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Li W, Chen X, Xu S, Wang T, Han D, Xiao Y. Effects of storm runoff on the spatial-temporal variation and stratified water quality in Biliuhe Reservoir, a drinking water reservoir. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:19556-19574. [PMID: 38358632 DOI: 10.1007/s11356-024-32431-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 02/07/2024] [Indexed: 02/16/2024]
Abstract
Stormflow runoff is an important non-point source of pollution in drinking water reservoirs. Storm runoff is usually very turbid and contains a high concentration of organic matter, therefore affecting water quality when it enters reservoirs. In order to investigate the impact of storm runoff on spatial-temporal variation and stratification of water quality during this rainstorm event, the inflow process of the storm runoff was studied through a combination of field investigation and simulation using the Delft3D-Flow model. Water samples were collected from Biliuhe Reservoir at four different periods: before storm runoff, storm runoff flood peak period, 1 week after storm runoff, and 5 weeks after storm runoff. The results showed that the input of storm runoff resulted in a significant increase in the nitrogen (N) and phosphorus (P) in the reservoir water, especially in the reservoir entrance. The concentrations of total nitrogen (TN) and total phosphorus (TP) gradually decreased after the flood peak period; however, the average concentrations of TN and TP in the entire reservoir remained higher than those before the storm runoff levels for an extended duration. The storm runoff will greatly contribute to the contamination of water quality in a reservoir, and the water quality cannot be quickly restored by self-purification in the short term. During the flood peak period, under the influence of density current, the electrical conductivity (EC) and turbidity increased significantly in the water depth of 10-15 m, so that the reservoir water had obvious stratification between 10 and 15 m. The form of pollutants in storm runoff was mostly in particle phosphorus. Total particulate phosphorus (TPP) concentration was 0.015 ± 0.011 mg/L, accounting for 44.12% of total phosphorus (TP) concentration in storm runoff flood peak period. The process of a rainstorm caused runoff, which carried high levels of turbidity, particulate phosphorus, and organic matter. The storm runoff disrupts the stratification of the reservoir water. In terms of vertical distribution, the turbidity in the reservoir area increased to 73.75 NTU. Therefore, the occurrence of significant turbidity density flow in the reservoir is frequently accompanied by intense rainfall events. Gaining insights into the impact of storm runoff on the vertical distribution of reservoir turbidity can help managers in selecting an appropriate inlet height to mitigate high turbidity outflow.
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Affiliation(s)
- Weijia Li
- School of Hydraulic Engineering, Dalian University of Technology, Dalian, 116024, China
| | - Xiaoqiang Chen
- School of Hydraulic Engineering, Dalian University of Technology, Dalian, 116024, China.
| | - Shiguo Xu
- School of Hydraulic Engineering, Dalian University of Technology, Dalian, 116024, China
| | - Tianxiang Wang
- School of Ocean Science and Technology, Dalian University of Technology, Panjin, 124221, China
| | - Dongning Han
- School of Hydraulic Engineering, Dalian University of Technology, Dalian, 116024, China
| | - Yao Xiao
- School of Hydraulic Engineering, Dalian University of Technology, Dalian, 116024, China
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2
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Chen S, Liu H, Zhang H, Li K, Wang N, Sun W, Liu X, Niu L, Ma B, Yang F, Li H, Zhao D, Xing Y. Temporal patterns of algae in different urban lakes and their correlations with environmental variables in Xi'an, China. J Environ Sci (China) 2023; 133:138-151. [PMID: 37451783 DOI: 10.1016/j.jes.2022.07.036] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 07/20/2022] [Accepted: 07/22/2022] [Indexed: 07/18/2023]
Abstract
Urban lakes were critical in aquatic ecology environments, but how environmental factors affected the distribution and change characteristics of algal communities in urban lakes of Xi'an city was not clearly. Here, we investigated the algal community structure of six urban lakes in Xi'an and evaluated the effects of water quality parameters on algae. The results indicated that the significant differences on physicochemical parameters existed in different urban lakes. The maximum concentration of total phosphorus in urban lakes was (0.18 ± 0.01) mg/L and there was a phenomenon of phosphorus limitation. In addition, 51 genera of algae were identified and Chlorella sp. was the dominant algal species, which was affiliated with Chlorophyta. Network analysis elucidated that each lake had a unique algal community network and the positive correlation was dominant in the interaction between algae species, illustrating that mature microbial communities existed or occupied similar niches. Redundancy analysis illustrated that environmental factors explained 47.35% variance of algal species-water quality correlation collectively, indicating that water quality conditions had a significant influence on the temporal variations of algae. Structural equation model further verified that algal community structure was directly or indirectly regulated by different water quality conditions. Our study shows that temporal patterns of algal communities can reveal the dynamics and interactions of different urban ecosystem types, providing a theoretical basis for assessing eutrophication levels and for water quality management.
