Study on the proportion and flow path of Yangtze River water diversion into Taihu Lake Open Access

With intensive human activities, the uneven distribution of water resources and pollution-induced water shortages make regional water diversion more frequent, and the impact of water diversion projects on lake hydrodynamics, water quality, and water ecology has gradually become a hot issue. (Zhang et al. 2016; Song et al. 2019a, 2019b; Zhang 2019; Dai et al. 2020b; Xu et al. 2020c).

Taihu Lake is a typical large shallow-water lake. Since the end of the last century, the volume of water entering Taihu Lake has increased from seven billion cubic meters to 11 billion cubic meters, and the lake residence period has decreased from 300 days to approximately 170 days. In addition, the hydrodynamic conditions of the lake body and the hydrological regime of the basin have undergone significant changes (Xu et al. 2020c). With the implementation of the water diversion project from the Yangtze River to Taihu Lake (WDYT) and the construction of increasingly intensive regional water conservancy projects, a large number of studies have shown that artificial external water diversion is highly correlated with changes in the residence period in Taihu Lake (Hu et al. 2008; Zhai et al. 2010). However, previous studies have focused on the influence of water diversion on the hydrodynamics and water quality of Taihu Lake, focusing on the internal migration and transformation process of the lake body after water diversion (Li et al. 2013a, 2013b; Xu et al. 2020a). Very little research has been done on the flow process in the river network from the Yangtze River to the entrance of the lake, which leads to an unclear knowledge of the weight of the water diversion in the lake volume and the route into the lake in the complex river network.

The aim of this study was to investigate the source and path of water inflow into Taihu Lake, namely the surface water traceability. Currently, the research on water traceability primarily includes three types: the isotope tracer method based on physical and chemical characteristics; the source acceptor model method based on water quality monitoring data; and the hydrological inversion method based on the mathematical model (Liu & Yamanaka 2012; Gholizadeh et al. 2016; Murphy 2019; Yi et al. 2020). However, in a plain river network area, a large number of monitoring stations needed to be established; besides, it was difficult to conduct such research due to the density and accuracy of monitoring stations for water quantity and water quality in the Taihu Lake Basin.

In recent years, with the rapid development of computer computing power and improvements in monitoring data, mathematical models of the water environment have been widely used in hydrological inversion simulations and pollution source analyses of watersheds (Jin & Yong n.d.; Zhang et al. 2010). Yan et al. evaluated the inflow of pollutants from different underlying surfaces under rainfall-runoff based on the Walrus model. Based on the SWAT model, Chen et al. analyzed the source of phosphorus in the river system of the Yonghe River Basin and its flow state in the river network (Cheng et al. 2021). Essenfelder et al. introduced the coupled machine learning method based on hydrological simulation and proposed a simulation of the IWT flow contribution without observed data (Essenfelder & Giupponi 2020). Dou et al. established a one-dimensional hydrodynamic model and a heavy metal migration model to evaluate the influence of changes in hydrodynamic conditions on the cadmium migration in a tidal energy river network and summarized its migration rules (Dou et al. 2013). Considering the scale of the Taihu Basin is larger and intensive monitoring points are required to more fully cover the river network area, it is difficult to analyze the source receptor model or perform an isotope experiment. In previous studies, a river in plain river network areas was usually generalized as a one-dimensional model, because rivers in this region often only need to consider the diffusion process along the length direction. In Changzhou, Yixing, Wuxi and other areas of the Taihu basin, the 1-D river network model has achieved good simulation results, which can be used to calculate the river hydrodynamic force and the migration and transformation process of algae, heavy metals and other substances in the region (Wang et al. 2017; Chen et al. 2019a; Bu et al. 2020; He et al. 2020).

It can be seen from the previous studies that the solution of the convection-diffusion equation is the main technical method to study the material diffusion with water flow (Song & Pang 2019; Pang et al. 2020). The implicit finite control volume method is widely used in water quality model because of its good conservation and stability, with the simple structure and versatility program (Appadu 2013). Luo et al. have simulated the migration process of pollutants in the river network in Yixing area by using the hypothesis of full mixing, which has proved the availability of this method in a plain river network area (Li et al. 2019, 2020). On the basis of the use of the fully mixing hypothesis, we adopt conservative material from different sources of water, avoid the different types of water, conservative the degradation of material from other sources, thus obtained by conservative substance concentration within a certain section of the water in the river network composition proportion, in order to study the flow path of different water sources from diversion stations.

This study is based on hydrological data analysis from 1990 to 2019, constructing a complex river network mathematical model coupled with the convection-diffusion model of conservative material. The aim of this study is to calculate the proportion and flow path of water diversion from Yangtze River into Taihu Lake, which could provide strong support for subsequent regional water transfer projects and integrated regional pollution control programmes.

