Spatiotemporal changes of eutrophication and heavy metal pollution in the inflow river system of Baiyangdian after the establishment of Xiongan New Area

Introduction

Water quality of inland waters is increasingly disconcerting for a long period due to the hazardous impacts of water deterioration in the world (Huang et al., 2019; Tong et al., 2017; Wang et al., 2021a). The water quality of inland waters is determined by numerous factors such as climate, hydrologic conditions, and anthropogenic activities (Sinha, Michalak & Balaji, 2017; Wang et al., 2021a; Zhuang et al., 2019). Generally, land use intensification and urbanization with increased population density have been considered as the most important driving factors for the declining water quality in inland waters (Huang et al., 2019; Tong et al., 2017; Zhou et al., 2017), which resulted in the increased wastewater discharge from households, agriculture and industry (Meng, Zhang & Shan, 2021; Tong et al., 2017; Zhou et al., 2017). In China, inland waters are generally surrounded by densely populated areas, and the severe contamination has occurred in these inland waters, such as Taihu, Dianchi and Poyang lakes (Lv et al., 2020; Wang et al., 2021a; Wu et al., 2017), as well as Baiyangdian (Li, Chen & Sun, 2021a; Meng, Zhang & Shan, 2021; Zhang et al., 2018). The water quality of inland waters has been extensively studied with special emphasis on topics, such as eutrophication (Sinha, Michalak & Balaji, 2017; Tong et al., 2017) and nutrient loading (Ni, Wang & Wang, 2016; Tao et al., 2020; Zhu et al., 2019). Eutrophication due to phosphorus and nitrogen pollution has posed a risk to the health and stability of the aquatic ecosystem, and ammonia nitrogen (NH₄⁺-N), total phosphorus (TP) and chemical oxygen demand (COD) are three important parameters of eutrophication in inland waters (Li et al., 2021b; Meng, Zhang & Shan, 2021; Ni, Wang & Wang, 2016; Tong et al., 2017; Zhao et al., 2020). Water pollution caused by heavy metals also has caused widespread concern due to their health threat to aquatic biota and humans (Rajeshkumar & Li, 2018; Zhang et al., 2017; Zhang, Wu & Giesy, 2019). At present, heavy metal pollution displayed an increasing trend in many lakes and reservoirs in China (Huang et al., 2019), and a large number of heavy metals were still released from historical polluted sediments, causing a high risk of contamination to the aquatic ecosystem (Ke et al., 2017; Vu et al., 2017; Zhang et al., 2018).

Pollution in inflow rivers seriously endangers the water environment in downstream lakes. Comprehensive measures have been made regarding pollution reduction in inland waters in last decades (Chen et al., 2021a; Wang et al., 2021b; Zhou et al., 2017); however, the serious pollutions were still frequently observable due to the measures not taking serious consideration of the water pollution in inflow rivers (Gao et al., 2021; Lv et al., 2020; Wang et al., 2021a). The inflow rivers and the stream networks could collect domestic, agricultural and industrial wastewater from densely populated areas in the whole watershed, which have become the main reason for the water deteriorating in the downstream waters (Aubriot et al., 2020; Gao et al., 2021; Lv et al., 2020; Wang et al., 2021a; Wang et al., 2021b). In addition, the dominant contributors to the pollutants were presently changed from point source pollution (e.g., local industries) to the diffuse source pollution and internal pollution loading, which had greatly spatiotemporal variations along the inflow river systems (Huang et al., 2018; Wang et al., 2017; Xia et al., 2018; Zha et al., 2018; Zhu et al., 2019). A single pollution control method could not deal with the spatiotemporally varied pollution (Huang et al., 2018; He et al., 2020). Thus, water quality management strategies could hardly be successful unless the spatiotemporal variation of water pollution are taken into serious consideration, and spatiotemporal flexible measures should be furtherly made along the inflow rivers for the greater improvement of water quality (Aubriot et al., 2020; Gao et al., 2021; He et al., 2020; Wang et al., 2021a).

