Metabolic activity of Planktothrix rubescens and its consequences on oxygen dynamics in laboratory experiment: A stable isotope study.

Fluctuations in dissolved oxygen (DO) contents in natural waters can become intense during cyanobacteria blooms. In a reconnaissance study, we investigated DO concentrations and stable isotope dynamics during a laboratory experiment with the cyanobacterium Planktothrix rubescens in order to obtain insights into primary production under specific conditions. This observation was extended to sub-daily timescales with alternating light and dark phases. Dissolved oxygen concentrations and its isotopes (δ18ODO) ranged from 0.02 to 0.06 mmol · L-1 and from +9.6‰ to +23.4‰. The δ18ODO proved to be more sensitive than concentration measurements in response to metabolic variation and registered earlier shifts to dominance by respiration. Oxygen (O2) contents in the headspace and its isotopes (δ18OO2) ranged from 2.62 to 3.20 mmol · L-1 and from +9.8‰ to +21.9‰. Headspace samples showed less fluctuations in concentration and isotope trends because aquatic processes were hardly able to alter signals once the gas had reached the headspace. Headspace δ18OO2 values were corrected for gas-water equilibration and were determined to be higher than the mean δ18OH2O of -8.7‰. This finding suggests that counteracting respiration was important even during the highest photosynthetic activity. Additionally, headspace analyses led to the definition of a fractionation factor for respiration (αR) of this cyanobacterium with a value of 0.980. This value confirms the one commonly used for cyanobacteria. Our findings may become important for the management of water bodies where decreases in DO are caused by cyanobacteria.

Synergistic Effects of Warming and Internal Nutrient Loading Interfere with the Long-Term Stability of Lake Restoration and Induce Sudden Re-eutrophication.

Phosphorus (P) precipitation is among the most effective treatments to mitigate lake eutrophication. However, after a period of high effectiveness, studies have shown possible re-eutrophication and the return of harmful algal blooms. While such abrupt ecological changes were attributed to the internal P loading, the role of lake warming and its potential synergistic effects with internal loading, thus far, has been understudied. Here, in a eutrophic lake in central Germany, we quantified the driving mechanisms of the abrupt re-eutrophication and cyanobacterial blooms in 2016 (30 years after the first P precipitation). A process-based lake ecosystem model (GOTM-WET) was established using a high-frequency monitoring data set covering contrasting trophic states. Model analyses suggested that the internal P release accounted for 68% of the cyanobacterial biomass proliferation, while lake warming contributed to 32%, including direct effects via promoting growth (18%) and synergistic effects via intensifying internal P loading (14%). The model further showed that the synergy was attributed to prolonged lake hypolimnion warming and oxygen depletion. Our study unravels the substantial role of lake warming in promoting cyanobacterial blooms in re-eutrophicated lakes. The warming effects on cyanobacteria via promoting internal loading need more attention in lake management, particularly for urban lakes.

Storm impacts on phytoplankton community dynamics in lakes.

In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short-term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well-developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short- and long-term. We summarize the current understanding of storm-induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.

Improved Understanding of Dissolved Organic Matter Processing in Freshwater Using Complementary Experimental and Machine Learning Approaches.

Dissolved organic matter plays an important role in aquatic ecosystems and poses a major problem for drinking water production. However, our understanding of DOM reactivity in natural systems is hampered by its complex molecular composition. Here, we used Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and data from two independent studies to disentangle DOM reactivity based on photochemical and microbial-induced transformations. Robust correlations of FT-ICR-MS peak intensities with chlorophyll a and solar irradiation were used to define 9 reactivity classes for 1277 common molecular formulas. Germany's largest drinking water reservoir was sampled for 1 year, and DOM processing in stratified surface waters could be attributed to photochemical transformations during summer months. Microbial DOM alterations could be distinguished based on correlation coefficients with chlorophyll a and often shared molecular features (elemental ratios and mass) with photoreactive compounds. In particular, many photoproducts and some microbial products were identified as potential precursors of disinfection byproducts. Molecular DOM features were used to further predict molecular reactivity for the remaining compounds in the data set based on a random forest model. Our method offers an expandable classification approach to integrate the reactivity of DOM from specific environments and link it to molecular properties and chemistry.

