Ecotoxicological assessment of cyclic peptides produced by a Planktothrix rubescens bloom: Impact on aquatic model organisms.

Cyanobacterial blooms, a natural phenomenon in freshwater ecosystems, have increased in frequency and severity due to climate change and eutrophication. Some cyanobacteria are able to produce harmful substances called cyanotoxins. These metabolites possess different chemical structures and action mechanisms representing a serious concern for human health and the environment. The most studied cyanotoxins belong to the group of microcystins which are potent hepatotoxins. Anabaenopeptins are another class of cyclic peptides produced by certain species of cyanobacteria, including Planktothrix spp. Despite limited knowledge regarding individual effects of anabaenopeptins on freshwater organisms, reports have identified in vivo toxicity in representatives of freshwater zooplankton by cyanobacterial extracts or mixtures containing anabaenopeptins. This study focused on the isolation and toxicity evaluation of the cyanotoxins produced in the 2022 Planktothrix rubescens bloom in Averno lake, Italy. The three main cyclic peptides have been isolated and identified by nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry (MS) and optical analyses as anabaenopeptins A and B, and oscillamide Y. Ecotoxicological tests on the aquatic model organisms Daphnia magna (crustacean), Raphidocelis subcapitata (algae), and Aliivibrio fischeri (bacterium) revealed that anabaenopeptins A and B do not generate significant toxicity at environmentally relevant concentrations, being also found a stimulatory effect on R. subcapitata in the case of anabaenopeptin A. By contrast, oscillamide Y displayed toxicity. Ecological implications based on ECOSAR predictions align with experimental data. Moreover, long-term exposure bioassays on different green unicellular algae species showed that R. subcapitata was not significantly affected, while Scenedesmus obliquus and Chlorella vulgaris exhibited altered growth patterns. These results, together with the already-known background in literature, highlight the complexity of interactions between organisms and the tested compounds, which may be influenced by species-specific sensitivities, physiological differences, and modes of action, possibly affected by parameters like lipophilicity.

Assessment of in-situ monitoring and tracking the vertical migration of cyanobacterial blooms using LISST-HAB.

Cyanobacterial harmful algal blooms (cyanoHABs) are becoming increasingly common in aquatic ecosystems worldwide. However, their heterogeneous distributions make it difficult to accurately estimate the total algae biomass and forecast the occurrence of surface cyanoHABs by using traditional monitoring methods. Although various optical instruments and remote sensing methods have been employed to monitor the dynamics of cyanoHABs at the water surface (i.e., bloom area, chlorophyll a), there is no effective in-situ methodology to monitor the dynamic change of cell density and integrated biovolume of algae throughout the water column. In this study, we propose a quantitative protocol for simultaneously measurements of multiple indicators (i.e., biovolume concentration, size distribution, cell density, and column-integrated biovolume) of cyanoHABs in water bodies by using the laser in-situ scattering and transmissometry (LISST) instrument. The accuracy of measurements of the biovolume and colony size of algae was evaluated and exceeded 95% when the water bloom was dominated by cyanobacteria. Furthermore, the cell density of cyanobacteria was well estimated based on total biovolume and mean cell volume measured by the instrument. Therefore, this methodology has the potential to be used for broader applications, not only to monitor the spatial and temporal distribution of algal biovolume concentration but also monitor the vertical distribution of cell density, biomass and their relationship with size distribution patterns. This provides new technical means for the monitoring and analysis of algae migration and early warning of the formation of cyanoHABs in lakes and reservoirs.

Functional trait-based phytoplankton biomass and assemblage analyses in the pre-growing season for comprehensive algal bloom risk assessment.

