Research on water environmental capacity accounting of the Yongzhou Section of Xiangjiang River Basin based on the SWAT-EFDC coupling model

It is the rapid urbanization that has led to the increasingly serious problem of the river basin water environment, and the environmental protection of watershed water is essential for sustainable economic and social development. The upper reaches of the first-level tributary of the Yangtze River in the Yongzhou Section of Xiangjiang River Basin are also the final receiving water body of non-point source nitrogen and phosphorus pollutants in the basin. The Xiangjiang River Basin would experience water shortages induced by climate change and pollution source emission (Wang et al. 2017). It is very important to understand the water environmental capacity (WEC) of nitrogen and phosphorus in the Yongzhou Section of Xiangjiang River Basin for water environmental protection and governance. The concept of WEC was first derived from the TMDL (total maximum daily loads) management plan proposed by the United States in 1972 (USEPA 1999). At present, the commonly used methods for the calculation of WEC include the trial-and-error method, the analytical method, the probabilistic dilution model method, the stochastic theory and the system optimization method (Thomann & Sobel 1964; Burn & Lence 1992; Zhang 2017; Wang et al. 2019). With the maturity of various water quality models, the model can identify the relationship between water quality and pollutant response, making it widely used in WEC research and becoming the focus of research (Deng et al. 2010; Fang 2015; Feng 2016; Meng 2018). The analytical method is to use a river model verified by actual measurement data to predict the flow and pollutant concentration of each section of the water body and then substitute it into the WEC calculation model for accounting. The method is characterized by strong operability, clear physical concepts and relatively objective calculation results, making it one of the most popular used methods.

Domestic scholars use the WASP model, the EFDC model and other water quality models together with the WEC calculation model (i.e., analytical method) to calculate the WEC. Their studies were often utilized to calculate the temporal and spatial distribution of WEC in small watersheds (Yen et al. 2012; Xu 2014, 2018; Tang 2016; Yao et al. 2018; Zhao 2018; Wang et al. 2019; Zheng et al. 2019; Hu et al. 2020). Compared with the methods used previously, the analytical method employed in their studies can simulate the transformation and interactions between nitrogen and phosphorus in different forms. The main disadvantages of the analytical method are as follows: (1) A large amount of data has to be used. Unfortunately, the hydrology and water quality stations and monitoring frequency of large-scale river basins in our country can hardly satisfy the needs of water environment capacity calculations. In that case, it is impossible to accurately calculate the true situation of the water environment capacity of the basin by using water quality models according to the measured data of hydrology and water quality at a few sites. (2) Due to the lack of measured water quality data, a large number of parameters of the water environment capacity calculation model have to quote the empirical values, which brings greater uncertainty to the calculation results. (3) The use of river water quality models, such as the EFDC model alone, requires many field surveys on river topography, water depth and other data, which consumes a lot of manpower, material resources and time. It is not realistic to carry out a large-scale survey on a large quantity of river basins from the perspective of time and cost.

At present, the commonly used hydrological models mainly include the HSPF model (Zhang et al. 2012), the AGNPS model (Meng & Zhao 2008), the L-THIA model (Shen et al. 2007; Hui 2015) and the SWAT model (Li 2012; Jiang 2015; Zhai 2015), which are widely used. The coupling of the SWAT model with the EFDC model, the WASP model and other water quality models in hydrological models shows the good effect, which is widely used in river and lake water bodies (Liu et al. 2008; Du et al. 2016; He et al. 2020). It can be used for the analysis of the input meteorological data, DEM elevation map, land-use-type map, soil distribution map and other data through the simulation of the hydrological process, and the output of the water system of the river basin, the runoff of the sub-basin, the outlet of the sub-basin, the river elevation, the water depth, nitrogen and phosphorus pollution load and other simulation results. The calibrated results can be used as the boundary conditions of water quality models, such as the EFDC model to realize the coupling of hydrology and water quality models, so as to eliminate the disadvantages of insufficient data, large amount of preliminary investigation work and high cost when using water quality models to calculate WEC in large river basins. Based on the hydrodynamic water quality simulation of the SWAT-EFDC coupling model, this paper identifies the relationship between pollution sources and water quality response. Under the premise of the satisfaction of the water quality standards required by water function zoning, the theoretical formula of one-dimensional water environment capacity was used to calculate the WECs of total phosphorus and total nitrogen in 2017, and the WEC and remnant WEC of the total nitrogen and total phosphorus in the Yongzhou Basin, Xiangjiang River under different hydrological conditions, thereby providing references for the calculation of the WEC of large river basins, and establishing a total amount control plan for the Xiangjiang River Yongzhou Basin. It can also provide a basis for the formulation, and data support for the further development and control of the water environment of the river basin.

