Schmidt Stability Research Articles

Local Hilbert–Schmidt stability

We introduce a notion of local Hilbert–Schmidt stability, motivated by the recent definition by Bradford of local permutation stability, and give examples of (non-residually finite) groups that are locally Hilbert–Schmidt stable but not Hilbert–Schmidt stable. For amenable groups, we provide a criterion for local Hilbert–Schmidt stability in terms of group characters, by analogy with the character criterion of Hadwin and Shulman for Hilbert–Schmidt stable amenable groups. Furthermore, we study the (very) flexible analogues of local Hilbert–Schmidt stability, and we prove several results analogous to the classical setting. Finally, we prove that infinite sofic, respectively hyperlinear, property (T) groups are never locally permutation stable, respectively locally Hilbert–Schmidt stable. This strengthens the result of Becker and Lubotzky for classical stability, and answers a question of Lubotzky.

Understanding stratification and turnover dynamics of a tropical lake using extensive field observations and 3D hydrodynamic simulations

The stratification and turnover dynamics of a tropical lake were evaluated using field observations and 3D hydrodynamic simulations. Located in the Philippines, Sampaloc Lake is a 104-ha and 27-m deep volcanic crater lake with enclosed watershed, which is at risk of the impacts of intensive aquaculture, rapid urbanization and climate change. Temperature, dissolved oxygen (DO) and chlorophyll-a (Chl-a) were measured at seven sampling stations using a multiprobe. Kruskal-Wallis test revealed that the three parameters are not significantly different among stations, indicating that one sampling station can represent the water quality of the whole lake. Schmidt's Stability Index (SSI) and thermocline strength, together with DO and Chl-a gradients decreased from October 2022 (stratified) to January 2023 (turnover). After successfully verifying the 3D numerical model, sensitivity analyses of water temperature to varying weather, together with particle tracking simulations, were implemented to determine the timing of isothermal state, upwelling, partial mixing, and full turnover. Compared to air temperature, variations in wind speed have more pronounced effects on the delay or progression of isothermal conditions in the lake based on SSI, Lake Number and Wedderburn Number. Isothermal conditions do not necessarily coincide with the timing of full turnover, with the latter being delayed by two days than the former, on average. Results revealed that full turnover can occur several weeks earlier with the decrease in AT and increase in WS. This study can advance the understanding of thermal and turnover dynamics of stratified tropical lakes, leading to better management of the water quality of these water bodies.

Factors contributing to the minimum water column stability and timing of the winter turnover in the Ogouchi reservoir

Turnover in lakes and reservoirs causes circulation in the water column from the bottom to the surface when the water column stability becomes low. Previous studies commonly mentioned that turnover occurs when stratification indices become small, but the threshold is rarely discussed. While turnover phenomena have been extensively studied by evaluating changes in bottom dissolved oxygen (DO), the relationship between the disappearance of hypoxia and water temperature indices has not been determined. This study focused on the factors influencing the minimum thermal gradient (TG) and Schmidt Stability Index (SSI), and the timing of turnover events using DO as an indicator of mixing in the Ogouchi reservoir from 1992 to 2001. The results showed that the occurrence of minimum TG and SSI is mainly driven by inflow retention time and average maximum wind speed. Moreover, minimum air temperature and outflow retention time have few contributions to minimum SSI. It was found that 7 out of 10 years exhibited full winter turnover, while the remaining years showed incomplete mixing with persistent hypoxia at the reservoir bottom. This study identifies four cases based on onset thresholds of 0.0035 °C m−1 for TG and 30 J m−2 for SSI to explain turnover event: Case 1: an ideal state with stratification indices below the threshold, resulting in the disappearance of hypoxia; Case 2: indices above the threshold sustain hypoxia; Case 3: an irregular state where the indices exceed the threshold, yet hypoxia disappears; and Case 4: an unexpected persistence of hypoxia despite being below the threshold. The majority of the years (70 percent) were explained by thresholds. The multiple regression analysis indicated the importance of wind speed on the turnover event. Therefore, the effect of wind shear was analyzed for 30 percent of the years that cannot be explained by thresholds (cases 3 and 4). Case 3 shows turnover occurrence due to strong accumulated wind shear, despite exceeding thresholds. Conversely, Case 4 reveals weak wind shear preventing bottom water upwelling, even below thresholds. In conclusion, the precise TG and SSI thresholds for the onset of turnover event were determined using DO data. The thresholds explained the occurrence and non-occurrence of turnover event in most of the years and wind speed clarified unexplained cases by thresholds. The presented method successfully evaluated the timing of turnover and can be applicable elsewhere.

