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Eutrophication evaluation of the lakes under different water connectivity around Poyang Lake region
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Currently, the decline in the quality of river and lake water continues, for this reason, activities to control pollution and improve river and lake water quality are required. One effort to prevent this problem is to implement online water quality monitoring technology continuously and in real time. The information generated from the water quality monitoring system can be used as a basis for planning watershed management and determining river and lake water management policies at the national and regional levels. The purpose of this activity is to analyze river and lake water quality data and evaluate the performance of the monitoring systems in 16 water quality monitoring stations that have been built. The data being analyzed is from 2016 to 2020 and includes the parameters of temperature, conductivity, TDS, DO, pH, and turbidity. The 16 station locations are spread over the Ciliwung River, Cisadane River, Citarum River, Serayu River, Bengawan Solo River, and Lake Toba. This research method uses descriptive statistical analysis and the STORET method, which refers to the Decree of the Minister of Environment and Forestry Number 115 of 2003 and Government Regulation of the Republic of Indonesia Number 82 of 2001. The results of this study indicate that most of the rivers monitored fall into the moderate to heavily polluted category, especially the rivers downstream of the Ciliwung, Cisadane, and Bengawan Solo rivers. The results of the analysis of DO, TDS, conductivity, and turbidity parameters from 16 monitoring stations, mostly met the Class II quality standards.
Floodplains play essential roles in the ecological functions of regional environments. The merging and coalescence of bacterial communities in aquatic environments results in periodic patterns driven by regular hydrological activities, which may, in turn, influence ecological activities. However, the degree of bacterial community coalescence in the lateral and vertical directions as well as the underlying hydrological mechanism of floodplain ecosystems is poorly understood. Therefore, we investigated the spatiotemporal patterns and coalescence processes of planktonic and sedimentary bacterial communities during normal and high-water periods in a floodplain ecosystem of the Yellow River source region. We classified bacterial operational taxonomic units (OTUs) based on 16S rRNA gene sequencing, and quantified community coalescence by calculating the proportions of overlapping OTUs, the contributions of upstream sources to downstream sinks, and positive/negative cohesion. The results revealed major differences in the composition and diversity of planktonic and sedimentary bacterial communities. Bacterial community diversity in the high-water period was higher than in the normal period. Laterally, hydrological connectivity promoted the immigration and coalescence of bacterial communities to oxbow lakes in both the mainstream and tributaries, with the coalescence degree of planktonic bacteria (2.9%) higher than that of sedimentary bacteria (1.7%). Vertically, the coalescence degree of mainstream planktonic and sedimentary bacterial communities was highest, reaching 2.9%. Co-occurrence network analysis revealed that hydrological connectivity increased the complexity of the bacterial network and enhanced the coalescence of keystone species to oxbow lakes. Furthermore, community coalescence improved the competitiveness and dispersal of bacterial communities. This study demonstrated that coalescence of bacterial communities is driven by hydrological connectivity in a floodplain ecosystem. Further studies should investigate the processes of bacterial community coalescence in floodplains in more detail, which could provide new approaches for environmental protection and ecological function preservation.
Algal blooms constitute an emerging threat to global inland water quality, yet their spatial and temporal distribution at the global scale remains largely unknown. Here we establish a global bloom database, using 2.91 million Landsat satellite images from 1982 to 2019 to characterize algal blooms in 248,243 freshwater lakes, representing 57.1% of the global lake area. We show that 21,878 lakes (8.8%) spread across six continents have experienced algal blooms. The median bloom occurrence of affected lakes was 4.6%, but this frequency is increasing; we found increased bloom risks in the 2010s, globally (except for Oceania). The most pronounced increases were found in Asia and Africa, mostly in developing countries that remain reliant on agricultural fertilizer. As algal blooms continue to expand in scale and magnitude, this baseline census will be vital towards future risk assessments and mitigation efforts.
The quality of aquaculture waters is directly related to water management and aquaculture efficiency, which puts forward higher requirements for water quality evaluation. Based on the consideration of the influence of temporal and spatial changes on the water quality, this paper proposed an improved fuzzy comprehensive evaluation method for aquaculture water quality evaluation. Specifically, constructing a new membership function in the first place, and then selecting dissolved oxygen, pH, temperature and ammonia nitrogen content as water quality indexes for aquaculture, after that, collecting 60 sets of water quality index for different seasons in the past three years, finally, evaluating the water quality of Yangjiabo Aquaculture Base. Meanwhile, comparing it with the evaluation results of the single factor evaluation method and the traditional fuzzy evaluation method. The results show that the water quality of the Yangjiabo Aquaculture Base is at the worst level in winter, and the water quality has improved significantly in spring, summer and autumn. Compared with the other two method, the improved method can comprehensively reflect the changes in water quality with time and space, which is more practical, and so it can be considered to provide a scientific basis for efficient aquaculture and water quality classification.