The research area is in the upper reaches of the Xiangjiang River which is the largest river in Hunan Province and a major tributary of the Yangtze River. Its west source originates from Haiyang Mountain in Lingchuan County of Guangxi Zhuang Autonomous Region, and its east source originates from Yegouling, Lanshan County, Hunan Province. Xiangjiang River has a total length of 948 km and a drainage area of 94,700 km², which has a drainage basin with the largest amount of water resources and the highest utilization rate. Besides, the river belongs to the Dongting Lake water system dominated by a subtropical monsoon climate. The long-term average annual rainfall is between 1,200 and 1,900 mm, and the annual average temperature is between 17.6 and 18.6 °C. Red soil and yellow soil are the main soil types, and the annual average sunshine is between 101.5 and 113 kcal/cm² (YCHO 2018).

There are 363 urban point sources in the research area, including 18 urban centralized sewage treatment plants, 143 rural centralized sewage treatment facilities and 202 industrial enterprises (the statistics only include the enterprises that directly discharge wastewater into rivers). At the same time, there are also 2,758 large-scale livestock and poultry farms in 2017.

The total nitrogen emissions are 12,927.12 t/a, and the total phosphorus emissions are 1,501.82 t/a in the area. These emissions are composed of three parts. Most of the emissions are from the planting industry with a total nitrogen emission of 9,464.1 t/a and a total phosphorus emission of 864 t/a. The emissions from the large-scale livestock and poultry farms are in the second place, which have a total nitrogen emission of 2,362.29 t/a and a total phosphorus emission of 575.66 t/a. The least emissions come from the urban point sources with the total nitrogen emission of 1,100.73 t/a and the total phosphorus emissions of 64.32 t/a (YEEB 2020).

The database for the SWAT model and the EFDC model is classified into two categories: spatial database and attribute database. See Table 1 for the names, parameters and sources of the main data.

The SWAT model, also called the distributed watershed hydrological model (Soil and Water Assessment Tool model), consists of three parts, i.e., hydrological process model, soil erosion model and pollution load model. They are used to simulate runoff, sediment, nutrients, pesticides and other substances, respectively.

First, input the spatial data and attribute data required by the database (including weather data, terrain data, soil data and land use/cover data) into the SWAT model, then identify the DEM image and calculate the catchment area of the watershed, and finally extract the river network and divide the sub-basin. By setting the thresholds for land-use type, soil type and slope division to 10, 10 and 15%, respectively, the total area of the watershed is calculated to be 1,8633.6 km², and the watershed is divided into 115 sub-basins and 818 HURs.

The research area is a typical area dominated by agroforestry ecosystems, and there are eight types of land. The land-use types that cover the biggest area include forest land, paddy field and dry land in sequence, accounting for 89.3% of the total watershed in the test area, as shown in Figure 1. The division of its sub-basins and the distribution of water systems are shown in Figure 2.

The EFDC model, also called Environmental Fluid Dynamics Code, integrates multiple mathematical models, including hydrodynamic module, temperature module, salinity module, dye module, water quality module, sediment module and Lagrangian tracer. It can be used in water bodies such as rivers, lakes, estuaries, reservoirs, wetlands and coastal areas, covering the simulation of processes, such as one-dimensional, two-dimensional and three-dimensional flow fields of water systems, material transportation, ecological processes and freshwater inflow.