The study area is located in the Middle-Lower Yangtze plains (119°05 ‘01 ‘E, 32°15′ 30″ N–120°57 ‘10 ‘E, 31°7′ 9″ E) and includes two water conservancy zones: the Wucheng Area and the West Lake Area, with a total area of 11,000 km² (Figure 1). The region has a subtropical monsoon climate, with high temperatures in summer and little rain in winter. It is one of the most densely populated and economically active regions in China. The area connects the Yangtze River and the Taihu Lake area with the plain river network, and it is surrounded in the west by mountains and in the east by the Wangyu River, which is divided into separate basins. The overall topography is high in the west and low in the east, the surface elevation of the plain area is 5–8 meters. The general trend of river flow is from west to east, but due to tides, flat terrain and artificial scheduling, reverse flow is often present.

From 2007 to 2017, the total water inflow from the Wucheng Area and the West Lake Area accounted for approximately 75% of the total water inflow from Taihu Lake, and the 10 main sluice stations along the Yangtze River accounted for more than 85% of the total amount of water diverted from the Taihu Basin (Ji et al. 2019), including the Jianbi Station (JBS), the Jiuqu Station (JQS), the Xinmeng River Station (XMS), the Weicun Station (WCS), the Zao River Station (ZRS), the Xicheng River Station (XCS), the Baiqu River Station (BQS), the Zhangjiagang River Station (ZJGS), the Eleventh River Station (ELVS), and the Changshu Station (CSS), with an average annual diversion volume during the past decade of 5.01 billion cubic meters. Due to the implementation of a water diversion project from the Yangtze River to Taihu Lake, the eastern portion of the Wangyu River contains sluice gates. In addition to evaporation, the water in the region is primarily discharged into the Yangtze River during the flood season, flows to the downstream areas along the Grand Canal and flows to Taihu Lake. The water flowing into Taihu Lake is primarily from 15 main rivers, with an average inflow of 11.16 billion cubic meters during the past 10 years. In recent years, in order to reduce the impact of nutrients from the rivers that enter Taihu Lake, the sluice gates at the entrance of the WJR, ZHR, LXR, and XXR are closed all year round, and the WITL primarily flows through the West Lake Area and Zhushan Bay (ZSB).

In this study, the meteorological data from 1990 to 2019 including Liyang station (58345) and Changzhou station (58343) were obtained from China Meteorological data network (http://data.cma.cn/). The amount of YRD and WITL from 1990 to 2019 has been published by the Taihu Basin Administration (http://www.tba.gov.cn/). The urban area from 1990 to 2019 is obtained from the annual remote sensing image data of 30 m precision downloaded from the Geospatial data cloud (http://www.gscloud.cn/) after processing with Envi5.3.

The method in this paper is firstly to analyze the variation trend of WITL and YRD by MK mutation test. Secondly, a one-dimensional simulation model was constructed to simulate the flow process of YRD in the complex river network area. Finally, conservative material markers were added for different diversion sources, so that the water composition types of different sections could be quickly obtained through the simulation process, and the proportion of water and the change process in space could be calculated (Figure 2).

UF_k :Following the standard normal distribution and given the confidence level α, the same method was applied to the time series in reverse order (x_n,x_n−1,x_n−1,…,x₁). Then UB_k̀ = −UF_k and k̀ =n+1−k. The UF_k, UB_k̀, and U_α curves (U_0.05=±1.96) were then analyzed. When the UF_k or UB_k̀>0, this indicated an upward trend. When the UF_k or UB_k̀ < 0, this indicated a downward trend. When the trend curve exceeded the U_α curve, this indicated a significant upward or downward trend. When the UF_k and UB_k̀ curves intersected between the U_α curves, the intersection point was the moment of mutation (Yue et al. 2002; Hamed 2009; 2008; Kisi & Ay 2014).

The measured discharge of the primary rivers that enter Taihu Lake and the calculation results of the model were calibrated. According to the regional annual rainfall data from 1990 to 2019 obtained from China Meteorological Data Network (http://data.cma.cn/), the years of P = 10%, P = 50%, and P = 90% were selected to define 2016, 2014, and 2013 as the wet, normal, and dry years, respectively, in this calculation. The model parameters were calibrated in 2014 (normal year) and verified in 2013 (dry year) and 2016 (wet year). The regional water quantities for each typical year are shown in Table 1.

The primary riverways in the research area were generalized as 125 branches in the model (Figure 1). The model consisted of 21 upstream boundaries and 22 downstream boundaries.

