Morphological study of lakes defines the sensitivity of their watershed. Moreover, it plays important role in safeguarding the lake’s ecosystem services through proper planning and utilization of the lakes’ resources. In the last few decades, the morphology of lakes in Ethiopian and Kenyan Rift (EKR) valley are experiencing contradicting morphological changes. Being in the same system, some are shrinking and others are expanding beyond their natural boundaries. The objective of this review is to shed light on the trends in spatio-temporal water level fluctuation and their contributing factors for lakes to the academia and decision makers. Peer reviewed article journals, conference proceedings, thesis, and book chapters collected from online sources and supplied by authors on request formed a database of 346 documents where 226 are critically assessed. The review indicated that lakes in Ethiopian rift are shrinking and expanding, while Kenyan lakes are expanding. The en-dorheic lakes suffered the most fluctuations due to anthropogenic factors at the expense of loss of forest and woodlands in their watershed. While the lakes’ water quality related to the morphological changes are given less attention, the predicted 12 m drop of Lake Turkana due to projects in the Omo catchment did not materialize.

Large water bodies such as the Laurentian Great Lakes have significant influences on local and regional climate through their unique physical features. Due to the coarse spatial resolution of general circulation models (GCMs), the Great Lakes are geometrically ignored in most GCMs. Thus, the dynamical downscaling technique serves as a necessary and feasible solution to bridge the gap. The Weather Research and Forecasting model (WRF) with an updated lake scheme is employed to downscale from a GCM, GFDL-CM3. The WRF-Lake’s performance is evaluated against observations, the GCM, as well as 23 other GCMs. Results show that the coupled air-lake model, with a fine spatial resolution and realistic lake bathymetries, reproduced a more reasonable spatiotemporal climatology than GCMs, as well as the lake-induced characteristics that were missed in GCMs. With lakes present, the seasonal variability of air temperature was reduced in WRF-Lake relative to GFDL-CM3, especially in summer. A reduced air temperature trend, about 4.5 °C/100 year in the 21st century, was projected in WRF-Lake. The seasonal evolutions of lake surface temperature and lake ice coverage were well captured by the lake model. The lake surface temperature was projected to be warming by 3.5-4 °C and the lake ice diminishing by 58.9% - 86%. Those results brought by the WRF-Lake model suggest that a fine resolution of the topography and the incorporation of the lake-atmosphere interactions are crucial to improve the understanding of the climate and climate change in the Great Lakes region.

Aquatic ecosystems are often subject to degradation due to various environmental stressors. The accumulation of an organic sediment layer causes shallowing, algal blooms, and hypertrophy in water reservoirs. The processes of overgrowth and shallowing lead to a reduction in the ecosystem services provided by the reservoir as well as may potentially cause the disappearance of the water body. To address these challenges and restore the ecological balance of water reservoirs, effective and sustainable revitalisation methods are essential. In recent years, biotechnological approaches, particularly utilizing microbiological interventions, have emerged as promising strategies for water reservoir revitalization. Microorganisms, with their remarkable ability to degrade pollutants and enhance nutrient cycling, offer great potential in remediating environmental issues in a natural and eco-friendly manner. The article presents the results of a study of 34 Polish reservoirs subjected to reclamation with microbial biopreparations from 2014 to 2023. The results of changes in bottom sediment reduction, water transparency, dissolved oxygen concentration, and water turbidity are presented. Reduction of and morphological changes in the fraction of soft organic sediments, an improvement in the oxygen profile of the bottom and surface water layers, and an increase of water transparency were observed after the reclamation with the use of biopreparations.

Environmental physical and chemical factors controlling the abundance and biodiversity of zooplankton in permafrost-affected lakes are poorly known yet they determine the response of the ecosystems to on-going climate change and water warming. Here we assessed the current status of zooplankton communities of lake ecosystems in the North-West of the Bolshezemelskaya tundra (Nenets Autonomous district), and provide new information about the composition and structure of zooplankton. Results demonstrate that the structure of zooplankton communities is influenced by morphometric features of lakes and the degree of their overgrowth by macrophytes. According to the level of zooplankton development, most tundra lakes were of the oligotrophic type with an average biomass of up to 1 g/m3. The largest number of species was observed in zooplankton communities of small lakes with an area of up to 0.02 km2 and overgrown with macrophytes. The analysis of factors that influence the formation of the lakes zoocenosis demonstrated that the species composition and quantitative characteristics of zooplankton are chiefly controlled by pH and water mineralization. A comparison of the results obtained with the literature data on the lakes of this region collected 60 years ago confirms that the ecosystems of the studied lakes are in a stable state. Overall, these new insights will improve our knowledge of factors controlling the zooplankton spatial dynamics in unique but quite abundant thermokarst lakes of NE European Tundra, subjected to on-going climate warming.