Firstly, we rely on the Google Earth image map to draw the river base map according to the river channel generated by the SWAT model, and then use the CVLGrid1.1 to generate a grid of all the river channels. After that, we use the elevation and water depth data of each point in the sub-basin file output by the SWAT model and employ the terrain interpolation function of EFDC to set the river topography and water depth of the entire study area. Then, the hydrology and pollution source load data, as well as the measured water temperature and meteorological data required in the .rch file output by the SWAT model, are used as the boundary conditions of hydrodynamics and water quality to realize the coupling of the SWAT simulation and the EFDC model. Subsequently, all the pollution sources in the basin are generalized as point sources and non-point sources, and input into the EFDC model. At last, the generalized pollution source setting interface diagram is obtained, as shown in Figure 3.

The SWAT model simulation period is from January 2000 to December 2019. To avoid the errors because many variables are zero at the beginning of the model operation, the first 5 years are selected as the model's warm-up period to improve the model accuracy. The runoff, ammonia nitrogen and total phosphorus data of Daoxian Station and Lengshuitan Station were selected in the upstream and downstream, respectively, for parameter calibration and result verification. The spatial calibration was implemented sequentially from upstream to downstream; in terms of calibration object, the calibration of the flow was made first, which was followed by the calibration of the ammonia nitrogen and total phosphorus (Moriasi et al. 2015). Daoxian Station uses the period from 2005 to 2017 as the regular rate, while Lengshuitan Station uses the period from 2012 to 2017. And both stations use the period from 2018 to 2019 as the verification period. Because Lengshuitan Station was built in 2012, the observation data started in 2012.

The model selects R² (coefficient of determination) and E_ns (Nash–Sutcliffe efficiency coefficient) as the indicators for model evaluation. The certainty coefficients of runoff, ammonia nitrogen and total phosphorus of the two stations are greater than 0.68, and the Nash coefficient is greater than 0.61 (refer to Table 2 for details). It is generally believed that if the conditions, i.e., R² > 0.6 and E_ns > 0.5, are satisfied at the same time, and the simulation results are acceptable (Zhao et al. 2017).

The EFDC model simulation time period is from January 1, 2017 to December 31, 2017, with January 1, 2017 as the 0th day, and December 31, 2017 as the 364th day. The time step of the model is 5 s, and the initial water temperature is set to 6 °C. Using the cold start and based on the EFDC's hydrodynamic module, temperature module and water quality module, the model selects the parameters related to chemical oxygen demand, nitrogen and phosphorus and uses the water quality monitoring data of Daoxian Station from January to May 2017 for adjustment. Besides, it employs the data of water level, water temperature and water quality of Daoxian Station for verification.

In this study, the data of water level, water temperature and water quality of Daoxian Hydrological Station in 2017 were selected for calibration. As shown in Figure 4(a)–4(d), the relative error range of the water level at Daoxian Station in 2017 was between 0.35 and 1.37%, the relative error range of water temperature was between 0.5 and 17.06%, the relative error range of ammonia nitrogen was between 2.67 and 14.8% and the relative error range of total phosphorus was between 1.14 and 23.32%. Because the relative error of all data is within 25%, and the curve fits well with the actual value, the simulation effect of the model is great (Fan 2017).

According to the Calculation Regulations for Pollution Capacity of Water Area (GB/T25173-2010) (Li 2019), the design flow rate should be 90% of the driest monthly average flow or the driest monthly average flow for the past 10 years. However, using the average flow rate of the driest month for the past 10 years is too strict for the Xiangjiang River Basin where the water quality is still excellent. Based on the actual situation, 90% of the average flow rate of the driest month is selected as the design flow to calculate the conservative water environment capacity (Ma et al. 2021). On the other hand, the pollutant source survey data of this project uses 2017 as the base year. Therefore, the average flow in 2017 is selected as the design flow for the calculation of the WEC and remaining environmental capacity in 2017.

According to the results of the Yongzhou Water Environment Function Zoning (YWRB 2014), the Xiangjiang River Basin in Yongzhou is divided into 58 first-level water function areas and 53 second-level water function areas. At present, the current water quality of the assessment sections in all functional areas is better than that of Category III. According to the requirements of the Ministry of Ecology and Environment of the People's Republic of China on the cross-sectional assessment of national and provincial water quality control in the Yangtze River Basin and the principle of ‘improving only, not deteriorating’, the eight source protection areas implement the Surface Water Environmental Quality Standards(GB3838-2002) Class II standard, and the rest follows the Class III water quality standard.

