Lake Surface Water Research Articles

Constructed wetland mesocosms improve the biodegradation of microcystin-LR and cylindrospermopsin by indigenous bacterial consortia

Cyanobacterial blooms releasing harmful cyanotoxins, such as microcystin (MC) and cylindrospermopsin (CYN), are prominent threats to human and animal health. Constructed wetlands (CW) may be a nature-based solution for bioremediation of lake surface water containing cyanotoxins, due to its low-cost requirement of infrastructure and environmentally friendly operation. There is recent evidence that microcystin-LR (MC-LR) can efficiently be removed in CW microcosms where CYN degradation in CW is unknown. Likewise, the mechanistic background regarding cyanotoxins transformation in CW is not yet elucidated. In the present study, the objective was to compare MC-LR and CYN degradation efficiencies by two similar microbial communities obtained from CW mesocosms, by two different experiments setup: 1) in vitro batch experiment in serum bottles with an introduced CW community, and 2) degradation in CW mesocosms. In experiment 1) MC-LR and CYN were spiked at 100 µg L−1 and in experiment 2) 200 µg L−1 were spiked. Results showed that MC-LR was degraded to ≤1 µg L−1 within seven days in both experiments. However, with a markedly higher degradation rate constant in the CW mesocosms (0.18 day−1 and 0.75 day−1, respectively). No CYN removal was detected in the in vitro incubations, whereas around 50 % of the spiked CYN was removed in the CW mesocosms. The microbial community responded markedly to the cyanotoxin treatment, with the most prominent increase of bacteria affiliated with Methylophilaceae (order: Methylophilales, phylum: Proteobacteria). The results strongly indicate that CWs can develop an active microbial community capable of efficient removal of MC-LR and CYN. However, the CW operational conditions need to be optimized to achieve a full CYN degradation. To the best of our knowledge, this study is the first to report the ability of CW mesocosms to degrade CYN.

Source-specific categorization of microplastics in nearshore surface waters of the Great Lakes

Actions aimed at reducing microplastic pollution need source-specific information to tailor local and global efforts. We applied a source-specific categorization scheme to quantify and characterize microplastics using robust QA/QC methods in 98 nearshore surface waters collected using manta trawls from three Laurentian Great Lakes. The greatest abundances (max. 2.0 x 107 particles/km2) were found adjacent to the Greater Toronto Area, where fragments consistent with commercial and industrial activities contributed up to 58 % ± 21 % of particles on average (0.335 – 4.75 mm size range; near wastewater discharges in Humber Bay, Lake Ontario). Irregularly-shaped polyethylene microbeads were consistently more abundant than spherical microbeads as is typical in personal care products and contributed significantly (up to 44 % ± 21 % on average; Hamilton Harbour, Lake Ontario) in areas dominated by wastewater inputs. Using source-specific microplastic morphology categories may facilitate 1) the development of specific mitigation initiatives for identified and significant sources, and 2) assessing the effectiveness of implemented reduction measures at local levels in marine coastal environments, estuaries, and freshwaters globally.

Perspectives from modern hydrology and hydrochemistry on a lacustrine biodiversity hotspot: Ancient Lake Poso, Central Sulawesi, Indonesia

The highly biodiverse Lake Poso, located in Central Sulawesi, Indonesia, can be considered one of the least studied ancient lakes in the world. Here, we present a comprehensive analysis of Lake Poso's hydrology and hydrochemistry, shedding light on factors that may have contributed to the exceptional biodiversity. Riverine and lake water chemical compositions indicated a soft water lake and relative major cation and anion abundances of Ca2+ ≫ Mg2+ > Na+ > K+ and HCO3– ≫ SO42− > Cl−, primarily a result of the high annual precipitation and chemical weathering of calcareous-siliceous metamorphic bedrock. Lake Poso’s nutrient concentrations were low (average DIN/TDP mass ratio of 6.2 and 50.9 for the lake surface water and its tributaries, respectively), indicating that most of the inlets were P-limited and that the lake was likely P-limited as well. Metal pollutants indicated a minor to moderate impact of anthropogenic land use (∼32 % of the catchment area). Water isotopic compositions of the different tributaries clearly delineated rivers draining higher elevation catchments with lower δ2H and δ18O from those draining lower elevation catchments with higher δ2H and δ18O. Surface lake water isotopic compositions indicated detectable evaporation from the lake leading toward more enriched isotope compositions than the integrated source signal. Overall, the findings suggested that Lake Poso remains relatively resilient to anthropogenic land use and related nutrient and pollutant inputs. However, ongoing alterations to its hydrological balance due to significant changes in land use may drive the lake towards higher trophic levels in the future.

