https://orcid.org/0000-0002-8954-6362
Abstract
The Three Gorges Reservoir on the Yangtze River is the largest water control project in the world. While exerting great benefits (i.e., flood control, hydropower generation, inland river navigation and scenic tourism), the eutrophication of the tributary bay of the Three Gorges Reservoir has become one of the main environmental problems. This paper is to study the causes of water environment evolution in the tributary bay and investigate the driving force of eutrophication succession after the Three Gorges Reservoir enters the regular operation. By considering the Meixi River on the left bank of the mainstream of the Three Gorges Reservoir area (a typical tributary), this paper developed a three-dimensional hydrodynamic, water quality and water eutrophication mathematical model for the Meixi tributary bay, calibrated with measured data about hydrological regime (water level, flow), hydrodynamic factors (velocity) and water quality (water temperature, Chl-a, TP, TN, etc.). The annual variation of Chl-a concentration in the tributary bay was simulated, and the response relationship between the variation of Chl-a concentration and water conditions of the mainstream and tributary bay (e.g., reservoir water level, reservoir bay velocity, exogenous nutrient input, water temperature stratification and other factors) was analyzed. Results show that the water storage operation of the Three Gorges Reservoir contributes to the low flow velocity maintenance (≤0.05 m/s) in the tributary bay, the backward flow of the mainstream and the sufficient nutrients carried by the tributary water; the water temperature stratification is more likely to occur in the slow detention area in the middle-upper part of the bay in spring and summer, which provides a potential driving force for algae blooms. With the continuous decline of pollution load input in the reservoir basin, the algae blooms in tributary bay was the result of the combined action of low water level operation, low flow velocity (≤0.02 m/s), a large number of non-point source loads input with rainfall and runoff (the proportion of wet year is >70%), and obvious water temperature stratification in shallow water area, and the suitable meteorological conditions are the main inducing factors. Therefore, since the ecological regulation cannot be applied to the multitudinous tributary bays, the non-point source pollution control in the tributary bay is the key to controlling factor.
HIGHLIGHTS
A three-dimensional hydrodynamic, water quality and water eutrophication mathematical model is developed.
The study analyses hydrodynamic characteristics, spatiotemporal variability and driving mechanism of water eutrophication.
The article provides insights into environmental management in the tributary bay of the Three Gorges Reservoir area.
INTRODUCTION
The Three Gorges Reservoir on the Yangtze River is the largest hydropower project in China, with a surface width of 60–1,000 m, a reservoir length of 663 km and a total coverage area of 1,084 km2. The normal water level is 175 m, the flood control level is 145 m, the total submerged land area is 632 km2, and the total storage capacity is 39.3 billion m3, of which the flood control storage capacity is 22.15 billion m3. Since the trial impounding of the Three Gorges Reservoir in 2003, the operation of the reservoir has had a strategic significance for ensuring the flood control safety of the middle and lower reaches of the Yangtze River, promoting the development of the golden waterway of the Yangtze River, accelerating the green and high-quality development of the Yangtze River economic belt (Jiao et al. 2018).
The Three Gorges Reservoir has made great contributions to flood mitigation and irrigation, hydropower generation, and shipping. However, this has been accompanied by a suite of environmental problems, such as soil erosion, non-point source pollution, ecological deterioration of falling zone, water eutrophication in the tributary bay, which are becoming increasingly serious. It is entirely possible that there may be eutrophication problems, which was put forward by some scholars before the Three Gorges Reservoir was built (Luo et al. 1999; Li & Liao 2003; Liu et al. 2003). After half a year of first impoundment stage in 2003, algal bloom appeared in some tributary bays. The Phytoplankton abundance has increased in front of the dam and the backwater reach. The nutritional status category in the whole sections changed from ‘poor-medium nutrition’ to ‘medium-rich nutrition’ after impoundment (Cai & Hu 2006; Zhang et al. 2006; Qi et al. 2021). As the storage level of the reservoir gradually rises, the backwater area of the reservoir area gradually expands, and there are more tributary bays from bottom to top facing increasingly severe water eutrophication problems.
