Home Journals Articles Updates About
CN
image
收藏切换
Reducing eutrophication risk of a reservoir by water replacement: a case study of the Qingcaosha reservoir in the Changjiang Estuary
收藏切换
PDF
Yizhong CHEN1, 2, Jianrong ZHU1, *
Acta Oceanologica Sinica | 2018, 37(6) : 23 - 29
Less
收藏切换
Acta Oceanologica Sinica | 2018, 37(6): 23-29
• Marine Chemistry •
Reducing eutrophication risk of a reservoir by water replacement: a case study of the Qingcaosha reservoir in the Changjiang Estuary
Full
Yizhong CHEN1, 2, Jianrong ZHU1, *
Affiliations
  • 1 State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China
  • 2 Shanghai Academy of Environmental Sciences, Shanghai 200233, China
Published: 2018-06-25 doi: 10.1007/s13131-018-1183-7
Outline
收藏切换

Eutrophication of freshwater systems in cities is a major concern worldwide. Physical, biological and chemical methods have been used in eutrophic lakes and reservoirs to reduce their eutrophic state and algal biomass, but these approaches are not effective without a substantial reduction in nutrients input, which could take decades to achieve in the developing countries. This study aims to assess the risk of eutrophication and algal bloom in a coastal reservoir with high nutrient inputs to confirm the feasibility of inhibiting the reservoir's eutrophic state by hydrodynamic operations. A variety of water quality indexes (e.g., water temperature, secchi depth, dissolved oxygen, total nitrogen, total phosphorus, phytoplankton chlorophyll a) at five observed sites were investigated in the Qingcaosha reservoir, which located in the Changjiang Estuary, during the construction, trial and normal operation periods from 2009 to 2012. No water exchange happened during the construction from April 2009 to October 2010, and the water exchange increased during the trial from October 2010 to January 2011, and during normal operation period from January 2011. The comprehensive nutrition state index (TLI) calculated by several representative water quality indexes was adopted to evaluate the variation of the trophic state in the reservoir. The peak values of TLI reached 51 in the summer of 2009, and 55 in the summer of 2011, higher than the eutrophication threshold value 50. The lowest TLI, about 32, appeared in the summer of 2010. The values of TLI in other observation periods could keep under 50. The results showed that the reservoir could easily deteriorate into the eutrophic state because of excess nutrients and algal blooms in the summer of 2009 and 2011, while the eutrophication and algal blooms could be reduced by the lack of nutrients in 2010 or adequate water replacement in 2012. The temporal and spatial variations of water quality indexes were presented based on observation data and analysis. The adequate water replacement in the reservoir driven by tides was tested to be an efficient and economical method for controlling eutrophication and algae blooms in the water environment with high nutrient inputs.

estuarine reservoir  /  eutrophic state  /  algal bloom  /  operation way
Yizhong CHEN, Jianrong ZHU. Reducing eutrophication risk of a reservoir by water replacement: a case study of the Qingcaosha reservoir in the Changjiang Estuary[J]. Acta Oceanologica Sinica, 2018 , 37 (6) : 23 -29 . DOI: 10.1007/s13131-018-1183-7
Full Text
Less
1 Introduction
Less
Aquatic systems impacted by human activities continue to deteriorate with the economic development. Because of the high input of nutrients, many freshwater systems have become eutrophic, and the resulting algae blooms have triggered drinking water crises throughout the world (Carmichael, 2001; Huisman et al., 2005; Paerl et al., 2001). Lake Erie (US/Canada), Lake Winnipeg (Canada), Lake Victoria (the largest of the African rift lakes), and Lakes Biwa and Kasimagaura (Japan's largest lakes) have suffered from eutrophication (Paerl et al., 2011). Many lakes and reservoirs in China, especially those near urban areas, have deteriorated to a eutrophic state due to excessive inflows of nitrogen, phosphorus, organic matter and other pollutants (Chen et al., 2009). The Chinese government and many researchers have adopted measures to recover and manage these eutrophic lakes. Restoration projects have been implemented at the Lake Taihu (Pu et al., 1993), Lake Dianchi (Li et al., 2005), Lake Wuli (Chen et al., 2006), Lake Mochou (Pu et al., 2001), and other small lakes and reservoirs (Tu et al., 2004) throughout China.