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Affiliation(s)
- Shengnan Chen
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China.
| | - Hanyan Liu
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Haihan Zhang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Kai Li
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Na Wang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Weimin Sun
- National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China, Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Institute of Eco-environmental and Soil Sciences, Guangdong Academy of Sciences, Guangzhou 510650, China; Guangdong-Hong Kong-Macao Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Xiang Liu
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Limin Niu
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Ben Ma
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Fan Yang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Haiyun Li
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Daijuan Zhao
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Yan Xing
- Shaanxi Environmental Monitoring Center, Xi'an 710054, China
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Zhang H, Zhao D, Ma M, Huang T, Li H, Ni T, Liu X, Ma B, Zhang Y, Li X, Lei X, Jin Y. Actinobacteria produce taste and odor in drinking water reservoir: Community composition dynamics, co-occurrence and inactivation models. JOURNAL OF HAZARDOUS MATERIALS 2023; 453:131429. [PMID: 37099929 DOI: 10.1016/j.jhazmat.2023.131429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 03/19/2023] [Accepted: 04/14/2023] [Indexed: 05/03/2023]
Abstract
Taste and odor (T&O) has become a significant concern for drinking water safety. Actinobacteria are believed to produce T&O during the non-algal bloom period; however, this has not been widely investigated. In this study, the seasonal dynamics of the actinobacterial community structure and inactivation of odor-producing actinobacteria were explored. The results indicated that the diversity and community composition of actinobacteria exhibited significant spatiotemporal distribution. Network analysis and structural equation modeling showed that the actinobacterial community occupied a similar environmental niche, and the major environmental attributes exhibited spatiotemporal dynamics, which affected the actinobacterial community. Furthermore, the two genera of odorous actinobacteria were inactivated in drinking water sources using chlorine. Amycolatopsis spp. have a stronger chlorine resistance ability than Streptomyces spp., indicating that chlorine inactivates actinobacteria by first destroying cell membranes and causing the release of intracellular compounds. Finally, we integrated the observed variability in the inactivation rate of actinobacteria into an expanded Chick-Watson model to estimate its effect on inactivation. These findings will deepen our understanding of the seasonal dynamics of actinobacterial community structure in drinking water reservoirs and provide a foundation for reservoir water quality management strategies.
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Affiliation(s)
- Haihan Zhang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China.
| | - Daijuan Zhao
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Manli Ma
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Tinglin Huang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Haiyun Li
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Tongchao Ni
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Xiang Liu
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Ben Ma
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Yinbin Zhang
- Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, China
| | - Xuan Li
- College of Environmental Science & Engineering, Yancheng Institute of Technology, Yancheng 224051, China
| | - Xiaohui Lei
- Department of Rehabilitation, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, China
| | - Yaofeng Jin
- Department of Pathology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, China
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4
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Zhang H, Yang Y, Liu X, Huang T, Ma B, Li N, Yang W, Li H, Zhao K. Novel insights in seasonal dynamics and co-existence patterns of phytoplankton and micro-eukaryotes in drinking water reservoir, Northwest China: DNA data and ecological model. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159160. [PMID: 36195142 DOI: 10.1016/j.scitotenv.2022.159160] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 08/31/2022] [Accepted: 09/28/2022] [Indexed: 06/16/2023]
Abstract
Although associations between phytoplankton and micro-eukaryotes have been studied in aquatic ecosystems, there are still knowledge gaps in comprehending their dynamics and interactions in drinking water reservoirs. Here, the seasonal dynamics of phytoplankton and micro-eukaryotic diversities and their co-existence patterns were studied in a drinking water reservoir, Northwest China. The highest phytoplankton diversity was observed in summer, and Chlorella sp. that belongs to Chlorophyta was the most abundant genus. The highest eukaryotic diversity was also detected in summer, and Rimostrombidium sp. that belongs to Ciliophora was the most dominant genus. Mantel test showed that the phytoplankton diversity was significantly correlated with ammonia nitrogen (r = 0.561, p = 0.001) and dissolved organic carbon (r = 0.267, p = 0.017), while the eukaryotic diversity was significantly associated with ammonia nitrogen (r = 0.265, p = 0.034) and temperature (r = 0.208, p = 0.046). PLS-PM (Partial Least Squares Path Modeling) further revealed that nutrients (P < 0.01) significantly affected the phytoplankton diversity, while nutrients (P < 0.01) and temperature (P < 0.01) significantly influenced the eukaryotic diversity. Co-occurrence network displayed the primarily positive interactions (77.66% positive and 22.34% negative) between phytoplankton and micro-eukaryotes. These findings could deepen our understanding of interactions between phytoplankton and micro-eukaryotes and their driving factors under changing aquatic environments of drinking water reservoirs.