Arctic-boreal lakes of interior Alaska dominated by contemporary carbon

Northern high-latitude lakes are critical sites for carbon processing and serve as potential conduits for the emission of permafrost-derived carbon and greenhouse gases. However, the fate and emission pathways of permafrost carbon in these systems remain uncertain. Here, we used the natural abundance of radiocarbon to identify and trace the predominant sources of methane, carbon dioxide, dissolved inorganic and organic carbon in nine lakes within the Yukon Flats National Wildlife Refuge in interior Alaska, a discontinuous permafrost region with high landscape heterogeneity and susceptibility to climate, permafrost, and hydrological changes. We find that although Yukon Flats lakes primarily process young carbon (modern to 1290 ± 60 years before present), permafrost-derived carbon is present in some of the sampled lakes and contributes, at most, 30 ± 10% of the dissolved carbon in lake surface waters. Apportionment of young carbon and legacy carbon (carbon with radiocarbon age ⩾5000 years before present) is decoupled among the dissolved inorganic and organic carbon species, with methane showing a stronger legacy signature. Our observations suggest that permafrost-thaw-related transport of carbon through Yukon Flats lacustrine ecosystems and into the atmosphere is small, and likely regulated by surficial sediments, permafrost distribution, wildfire occurrence, or masked by contemporary carbon processes. The heterogeneity of lakes across our study area and northern landscapes more broadly cautions against using any one region (e.g. Yedoma permafrost lakes) to upscale their contribution across the pan-Arctic.

Impact of a Severe Dust Event on Diurnal Behavior of Surface Water Temperature in Subtropical Lake Kinneret

Dust impact on lake surface water temperature (SWT) over lakes, located in the Eastern Mediterranean, has not yet been discussed in previous publications. We investigated the effect of an extreme dust intrusion on the diurnal behavior of SWT in Lake Kinneret, appearing from 7–9 September 2015. This was carried out using METEOSAT and in-situ observations of SWT. In the presence of dust, METEOSAT SWT decreased along with increasing dust pollution both in the daytime and nighttime. This contradicted in-situ measurements of SWT at a depth of 20 cm which increased to 1.2 °C in the daytime and to 1 °C in the nighttime, compared to SWT on clear-sky September 6. The in-situ radiometer measurements of upwelling longwave radiation (ULWR) provided us with a criterion for assessing the reliability of METEOSAT and in-situ observations of SWT. Using this criterion, we found that, in the presence of dust, in-situ SWT was in line, whereas METEOSAT SWT contradicted in-situ ULWR. Considering in-situ ULWR is determined by actual SWT, we concluded that, in the presence of dust, in-situ SWT were capable of reproducing Kinneret SWT, while METEOSAT was incapable of doing so. An observed increase in daytime air temperature during the dust intrusion contributed to an increase in daytime Kinneret SWT. In the presence of maximal dust pollution on September 8, atmospheric humidity (ρv) exceeded by 30% that on clear-sky September 6. This increase in ρv was observed in the absence of moisture advection indicating that dust intrusion can cause additional evaporation from Lake Kinneret and, consequently, intensify its drying up.

Attribution of Lake Surface Water Temperature Change in Large Lakes Across China Over Past Four Decades