A lot of research work have been carried out about the eutrophication of the tributary bay. Qiu et al. (2011) and Liu Yujie et al. (Liu & Yin 2014) studied the eutrophication and water bloom in the tributaries in the Three Gorges Reservoir by analyzing the monitoring data. Chen et al. (2019) and Liu et al. (2016a) summarized research results on the water eutrophication to research the mechanisms of water bloom. Xiao et al. (2017) applied a grey Bernoulli model to predict the spatial and temporal dynamics of water bloom and Yin (2014) built a set of analogy forecast models for eutrophication with the analogy factors of nutrient load to forecast the eutrophication trends. However, these researches on the water eutrophication cannot cover the entire impoundment process and the regular operation period of high-water level. Based on HEC-RAS, Li et al. (2012) set up a one-dimensional (1D) hydrodynamic model on Pengxi Backwater and Jiang et al. (2013) employed numerical simulations to simulate the hydrodynamic field of the Xiangxi Bay under the effect of temperature density current. At present, there are few studies on this Meixi River using numerical model. So, the driving mechanisms of hydrodynamics are investigated through the three-dimensional (3D) simulation technology for hydrodynamics and water environment on the Meixi River. Our study will further reveal the causes and driving mechanisms of eutrophication evolution in the typical tributary bay, and provide insights into ecological and environmental management in the tributary bay of the Three Gorges Reservoir area. In our study, major difficulties and challenges is to build a 3D hydrodynamic, water quality and water eutrophication mathematical model. Using the model, we systematically analyze the features of algae bloom in the tributary bay, the evolutional characteristics of algae community in algae boom period and its relationship with the environmental factors, the correlation between hydrological and hydrodynamic changes and algae growth.
MATERIALS AND METHODS
Study area
Changes in the eutrophication status of the main tributaries before and after the normal operation of the Three Gorges Reservoir.
Changes in the eutrophication status of the main tributaries before and after the normal operation of the Three Gorges Reservoir.
Annual changes of algal blooms in the tributaries of the Three Gorges Reservoir area in 2008–2019.
Annual changes of algal blooms in the tributaries of the Three Gorges Reservoir area in 2008–2019.
The length of the mainstream in the Three Gorges Reservoir area is 663 km. The topography in the reservoir area is complex. Along the Yangtze River, there are many river systems and numerous tributaries, and the different tributary bays have different geometric forms and drainage characteristics. Considering the location of 38 main tributaries in the reservoir area, the upstream inflow, the length of backwater, the proportion of water-fluctuating zone area and the occurrence of water blooms in recent years, the Meixi River in Fengjie County, Chongqing City is selected as a typical tributary bay to study the eutrophication mechanism.
The location of the Meixi Bay and water quality monitoring site in the Three Gorges Reservoir of the Yangtze River.
The location of the Meixi Bay and water quality monitoring site in the Three Gorges Reservoir of the Yangtze River.
Data source
The daily water level and daily flow in Fengjie Station, located in the main stream of the Three Gorges Reservoir area, are from the published data by the China Three Gorges Corporation. The meteorological data measured by the Fengjie Weather Station, located at the mouth of the Meixi River, are used as the data of the Meixi River tributary bay. Because there is no hydrological station in the Meixi River, the adjacent Daning River is analogous to the measured flow process of the Meixi River with area scaling to calculate the daily flow of the Meixi tributaries bay. The data include the measured water temperature of the mainstream of the Three Gorges Reservoir area and the upper reaches of the Meixi River, and water quality control section in the mainstream of the Yangtze River and the Meixi Bay (the end of the reservoir is 145 m, and the location is shown in Figure 3) and the water quality data of the upstream inflow of the tributary used as the monthly measured water quality parameters in the upstream control section of the 175 m backwater to get intermediate data with linear interpolation.