Impacts of Varying Dam Outflow Elevations on Water Temperature, Dissolved Oxygen, and Nutrient Distributions in a Large Prairie Reservoir.

Dam operations are known to have significant impacts on reservoir hydrodynamics and solute transport processes. The Gardiner Dam, one of the structures that forms the Lake Diefenbaker reservoir located in the Canadian Prairies, is managed for hydropower generation and agricultural irrigation and is known to have widely altering temperature regimes and nutrient circulations. This study applies the hydrodynamic and nutrient CE-QUAL-W2 model to explore how various withdrawal depths (5, 15, 25, 35, 45, and 55 m) influence the concentrations and distribution of nutrients, temperature, and dissolved oxygen (DO) within the Lake Diefenbaker reservoir. As expected, the highest dissolved nutrient (phosphate, P O 4 3 - - P and nitrate, N O 3 - - N ) concentrations were associated with hypoxic depth horizons in both studied years. During summer high flow period spillway operations impact the distribution of nutrients, water temperatures, and DO as increased epilimnion flow velocities route the incoming water through the surface of the reservoir and reduce mixing and surface warming. This reduces reservoir concentrations but can lead to increased outflow nitrogen (N) and phosphorus (P) concentrations. Lower withdrawal elevations pull warmer surface water deeper within the reservoir and decrease reservoir DO during summer stratification. During fall turnover low outflow elevations increase water column mixing and draws warmer water deeper, leading to slightly higher temperatures and nutrient concentrations than shallow withdrawal elevations. The 15 m depth (540 m above sea level) outflow generally provided the best compromise for overall reservoir and outflow nutrient reduction.

Sensors in the Stream: The High-Frequency Wave of the Present.

New scientific understanding is catalyzed by novel technologies that enhance measurement precision, resolution or type, and that provide new tools to test and develop theory. Over the last 50 years, technology has transformed the hydrologic sciences by enabling direct measurements of watershed fluxes (evapotranspiration, streamflow) at time scales and spatial extents aligned with variation in physical drivers. High frequency water quality measurements, increasingly obtained by in situ water quality sensors, are extending that transformation. Widely available sensors for some physical (temperature) and chemical (conductivity, dissolved oxygen) attributes have become integral to aquatic science, and emerging sensors for nutrients, dissolved CO2, turbidity, algal pigments, and dissolved organic matter are now enabling observations of watersheds and streams at time scales commensurate with their fundamental hydrological, energetic, elemental, and biological drivers. Here we synthesize insights from emerging technologies across a suite of applications, and envision future advances, enabled by sensors, in our ability to understand, predict, and restore watershed and stream systems.

Automatic High Frequency Monitoring for Improved Lake and Reservoir Management.

Recent technological developments have increased the number of variables being monitored in lakes and reservoirs using automatic high frequency monitoring (AHFM). However, design of AHFM systems and posterior data handling and interpretation are currently being developed on a site-by-site and issue-by-issue basis with minimal standardization of protocols or knowledge sharing. As a result, many deployments become short-lived or underutilized, and many new scientific developments that are potentially useful for water management and environmental legislation remain underexplored. This Critical Review bridges scientific uses of AHFM with their applications by providing an overview of the current AHFM capabilities, together with examples of successful applications. We review the use of AHFM for maximizing the provision of ecosystem services supplied by lakes and reservoirs (consumptive and non consumptive uses, food production, and recreation), and for reporting lake status in the EU Water Framework Directive. We also highlight critical issues to enhance the application of AHFM, and suggest the establishment of appropriate networks to facilitate knowledge sharing and technological transfer between potential users. Finally, we give advice on how modern sensor technology can successfully be applied on a larger scale to the management of lakes and reservoirs and maximize the ecosystem services they provide.