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Affiliation(s)
- Haihan Zhang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China.
| | - Yansong Yang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Xiang Liu
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Tinglin Huang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Ben Ma
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Nan Li
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Wanqiu Yang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Haiyun Li
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Kexin Zhao
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
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Si F, Huang T, Li N, Li K, Wen G, Li Y, Zhang H. Effects of flood discharge on the water quality of a drinking water reservoir in China - Characteristics and management strategies. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 314:115072. [PMID: 35452880 DOI: 10.1016/j.jenvman.2022.115072] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 04/04/2022] [Accepted: 04/10/2022] [Indexed: 06/14/2023]
Abstract
Stormflow runoff is an important non-point source of pollution in drinking water reservoirs. Rationally managed flood discharge processes at estuaries can reduce the high concentration of pollutants carried by runoff, and thus their impacts on water plant operations. In this study, the physical and chemical water quality parameters upstream from a dam were measured for a flood discharge process in the Jinpen Reservoir of Northwest China. The results showed that the time needed for the flood to reach the reservoir was ∼9 h after flooding began, and this lag effect meant that water in the metalimnion and hypolimnion were vented in advance. Consequently, the undercurrent intruded into the hypolimnion. The water temperature increased by 1.83 °C, and the Schmidt stability index decreased from 3291.37 J m-2 to 2496.32 J m-2. Flood discharge can effectively reduce the volume of pollutants; however, it cannot completely prevent the deterioration of water quality in the main reservoir. The turbidity of the reservoir still exceeded 300 NTU after the flood discharge. When the outflow discharge decreased, the critical height of aspiration also decreased, and dissolved pollutants could neither be vented nor precipitated quickly, not allowing their concentration within the reservoir to decrease further. A three-dimensional hydrodynamic model was successfully used to simulate flood processes and determine an optimal flood discharge plan. We found that the elevations of the outlet and undercurrent layer are essential to determine the efficiency of flood discharge, while appropriate timing and outflow discharge volumes may further enhance the results. Therefore, using a hydrodynamic model to predict the position of an undercurrent layer, and opening spillways near the elevation of the undercurrent layer can improve the efficacy of flood discharge. Our findings provide novel insights that may be used to improve the operation and management of source water reservoirs.
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Affiliation(s)
- Fan Si
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an, 710055, PR China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, PR China
| | - Tinglin Huang
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an, 710055, PR China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, PR China.
| | - Nan Li
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an, 710055, PR China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, PR China
| | - Kai Li
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an, 710055, PR China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, PR China
| | - Gang Wen
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an, 710055, PR China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, PR China
| | - Yang Li
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an, 710055, PR China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, PR China; School of Energy and Environment, Zhongyuan University of Technology, Zhengzhou, 450007, PR China
| | - Haihan Zhang
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an, 710055, PR China; Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, PR China
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Deng L, Shahab A, Xiao H, Li J, Rad S, Jiang J, Jiang P, Huang H, Li X, Ahmad B, Siddique J. Spatial and temporal variation of dissolved heavy metals in the Lijiang River, China: implication of rainstorm on drinking water quality. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:68475-68486. [PMID: 34275078 DOI: 10.1007/s11356-021-15383-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 07/06/2021] [Indexed: 05/16/2023]
Abstract
Lijiang River is an essential drinking water source and natural scenery in the Guilin City. For the first time, implications of rainstorm were taken into consideration by investigating spatial and temporal variation of dissolved heavy metals (HMs) in the Lijiang River water. A total of 68 water samples were collected during low flow (normal) season and high flow (rainstorm) season from 34 sampling sites. Dissolved HMs including Cr, Mn, Co, Cu, Zn, As, Cd, Sb, and Pb were found to meet the respective drinking water standards, while comparatively higher concentration was observed after the rainstorm season, except for Cr. Multivariate statistical analysis showed that Co, Cu, Cr, Zn, Sb, and Pb in normal season were mainly controlled by anthropogenic sources. Furthermore, higher concentrations of Mn, Cu, Cd, Pb, Co, and Zn during the high flow season were attributed to rainstorm. The water quality index (WQI) showed good grades and comparatively lower in rainstorm season. The results of health risk assessment revealed that HMs in Lijiang River posed limited health risk; however, As posed potential health risk specially in rainstorm season. It is suggested to adopt preventive measures for mining activities and industrial waste-water discharge at the river's upstream and downstream.