Upland lakes (ULs) of the Carajás, southeastern Amazonia, have been intensively studied to their evolution during the Quaternary, as well as the development of the associated biota. In this review, several classical and modern approaches from structural geology to the pollen rain and sedimentary data which cover an area of around 41,300 km² were compiled. Multi-elemental geochemistry indicates that the detrital sediments derived from weathered crusts and soils, while the sedimentary organic matter represent autochthonous (siliceous sponge spicules, algae, macrophytes) and allochthonous (C3 plants and freshwater DOC) sources. Modern pollen rain suggests that even small lakes and canga areas can reflect forest signal, which depends on the topographic control and prevailing wind direction on pollen deposition. Integrated data of the sedimentary cores indicate that the active lakes never dried up during the last 50 ka cal BP. However, subaerial exposure occurs on filled lakes such as ST02 Lake during the LGM, LB3 and R2 lakes at the mid-Holocene due to drier paleoclimate conditions. Considering the organic proxies, only LB3 Lake presents expansion of C4 canga (montane savanna) plants since ULs of the Serra da Bocaína does not present siderites. Siderite formation on ULs deposits also points to drier paleoenviromental conditions, interrupting predominantly wet conditions. However, there is no evidence for widespread expansion of savanna into Southeastern Amazonia during the late Pleistocene and Holocene.

We have used Daphnia cucullata as a model organism for the first time in the four deepest Latvian lakes from the Boreal biogeographical region lakes in order to find the genetic diversity of Daphnia cucullata populations. During the research, the most appropriate microsatellite markers for future genetic studies of Daphnia cucullata populations in Boreal biogeographical region lakes. It was the loci Dgm105 and Dgm101, in which the maximum number of alleles and the maximum number of private alleles were found. The Dgm105 locus had five private alleles (62% of all detected alleles), while the Dgm101 locus had four private alleles (57% of all detected alleles) in these loci. We was determined the observed heterozygosity (Hobs) and the expected heterozygosity (Hexp) level (by Hardy-Weinberg), the number of polymorphic loci, the number of detected alleles in each analyzed microsatellite locus, the average number of alleles at the locus (Na), the average effective number of alleles at the locus (Ne), FST of the population genetic differentiation, the genetic distance (D) (by Nei) and significance (χ2- test) of differences between the levels of observed and expected heterozygosity. It was shown that Daphnia cucullata populations from lakes with a low number of zooplankton taxa (Riča and Geraņimovas-Ilzas) have a higher genetic diversity compared to lakes with a high number of zooplankton taxa (Dridzis and Svente) in lakes. It was found, that Daphnia cucullata populations from lakes Dridzis and Svente have the least genetic distance and these populations form a single genetic group, as confirmed by clustering

Artemia (brine shrimp), holds significant value as a live feed for larval fish and crustaceans, owing to their distinctive dietary requirements. However, it is vital to acknowledge that Artemia also carries potential risk as a vector of infection. We conducted a metagenomic analysis to explore the virome present in Artemia cysts collected from inland salt lakes across four distinct regions in Kazakhstan. The study identified the presence of dsDNA phages and RNA virus sequences, with a predominant representation from the Reoviridae, Nodaviridae, Dicistroviridae, Picornaviridae, Astroviridae, Tombusviridae, and Solemoviridae families. In general, this study has significantly enhanced our understanding of the virome of Artemia cysts in the saline lakes of Kazakhstan. It has also furnished crucial insights for the identification, surveillance, and management of viral infections that impact brine shrimp and fish species populations.

Monitoring lakes in high-latitude areas can provide a better understanding of freshwater systems sensitivity and accrete knowledge on climate change impacts. Phytoplankton are sensitive to various conditions: warmer temperatures, earlier ice-melt and changing nutrient sources. Satellite imagery can monitor algae biomass over large areas. The detection of chlorophyll a (chl-a) concentrations in small lakes is hindered by the low spatial resolution of conventional ocean colour satellites. The short time-series of the newest generation of space-borne sensors (e.g. Sentinel-2) is a bottleneck for assessing long-term trends. Although previous studies have evaluated the use of high-resolution sensors for assessing lakes' chl-a, it is still unclear how the spatial and temporal variability of chl-a concentration affect the performance of satellite estimates. We discuss the suitability of Landsat (LT) 30-m resolution imagery to assess lakes' chl-a concentrations under varying trophic conditions, across extensive high-latitude areas in Finland. We use in situ data obtained from field campaigns in 19 lakes and generate remote sensing estimates of chl-a, taking advantage of the long-time span of the LT 5 and 7 archives, from 1984 to 2017. Our results show that linear models based on LT data can explain approximately 50 % of the chl-a interannual variability. However, we demonstrate that the accuracy of the estimates is dependent on the lake's trophic state, with models performing in average twice as better in lakes with higher chl-a concentration (> 20 µg/l) in comparison with less eutrophic lakes. Finally, we demonstrate that linear models based on LT data can achieve high accuracy (R2 = 0.9; p-value < 0.05) in determining lakes' annual mean chl-a concentration, allowing the mapping of the trophic state of lakes across large regions. Given the long time-series and high spatial resolution, LT-based estimates of chl-a provide a tool for assessing the impacts of environmental change.

