the Reynolds average is applied, there is an attached stress term, as in the equation
v ¯ t + · v ¯ v ¯ = 1 ρ p + 1 ρ · [ μ v ¯ + v ¯ T 1 ρ · τ + g
where τ is the Reynolds stress tensor. It is modelled with the vortex viscosity assumption and the realizable k-ε turbulence model. The realizable k-ε turbulence model has the same k equation as the standard k-ε model, but different ε equation and vortex viscosity formulae. The realizable k-ε turbulence model demonstrates better performance in a detached flow [25].
The mechanical energy and processes are neglected in our study. Only the internal energy is considered within the energy conservation equation. Thus, the energy conservation equation is reduced to the internal energy transport equation, as follows:
E t + · v ¯ E = 1 ρ · ( k e f f T )
where E is the internal energy, E = c p T T r e f , where c p is the specific heat capacity and T r e f is the reference temperature, usually absolute zero. k e f f is the effective diffusion factor, including the effects of both molecular and turbulence diffusion.

2.2.2. Numerical Schemes

The above control equations are solved via the finite volume method (FVM), the transient term is solved via the first-order formulation, and the gradient term is solved via the cell-based least square method. More details are shown in Table 1.
The SIMPLE (Semi-Implicit Method for Pressure-Linked Equations) was selected for pressure–velocity coupling. The time step was small enough to ensure that the CFL (Courant–Friedrichs–Lewy) number was less than 1. The maximum iteration of one time step was set to 20. In order to ensure that the fluid renewal degrees would be similar under various operating conditions, the simulated total time was calculated as the total volume of the domain/total volumetric flow rate. Thereby, the influence of the initial conditions on the result is minimalized. When the depth within the channel is 0.6 m, the volume of the calculated domain is 16.15 m3.

2.2.3. Initial and Boundary Conditions

The flow rate of each inlet is relatively small, and the water’s surface is almost a plane, so, the water’s surface was assumed to be a rigid lid, where a slip wall boundary condition was applied. The shear stress is 0 everywhere on this boundary.
The inlets were approximated to circles on the water’s surface, upon which the velocity was evenly distributed. The total volumetric inflow rates are shown in Table 2. The outlet was set up as a pressure outlet, for which the gauge pressure was 0. Reversed flow was allowed at the boundary, which was closed to the actual situation.
The initial and boundary conditions for the temperature were set up according to field measurements. These measurements were conducted from 9 November 2021 to 11 November 2021. The temperature of the cooling water varies from 17.5 to 19.6 °C, and the temperature of the tailwater varies from 15.3 to 15.4 °C. Thus, the temperature of the cooling water was generally about 3 °C higher than that of the tailwater. Thus, in the simulation, the temperatures of the inlets and the ambient environment were set to 18 °C and 15 °C, respectively. A temperature convection model was applied to the wall and to the water’s surface, where the heat fluxes were 1200 W/m2 and 30 W/m2, respectively.

2.2.4. Mesh

The length, width, and height of the domain were 12 m, 2 m, and 0.6 m, respectively. Three boundary layers were divided near the wall. The near-wall layer thickness was 1 cm. The mesh, which had 562,000 cells, is shown in Figure 3. The mesh quality was checked and improved by ANSYS® Fluent. The minimum and maximum cell volume are 4.47 × 10−8 and 2.60 × 10−4 m3, respectively.
To validate mesh grid convergence about ensuring that the numerical solution of the simulation was independent of the grid size, a coarse and a fine mesh were carried out. They had 454,119 and 739,961 cells, respectively. The procedure to generate mesh was the same. For coarse, medium, and fine mesh, cell size was 0.045, 0.05, and 0.055 m, respectively. It was the only changed parameter to generate different mesh. The main results are shown in Table 3. The average temperature had less than 0.02 K error between fine and medium mesh, which implied good mesh convergence. The turbulent kinetic energy was relatively sensitive to mesh. The average and maximum TKE had a positive relationship with mesh resolution, the relative error of average TKE between fine and medium mesh was 10.4% while maximum TKE had less error. In terms of the application scenario, the medium mesh was sufficient.