Temperatures and hypolimnetic oxygen in German lakes: Observations, future trends and adaptation potential.

We investigated trends in temperature, stratification, and hypolimnetic oxygen concentration of German lakes under climate change using observational data and hydrodynamic modelling. Observations from 46 lakes revealed that annually averaged surface temperatures increased by + 0.5 °C between 1990 and 2020 while bottom temperatures remained almost constant. Modelling of 12 lakes predicted further increases in surface temperatures by 0.3 °C/decade until the year 2099 in the most pessimistic emission scenario RCP 8.5 (RCP 4.5: + 0.18 °C/decade; RCP 2.6: + 0.04 °C/decade). Again, bottom temperatures increased much less while summer stratification extended by up to 38 days. Using a simplified oxygen model, we showed that hypolimnetic oxygen concentrations decreased by 0.7-1.9 mg L-1 in response to the extended stratification period. However, model runs assuming lower productivity (e. g. through nutrient reduction) resulted in increased oxygen concentrations even in the most pessimistic emission scenario. Our results suggest that the negative effects of climate change on the oxygen budget of lakes can be efficiently mitigated by nutrient control.

Cascading climate effects in deep reservoirs: Full assessment of physical and biogeochemical dynamics under ensemble climate projections and ways towards adaptation.

We coupled twenty-first century climate projections with a well-established water quality model to depict future ecological changes of Rappbode Reservoir, Germany. Our results document a chain of climate-driven effects propagating through the aquatic ecosystem and interfering with drinking water supply: intense climate warming (RCP8.5 scenario) will firstly trigger a strong increase in water temperatures, in turn leading to metalimnetic hypoxia, accelerating sediment nutrient release and finally boosting blooms of the cyanobacterium Planktothrix rubescens. Such adverse water quality developments will be suppressed under RCP2.6 and 6.0 indicating that mitigation of climate change is improving water security. Our results also suggested surface withdrawal can be an effective adaptation strategy to make the reservoir ecosystem more resilient to climate warming. The identified consequences from climate warming and adaptation strategies are relevant to many deep waters in the temperate zone, and the conclusion should provide important guidances for stakeholders to confront potential climate changes.

Sudden eutrophication of an aluminum sulphate treated lake due to abrupt increase of internal phosphorus loading after three decades of mesotrophy.

Aluminum salts are widely used to immobilize phosphorus (P) in lakes suffering from internal loading. However, longevity of treatments varies among lakes; some lakes eutrophy faster than others. We conducted biogeochemical investigations of sediments of a closed artificial Lake Barleber, Germany that was successfully remediated with aluminum sulfate in 1986. The lake became mesotrophic for almost 30 years; a rather rapid re-eutrophication took place in 2016 leading to massive cyanobacterial blooms. We quantified internal loading from sediment and analyzed two environmental factors that might have contributed to the sudden shift in trophic state. Increase in lake P concentration started in 2016, reaching 0.3 mg L-1, and remained elevated into the spring of 2018. Reducible P fraction in the sediment was 37 - 58% of total P, indicating a high potential for mobilization of benthic P during anoxia. Estimated P release from sediments for 2017 was approximately 600 kg for the whole lake. This is consistent with sediment incubation results; higher temperature (20°C) and anoxia contributed to release of P (27.9 ± 7.1 mg m-2 d-1, 0.94 ± 0.23 mmol m-2 d-1) to the lake, triggering re-eutrophication. Loss of aluminum P adsorption capacity together with anoxia and high water temperatures (organic matter mineralization) are major drivers of re-eutrophication. Accordingly, treated lakes at some time require a repeated aluminum treatment for sustaining acceptable water quality and we recommend regular sediment monitoring in treated lakes. This is crucial given the effects of climate warming on duration of stratification in lakes which may result in the need for treatment of many lakes.