Towards better understanding of factors controlling carbon (C) exchange between inland waters and atmosphere, we addressed inorganic carbon cycle in semi-arid lakes of Central Eurasia, subjected to strong impact of on-going climate change. For this, we assessed the hydrochemical vari-ability and quantified its control on formation of authigenic carbonate minerals, occurring within the upper layer of sediments in 43 semiarid lakes located in the southwest of Western Siberia (Central Eurasia). Based on measurements of pH, total dissolved solids (TDS), cationic and anionic composition, dissolved organic and inorganic C, as well as textural and mineralogical characterization of bottom sediments using X-ray diffraction and scanning electron microscopy, we demonstrate that lake water pH and TDS are primarily controlled by both lithological and climatic context of the lake watershed. We have not revealed any direct relationships between lake morphology and water chemistry. The most common authigenic carbonates scavenging atmospheric CO2 in the form of insoluble minerals in lake sediments were calcite, aragonite, Mg-calcite, dolomite and hydro-magnesite. The calcite was the most common component, aragonite mainly appears in lakes with sediments enriched in gastropod shells or artemia cysts, while hydromagnesite was most common in lakes with high Mg/Ca molar ratios, as well at high DIC concentrations. The relationships between mineral formation and water chemistry established in this study can be generalized to a wide suite of arid and semi-arid lakes in order to characterize current status of inorganic C cycle and predict its possible modification under on-going climate warming such as water temperature rise and change of hydrological connectivity, primary productivity and nutrient regime.

In this study, a new approach for estimating volume variations of lakes and reservoirs using water levels from satellite altimetry and surface areas from optical imagery is presented. Both input data sets, namely water level time series and surface area time series, are provided by DGFI-TUM‘s Database of Hydrological Time Series of Inland Waters (DAHITI). The approach is divided into three parts. In the first part, a hypsometry model based on the new modified Strahler approach is computed by combining water levels and surface areas. The hypsometry model describes the dependency between water levels and surface areas of lakes and reservoirs. In the second part, a bathymetry between minimum and maximum surface area is computed. For this purpose, DAHITI land-water masks are stacked using water levels derived from the hypsometry model. Finally, water levels and surface areas are intersected with the bathymetry to estimate a time series of volume variations in relation to the minimum observed surface area. The results are validated with volume time series derived from in-situ water levels in combination with bathymetric surveys. In this study, 28 lakes and reservoirs located in Texas are investigated. The absolute volumes of the investigated lakes and reservoirs vary between 0.099 km³ and 6.448 km³. The correlation coefficients of the resulting volume variation time series with validation data vary between 0.80 and 0.99. Overall, the relative errors with respect to volume variations vary between 2.8% and 14.9% with an average of 8.3% for all 28 investigated lakes and reservoirs. When comparing the resulting RMSE with absolute volumes, the absolute errors vary between 1.5% and 6.4% with an average of 3.1%. This study shows that volume variations can be calculated with a high accuracy which depends essentially on the quality of the used water levels and surface areas. In addition, this study provides a hypsometry model, high-resolution bathymetry and water level time series derived from surface areas based on the hypsometry model. All data sets are publicly available on the Database of Hydrological Time Series of Inland Waters (DAHITI, https://dahiti.dgfi.tum.de).