3. Results

The velocity and temperature fields are the most important results of our study, as they play a decisive role in attracting fish to the system.
The pathlines affected by the velocity magnitude are shown in Figure 4. The five inflows look as though they jet into the water. The jets induce the vortices beside them and maintain their shape and magnitude when flowing downward until they hit the bottom. After hitting the bottom, the jets break, and the velocity magnitude decreases significantly. A few pathlines reach the tank on the right side. Near the outlets, the flow is turbulent, with many vortices, which induces reverse flow into some areas of the outlet, i.e., the water flows back through the outlet into the domain.
The temperature distribution is unlike that of the velocity. The velocity can dissipate within the interior while the temperature is preserved, as the heat source is negligible in our case. The temperature is relatively uniform within the calculated domain, except within the boundaries. Within the interior, the temperature of over 90% of the volume is less than 0.5 °C below the inflow temperature.
As shown in Figure 5, the temperature of the outside surface varies widely. The temperature of the front wall is determined by the temperature and velocity inside the structure. Where hot water flows past, there will be a relatively high temperature.
Although the thin metal wall has good heat conductivity, the temperatures of water close to the inside and the outside of the wall drop distinctly because the boundary layer limits heat convection.
The water’s surface has almost the same temperature as that of the inflow, since the heat flux between the water and air is relatively small.
The temperature of each outlet has several local minimums, which are induced via the reserve flow from the outside to the inside. The reserve flow is likely due to the macroscale vortex motion.
The flow rate of the cooling water varies, from 0.03 to 0.2 m3/s. The mean temperature inside of the channel shows a positive relation with the flow rate, as presented in Figure 6. After the flow reaches a steady state, the temperature is not as sensitive to the flow rate. The temperature range is less than 0.1 °C.
The dependency of the TKE on the total flow rate is shown in Figure 7. Theoretically, the TKE is zero when the flow rate is zero. As the flow rate increases, both the average and the maximum TKE increase sharply. The relationship can be fitted using quadratic functions. The maximum TKE is about 30 times greater than the average TKE. The maximum value appears in the mixing layer between the jet and the ambient water.

4. Discussion

The velocity field of the tailwater is suitable for fish migration. Thus, the design of the collecting channel does not unilaterally stress the flow rate. Instead, the flow structure and temperature distribution are stressed, according to our study. The current simulated results show potential benefits for local fish species.
The main bypassing fish species are Schizothorax davidi, Spinibarbus sinensis, and Leiocassis longirostris. The key characteristics and behaviors of these species are shown in Table 4 [26,27,28].
The fish are able to move towards their preferred temperature and avoid too-hot or too-cold areas. Tendency and avoidance behaviors were widely studied on various species [29]. Two of the three target species are warm-water fish, which means they have a minimum temperature at which reproduction can occur. The proper temperature range for L. longirostris is 22~28 °C in captivity [30,31]. The influence of temperature on the swimming performance of S. sinensis was studied systematically [32,33]. S. sinensis reached its maximum critical swimming velocity, 8.21 BL/s (BL—body length), at 27.2 °C. Below or above this temperature, its critical swimming velocity decreased. S. davidi is a cold water fish, which means it has a maximum temperature at which reproduction can occur. Warm or cold water is a rough classification, while better indicators are three base-point temperatures, namely: biological minimum temperature (biological zero), biological optimum temperature, and biological maximum temperature. The biological minimum temperature for the embryonic development of S. davidi is 11.3 °C. Under experimental conditions, the ideal temperature for incubation was 14.5 °C [34]. Another experiment [35] proposed that the proper temperature range for eggs is 16~18 °C. The incubation time is about 134 h. The adult fish have much higher temperature requirements.
The reservoir changed the natural seasonal rhythm of water temperature within the river. After the dam was constructed, the downstream water temperatures were lower than those of its natural state in spring and summer. This temperature change delays the spawning season of some aquatic creatures. The temperature compensation within the facility corrects this altered seasonal rhythm for fish.
The fish can tolerate high turbulent kinetic energy (TKE), generated with hydraulic machinery, of up to 0.089 m2/s2 [36]. It was revealed that the fish have a preferred TKE range. The preferred TKE range for a Chinese sturgeon spawning habitat is 0.010~0.015 m2/s2 [37]. The typical range of the spatial maximum TKE within a vertical slot fishway is 0.03~0.07 m2/s2 at different flow rates, and, in most areas, it is below 0.01 m2/s2 [38]. The TKE measured using ADV in a vertical slot fishway ranged from 0.01 to 0.2 m2/s2 in most areas when the flow rate of was 1.0 m3/s and the water depth was 1.3 m [39]. In our case, throughout the designed flow rate range, the maximum TKE was below 0.062 m2/s2, which is safe for the fish. When the flow rate was equal to 0.1 m2/s2, the maximum TKE was 0.015 m2/s2, which is comparable with the natural habitat.
As the inlets of the collecting channel are above water, the flow makes sound and causes air bubbles to enter the water. There is some evidence showing that the low-frequency sound can attract fish [40]; however, for our target fish species, there is little related research. The effects of our design require long-term monitoring after construction.