Water quality of inland waters in the North China Plain was found to be the poorest in China due to the high coverage of developed land (cities and cropland) and population density (Zhou et al., 2017). In addition, the relatively increased evaporation in this region created more protracted periods of drought in spring and early summer, which prolonged the water retention time and amplifying the deterioration of water quality in inland waters (Piao et al., 2010; Sinha, Michalak & Balaji, 2017). Baiyangdian is the largest lake in North China Plain, playing an irreplaceable role in maintaining the environmental health in this region (Cheng, Bo & Sun, 2018; Guo, Huo & Ding, 2015; Yi, Lin & Tang, 2020; Zhao et al., 2021). However, with the rapid development of industry and agriculture, tons of pollutants were discharged into the water of inflow river systems and Baiyangdian since 1980s, which not only severely contaminated of the water body but also the sediments and aquatic biota (Guo, Huo & Ding, 2015; Meng, Zhang & Shan, 2021; Tao et al., 2020). The Xiongan New Area started to be built around Baiyangdian in 2017, which aimed to establish an advanced new area for the coordinated development of ecology and economy in China (Xia & Zhang, 2017). Since then, the water quality of Baiyangdian has been greatly concerned (Cheng, Bo & Sun, 2018; Meng, Zhang & Shan, 2021; Zhao et al., 2021). The Chinese central and local governments have made substantial investments to environmental remediation in order to improve the water quality in Baiyangdian watershed to guarantee the healthy development of Xiongan New Area (Chen et al., 2021a; Xia & Zhang, 2017; Zhao et al., 2021). Presently, point source pollution has been basically controlled (Chen et al., 2021a; Li, Chen & Sun, 2021a). However, the water pollution in Baiyangdian was still in a high level, especially the severely eutrophic parameters of NH₄⁺-N, TP and COD, as well as the serious heavy metal pollution of plumbum (Pb), cadmium (Cd) and chromium (Cr) in the water and sediments (Li et al., 2021b; Gao et al., 2019; Meng, Zhang & Shan, 2021; Zhao et al., 2021). The diffuse source pollution in this watershed became a main problem, such as agricultural sewage, domestic garbage and sediment release (Li et al., 2017; Li, Chen & Sun, 2021a; Tao et al., 2020; Zhu et al., 2019), which were carried by the inflow rivers from the whole watershed to contaminate the water environment in Baiyangdian and Xiongan New Area (Meng, Zhang & Shan, 2021; Tao et al., 2020; Zhao et al., 2020). Thus, eliminating the diffuse source pollution of the inflow rivers is critically important for the improvement of the water quality in Baiyangdian (Li, Chen & Sun, 2021a; Zhao et al., 2020; Zhao et al., 2021), and a flexible set of measures for water pollution control should be adopted considering the spatiotemporal differences of the diffuse source pollution (He et al., 2020; Huang et al., 2018; Tong et al., 2017). Surprisingly, our literature review has found that the spatiotemporal distributions and variability of water pollution in the inflow rivers of Baiyangdian have not been explored since the establishment of Xiongan New Area; in particular, we lack the timely understanding about the pollution hotspots, serious periods and potential sources in a whole inflow river system to distinguish the weak parts in current pollution treatments.

In this study, a typical inflow river system of the Baiyangdian–Fuhe river system (FRS) was selected, which is one of the main water sources of Baiyangdian and passes through a big city, as well as many towns and villages (Cheng, Bo & Sun, 2018; Guo, Huo & Ding, 2015). Thus, FRS received strong impact of anthropogenic activities and was considered as one of the most seriously polluted inflow rivers of Baiyangdian (Li et al., 2017; Liang et al., 2017). To better guide the pollution control strategies, we measured the water eutrophication (NH₄⁺-N, TP and COD) and heavy metal pollution (Pb, Cd and Cr) of the FRS from the headstream to the estuary in three seasons to investigate the spatiotemporal pollution pattern, identify the pollution hotspots and periods, and make a timely assessment of the water quality after the establishment of Xiongan New Area. We aimed to reveal the weak parts in current pollution treatments, and provide scientific basis to make spatiotemporally flexible measures for water quality improvement in Baiyangdian watershed. This study could be a reference for the water pollution treatment and ecological restoration in other inland waters.