AbstractLake surface water temperature (LSWT) is a key parameter in lake energy budget and is highly vulnerable to climate change. However, the long‐term trends in LSWT across China and their driving factors remain uncertain. Here, we used a calibrated lake model to simulate LSWT over 1979–2018 for 91 large lakes (>100 km2) across China. Simulations reveal an overall LSWT warming trend (0.040°C yr−1, p < 0.05), but with large spatial variations. The majority of these lakes show significant warming trends (84%, 0.053°C yr−1), while a significant cooling trend is found in the seven lakes in the northwestern Tibetan Plateau (−0.064°C yr−1). LSWT of approximately 42% of the lakes increases more rapidly than the corresponding ambient air temperature. Regionally, the warming trend is highest for lakes in the Eastern Plain (0.049°C yr−1) and the lowest in the Yunnan‐Guizhou Plateau (0.016°C yr−1). The increases in simulated LSWT also vary across seasons, with a higher rate in winter and spring than in summer and autumn. Changes in air temperature, downward longwave radiation, and wind speed are the most important climatic drivers for LSWT changes. Lake surface warming could be more rapid under future global warming, necessitating greater attention to lake‐atmosphere interactions.

Assessing the soil salinity vulnerability and groundwater quality variations due to drying up of the lake.

Shrinkage of lakes is considered a serious ecological challenge. The impact of this phenomenon on the environment can be devastating. Monitoring the spatiotemporal variations of lake's water surface and its salinization is essential for planning and adopting mitigation measures. In this study, a new multiscale-kernel-based method was used to assess the spatiotemporal variations of the shrinkage of the Urmia Lake and develop soil salinity vulnerability map for its basin. For this aim, remote sensing, empirical wavelet transform (EWT), differential symbolic entropy (DSE), and Gaussian regression process (GPR) techniques were used. Vulnerable areas were identified using geo-environmental parameters extracted from the in situ observations and satellite datasets. In the next step, considering three time periods including the lake normal period, lake drying period, and lake restoration period, the variations in the quality of groundwater were investigated. Results showed that the east and south sections of the lake were more prone to severe salinization. Saline lands caused negative impacts on air quality and agricultural activities in these areas. It was found that both climate change and human activities had contributed to the shrinking of the lake. Results showed that the quality of groundwater in the area around the lake has been affected by the excessive salinity of the lake water and the encroachment process of saline water. The water quality index has increased during the drying period of the lake and caused negative effects on the quality of water used for drinking and agricultural activities. In the lake restoration period, a slight increase in water quality was observed.

Controlling Factors of Organic-Rich Lacustrine Shale in the Jurassic Dongyuemiao Member of Sichuan Basin, SW China

Organic-rich continental shale, widespread in the Sichuan Basin during the deposition of the Jurassic Dongyuemiao Member (J1d), is considered the next shale hydrocarbon exploration target in southern China. To identify a shale gas sweetspot and reduce exploration risk, it is of great significance to determine the organic matter (OM) enrichment mechanism of J1d shale. In this study, based on sedimentological characteristics and organic matter content, high-resolution major and trace elements were systematically analyzed to demonstrate terrigenous influx, paleoredox, paleosalinity, paleoproductivity, and paleoclimate. The 1st section interval of the J1d 1st submember is dominated by shallow lake subfacies, while the other intervals have the characteristic of semideep to deep lake subfacies. The 1st submember interval of J1d lacustrine shale is characterized by the warmest-humid paleoclimate, strongest weathering degree, highest terrigenous input, moderate paleoproductivity, and paleoredox condition. Within the Dongyuemiao 1st submember, the 4th section interval has the highest paleoproductivity and the most oxygen-deficient condition in bottom water. During the deposition period of the 2nd submember, the sedimentary environment turned to a cold-dry paleoclimate, weak weathering degree, low terrigenous input, low paleosalinity, and high paleoproductivity. Under the background of semideep and deep lake, the terrigenous OM input plays the most critical role in controlling OM enrichment. Moreover, the high primary productivity of lake surface water and the suboxic condition of lake bottom water contribute to the formation of relatively higher TOC lacustrine shale interval in the 4th section of 1st submember.