Lake eutrophication is a global challenge. The models of eutrophication response and watershed optimization control decision-making are the key to formulating economic and efficient action plans. However, the existing reviews of eutrophication model mainly focus on the single aspects of model development, case study, sensitivity analysis, uncertainty analysis, simplification and surrogate model. There is a lack of the summary of studies on the coupling of macro and micro aspects, such as the non-linear response, treatment decision and water quality improvement and long-term evolution of ecosystems. Therefore the models and methods of lake eutrophication response simulation and pollution-reduction optimization were summarized and analyzed in this study. The eutrophication models are divided into (a) data-driven statistical models, (b) causal-driven mechanism models, and (c) decision-oriented optimization models. Generalized statistical models including classic statistics, Bayesian statistics, and machine learning are often used on response relationships establishment, time series analysis, and spatio-temporal forecasting and early warning. The mechanism model consists of the hydrological, hydrodynamic, water quality, aquatic ecology, and other processes. It is usually used to simulate the change on different spatial and temporal scales, in conjunction with the watershed models. Among them, sensitivity analysis, parameter verification, and model uncertainty will cause high computing costs. The decision-oriented optimization model combines the mechanism model to form a “simulation-optimization” system, which derives a variety of methods such as stochastic optimization and interval optimization under uncertainty. It can deal with the cost of computing time through parallel calculation, simplification, and surrogate models. The challenges for future lake management were identified, including: (a) integration of the external input and the heterogeneity of the lake's nitrogen, phosphorus and algae; (b) improving the correlation and accuracy of optimal control decisions and water quality targets; and (c) exploring the long-term changes of lake ecosystems trajectory and driven factors. Several research focus were proposed to deal with the challenges, including (a) prediction of lake water quality response based on multivariate data fusion and machine learning algorithms; (b) upscaling or downscaling coupling of mechanism models based on biomass and action-driven agent-based model to express the interaction process of population at multiple scales; (c) machine learning algorithms and mechanism models are directly coupled or data assimilation to reduce simulation errors; and (d) multiple simulation models with different spatial-temporal scales are fused to achieve precise and dynamic optimization.
Nutrient zoning is an important basis for the monitoring, evaluation, protection and management in lakes. In comparison to other freshwater lakes, Poyang Lake contains better water quality as the biggest fresh-water lake in China. The eco-environmental indicators change by spatial distributions, which is significant for the nutrient zoning of Poyang Lake. Through the nutrient zoning indicator analysis, a standard index system of Poyang Lake was set up containing five indicators: transparency, chla, TN, TP, and COD. By using hierarchical cluster analysis combined with administrative boundaries and aquatic ecological zoning steps, principles, and methods, Poyang Lake was divided into six zonings: Rujiangshuidao Region, West Lake Region, North Lake Region, South Lake Region, Northeast Lake Region, and Southeast Lake Region. The decreasing order of trophic level index in every individual region is from North Lake Region, Northeast Lake Region, Southeast Lake Region, South Lake Region, West Lake Region, to Ruijiangshuidao Region. Nutrient zoning could provide scientific support for eutrophication research, eco-environment protection and management in Poyang Lake.
于2014年冬季和夏季调查太湖全湖116个样点的大型底栖动物,分析其群落结构及与环境因子的关系.共记录底栖动物55种,隶属3门7纲18目27科52属,底栖动物的平均密度和生物量分别为405.5 ind./m²和146.6 g/m².优势度分析表明,河蚬(Corbicula fluminea)、铜锈环棱螺(Bellamya aeruginosa)、霍甫水丝蚓(Limnodrilus hoffmeisteri)、太湖大螯蜚(Grandidierella aihuensis)、寡鳃齿吻沙蚕(Nephtys oligobranchia)和拟背尾水虱属一种(Paranthura sp.)是太湖大型底栖动物的优势种.基于环境因子聚类分析,可将全湖分为3个区:敞水区、水生植被区和富营养区.方差分析表明各湖区间环境因子差异显著.统计分析表明,3个区底栖动物群落结构相似性低,差异显著.典范对应分析表明,水深、总氮、总磷、铵态氮、水生植物、溶解性有机碳和沉积物中值粒径与大型底栖动物群落结构显著相关.K-优势曲线、物种多样性指数显示,从水生植被区→敞水区→富营养区,营养水平增加,底栖动物多样性逐渐降低,生物量逐渐升高.研究结果表明营养水平、底质类型以及水生植被的分布是决定太湖大型底栖动物群落结构及多样性的关键因子.To characterize the community structure of macrozoobenthos and to examine their relationships with environmental factors,macrozoobenthos were investigated at 116 sites of Lake Taihu in winter and summer of 2014. A total of 55 species were recorded, belonging to 3 phyla, 7 classes, 18 orders and 27 families. The mean density and biomass of macrozoobenthos were 405.5 ind./m² and 146.6 g/m², respectively. Corbicula fluminea, Bellamya aeruginosa, Limnodrilus hoffmeisteri, Grandidierella aihuensis, Nephtys oligobranchia and Paranthura sp. were the dominant species in Lake Taihu. The 116 sampling sites were classified into three groups based on cluster analysis using environmental factors. One-way ANOVA showed that environmental factors differed significantly among the three groups. Analysis of similarities and non-metric multidimensional scaling showed that macrozoobenthic assemblages exhibited remarkable difference among the three groups. Canonical correspondence analysis demonstrated that macrozoobenthic community structure was highly correlated with habitat-specific differences in water depth, total nitrogen, total phosphorus, ammonium nitrogen, macrophytes, dissolved organic carbon and Φ50. From the east and southwest to the north area of Lake Taihu, the diversity indexes of macrozoobenthos decreased but the density and biomass increased with the increase of trophic status index. Our results showed that the trophic level, bottom sediment type and macrophytes coverage were the key factors regulating community structure and diversity of macrozoobenthos.