Effects of hydropeaking by an upstream dam on thermal mixing in a riverine lake

The hydropeaking operations of a hydropower dam can significantly affect the flow and thermal regimes in riverine reservoirs, and this effect is very complex, both in space and time. In this study, we used a 3D hydrodynamic model, calibrated with field datasets, to investigate the thermal mixing resulting from hydropeaking within Paldang Lake (PL) in South Korea. The spatiotemporal temperature patterns revealed that density currents critically affected thermal mixing in the reservoir and developed differently based on upstream dam operations and flooding events. Notably, the confluence of the North Han River (NHR) and South Han River (SHR) played a key role in shaping the thermal regime. During the hydropeaking release from the upstream dam in the NHR, the colder water of the NHR from the deep-water discharge of the upstream dam plunged beneath the warmer water of the SHR, leading to three-dimensional mixing. Consequently, the thermal mixing patterns varied depending on the discharge patterns from the upstream dam. Additionally, diurnal variations in the dam discharge frequently affected areas of the reservoir exhibiting high Schmidt stability. During the non-operation period of the upstream dam, the SHR flow backflowed into the downstream section of the NHR, resulting in the confluent area exhibiting the poorest vertical mixing. Secondary currents also played a crucial role in influencing the flow and thermal regimes, with the intensity of the secondary flow varying along the longitudinal mainstream of the reservoir. The thermal mixing state was predominantly weakened to partial mixing within a curved reach owing to the secondary current. Overall, this study demonstrates that the complexity of flow and thermal processes in the PL is significantly influenced by hydropeaking events. These findings emphasize the importance of understanding density currents and secondary flows according to dam operation in managing riverine reservoirs for enhanced ecological health and sustainable water resource management.

Modular Compositional Learning Improves 1D Hydrodynamic Lake Model Performance by Merging Process‐Based Modeling With Deep Learning

AbstractHybrid Knowledge‐Guided Machine Learning (KGML) models, which are deep learning models that utilize scientific theory and process‐based model simulations, have shown improved performance over their process‐based counterparts for the simulation of water temperature and hydrodynamics. We highlight the modular compositional learning (MCL) methodology as a novel design choice for the development of hybrid KGML models in which the model is decomposed into modular sub‐components that can be process‐based models and/or deep learning models. We develop a hybrid MCL model that integrates a deep learning model into a modularized, process‐based model. To achieve this, we first train individual deep learning models with the output of the process‐based models. In a second step, we fine‐tune one deep learning model with observed field data. In this study, we replaced process‐based calculations of vertical diffusive transport with deep learning. Finally, this fine‐tuned deep learning model is integrated into the process‐based model, creating the hybrid MCL model with improved overall projections for water temperature dynamics compared to the original process‐based model. We further compare the performance of the hybrid MCL model with the process‐based model and two alternative deep learning models and highlight how the hybrid MCL model has the best performance for projecting water temperature, Schmidt stability, buoyancy frequency, and depths of different isotherms. Modular compositional learning can be applied to existing modularized, process‐based model structures to make the projections more robust and improve model performance by letting deep learning estimate uncertain process calculations.

Influences of hydrodynamics on dissolved inorganic carbon in deep subtropical reservoir: Insights from hydrodynamic model and carbon isotope analysis

Dam construction significantly impacts river hydrodynamics, subsequently influencing carbon biogeochemical processes. However, the influence of hydrodynamic conditions on the migration and transformation of Dissolved Inorganic Carbon (DIC) remains uncertain. To bridge this knowledge gap, we integrated hydrochemistry, isotopic composition (δ13CDIC), and a hydrodynamic model (CE-QUAL-W2) to examine the distinctions, control mechanisms, and environmental effects of DIC biogeochemical processes in a typical large and deep reservoir (Hongjiadu Reservoir) under different hydrodynamic conditions. We evaluated hydrodynamic alterations through the Schmidt stability index and relative water column stability. The analysis disclosed that during weak hydrodynamics periods, the energy necessary for complete mixing the surface and deep water was 34 times higher (3615.32 J/m2 vs.106.86 J/m2), and stability was 13 times greater (312.96 vs. 24.69) compared to periods of strong hydrodynamics. Additionally, the spatiotemporal heterogeneity of DIC concentrations (1.4 % to -9.1 %) and δ13CDIC (-1.7 % to -19.5 %) from the dry to wet seasons reflected disparities in DIC control mechanisms under varied hydrodynamic conditions. Based on model simulations, our calculations indicate that during weak hydrodynamics periods, the enhancement of the biological carbon pump effect resulted in substantial sequestration of DIC, reaching up to 379.6 t-DIC·d−1 in the water. Conversely, during strong hydrodynamics periods, DIC retention capacity decreased by 69.2 t·d−1, resulting in reservoir CO2 emissions of 22.7 × 104 t, which were more than 7 times higher than during weak hydrodynamics periods (3.2 × 104 t). Our findings emphasize the discernible impact of hydrodynamic conditions on reservoir biogeochemical processes related to DIC. Considering the increasing construction of reservoirs globally, understanding and controlling hydrodynamic conditions are crucial for mitigating CO2 emissions and optimizing reservoir management.