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Affiliation(s)
- Liming Deng
- College of Environmental Science and Engineering, Guilin University of Technology, Guilin, 541004, China
| | - Asfandyar Shahab
- College of Environmental Science and Engineering, Guilin University of Technology, Guilin, 541004, China
| | - He Xiao
- College of Environmental Science and Engineering, Guilin University of Technology, Guilin, 541004, China.
- State Key Laboratory of Isotope Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China.
- CAS Center for Excellence in Deep Earth Science, Guangzhou, 510640, China.
| | - Jieyue Li
- College of Environmental Science and Engineering, Guilin University of Technology, Guilin, 541004, China
| | - Saeed Rad
- College of Environmental Science and Engineering, Guilin University of Technology, Guilin, 541004, China.
| | - Jinping Jiang
- College of Environmental Science and Engineering, Guilin University of Technology, Guilin, 541004, China
| | - Pingping Jiang
- College of Environmental Science and Engineering, Guilin University of Technology, Guilin, 541004, China
| | - Hongwei Huang
- College of Environmental Science and Engineering, Guilin University of Technology, Guilin, 541004, China
| | - Xiangkui Li
- College of Environmental Science and Engineering, Guilin University of Technology, Guilin, 541004, China
| | - Bilal Ahmad
- Institute of Agriculture Science and Forestry, University of Swat, Mingora, 19130, Pakistan
| | - Jamil Siddique
- Department of the Earth Sciences, Quaid-I-Azam University Islamabad, Islamabad, 45320, Pakistan
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Yu H, Xu S, Li W, Liu J. Removal process of phosphorus during the settlement of particulates with runoff and its implication for reservoir management. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:49588-49601. [PMID: 33939096 DOI: 10.1007/s11356-021-14137-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 04/22/2021] [Indexed: 06/12/2023]
Abstract
Substantial particulates and phosphorus (P) loads are carried into the reservoir by flood runoff and the P exchange between water and settling particulates under variable water conditions in the reservoir after flooding is critical to the removal of active P from water. To investigate the impact of particulate sedimentation on P changes in reservoir water, runoff samples were collected at four locations in the upstream channels of two reservoirs after a rainstorm. Two batches of particulate sedimentation simulations were conducted separately in four plexiglass columns to analyze the changes of water P and environmental factors during particulate sedimentation. The results showed that the contents of total P (TP), total particulates P (TPP), and phosphate (PO43-) decreased with the settlement of particulates. The correlation between the environmental factors and the amount of PO43- in water changed from uncorrelated to correlated with particulate settlement, implying that the rapid settling of particulates might weaken the effect of environmental factors on P exchange between water and particulates. Particulates firstly release PO43- rapidly in river or reservoir and then adsorb PO43- slowly during settlement in reservoirs. Coarse particulates release more and adsorb less PO43- during settlement, and fine particulates play an important role in the removal of water PO43- due to the slow sedimentation rates. Therefore, to mitigate the reactive P content of reservoir water, the loss of coarse particulates from the watershed should be controlled, and the discharge of water with particulates downstream should also be avoided during the flood season.
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Affiliation(s)
- Huijuan Yu
- Faculty of Infrastructure Engineering, Dalian University of Technology, Linggong Road 2, Dalian, 116024, China
| | - Shiguo Xu
- Faculty of Infrastructure Engineering, Dalian University of Technology, Linggong Road 2, Dalian, 116024, China.