Note that due to the lack of measured concentration data at the inlet and outlet of each sub-basin, the pollutant concentration value output by the EFDC model was used in this study to determine the degradation coefficient.

According to the calculation formula of one-dimensional theoretical water environment capacity, using the total nitrogen and total phosphorus as the accounting factors, the 90% driest monthly average flow and 2017 monthly average flow of each sub-basin were selected as the design hydrological parameters. The concentration results of total nitrogen and total phosphorus at the upstream outlet output by the EFDC model were used as the pollution concentration C₀ of the river section. In the meantime, the WEC of each sub-basin river section was calculated based on the following factors, including the water quality target of the water function zoning as the standard concentration C_s for pollutant control, the sum of the pollutant flows of the sub-basin as the total discharge q of the sub-basin, the flow of the upstream water outlet as the design flow Q₀, the average flow velocity of each grid of the river section as u, and k determined by the empirical attenuation system. According to the classification requirements of water body types, the 115 sub-basins in the Yongzhou Section of Xiangjiang River Basin are divided into 36 secondary basins, and the water environment capacity is shown in Figures 5 and 6. It can be seen from Figures 5 and 6 that the top three water environmental capacities of total nitrogen and total phosphorus in the Yongzhou Section of Xiangjiang River Basin are the main basin of the Xiangjiang River, the Yongming River basin and the Luhong River basin. While the last three are Moujiang River Basin, Hengjiang River Basin and Shejiang River Basin, all of them are located within the territory of Shuangpai, Yongzhou. The main reason is that the three tributary rivers are short with small flow. The WEC of the=total nitrogen in the Yongzhou Section of Xiangjiang River Basin in 2017 was 27,673.04 t, which was 19,497.61 t/a under the 90% guarantee rate, about 0.7 times of the total. The WEC of total phosphorus in the Yongzhou Section of Xiangjiang River Basin in 2017 was 4,877.22 t, which was 2,938.64 t/a under the 90% guarantee rate, about 0.6 times of the total. Obviously, the WEC of total phosphorus suffers a stronger impact by hydrological conditions than the total nitrogen does. Furthermore, the result shows no matter what the hydrological conditions were, the river basin with longer river generally had a larger WEC, which was consistent with that of Ma et al.’s (2021) paper.

According to the long-term hydrological statistics of the Yongzhou Section of Xiangjiang River Basin, the Xiangjiang River has a wet season from May to September, a dry season from December to February, and the rest of the time belongs to the normal season. It can be seen from Figures 7 and 8 that the WECs of total nitrogen and total phosphorus in the secondary watershed of the Yongzhou Basin of Xiangjiang River at different water periods in 2017 are sequenced in the descending order as wet season > normal season > dry season, the WEC had an uncertain range of fluctuations during the year, as noted by Ma et al. (2020). The main reason for the largest water environment capacity in the high water period is that the non-point source nitrogen and phosphorus pollution is well controlled. Although the pollution of nitrogen and phosphorus is heavy during the wet season, the WEC increases faster when the river flow increases on a large scale. The WECs of total nitrogen and total phosphorus in the dry season are 6,821.23 and 966.46 t, respectively; those in the normal season are 9,243.36 and 1,622.83 t, respectively and in the wet season, the above values are 11,608.45 and 2,288.93 t, respectively. The WECs of total nitrogen and total phosphorus in the wet season of the Xiangjiang River Yongzhou Basin are about twice that in the dry season, while in the normal season, it is generally about 1.5 times that in the dry season. The WEC of total nitrogen is slightly less than twice and 1.5 times, while the WEC of total phosphorus is slightly larger than twice and 1.5 times, showing that the capacity is large in summer and autumn, and small in spring and winter.

