Modeling the interaction of light and nutrients as factors driving lake eutrophication

Long-term prediction of algal chlorophyll based on empirical models and the machine learning approach in relation to trophic variation in Juam Reservoir, Korea

This study analyzed spatiotemporal variation and long-term trends in water quality indicators and trophic state conditions in an Asian temperate reservoir, Juam Reservoir (JR), and developed models that forecast algal chlorophyll (CHL-a) over a period of 30 years, 1993-2022. The analysis revealed that there were longitudinal gradients in water quality indicators along the reservoir, with notable influences from tributaries and seasonal variations in nutrient regimes and suspended solids. The empirical model showed phosphorus was found to be the key determinant of algal biomass, while suspended solids played a significant role in regulating water transparency. The trophic state indices indicated varying levels of trophic status, ranging from mesotrophic to eutrophic. Eutrophic states were particularly observed in zones after the summer monsoons, indicating a heightened risk of algal blooms, which were more prevalent in flood years. The analysis of trophic state index deviation suggested that phosphorus availability strongly influences the reservoir trophic status, with several episodes of non-algal turbidity at each site during Mon. Increases in non-algal turbidity were more prevalent during the monsoon in flood years. This study also highlighted overall long-term trends in certain water quality parameters, albeit with indications of shifting pollution sources towards non-biodegradable organic matter. According to the machine learning tests, a random forest (RF) model strongly predicted CHL-a (R2 = 0.72, p < 0.01), except for algal biomass peaks (>60 μg/L), compared to all other models. Overall, our research suggests that CHL-a and trophic variation are primarily regulated by the monsoon intensity and predicted well by the machine learning RF model.

Potential geographical distribution of harmful algal blooms caused by the toxic dinoflagellate Karenia mikimotoi in the China Sea

The fish-killing dinoflagellate Karenia mikimotoi frequently blooms in China and poses a threat to food safety and human health. To better understand harmful algal blooms (HABs) caused by K. mikimotoi and predict the risk of HABs under climate change, the combined effect of nitrate and norfloxacin (NOR) on the growth of K. mikimotoi was tested. A growth model was used to test the effects of nutrients and pollutants on the carrying capacity of the unicellular algae. The carrying capacity increased with increasing concentrations of nitrate and NOR, reaching a maximum at 62.2 μmol L-1 of nitrate and 9.03 mg L-1 of NOR. The calculated carrying capacity of K. mikimotoi in the China Sea showed a declining trend from nearshore to offshore, with a value >30 × 106 cells L-1 in the estuary of the Changjiang River and Hangzhou Bay. The HAB index proposed in this study as a measurement of HAB risk was constructed using the carrying capacity and relative abundance from the MaxEnt (maximum entropy) model. The index showed that HABs caused by K. mikimotoi consecutively occurred in Zhejiang and Fujian coastal waters and predicted that they will continue until 2100, regardless of the greenhouse gas emission scenario. The center of the integrated area moved northward, with a range of 120-900 km. The HAB index integrates the characteristics of the carrying capacity and suitability of habitats, and expresses the information contained in the intensive and extensive variables that affect HAB occurrence. This index is a promising predictor of HAB risk in coastal waters.

Relative impact of environmental variables on the lake trophic state highlights the complexity of eutrophication controls