Materials & Methods

Sample collection

A typical inflow river system of Baiyangdian–Fuhe river system (FRS) was selected to study the spatiotemporal pollution patterns and assess the water quality. Sampling was carried out sequentially along FRS from the headstream to the estuary area, taking into account of the topographic distribution, flow path distance and surrounding land uses, and a total of fourteen sampling sites were set up (Fig. 1). The source of FRS is located in the Mountain area in the west of Baoding. The area of the “headstream” in Fig. 1 is located near the mountain area and before the densely populated areas, thus we considered it is a part of the headstream of FRS. The water quality in FRS would not change too much during the water transformation in the mountain area due to the low anthropogenic activities and wastewater discharge. Therefore, we started our sampling from the “headstream” area in Fig. 1. River water was sampled in three seasons: spring (May, headstream was not collected), summer (July) and autumn (October) of 2020, respectively. In order to reduce experimental errors, at least four sample points were randomly selected in different areas in each sample site, and water samples at each sample point were taken at two depths: ∼0.1 m below the water surface (surface samples) and ∼0.3 m below the water surface (deep samples). Each sample was collected 150 ml water into a brown polyethylene bottle, which was acid cleaned and rinsed with surface water before sampling. The water samples were stored in a cooler with ice bags and then placed in a refrigerator at 4 °C after returning to our laboratory.

Results

Extreme pollution in individual sampling site of FRS in three seasons

The changes of eutrophication and heavy metal pollution along the sampling route in FRS are showed in Fig. 2. Three season average concentrations of eutrophic parameters (NH₄⁺-N, TP and COD) were higher in the sampling sites of out-of-city area and farmland area, whereas, the higher average concentrations of heavy metals (Pb, Cd and Cr) were concentrated in the out-of-city city area and town area. Pollution of eutrophication was generally worse than the heavy metal in FRS (Fig. 2). In spring, NH₄⁺-N in F6 and COD in F6, 11 were worse than Class V water standard (Table S2); the other parameters higher than Class III standard were: NH₄⁺-N in F7, TP in F7-8, COD in F7 and Cd in F8-9, 11, 14. In summer, NH₄⁺-N in F5, 7-14 were worse than Class III standard; the other parameters higher than Class III standard were: NH₄⁺-N in F2-4, TP in F8, 13, COD in F8 and Cd in F9. In autumn, NH₄⁺-N in F7, 13-14 and TP in F7, 9 were worse than Class III water standard. Overall, the pollution hotspots (>Class III standard) in FRS were mostly (>94%) appeared after the water flowing over the city.

Variation of water pollution among different classified areas

Sampling sites in FRS could be classified into five areas: Headstream, City, Towns, Farmland and Estuary (Fig. 1). There were greatly spatiotemporal changes in each pollution parameter among these five areas (Fig. 3): (1) NH₄⁺-N (average 4.59 ± 0.15 and 0.98 ± 0.04 mg L⁻¹) and TP (average 0.14 ± 0.01 and 0.11 ± 0.02 mg L⁻¹) were all higher in summer and autumn, and increased dramatically from the city area to the estuary; (2) NH₄⁺-N and TP had higher concentrations in city area in spring; (3) concentrations of COD (average 42.07 ± 6.93 mg L⁻¹) were higher in spring with the severe pollution in the city and farmland areas, whereas, COD in summer and autumn was higher in the city area; (4) Cd (average 4.58 ± 0.40 µg L⁻¹) also showed higher concentrations in spring than those in summer and autumn in each area in FRS, however there was no significant temporal variation in Pb and Cr; (5) Pb in spring and summer (16.65 ± 0.85 and 13.07 ± 0.39 µg L⁻¹) was worse than Cd and Cr; and (6) there was no significant spatial variation in Pb after the headstream, whereas, Cd (5.65 ± 1.27, 2.83 ± 0.64 and 2.73 ± 0.32 µg L⁻¹) and Cr (20.00 ± 4.15, 15.45 ± 2.43 and 21.14 ± 3.71 µg L⁻¹) in the town area in three seasons were all higher than other places in FRS.