| | - Weijia Li
- Faculty of Infrastructure Engineering, Dalian University of Technology, Linggong Road 2, Dalian, 116024, China
| | - Jianwei Liu
- Faculty of Infrastructure Engineering, Dalian University of Technology, Linggong Road 2, Dalian, 116024, China
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Yang Y, Deng Y, Tuo Y, Li J, He T, Chen M. Study of the thermal regime of a reservoir on the Qinghai-Tibetan Plateau, China. PLoS One 2020; 15:e0243198. [PMID: 33347489 PMCID: PMC7751983 DOI: 10.1371/journal.pone.0243198] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 11/17/2020] [Indexed: 11/19/2022] Open
Abstract
The Qinghai-Tibetan Plateau region has unique meteorological characteristics, with low air temperature, low air pressure, low humidity, little precipitation, and strong diurnal variation. A two-dimensional hydrodynamic CE-QUAL-W2 model was configured for the Pangduo Reservoir to better understand the thermal structure and diurnal variation inside the reservoir under the local climate and hydrological conditions on the Qinghai-Tibetan Plateau. Observation data were used to verify the model, and the results showed that the average error of the 6 profile measured monthly from August to December 2016 was 0.1°C, and the root-mean-square error (RMSE) was 0.173°C. The water temperature from August 2016 to September 2017 was simulated by inputting measured data as model inputs. The results revealed that the reservoir of the Qinghai-Tibetan Plateau was a typical dimictic reservoir and the water mixed vertically at the end of March and the end of October. During the heating period, thermal stratification occurred, with strong diurnal variation in the epilimnion. The mean variance of the diurnal water temperature was 0.10 within a 5 m water depth but 0.04 in the whole water column. The mixing mode of inflow changed from undercurrent, horizontal-invaded flow and surface layer flow in one day. In winter, the diurnal variation was weak due to the thermal protection of the ice cover, while the mean variance of diurnal water temperature was 0.00 within both 5 m and the whole water column. Compared to reservoirs in areas with low altitude but the same latitude, significant differences occurred between the temperature structure of the low-altitude reservoir and the Pangduo Reservoir (P<0.01). The Pangduo Reservoir presented a shorter stratification period and weaker stratification stability, and the annual average SI value was 26.4 kg/m2, which was only 7.5% that of the low-altitude reservoir. The seasonal changes in the net heat flux received by the surface layers determined the seasonal cycle of stratification and mixing in reservoirs. This study provided a scientific understanding of the thermal changes in stratified reservoirs under the special geographical and meteorological conditions on the Qinghai-Tibetan Plateau. Moreover, this model can serve as a reference for adaptive management of similar dimictic reservoirs in cold and high-altitude areas.
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Affiliation(s)
- Yanjing Yang
- State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, China
| | - Yun Deng
- State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, China
| | - Youcai Tuo
- State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, China
| | - Jia Li
- State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, China
| | - Tianfu He
- State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, China
| | - Min Chen
- State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, China
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Zhang H, Yan M, Huang T, Huang X, Yang S, Li N, Wang N. Water-lifting aerator reduces algal growth in stratified drinking water reservoir: Novel insights into algal metabolic profiling and engineering applications. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 266:115384. [PMID: 32823043 DOI: 10.1016/j.envpol.2020.115384] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 08/04/2020] [Accepted: 08/04/2020] [Indexed: 06/11/2023]
Abstract
Water-lifting aerator (WLA) which was developed by Professor Tinglin Huang at Xi'an University of Architecture and Technology, China has multi-functional water quality improvement that significantly inhibits the occurrence of harmful algal blooms (HABs) in deep drinking water reservoirs. However, the biological mechanism of WLA to the suppress algal growth has not been comprehensively understood. Here, the cellular mechanism that allows WLA to control HABs was explored based on the combination of both laboratory simulation and field investigation. Under simulated hydrodynamic conditions, the results showed that the cell density, chlorophyll a content, chlorophyll fluorescence parameters, and dehydrogenase activity in Microcystis aeruginosa all peaked under light conditions at 25 °C. The metabolic activity of M. aeruginosa varied significantly under low temperature at 6 °C and light conditions when cultured for 48 h. The extracellular organic matter (EOM) and intracellular organic matter (IOM) contents of M. aeruginosa were both resolved into three components. Moreover, the total fluorescence intensities from EOM and IOM both peaked under light conditions at 25 °C. The field investigation showed that the growth of algae was decreased significantly in Lijiahe drinking water reservoir with WLA application. The chlorophyll fluorescence parameters decreased significantly after vertical mixing, thereby indicating that the WLA weakened the photosynthetic ability and reduced the biological activity of algae in situ. In addition, the WLA significantly affected the vertical distribution of the phytoplankton community composition. Altogether, these results shed new lights on understanding the control of algal blooms by WLA in stratified drinking water reservoirs. WLA has broad prospect of engineering applications, which can control algal blooms of water supply resources in situ, therefore, reduce the content of disinfection by-products in drinking water treatment plants.