A new method, with the non-fully mixed coefficient (NFMC) considered, was put forward to calculate the water environmental carrying capacity (WECC) for huge river-connected lakes, of which the hydrological conditions always vary widely during a year. Poyang Lake, the most typical river-connected lake and the largest freshwater lake in China, was selected as the research area. Based on field investigations and numerical simulation, the monthly pollutant degradation coefficients and non-fully mixed coefficients of different lake regions were determined to explore the WECCs of COD, TN and TP of Poyang Lake in a common water year. It was found that under the hydrological conditions of a common water year the total WECCs of COD, TN and TP in the lake were respectively 181.9 × 104 t, 33.3 × 104 t and 1.86 × 104 t. Due to the varied lake water volume and self-purification ability, an evident temporal fluctuation of WECCs in Poyang Lake was observed. The dry seasons were characterized by a higher NFMCs but lower WECCs owing to the lower water level and degradation ability. Variation coefficients of COD and TN WECC were close to each other, of which the average level was about 58.5%, a little higher than that of TP.
Artificial landscape water bodies filled by treated wastewater pose a risk of developing algal blooms due to high nutrient levels of treated wastewater. In this study, water exchange experiments were conducted using treated wastewater in an artificial landscape pond, and a eutrophication model was calibrated and applied to evaluate the effects of water exchange on algae growth in the pond. The results indicate that the joint dilution process and nutrient supply process of water exchange initially cause the algae level to rise and then rapidly decline as the hydraulic resident time (HRT) decreases, and HRT has a critical point at which the pond faces the highest risk of algal bloom. The study also indicates that phosphorus (instead of nitrogen) is the primary limiting factor of algae growth. Therefore, the critical HRT should be avoided and phosphorus is the target pollutant to be controlled in landscape pond water management.
Relieving phosphorus loading is a key management tool for controlling Lake Erie eutrophication. During the 1960s and 1970s, increased phosphorus inputs degraded water quality and reduced central basin hypolimnetic oxygen levels which, in turn, eliminated thermal habitat vital to cold-water organisms and contributed to the extirpation of important benthic macroinvertebrate prey species for fishes. In response to load reductions, initiated in 1972, Lake Erie responded quickly with reduced water-column phosphorus concentrations, phytoplankton biomass, and bottom-water hypoxia (dissolved oxygen < 2 mg/l). Since the mid-1990s, cyanobacteria blooms increased and extensive hypoxia and benthic algae returned. We synthesize recent research leading to guidance for addressing this re-eutrophication, with particular emphasis on central basin hypoxia. We document recent trends in key eutrophication-related properties, assess their likely ecological impacts, and develop load response curves to guide revised hypoxia-based loading targets called for in the 2012 protocol amending the Great Lakes Water Quality Agreement. Reducing central basin hypoxic area to levels observed in the early 1990s (ca. 2,000 km2) requires cutting total phosphorus loads by 46% from the 2003-2011 average or reducing dissolved reactive phosphorus loads by 78% from the 2005-2011 average. Reductions to these levels are also protective of fish habitat. We provide potential approaches for achieving those new loading targets, and suggest that recent load reduction recommendations focused on western basin cyanobacteria blooms may not be sufficient to reduce central basin hypoxia to 2,000 km2.
Chlorophyll-a (Chl-a) and abiotic variables were measured in the main channel and floodplain waterbodies of the Middle Paraná River to analyse the system dynamics and to assess their spatial variability during different hydrological phases, including an extreme flood. We wanted to test that the flood does not always have a homogenising effect in a river–floodplain system. An explanatory model for Chl-a was performed according to Akaike’s Information Criterion (AIC), and the relation of water level with the coefficient of variation (CV) among sites for each variable was explored. The model explained 64% of Chl-a variability. Water level, depth:euphotic zone ratio (Z
d:Z
eu) (inverse correlation) and conductivity (direct correlation) were the significant explicative variables. The CV of Chl-a decreased with flood from the main channel to the floodplain, but for turbidity, Z
d:Z
eu, pH, dissolved oxygen, soluble reactive phosphorus and Chl-a:pheophytin-a ratio, it increased. However, within the floodplain, CV of turbidity, Z
d:Z
eu and pH decreased during flood. These suggest that the homogenising effect frequently observed during inundation cannot be generalised and that the floodplain may maintain its identity even during flood. The extreme flood and its overlap with the warm season and sedimentological pulse probably contributed to the heterogeneity in the spatial gradient.