Models and methods
The above equations are based upon the following assumptions (Al-Mansori & Al-Zubaidi 2020; Yamini et al. 2020; Karim et al. 2021):
The liquid is incompressible. As a result, the density of liquid changes under pressure.
The liquid has a free surface. So, the water level will rise and fall freely.
In the established hydrodynamics model in the Meixi bay, it considered not only the physical and chemical processes of phytoplankton in the river, but also the influence of exogenous nutrient salt input and endogenous circulation on phytoplankton (Cheng 2018). Phytoplankton takes in nutrients such as NH4−, NO3−, PO43− and Si from external sources to respiration, and generates the dissolved oxygen through photosynthesis. Phytoplankton can produce detritus after its excretion and death, and the detritus will be re-entered into the water in the form of nutrients through sedimentation and resuspension, forming a continuous cycle of nitrogen, phosphorus and silicon in the water.
The Meixi Bay is about 19.6 km long. The tributary and its adjacent main stream use the Cartesian coordinates in the horizontal direction with a resolution of 50 m × 50 m, and the vertical direction is divided into 10 layers using Sigma coordinates by spatial discretization to get a total of 27,440 computational grids. It was adopted boundary conditions of water flow for the mainstream and the upstream of the tributary in the reservoir area, while the boundary condition of water level for the downstream of the tributary confluence. Monthly measured data of water temperature and water quality were collected for the mainstream and its tributary and the linear interpolation was used to obtain the daily process. The measured data in 2004 for flow, water temperature and water quality were used to calibrate parameters of the 3D hydrodynamic, water quality and water eutrophication mathematical model of the Meixi Bay, and the data in 2017 were used to verify the model. The hydrodynamic simulation variables include flow field, velocity, water level, water depth, water temperature, etc., and the model parameters for calibration are water level and water temperature. It can be seen in the water quality simulation results of different sections of the Meixi Bay that the built hydrodynamic, water quality and water eutrophication mathematical model in the Meixi Bay is so reliable that it can simulate the water environment evolution and provide a reliable technical tool to study the driving mechanism of the water eutrophication evolution with the interactions between the mainstream and its tributary. Through calibration and validation, we get the key parameters (Table 1). With the sensitivity analysis for parameter, Chl-a concentration is mainly affected by the following four parameters: Maximum phytoplankton growth rate, Lower optimum temperature for algal growth, Phosphate half saturation constant for alga and Phytoplankton linear mortality rate. However, dissolved oxygen concentration is mainly affected by the following four parameters: maximum phytoplankton growth rate, lower optimum temperature for algal growth, phytoplankton basal respiration rate and detritus remineralization rate.
The value of key parameters
| Parameters | Value | Unit |
|---|---|---|
| Maximum phytoplankton growth rate | 1/86,400 | d−1 |
| Lower optimum temperature for algal growth | 25 | °C |
| Phosphate half saturation constant for alga | 0.3 | mmolP·m−3 |
| Phytoplankton linear mortality rate | 0.035/86,400 | d−1 |
| Phytoplankton basal respiration rate | 0.2/86,400 | d−1 |
| Detritus remineralization rate | 0.127/86,400 | d−1 |
| Parameters | Value | Unit |
|---|---|---|
| Maximum phytoplankton growth rate | 1/86,400 | d−1 |
| Lower optimum temperature for algal growth | 25 | °C |
| Phosphate half saturation constant for alga | 0.3 | mmolP·m−3 |
| Phytoplankton linear mortality rate | 0.035/86,400 | d−1 |
| Phytoplankton basal respiration rate | 0.2/86,400 | d−1 |
| Detritus remineralization rate | 0.127/86,400 | d−1 |
RESULTS AND DISCUSSION
Hydrodynamic characteristics and spatiotemporal variability in the Meixi Bay
The change of flow velocity in the different horizons in 2007.