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Affiliation(s)
- Haihan Zhang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an, 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China; Xi'an Key Laboratory of Water Source and Water Quality Guarantee, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Miaomiao Yan
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an, 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China; Xi'an Key Laboratory of Water Source and Water Quality Guarantee, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Tinglin Huang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an, 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China; Xi'an Key Laboratory of Water Source and Water Quality Guarantee, Xi'an University of Architecture and Technology, Xi'an, 710055, China.
| | - Xin Huang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an, 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China; Xi'an Key Laboratory of Water Source and Water Quality Guarantee, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Shangye Yang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an, 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China; Xi'an Key Laboratory of Water Source and Water Quality Guarantee, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Nan Li
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an, 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China; Xi'an Key Laboratory of Water Source and Water Quality Guarantee, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Na Wang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an, 710055, China; School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China; Xi'an Key Laboratory of Water Source and Water Quality Guarantee, Xi'an University of Architecture and Technology, Xi'an, 710055, China
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Water Level Decline in a Reservoir: Implications for Water Quality Variation and Pollution Source Identification. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17072400. [PMID: 32244699 PMCID: PMC7177727 DOI: 10.3390/ijerph17072400] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 03/28/2020] [Accepted: 03/28/2020] [Indexed: 12/30/2022]
Abstract
Continuous water-level decline makes the changes of water quality in reservoirs more complicated. This paper uses trend analyses, wavelet analysis and principal component analysis-multiple linear regression to explore the changes and pollution sources affecting water quality during a period of continuous reservoir water level decline (from 65.37 m to 54.15 m), taking the Biliuhe reservoir as an example. The results showed that the change of water level of Biliuhe reservoir has a significant 13-year periodicity. The unusual water quality changes during the low water level period were as follows: total nitrogen continued to decrease. And iron was lower than its historical level. pH, total phosphorus, and ammonia nitrogen were higher than historical levels and fluctuated seasonally. Permanganate index increased as water level decreased after initial fluctuations. Dissolved oxygen was characterized by high content in winter and relatively low content in summer. The pollutant sources of non-point source pollution (PC1), sediment and groundwater pollution (PC2), atmospheric and production & domestic sewage (PC3), other sources of pollution (PC4) were identified. The main source of DO, pH, TP, TN, NH4-N, Fe and CODMn were respectively PC3 (42.13%), PC1 (47.67%), PC3 (47.62%), PC1 (29.75%), PC2 (47.01%), PC1 (56.97%) and PC2 (50%). It is concluded that the continuous decline of water level has a significant impact on the changes and pollution sources affecting water quality. Detailed experiments focusing on sediment pollution release flux, and biological action will be explored next.
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Yan M, Chen S, Huang T, Li B, Li N, Liu K, Zong R, Miao Y, Huang X. Community Compositions of Phytoplankton and Eukaryotes during the Mixing Periods of a Drinking Water Reservoir: Dynamics and Interactions. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E1128. [PMID: 32053903 PMCID: PMC7068298 DOI: 10.3390/ijerph17041128] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 02/05/2020] [Accepted: 02/07/2020] [Indexed: 11/17/2022]
Abstract
In deep drinking water reservoir ecosystems, the dynamics and interactions of community compositions of phytoplankton and eukaryotes during the mixing periods are still unclear. Here, morphological characteristics combined with high-throughput DNA sequencing (HTS) were used to investigate the variations of phytoplankton and the eukaryotic community in a large canyon-shaped, stratified reservoir located at the Heihe River in Shaanxi Province for three months. The results showed that Bacillariophyta and Chlorophyta were the dominant taxa of the phytoplankton community, accounting for more than 97% of total phytoplankton abundance, which mainly consisted of Melosira sp., Cyclotella sp., and Chlorella sp., respectively. Illumina Miseq sequencing suggested that the biodiversity of eukaryotes increased over time and thatspecies distribution was more even. Arthropoda (6.63% to 79.19%), Ochrophyta (5.60% to 35.16%), Ciliophora (1.81% to 10.93%) and Cryptomonadales (0.25% to 11.48%) were the keystone taxa in common, contributing over 50% of the total eukaryotic community. Cryptomycota as a unique fungus was observed to possess significant synchronization with algal density, reaching a maximum of 10.70% in December (when the algal density distinctly decreased) and suggesting that it might affect the growth of algae through parasitism. Co-occurrence network patterns revealed the complicated and diverse interactions between eukaryotes and phytoplankton, suggesting that eukaryotes respond to variations in dynamic structure of the phytoplankton community, although there might be antagonistic or mutualistic interactions between them. Redundancy analysis (RDA) results showed that environmental variables collectively explained a 96.7% variance of phytoplankton and 96.3% variance of eukaryotic microorganisms, indicating that the temporal variations of phytoplankton and eukaryotic microorganisms were significantly affected by environmental conditions. This study shows that potential interactions exist between phytoplankton and eukaryotic microorganism communities, andcould improve our understanding of the ecological roles of phytoplankton and eukaryotic microorganisms in changing aquatic ecosystems. However, long-term investigations are necessary in order to obtain comprehensive understandings of their complicated associations.