Algal bloom (AB) risk assessment is critical for maintaining ecosystem health and human sustainability. Previous AB risk assessments have focused on the potential occurrence of ABs and related factors in the growing season, whereas their hazards, especially in the pre-growing season, have attracted less attention. Here, we performed a comprehensive AB risk assessment, including water trophic levels, phytoplankton biomass, functional trait-based assemblages, and related environmental factors, in the pre-growing season in Dongting Lake, China. Although mesotrophic water and low phytoplankton biomass suggested low AB potential, toxic taxa, which constituted 13.28% of the phytoplankton biomass, indicated non-negligible AB hazards. NH4+ and water temperature were key factors affecting phytoplankton motility and toxicity. Our study establishes a new paradigm for quantitative AB risk assessment, including both potential AB occurrence and hazards. We emphasize the importance of phytoplankton functional traits for early AB warning and NH4+ reduction for AB control in the pre-growing season.

Assessment of ecological status of Uppanar and Vellar estuaries through multivariate pollution indices.

Multivariate pollution degree indices were utilized to evaluate the environmental condition of the Uppanar and Vellar estuaries. The Trophic Index (TRIX) indicates a state of "moderate eutrophication" with a value of 4.92, while the Trophic State Index (TSI) ranged from 40.3 to 57.2, categorizing the trophic states from "oligotrophic" to "eutrophic". The Comprehensive Pollution Index (CPI) showed a range of 0.13 to 0.94, classifying pollution levels from "unpolluted" to "slightly polluted". The study revealed that the Uppanar and Vellar estuaries underwent seasonal variations, transitioning from an oligotrophic state during the post-monsoon and summer periods to a eutrophic state in the pre-monsoon and monsoon seasons. The application of multivariate statistical tools allowed the identification of pollution indicator species to assess the estuarine systems. The insights gained from this study can be valuable for assessing other ecosystems facing similar anthropogenic activities, providing a basis for informed management and conservation strategies.

An innovative method based on Gaussian cloud distribution and sample information richness for eutrophication assessment of Yangtze's lakes and reservoirs under uncertainty.

The precise assessment of a water body's eutrophication status is essential for making informed decisions in water environment management. However, conventional approaches frequently fail to consider the randomness, fuzziness, and inherent hidden information of water quality indicators. These would result in an unreliable assessment. An enhanced method was proposed for the eutrophication assessment under uncertainty in this study. The multi-dimension gaussian cloud distribution was introduced to capture the randomness and fuzziness. The Shannon entropy based on various sample size and trophic levels was proposed to maximize valuable information hidden in the datasets. Twenty-seven significant lakes and reservoirs located in the Yangtze River Basin were selected to demonstrate the proposed method. The sensitivity and consistency were used to evaluate the accuracy of the proposed method. Results indicate that the proposed method has the capability to effectively assess the eutrophication status of lakes and reservoirs under uncertainty and that it has a better sensitivity since it can identify more than 33-50% trophic levels compared to the traditional methods. Further scenario experiments analysis revealed that the sample information richness, i.e., sample size and the number of trophic levels is of great significance to the accuracy/robustness of the method. Moreover, a sample size of 60 can offer the most favorable balance between accuracy/robustness and the monitoring expenses. These findings are crucial to optimizing the eutrophication assessment.

Seasonal impact of constructed wetlands on nitrogen and phosphorus in sediments of flood control lakes with pollution assessment.

The primary drivers of eutrophication in lakes following the reduction of external nutrient inputs are the release of N and P from sediments. Constructed wetlands play a pivotal role in ameliorating N, P, and other biogenic element levels. However, the presence of large vegetation in these wetlands also substantially contributes to nutrient accumulation in sediments, a phenomenon influenced by seasonal variations. In this study, a typical constructed wetland was selected as the research site. The research aimed to analyze the forms of N and P in sediments during both summer and winter. Simultaneously, a comprehensive pollution assessment and analysis were conducted within the study area. The findings indicate that elevated summer temperatures, together with the presence of wetland vegetation, promote the release of N through the nitrification process. Additionally, seasonal variations exert a significant impact on the distribution of P storage. Furthermore, the role of constructed wetlands in the absorption and release of N and P is primarily controlled by the influence of organic matter on nitrate-nitrogen, nitrite-nitrogen, and available phosphorus, and is also subject to seasonal fluctuations. In summary, under the comprehensive influence of constructed wetlands, vegetation types, and seasons, sediments within the lake generally exhibit a state of mild or moderate pollution. Therefore, targeted measures should be adopted to optimally adjust vegetation types, and human intervention is necessary, involving timely sediment harvesting during the summer to reduce N and P loads, and enhancing sediment adsorption and retention capacity for N and P during the winter.