5. Conclusions

In conclusion, the proposed fish collection and transportation facility considered the velocity, turbulent kinetic energy, and temperature in order to provide a suitable environment for the migration of fish bypassing the dam. The inflow of the fish collecting channel can provide steady temperature compensation, increase the turbulent kinetic energy, generate an attractive outflow, and generate a low-frequency sound. As discussed above, these factors are beneficial for some local fish species, and they are harmless for others. For the various behavior patterns and complex mechanisms of fish, the biological and ecological effects of the facility still require further research and monitoring.

Author Contributions

Conceptualization, Q.Z. and Y.T.; methodology, Q.Z.; software, Q.Z.; validation, J.S.; formal analysis, Q.Z. and Y.T.; investigation, Q.Z.; resources, J.S.; writing—original draft preparation, Q.Z.; writing—review and editing, J.Q.; visualization, Q.Z.; supervision, J.S., W.Z. and J.Q.; project administration, J.S.; funding acquisition, J.S. and W.Z. All authors have read and agreed to the published version of the manuscript.


This research was funded by the Ministry of Science and Technology of the People’s Republic of China, grant number 2022YFC3204201.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. Schematic diagram of the fish collection and transportation facility.
Figure 1. Schematic diagram of the fish collection and transportation facility.
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Figure 2. Detail of the fish collecting channel.
Figure 2. Detail of the fish collecting channel.
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Figure 3. The mesh and boundary conditions of the domain.
Figure 3. The mesh and boundary conditions of the domain.
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Figure 4. The pathlines affected by the velocity magnitude (total flow rate = 0.05 m3/s).
Figure 4. The pathlines affected by the velocity magnitude (total flow rate = 0.05 m3/s).
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Figure 5. The temperature of the outside surface (total flow rate = 0.05 m3/s).
Figure 5. The temperature of the outside surface (total flow rate = 0.05 m3/s).
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Figure 6. The relationship between the mean temperature and the total flow rate.
Figure 6. The relationship between the mean temperature and the total flow rate.
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Figure 7. The relationship between the turbulent kinetic energy and the total flow rate.
Figure 7. The relationship between the turbulent kinetic energy and the total flow rate.
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Table 1. Discrete schemes.
Table 1. Discrete schemes.
TransientFirst-Order Implicit
Spatial DiscretizationGradientLeast square
MomentumSecond-order upwind
Turbulence kinetic energyFirst-order upwind
Turbulence dissipation energyFirst-order upwind`
EnergySecond-order upwind
Table 2. Operating conditions under the numerical simulation.
Table 2. Operating conditions under the numerical simulation.
No.Tailwater Elevation/mFlow Rate/m3/sInflow Temperature/°CAmbient Temperature/°C
2372.60 0.05 1815
3372.60 0.1 1815
4372.60 0.2 1815
Table 3. The main results of different mesh sizes.
Table 3. The main results of different mesh sizes.
Average Temperature (K)Max. Temperature (K)Average TKE (m2/s2)Maximum TKE (m2/s2)
Fine Mesh291.10291.150.00055180.01425
Medium Mesh291.08291.150.00049980.01527
Coarse Mesh290.78291.150.00040210.01868
Table 4. Key behaviors of the target fish species.
Table 4. Key behaviors of the target fish species.
SpeciesTemperature PreferenceCommon LengthMax Length
Schizothorax davidiCold water12.5 cm39.5 cm
Spinibarbus sinensisWarm water15.1 cm47.1 cm
Leiocassis longirostrisWarm water28.5 cm66.0 cm
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Zhang, Q.; Tang, Y.; Shi, J.; Zhou, W.; Qian, J. Numerical Study on Fish Collection and Transportation Facility with Water Temperature Compensation. Water 2023, 15, 3185.

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Zhang Q, Tang Y, Shi J, Zhou W, Qian J. Numerical Study on Fish Collection and Transportation Facility with Water Temperature Compensation. Water. 2023; 15(18):3185.

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Zhang, Qi, Youmin Tang, Jiayue Shi, Wu Zhou, and Jin Qian. 2023. "Numerical Study on Fish Collection and Transportation Facility with Water Temperature Compensation" Water 15, no. 18: 3185.

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