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Affiliation(s)
- Miaomiao Yan
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi’an University of Architecture and Technology, Xi’an 710055, China; (M.Y.); (T.H.); (N.L.); (K.L.); (R.Z.); (Y.M.); (X.H.)
| | - Shengnan Chen
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi’an University of Architecture and Technology, Xi’an 710055, China; (M.Y.); (T.H.); (N.L.); (K.L.); (R.Z.); (Y.M.); (X.H.)
| | - Tinglin Huang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi’an University of Architecture and Technology, Xi’an 710055, China; (M.Y.); (T.H.); (N.L.); (K.L.); (R.Z.); (Y.M.); (X.H.)
| | - Baoqin Li
- Guangdong Key Laboratory of Integrated Agro-Environmental Pollution Control and Management, Guangdong Institute of Eco-Environmental Science and Technology, Guangzhou 510650, China;
| | - Nan Li
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi’an University of Architecture and Technology, Xi’an 710055, China; (M.Y.); (T.H.); (N.L.); (K.L.); (R.Z.); (Y.M.); (X.H.)
| | - Kaiwen Liu
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi’an University of Architecture and Technology, Xi’an 710055, China; (M.Y.); (T.H.); (N.L.); (K.L.); (R.Z.); (Y.M.); (X.H.)
| | - Rongrong Zong
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi’an University of Architecture and Technology, Xi’an 710055, China; (M.Y.); (T.H.); (N.L.); (K.L.); (R.Z.); (Y.M.); (X.H.)
| | - Yutian Miao
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi’an University of Architecture and Technology, Xi’an 710055, China; (M.Y.); (T.H.); (N.L.); (K.L.); (R.Z.); (Y.M.); (X.H.)
| | - Xin Huang
- Shaanxi Key Laboratory of Environmental Engineering, Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi’an University of Architecture and Technology, Xi’an 710055, China; (M.Y.); (T.H.); (N.L.); (K.L.); (R.Z.); (Y.M.); (X.H.)
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12
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Huang Y, Yang C, Wen C, Wen G. S-type Dissolved Oxygen Distribution along Water Depth in a Canyon-shaped and Algae Blooming Water Source Reservoir: Reasons and Control. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16060987. [PMID: 30893863 PMCID: PMC6466274 DOI: 10.3390/ijerph16060987] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 03/14/2019] [Accepted: 03/15/2019] [Indexed: 11/21/2022]
Abstract
Dissolved oxygen (DO) is a crucial indicator of water quality. DO usually shows a monotonic decrease along water depth during thermal stratification in reservoir, whereas metalimnetic oxygen minimum (MOM) is observed in some cases. Although MOM phenomena have been reported in different areas, the characteristics of different reservoirs are greatly different, and few comprehensive studies have been published regarding MOM in Chinese drinking water source reservoirs. The DO distribution along water depth was determined and the detailed reasons were clarified by two-years of field monitoring. In addition the effect of water lifting aerators (WLAs) on DO improvement was investigated in the Lijiahe Reservoir in Northwest China. A typical S-type DO distribution with two anaerobic water layers, below the epilimnion (10–25 m water depth) and above the sediment (bottom water), was observed derived from the decomposition of dead algae or organic matter and the restriction of DO vertical exchange. Moreover, after WLAs’ operation since 10 June 2018, the water body was completely mixed and DO was rich and uniform along water depth by eliminating the water stratification and inhibiting algae growth. The deep understanding of the DO distribution in a deep canyon-shaped reservoir and the technical support for reservoir restoration are meaningful for optimizing reservoir management.
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Affiliation(s)
- Yuwei Huang
- Faculty of Urban Construction and Environmental Engineering, Chongqing University, Chongqing 400444, China.
| | - Chun Yang
- Faculty of Urban Construction and Environmental Engineering, Chongqing University, Chongqing 400444, China.
| | - Chengcheng Wen
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China.
- Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China.
| | - Gang Wen
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi'an University of Architecture and Technology, Xi'an 710055, China.
- Shaanxi Key Laboratory of Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China.