Multi-decadal change in summer mean water temperature in Lake Konnevesi, Finland (1984–2021)

Depth-resolved water temperature data on the thermal environment of lakes are often hindered by sparse temporal frequency, limited depth resolution, or short duration that create many challenges for long-term analysis. Where high frequency and depth-resolved data exist, they can provide a wealth of knowledge about how lakes are responding to a changing climate. In this study, we analyzed around 950 profiles of summer mean water temperature (July to September), which includes about 30,600 unique observations, from a subarctic lake (Lake Konnevesi, Finland) to understand the changes in lake surface water temperature (LSWT), lake deepwater temperature (LDWT), and lake volumetrically weighted mean temperature (LVWMT) from 1984 to 2021. Statistical analysis of this dataset revealed a substantial warming of LSWT (0.41 °C decade−1) and LVWMT (0.32 °C decade−1), whilst LDWT remained unchanged (0.00 °C decade−1). Our analysis using a generalized additive model suggested the inter-annual variability in LSWT and LVWMT correlated significantly with the upward trends of summer mean air temperature and solar radiation, but suggested no significant effect of observed changes in ice departure dates and near-surface wind speed. None of the investigated predictors correlated with the change in the LDWT. Due to the variable response of lake surface and bottom water temperature to climate change in this subarctic lake, our data suggest a substantial increase in lake thermal stability. Our study supports the growing literature on lake thermal responses to climate change, and illustrates the unique contrast of climate change impacts at the surface and at depth in lake ecosystems, with deep waters acting as a potential thermal refuge to aquatic organisms within a warming world.

Nutrient and environmental factors regulating western Lake Erie cyanobacterial blooms

Abstract Over the past two decades, western Lake Erie has experienced recurring summer cyanobacterial blooms that pose severe negative impacts on human, animal, and ecological health. Previous research has identified a strong correlation between annual cyanobacterial bloom intensity and preceding spring (March-July) phosphorus loading from the Maumee river, the largest tributary to western Lake Erie, which is used to predict upcoming summer bloom severity. Maumee river spring phosphorus load, however, does not explain all the variation of bloom severity between years. Considering additional environmental parameters may help to better capture the physical and biogeochemical processes that regulate bloom severity, eventually leading to improved cyanobacterial forecasts which serve as an early warning for Lake Erie stakeholders. We aggregated various environmental parameters that may influence western Lake Erie cyanobacterial blooms to examine these factors as potential predictors for annual bloom severity. These included nitrogen and phosphorus loading from the Maumee river, freshwater discharge from the primary rivers and tributaries (Detroit, Huron, Raisin, Maumee, and Portage rivers), seasonal lake surface water temperature (mean winter, spring, and summer temperature), and Lake Erie winter ice extent and duration from 2002-2022. Empirical model results show that spring phosphorus loading, as total bioavailable phosphorus, from the Maumee river remains the dominant environmental factor controlling cyanobacterial blooms. However, additional environmental factors, such as Maumee river winter phosphorus loads and Lake Erie winter ice extent and timing, are likely important in modulating bloom severity, particularly in years with moderate phosphorus loads. Finally, we suggest incorporating mechanistic or rule-based models, in addition to empirical models, to better understand and predict annual cyanobacterial bloom severity. The updated models not only improve seasonal forecast accuracy which provides advanced warning of bloom severity to Lake Erie stakeholders, but also helps identify which factors we can better manage to reduce the frequency of severe blooms.

Polymer Characterization of Submerged Plastic Litter from Lake Tahoe, United States.

Monitoring plastic litter in the environment is critical to understanding the amount, sources, transport, fate, and environmental impact of this pollutant. However, few studies have monitored plastic litter on lakebeds which are potentially important environments for determining the fate and transport of plastic litter in freshwater basins. In this study, a self-contained underwater breathing apparatus was used for litter collection at the lakebed along five transects in Lake Tahoe, United States. Litter was brought to the surface and characterized by litter type. Plastic litter was subsampled, and polymer composition was determined using attenuated total reflection Fourier transform infrared spectroscopy. The average plastic litter from the lakebed for the five dive transects was 83 ± 49 items per kilometer. The top plastic litter categories were other plastic litter (plastic litter that did not fall in another category), followed by food containers, bottles <2 L, plastic bags, and toys. These results are in line with prior studies on submerged litter, and intervention approaches or ongoing education are needed. The six polymers most frequently detected in the subsamples were polyvinyl chloride, polystyrene/expanded polystyrene, polyethylene terephthalate/polyester, polyethylene, polypropylene, and polyamide. These observations reflect global plastic production and microplastic studies from lake surface water and sediments. We found that some litter subcategories were primarily comprised of a single polymer type, therefore, in studies where the polymer type cannot be measured but litter is categorized, these results could provide an estimate of the total polymer composition for select litter categories.