Flow field of the Xiangxi Bay in TDR operation period.
The characteristics of water volume and substance exchange in the Meixi Bay
Based on the simulated results of 3D hydrodynamic, water quality and water eutrophication mathematical model of the Meixi Bay, the water exchange process between the mainstream of the Three Gorges Reservoir area and the Meixi tributary bay was analyzed. The results show that the amount of water flowing out into the mainstream of the Meixi Bay is almost equivalent to the backward flow from mainstream into the tributary bay of the reservoir in 2017. There is a continuous water exchange with the interaction of the main stream and the tributary bay, which allows water masses from the mainstream of the Yangtze River to flow into the tributary bays easily, accelerating the mixing of water bodies in the tributary bays and the migration, diffusion and mixing process of pollutants, and in the density flow and upstream of the tributary bays. Under the combined effect of the density flow and the upstream flow, the flow direction of the water bodies is not the same as in different sections and in the different layers, and there are the income and expenditure of nutrients in the entire tributary bay (Ye et al. 2006, 2007; Zhou et al. 2009, 2011; Zhe et al. 2009; Jian et al. 2018). The annual average values of the water exchange between the mainstream and the tributary at the mouth, middle and tail of the Meixi River are 210.15, 83.60 and 77.21 m3/s, respectively, and has a characteristic of gradually decreasing from the bottom to the top. The water exchange volume is 2.5 to 3.0 times that of the middle and upper part of the reservoir. In addition, the amount of water exchange between Meixi bays and the mainstream is highly heterogeneous and has obvious characteristics of temporal and spatial variation.
Phytoplankton evolution in the Meixi Bay
Annual phytoplankton changes of the Meixi Bay in 2017.
Spatial distribution of phytoplankton during the flood season of 2017.
Driving mechanism of water eutrophication in the Meixi Bay
Water eutrophication is the natural response of organisms to the increase of nutrient concentration, and the cyanobacteria bloom is the most obvious sign of the water eutrophication, which is mainly caused by many cyanobacteria accumulating on the water surface to cause the change of water color. Abiotic factors such as nutrients, hydrodynamic conditions, temperature and light, and biological factors such as zooplankton predation are the main factors of the eutrophication of lakes and reservoirs. Based on the research results of the hydrodynamic characteristics, evolutional characteristics of water environment, phytoplankton and nutrients, the daily operation of the Three Gorges Reservoir, and water temperature stratification, water eutrophication evolution and the driving mechanism of cyanobacteria blooms in the Meixi Bay is mainly reflected in the following aspects:
The slow flow regime provides a suitable dynamic environment for the water eutrophication of the reservoir and tributary bay and the occurrence of algal blooms.
Cyanobacteria easily multiply to form large colony aggregates, and these colonies can adjust the sugar content in their cells to offset the buoyancy provided by the air sacs, and thus move up and down in the water. When the mixing rate in the vertical direction of the water section exceeds the floating rate of its large colony aggregates, it is difficult for the cyanobacteria to float up under the buoyancy provided by the airbags, and it can inhibit the proliferation of buoyant cyanobacteria and be replaced by diatoms and green algae. Therefore, increasing the water flow speed to shorten the hydraulic retention time is expected to be an effective method to control water bloom in slow-flowing rivers such as lakes and reservoirs.
The water stratification caused by the stratified density current is the key factor affecting the succession of the phytoplankton community, water bloom and its temporal-spatial distribution in the reservoir bay.
The change of water depth in the estuary of the Meixi Bay after the operation of the Three Gorges Reservoir.
The change of water depth in the estuary of the Meixi Bay after the operation of the Three Gorges Reservoir.
Annual variation of water flow in the middle of the Meixi Bay in 2017.
Temporal and spatial variations of Chl-a in the Meixi Bay and vertical distribution of tail sections in 2017.