Data evaluation strategy for identification of key molecular formulas in dissolved organic matter as proxies for biogeochemical reactivity based on abundance differences from ultrahigh resolution mass spectrometry.

The molecular composition of dissolved organic matter (DOM) is of relevance for global carbon cycling and important for drinking water processing also. The detection of variation of DOM composition as function of time and space from a methodological viewpoint is essential to observe DOM processing and was addressed so far. High resolution concerning DOM quality was achieved with Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS). However almost none of the existing FTICR-MS data sets were evaluated addressing the fate of single mass features / molecular formulas (MFs) abundance during experiments. In contrast to former studies we analyze the function of MF abundance of time and space for such MFs which are present in all samples and which were formerly claimed as recalcitrant in not all but a great number of studies. For the first time the reactivity of MFs was directly compared by their abundance differences using a simple equation, the relative intensity difference (δRI). Search strategies to find out the maximum δRI values are introduced. The corresponding MFs will be regarded as key MFs (KEY-MFs). In order to test this new approach data from a recent photo degradation experiment were combined with monitoring surveys conducted in two drinking water reservoirs. The δRI values varied over one order of magnitude (more than five-fold). MFs like C9H12O6 and C10H14O6 revealed high biogeochemical reactivity as photo products. Some of the KEY-MFs were identical with MFs identified as disinfection byproducts precursors in recent studies. Other KEY-MFs were oxygen-rich and relatively unsaturated (poly-phenol-like) and hence relevant to flocculation procedures.

Impacts of salinity and fish-exuded kairomone on the survival and macromolecular profile of Daphnia pulex.

Global warming is already causing salinization of freshwater ecosystems located in semi-arid regions, including Turkey. Daphnids, which are important grazers on phytoplankton and a major food source for fish and invertebrates, are sensitive to not only changes in salinity levels, but also presence of predators. In this study, the interactive effect of salinity toxicity (abiotic factor) with predation pressure mimicked by the fish-exuded kairomone (biotic factor) and the effect of salt acclimation on daphnids were investigated. Impacts of these stressors on daphnid survival, life history and molecular profile were observed. The presence of the kairomone antagonistically alters the effect of salinity, as observed from the 24- and 48-h LC(50) values and survival results. Molecular findings provided solid evidence to this antagonism at even lower salt concentrations, for which antagonism was not evident with organismal data. Fish predation counterbalances the negative effect of salinity in terms of reserve energy density. Therefore, it is important to investigate multiple stressor effects in ecotoxicological bioassays complemented with molecular techniques. The single effect of increasing salinity resulted in increased mortality, decreased fecundity, and slower somatic growth in Daphnia, despite their acclimation to salinity. This insignificance of acclimation indicates that Daphnia do not have any physiological mechanisms to buffer the adverse effects of salinity, making it a very crucial factor. Salinity-induced reduction in population growth rate of freshwater keystone species Daphnia-despite acclimation-indicates that global warming-induced salinity may cascade through the food web and lead to dramatic environmental consequences in the structure of lake ecosystems.

Novel evaluations of sources and sinks of dissolved oxygen via stable isotopes in lentic water bodies.

Dissolved oxygen (DO) dynamics of a temperate drinking water reservoir in the Harz Mountains (Germany) were investigated over a time period of 18 months. Via depth profiles in a fortnightly sampling resolution we were able to trace DO and temperature dynamics including the formation and breakdown of a Metalimnetic Oxygen Minimum (MOM) by means of DO concentration, saturation patterns and stable isotope ratios of dissolved oxygen (expressed as δ18ODO). Over the evaluation period, 19.4 % of the samples collected had δ18ODO values compatible with atmospheric equilibration (+24.6 ‰ ± 0.4 ‰). With values smaller and larger than this threshold, the remaining δ18ODO values showed that 40.8 % of our samples were dominated by photosynthesis and 39.8 % by respiration. From December to April the reservoir was mixed and DO consumption by respiration exceeded production via photosynthesis. During stratification period, quantification of respiration/photosynthesis rates (R/P) confirmed the epilimnion as a photosynthetic (i.e. net-autotrophic) environment while the hypolimnion was heterotrophic and dominated by respiration at various degrees. Samples of the MOM zone showed the highest R/P ratios and had among the most positive δ18ODO signals caused by respiration. This study showed that combinations of DO concentrations and their isotope ratios are promising to quantify critical zones of respiration and photosynthesis in aquatic environments.