For the effective management of lakes apart from defining and monitoring their current state it is crucial to identify environmental variables that are mostly responsible for the nutrient input. We used interpretative machine learning to investigate the environmental parameters that influence the lake's trophic state and recognize their patterns. We analysed the influence of the 25 environmental variables on the commonly used trophic state indicators values: total phosphorus (TP), Chlorophyll-a (Chl-a) and Secchi depth (SD) of 60 lakes located in the Central European Lowlands. We attempted to delineate the lakes into groups due to the influence of common prevailing environment variable/variables on the water trophic state reflected by each indicator. The results indicated that the relative impact of environmental variables on the lake trophic state has an individual hierarchy unique for each indicator. The most important are variables related to catchment impact on the lake, Ohle ratio (L. catchment area/L. area) for TP and Schindler ratio (L. area + L. catchment area)/L. volume for Chl-a and SD. There are also few variables strongly influential only for small sub-groups of lakes that stand out: lake maximum depth, catchment slope steepness expressed by the height standard deviation. The methods used in the study enabled the assessment of the character of the influence of the environmental variables on the indicator value and revealed that most essential variables (Ohle ratio for TP and Schindler ratio for Chl-a and SD) have bimodal distribution with a clear threshold value. These findings contribute to a better understanding of the drivers shaping the lake trophic status and have implication for planning effective management strategies.

A critical review of operational strategies for the management of harmful algal blooms (HABs) in inland reservoirs

Occurrences of freshwater harmful algal blooms (HABs) are increasing on a global scale, largely in part due to increased nutrient input and changing climate patterns. While reservoir management strategies that can influence phytoplankton are known, there is no published guideline or protocol for the management of harmful algal blooms. There is a need to establish what factors are the predominant drivers of blooms, and how common reservoir management strategies specifically influence each factor. The following literature review seeks to establish the benefits and drawbacks of operational management strategies that currently exist. The main focus is altering hydrodynamic conditions (hypolimnetic withdrawals, surface flushing, pulsed inflow, artificial mixing), in order to induce environmental changes within the reservoir itself. Since excess nutrients are one of the biggest contributors to worsening bloom conditions, internal nutrient dynamics and reduction are also discussed. Additionally, we review the predominant seasonal factors (stratification, light, temperature, and wind) that affect likelihood of bloom occurrence and duration. The ultimate objective of this review is to increase understanding of the relationships between HAB drivers and reservoir operations in order to inform the development of data, modeling, and management strategies for the prevention and mitigation of blooms.

Spatiotemporal pattern and biodegradation process of amino acids in the large shallow eutrophic lake Taihu, China

Organic matter (OM) and nutrient inputs generated by human activities promote the development of eutrophication. Amino acids (AAs) are an integral part of OM, and studying their patterns will provide new insights into organic matter dynamics in lakes. Four seasonal field campaigns in eutrophic Lake Taihu and a 14-day phytoplankton degradation experiment were carried out to determine the variability and bioavailability of amino acids. The quality and quantity of AAs varied among different seasons and lake types. The concentrations of particulate (PAA) and dissolved (DAA) AA were 14.67 ± 13.25 μM (carbon- and nitrogen-normalized PAA yields: PAA-C%, 23.8 ± 13.5%; PAA-N%, 22.8 ± 2.1%) and 2.95 ± 1.05 μM (carbon- and nitrogen-normalized DAA yields: DAA-C%, 3.7 ± 1.1%; DAA-N%, 12.6 ± 11.2%) in Lake Taihu, respectively. PAA and DAA showed high mean values in the algal-dominated northern area in summer. Glutamic acid (Glu), alanine (Ala), aspartic acid (Asp) and glycine (Gly) contributed to nearly 50% of PAA, while Gly, accounting for 17-24%, was the main component of DAA. During a 14-day phytoplankton degradation period, 98% of Chl a, 63% of POC and 92% of PAA were removed in the dark treatment, and a more obvious downward trend was recorded than in the light treatment. Principal component analysis of the indices of PAA indicated that Glu, arginine (Arg) and histidine (His) were dominant on day 0, while Gly and lysine (Lys) were dominant on day 14. There were notable serine + threonine (Ser + Thr [mol%]) and aspartic acid/glycine ratio (Asp/Gly [mol%]) end-member divisions among different organic matter sources. DAA had higher Ser + Thr [mol%] and lower Asp/Gly [mol%] values than PAA. The amino acid degradation index (DI) of PAA and DAA was 0.97 ± 0.28 and - 1.04 ± 0.43, respectively. The fresh DAA from the algae degradation incubation also had DI values similar to those of field DAA in the northern algae-dominated lake region. Amino acid parameters (AA-C%, DI values, Ser + Thr [mol%] and Asp/Gly [mol%]) were calculated to indicate the source, freshness and bioavailability of organic matter in eutrophic shallow Lake Taihu.