Flexible Hilbert–Schmidt stability versus hyperlinearity for property (T) groups

Flexible Hilbert–Schmidt stability versus hyperlinearity for property (T) groups

Effect of Climate Change on Water Temperature and Stratification of a Small, Temperate, Karstic Lake (Lake Kozjak, Croatia)

As closed systems, lakes are extremely vulnerable to climate change. Understanding the response to climate change is crucial for effective management and conservation of the lakes and their associated ecosystems. This study focuses on Lake Kozjak, Croatia, a small lake belonging to the Plitvice Lakes system. This system represents a unique hydrogeological karstic phenomenon, closely dependent on a delicate biochemical balance necessary for tufa formation. We apply a simple one-dimensional model, SIMO v.1.0, to predict future water temperature in Lake Kozjak under three scenarios (RCP2.6, RCP4.5 and RCP8.5) from 2006 to 2100. The model was calibrated using measured water temperature profiles and meteorological data from a nearby station. In addition to analyzing the average temperatures of the epilimnion, hypolimnion and the whole lake, we also studied the surface and bottom layer temperatures and their relation to specific forcing parameters. The Schmidt stability index was used as a quantitative indicator to assess lake stability. The simulation results indicate average lake water temperature increase of 0.51, 1.41 and 4.51 °C (100 y)−1 for RCP2.6, RCP4.5 and RCP8.5, respectively. This increase in the water temperature is not accompanied by a substantial strengthening of stratification under RCP2.6 and RCP4.5 scenarios due to the temperature raise being present both in the epilimnion and hypolimnion. However, significant lengthening of the stratification period is observed even for the most stringent scenario, 16, 28 and 47 d (100 y)−1 for RCP2.6, RCP4.5 and RCP8.5, respectively. The predicted water temperature increase and prolonged stratification period may carry serious ecological and environmental implications.Highlights• Mean lake water temperature is projected to increase by 0.51 to 4.51 °C (100 y)−1.• Baseline scenario surface temperature increase of 5.2 °C (100 y)−1 is predicted.• Stratification period is predicted to lengthen by 16 (RCP2.6) to 47 days (RCP8.5).• Substantial stratification strengthening is expected only under RCP8.5.

Effects of Hydrological Drought Periods on Thermal Stability of Brazilian Reservoirs

Droughts can impact ecosystem services provided by reservoirs. Quantifying the intensity of droughts and evaluating their potential effects on the thermal stability of reservoirs are subjects that demand greater attention, due to both the importance of temperature on aquatic metabolism and the climate change scenarios that predict an increase in the frequency of extreme weather events. This study aimed to investigate drought periods in ten Brazilian reservoirs and to discuss their effects on each reservoir’s thermal stability. The Standardized Precipitation Index at a twelve month timescale (SPI-12) was applied to identify the hydrological drought periods. One-dimensional vertical hydrodynamic modeling was used to simulate the water balance and the thermal dynamics in the reservoirs. Schmidt Stability Index (St) was calculated to assess the thermal stability of the reservoirs. The drought periods identified by the SPI-12 are related to decreasing water levels of the reservoirs, but the dam operating strategies and the upstream influence of cascading reservoirs are important drivers of fluctuations. A significant difference in St between wet and dry conditions was found only during summer for all reservoirs. Thus, this study identified alterations in thermal regime during drought periods according to the seasons and the reservoirs characteristics.

Uncertainty in projections of future lake thermal dynamics is differentially driven by lake and global climate models.