Reservoir water quality deterioration due to deforestation emphasizes the indirect effects of global change.

Deforestation is currently a widespread phenomenon and a growing environmental concern in the era of rapid climate change. In temperate regions, it is challenging to quantify the impacts of deforestation on the catchment dynamics and downstream aquatic ecosystems such as reservoirs and disentangle these from direct climate change impacts, let alone project future changes to inform management. Here, we tackled this issue by investigating a unique catchment-reservoir system with two reservoirs in distinct trophic states (meso­ and eutrophic), both of which drain into the largest drinking water reservoir in Germany. Due to the prolonged droughts in 2015-2018, the catchment of the mesotrophic reservoir lost an unprecedented area of forest (exponential increase since 2015 and ca. 17.1% loss in 2020 alone). We coupled catchment nutrient exports (HYPE) and reservoir ecosystem dynamics (GOTM-WET) models using a process-based modeling approach. The coupled model was validated with datasets spanning periods of rapid deforestation, which makes our future projections highly robust. Results show that in a short-term time scale (by 2035), increasing nutrient flux from the catchment due to vast deforestation (80% loss) can turn the mesotrophic reservoir into a eutrophic state as its counterpart. Our results emphasize the more prominent impacts of deforestation than the direct impact of climate warming in impairment of water quality and ecological services to downstream aquatic ecosystems. Therefore, we propose to evaluate the impact of climate change on temperate reservoirs by incorporating a time scale-dependent context, highlighting the indirect impact of deforestation in the short-term scale. In the long-term scale (e.g. to 2100), a guiding hypothesis for future research may be that indirect effects (e.g., as mediated by catchment dynamics) are as important as the direct effects of climate warming on aquatic ecosystems.

Light-induced fluorescence quenching leads to errors in sensor measurements of phytoplankton chlorophyll and phycocyanin.

Optical sensors for fluorescence of chlorophyll a (f-Chl a) and phycocyanin (f-PC) are increasingly used as a proxy for biomass of algae and cyanobacteria, respectively. They provide measurements at high-frequency and modest cost. These sensors require site-specific calibration due to a range of interferences. Light intensity affects the fluorescence yield of cyanobacteria and algae through light harvesting regulation mechanisms, but is often neglected as a potential source of error for in-situ f-Chl a and f-PC measurements. We hypothesised that diel light variations would induce significant f-Chl a and f-PC suppression when compared to dark periods. We tested this hypothesis in a controlled experiment using three commercial fluorescence probes which continuously measured f-Chl a and f-PC from a culture of the cyanobacterium Dolichospermum variabilis as well as f-Chl a from a culture of the green alga Ankistrodesmus gracilis in a simulated natural light regime. Under light, all devices showed a significant (p<0.01) suppression of f-Chl a and f-PC compared to measurements in the dark. f-Chl a decreased by up to 79% and f-PC by up to 59% at maximum irradiance compared to dark-adapted periods. Suppression levels were higher during the second phase of the diel cycle (declining light), indicating that quenching is dependent on previous light exposure. Diel variations in light intensity must be considered as a significant source of bias for fluorescence probes used for algal monitoring. This is of high relevance as most monitoring activities take place during daytime and hence f-Chl a and f-PC are likely to be systematically underestimated under bright conditions. Compensation models, design modifications to fluorometers and sampling design are discussed as suitable alternatives to overcome light-induced fluorescence quenching.