Evolution of urban black and odorous water: The characteristics of microbial community and driving-factors

Urban black blooms that are primarily caused by organic carbon are deleterious environmental problems. However, detailed studies on the microbial characteristics that form urban black blooms are lacking. In this study, we observed the composition, diversity, and function of bacterial community in the overlying water and sediments during the occurrence and remediation of urban black blooms using high-throughput 16S rRNA gene amplicon sequencing analysis. First, we found that pivotal consortia in the overlying water increased significantly during the formation of black blooms, including the genera Acidovorax, Brevundimonas, Pusillimonas, and Burkholderiales involved in the degradation of refractory organics, as well as the genera Desulfovibrio, Dechloromonas, and Rhizobium related to the production of black and odorous substances. An RDA analysis revealed that chemical oxygen demand, dissolved oxygen, and oxidation reduction potential were related to the changes in microbial community composition. Furthermore, aeration was found to accelerate the removal of ammonia nitrogen and enhance the function of microbial community by stimulating the growth of order Planktomycetes during the remediation of black blooms, but aeration substantially damaged the microbial diversity and richness. Therefore, the health of the aquatic ecosystem should be comprehensively considered when aeration is applied to restore polluted waterbodies. Notably, we observed a large number of pathogenic bacteria in urban black blooms, which emphasizes the importance of treating domestic sewage so that it is harmless. Together, these findings provide new insights and a basis to prevent and manage urban black blooms.

A Three-Dimensional Coupled Hydrodynamic-Ecological Modeling to Assess the Planktonic Biomass in a Subalpine Lake

In this study, a coupled three-dimensional hydrodynamic-ecological model was developed to comprehensively understand the interaction between the hydrodynamics and ecological status of a lake. The coupled model was utilized to explore the hydrodynamics, water quality, and ecological status in an ecologically rich subalpine lake (i.e., Tsuei-Feng Lake (TFL), located in north-central Taiwan). The measured data of water depth, water temperature, water quality, and planktonic biomass were gathered to validate the coupled model. The simulated results with a three-dimensional hydrodynamic and water quality-ecological model reasonably reproduced the variations in observed water depth, water temperature, water quality, and phytoplankton and zooplankton biomass. Sensitivity analysis was implemented to determine the most influential parameter affecting the planktonic biomass. The results of sensitivity analysis indicated that the predation rate on phytoplankton (PRP) significantly affects the phytoplankton biomass, while the basal metabolism rate of zooplankton (BMZ) importantly affects the zooplankton biomass. Furthermore, inflow discharge was the most important environmental factor dominating the phytoplankton and zooplankton biomass of TFL. This implies that the runoff in the catchment area caused by rainfall and the heavy rainfall induced by climate change may affect the planktonic biomass of the lake.

Eutrophication model driven by light and nutrients condition change in sluice-controlled river reaches

River eutrophication has become a challenging environmental problem worldwide because of the strong interference of anthropogenic activities and hydraulic structures. The driving mechanism of algae growth in sluice-controlled river reaches (SCRRs) is more complicated than that of natural rivers, because the operation mode of the sluices is an important influencing factor which changes the light and nutrient conditions of the water body. The main purpose of this study was to assess algal growth in SCRRs under external conditions and sluice regulation. In this study, a eutrophication model for SCRRs was developed based on the mechanism of river hydrodynamics and algae growth kinetics, considering the variation in underwater light intensity and nutrient condition. By choosing the light intensity, phosphorus concentration and sluice gate opening size as the influencing factors, 16 different combination conditions were proposed by orthogonal experimental design, and eutrophication of water bodies in the SCRRs was simulated using a eutrophication model. In the scenario design, four gate opening sizes were set, and the light intensity and nutrients were enlarged or reduced based on the original monitoring data. The results showed that both light intensity and nutrient concentration can promote the algal growth within a suitable range, and increasing the gate opening size can inhibit algal growth.