Assessment of two non-invasive techniques for measuring turbulent benthic fluxes in a shallow lake.

Benthic fluxes refer to the exchange rates of nutrients and other compounds between the water column and the sediment bed in aquatic ecosystems. Their quantification contributes to our understanding of aquatic ecosystem functioning. Near-bed hydrodynamics plays an important role at the sediment-water interface, especially in shallow lakes, but it is poorly considered by traditional measuring techniques of flux quantification, such as sediment incubations. Thus, alternative sampling techniques are needed to characterize key benthic fluxes under in-situ hydrodynamic conditions. This study aimed to evaluate the performance of two promising methods: relaxed eddy accumulation (REA) and mass transfer coefficient (MTC). We applied them in a hyper-eutrophic shallow lake to measure the fluxes of ammonium, phosphate, iron, and manganese ions. For the first time, REA revealed hourly nutrient flux variations, indicating a strong lake biogeochemical dynamics at short time-scales. Daily average fluxes are of similar orders of magnitude for REA and MTC for ammonium (24 and 42 mmol m2 d-1), manganese (1.0 and 0.8), and iron (0.8 and 0.7) ions. They are one order of magnitude higher than fluxes estimated from sediment incubations, due to the difficulty in reproducing in-situ oxygen and hydrodynamic conditions in the laboratory. Although the accuracy of both techniques needs to be improved, the results revealed their potential: REA follows the short-term biogeochemical dynamics of sediments, while MTC could be widely used for lake monitoring because of its simpler implementation.

A life cycle assessment of early-stage enzyme manufacturing simulations from sustainable feedstocks.

Enzyme-catalyzed reactions have relatively small environmental footprints. However, enzyme manufacturing significantly impacts the environment through dependence on traditional feedstocks. With the objective of determining the environmental impacts of enzyme production, the sustainability potential of six cradle-to-gate enzyme manufacturing systems focusing on glucose, sea lettuce, acetate, straw, and phototrophic growth, was thoroughly evaluated. Human and ecosystem toxicity categories dominated the overall impacts. Sea lettuce, straw, or phototrophic growth reduces fermentation-based emissions by 51.0, 63.7, and 79.7%, respectively. Substituting glucose-rich media demonstrated great potential to reduce marine eutrophication, land use, and ozone depletion. Replacing organic nitrogen sources with inorganic ones could further lower these impacts. Location-specific differences in electricity result in a 14% and a 27% reduction in the carbon footprint for operation in Denmark compared to the US and China. Low-impact feedstocks can be competitive if they manage to achieve substrate utilization rates and productivity levels of conventional enzyme production processes.

Large reductions in nutrient losses needed to avoid future coastal eutrophication across Europe.

Rapid technological development in agriculture and fast urbanization have increased nutrient losses in Europe. High nutrient export to seas causes coastal eutrophication and harmful algal blooms. This study aims to assess the river exports of nitrogen (N) and phosphorus (P), and identify required reductions to avoid coastal eutrophication in Europe under global change. We modelled nutrient export by 594 rivers in 2050 for a baseline scenario using the new MARINA-Nutrients model for Europe. Nutrient export to European seas is expected to increase by 13-28% under global change. Manure and fertilizers together contribute to river export of N by 35% in 2050. Sewage systems are responsible for 70% of future P export by rivers. By 2050, the top ten polluted rivers for N and P host 42% of the European population. Avoiding future coastal eutrophication requires over 47% less N and up to 77% less P exports by these polluted rivers.

Ecological risk assessment under the PSR framework and its application to shallow urban lakes.