Unravelling winter diatom blooms in temperate lakes using high frequency data and ecological modeling.

In temperate lakes, it is generally assumed that light rather than temperature constrains phytoplankton growth in winter. Rapid winter warming and increasing observations of winter blooms warrant more investigation of these controls. We investigated the mechanisms regulating a massive winter diatom bloom in a temperate lake. High frequency data and process-based lake modeling demonstrated that phytoplankton growth in winter was dually controlled by light and temperature, rather than by light alone. Water temperature played a further indirect role in initiating the bloom through ice-thaw, which increased light exposure. The bloom was ultimately terminated by silicon limitation and sedimentation. These mechanisms differ from those typically responsible for spring diatom blooms and contributed to the high peak biomass. Our findings show that phytoplankton growth in winter is more sensitive to temperature, and consequently to climate change, than previously assumed. This has implications for nutrient cycling and seasonal succession of lake phytoplankton communities. The present study exemplifies the strength in integrating data analysis with different temporal resolutions and lake modeling. The new lake ecological model serves as an effective tool in analyzing and predicting winter phytoplankton dynamics for temperate lakes.

Forecasting water temperature in lakes and reservoirs using seasonal climate prediction.

Seasonal climate forecasts produce probabilistic predictions of meteorological variables for subsequent months. This provides a potential resource to predict the influence of seasonal climate anomalies on surface water balance in catchments and hydro-thermodynamics in related water bodies (e.g., lakes or reservoirs). Obtaining seasonal forecasts for impact variables (e.g., discharge and water temperature) requires a link between seasonal climate forecasts and impact models simulating hydrology and lake hydrodynamics and thermal regimes. However, this link remains challenging for stakeholders and the water scientific community, mainly due to the probabilistic nature of these predictions. In this paper, we introduce a feasible, robust, and open-source workflow integrating seasonal climate forecasts with hydrologic and lake models to generate seasonal forecasts of discharge and water temperature profiles. The workflow has been designed to be applicable to any catchment and associated lake or reservoir, and is optimized in this study for four catchment-lake systems to help in their proactive management. We assessed the performance of the resulting seasonal forecasts of discharge and water temperature by comparing them with hydrologic and lake (pseudo)observations (reanalysis). Precisely, we analysed the historical performance using a data sample of past forecasts and reanalysis to obtain information about the skill (performance or quality) of the seasonal forecast system to predict particular events. We used the current seasonal climate forecast system (SEAS5) and reanalysis (ERA5) of the European Centre for Medium Range Weather Forecasts (ECMWF). We found that due to the limited predictability at seasonal time-scales over the locations of the four case studies (Europe and South of Australia), seasonal forecasts exhibited none to low performance (skill) for the atmospheric variables considered. Nevertheless, seasonal forecasts for discharge present some skill in all but one case study. Moreover, seasonal forecasts for water temperature had higher performance in natural lakes than in reservoirs, which means human water control is a relevant factor affecting predictability, and the performance increases with water depth in all four case studies. Further investigation into the skillful water temperature predictions should aim to identify the extent to which performance is a consequence of thermal inertia (i.e., lead-in conditions).

Ensemble warming projections in Germany's largest drinking water reservoir and potential adaptation strategies.