The use of pesticides in Polish agriculture after integrated pest management (IPM) implementation

The aim of the conducted study was to characterize the attitudes and practices of Polish farmers in the area of performing chemical plant protection treatments. A particular attention was paid to identifying the relationship between the direction of changes in the volume of chemical plant protection product consumption and selected attributes of farms. The main time range of the analyses covered the period of 2013-2017. Statistical data and results of representative surveys carried out on a sample of 1101 farms in Poland were used in the research process. Due to the large number of variants of the analysed variables, a multiple correspondence analysis was used, which made it possible to determine the correlation between the examined features (direction of changes in pesticide use relative to the farm area, economic size of the farm and location of the farm). Statistical analysis showed the existence of strong relationships between the physical (1) and economic (2) size of farms and the direction of changes in pesticide consumption ((1) φ2 = 0.0907; (2) φ2 = 0.1141)). According to empirical studies, the reduction of pesticide consumption took place mainly on the smallest farms. The implementation of the integrated plant protection directive has not resulted in significant changes in the form of reduced pesticide use in large-scale field crops. This raises the need to modify the strategy and model of crop protection in large-scale field crops in Poland.

Selection of water source for water transfer based on algal growth potential to prevent algal blooms

Water transfer is becoming a popular method for solving the problems of water quality deterioration and water level drawdown in lakes. However, the principle of choosing water sources for water transfer projects has mainly been based on the effects on water quality, which neglects the influence in the variation of phytoplankton community and the risk of algal blooms. In this study, algal growth potential (AGP) test was applied to predict changes in the phytoplankton community caused by water transfer projects. The feasibility of proposed water transfer sources (Baqing River and Jinsha River) was assessed through the changes in both water quality and phytoplankton community in Chenghai Lake, Southwest China. The results showed that the concentration of total nitrogen (TN) and total phosphorus (TP) in Chenghai Lake could be decreased to 0.52 mg/L and 0.02 mg/L respectively with the simulated water transfer source of Jinsha River. The algal cell density could be reduced by 60%, and the phytoplankton community would become relatively stable with the Jinsha River water transfer project, and the dominant species of Anabaena cylindrica evolved into Anabaenopsis arnoldii due to the species competition. However, the risk of algal blooms would be increased after the Baqing River water transfer project even with the improved water quality. Algae gained faster proliferation with the same dominant species in water transfer source. Therefore, water transfer projects should be assessed from not only the variation of water quality but also the risk of algal blooms.

The role of morphological changes in algae adaptation to nutrient stress at the single-cell level

Individual cell heterogeneity within a population can be critical to its peculiar function and fate. Conventional algal cell-based assays mainly analyze the average responses from a population of algal cells. Therefore, the mechanisms through which changes in population characteristics are driven by the behavior of single algal cells are still not well understood. Algal cells may modulate their physiology and metabolism by changing their morphology in response to environmental stress. In this study, an algal single-cell culture and analysis system was developed to investigate the potential role of morphological changes by algal cells during adaptation to nutrient stress based on a microwell array chip. The surface-to-volume ratio of Microcystis aeruginosa (M. aeruginosa) and the volume of Scenedesmus obliquus (S. obliquus) significantly increased with increasing culture time under nutrient stress. The eccentricity of M. aeruginosa and S. obliquus gradually increased and decreased, respectively, with increasing culture time, indicating that the morphology of M. aeruginosa and S. obliquus became increasingly irregular and regular, respectively, under nutrient stress. There were significant correlations between the morphological characteristics and physiological characteristics of M. aeruginosa and S. obliquus under nutrient stress. In M. aeruginosa, an increased surface-to-volume ratio facilitated a high specific fluorescence intensity, specific Raman intensity, and maximum electron transport rate. In S. obliquus, increased cell volume enhanced nutrient absorption, which facilitated a higher specific growth rate. M. aeruginosa and S. obliquus adopted different adaptation strategies in response to nutrient stress based on morphological changes. These findings facilitate the development of management strategies for controlling harmful cyanobacterial blooms.