Shallow urban lakes are naturally vulnerable to ecosystem degradation. Rapid urbanization in recent decades has led to a variety of aquatic problems such as eutrophication, algal blooms, and biodiversity loss, increasing the risk to lake-wide ecological sustainability. Instead of a simple binary assessment of ecological risk, holistic evaluation frameworks that consider multiple stressors and receptors can provide a more comprehensive assessment of overall ecological risk. In this study, we analyzed a combined dataset of government statistics, remote sensing images, and 1 year of field measurements to develop an index system for urban lake ecological risk assessment based on the pressure-state-response (PSR) framework. We used the developed ecological safety index (ESI) system to evaluate the ecological risk for three urban lakes in Jiangsu Province, China: Lake Yangcheng-LYC, Lake Changdang-LCD, and Lake Tashan-LTS. LYC and LTS were classified as "mostly safe" and "generally recognized as safe," respectively, while LCD was assessed as having "potential ecological risk." Our data suggest that socioeconomic pressure and aquatic health are the two main factors affecting the ecological risk in both LYC and LCD. The ecological risk of LTS could be improved more effectively if regional management plans are well implemented. Our study highlights the pressure of external wastewater loading, low forest-grassland coverage, and lake shoreline damage on the three selected urban lakes. The findings of this study can inform watershed management for lake ecosystem restoration and environmental sustainability.

Prediction of chlorophyll a and risk assessment of water blooms in Poyang Lake based on a machine learning method.

Four different methods were used to identify the important factors influencing chlorophyll-a (Chl-a) content: correlation analysis (CC-NMI), principal component analysis (PCA), decision tree (DT), and random forest recursive feature elimination (RF-RFE). Considering the relationship between Chl-a and its active and passive factors, we established machine learning combination models based on multiple linear regression (MLR), multi-layer perceptron (MLP), and support vector regression (SVR) to predict Chl-a content for Poyang Lake, China. Then, the predictive effects of different combination models were compared and evaluated from multiple perspectives. Considering the actual needs for eutrophication prevention and control, the concept of risk probability was then introduced to assess the risk degree of risk associated with water blooms in Poyang Lake. The results indicated that the mean R2 for the Chl-a predictions using the MLR, MLP, and SVR models was 0.21, 0.61, and 0.75, respectively. Consequently, the SVR model demonstrated higher precision and more accurate predictions. Compared to other methods, integrating the SVR model with the RF-RFE method significantly improved the prediction accuracy, with the R2 increasing to 0.94. For Poyang Lake, 8.8% of random samples indicated a low risk level with a water bloom probability of 21.1%-36.5%; one sample indicated a medium risk level with a risk probability of 45.5%. The research results offer valuable insights for predicting eutrophication and conducting risk assessments for Poyang Lake. They also provide reliable scientific support for making decisions about eutrophication in lakes and reservoirs. Therefore, the results hold significant theoretical importance, practical value, and potential for widespread application.

Assessment of toxicity and antimicrobial performance of polymeric inorganic coagulant and evaluation for eutrophication reduction.

In this study, the efficacy of the promising iron-based polymeric inorganic coagulant (POFC) was assessed for the reduction of eutrophication effect (freshwater toxicity) and the microbial loads from wastewater. Toxicity assessment for POFC was conducted on mice and skin cell lines. The results confirm the lower toxicity level of POFC. The POFC showed excellent antibacterial efficacy against Gram-positive and Gram-negative bacteria. Moreover, it demonstrated a remarkable effectiveness against black fungus such as Aspergillus niger and Rhizopus oryzae. Additionally, POFC showed antiviral effectiveness against the highly pathogenic H5N1 influenza virus as well as Middle East respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). POFC-based treatment gives excellent removal percentages for phosphate, and phosphorus at doses below 60 ppm with a low produced sludge volume that leads to 84% decrease in the rate of eutrophication and freshwater toxicity. At a POFC concentration of 60 ppm, remarkable reduction rates for total coliforms, fecal coliforms, and E. coli were achieved. After POFC-based coagulation, the produced sludge retains a lower bacterial density due to the antibacterial activity of POFC. Furthermore, it revealed that the observed removal efficiencies for fungi and yeasts in the produced sludge reached 85% at a POFC dose of 60 ppm. Overall, our research indicates that POFC has potential for application in pre-treatment of wastewater and serves as an antimicrobial agent.