As the financial center of China, Shanghai is home to more than twenty million residents. Poor water quality has troubled this city for many years. In 2007, a coastal reservoir project was initiated in the Changjiang Estuary to build the largest drinking water source in Shanghai. This estuarine reservoir, named the Qingcaosha Reservoir, was designed to supply 7 190 000 m3 of freshwater per day (more than 50% of the total freshwater supply in Shanghai) and serve more than 13 million people in Shanghai. It was finished in 2010 and started normal operation in 2011. It is located on the northern end of Changxing Island (Fig. 1). The distribution of freshwater and saltwater fluctuates due to tidal activity in this area (Chang et al., 2014; Qiu and Zhu, 2013; Wu et al., 2006). Utilizing the difference of water level between inside and outside of the reservoir, the water gates at the northwest (upper reach) and southeast (lower reach) of the Qingcaosha Reservoir are manually controlled to draw and discharge freshwater and to avoid saltwater when replacing water in the reservoir. The total area of the reservoir is 66.15 km2. The water depth in the reservoir varies from 2.7 m to 12.1 m, generally increasing from the northwest (upper reach) to the southeast (lower reach). A large central wetland was set in the northwest central position of the reservoir. This reservoir was enclosed and had no water exchange with the Changjiang Estuary while under construction from April 2009 to September 2010. The project was completed and began to draw water in October 2010. The water supply of the reservoir was approximately 800 000 t/d and the water gates opened only once per day to draw water from the Changjiang Estuary during the trial period from October 2010 to December 2010. After the trial period, the water supply gradually increased to 2.5×106 t/d at the end of 2011 and 4×106 t/d at the end of 2012. The water gate operation was changed to run twice per day to intake water in the reservoir by means of the semi-diurnal tides.
The substantial water discharge of the Changjiang River exports abundant nutrients into the estuary. The annual nutrients flowing to the sea by the Changjiang River is markedly higher than in other estuaries in China (Shen et al., 1992). Its annual flows of total inorganic nitrogen, phosphate, silicate and nitrate are 8.88×106 t, 1.36×104 t, 2.04×106 t and 6.36×106 t, respectively (Gao and Song, 2005). Sharp reduction of such high nutrient inputs for the Qingcaosha Reservoir is difficult and expensive. The researchers and managers of the Qingcaosha Reservoir want to find some efficient and economical methods to keep the trophic state of the drinking water source at a safe level. This study aims to assess the risk of eutrophication and algal blooms in the estuarine reservoir with high nutrient inputs to confirm the feasibility of inhibiting the reservoir's eutrophic state by appropriate reservoir hydraulic operations.
2 Methods
Less
Five observation sites were designed in the Qingcaosha Reservoir (Fig. 1). Site #1 was located in the northwest of the reservoir; Sites #2 and #3 were located at the southern and northern ends of the central wetland, respectively; Site #4 was located near the center of the reservoir; and Site #5 was located at the southeast end of the reservoir. The depths of Sites #1–#5 are 2.7 m, 4.6 m, 8.6 m, 9.7 m, and 10.8 m, respectively. The investigation began in September 2009 at Site #1 and began in April 2009 at the other sites. The monitoring work was completed in December 2012. The water was sampled at a depth of 0.5 m below the surface and 0.5 m above the bottom at each site. Water temperature, Secchi depth (SD) and dissolved oxygen (DO) were measured at all sites. Chemical oxygen demand (CODMn), ammonia nitrogen (NH3-N), nitrate nitrogen (NO3-N), nitrite nitrogen (NO2-N), total nitrogen (TN), total phosphorus (TP), dissolved total phosphorus (DTP), and phytoplankton chlorophyll a (Chl a) were sampled at all sites and analyzed in the laboratory. The sampling, measurement and analysis methods all followed the standard procedures recommended by the Ministry of Environmental Protection of the People's Republic of China (Wei, 2002) (Table 1).