Nitrous oxide emission during denitrifying phosphorus removal process: A review on the mechanisms and influencing factors

Excessive emissions of nitrogen (N) and phosphorus (P) pollutants are leading to increased eutrophication of water bodies. Biological N and P removal processes have become a research priority in the field of sewage treatment with the aim of improving sewage discharge standards in countries worldwide. Denitrifying P removal processes are more efficient for solving problems related to carbon source competition, sludge age conflict, and high aeration energy consumption compared to traditional biological N and P removal processes, but they are easy to produce nitrous oxide (N₂O) in the process of sewage treatment. N₂O is a greenhouse gas with a global warming potential approximately 190-270 times that of CO₂ and 4-21 times that of CH₄, which was produced and released into the environmental in denitrifying P removal systems under conditions of a low C/N ratio, high dissolved oxygen, and low activity of denitrifying phosphorus accumulating organisms (DPAOs). This paper reviews the emission characteristics and influencing factors of N₂O during denitrifying P removal processes and proposes appropriate strategies for controlling the emission of N₂O. This work serves as a basis for the development of new sewage treatment processes and the reduction of greenhouse gas emissions in future wastewater treatment plants.

Exploring nutrient and light limitation of algal production in a shallow turbid reservoir

Harmful algal blooms are increasingly recognized as a threat to the integrity of freshwater reservoirs, which serve as water supplies, wildlife habitats, and recreational attractions. While algal growth and accumulation is controlled by many environmental factors, the relative importance of these factors is unclear, particularly for turbid eutrophic systems. Here we develop and compare two models that test the relative importance of vertical mixing, light, and nutrients for explaining chlorophyll-a variability in shallow (2-3 m) embayments of a eutrophic reservoir, Jordan Lake, North Carolina. One is a multiple linear regression (statistical) model and the other is a process-based (mechanistic) model. Both models are calibrated using a 15-year data record of chlorophyll-a concentration (2003-2018) for the seasonal period of cyanobacteria dominance (June-October). The mechanistic model includes a novel representation of vertical mixing and is calibrated in a Bayesian framework, which allows for data-driven inference of important process rates. Both models show that chlorophyll-a concentration is much more responsive to nutrient variability than mixing, light, or temperature. While both models explain approximately 60% of the variability in chlorophyll-a, the mechanistic model is more robust in cross-validation and provides a more comprehensive assessment of algal drivers. Overall, these models indicate that nutrient reductions, rather than changes in mixing or background turbidity, are critical to controlling cyanobacteria in a shallow eutrophic freshwater system.

Coupling Flow, Heat, and Reactive Transport Modeling to Reproduce In Situ Redox Potential Evolution: Application to an Infiltration Pond

Redox potential (Eh) measurements are widely used as indicators of the dominant reduction-oxidation reactions occurring underground. Yet, Eh data are mostly used in qualitative terms, as actual values cannot be used to distinguish uniquely the dominant redox processes at a sampling point and should therefore be combined with a detailed geochemical characterization of water samples. In this work, we have intensively characterized the redox potential of the first meter of soil in an infiltration pond recharged with river water using a set of in situ sensors measuring every 12 min during a 1 year period. This large amount of data combined with hydrogeochemical campaigns allowed developing a reactive transport model capable of reproducing the redox potential in space and time together with the site hydrochemistry. Our results showed that redox processes were mainly driven by the amount of sedimentary organic matter in the system as well as by seasonal variation of temperature. As a subsidiary result, our work emphasizes the need to use a fully coupled model of flow, heat transport, solute transport, and the geochemical reaction network to fully reproduce the Eh observations in the topsoil.