Dynamics of algal blooms in typical low-latitude plateau lakes: Spatiotemporal patterns and driving factors.

The alpine lakes distributed on the plateau are crucial for the hydrological, and biogeochemical cycle, and also serve as a guarantee for regional economic development and human survival. However, under the influence of human interference and climate fluctuations, lakes are facing problems of eutrophication and subsequent algal blooms (ABs) with acceleration, and the development and driving factors of this phenomenon need to be considered as a whole. In this study, ten lakes located on the Yunnan-Guizhou Plateau were selected as the study area to analyze the spatiotemporal distribution of ABs and possible controlling forces. The FAI (Floating Algae Index) derived from multiple MODIS products and water quality data under high-frequency monitoring were selected as the data sources for characterizing ABs. Three nutrient parameters and five meteorological variables were used to explore the driving factors affecting ABs. Various methods of trend detection and correlation analysis have been applied. The main results are as follows: (1) Dianchi Lake (in lake area) and Xingyun Lake (in area proportion) are the two lakes with the most serious ABs in the historical period; (2) ABs are mainly distributed on the shoreline and northern edge of lakes, and tend to stay away from the lake center during high-temperature periods of the day; (3) Six lakes show a decreasing trend in ABs, especially after 2018, while other lakes (including Fuxian, Chenghai, Yangzong, and Erhai) are increasing, not only in peak value but also in duration; (4) Lakes with severe ABs are all P-restricted lakes, the minimum temperature is the most sensitive meteorological factor, while the impact of precipitation against ABs has a time lag; (5) Establishing a warning system of temperature and nutrient concentration is critical in ABs adaptive strategy. This study is expected to provide scientific references for regional water management and the restoration of the eutrophic aquatic ecosystem.

Making waves: The sensitivity of lakes to brownification and issues of concern in ecological status assessment.

Brownification or increasing water colour is a common problem in aquatic ecosystems. It affects both physico-chemical properties and biotic communities of the impacted waters. A common view is that lakes having low background water colour are most sensitive to brownification. In this article, we show that although low-colour and high-colour lakes respond differently to brownification, the effects on biotic communities can be strong irrespective of water colour. For phytoplankton production, the effect of brownification can be positive at low colour and negative at high colour, the relative effect being strongest at high colour. For fish foraging, the disturbance per increasing unit of colour may also be highest at high-colour conditions. Additionally, the presently used classification systems mostly describe the effects of eutrophication and do not account for the effects of brownification. Studies on the whole colour range of lakes are needed and indicators used in the ecological status assessment of lakes must be developed to reveal the effects of brownification. Indicators distinguishing the effects of brownification from those of eutrophication are especially needed.

Accelerated eutrophication alters fish and aquatic health: a quantitative assessment by using integrative multimarker, hydrochemical, and GIS modelling method in an urban lake.