A novel optimized model based on NARX networks for predicting thermal anomalies in Polish lakes during heatwaves, with special reference to the 2018 heatwave

In 2018, Europe experienced one of the most severe heatwaves ever recorded. This extreme event's impact on lake surface water temperature (LSWT) in Polish lakes has largely remained unknown. In this study, the impact of the 2018 European heatwave on LSWT in 24 Polish lakes was investigated based on a long-term observed dataset (1987–2020). To capture the LSWT dynamics during the heatwave period and reproduce lake heatwaves, a novel BO-NARX-BR model was developed and evaluated. This model combines the capabilities of the Nonlinear Autoregressive network with Exogenous Inputs (NARX) neural network, the Bayesian Optimization (BO) algorithm for optimizing the number of NARX hidden nodes and lagged input/target values, and the Bayesian Regularization (BR) backpropagation algorithm for the NARX training. The results showed that from April to October 2018, the mean and maximum LSWTs were 2.35 and 3.38 °C warmer than the base-period average (1987–2010) due to the impact of the extreme heatwave. The NARX-based model outperformed another widely used model called air2water in calibration and validation periods. The results also revealed that the BO-NARX-BR model produced significantly better results in capturing lake heatwaves, with computed duration and intensity of lake heatwaves close to the in-situ data. Additionally, LSWT anomaly significantly impacted the duration and intensity of heatwaves that occurred in lakes. Extreme climatic events are gaining increasing importance for the functioning of various elements of the hydrosphere. Such a situation encourages the search for more accurate methods and tools for their prediction. The model applied in the paper corresponds with these assumptions, and its good performance allows for its adaptation to lakes in other regions.

How Do Extreme Lake Water Temperatures in Poland Respond to Climate Change?

Lakes are vital components of the Earth’s hydrological cycle and are susceptible to the impacts of climate change. Understanding the changes in terms of minimum and maximum lake surface temperatures is crucial for assessing the effects of climate change on freshwater ecosystems. This study focuses on ten lakes in Poland to investigate the impacts of climate change on lake temperatures in different geographical regions. The Mann–Kendall (MK) and Sen tests were employed to analyze trends and changes in minimum and maximum water temperatures, respectively. The results reveal significant increases in the minimum and maximum temperatures, particularly in May and June. Different lakes exhibit varying trends and variability in temperature changes over time, indicating the vulnerability of these ecosystems. The current study also examines the magnitude of annual temperature changes and classifies them into different levels. This analysis highlights the complex relationship between air temperature, seasonal cycles, and lake morphometric characteristics in shaping variations in lake surface water temperature. These findings contribute to understanding the impacts of climate change on Poland’s lakes and provide valuable insights for developing conservation strategies and adaptive measures to protect freshwater resources.

Investigation of Meteorological Effects on Çivril Lake, Turkey, with Sentinel-2 Data on Google Earth Engine Platform

Lakes and reservoirs, comprising surface water bodies that vary significantly seasonally, play an essential role in the global water cycle due to their ability to hold, store, and clean water. They are crucial to our planet’s ecology and climate systems. This study analyzed Harmonized Sentinel-2 images using the Google Earth Engine (GEE) cloud platform to examine the short-term changes in the surface water bodies of Çivril Lake from March 2018 to March 2023 with meteorological data and lake surface water temperature (LSWT). This study used the Sentinel-2 Level-2A archive, a cloud filter, the NDVI (normalized difference vegetation index), NDWI (normalized difference water index), MNDWI (modified NDWI), and SWI (Sentinel water index) methods on lake surfaces utilizing the GEE platform and the random forests (RFs) method to calculate the water surface areas. The information on the water surfaces collected between March 2018 and March 2023 was used to track the trend of changes in the lake’s area. The seasonal (spring, summer, autumn, and winter) yearly and monthly changes in water areas were identified. Precipitation, evaporation, and temperature are gathered meteorological parameters that impact the observed variation in surface water bodies for the same area. The correlations between the lake area reduction and the chosen meteorological parameters revealed a strong positive or negative significant association. Meteorological parameters and human activities selected during different seasons, months, and years have directly affected the shrinkage of the lake area.