The upstream boundaries were set as a time-serialized flow value, including the diversion flow and the inflow flow of the mountain rivers. Among them, the diversion flow is obtained from the open data on the website of Taihu Basin Administration (http://www.tba.gov.cn/), while there is no measured data on the inflow flow of mountainous rivers, in this study which is calculated by NAM model using the meteorological data of Liyang Precipitation station. NAM model can be used to calculate the runoff of a individual watershed as a inflow boundary of a hydrodynamic (HD) model's river network.

The downstream boundaries were set as a time-serialized water level value: the river flowing into Taihu Lake is set as the water level of Taihu Lake; the river channel flowing into Yangtze River is set as the interpolated water level of the surrounding hydrological stations; in addition, the outflow boundary of the Grand Canal is set as the water level of Fengqiao Station. All the water level data were obtained from the open data on the website of Jiangsu Provincial Water Resources Department (http://www.jiangsu.gov.cn).

There were a total of 1,287 calculation nodes for the water levels and flows. The control of the dams and sluices in the river network was calculated based on the principle of the Taihu Lake water level control line and the actual daily water volume in the Annual Hydrological Report P.R. China.

where N is the total number of simulations; i is the number of simulations; S_i is the value of the ith simulation; M_i is the value measured in the ith time; is the simulated average; and is the measured average value.

The four selected rate points were the representative inflow rivers to each bay of Taihu Lake, and the evaluation results of each station (Table 1) showed that the simulated flows were in good agreement with the measured flows. The Manning coefficients of each section of river in the model were calibrated to 0.018–0.03 s·m^−1/3 (Xia et al. 2018), and the comprehensive runoff coefficient was 0.4–0.7 (Chen et al. 2019c). The simulation accuracy of the amount of water into the lake reached greater than 90%, which can reflect the hydrological and hydrodynamic processes of each typical year in the study area (Figure 4).

According to the measured data from 1990 to 2019, the M–K mutation test method was used to analyze the rainfall, water diversion, and lake water inflow (Figure 5). When the significance level, α, was set at 0.05, the threshold value of whether the M–K bilateral test statistic passed the test was ±1.960 (Yue et al. 2002; Chen et al. 2007). Before 2000, the average amount of WITL in the study area was about 4.5 million, and it then showed a significant upward trend and mutation points around 2003. The primary factors that affected the amount of lake water were natural rainfall and artificial water diversion (from the Wangyu River and other stations along the river), and the runoff of natural rainfall was primarily related to the annual rainfall, evaporation, and the regional runoff coefficient (land use type) (Hundecha & Bárdossy 2004). Although the rainfall and evaporation have a slight upward trend, they remain stable on the whole and there is no significant abrupt change. There were similar mutation years in urban area, water diversion along the river and water inflow into the lake, all of which increased significantly in 2003, and the changing trend of water diversion along the river and water inflow into the lake was basically the same (Zhou et al. 2013).

Around 2003, the Taihu Basin witnessed the most rapid economic development. Rapid economic development and population concentration led to the expansion of urban area, and at the same time, the regional water demand was greatly increased (Zhang et al. 2017, 2016; Yan 2018; Wu et al. 2020). A series of water diversion and drainage projects in the Taihu basin began to be implemented from this period. In 2002, the ‘Yangtze-Taihu Water Diversion ‘ project of Wangyu River began to run formally (Li et al. 2013b), the construction of the diversion station along the Yangtze River in Wucheng Area also has been constantly improved, and the water diversion has also begun to rise steadily (Xu et al. 2020a). Over the past 30 years, the YRD has increased by 84%, while the WITL has increased by 95%, which shows that there is a close relationship between the two, but the proportion of the YRD and how to reach the Taihu Lake through the Grand Canal still need to be quantified by hydrodynamic model (Ji et al. 2019).

Based on a 1—D hydrodynamic model coupled with the convection-diffusion model of conservative material (Zhu et al. 2003), the definition of rainfall runoff was the first type of conservative material, termed RR. The water diversion from the Yangtze River stations maintained material for the second category of the WD, which was subdivided into the water diversion of each station. The proportion of the YRD in the WITL was investigated during three typical years of wet, normal, and dry. The data of this study were based on the period from 2013 to 2016, and the regional runoff coefficient did not change significantly during this time (Hu & Wang 2009; Zhou et al. 2013). Therefore, it can be considered that the amount of natural rainfall runoff in recent years was only related to the annual precipitation, while the amount of the YRD was connected to the annual rainfall, regional water demand, and other factors (Li et al. 2013b).