It can be seen from Figures 9 and 10 that the overall situation of the residual WEC (the residual WEC is equal to the actual WEC minus the current pollutant emissions) of total nitrogen and total phosphorus in the Yongzhou Basin of Xiangjiang River is relatively good. In 2017, the residual WECs of total nitrogen and total phosphorus in the entire basin were 14,646.69 and 3,358.67 t, respectively, and the remaining WECs of all secondary basins were positive. In general, the residual WEC of total phosphorus in the Yongzhou Section of the Xiangjiang River Basin was larger in the southern region and smaller in the northern region. Among the secondary basins in the Yongzhou Section of Xiangjiang River Basin, the remaining WECs of total nitrogen and total phosphorus in the main basin of the Xiangjiang River were the largest, i.e., 4,861.39 and 1,191.11 t/a, respectively. Meanwhile, its current emissions of non-point source nitrogen and phosphorus pollution were also relatively large. The principle of ‘Focusing on governance, improving quality and efficiency’ is practiced, and agricultural non-point source pollution prevention and control measures are taken to promote the development of existing agricultural industrialization. The remaining WECs of total nitrogen and total phosphorus in the Yanjiang River Basin were the smallest, i.e., 2.57 and 0.57 t/a, respectively. The development of large-scale agricultural development projects, as well as the livestock and poultry breeding projects in this basin, must be strictly restricted. The residual WECs of total nitrogen and total phosphorus in the Baishui River Basin, Yanjiang River Basin, Yijiang River Basin, Ningyuan River Basin, Jiuyi River Basin, Mengba Basin and Yongming River Basin were relatively large, and its non-point source pollution control was well implemented. When formulating plans for livestock, poultry breeding and agricultural planting in the basin, the government can appropriately expand the scale following the principle of ‘Combination of prevention and control, and green development’. The residual WECs of total nitrogen and total phosphorus in the Yanjiang River Basin, Daheba Basin, Maojiang River Basin, Yongjiang River Basin, Hengjiang River Basin, Moujiang Basin, Shejiang River Basin, Zhonghe (Shuangpai) Basin, Longjiangqiao Basin and Lianxi River Basin were relatively small, and their current emission levels of total nitrogen and total phosphorus were relatively high, which were the key areas for non-point source control and water environmental protection in the entire river basin. These river basins are environmentally sensitive areas, and the principle of ‘Governing priority, strict control of increments’ should be implemented in addition to the utilization of the existing environmental capacity and appropriate development. Moreover, the results of the remaining WEC could be applied to divide the water environment control units in the Yongzhou Section of Xiangjiang River Basin and build a water environment zoning management and control system.

• 1.

  The simulation curve of the SWAT and EFDC coupling model shows good curve fitness with the actual value, and the relative error is within the acceptable range. Therefore, the simulation effect of the model is good.

• 2.

  The total nitrogen WEC of the Yongzhou Section of Xiangjiang River Basin in 2017 was 27,673.04 t, which was 19,497.61 t/a under the 90% guarantee rate; while the total phosphorus WEC of the Yongzhou Section of Xiangjiang River Basin in 2017 was 4,877.22 t, which was 2,938.64 t/a under the 90% guarantee rate. Obviously, the WEC of total phosphorus suffers a stronger impact by hydrological conditions than the total nitrogen does.

• 3.

  The WEC had an uncertain range of fluctuations in 2017, the WECs of total nitrogen and total phosphorus in the low water period were 6,821.23 and 966.46 t, respectively, those in the normal water period were 9,243.36 and 1,622.83 t, respectively and the values in the high water period were 11,608.45 and 2,288.93 t, respectively.

• 4.

  The overall situation of the residual WECs of total nitrogen and total phosphorus in the Yongzhou Section of Xiangjiang River Basin River is relatively good. In 2017, the residual WECs of total nitrogen and total phosphorus in the entire basin were 14,646.69 and 3,358.67 t, respectively. The residual WECs of total nitrogen and total phosphorus in the Yanjiang River Basin, Daheba Basin and Maojiang River Basin were relatively small, and their current emission levels of total nitrogen and total phosphorus were relatively high, which were the key areas for non-point source control and water environmental protection in the entire river basin.

This work was supported by the National Natural Science Foundation of China (No.51638006); National Natural Science Foundation of China Youth Fund (No.41807136); Guangxi Science and Technology Base and Talent Special Project (Guike AD19110012); Guangxi Key Laboratory of Environmental Pollution Control Theory and Technology Open Fund (Guikeneng 1701K006).

All relevant data are included in the paper or its Supplementary Information.