The comprehensive nutrition state index (TLI) was adopted to evaluate the trophic state of the Qingcaosha Reservoir. Five water quality indexes (Chl a, TP, TN, SD and CODMn) were selected to calculate the TLI (Jin and Tu, 1990). The trophic states of lakes and reservoirs are classified into different levels according the TLI values (Table 2), which can range from 0 to 100.
The equation to calculate the TLI is as follows:
$TLI =\sum\limits_{j = 1}^m {{W_j}} \times TL{I_j} , $
where m is the number of water quality indexes, j is the number of each water quality index, Wj is the weight of each water quality index, and TLIj is the calculated TLI of each water quality index. Based on the Chl a value, the value of Wj is calculated as follows:
${W_j} = r_{ij}^2/\sum\limits_{j = 1}^m {r_{ij}^2} $,
where rij indicates the correlation coefficient of the water quality index j, calculated according to the reference parameter Chl a. rij is determined according to the calculated results from the 26 major lakes in China (Jin, 1995) (Table 3).
The TLI of each water quality index is calculated as follows:
$TLI\left( {{\rm {Chl}} \,\, a} \right) = 10 \times \left( {2.5 + 1.086 \times {{\ln } \,{{\rm {Chl}}\,\, a}}} \right), $
$TLI\left( {\rm {TP}} \right) = 10 \times \left( {9.436 + 1.624 \times {{\ln } \,{\rm {TP}}}} \right), $
$TLI\left( {\rm {TN}} \right) = 10 \times \left( {5.453 + 1.694 \times {{\ln }\,\, {\rm {TN}}}} \right), $
$TLI\left( {\rm {SD}} \right) = 10 \times \left( {5.118 + 1.94 \times {{\ln }\, {\rm {SD}}}} \right), $
$TLI\left( {\rm {COD_{Mn}}} \right) = 10 \times \left( {0.109 + 2.66 \times {{\ln }\,\, {\rm {COD_{Mn}}}}} \right).$
3 Results and discussion
Less
The observation data were analyzed to show the temporal and spatial variations of water quality indexes in the Qingcaosha Reservoir. The calculated result of TLI was used to evaluate the trophic state of this reservoir during the construction, trial and normal operation period.
3.1 Water quality index analysis in the Qingcaosha Reservoir
There was little spatial variation of water temperature in the reservoir during the observation period. No thermocline was observed in this reservoir. The water temperature in the entire reservoir fluctuated seasonally, ranging from 2.5°C in winter to 32.5°C in summer.
When the reservoir was enclosed, the vertical DO concentrations varied greatly at the measured sites due to the deficiency of water exchange and the influence of phytoplankton photosynthesis at the surface layer. The maximum difference of DO between the surface layer and bottom layer was 6 g/m3. This phenomenon disappeared after the reservoir began operations. DO also fluctuated seasonally, ranging from 6 g/m3 in summer to 14 g/m3 in winter.
The SD in the reservoir was mainly influenced by the growth of phytoplankton and wave induced by wind. The SD generally decreased in summer and increased in winter and spring. The peak value of SD at Site #5 was 1.8 m in the spring of 2010, 1.6 m in the spring of 2011 and 1.7 m in the winter of 2011. The valley value at Site #1 was 0.5 m in the summer of 2009 and 0.17 m in the summer of 2010. With the increasing water exchange in the reservoir, the SD at Site #1 gradually stabilized at 0.25 m. However, obvious fluctuations of SD continued at the other observation sites (Fig. 2). The horizontal variation of SD was primarily increasing from the northwest (the upper reach) to the southeast (the lower reach). This phenomenon could be explained by the settlement process of the suspended solids (SS). The SS was drawn from the northwest gate and kept settling with the water movement to the southeast end of the reservoir.