The results showed that annual rainfall accounted for the largest proportion of lake water volume in the three typical years, with a weight range of 73.6–58%. In contrast, the weight of the water diversion from the river accounted for 26.4–42% (Figure 6). It can be seen that during dry years, the YRD accounted for nearly half of the total water inflow into the lake, which was basically consistent with the trend of the analysis of the water inflow into the lake by Zhu Wei and other scholars (ZHU et al. 2021). This indicated that the proportion of the YRD in the WITL has reached a point in recent years that cannot be ignored.

This was primarily due to the rapid economic development of the Taihu Lake Basin, which has led to a direct increase in the regional water consumption. In addition, under the condition of insufficient natural rainfall in the region, the demand for the YRD water has increased significantly (Jin & Yong n.d.). Additionally, the rapid construction of regional infrastructure during the past two decades has led to an increase in the regional runoff coefficient during the past two years, which has reduced the natural water storage capacity of the region, highlighted the shortage of available water in the region, and stimulated the demand of water diversion along the river in reverse (Zhai et al. 2010; Deng et al. 2016). The dry year, due to the lack of rainfall, led to the YRD demand increases, which made the West Lake Area water quantity increase in recent years by 30% relative to the 1990s, which was consistent with the average weight of the YRD.

Furthermore, according to the analysis of the primary river into Taihu Lake due to the influence of the proportion of the YRD, it was found that the most affected by the YRD was the Wangyu River, because its channel is direct from the Yangtze River to Taihu Lake. The YRD accounts for the vast majority of the proportion, and the amount waterlogging water floods affected due to the artificial scheduling area exist mostly outside the Yangtze River, the annual rainfall into the lake is generally less than 5% (Hu et al. 2008). Except for the Wangyu River, the Xiaoxi River, the Liangxi River, the Zhihu River, and the Wujin River, because the gate was closed all year round, its water quantity into the lake was basically zero (Wang et al. 2019) (Figure 6). In addition, Taige River is the largest river in the western part of the lake that is affected by the river diversion (35%–72%), followed by the Caoqiao River and the Taige South River, which run into Zhushan Bay. This also has certain influences on the Zhandu River, the Shedu River, the Guandu River, and the Chengdong River in the West Lake Area, and rivers south of the Chengdong River, such as Wuxi River, which was the least affected by YRD (1–3%) showing a decreasing trend from north to south.

The spatial heterogeneity of the results indicates that the water diversion ratio is closely related to the water diversion distance, because the longer water diversion channel is more able to dilute the proportion of water coming from the source, which is very important for the selection of the water diversion point (Deng et al. 2016). Such as for the Taige River, which is the river with the largest discharge into Zhushan Bay of Taihu Lake, the YRD accounts for more than 40% of the total water volume in the dry year, Taige River had an important influence on the water quality of Zhushan Bay. Therefore Zhushan Bay had the worst water quality and the most serious eutrophication in Taihu Lake, which was closely related to the water diversion. If the YRD continues to increase, the pollution flux into Zhushan Bay will be greatly increased, bringing a huge risk of eutrophication to the lake area or even a wider area (Wu et al. 2019; Zhang et al. 2020).

Based on the research of WITL composition, the YRD ratio of the upper river of WITL was calculated, again marked the upper with different conservative materials and use the model to recalculate. The path of water diversion flowing from the diversion station to the middle river, then from the middle river to the primary inflowing rivers is obtained (Figure 7). This was done to obtain the primary flow paths in the river network after the water diversion. The water diversion paths of the YRD were summarized into the following four paths (Xu et al. 2020b):

• (1)

  The WYR Pathway: YRD → WYR → Gong Bay

• (2)

  The WYYR Pathway: YRD → WYYR (YAR,XLR) →TGR (CQR,TSR) → Zhushan Bay

• (3)

  The Western Ge Lake Pathway: YRD → DJLCR → HLR (BGR,ZGR) → Ge Lake → TGR (CQR,TSR,SDR) → Zhushan Bay

• (4)

  The NXR Pathway: YRD → DJLCR → CDR (GDR,HXR,DPR,WXR) → West Lake Bay

It can be seen that the proportions of YRD → WITL pathways were basically the same, and the water quantity of each pathway fluctuated with a change in the actual water diversion from each station during three typical years (Figure 7). The water diversion from Changshu Station basically through Wangyu River flowing into Taihu lake (more than 98%). The total amounts of water diversion along this path into the lake during the wet, normal, and dry years were 12.3%, 39.1%, and 43.7%, respectively. In addition, due to the high water level of the Wangyu River during the diversion period, there was very little diversion from the Baiqu River, the Zhangjiagang River, and the Xicheng River entrance through the reciprocating river network into the Wangyu River. Therefore, the WYR pathway was less affected by the external water volume, which could be the highest quality water access filling water for Taihu Lake compared with the other pathways (Yan 2018; Xu et al. 2020a).