Relationships among water pollution parameters in FRS

Pearson’s correlation analysis showed there were many strongly positive relationships in the eutrophic parameters and heavy metals (Fig. 4A). Eutrophic parameters: NH₄⁺-N significantly correlated with TP (p =0.0003). Eutrophic parameters and heavy metals: NH₄⁺-N, TP and COD all significantly correlated with Pb (p were 0.0129, 0.0485 and 0.0044), and COD significantly correlated with Cd (p < 0.0001). Principal component analysis (PCA) showed that the first and second principal components (PCs, denoted as Dims in Fig. 4B) explained 42.6% and 33% of the total variance of the heavy metal concentrations in FRS, respectively. Pb and Cd were both positively associated with PC1 with correlations of 66.6% and 79.2%, and Pb was negatively associated with PC2 (correlation: −54.9%); Cr was positively associated with PC2 (correlation: 83%), but also partly associated with PC1 with a correlation of 45.4% (Table S3).

Water quality assessment: changes of WQI with the distance to Baiyangdian

In spring, WQI_E mostly exceeded 1.5 in the areas of out-of-city and farmland in FRS (Fig. 5A), which indicated the water was moderately eutrophic based on Class III water standard in China (Table S1). In summer and autumn, WQI_E increased gradually from the headstream to the estuary area, which both had a significantly negative linear correlation with the distance to the estuary area (p were < 0.001 and 0.009). WQI_E in summer significantly increased from about 0.25 (unpolluted level) to around 2.5 (serious pollution) along FRS with a correlation curve slope of 0.027 (p < 0.001), which were dramatically higher than those in autumn.

Based on the Class I water standard, WQI_HM were all higher than 2.0 (moderate pollution, Table S1) when FRS flowed over the city in spring, and WQI_HM even significantly exceeded 2.5 in the middle areas of FRS (Fig. 5B). WQI_HM showed relative lower values in summer and autumn compared with spring, with significantly single peak curve patterns from the headstream to the estuary area (p were 0.002 and 0.021). The curves increased significantly from about 1.0 (unpolluted level) at both ends of FRS to more than 2.0 around the town area (p < 0.001). Based on Class III water standard, WQI_HM showed similar spatiotemporal variations along FRS, but all sampling sites were in unpolluted levels (Fig. S1).

Discussion

The eutrophication showed an overall improvement in many China’s inland waters in recent decades (Huang et al., 2019; Zhou et al., 2017). However, the nutrient pollutants were not fully eliminated: the moderate to heavy eutrophication were also found (Guo et al., 2020; Wang et al., 2017; Wu et al., 2017), and the continuous water quality improvement is needed to effectively control the water pollution in their inflow rivers (Lv et al., 2020; Wang et al., 2021a; Wang et al., 2021b; Gao et al., 2021). Our study found a considerable improvement of eutrophication in the inflow river system of Baiyangdian comparing with previous studies, particularly after the establishment of Xiongan New Area in 2017. In the city area of FRS, NH₄⁺-N dramatically decreased from 17.97∼36.92 (2009), 11.34 (2013), 13.33∼27.18 (2014) and 11.89 ± 1.26 (2017) to 1.98 ± 0.28 mg L⁻¹ in our study (Fig. 3); TP decreased even more greatly: from 2.34 (2008), 1.53 (2013), 1.23∼2.15 (2014), 2.25 ± 0.28 (2015) and 2.90 ± 0.18 (2017) to 0.19 ±0.04 mg L⁻¹; whereas, COD (17.65 ± 6.89 mg L⁻¹) moderately decrease comparing with 33.84 ± 4.47 (2005), 31.4 (2013), 54.63 (2014) and 56.93 ± 10.91 mg L⁻¹ (2017) (Dong, 2018; Jia, 2015; Li, 2014; Qiu et al., 2009; Wang et al., 2010). Similar changes of eutrophication were also observed in town and farmland areas (Dong, 2018; Li, 2014; Wang et al., 2010). Eutrophication in the estuary area was not improved so much: NH₄⁺-N from 13.20∼17.27 (2005-2009) to 3.51 ± 0.37 mg L⁻¹, TP from 0.34 (2008) to 0.14 ± 0.01 mg L⁻¹ and COD from 23.13 ± 4.81 (2005) to 13.17 ± 3.20 mg L⁻¹(Qiu et al., 2009; Li et al., 2017; Wang et al., 2010). However, the eutrophic parameters in nearly half of the sample sites in FRS still did not reach the present water quality requirement of Baiyangdian (Class III water standard, Fig. 3), and the NH₄⁺-N and TP in summer and COD in spring in FRS were all higher than those in Baiyangdian (Li et al., 2021b; Meng, Zhang & Shan, 2021; Zhao et al., 2020), which were great threats to the water quality of Baiyangdian (Table S2). In addition, the seriously eutrophic parameters were also observed in many sampling sites, particularly, the NH₄⁺-N and COD in spring and the NH₄⁺-N in summer significantly exceeded the Class V water standard in some hotspots (p < 0.001, Fig. 2), which may have tremendous influences on the water quality of the whole FRS and Baiyangdian. Thus, eutrophication, especially NH₄⁺-N and COD, did not improved in the whole FRS, and the current water quality treatments in Baiyangdian watershed only alleviated the eutrophic pollution in FRS. Furthermore, the eutrophication of Baiyangdian needed to be greatly improved to meet the higher water quality requirement as a natural reserve (Class I water standard, Table S2). All these demonstrated that more precise pollution remediations are needed to deal with the eutrophic pollutants in FRS in the future.