The ramifications of anthropogenic activities on the environment and the welfare of aquatic life in lakes worldwide are becoming increasingly alarming. There is a lack of research in the Indian Himalayas on fish biomarker responses to stressful aquatic conditions and the use of environmetric modelling in GIS. Our research evaluates the environmental health of urban lakes in multiple basins using multi-biomarker endpoints (13 features) in Schizothorax niger and hydrochemical characterization (9 features) of water. The study covers 31 grids, each at a distance of 1 km2. This study demonstrated a statistically significant (P = 0.001) increase in white blood cells (WBC), mean cell size (MCH), helminth infection, and health assessment index score (HAIS) score in fish from a highly eutrophic cluster or basin compared to a reference cluster, which is indicative of environmental stress in fish. Based on hydrochemical similarities, the lake water datasets were divided into three categories using hierarchical cluster analysis (HCA). In the PCA analysis, the first three principal components were responsible for 78.1% of the data's variance. The first principal component (PC1) accounted for 57.4% of the variance and had a strong positive loading from ammonia, total phosphate, pH, nitrates, and total alkalinity for water quality parameters. Additionally, PC1 had a favourable loading from WBC, helminth infection (%), and the health assessment index score (HAIS) for biological endpoints. These findings are in alignment with the results of the multivariate analysis. The trophic state index (TSI) showed a significant (P < 0.05) increase in Cluster 1, which includes the peripheral areas of Hazratbal and Gagribal side (> 70), compared to the reference cluster. The multiple regression model indicates that ammonia, phosphate, and nitrate significantly impact the general health of fish (R2 > 0.7). A novel methodology for monitoring water quality fluctuations across different basins and clusters is presented in this study. By integrating fish health biomarkers and GIS technology, we have developed a comprehensive approach to evaluate the overall well-being of aquatic habitat. This technique may prove beneficial in the management of urban lentic water bodies in the Kashmir Himalayas and other comparable water systems around the globe, while also supporting sustainable practices.

An Assessment of Potential Threats to Human Health from Algae Blooms in the Indian River Lagoon (USA) 2018-2021: Unique Patterns of Cytotoxicity Associated with Toxins.

The Indian River Lagoon (IRL), a 156-mile-long estuary located on the eastern coast of Florida, experiences phytoplankton bloom events due to increased seasonal temperatures coupled with anthropogenic impacts. This study aimed to gather data on the toxicity to human cells and to identify secondary metabolites found in water samples collected in the IRL. Water samples from 20 sites of the IRL were collected during the wet and dry seasons over a three-year period. A panel of cell lines was used to test cytotoxicity. Hemagglutination, hemolysis, and inhibition of protein phosphatase 2A (PP2A) were also measured. Cytotoxic blooms were seen both in the south (Microcystis) and the north (Pyrodinium) of the IRL. Each toxin induced a consistent pattern of cytotoxicity in the panel of human cell lines assayed. During blooms, cytotoxicity due to a single type of toxin is obvious from this pattern. In the absence of blooms, the cytotoxicity seen reflected either a mixture of toxins or it was caused by an unidentified toxin. These observations suggest that other toxins with the potential to be harmful to human health may be present in the IRL. Moreover, the presence of toxins in the IRL is not always associated with blooms of known toxin-producing organisms.

Detection and mapping of water and chlorophyll-a spread using Sentinel-2 satellite imagery for water quality assessment of inland water bodies.

Water quality monitoring of reservoirs is currently a significant challenge in the tropical regions of the world due to limited monitoring stations and hydrological data. Remote sensing techniques have proven to be a powerful tool for continuous real-time monitoring and assessment of tropical reservoirs water quality. Although many studies have detected chlorophyll-a (Chl-a) concentrations as a proxy to represent nutrient contamination, using Sentinel 2 for eutrophic or hypereutrophic inland water bodies, mainly reservoirs, minimal efforts have been made for oligotrophic and mesotrophic reservoirs. The present study aimed to develop a modeling framework to map and estimate spatio-temporal variability of Chl-a levels and associated water spread using the Modified Normalized Difference Water Index (MNDWI) and Maximum Chlorophyll Index (MCI). Moreover, the impact of land use/land cover type of the contributing watershed in the oligo-mesotrophic reservoir, Bhadra (tropical reservoir), for 2018 and 2019 using Sentinel 2 satellite data was analyzed. The results show that the water spread area was higher in the post-monsoon months and lower in the summer months. This was further validated by the correlation with reservoir storage, which showed a strong relationship (R2 = 0.97, 2018; R2 = 0.93, 2019). The estimated Chl-a spread was higher in the winter season, because the reservoir catchment was dominated by deciduous forest, producing a large amount of leaf litter in tropical regions, which leads to an increase in the level of Chl-a. It was found that Chl-a spread in the reservoir, specifically at the inlet sources and near agricultural land practices (western parts of the Bhadra reservoir). Based on the findings of this study, the MCI spectral index derived from Sentinel 2 data can be used to accurately map the spread of Chl-a in diverse water bodies, thereby offering a robust scientific basis for effective reservoir management.