Temporal and spatial variations of Chl-a in the Meixi Bay and vertical distribution of tail sections in 2017.
The correlation between Chl-a and the buoyancy frequency at different locations in the Meixi Bay.
The correlation between Chl-a and the buoyancy frequency at different locations in the Meixi Bay.
The water stratification increased in August, but the concentration of Chl-a decreased significantly. The degree of stratification in the upper reaches of the tributary bay is stronger than that in the middle part and the estuary, but the correlation between the Chl-a concentration and the buoyancy frequency is more complicated than that in the middle part and the estuary. During the period from April to July, the concentration of Chl-a gradually increased along with the increase in the water stratification; while the performance from August to September was completely opposite to the previous period, showing that the water stratification disappeared, but the concentration of Chl-a also remains at a relatively high level.
Non-point source load input is the main material source for the evolution of water eutrophication and algal bloom in the tributary bay.
Every year from March to October is the high incidence and sensitive period in the tributary bay of the Three Gorges Reservoir (Ministry of Ecology & Environment of the People's Republic of China). In this period, the nutrient source of the typical section is of decisive significance for the evolution of the water eutrophication of the tributary bay (Zhe et al. 2009; Ran et al. 2010; Ye & Cai 2011; Zhou et al. 2011). Based on the inversion simulation results of the 3D hydrodynamic, water quality and water eutrophication mathematical model of the Meixi Bay, combined with the water volume and water quality boundary conditions of the mainstream and tributary streams of the same period, it can be calculated that the total income and expenditure of nutrients such as P and N at different characteristic sections in the estuary, in the middle and at the tail of the Meixi Bay, which is at the end of the backwater level at the water level of 145 m. The results show that: the total phosphorus (TP) load of non-point source input in the Meixi River Basin accounts for 59% of the total cross-section revenue and expenditure yearly, and is the main source of nutrients in the high-prone area of cyanobacteria blooms.
From the analysis of the sensitive period of water bloom in the reservoir area (from March to October), it shows that the TP load from non-point source input in the basin accounts for 72% of the total revenue and expenditure of the sections, and is the most important source of nutrient contribution during the high incidence period of water bloom. From the analysis of the nutrients source of the tributary bay when the water bloom occurs in July, the TP load of non-point source input in the Meixi Bay accounts for 75% of the total revenue and expenditure, and the total nitrogen (TN) input also accounts for 72% (Qi et al. 2021). Therefore, the non-point source input in the watershed is the most important nutrients source during the occurrence of cyanobacteria blooms in the Meixi Bay; on the other hand, when water blooms occur in the tributary bay, the proportion of nutrient load input from the main stream of the reservoir area has been lower than 25%. Therefore, to reduce water eutrophication and algae blooms in the Meixi Bay, the effective measures for improving the water environment in the Meixi Bay is to control the input of non-point source load in the watershed, to intercept of non-point source in the process of rainfall and runoff transportation, and to improve the systematic restoration of the belt ecosystem by its terminal interception of the diffusive currents around the reservoir.
The correlation coefficient of the water quality parameters in June to September in the Meixi Bay
| Water quality parameters | CODMn | TN | TP | Chl-a | SD | Water temperature |
|---|---|---|---|---|---|---|
| CODMn | 1 | |||||
| TN | −0.133 | 1 | ||||
| TP | 0.852 | 0.432 | 1 | |||
| Chl-a | −0.155 | −0.700 | 0.093 | 1 | ||
| SD | −0.158 | 0.847 | −0.062 | −0.936 | 1 | |
| Water temperature | −0.696 | 0.035 | 0.237 | 0.629 | −0.317 | 1 |
| Water quality parameters | CODMn | TN | TP | Chl-a | SD | Water temperature |
|---|---|---|---|---|---|---|
| CODMn | 1 | |||||
| TN | −0.133 | 1 | ||||
| TP | 0.852 | 0.432 | 1 | |||
| Chl-a | −0.155 | −0.700 | 0.093 | 1 | ||
| SD | −0.158 | 0.847 | −0.062 | −0.936 | 1 | |
| Water temperature | −0.696 | 0.035 | 0.237 | 0.629 | −0.317 | 1 |
The relationship between the chlorophyll concentration and water quality indicators such as TN, TP and water temperature in 2017 at the tail section of the Meixi Bay.