Freshwater ecosystems provide vital services, yet are facing increasing risks from global change. In particular, lake thermal dynamics have been altered around the world as a result of climate change, necessitating a predictive understanding of how climate will continue to alter lakes in the future as well as the associated uncertainty in these predictions. Numerous sources of uncertainty affect projections of future lake conditions but few are quantified, limiting the use of lake modeling projections as management tools. To quantify and evaluate the effects of two potentially important sources of uncertainty, lake model selection uncertainty and climate model selection uncertainty, we developed ensemble projections of lake thermal dynamics for a dimictic lake in New Hampshire, USA (Lake Sunapee). Our ensemble projections used four different climate models as inputs to five vertical one-dimensional (1-D) hydrodynamic lake models under three different climate change scenarios to simulate thermal metrics from 2006 to 2099. We found that almost all the lake thermal metrics modeled (surface water temperature, bottom water temperature, Schmidt stability, stratification duration, and ice cover, but not thermocline depth) are projected to change over the next century. Importantly, we found that the dominant source of uncertainty varied among the thermal metrics, as thermal metrics associated with the surface waters (surface water temperature, total ice duration) were driven primarily by climate model selection uncertainty, while metrics associated with deeper depths (bottom water temperature, stratification duration) were dominated by lake model selection uncertainty. Consequently, our results indicate that researchers generating projections of lake bottom water metrics should prioritize including multiple lake models for best capturing projection uncertainty, while those focusing on lake surface metrics should prioritize including multiple climate models. Overall, our ensemble modeling study reveals important information on how climate change will affect lake thermal properties, and also provides some of the first analyses on how climate model selection uncertainty and lake model selection uncertainty interact to affect projections of future lake dynamics.

Combined effects of climatic change and hydrological conditions on thermal regimes in a deep channel-type reservoir

The thermal regime in large reservoirs plays a significant role in the water quality and ecosystem succession; however, little is known about the impacts of regional climate changes and hydrological conditions on a sizeable stratified reservoir with strong inflow conditions, i.e., the Xiangjiaba Reservoir. Using measured data from 2014 to 2018, the monthly and seasonal variations of the water temperature, thermal stability, and their influencing factors were addressed by using empirical models. The results showed substantial variability and seasonality in the reservoir water temperature, which correlated highly with the air temperature, inflow water temperature, and discharge. Correspondingly, there was a seasonal varying thermal stratification in the reservoir's yearly cycle, with its duration being up to 4 ~ 5months, the maximum surface-bottom water temperature difference being up to 7 ~ 10°C. There were significant positive correlations between Schmidt's stability index of the thermal structure and inflow-reservoir temperature difference and the surface-bottom temperature differences, while negative correlations with large discharge. Moreover, the inflow tends to influence thermal stability by retaining hypolimnion cold water, with its maximum bottom hysteresis residence time being up to ~ 4months. Research findings indicated that climate warming in the recent 30years (1988 ~ 2017) would cause a 0.213°C/decade and 0.153kJ/m2/decade increase in reservoir surface water temperature and Schmidt's stability index, respectively. Among these variations, the inflow temperature increase caused by climate change accounted for the largest proportion, i.e., 0.16°C/decade and 0.115kJ/m2/decade. Therefore, climate warming significantly affected the thermal regimes in this large reservoir, and the inflow water temperature increase due to warm air was the main factor altering the reservoir's thermal structure. Findings from the present study provide a fresh perspective on how to best optimize the deep channel-type reservoirs' water quality in the face of anticipated climate change.

Mixing regimes in a cluster of seven maar lakes in tropical monsoon Asia

ABSTRACT The 7 maar lakes of San Pablo are a cluster of small volcanic lakes on Luzon Island, Philippines. These lakes, which are heavily utilized for aquaculture and ecotourism, usually experience fish kills that coincide with the northeast monsoon (NEM). This study explores limnophysical processes, particularly mixing regimes, in the lakes in relation to prevailing monsoons. We monitored monthly vertical and seasonal profiles of water temperature, salinity, conductivity, and dissolved oxygen from October 2016 to December 2018. Three types of mixing regimes were observed among the lakes, which have similar surface areas but different depths: polymixis in the shallowest; warm monomixis in lakes with intermediate depth; and meromixis in the deepest. A boundary between monomixis and meromixis was identified between 36 and 62 m depth. Monthly monitoring showed seasonal mixing occurred exclusively during the NEM (Nov–Apr). We also incorporated meteorological data into the model and performed multiple regression analysis for each lake to determine the best predictor: lake stability, as indicated by the Schmidt stability (ST ). A between-lake comparison showed lake stability was strongly correlated with both air temperature and wind speed, suggesting these 2 meteorological variables are involved in establishing thermal stratification in the lakes during the southwest monsoon. This study provides insights for adaptive lake management and projections of climate impacts on these understudied tropical lake ecosystems in Southeast Asia.