Based on the annual averaged data at the observation sites, the dissolved inorganic nitrogen (DIN), considered as the sum of NH3-N, NO3-N and NO2-N, accounted for 63.1%–67.8% of the TN. The proportion of particulate nitrogen (PN) in the TN was low. Thus, the TN was not mainly influenced by the wave and SS, and varied little in the vertical during the observation period (Fig. 3). The spatial difference of TN was small during the reservoir's closed period, except that the TN at Site #1 was slightly higher than at the other sites in the summer of 2009 and the spring of 2010, because of the growth of phytoplankton. The concentration of TN in the entire reservoir decreased from 1.8 g/m3 to 0.5 g/m3 during the closed period due to the lack of nutrients input and water self-purification (Fig. 2). The concentration of TN at Site #1 clearly increased after October 2010 because of the high nutrient inputs from the Changjiang Estuary. It exceeded 2.6 g/m3 in July 2011 and fluctuated in the range of 1.2–2.2 g/m3 in the remaining observation period. During the operation period, the concentration of TN at Site #1 was substantially higher than the other sites, and the others did not obviously differ from each other (Fig. 2). This showed that the TN decreased mainly in the northwest area, because of the nutrients absorption function of the central wetland. Wetlands are well known as the highly effective systems mitigating the negative effects of nitrogen and phosphorus excess. Natural and artificial wetlands are widely applied in the worldwide (Alongi, 2008; Álvarez-Rogel et al., 2016; Kang et al., 2017).
The major component of TP in the reservoir was particulate phosphorus (PP). The annual averaged ratios of DTP/TP were only 26.2%–30.6% at the measured sites. Therefore, an intense fluctuation was found in the analyzed results of TP. The range of TP was 0.005–0.11 g/m3 during the reservoir's closed period, and this range changed to 0.01–0.17 g/m3 after the reservoir began to operate (Fig. 2). Due to the settlement of SS, the TP in the surface layer was lower than in the bottom layer from 2009 to 2011. After 2012, the surface concentration of TP was occasionally higher than the bottom concentration (Fig. 3) because of the gradually intensified vertical turbulence during the operation period. The horizontal variation of TP was mainly decreasing from northwest to southeast. Along with the increase of nutrients input, the horizontal gradient of TP gradually increased after the reservoir began to operate in October 2010. This phenomenon was observed in the entire reservoir (Fig. 2), primarily due to the nutrients absorption function of the central wetland and the settlement of PP in the entire reservoir.
The surface concentration of Chl a was much higher than the bottom concentration in the summers of 2009 and 2011, because of the rapid growth of phytoplankton. However, the bottom concentration of Chl a was occasionally higher than the surface concentration in 2012 due to the gradually intensified vertical turbulence (Fig. 3). For the stagnant water environment and sufficient nutrients, the phytoplankton grew quickly throughout the reservoir in 2009. An algal bloom occurred and the peak concentration of Chl a at Site #1 reached 50 mg/m3 in the summer of 2009 (Fig. 2). The concentrations of TN and TP decreased to 0.5 g/m3 and 0.01 g/m3 in the summer of 2010 because of no nutrient inputs (the reservoir was enclosed) and water self-purification. The Qingcaosha Reservoir had not reached a eutrophic state (Nürnberg, 1996), and the low nutrients could not support the growth of phytoplankton. Therefore, the concentration of Chl a was reduced to 2 mg/m3 and no algal bloom happened in the summer of 2010. After October 2010, the reservoir began to operate, and the fresh water with high nutrients in the Changjiang Estuary was drawn into the reservoir. The growth of phytoplankton rose again and the peak concentration of Chl a at Site #1 reached 25 mg/m3 in the summer of 2011. However, the growth of phytoplankton had been weakened with the gradual increase of water replacement in the reservoir since 2012. The Chl a in the entire reservoir was limited to less than 10 mg/m3 in the summer of 2012, even with high concentrations of nutrients. The variations of Chl a in 2012 show that the adequate water replacement is an effective method for controlling algae blooms in a eutrophic water environment. The similar conclusion was reached in the study of Dianshan Lake in Shanghai, the accumulation and growth of phytoplankton in lakes and reservoirs with high nutrients could be effectively inhibited by the increasing discharges (Chen et al., 2016). The main reason of this phenomenon is that the algae can be quickly transported out of lakes and reservoirs by adding inflow and outflow discharges before they have the opportunity to bloom.