Water pollution caused by heavy metals has caused widespread concern due to their health effects on aquatic animals and humans (Ismail et al., 2016; Rajeshkumar & Li, 2018; Zhang et al., 2017), whereas many previous studies only concerned the eutrophication in the water of FRS and Baiyangdian (Jia, 2015; Li et al., 2021b; Liang et al., 2017; Zhao et al., 2020), and only one research has reported the pollution of heavy metals in the estuary area of FRS: Pb (0.91 µg L⁻¹), Cd (0.08 µg L⁻¹) and Cr (3.75 µg L⁻¹) in the summer of 2016 (Gao et al., 2019). Our study showed that the pollution of heavy metal in FRS was much better than the eutrophic pollution: heavy metals in many sampling sites have nearly reached the Class I water standard (Fig. 3). The average concentrations of Pb, Cd and Cr in FRS stayed in a relative moderate level compared with other aquatic systems globally. In the Dan River drainage, the average concentrations of Cr and Cd were 0.10 and 0.70 µg L⁻¹ (Meng et al., 2016), which were dramatically lower than we found in FRS. Heavy metal pollution in rivers of Greece increased from 1999 to 2019; however, the recent contents of Pb, Cd and Cr were still comparable to the concentrations in FRS (Karaouzas et al., 2021). Whereas, in Houjing River of Taiwan, the average concentrations of Pb, Cd and Cr were 569, 8 and 96 µg L⁻¹ (Vu et al., 2017), in which Pb and Cr were significantly higher than those in FRS. In Huaihe River, the average Pb, Cd and Cr concentrations were 155.60, 69.54 and 22.13 µg L⁻¹ (Wang et al., 2017), and Pb and Cd were significantly higher than Class V water standard and also dramatically higher than what we found in FRS. Furthermore, the similar concentration distributions of heavy metals could indicate the long-distance transportation of heavy metals from the inflow rivers to the downstream lakes (Guo et al., 2020; Meng et al., 2016). Our results displayed the mobility and influence of heavy metals in FRS to the water of Baiyangdian (Fig. 3): the concentrations of heavy metals Cr, Cd and Pb in FRS showed the similar concentration distributions but were all significantly higher than those in water of Baiyangdian (Gao et al., 2019; Meng, Zhang & Shan, 2021; Zhao et al., 2020). The inflow rivers could collect heavy metals from the whole watershed and severely contaminate themselves and downstream lakes (Guo et al., 2020; Meng et al., 2016; Lv et al., 2020). Therefore, in order to completely ameliorate the pollution of heavy metals in Baiyangdian, the sources and routes of heavy metals entering the inflow rivers should be concerned and eliminated.