Lake stability and anoxia dynamics revealed from high frequency vertical profiling in a eutrophic polymictic reservoir

ABSTRACT High-frequency water quality monitoring is rapidly growing in freshwater research and management. Sensor deployments at fixed depths in naturally formed lakes dominate the current understanding of ecosystem dynamics, with comparatively few studies focusing on reservoirs. Here we examined how environmental parameters affect the water column stability and dissolved oxygen (DO) dynamics in a North Texas eutrophic reservoir. We used an autonomous water quality monitoring profiler that recorded temperature, DO, and pH as well as wind speed, wind direction, and air temperature from an on-platform mounted weather station. Data were collected every 2 h from 25 April to 29 October 2019, with each profile spanning from the surface to 10 m depth at 0.5 m steps. Throughout most of the sampling period, the lake had no distinct thermocline, but we observed an oxycline throughout most of the monitoring period, with multiple mixing events. Near the sediments, periods of anoxia lasting hours to days were first observed in May, and July through September were chronically anoxic. In August and September, DO was frequently <2.0 mg L−1 throughout the entire water column, with 2 periods of total water column anoxia. Surface DO measurements for each 2 h interval were highly synchronous with Schmidt stability. During decreasing and low Schmidt stability or Lake Number, the oxycline destabilized in association with changes in wind direction and speed. Our results indicate that DO can be highly dynamic in polymictic reservoirs, with strong implications for carbon and nitrogen biogeochemical cycles.

Effects of flood discharge on the water quality of a drinking water reservoir in China – Characteristics and management strategies

Stormflow runoff is an important non-point source of pollution in drinking water reservoirs. Rationally managed flood discharge processes at estuaries can reduce the high concentration of pollutants carried by runoff, and thus their impacts on water plant operations. In this study, the physical and chemical water quality parameters upstream from a dam were measured for a flood discharge process in the Jinpen Reservoir of Northwest China. The results showed that the time needed for the flood to reach the reservoir was ∼9 h after flooding began, and this lag effect meant that water in the metalimnion and hypolimnion were vented in advance. Consequently, the undercurrent intruded into the hypolimnion. The water temperature increased by 1.83 °C, and the Schmidt stability index decreased from 3291.37 J m−2 to 2496.32 J m−2. Flood discharge can effectively reduce the volume of pollutants; however, it cannot completely prevent the deterioration of water quality in the main reservoir. The turbidity of the reservoir still exceeded 300 NTU after the flood discharge. When the outflow discharge decreased, the critical height of aspiration also decreased, and dissolved pollutants could neither be vented nor precipitated quickly, not allowing their concentration within the reservoir to decrease further. A three-dimensional hydrodynamic model was successfully used to simulate flood processes and determine an optimal flood discharge plan. We found that the elevations of the outlet and undercurrent layer are essential to determine the efficiency of flood discharge, while appropriate timing and outflow discharge volumes may further enhance the results. Therefore, using a hydrodynamic model to predict the position of an undercurrent layer, and opening spillways near the elevation of the undercurrent layer can improve the efficacy of flood discharge. Our findings provide novel insights that may be used to improve the operation and management of source water reservoirs.

Thermal mixing of Lake Erhai (Southwest China) induced by bottom heat transfer: Evidence based on observations and CE-QUAL-W2 model simulations