A numerical trophic state index for lakes has been developed that incorporates most lakes in a scale of 0 to 100. Each major division ( 10, 20, 30, etc. ) represents a doubling in algal biomass. The index number can bc calculated from any of several parameters, including Secchi disk transparency, chlorophyll, and total phosphorus. My purpose here is to present a new ap- proach to the trophic classification of lakes. This new approach was developed because of frustration in communicating to the pub- lic both the current nature or status of lakes and their future condition after restoration when the traditional trophic classification system is used. The system presented hcrc, termed a trophic state index (TSI), in- volves new methods both of defining trophic status and of determining that status in lakes. All trophic classification is based on the division of the trophic continuum, howcvcr this is defined, into a series of classes termed trophic states. Traditional systems divide the continuum into three classes: oligotrophic, mesotrophic, and cutrophic. There is often no clear delineation of these divisions. Determinations of trophic state are made from examination of several di- verse criteria, such as shape of the oxygen curve, species composition of the bottom fauna or of the phytoplankton, conccntra- tions of nutrients, and various measures of biomass or production. Although each changes from oligotrophy to eutrophy, the changes do not occur at sharply defined places, nor do they all occur at the same place or at the same rate. Some lakes may be considered oligotrophic by one criterion and eutrophic by another; this problem is
Eutrophication has become a serious threat to the lake systems all over the world. This is mainly due to the pollution caused by anthropogenic activities. Carlson trophic state index (CTSI) is commonly used for the classification of trophic conditions of surface waters. The study is conducted to assess the trophic status of a tropical lake (Akkulam-Veli lake, Kerala, India) using CTSI based on Secchi disc depth (SD), total phosphorus (TP) and chlorophyll-a. The TSI values based on SD and TP are high (>70), indicating the hypereutrophic state which needs urgent action for the restoration of the fragile ecosystem. The higher TP in both lakes, and the lower value of chlorophyll-a in the Akkulam part, warrant explanation, are discussed here. The influence of other biochemical parameters in both the Akkulam and the Veli part of the lake has been assessed. Correlation analysis is conducted to study the effect of various water quality parameters. The variation in the water quality before and after the opening of sand bar is studied using paired t test. As almost all the lakes in the world are experiencing similar situation of extinction, this study is helpful to have an insight in the hydrochemistry of the lake as well as to identify the worst affected areas of the lakes.
The hydrological regimes and environmental changes in large riverine lakes are known for their complexity and high level of uncertainty. Scientifically uncovering the response mechanisms of water environments under complex hydrological conditions has become a challenging research objective, in the interdisciplinary of environmental science and hydrology. This study delved into the unstable response process between water level and quality of Poyang Lake, the largest freshwater lake as well as one of the most intense hydrological variability water bodies in China. We developed a non-steady state identification approach incorporates Seasonal and Trend decomposition using Loess (STL) and Wavelet Correlation (WTC) methods. The results showed that there were remarkable alterations in the hydrological regime and water quality at both seasonal and long-term scale of Poyang Lake over the past nine years. These alterations were accompanied by significant non-steady state characteristics, reflecting the changes in the response between water level and quality. The employment of the STL-WTC method revealed a significant nonlinear response between the long-term trends of water level and quality, in both the 4-month and 12-month frequency bands. In particular, our findings showed an intriguing shift towards in-phase behavior between water level and quality in the 12-month frequency band, rather than the anti-phase pattern observed previously. This correlation changed more significantly in seasons where the fluctuation pattern of water level varied sharply, such as summer and winter in Poyang Lake. Our study underscored the hydrological conditions and water quality of large lakes connected to rivers do not exhibit a long-term stable unidirectional response state, alterations in hydrological rhythms may induce a transition in the relationship from negative correlation towards nonlinear positive correlation between water level and water quality. Finally, this non-steady state fluctuation of water conditions can further exacerbate long-term and seasonal degradation of water quality.
The environmental factors contributing to the Microcystis aeruginosa bloom (hereafter
referred to as Microcystis bloom) are still debatable as they vary with season and
geographic settings. We examined the environmental factors that triggered Microcystis
bloom outbreak in India’s largest brackish water coastal lagoon, Chilika. The warmer
water temperature (25.31−32.48 ºC), higher dissolved inorganic nitrogen (DIN) loading
(10.15−13.53 μmol L-1), strong P−limitation (N:P ratio 138.47- 246.86), higher water
transparency (46.62−73.38 cm), and low-salinity (5.45−9.15) exerted a strong positive
influence on blooming process. During the bloom outbreak, M. aeruginosa proliferated,
replaced diatoms, and constituted 70−88% of the total phytoplankton population. The
abundances of M. aeruginosa increased from 0.89 × 104 cells L−1 in September to
1.85 × 104 cells L−1 in November and reduced drastically during bloom collapse (6.22
× 103 cells L−1) by the late November of year 2017. The decrease in M. aeruginosa
during bloom collapse was associated with a decline in DIN loading (2.97 μmol L-1)
and N:P ratio (73.95). Sentinel-3 OLCI-based satellite monitoring corroborated the field
observations showing Cyanophyta Index (CI) > 0.01 in September, indicative of intense
bloom and CI < 0.0001 during late November, suggesting bloom collapse. The
presence of M. aeruginosa altered the phytoplankton community composition.
Furthermore, co-occurrence network indicated that bloom resulted in a less stable
community with low diversity, inter-connectedness, and prominence of a negative
association between phytoplankton taxa. Variance partitioning analysis revealed that
TSM (16.63%), salinity (6.99%), DIN (5.21%), and transparency (5.15%) were the most
influential environmental factors controlling the phytoplankton composition. This study
provides new insight into the phytoplankton co-occurrences and combination of
environmental factors triggering the rapid onset of Microcystis bloom and influencing
the phytoplankton composition dynamics of a large coastal lagoon. These findings
would be valuable for future bloom forecast modeling and aid in the management of
the lagoon.