3.2 Trophic state assessment of the water environment in the Qingcaosha Reservoir
Using the spatially averaged data, the TLI was calculated to reflect the variation of the water trophic state in the Qingcaosha Reservoir (Fig. 4). The trophic state of the reservoir deteriorated from mesotrophic state to mild eutrophic state because of the rapid growth of phytoplankton, sufficient nutrients and the obvious decline of SD from July 2009 to October 2009. The trophic state quickly recovered to mesotrophic state due to the low concentrations of nutrients and the slow growth of phytoplankton from November 2009 to September 2010. The reservoir began to operate in October 2010, and the growth of phytoplankton was then reactivated along with the high nutrient inputs from the Changjiang Estuary. Thus, the trophic state of the Qingcaosha Reservoir gradually deteriorated to a mild eutrophic state again in July 2011. With regard to the increase of TN and TP, the peak value of TLI in the summer of 2011 was higher than in the summer of 2009. In 2012, the concentrations of nutrients in the reservoir remained high due to the increasing inflow from the Changjiang Estuary, but the growth of phytoplankton was restricted because of the more frequent water replacement (Fig. 2). Thus, the trophic state of the Qingcaosha Reservoir remained mesotrophic in 2012 (Fig. 4).
According the analysis above, the nutrients in the Qingcaosha Reservoir, which is the cause of the eutrophication and algal blooms, are difficult to reduce because the nutrients input from the Changjiang Estuary is high. Reducing the input of nutrients is still the ultimate method to address eutrophication in lakes and reservoirs (Edmondson, 1970; Schindler, 2006), but this could take decades to achieve in the developing countries (Paerl et al., 2011; Qin et al., 2015). The toxins and odorous compounds generated by algae blooms are much more dangerous than normal nutrients in a drinking water system (Burgos et al., 2014; Ma et al., 2013; Song et al., 2007; Ueno et al., 1996), and the technological requirements and costs required to remove the former are much higher than the latter. Biological methods such as filter-feeding fish, shellfish and aquatic plants, and physical methods including mechanical measures and artificial isolation equipment have been used in eutrophic lakes to reduce algal biomass, but these approaches are not effective without a substantial reduction in nutrients input (Chen et al., 2009; Pu et al., 1993). The positive effects of artificial water diversion and exchange have been proven to decrease the concentrations of phytoplankton in non-tidal areas, but it is difficult to exchange water sufficiently over an entire area and the cost is prohibitive (Hu et al., 2008; Li et al., 2013).
The results of this study show that the adequate water replacement driven by tides is an appropriate operation way to inhibit the eutrophic state of estuarine reservoirs with high nutrient inputs. Reservoirs set in estuarine area have a natural advantage in restricting the growth of phytoplankton in the high nutrients environment by utilizing the tidal range, and these reservoirs can exchange water frequently with the control of water gates. It is an efficient and economical way to low down the risk of eutrophication and algal blooms in the drinking water sources, while it takes decades to reduce the input of nutrients loads from the upper reaches to a safe level.
4 Conclusions
Less
The variations of the nutrients and Chl a in the Qingcaosha Reservoir were analyzed based on the observed data at five sites from 2009 to 2012. In the summer of 2009, the unfinished reservoir was not connected to the estuary, and the phytoplankton quickly grew because of enough nutrients and the stagnant water condition. In the summer of 2010, the nutrients in the reservoir clearly decreased and no algae bloom occurred due to the lack of nutrients input and water self-purification. The concentrations of nutrients in the reservoir quickly increased and the growth of phytoplankton was reactivated after the reservoir began to operate in October 2010. The peak concentration of Chl a reached 25 mg/m3 in the summer of 2011, but it was limited to below 10 mg/m3 in 2012 due to the adequate water replacement in the reservoir. The analysis and discussion results suggest that the adequate water replacement driven by tides could be an efficient and economical method for controlling eutrophication and algae blooms in the water environment with high nutrient inputs. The effective inhibition on eutrophication and algae blooms could also decrease the risk of the toxins and odorous compounds generated by algae blooms in the drinking water supplies.