The relationship between the chlorophyll concentration and water quality indicators such as TN, TP and water temperature in 2017 at the tail section of the Meixi Bay.
In conclusion, after the Three Gorges Reservoir was built, the channel had become a low-velocity, relatively static, slow flow in the tributary bay and stratified density flow formed by the water temperature difference between the mainstream and the tributary bay, and it can also provide sufficient exogenous nutrient supplementation and local accumulation of the tributary bay. After the water storage, the hydrological and hydrodynamic conditions of the tributary bay had changed and it was suitable for algae blooms and inhabiting. When the sufficient nutrient inputting in the mainstream and its tributary, the concentration of Chl-a in the tributary bay had changed with the meteorological conditions such as water temperature and sunlight. Therefore, the water eutrophication and algal blooms in the tributary bays of the Three Gorges Reservoir are the results of the combined effects of slow flow regimes, low water levels, high nutrient concentration inputs, and suitable meteorological conditions. During the regular operation, it is not usually considered the diversity of natural conditions and temporal-spatial difference in the tributary bay, the controlling of non-point source input in the watershed will become the first choice for the prevention and control of water eutrophication and algae blooms in the tributary bay of the Three Gorges Reservoir. The effective measures for improving the water environment in the Meixi Bay is to control the input of non-point source load in the watershed, to intercept of non-point source in the process of rainfall and runoff transportation, and to improve the systematic restoration of the belt ecosystem by its terminal interception of the diffusive currents around the reservoir.
CONCLUSION
Since the Three Gorges Reservoir began its 175 m experimental storage in 2008 and gradually entered regular operation, the water quality of the mainstream in the reservoir area has maintained Class II to III, and the water quality is in good condition. The water quality of each section basically has a trend of gradual improvement. The water eutrophication in the tributary bay is relatively prominent. The numbers of meso-eutrophic sections have gradually increased, and the degree of the water eutrophication has gradually increased. However, the numbers of tributaries with water blooms have shown a fluctuating downward trend since 2012, and the occurrence season of water blooms gradually concentrates from spring and autumn to summer.
The evolution of water eutrophication and the driving mechanism of cyanobacteria blooms in the tributary bay of the Three Gorges Reservoir are as following: the low flow velocity of the tributary bay reducing from 1.0–3.0 m/s to 0–0.05 m/s since the impoundment of the Three Gorges Reservoir and the influence of the stratified density flow caused by the temperature difference between the mainstream and tributary, can result in the backward flow from the Yangtze River into the tributary bays, and a slow retention zone with low-velocity in the middle and upper parts of the bay has been formed. In spring and summer, water temperature stratification is more likely to occur, which provides potentially suitable habitat conditions for algae blooming. At the same time, the slow-flowing water can cause poor vertical water exchange. Nutrients from the periphery of the tributary bay and the upstream of the tributary tend to accumulate in the middle and upper parts of the reservoir, and the conditions of suitable habitat that water temperature and light reach the growth threshold, can cause the increasing of water eutrophication and the high frequency of algal blooms in the tributary bay.
The water eutrophication and algae blooms in the tributary bay of the Three Gorges Reservoir area are the combined results of slow flow, low water level, high nutrient concentration input, and suitable meteorological conditions. During the regular reservoir operation, it does not usually consider the diversity of natural conditions and temporal-spatial difference in the tributary bay, so the controlling of non-point source input in the watershed plays an irreplaceable role in the prevention and control of water eutrophication and algae blooms in the tributary bay of the Three Gorges Reservoir.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.
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