Current numerical methods for simulating biophysical processes in aquatic environments are typically constructed in a grid-based Eulerian framework or as an individual-based model in a particle-based Lagrangian framework. Often, the biogeochemical processes and physical (hydrodynamic) processes occur at different time and space scales, and changes in biological processes do not affect the hydrodynamic conditions. Therefore, it is possible to develop an alternative strategy to grid-based approaches for linking hydrodynamic and biogeochemical models that can significantly improve computational efficiency for this type of linked biophysical model. In this work, we utilize a new technique which links hydrodynamic effects and biological processes through a property-carrying particle model (PCPM) in a Lagrangian/Eulerian framework. The model is tested in idealized cases and its utility is demonstrated in a practical application to Sandusky Bay. Results show the integration of Lagrangian and Eulerian approaches allows for a natural coupling of mass transport (represented by particle movements and random walk) and biological processes in water columns which is described by a nutrient-phytoplankton-zooplankton-detritus (NPZD) biological model. This method is far more efficient than traditional tracer based Eulerian biophysical models for 3-D simulation, particularly for a large domain and/or ensemble simulations.

Nowadays, one of the greatest challenges in Data Meshes revolves around detecting and creating Data Domains and Data Products for providing the ability to adapt easily and quickly to changing business needs. This requires a disciplined approach to identify, differentiate and prioritize distinct data sources according to their content and diversity. The current paper tackles this highly com-plicated issue and suggests a standardized approach that integrates the concept of Data Blueprints with Data Meshes. In essence, a novel standardization framework is proposed that creates Data Products using a metadata semantic enrichment mechanism, the latter also offering Data Domain readiness and alignment. The approach is demonstrated using real-world data produced by mul-tiple sources in a poultry meat production factory. A set of functional attributes is used to compare qualitatively the proposed approach against existing data structures utilized in storage architectures with quite promising results. Finally, experimentation with different scenarios varying in data product complexity and granularity suggests successful performance.

Although sources of seston are much more complicated in lakes compared to marines, the influences of different source on the spatiotemporal variations in seston stoichiometry are still underexplored, especially in large eutrophic floodplain lakes. Here, we investigated the seston stoichiometry across a typical large eutrophic floodplain lake (Lake Taihu) over one year. In addition, we used the n-alkanes proxies for source estimation which are more robust than other elemental indicators (e.g. C: N ratios). Throughout the study, the average value of C: N: P ratio of 143: 19: 1 across Lake Taihu was higher than the classical Redfield ratio, but closed to the synthesized data from other lakes. Generally, seston C: N ratios varied the least across all environments, but C: P and N: P ratios varied widely and shown a significant seasonal pattern with lower ratios of N: P and C: P during senescence seasons and higher ratios in the growing seasons. This seasonal change was mainly associated with the shift from terrestrial-derived seston to algal-derived seston as, the significant lower ratios of terrestrial-derived seston from surrounding agricultural watershed. Spatially, the mean ratios of each site were similar, except relative high values of C: P and N: P ratios in the algal dominated area. Statistically, the predictive power of environmental variables was strongly improved by adding n-alkanes proxies. However, apart from sources indicators, particulate phosphorus (PP) contents also partly explained the spatiotemporal variations in stoichiometric ratios. Nevertheless, the mechanisms behind the dynamics of PP could be totally different and source-specific. This study highlights the priority of using n-alkanes proxies as tools to identify the source of seston which is essential to interpret the spatiotemporal variations in seston stoichiometric ratios among eutrophic floodplain lakes.

Carbon (C) cycle n inland waters, including its concentrations and carbon dioxide (CO2) emis-sions from water surfaces are at the forefront of biogeochemical studies, especially in the re-gions, strongly impacted by on-going climate change. Towards better understanding of C stor-age, transport and emission in Central Asian mountain regions, extremely poorly studied until now, here we carried out systematic measurements of dissolved C and CO2 emissions in 15 riv-ers and 5 lakes located along a macro-transect of various natural landscapes in the Sayan-Altai mountain region, from high mountains of the Western Sayan in the northwest of Tyva to arid (dry) steppe and semi-deserts in intermountain basins of the southeast of Tyva, the border with Mongolia. New data on major hydrochemical parameters, CO2 fluxes by floating chambers, dis-solved organic and inorganic carbon concentrations collected over four main hydrological sea-sons allowed to assess the current C biogeochemical status of these water bodies in order to judge possible future changes under climate warming. We further tested the impact of perma-frost, river watershed size, lake area and climate parameters as well as ‘internal’ biogeochemical drivers (pH, mineralization, organic matter quality and bacterial population) on CO2 concentra-tion and emissions in lakes and rivers of this region, and compared them with available data on other subarctic and mountain settings.

With this article, impact of effluent mixed water with the quality of the Mansagar Lake has been established by evaluating the physico-chemical parameters and the heavy-metal contents experimentally. The process of calculating water quality and the metal pollution quality indices is also explained in brief with respect to selected sample locations and varied environmental conditions (Pre- and Post-Monsoon season). Distribution trends of Pearson‘s correlation factor have also been discussed to establish their relation among the physico-chemical parameters and the heavy-metal contents for varied environmental conditions. In the end, detailed discussion on observations made during this study and useful recommendations are also elaborated in details. With this article, we intend to present a document for better understanding of the water quality of this lake in view of futuristic management strategies to be adopted to maintain it heritage values.