Improvements and Evaluation of the FLake Model in Dagze Co, Central Tibetan Plateau

FLake has been one of the most extensively used lake models in many studies for lake thermal structure simulations. However, due to the scarcity of lake temperature observations, its applicability and performance on lakes over the Tibetan Plateau are still poorly investigated, especially in small- to medium-sized lakes. In this study, based on water profile observations in Dagze Co, a medium-sized lake on the central Tibetan Plateau, the sensitivity of lake thermal features to three key parameters in FLake was investigated. The performance of FLake in reproducing the lake thermal features was evaluated and improved by optimizing these key parameters. The results showed that the FLake model with default parameter settings can generally reproduce the thermal features of Dagze Co, but there are still significant deviations compared to observation. The sensitive experiments demonstrated that the thermal structure of the lake obviously responds to the change in the water extinction coefficient (Kd), friction velocity (u*), and ice albedo (αice). Based on previous studies and sensitive experiments, the three key parameters were set to the optimized value, which substantially improved the performance of FLake. The values of bias and RMSE of simulated lake surface water temperature decreased from 3.08 °C and 3.62 °C to 2.0 °C and 2.48 °C after parameter optimization. The integration of a simple salinity scheme further improved the ability of FLake to reproduce the observed thermal features of Dagze Co. These results will improve our understanding of thermal processes in lakes on the Tibetan Plateau, as well as the applicability of lake models.

Lake Ice Simulation and Evaluation for a Typical Lake on the Tibetan Plateau

This study aims to simulate the lake ice conditions in the Nam Co lake using a lake ice model, which is a one-dimensional physics-based model that utilizes enthalpy as the predictor variable. We modified the air density schemes within the model to improve the accuracy of the lake ice simulation. Additionally, the process of lake ice sublimation was included, and the effect of lake water salinity on the freezing point was considered. Using the improved lake ice model, we simulated lake surface water temperature, lake ice thickness, and interannual variations in lake ice phenology, and we compared these results with observations at Nam Co. The results demonstrate that the improved model better reproduces the lake surface water temperature, lake ice thickness, and lake ice phenology at Nam Co. Additionally, the thin air density affects lake processes by weakening sensible heat and latent heat, which ultimately leads to a delayed ice-on date and a slightly earlier ice-free date in Nam Co. This study contributes to an enhanced understanding of the freeze–thaw processes in Nam Co and reduces the biases in lake ice simulation on the Tibetan Plateau through the lake model improvement.

Investigating the warming effect of urban expansion on lake surface water temperature in the Dianchi lake watershed

Study regionDianchi lake (DCL) watershed, located in southwestern China, has undergone significant urbanization. Study focusDue to the accelerating urbanization in the watershed, the influence of urban expansion on lake surface water temperature (LSWT) has become increasingly significant. However, there is currently no quantitative study on the specific warming value of LSWT caused by urban expansion. This study primarily quantifies the increase in LSWT caused by urban expansion from two perspectives: the rise in near-surface air temperature (NSAT) resulting from urban expansion and the thermal runoff generated by urban expansion. New hydrological insights for the regionWe found that the DCL watershed experienced significant urban expansion between 2001 and 2018. In this context, the cumulative increase in LSWT caused by the newly added impervious surface (IS) through NSAT is about 0.25 °C. The cumulative warming of the newly added IS on the LSWT through thermal runoff is about 0.05–0.06 °C. Urban expansion mainly affects the LSWT by increasing the NSAT.