Acknowledgements
Less
The authors thank all the people who provided the observed data used in the paper.
Funding
Less
  • The National Key R & D Program of China under contract No. 2017YFC0405400; the Shanghai Municipal Science and Technology Commission, China under contract Nos 12231201603 and 15YF1409900.
References
Less
Alongi D M. 2008. Mangrove forests: resilience, protection from tsunamis, and responses to global climate change. Estuarine, Coastal and Shelf Science, 76(1): 1–13
Álvarez-Rogel J, del Carmen Tercero M, Isabel Arce M, et al. 2016. Nitrate removal and potential soil N2O emissions in eutrophic salt marshes with and without Phragmites australis. Geoderma, 282: 49–58
Burgos L, Lehmann M, de Andrade H H R, et al. 2014. In vivo and in vitro genotoxicity assessment of 2-methylisoborneol, causal agent of earthy-musty taste and odor in water. Ecotoxicology and Environmental Safety, 100: 282–286
Carmichael W W. 2001. Health effects of toxin-producing cyanobacteria: "the cyanoHABs". Human and Ecological Risk Assessment: An International Journal, 7(5): 1393–1407
Chang P H, Isobe A, Kang K R, et al. 2014. Summer behavior of the Changjiang diluted water to the East/Japan Sea: a modeling study in 2003. Continental Shelf Research, 81(1): 7–18
Chen Kaining, Bao Xianming, Shi Longxin, et al. 2006. Ecological restoration engineering in Lake Wuli, Lake Taihu: a large enclosure experiment. Journal of Lake Sciences, 18(2): 139–149
Chen Feizhou, Song Xiaolan, Hu Yaohui, et al. 2009. Water quality improvement and phytoplankton response in the drinking water source in Meiliang Bay of Lake Taihu, China. Ecological Engineering, 35(11): 1637–1645
Chen Yizhong, Lin Weiqing, Zhu Jianrong, et al. 2016. Numerical simulation of an algal bloom in Dianshan Lake. Chinese Journal of Oceanology and Limnology, 34(1): 231–244
Edmondson W T. 1970. Phosphorus, nitrogen, and algae in Lake Washington after diversion of sewage. Science, 169(3946): 690–691
Gao Xuelu, Song Jinming. 2005. Phytoplankton distributions and their relationship with the environment in the Changjiang Estuary, China. Marine Pollution Bulletin, 50(3): 327–335
Hu Weiping, Zhai Shujing, Zhu Zecong, et al. 2008. Impacts of the Yangtze River water transfer on the restoration of Lake Taihu. Ecological Engineering, 34(1): 30–49
Huisman J, Matthijs H C P, Visser P M. 2005. Harmful Cyanobacteria. Dordrecht, the Netherlands: Springer-Verlag
Jin Xiangcan. 1995. Chinese Lake Environment (in Chinese). Beijing: China Ocean Press
Jin Xiangcan, Tu Qingying. 1990. The Standard Methods in Lakes Eutrophication Investigation (in Chinese). 2nd ed. Beijing: China Environmental Science Press
Kang Yan, Zhang Jian, Xie Huijun, et al. 2017. Enhanced nutrient removal and mechanisms study in benthic fauna added surface-flow constructed wetlands: the role of Tubifex tubifex. Bioresource Technology, 224: 157–165
Li Wenchao, Pan Jizheng, Chen Kaining, et al. 2005. Studies and demonstration engineering on ecological restoration technique in the Littoral Zone of Lake Dianchi: the target and feasibility. Journal of Lake Sciences, 17(4): 317–321
Li Yiping, Tang Chunyan, Wang Chao, et al. 2013. Improved Yangtze River Diversions: are they helping to solve algal bloom problems in Lake Taihu, China?. Ecological Engineering, 51: 104–116
Ma Zhimei, Xie Ping, Chen Jun, et al. 2013. Microcystis blooms influencing volatile organic compounds concentrations in Lake Taihu. Fresenius Environmental Bulletin, 22(1): 95–102