The thermal structure of a lake is strongly associated its hydrodynamics and climatic conditions, and is an important basis to understand the physical, chemical, and ecological processes of the lake. Lake Erhai (100°05′–100°17′N and 25°36′–25°58′E) is a large and deep lake in Yunnan Province, located on the Yunnan–Guizhou Plateau of Southwest China. Some deep lakes located in areas adjacent to Lake Erhai with similar climatic conditions and water depths are warm monomictic lakes. However, the historical data of the surface water temperature and bottom water temperature for the past 15 years (2004–2018) showed small differences (<1 °C). However, ours and some other studies on the vertical water temperature profile showed mixing of the entire water column in different seasons. We have applied a well-established hydrodynamics model (CE-QUAL-W2) to explore the main process that induces the particular thermal structure of Lake Erhai. Model calibration was conducted twice, once with the extinction coefficient (Kd) and fraction of solar radiation absorbed in the surface layer (BETA) as the main calibrated parameters, and the other considering the process of bottom-water heat exchange, represented by the sediment temperature (TSED) parameter in the CE-QUAL-W2 model. The simulation results showed that the model can reproduce water level and surface water temperature accurately with the first calibration (TSED is 14.8 °C), however, only when the TSED is greater than 24 °C, the RMSE can be less than 2 °C. The model reproduces the bottom water temperature well when the TSED value was 29.6 ± 0.37 °C. Moreover, a series of scenarios were conducted to quantify the effect of wind speed and/or tributary inflows temperature on the thermal structure of Lake Erhai, and two stability indices (Schmidt stability, Birgean work) were calculated to quantify the energy required for stratification and mixing. These results demonstrated that the most likely process to establish the holomixis of Lake Erhai is geothermal heat transfer from sediment to water column, and an additional 12% heat flux from sediment plus the actual external energy supplies from sediment are required to mix the entire water column of Lake Erhai in summer.

Stratification in a Reservoir Mixed by Bubble Plumes under Future Climate Scenarios

During summer, reservoir stratification can negatively impact source water quality. Mixing via bubble plumes (i.e., destratification) aims to minimise this. Within Blagdon Lake, a UK drinking water reservoir, a bubble plume system was found to be insufficient for maintaining homogeneity during a 2017 heatwave based on two in situ temperature chains. Air temperature will increase under future climate change which will affect stratification; this raises questions over the future applicability of these plumes. To evaluate bubble-plume performance now and in the future, AEM3D was used to simulate reservoir mixing. Calibration and validation were done on in situ measurements. The model performed well with a root mean squared error of 0.53 °C. Twelve future meteorological scenarios from the UK Climate Projection 2018 were taken and down-scaled to sub-daily values to simulate lake response to future summer periods. The down-scaling methods, based on diurnal patterns, showed mixed results. Future model runs covered five-year intervals from 2030 to 2080. Mixing events, mean water temperatures, and Schmidt stability were evaluated. Eight scenarios showed a significant increase in water temperature, with two of these scenarios showing significant decrease in mixing events. None showed a significant increase in energy requirements. Results suggest that future climate scenarios may not alter the stratification regime; however, the warmer water may favour growth conditions for certain species of cyanobacteria and accelerate sedimentary oxygen consumption. There is some evidence of the lake changing from polymictic to a more monomictic nature. The results demonstrate bubble plumes are unlikely to maintain water column homogeneity under future climates. Modelling artificial mixing systems under future climates is a powerful tool to inform system design and reservoir management including requirements to prevent future source water quality degradation.

A potential tipping point in the thermal regime of a warm monomictic reservoir under climate change using three-dimensional hydrodynamic modeling

ABSTRACT The response of the Maroon reservoir in southwest Iran is modeled to evaluate possible impacts of 21st century climate change. Projections of 3 CMIP5 General Circulation Models (GCMs) were investigated using 2 Representative Concentration Pathways (RCP4.5 and RCP8.5), which respectively represent low/medium and high greenhouse gas emission scenarios. The raw GCM projections are statistically bias-corrected to provide boundary conditions for the 3-dimensional Aquatic Ecosystem Model (AEM3D). A new overturn bias analysis method was developed to evaluate possible bias in the GCM predictors during the observational (historic) period and determined it to be negligible. The modeling results, quantified by the analysis of various limnological parameters (onset and length of mixing and stratification periods, hypolimnion and epilimnion thickness and temperature, Brunt-Väisälä frequency, and Schmidt stability) indicate for RCP4.5 a continuous reduction in winter mixing and complete suppression of mixing by the end of the 21st century, implying a switch from monomictic to weakly oligomictic behavior. Under RCP8.5, the behavior transition occurs abruptly in the late 2050s in the form of a tipping point, followed by intermittent oligomictic behavior and transition to permanent stratification (thermal meromixis) within a decade. The change in behavior occurs because the surface and mixing temperatures significantly increase due to climate warming, whereas the hypolimnion is less affected, partly because of milder warming of cold winter river inflows (underflow) and strengthening stratification. The climate change-induced tipping point for the thermal regime of Maroon reservoir might serve as an indicator of changes in other warm monomictic systems.