We did not find any previous study that has shown the spatiotemporal pattern of water pollution in FRS, whereas, the present study displayed dramatically spatial and temporal variations of eutrophication and heavy metal pollution (Figs. 2, 3 and 5), which were consistent with other aquatic ecosystems (Chen et al., 2021b; Guo et al., 2020; Wang et al., 2021a). The captured spatiotemporal patterns would allow us to identify the pollution hotspots and seriously polluted periods in FRS. The eutrophication in FRS showed that NH₄⁺-N and TP increased significantly from the city area to the estuary area in summer and autumn, and NH₄⁺-N and TP in these two seasons were all higher than those in spring (Fig. 3), which could be mainly due to the domestic sewage (Li et al., 2017; Wang et al., 2017) and runoffs from intensive agricultural activities (Tao et al., 2020; Wang et al., 2017), whereas COD contents in spring were higher than those in summer and autumn in FRS, which may be caused by the deteriorated stagnant wastewater and sediment release due to the low flow rate of FRS in spring (Ni, Wang & Wang, 2016; Piao et al., 2010; Zhu et al., 2019). Regarding water quality assessment, WQI_E revealed pollution hotspots around the middle area of FRS in spring, and WQI_E in summer and autumn linearly increased from unpolluted levels to serious pollution along FRS, showing the pollution hotspots in these two seasons were in farmland and estuary areas (Fig. 5A). The seriously eutrophic water accumulated in the end of FRS could directly enter Baiyangdian and cause contamination, which demonstrated a great influence of inflow rivers’ eutrophic pollutants to the eutrophication in lakes. In contrast to eutrophication, different spatiotemporal variations of the heavy metals were observed in FRS. The contents of Pb were mostly higher than Cd and Cr but without clear spatial variations in FRS (Fig. 3), which indicated Pb could be mainly originated from a constantly line sources along FRS–traffic pollution (Ewen, Anagnostopoulou & Ward, 2009; Vu et al., 2017). Cd and Cr in the town area were all higher than other places in three seasons, which indicated Cd and Cr were likely due to the release from historical polluted sediments in the town area (Peng et al., 2009; Vu et al., 2017) or the industrial wastewater in the town and city areas (Chen et al., 2021a; Li, Chen & Sun, 2021a). The higher concentrations of Cd in spring additionally confirmed that Cd pollution was tremendously influenced by the accumulation effect in stagnant water originating from sediments (Meng et al., 2016; Peng et al., 2009; Wang et al., 2017). WQI_HM showed single peak curves along FRS, and increased significantly from unpolluted levels at both ends of FRS to the highest level of pollution just after the city area (around the town area), furtherly demonstrating the pollution hotspots of heavy metals were caused by the sources in the high population density regions (Fig. 5B). Meanwhile, different regions in the city area also greatly affected the water quality of FRS (Table 1): the water flowing through the middle of city was seriously polluted, whereas, the waters flowing through the edges of the city were only slightly polluted. Overall, these spatiotemporal distribution characteristics above clearly clarified the varied pollution hotspots, the seriously polluted periods and the potential sources in FRS. Water quality managements in the future should take serious considerations of these weak parts in current pollution treatments, and formulate and conduct spatiotemporally flexible treatments based on this study to furtherly improve water quality in the Baiyangdian watershed.