The second WYYR pathway had the largest amount of water quantity into the lake, which accounted for 51.6%, 34.5%, and 27.4% of the water diversion into the lake during the wet, normal, and dry years, respectively. It primarily transmits water from the Jianbi Station, the Jiuqu Station, the Weicun Station, and the Xinmeng Station to Taihu Lake, among which the Wuyi River is the most important connecting water transport route. It then flows primarily via the TGR and TSR into Taihu Lake. The third pathway of the Western Ge Lake Pathway accounted for 34.9%, 23.7%, and 26.8% during the wet, normal, and dry years, respectively, and the primary water sources were the JBS, JQS, and XMS after going through the HLR, BGR, and ZGR flowing into Ge Lake. In addition, they also then went through the TGR and TSR to enter into Taihu Lake. This pathway is also in the line of the upcoming Xinmeng River water diversion project, and at that time BGR will also become the primary water transmission route after the water diversion project is completed. The NXR pathway had only 1.2%, 2.6%, and 2.1% of the water quality pass through this water transmission line. The river in this area was not affected by the water diversion along the river, and the primary water source was the rainfall confluence of the Yixing–Liyang mountain area.

According to the YRD stations perspective, the water diversion was more primarily from the CSC, XCS, JBS, JQS, XMS, DSS, and ZRS. However, in the east of the ZGS, BQS, XCS, ELVS and ZJGS, there was very little water diversion into the lake as a result of the gate surrounding Zhushan Bay and Gong Bay nearly being closed all the year (Tang et al. 2020). A portion of the water diversion from these stations was discharged to the Yangtze River through the surrounding rivers, and the other portion was discharged into the Grand Canal. Currently, relevant studies have shown that the hydrological situation of the Grand Canal has changed, and the countercurrent phenomenon has increased in Changzhou section (Deng 2019). This may have been due to the high water level of the Grand Canal after the diversion of water from the eastern portion of the ZGS into the Grand Canal. This phenomenon is bound to lead to an increase in the YRD from the western ZGS station entry into the Taihu Lake because it is more difficult to flow into the Suzhou area through the Grand Canal. This is also an important reason why the YRD primarily enters Taihu Lake through the TGR, TSR and CQR.

From the perspective of water diversion pathways, the Wangyu River diversion pathway can be selected as a priority if it is needed to replenish water for Taihu Lake because the water quality of this pathway is relatively better (Zhao et al. 2011; Xu et al. 2020b). In addition, it will nearly not be affected by the pollution in the area of the river network after the completion of the subsequent Wangyu River-related projects. As for the WYYR pathway and the Western Ge Lake pathway, although they also have a high efficiency on transport into the lake, at the same time it should be noted that with a lot of the YRD going through the Changzhou, Yixing, and Liyang areas, this will also carry a large number of pollutants into the water channel from the cities, which will cause the Taihu Lake pollution load flux to increase dramatically (He et al. 2021). Therefore, the subsequent increase in water diversion should be based on the improvements in regional land pollution control; otherwise, the YRD is bound to bring the deterioration of water quality and water ecology in Taihu Lake (Dai et al. 2020a).

The proportion of water diversion from Yangtze River in the water inflow from Taihu Lake are calculated by 1-D hydrodynamic model coupled with the convection-diffusion model of conservative material. The results showed that:

• (1)

  The proportion of water diversion along the river into the lake cannot be ignored. During the past 30 years, the WITL and YRD have obviously increased, and the contribution of the YRD has reached 26.4–42% in typical wet, normal and dry years.

• (2)

  The contribution of the water diversion along the river to the main rivers into the lake was primarily affected by the spatial relationship. Taige River is the largest river in the western part of the lake that is affected by the river diversion (35%–72%), and Wuxi River is the smallest (1–3%).

• (3)

  The direct path for the YRD to enter Taihu Lake was through the Wangyu River, and the path with the largest amount of water was through the TGR and TSR of the WYYR and Gehu Lake.

This work was supported by the Major Science and Technology Program for Water Pollution Control and Treatment of China (2018ZX07208–005), the Fundamental Research Funds for the Central Universities and the World-Class Universities (Disciplines), the Characteristic Development Guidance Funds for the Central Universities, and the National Natural Science Foundation of China (No. 51879070)

All relevant data are available from an online repository or repositories at http://jssslt.jiangsu.gov.cn/, and http://www.tba.gov.cn/slbthlyglj/sj/sj.html.