In 2020, nearly 400 elephants died within the Okavango Delta region in Botswana, creating the worst-ever elephant mass die-off event in history. This catastrophic event was widely blamed on toxic cyanobacterial blooms after lab results showed the presence of toxin-forming cyanobacteria in inland waters of the Delta. However, it did not explain why we saw this mass die-off of elephants in 2020 and not in previous years. We conducted a landscape-wide time-series analysis using freely available European Space Agency’s Sentinel-2 and NASA’s Landsat-8 satellite data. We used existing bio-optical models, Normalized Difference Chlorophyll Index and Green Line Height, as proxies for chlorophyll-a and phycocyanin (cyanobacteria) concentrations. We found that 2020 was an exceptional year for cyanobacteria blooms in the Okavango Delta region compared to the past three years (2017–2019). Bloom phenology indicated that the cyanobacteria blooms initiated in September-October 2019, experienced an exponential growth reaching peak in January-February 2020, and eventually senescing in June 2020. This being a notoriously data-scarce region of the world, we did not have any means to perform site-specific validation of the models. Although magnitude and timeline of the blooms coincided with
the timeline of elephant death reports, our study do not confirm it to be the trigger. For the first time, we show the widespread nature of these blooms across the landscape, which may have increased the toxin exposure for elephants. We theorize that 2020 might have been the first year for such a mass die-off event, but it will certainly not be the last because warming trends under changing climate are creating increasingly suitable conditions for these blooms to be pervasive and ubiquitous. Through this preliminary study, we demonstrate the critical need for frequent and comprehensive monitoring of toxic cyanobacterial blooms in the Delta to avoid another such event in the future.
Harmful algal blooms (HABs) can have dire repercussions on aquatic wildlife and human health, and may negatively affect recreational uses, aesthetics, taste, and odor in drinking water. The factors that influence the occurrence and magnitude of harmful algal blooms and toxin production vary in space and time and remain poorly understood. It is within this context that we use machine learning (ML) and two 14-year (2005–2018) data sets on water quality and meteorological conditions of China's lakes and reservoirs to shed light on the magnitude and associated drivers of HAB events. General regression neural network (GRNN) models are developed to predict chlorophyll a concentrations for each lake and reservoir during two study periods (2005–2010 and 2011–2018). The developed models with an acceptable model fit are then analyzed by two indices to determine the areal HAB magnitudes and associated drivers. Our national assessment suggests that HAB magnitudes for China's lakes and reservoirs displayed a decreasing trend from 2006 (1363.3 km²) to 2013 (665.2 km²), and a slightly increasing trend from 2013 to 2018 (775.4 km²). Among the 142 studied lakes and reservoirs, most severe HABs were found in Lakes Taihu, Dianchi and Chaohu with their contribution to the total HAB magnitude varying from 89.2% (2013) to 62.6% (2018). HABs in Lakes Taihu and Chaohu were strongly associated with both total phosphorus and nitrogen concentrations, while our results were inconclusive with respect to the predominant environmental factors shaping the eutrophication phenomena in Lake Dianchi. The present study provides evidence that effective HAB mitigation may require both nitrogen and phosphorus reductions and longer recovery times; especially in view of the current climate-change projections. ML represents a robust strategy to elucidate water quality patterns in lakes, where the available information is sufficient to train the constructed algorithms. Our mapping of HAB magnitudes and associated environmental/meteorological drivers can help managers to delineate the hot-spots at a national scale, and comprehensively design the best management practices for mitigating the eutrophication severity in China's lakes and reservoirs.
This paper studies the influence of the impounding process during flood recession in the TGR on the distribution and rerelease of sediment phosphorus forms in the Xiangxi Bay in 2016. Influenced by the main stream of the Three Gorges Reservoir (TGR) flowing backward during impoundment, the water environmental conditions, sediment grain size and sediment-forming environment of the tributary bays change correspondingly. In this study, it is found that the water temperature (WT), turbidity and oxidation–reduction potential (ORP) of the overlying water in the Xiangxi Bay decrease, while the pH increases after impoundment in the TGR. The backward flow of the main stream containing a large amount of sediments increases the sediment content of the tributary bay, and the difference in sediment particle size between the main stream and tributaries narrows after resedimentation. The phosphorus adsorbed on the sediments increases the total phosphorus (TP) in the sediments of the Xiangxi River to 1.3 times its value before water impoundment. NaOH-P and HCl-P in the Xiangxi River sediments account for 42% and 38% of the TP, respectively, and the contents of the various phosphorus forms are ranked in the following order: NaOH-P > HCl-P > organic phosphorus (OP). After impoundment, HCl-P accounts for 67% of the TP, and the relative contents of the phosphorus forms are ranked as: HCl-P > OP > NaOH-P. Orthophosphate (PO43−-P) in the Xiangxi sediments before and after impoundment acts as a source, and the PO43−-P diffusion flux increases from approximately − 0.0029 to 0.0059 mg (m2 d)−1 before impoundment to 0.0067–0.1071 mg (m2 d)−1 after impoundment, which is mainly due to the increased difference in concentration of PO43−-P [ρ(PO43−-P)] between the sediment interstitial water and overlying water after impoundment. After nutrient recharge of the main stream of the Yangtze River, ρ(PO43−-P) of the overlying water is 3.7 times its value before impoundment, and after the release of NaOH-P in the sediments, ρ(PO43−-P) of the interstitial water is 8.3 times its value before water impoundment. Hence, the risk of nutrient release from the sediments in the Xiangxi Bay increases.