Antecedent lake conditions shape resistance and resilience of a shallow lake ecosystem following extreme wind storms

AbstractExtreme wind storms can strongly influence short‐term variation in lake ecosystem functioning. Climate change is affecting storms by altering their frequency, duration, and intensity, which may have consequences for lake ecosystem resistance and resilience. However, catchment and lake processes are simultaneously affecting antecedent lake conditions which may shape the resistance and resilience landscape prior to storm exposure. To determine whether storm characteristics or antecedent lake conditions are more important for explaining variation in lake ecosystem resistance and resilience, we analyzed the effects of 25 extreme wind storms on various biological and physiochemical variables in a shallow lake. Using boosted regression trees to model observed variation in resistance and resilience, we found that antecedent lake conditions were more important (relative importance = 67%) than storm characteristics (relative importance = 33%) in explaining variation in lake ecosystem resistance and resilience. The most important antecedent lake conditions were turbidity, Schmidt stability, %O2 saturation, light conditions, and soluble reactive silica concentrations. We found that storm characteristics were all similar in their relative importance and results suggest that resistance and resilience decrease with increasing duration, mean precipitation, shear stress intensity, and time between storms. In addition, we found that antagonistic or opposing effects between the biological and physiochemical variables influence the overall resistance and resilience of the lake ecosystem under specific lake and storm conditions. The extent to which these results apply to the resistance and resilience of different lake ecosystems remains an important area for inquiry.

Late summer peak in pCO2 corresponds with catchment export of DOC in a temperate, humic lake

ABSTRACT Humic lakes play a key role in the processing of organic carbon (OC) mobilised from their catchments, but knowledge of OC dynamics in lakes within maritime temperate climates is limited. Climate exerts a significant influence on mechanisms of OC capture, storage, and processing on the wet and cloudy west coast of Ireland. We examined a high-frequency dataset of partial pressure of CO2 (pCO2) in the surface waters of Lough Feeagh collected over 1 year. The annual pattern in pCO2 ranged between 491 and 1169 µatm and was strongly related to allochthonous riverine OC inputs. In contrast to observations in colder climates, a single peak in pCO2 occurred in Lough Feeagh in early September. Generalised additive mixed modelling revealed that 2 variables, inflow water colour concentration (a reliable proxy for DOC concentrations) and lake Schmidt stability, together explained 68% of pCO2 variability. Both the statistical analysis and timing of the peaks in inflow DOC and pCO2 strongly suggested that catchment carbon export drove pCO2 supersaturation in the lake, and hence CO2 emissions. We estimated that between 217 and 370 t CO2-C (0.55–0.94 t/ha) was emitted during the study period. These results highlight the interplay between catchment OC fluxes and climate in determining pCO2 dynamics in maritime temperate lakes.

Abiotic and biotic drivers of temporal dynamics in the spatial heterogeneity of zooplankton communities across lakes in recovery from eutrophication.

Seasonal and annual dynamics of the zooplankton community in lakes are affected by changes in abiotic drivers, trophic interactions (e.g., changes in phytoplankton and fish communities and abundances) and habitat characteristics (e.g. macrophyte abundance and composition). However, little is known about the temporal responses of the zooplankton community to abiotic and biotic drivers across lakes at the regional scale. Using a comprehensive 20-year dataset from 20 Danish lakes in recovery from eutrophication, we assessed the seasonal and annual trends in the spatial heterogeneity of zooplankton community across lakes and related it to abiotic and biotic drivers. We found significant seasonality and inter-annual decreases in spatial zooplankton heterogeneity in both shallow and deep lakes, with the decrease in the spatial turnover dominating the temporal dynamics of the beta diversity. For the inter-annual changes, decreased spatial heterogeneity of phytoplankton, macrophytes and fish were important biotic drivers at the regional scale. Using a series of ordinary least squares regressions and model selection with model averaging approaches, we revealed that both local (e.g., total phosphorus, total nitrogen, pH, Secchi depth, alkalinity, Schmidt stability, water temperature) and regional drivers (e.g., air temperature, solar irradiance) were important variables influencing the spatial zooplankton heterogeneity, although the directions depended on the beta diversity measures and water depth. Our results highlight an important role of bottom-up forces through phytoplankton community as well as macrophytes and top-down forces via fishes in driving the temporal changes in zooplankton community composition patterns at the regional scale.