The thermal structure in reservoirs affects the development of aquatic ecosystems, and can be substantially influenced by climate change and management strategies. We applied a two-dimensional hydrodynamic model to explore the response of the thermal structure in Germany's largest drinking water reservoir, Rappbode Reservoir, to future climate projections and different water withdrawal strategies. We used projections for representative concentration pathways (RCP) 2.6, 6.0 and 8.5 from an ensemble of 4 different global climate models. Simulation results showed that epilimnetic water temperatures in the reservoir strongly increased under all three climate scenarios. Hypolimnetic temperatures remained rather constant under RCP 2.6 and RCP 6.0 but increased markedly under RCP 8.5. Under the intense warming in RCP 8.5, hypolimnion temperatures were projected to rise from 5 °C to 8 °C by the end of the century. Stratification in the reservoir was projected to be more stable under RCP 6.0 and RCP 8.5, but did not show significant changes under RCP 2.6. Similar results were found with respect to the light intensity within the mixed-layer. Moreover, the results suggested that surface withdrawal can be an effective adaptation strategy under strong climate warming (RCP 8.5) to reduce surface warming and avoid hypolimnetic warming. This study documents how global scale climate projections can be translated into site-specific climate impacts to derive adaptation strategies for reservoir operation. Moreover, our results illustrate that the most intense warming scenario, i.e. RCP 8.5, demands far-reaching climate adaptation while the mitigation scenario (RCP 2.6) does not require adaptation of reservoir management before 2100.

The formation of a metalimnetic oxygen minimum exemplifies how ecosystem dynamics shape biogeochemical processes: A modelling study.

Metalimnetic oxygen minima are observed in many lakes and reservoirs, but the mechanisms behind this phenomena are not well understood. Thus, we simulated the metalimnetic oxygen minimum (MOM) in the Rappbode Reservoir with a well-established two-dimensional water quality model (CE-QUAL-W2) to systematically quantify the chain of events leading to its formation. We used high-resolution measured data to calibrate the model, which accurately reproduced the physical (e.g. water level and water temperature), biogeochemical (e.g. nutrient and oxygen dynamics) and ecological (e.g. algal community dynamics) features of the reservoir, particularly the spatial and temporal extent of the MOM. The results indicated that around 60% of the total oxygen consumption rate in the MOM layer originated from benthic processes whereas the remainder originated from pelagic processes. The occurrence of the cyanobacterium Planktothrix rubescens in the metalimnion delayed and slightly weakened the MOM through photosynthesis, although its decaying biomass ultimately induced the MOM. Our research also confirmed the decisive role of water temperature in the formation of the MOM since the water temperatures, and thus benthic and pelagic oxygen consumption rates, were higher in the metalimnion than in the hypolimnion. Our model is not only providing novel conclusions about the drivers of MOM development and their quantitative contributions, it is also a new tool for understanding and predicting ecological and biogeochemical water quality dynamics.

High frequency data provide new insights into evaluating and modeling nitrogen retention in reservoirs.

Freshwater ecosystems including lakes and reservoirs are hot spots for retention of excess nitrogen (N) from anthropogenic sources, providing valuable ecological services for downstream and coastal ecosystems. Despite previous investigations, current quantitative understanding on the influential factors and underlying mechanisms of N retention in lentic freshwater systems is insufficient due to data paucity and limitation of modeling techniques. Our ability to reliably predict N retention for these systems therefore remains uncertain. Emerging high frequency monitoring techniques and well-developed ecosystem modeling shed light on this issue. In the present study, we explored the retention of NO3-N during a five-year period (2013-2017) in both annual and weekly scales in a highly flushed reservoir in Germany. We found that annual-averaged NO3-N retention efficiency could be up to 17% with an overall retention efficiency of ∼4% in such a system characterized by a water residence time (WRT) of ∼4 days. On the weekly scale, the reservoir displayed negative retention in winter (i.e. a source of NO3-N) and high positive retention in summer (i.e. a sink for NO3-N). We further identified the critical role of Chl-a concentration together with the well-recognized effects from WRT in dictating NO3-N retention efficiency, implying the significance of biological processes including phytoplankton dynamics in driving NO3-N retention. Furthermore, our modeling approach showed that an established process-based ecosystem model (PCLake) accounted for 58.0% of the variance in NO3-N retention efficiency, whereas statistical models obtained a lower value (40.5%). This finding exemplified the superior predictive power of process-based models over statistical models whenever ecological processes were at play. Overall, our study highlights the importance of high frequency data in providing new insights into evaluating and modeling N retention in reservoirs.