Lake Heatwaves and Cold‐Spells Across Qinghai‐Tibet Plateau Under Climate Change

AbstractLake heatwaves (LHWs) and cold‐spells (LCSs), similar to marine heatwaves and cold‐spells, can have long‐term impacts on lake ecosystems and are vulnerable to climate change. Here we first comparatively assess LHW and LCS changes across the Qinghai‐Tibet Plateau (QTP) using satellite surface water temperature observations in 160 lakes over 1978–2017. Our findings reveal notable differences in the mean and trends of LHW and LCS metrics. Specifically, total days and frequency of LHW have been increasing at a rate of 8.82 ± 1.25 days per decade and 0.78 ± 0.10 counts per decade, respectively. Conversely, total days and frequency of LCS have decreased at −6.52 ± 1.46 days per decade and −0.51 ± 0.01 counts per decade, respectively. However, average duration and mean intensity show no significant difference. Additionally, the average duration of ice cover across the QTP has been decreasing (−2.60 ± 0.38 days per decade) due to the delayed freezing date (1.13 ± 0.18 days per decade) and earlier thawing date (−1.28 ± 0.27 days per decade) during 1978–2017. Furthermore, the annual mean lake surface water temperatures across the QTP exhibit a warming trend (0.00 ∼ 0.47°C per decade) from 1978 to 2017, with faster warming occurring in winter (0.00 ∼ 0.98°C per decade) compared to summer (−0.17 ∼ 0.47°C per decade). Accelerated lake warming will increase the frequency and mean intensity of LHWs while decreasing the number of LCSs. These results help to understand how QTP lakes respond to extreme temperatures under climate change.

Modelling Heat Balance of a Large Lake in Central Tibetan Plateau Incorporating Satellite Observations

The thermodynamics of many lakes around the globe are shifting under a warming climate, affecting nutrients and oxygen transportation within the lake and altering lake biota. However, long-term variation in lake heat and water balance is not well known, particularly for regions like the Tibetan Plateau. This study investigates the long-term (1963–2019) variation in the heat balance of a large lake in the Tibetan Plateau (Nam Co) by combining the strengths of modeling and remote sensing. Remotely sensed lake surface water temperatures from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Along Track Scanning Radiometer Reprocessing for Climate: Lake Surface Water Temperature and Ice Cover (ARC-Lake) are used to calibrate and validate a conceptual model (air2water) and a thermodynamic model (LAKE) for the studied lake, for which in situ observation is limited. The results demonstrate that remotely sensed lake surface water temperature can serve as a valuable surrogate for in situ observations, facilitating effective calibration and validation of lake models. Compared with the MODIS-based lake surface water temperature (LSWT) for the period 2000–2019, the correlation coefficient and root mean square error (RMSE) of the LAKE model are 0.8 and 4.2 °C, respectively, while those of the air2water model are 0.9 and 2.66 °C, respectively. Based on modeling, we found that the water temperature of Nam Co increased significantly (p &lt; 0.05) during the period of 1963–2019, corresponding to a warming climate. The rate of water temperature increase is highest at the surface layer (0.41 °C/10a). This warming trend is more noticeable in June and November. From 1963 to 2019, net radiation flux increased at a rate of 0.5 W/m2/10a. The increase in net radiation is primarily responsible for the warming of the lake water, while its impact on changes in lake evaporation is comparatively minor. The approaches developed in this study demonstrate the flexibility of incorporating remote sensing observations into modeling. The results on long-term changes in heat balance could be valuable for a systematic understanding of lake warming in response to a changing climate in the Tibetan Plateau.

Microplastic pollution in Kolavai Lake, Tamil Nadu, India: quantification of plankton-sized microplastics in the surface water of lake.

The prevalence of microplastics (MP) (< 5 mm) in aquatic habitats has recently raised concerns owing to their influence on humans and aquatic organisms, as they absorb organic pollutants and pathogens from the surrounding media because of their higher surface-to-volume ratio. Freshwater systems are severely affected by the increased intake of discarded waste from diverse sources. This study focused on the microplastic-to-zooplankton ratio and its potential impact on the environment's food chain. The sampling sites of Kolavai Lake were divided into three zones (18 stations) to investigate the spatial distribution of microplastics and zooplankton biota. The average microplastic abundance was 6.1 ± 2.5 particles/L. Fourier transform infrared spectroscopy (FTIR) and SEM analysis were performed to understand the chemical composition and surface morphology of microplastics. Water samples collected along the Central and Southern Zones revealed a high abundance of microplastics, which might be due to anthropogenic activities. A negative correlation was observed between the abundance of microplastics and zooplankton. The microplastic-to-zooplankton ratio was found to range from 0.05 to 0.74. Furthermore, the impact of microplastics in the lake ecosystem was analysed using the size and shape descriptors for both zooplankton and microplastics. These findings suggest that microplastics built up in aquatic environments, particularly those with rich biota, could be a severe concern because of their capacity to infiltrate the food web.