Light and nutrients are essential resources for phytoplankton growth and considered to shape the size structure and other morphometric traits (surface:volume ratio, deviation from spherical shape) of phytoplankton communities. If morphometric traits influence the growth and resource use, shifts by one of the two factors should influence the capability to utilize the other factor. We performed a two-step experiment, where a natural phytoplankton community was first exposed to three different light levels (supposed to be limiting, saturating and slightly inhibiting for the majority of species) and grown until stationary phase. Then, the pre-conditioned communities were split into two nutrient treatments (control and saturating nutrient pulse) and again grown until stationary phase under the medium light intensity. During the experimental light phase, community mean cell-size increased with light, but surface:volume ratio and deviation from spherical shape decreased. Moreover, in response to the following nutrient pulse, the low light pre-conditioned communities showed the highest initial growth rates in response to the nutrient pulse. The high light pre-conditioned communities showed the highest conversion of the nutrient pulse into biomass during the stationary phase. These results demonstrate how the imprint of one environmental factor on trait distribution influences the ability to cope with another. © © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: [email protected]
Eutrophication of inland waters is considered a serious global environmental problem. Satellite remote sensing (RS) has been established as an important source of information to determine the trophic state of inland waters through the retrieval of optically active water quality parameters such as chlorophyll-a (Chl-a). However, the use of RS techniques for assessment of the trophic state of inland waters on a global scale is hindered by the performance of retrieval algorithms over highly dynamic and complex optical properties that characterize many of these systems. In this study, we developed a new RS approach to assess the trophic state of global inland water bodies based on Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and the Forel-Ule index (FUI). First, the FUI was calculated from MODIS data by dividing natural water colour into 21 indices from dark blue to yellowish-brown. Then the relationship between FUI and the trophic state index (TSI) was established based on in-situ measurements and MODIS products. The water-leaving reflectance at 645 nm band was employed to distinguish coloured dissolved organic matter (CDOM)-dominated systems in the FUI-based trophic state assessment. Based on the analysis, the FUI-based trophic state assessment method was developed and applied to assess the trophic states of 2058 large inland water bodies (surface area >25 km2) distributed around the world using MODIS data from the austral and boreal summers of 2012. Our results showed that FUI can be retrieved from MODIS with a considerable accuracy (92.5%, R2 = 0.92) by comparing with concurrent in situ measurements over a wide range of lakes, and the overall accuracy of the FUI-based trophic state assessment method is 80.0% (R2 = 0.75) validated by an independent dataset. Of the global large water bodies considered, oligotrophic large lakes were found to be concentrated in plateau regions in central Asia and southern South America, while eutrophic large lakes were concentrated in central Africa, eastern Asia, and mid-northern and southeast North America.
The increasing eutrophication of Lake Poyang, the largest freshwater Chinese lake, has taken more and more attention in recent years, but the eutrophication of shallow lakes around Lake Poyang are known rather little. An annual limnological investigation was conducted in the year of 2014-2015 in 3 typical shallow lakes, adjacent to the southwest bank of Lake Poyang at the suburb of Nanchang City, Jiangxi Province. Parameters of the water quality and eutrophic level in the three lakes were time-serially monitored to deeply understand the seasonally dynamics and the driving mechanism. Results showed that the variation of CODMn in Lake Qingshan, Lake Yaohu and Lake Junshan ranged from 2.6-4.5 mg/L, 2.1-4.6 mg/L and 1.6-1.9 mg/L, respectively. Only Lake Junshan was still not affected by the organic pollution, and significant differences were found between each other among the three lakes. The contents of total nitrogen (TN) and total phosphorus (TP) in the water column of Lake Qingshan and Lake Yaohu largely exceeded the thresholds for eutrophic regime shifts (TN: 0.20 mg/L, TP: 0.02 mg/L), while the concentration of TP was only in Class IV-below V. The main form of nitrogen in the three lakes was soluble, and the main form of phosphorus in these lake were all particulate, except Lake Junshan. The contents of Chl.a in Lake Qingshan, Lake Yaohu and Lake Junshan were 34.65-184.48 μg/L, 7.66-120.67 μg/L and 2.42-17.41 μg/L, respectively, and the contents were all lowest in winter. Lake Junshanwas significantly different from both Lake Qingshan or Lake Yaohu in the Chl.a contents, but no significant difference in the Chl.a contents between Lake Qingshan and Lake Yaohu. The trophic states of the three lakes has been assessed with a synthesized trophic state index (TLI). It's found that Lake Qingshan was in the highest eutrophic level(from mild to moderate eutrophication), followed by Lake Yaohu(from mesotrophication to moderate eutrophication) and Lake Junshan (from oligotrophication to mesotrophication) during the studying period. Water temperature was found as one of the important environmental factors affecting the seasonal trophic fluatuation of these lakes. The significant positive relationships were calculated between Chl.a and TN or TP in water column of all lakes through Pearson correlation analysis, while Chl. a was tightly positively correlated with TDN and TDP only in Lake Qingshan and Lake Yaohu. Overall, nitrogen was one of the dominant factors affecting the environmental characteristics in these lakes, and phosphorus was the predominant factor affecting two eutrophic lakes. In the process of nutrient control, effective reduction of the nitrogen input should be considered in the eutrophic lakes while lowering the phosphorus discharge, especially, during the period of middle water temperature (15-25℃), and systematical regulation should be conducted in the mesotrophic lake (e.g. Lake Yaohu) through the combination of N reduction and P sources control, in particular, during the period of high water temperature at more than 25℃. It would provide a new way to protect and manage water environment of these shallow lakes around Lake Poyang.