Trace elements exhibiting high correlations may share similar analogous behaviors during transformation and migration (Ke et al., 2017; Wang et al., 2017), which can suggest their potential sources and pathways in the water environment (Chen et al., 2021b; Guo et al., 2020; Ke et al., 2017). Pearson’s correlation showed NH₄⁺-N, TP and COD all significantly correlated with Pb (p were 0.0129, 0.0485 and 0.0044) and COD significantly correlated with Cd (p < 0.0001, Fig. 4A), indicating Pb, Cd and eutrophic pollutants were likely originated from similar sources in FRS, such as inflows from domestic sewage and traffic activities (Chen et al., 2021b; Ewen, Anagnostopoulou & Ward, 2009; Guo et al., 2021), runoff from intensive applications of fertilizers and pesticides (Wang et al., 2017; Xia et al., 2018) and release from historical polluted sediments (Ni, Wang & Wang, 2016; Peng et al., 2009; Zhu et al., 2019). PCA showed that Pb was positively associated with PC1 but negatively associated with PC2 (Table S3), which furtherly indicated Pb in FRS could be attributed to the sources of traffic pollution, agricultural practices and historical polluted sediments rather than industrial wastewater discharges (Ewen, Anagnostopoulou & Ward, 2009; Wang et al., 2017). This is consistent with the finding in the spatiotemporal analysis that Pb could be originated from a constantly line sources along FRS (Fig. 3). Cd was also positively associated with PC1, confirming Pb and Cd have similar hydro-chemical characteristics and common sources in the water of FRS (Chen et al., 2021b; Zhuang et al., 2019). In addition, Cd significantly correlated with COD, which could more accurately attribute Cd pollution to the agricultural practices and polluted sediments as COD. In contrast to Pb and Cd, Cr positively associated with PC2 but also partly associated with PC1, which thus can attribute Cr to the sources of sewage releases from industrial activities and polluted sediments (Peng et al., 2009; Vu et al., 2017). All heavy metals partly attributed to the historical polluted sediments were consistent with the results that the WQI_HM were relatively higher in the stagnant water in spring (Fig. 5B). Industrial wastewater was imported into Baiyangdian water system since the 1980s, which caused two-thirds of this region to be contaminated and a large amount of pollution has accumulated in the sediments (Zhang et al., 2018; Zhu et al., 2019). Heavy metals released from these sediments could cause a long-term threat to the water quality and aquatic biota health in this region (Ismail et al., 2016; Ke et al., 2017; Rajeshkumar & Li, 2018).

With environmental remediations and increased government financed investments, the water quality (particularly eutrophication) in Chinese inland waters was improved markedly over recent decades (Huang et al., 2019; Zhou et al., 2017; Zhuang et al., 2019). However, in order to completely mitigate the water pollution from Chinese inland waters (include Baiyangdian watershed) in next decades, the importance of controlling the inflow river pollution and understanding its spatiotemporal variations was gradually recognized (He et al., 2020; Tong et al., 2017). We should deeply understand about the pollution sources of inland waters, the main pollutants deteriorating the water quality and the spatiotemporal variations of these pollutants (Huang et al., 2018; He et al., 2020; Wang et al., 2021a). Then, more effective water pollution treatments can be taken with focalizations to reduce the pollution from industrial activities, traffic pollution and agricultural practices, as well as the remediation of polluted sediments. For instance, specific constructed wetlands could be built based on this information for the water quality restoration of the targeted area and pollutants. Therefore, the spatiotemporal changes of the water pollution showed in this study, including the pollution hotspots, serious periods and potential sources, provided important scientific basis for making effective and flexible water quality treatments in the whole watershed of Baiyangdian.

Conclusions

Our study demonstrated a considerable improvement of the eutrophication and a good condition of the heavy metals in the water of FRS after the establishment of Xiongan New Area. However, the eutrophic parameters in nearly half of the sites in FRS still did not reach the present water quality requirement of Baiyangdian, and the heavy metals were mostly associated with traffic pollution, agricultural practices and historical polluted sediments, which were not easily to be controlled and eliminated. In addition, dramatically spatiotemporal changes of pollution in FRS were found in this study, allowing these conclusions: the eutrophication was highest in summer, and the severely eutrophic pollution concentrated around the estuary area, whereas the pollution of heavy metals was relatively similar among three seasons with the prominent pollution around the town area. The serious contamination in these varied pollution hotspots and periods in FRS may have tremendous influences on the water quality of the downstream Baiyangdian. All these findings revealed the weak parts in current pollution treatments, and provided scientific basis for conducting more precise water quality managements to fully eradicate the water pollutants in future.

Supplemental Information