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13
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Correlation Analysis of Rainstorm Runoff and Density Current in a Canyon-Shaped Source Water Reservoir: Implications for Reservoir Optimal Operation. WATER 2018. [DOI: 10.3390/w10040447] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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14
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Yang X, Tan L, He R, Fu G, Ye J, Liu Q, Wang G. Stochastic sensitivity analysis of nitrogen pollution to climate change in a river basin with complex pollution sources. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2017; 24:26545-26561. [PMID: 28952024 DOI: 10.1007/s11356-017-0257-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2016] [Accepted: 09/19/2017] [Indexed: 06/07/2023]
Abstract
It is increasingly recognized that climate change could impose both direct and indirect impacts on the quality of the water environment. Previous studies have mostly concentrated on evaluating the impacts of climate change on non-point source pollution in agricultural watersheds. Few studies have assessed the impacts of climate change on the water quality of river basins with complex point and non-point pollution sources. In view of the gap, this paper aims to establish a framework for stochastic assessment of the sensitivity of water quality to future climate change in a river basin with complex pollution sources. A sub-daily soil and water assessment tool (SWAT) model was developed to simulate the discharge, transport, and transformation of nitrogen from multiple point and non-point pollution sources in the upper Huai River basin of China. A weather generator was used to produce 50 years of synthetic daily weather data series for all 25 combinations of precipitation (changes by - 10, 0, 10, 20, and 30%) and temperature change (increases by 0, 1, 2, 3, and 4 °C) scenarios. The generated daily rainfall series was disaggregated into the hourly scale and then used to drive the sub-daily SWAT model to simulate the nitrogen cycle under different climate change scenarios. Our results in the study region have indicated that (1) both total nitrogen (TN) loads and concentrations are insensitive to temperature change; (2) TN loads are highly sensitive to precipitation change, while TN concentrations are moderately sensitive; (3) the impacts of climate change on TN concentrations are more spatiotemporally variable than its impacts on TN loads; and (4) wide distributions of TN loads and TN concentrations under individual climate change scenario illustrate the important role of climatic variability in affecting water quality conditions. In summary, the large variability in SWAT simulation results within and between each climate change scenario highlights the uncertainty of the impacts of climate change and the need to incorporate extreme conditions in managing water environment and developing climate change adaptation and mitigation strategies.
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Affiliation(s)
- Xiaoying Yang
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200433, China.
| | - Lit Tan
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200433, China
| | - Ruimin He
- State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, 210029, China
| | - Guangtao Fu
- Centre for Water Systems, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, EX4 4QF, UK
| | - Jinyin Ye
- Anhui Province Meteorological Observatory, Hefei, 230001, China
| | - Qun Liu
- Zhumadian City Bureau of Environmental Protection, Zhumadian, 463000, China
| | - Guoqing Wang
- State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, 210029, China.
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Long-term trends of phosphorus concentrations in an artificial lake: Socio-economic and climate drivers. PLoS One 2017; 12:e0186917. [PMID: 29049408 PMCID: PMC5648255 DOI: 10.1371/journal.pone.0186917] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2017] [Accepted: 10/10/2017] [Indexed: 11/19/2022] Open
Abstract
European freshwater ecosystems have undergone significant human-induced and environmentally-driven variations in nutrient export from catchments throughout the past five decades, mainly in connection with changes in land-use, agricultural practice, waste water production and treatment, and climatic conditions. We analysed the relations among concentration of total phosphorus (TP) in the Slapy Reservoir (a middle reservoir of the Vltava River Cascade, Czechia), and socio-economic and climatic factors from 1963 to 2015. The study was based on a time series analysis, using conventional statistical tools, and the identification of breaking points, using a segmented regression. Results indicated clear long-term trends and seasonal patterns of TP, with annual average TP increasing up until 1991 and decreasing from 1992 to 2015. Trends in annual, winter and spring average TP concentrations reflected a shift in development of sewerage and sanitary infrastructure, agricultural application of fertilizers, and livestock production in the early 1990s that was associated with changes from the planned to the market economy. No trends were observed for average TP in autumn. The summer average TP has fluctuated with increased amplitude since 1991 in connection with recent climate warming, changes in thermal stratification stability, increased water flow irregularities, and short-circuiting of TP-rich inflow during high flow events. The climate-change-induced processes confound the generally declining trend in lake-water TP concentration and can result in eutrophication despite decreased phosphorus loads from the catchment. Our findings indicate the need of further reduction of phosphorus sources to meet ecological quality standards of the EU Water Framework Directive because the climate change may lead to a greater susceptibility of the aquatic ecosystem to the supply of nutrients.
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