A preliminary phytoplanktonic index of biotic integrity (P-IBI) was developed to evaluate the ecosystem health of Taihu Lake in winter by means of the data that were collected from 29 sites in Taihu Lake and 4 sites in similar lakes or reservoirs in December 2012. The method of the least disturbed condition was used to find the reference sites. Fifty-one metrics were examined stepwise in the distribution analysis, discriminating power analysis, and redundancy analysis to obtain the core metrics. The final P-IBI included the total taxa number, Bacillariophyta taxa number (%), the Simpson diversity index of cells, cell density, Bacillariophyta cell density (%), and Chlorophyta individual density (%). These metrics were transformed into uniform scores using the ratio score method, and a P-IBI value was obtained by summing up the scores. According to the P-IBI assessment, 8 reference sites included 1 healthy site, and the rest were subhealthy; 2 of 25 impaired sites were subhealthy, while 9 were good-to-fair, 12 were fair, and the other 2 sites were poor. East Taihu Lake was best in terms of the health condition in the entire Taihu Lake, while the central region was the worst. The health conditions in other regions (Zhushan Lake, Gong Lake, eastern lakeshore, and western lakeshore) were intermediate, meaning relatively poor conditions. Our results suggest that ammonia nitrogen and total phosphorus are the major factors that correlate significantly with the P-IBI score for Taihu Lake in winter.
As one of the human activities that transform nature, construction of dams and dykes may impose significant effects on lake ecosystems. Due to lacking of comparative data for ecological monitoring, how the changes of phytoplankton community structure respond to altered hydrological connectivity between lakes and other water bodies is still unknown. This work chose Junshan Lake, the typical isolated lake from Poyang Lake floodplain, to investigate the succession in phytoplankton communities responding to altered connectivity. Phytoplankton samples were collected during the wet and dry seasons in Junshan Lake, to analyze the phytoplankton community structure. The results showed that, fifty three genera from six phyta were identified in Junshan Lake, with Chlorophyta (47.2%), Bacillariophyta (22.2%), Cyanophyta (14.8%) and Euglenophyta (9.3%) being the main phyta. The dominant species were Ceratium hirundinella (20.5%), Anabeana spp. (18.5%) and Microcystis spp. (12.9%) during the wet seasons. Cryptomonas ovate (38.4%), Aulacoseira granulata (15.2%) and Microcystis spp. (10.5%) dominated during the whole dry seasons. The total phytoplankton abundance was mainly composed of Cyanophyta (85.4% -87.0%). The total phytoplankton biomass was dominantly made up of Cyanophyta (45.0%), Dinophyta (21.1%), Bacillariophyta (15.6%) and Chlorophyta (11.5%) during the wet seasons. Cryptophyta (38.2%), Bacillariophyta (31.3%) and Cyanophyta (21.1%) were the main contributors of the total phytoplankton biomass during the dry seasons. The phytoplankton community structure changed from Dinophyta-Bacillariophyta type during the wet seasons of 2007-2008 to Cyanophyta- Dinophyta type during the wet seasons of 2012-2013, and changed from Dinophyta- Bacillariophyta type during the dry seasons of 2007-2008 to Cryptophyta- Bacillariophyta- Cyanophyta type during the dry seasons of 2012-2013. The abundance and biomass increased from 2.66 x 10(6) cell L(-1) during 2007-2008 to 6.77 x 10(7) cell x L(-1) during 2012- 2013, and from 0.72 mg x L(-1) during 2007-2008 to 12.30 mg x L(-1) during 2012-2013, respectively. The succession pattern of phytoplankton community in the Junshan Lake showed a decrease in the proportion of oligotrophic species as Chrysophyta and Dinophyta, and an increase in eutrophic species as Cyanophyta and Cryptophyta. Thus, being isolated from Poyang Lake might alter hydrologic factors so that the water exchange time became longer and the water flow became slower which could promote the growth and aggregation of phytoplankton eutrophication indicator species in Junshan Lake.
Dissolved organic matter (DOM) represents the major pool of organic precursors for harmful disinfection byproducts, such as haloacetic acids (HAAs), formed during drinking water chlorination, but much of it remains molecularly uncharacterized. Knowledge of model precursors is thus a prerequisite for understanding the more complex whole water DOM. The utility of HAA formation potential data from model DOM precursors, however, is limited due to the lack of comparability to water samples. In this study, the formation kinetics of dichloroacetic acid (DCAA) and trichloroacetic acid (TCAA), the two predominant HAA species, were delineated upon chlorination of seventeen model DOM precursors and sixty-eight inland lake water samples collected from the Upper Midwest region of the United States. Of particular interest was the finding that the DCAA and TCAA formation rate constants could be grouped into four statistically distinct clusters reflecting the core structural features of model DOM precursors (i.e., non-β-diketone aliphatics, β-diketone aliphatics, non-β-diketone phenolics, and β-diketone phenolics). A comparative approach built upon hierarchical cluster analysis was developed to gain further insight into the reactivity patterns of HAA precursors in inland lake waters as defined by the relative proximity to four model precursor clusters. This work highlights the potential for implementing an integrated kinetic-clustering approach to constrain the chlorine reactivity of DOM in source waters.
Exploratory data analysis on physical, chemical and biological data from sediments and water in Lake Champlain reveals a strong relationship between cyanobacteria, sediment anoxia, and the ratio of dissolved nitrogen to soluble reactive phosphorus. Physical, chemical and biological parameters of lake sediment and water were measured between 2007 and 2009. Cluster analysis using a self-organizing artificial neural network, expert opinion and discriminant analysis separated the dataset into no-bloom and bloom groups. Clustering was based on similarities in water and sediment chemistry and non-cyanobacteria phytoplankton abundance. Our analysis focused on the contribution of individual parameters to discriminate between no-bloom and bloom groupings. Application to a second, more spatially diverse dataset, revealed similar no-bloom and bloom discrimination; yet a few samples possess all the physico-chemical characteristics of a bloom without the high cyanobacteria cell counts suggesting that while specific environmental conditions can support a bloom, another environmental trigger may be required to initiate the bloom. Results highlight the conditions coincident with cyanobacteria blooms in Missisquoi Bay of Lake Champlain, and indicate additional data are needed to identify possible ecological contributors to bloom initiation.