Scientists have observed amyotrophic lateral sclerosis (ALS) disease clusters around certain lakes in the regions of northern New England and northern Ohio. A Parkinson’s disease cluster has also been observed in Vancouver. Cyanobacteria toxin exposure has been considered as a potential risk factor to explain this association. It is reported here that these regions have several commonalities in their environment, including a notable geologic history, the presence of abundant glacial sediments, and possible mineral and bentonite exposures. The possible association with and significance of these risk factors in ALS and Parkinson’s disease is discussed.

Artificial groundwater recharge is commonly used for drinking water supply. The resulting water quality is highly dependent on the raw water quality. In many cases, pre-treatment is required. Pre-treatment improves the drinking water quality, although how and to what extent it affects the subsequent pond water quality and infiltration process, is still unknown. We evaluated two treatment systems by applying different pre-treatment methods for raw water from a eutrophic and temperate lake. An artificial recharge pond was divided into two parts, where one received raw water, only filtered through a micro-screen with 500 µm pores (control treatment), while the other part received pre-treated lake water using chemical flocculation with polyaluminium chloride (PACl) combined with sand filtration, i.e. continuous contact filtration (contact filter treatment). Water quality such as cyanobacterial biomass, microcystin-LR as well as organic matter and nutrients were measured in both treatment processes. We found cyanobacterial biomass and microcystin-LR level after the contact filter treatment was significantly different from the control treatment and also significantly different in the pond water. In addition, with contact filter treatment, total phosphorus (TP) and organic matter removal were significantly improved in the end water, TP was reduced by 96 % (< 20 µg/L) and the total organic carbon (TOC) was reduced by 66 % instead of 55 % (TOC content around 2.1 mg/L instead of 3.0 mg/L). This full-scale onsite experiment demonstrated effective pre-treatment would benefit a more stable water quality system, with less variance and lower cyanotoxin risk. In a broader drinking water management perspective, the presented method is promising to reduce cyanotoxin risk, as well as TP and TOC, which are all predicted to increase with global warming and extreme weather.

The altitude of the habitat is one of the important regulators of species survival. Kaçkar Mountains National Park is located in the Eastern Black Sea region of Turkey. This is the first study on the benthic diatom flora of the high mountain lakes in Kaçkar Mountains National Park, which is situated between 2782 and 3075 m a.s.l. A total of 84 diatom species were identified from benthic communities of 15 habitats in summer (19 July, 28 August) and autumn (10 September) months of 2020. The genus Pinnularia (13 species) formed the basis of the taxonomic list followed by Eunotia (5 species), Navicula (5 species), and Frustulia (4 species) genera, respectively. The waters in all the studied lakes were fresh, low-saline, with low-alkaline or circumneutral pH and organically uncontaminated as evidenced by prevailed bioindicator groups. Statistical methods and comparative floristic results confirm the role of the lake altitude for the diatom species distribution. Species richness was higher in lakes with lower altitude, but a statistical approach also revealed a tendency for it to increase with altitude if species richness increased. Further studies will be needed to continue exploring this pattern. In the first round of analysis, diatom species groups were categorized according to IUCN categories, revealing one potentially threatened and one rare species. To protect studied high mountain lakes, their ecological conditions must be constantly monitored in the Kaçkar Mountains National Park.

Data Meshes is an approach to data architecture and organization that treats data as a product and focuses on decentralizing data ownership and access. It has recently emerged as a field that presents quite a few challenges related to data ownership, governance, security, monitoring, and observability. To address these challenges, this paper introduces an innovative algorithmic framework leveraging data blueprints to enable the dynamic creation of Data Meshes and Data Products in response to user requests, ensuring that stakeholders will have access to specific portions of the Data Mesh as needed. Ownership and governance concerns are addressed through a unique mechanism involving Blockchain and Non-Fungible Tokens (NFTs). This facilitates secure and transparent transfer of data ownership, with the ability to mint time-based NFTs. By combining these advancements with the fundamental tenets of Data Meshes, this research offers a comprehensive solution to the challenges surrounding data ownership and governance. It empowers stakeholders to navigate the complexities of data management within a decentralized architecture, ensuring a secure, efficient, and user-centric approach to data utilization. The proposed framework is demonstrated using real-world data from a poultry meat production factory.