Nürnberg G K. 1996. Trophic state of clear and colored, soft-and hardwater lakes with special consideration of nutrients, anoxia, phytoplankton and fish. Lake and Reservoir Management, 12(4): 432–447
Paerl H W, Fulton R S, Moisander P H, et al. 2001. Harmful freshwater algal blooms, with an emphasis on cyanobacteria. The Scientific World Journal, 1: 76–113
Paerl H W, Xu Hai, Mccarthy M J, et al. 2011. Controlling harmful cyanobacterial blooms in a hyper-eutrophic lake (Lake Taihu, China): The need for a dual nutrient (N & P) management strategy. Water Research, 45(5): 1973–1983
Pu Peimin, Wang Guoxiang, Li Zhengkui, et al. 2001. Degradation of healthy aqua-ecosystem and its remediation: theory, technology and application. Journal of Lake Sciences, 13(3): 193–203
Pu Peimin, Yan Jingsong, Dou Hongshen, et al. 1993. An experimental study on the physio-ecological engineering for improving Taihu Lake water quality in water source area of Mashan drinking water plant. Journal of Lake Sciences, 5(2): 171–180
Qin Boqiang, Li Wei, Zhu Guangwei, et al. 2015. Cyanobacterial bloom management through integrated monitoring and forecasting in large shallow eutrophic Lake Taihu (China). Journal of Hazardous Materials, 287: 356–363
Qiu Cheng, Zhu Jianrong. 2013. Influence of seasonal runoff regulation by the Three Gorges Reservoir on saltwater intrusion in the Changjiang River Estuary. Continental Shelf Research, 71: 16–26
Schindler D W. 2006. Recent advances in the understanding and management of eutrophication. Limnology and Oceanography, 51(1): 356–363
Shen Zhiliang, Lu Jiaping, Liu Xingjun, et al. 1992. Distribution characteristics of the nutrients in the Changjiang River estuary and the effect of the Three Gorges Project on it. Studia Marina Sinica, 33: 109–129
Song Lirong, Chen Wei, Peng Liang, et al. 2007. Distribution and bioaccumulation of microcystins in water columns: a systematic investigation into the environmental fate and the risks associated with microcystins in Meiliang Bay, Lake Taihu. Water Research, 41(13): 2853–2864
Tu Qingying, Zhang Yongtai, Yang Xianzhi. 2004. Approaches to the ecological recovery engineering in Lake Shishahai, Beijing. Journal of Lake Sciences, 16(1): 61–67
Ueno Y, Nagata S, Tsutsumi T, et al. 1996. Detection of microcystins, a blue-green algal hepatotoxin, in drinking water sampled in Haimen and Fusui, endemic areas of primary liver cancer in China, by highly sensitive immunoassay. Carcinogenesis, 17(6): 1317–1321
Wei Fusheng. 2002. Water and Wastewater Monitoring and Analysis Method (in Chinese). 4th ed. Beijing: China Environmental Science Press
Wu Hui, Zhu Jianrong, Chen Bingrui, et al. 2006. Quantitative relationship of runoff and tide to saltwater spilling over from the North Branch in the Changjiang Estuary: A numerical study. Estuarine, Coastal and Shelf Science, 69(1–2): 125–132
Appendix
Less
Year 2018 volume 37 Issue 6
PDF
35
19
Cite this Article
BibTeX
Article Info
doi: 10.1007/s13131-018-1183-7
  • Receive Date：2017-07-14
  • Online Date：2026-04-14
  • Published：2018-06-25
Article Data
Affiliations
History
  • Received：2017-07-14
  • Accepted：2017-08-13
Funding
The National Key R & D Program of China under contract No. 2017YFC0405400; the Shanghai Municipal Science and Technology Commission, China under contract Nos 12231201603 and 15YF1409900.
Affiliations
    1 State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China
    2 Shanghai Academy of Environmental Sciences, Shanghai 200233, China

Corresponding:

References
Share
https://castjournals.cast.org.cn/joweb/aos/EN/10.1007/s13131-018-1183-7
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House