Eutrophication assessment and environmental management perspectives of Tóbari: an arid subtropical coastal lagoon of the Gulf of California.

Coastal lagoons are vulnerable to eutrophication processes. In this study, we evaluate the eutrophication process in the restricted, arid subtropical Tóbari coastal lagoon, located in the eastern coast of the Gulf of California, where the main source of nutrient inputs and other pollutants is agricultural wastewater from the Yaqui Valley. The Assessment of Estuarine Trophic Status (ASSETS) model and the Trophic State Index (TRIX) were used to evaluate eutrophication. Overall, ASSETS showed that the Tóbari lagoon has a moderate eutrophication process, with seasonal symptoms of hypoxia, increased phytoplankton biomass, dominance of macroalgae (indicative of nutrient enrichment), and blooms development of potentially harmful algae species. The TRIX showed that the lagoon is mesotrophic most of the year. Challenges of environmental management detected correspond to reducing the input of nutrients and others contaminants from anthropic sources: agriculture, shrimp farming, livestock, and urban zones.

Analysis of future nitrogen and phosphorus loading in watershed and the risk of lake blooms under the influence of complex factors: Implications for management.

For the management of eutrophic lakes, watershed nitrogen and phosphorus control is oriented to future water quality. Assessing future nutrient dynamics and the risk of lake eutrophication is necessary. However, current assessments often lack integrated consideration of socioeconomic and climatic factors, which reduces the reference value of the results. In this study, a typical large shallow lake Chaohu, which is highly influenced by human activities, was selected as the study area, and the current and future total nitrogen (TN) and total phosphorus (TP) loading in the basin were analysed using the improved MARINA model, and the risk of water bloom were assessed. The results showed that socioeconomic factors alone varied future TN and TP loading by -24% to 32% and -40% to 34%, respectively, under different development patterns. After considering the effect of increased precipitation, the changes of TN and TP loading became -10% to 163% and -29% to 108%, respectively. The effect on loading reduction under the sustainable development pattern was weakened (58% and 28% for TN and TP loading, respectively) and the increase in loading under the brutal development pattern was significantly amplified (409% and 215% for TN and TP loading, respectively). The adoption of active environmental policies remained an effective way of loading control. However, the risk of water bloom in local lake areas might persist due to factors such as urbanization. Timely and comprehensive assessments can provide managers with more information to identify key factors that contribute to the risk of water blooms and to develop diverse water quality improvement measures. The insights from our study are applicable to other watersheds around the world with similar socio-economic background and climatic conditions.

Bacteriological and eutrophication risk assessment of an Argentinian temperate shallow urban lagoon.

The urban lagoons receive strong anthropic pressures and the tensions often coexist between the "urban" and the "natural," and this consequently generates pollution and risks to the environment and human health. Our main objective was to study the water quality and to assess the bacteriological and eutrophication risks in the temperate shallow urban lagoon of the Parque Unzué (Gualeguaychú, Argentina), and to predict these risks in climate change scenarios considering the temperature and the rains as indicators. This urban shallow lagoon is in a recreative multiuse park (Gualeguaychú city), in the floodplain of the Gualeguaychú river in the Center-East of Argentina (Neotropical region). Twenty-seven sampling in 3 sampling points (n = 81) were carried out during 2015-2019, and physicochemical and bacteriological parameters were measured. Phosphorus, organic matter, chlorophyll-a (Chl-a), and total coliforms (TC) frequently had a moderate and very high contamination factor (CF), and the pollution load index (PLI) indicated contamination with a frequency of 74.1 %. Moreover, the index (WQI) indicated poor (66.7 %) and good (33.3 %) water quality. Bacteriological and eutrophication predictive risk models showed an increase of the TC and the Chl-a concentration generating a current and future high risk of contamination of the lagoon under climate change scenarios that could generate ecosystemic function losses in the short-term.