Evaluation of the efficiency of three different mineral adsorbents in the removal of pollutants in samples from a tropical spring in Northeastern Brazil

Human water sources are increasingly threatened around the world due to various sources of pollution such as agriculture and industry. The objective of this study was to evaluate three new adsorbents as pollutant remedies for subsequent application in the Joanes River located in the State of Bahia in Brazil. The specific pollutants were nitrogen, phosphorus (P), aluminum (Al), iron (Fe), cyanobacteria, and saxitoxins. Initially, studies (pH 7 and 22°C) were performed with samples contaminated in the laboratory with phosphorus (P), nitrate ( NO 3 - ), and ammonia (NH₃ ), to select the most efficient adsorbent and to determine the equilibrium time. Pumice bituminous coal was found to have the best efficiencies (≥70%) at 360 min (equilibration time). The experimental data did not fit the Langmuir and Freundlich model. The bituminous coal with pumice stone was then applied to water samples from a designated capture point of the Joanes springs, a river system that is responsible for supplying the city of Salvador and the metropolitan region, located on the northern coast of Bahia. The removal efficiency analyses were performed on a DR6000 UV/VIS SPECTROPHOTOMETER, using the methodology defined in the Standard Methods 2017, after which this adsorbent was subjected to scanning electron microscopy. As a result, removal efficiencies (≥98%) were obtained for all contaminants (nitrogen, phosphorus (P), aluminum (Al), iron (Fe), cyanobacteria, and saxitoxins) as well as a highly heterogeneous layer pointed by SEM images, further demonstrating the adsorbent potential as a efficient alternative in environmental control after additional studies. PRACTITIONER POINTS: Pumice bituminous coal has proven to be an excellent adsorbent for a wide range of pollutants such as phosphorus, nitrogen, ammonia, toxins, cyanobacteria, and metals. The adsorbent promoted a high reduction in phosphorus concentrations (3.40 mg/L to 0.01 mg/L), about 98% and 81% for cyanobacteria (12,850 Cel/ml to 2,560 Cel/ml). The adsorbent promoted a high reduction in concentrations of 98% saxitoxins (4.32 µg/L to 0.2 µg/L).

A light-limited growth model considering the nutrient effect for improved understanding and prevention of macroalgae bloom

A useful growth process model for Ulva prolifera with light limitation considering the nutrient effect was proposed to better understand the development of macroalgae bloom. The interrelationship between light and nutrient limitation was demonstrated to obtain the mechanism. As a case study, thresholds of light and nutrients for different stages of Ulva prolifera growth were estimated using the proposed model. Limits of light intensity, nitrate, and phosphate concentration on the initial growth were found to be 40.0 W m^-2, 6.5 μmol L^-1, and 0.27 μmol L^-1, respectively. The minimal light intensity for initial growth was found to increase monotonously with decrease in the nutrient concentration. It was also observed that the minimal light intensity for growth increases as the density of Ulva prolifera increases and the nutrient concentration decreases. Similarly, the minimal nutrient concentration for initial growth increases monotonously with decrease in the light intensity. In addition, the minimal nutrient concentration for growth increases with increase in the density of Ulva prolifera and decrease in the light intensity. It was demonstrated that the phosphate limitation on the initial growth of Ulva prolifera seedling can occur in most coastal waters of the southern Yellow Sea and a tendency of approaching the phosphate limitation on the growth of the floating thalli of Ulva prolifera exists. Evidence was provided to support the argument that the macroalgae thalli from aquaculture rafts, rather than that from seedlings or spores, can contribute to the original biomass of the floating green Ulva prolifera in the southern Yellow Sea. The model presented in this study can provide new insights into the interrelationship between the light and nutrient limitation, as well as into the growth mechanism of floating seaweeds. It can also provide a more accurate prediction of seaweed growth in light- and nutrient-limited environments.