Eight field campaigns in the eutrophic, shallow, Lake Taihu in the summers from 2005 to 2007, and a phytoplankton degradation experiment of 33 days, were carried out to determine the contribution of phytoplankton degradation to CDOM. Significant and positive correlations were found between the CDOM absorption coefficient at 355 nm [a(CDOM)(355)], normalized fluorescence emission (QSU) at 450 nm from excitation at 355 nm [F(n)(355)], and the chlorophyll a (Chla) concentration for all eight field campaigns, which indicates that the decomposition and degradation of phytoplankton is an important source of CDOM. In the degradation experiment, the CDOM absorption coefficient increased as phytoplankton broke down during the first 12 days, showing the production of CDOM from phytoplankton. After 12 days, a(CDOM)(355) had increased from the initial value 0.41+/-0.03 m(-1) to 1.37+/-0.03 m(-1) (a 234% increase), and the Chla concentration decreased from the initial value of 349.1+/-11.2 microg/L to 30.4+/-13.2 microg/L (a 91.3% decrease). The mean daily production rate of CDOM from phytoplankton was 0.08 m(-1) for a(CDOM)(355). Parallel Factor Analysis (PARAFAC) was used to assess CDOM composition from EEM spectra, and four components were identified: a terrestrial-like humic component, two marine-like humic components, and a protein-like component. The rapid increase in marine-like humic fluorophores (C3 and C4) during the degradation experiment suggests that in situ production of CDOM plays an important role in the dynamics of CDOM. The field campaigns and experimental data in the present study show that phytoplankton can be one of the important CDOM producers in eutrophic shallow lakes.
TP, TN, chlorophyll a, potassium permanganate index and secchi depth (SD) and phytoplankton were determined in 15 tributaries of Three Gorges Reservoir. Trophic states were assessed and output fluxes of TN, TP and potassium permanganate index were calculated. The results showed that value of TN, TP, potassium permanganate index, SD and Chla were different in each tributary. SD, TN, TP, potassium permanganate index and Chla value are 0.45 - 1.5 m, 0.65 - 4.27 mg x L(-1), 0.011 - 0.432 mg x L(-1), 0.657 - 5.37 mg x L(-1) and 0.57 - 12.2 mg x m(-3) respectively. The water body of tributaries is polluted at various levels. The concentration of TN is abundant. The rate of TN and TP showed that a part of tributaries eutrophication are limited by TP. Utilizing the method of integrated nutrition state index, it assessed the trophic states degree of tributaries. All of the studied tributaries, 3 tributaries are eutropher, 10 tributaries are mesotropher and 2 tributaries are oligotropher respectively. 129 species of phytoplankton are identified, which belongs to 7 division and 67 genera. The dominant species are Bacillariophyceae, Chiorophyceae and Cyanophyta. The type of phytoplankton community is Bacillariophyceae-Chlorophyceaetype, Bacillariophyceae-Cyanophytatype and Cyanophyta-Chlorophyceaetype. The species and numbers of phytoplankton are various in different tributaries. The nutritive peculiarity belongs to responding type of phytoplankton. The nutrient fluxes load was calculated by discharge and concentration of each tributary. The nutrient fluxes load of TN, TP and potassium permanganate index are 3.14 x 10(5) t, 1.76 x 10(4) t and 2.74 x 10(5) t respectively in one year. After the Three Gorges Dam was completed in 2009, eutrophication trend of tributaries estuaries would be more serious with the decreasing of flow velocity.
Estimation about nitrogen and phosphorus of the Junshan Lake Agricultural Non-point source pollution into the lake
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Effects of Aquaculture on Water Environment and the Control Countermeasures
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Present situation and comprehensive exploitation of the resources of large and medium-sized lakes in Jiangxi Province
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Changes of total nitrogen concentration in Taihu Lake during 1987–2016
- Fan
The characteristics and cause analysis of oxygen consumption substances for the waterbody in the main channel of the Middle Route of South-to-North Water Diversion Project
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Analysis of Comprehensive Treatment Technology Scheme for LakeWater Environment——Taking the Water Treatment Project of a Lake in Northern China as an Example
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Mechanism and control strategy of lake eutrophication in the middle and lower reaches of Yangtze River
- Qing
Water quality change characteristics and eutrophication assessment of Poyang lake
- Wen
Lake eutrophication and its ecosystem response
- Qing
Jiangxi rivers and lakes encompassing
- Jiangxi Water Resources Department
Trophic State Evaluation in Water of Yao Lake
- Jiang
Community structure and the water quality during different hydrological periods in Poyang lake
- Yang
Analysis of spatial-temporal variations of total nitrogen and total phosphorus concentration and their influencing factors in Dongting Lake in the past two decades
- Zhang
Eutrophication assessment and estimation of water environmental capacity in lake Xiannv of Jiangxi
- Zhang
Discussion and case study overall evaluation method of lake eutrophication
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The Water Quality Evaluation of Taibo Lake Based on Fuzzy Comprehensive Evaluation Method
- Zhang