Lake Dynamics Research Articles

Zooplankton egg bank: characterization and effect of biotic factors on hatching

Many zooplankton organisms facing harsh environmental conditions producing resting eggs. Resting eggs accumulate in the sediment and create a resting egg bank. Knowledge on the egg bank structure, morphology and morphometry of the eggs as well as the effect of cues on hatching, contributes to the understanding zooplankton dynamics in lakes. Here we described the composition and structure of zooplankton egg bank from a shallow tropical lake and analyzed the effect of some biotic factors on hatching rates. In order to describe the structure and composition of the resting egg bank, we determined the richness, density, morphology and morphometry of the resting eggs isolated by the sugar flotation method. Diapausing eggs were measured and their external features studied by microphotography under optical microscope and SEM. To analyze the effect of biotic factors on hatching rates, we exposed the resting structures and the entire sediment to three biotic factors: a chlorophyte (Scenedesmus acutus), a cyanobacteria (Microcystis sp.) and a predatory rotifer (Asplanchna girodi). A total of 25 zooplankton species hatched from the sediments. Our results show that the medium density of the healthy-looking diapausing eggs was of 7.6 ± 2 diapausing eggs · cm−3 and that rotifers are the predominant group in the egg bank. Medium conditioned with the chlorophyte and the cyanobacteria resulted in a higher hatching rate. The ornamentations of rotifer diapausing eggs present different features, such as wrinkles and spines, which can help to taxonomic identification without the need of promoting hatching.

ПРОГРАММНО-АЛГОРИТМИЧЕСКИЙ КОМПЛЕКС ПРОГНОЗИРОВАНИЯ ДИНАМИКИ АРКТИЧЕСКИХ ОЗЕР РОССИИ НА ОСНОВЕ СПУТНИКОВЫХ СНИМКОВ И ЭНТРОПИЙНО-РАНДОМИЗИРОВАННОГО ПОДХОДА

The article is devoted to the problem of predicting the evolution of thermokarst lakes in permafrost zones as intensive sources of natural emissions of greenhouse gases into the atmosphere in the Arctic territories. Goal of the work. The purpose of the work was to consider the issues of creating a software-algorithmic complex for predicting the spatio-temporal dynamics of lakes in the Russian Arctic based on methods and algorithms of randomized machine learning. Materials and methods. For forecasting, time series of satellite measurements of the areas of thermokarst lakes in the Arctic zone of Russia and data on the average annual temperature and annual precipitation obtained on the basis of the ERA-5, ERA-Interim, etc. reanalysis systems are used for forecasting. Methods of entropy-randomized dynamics modeling are used fields of thermokarst lakes, allowing to predict changes in the areas of lakes in the Arctic zone. For the software implementation of a complex for predicting the evolution of the area of thermokarst lakes, modern geographic information systems are used. Results. The architecture of the software-algorithmic complex has been developed, based on the use of entropy-randomized modeling algorithms. The software-algorithmic forecasting complex makes it possible to train and test the model based on available historical data on the dynamics of the area of thermokarst lakes and climate changes in the Russian Arctic. Conclusion. The implementation of a software package based on the NextGIS Web geographic information system allows you to include forecasting applications in Python. The developed software package can be used in assessing and forecasting the dynamics of greenhouse gas emissions from lakes, which influence changes in air temperature in the northern regions.

SOCIO-ECONOMIC IMPACTS OF MORPHOLOGICAL DYNAMICS INDICATORS AND ECOLOGICAL CHANGE IN THE FISHERIES OF LAKE NOKOUÉ (SOUTH BENIN)

Lake Nokoué is experiencing serious environmental problems which threaten its existence and contribute to the reduction of goods and services for the beneficiary population. The objective of this study is to understand the dynamics of ecological factors and their impacts on the biocenosis. This study is based on bathymetric data collected in 11 stations on the lake following seasonal sampling from February 2017 to January 2018 and from March 2019 to February 2020. Documentary research, field surveys, interview guides, a camera digital and labeled sachets are the tools and materials used for data collection from 120 households. In addition, images from aerial and satellite photographs of the LANDSAT type (TM and ETM) were used to assess the dynamics of the acadjas of Lake Nokoué. The results were analyzed with the FPEIR model. The results show that from 2000 to 2020 Lake Nokoué experienced an increase in the number of acadja which went from 667 to 1417 or 47.07% followed by a decrease in its depth from West to East of the order of 0.5m. The factors favorable to the filling of Lake Nokoué are according to 70% of the population surveyed: the flood and its solid inputs, the proliferation of water hyacinth in the rainy season and its degeneration in the dry season, the erosion of the banks, the intrusion of marine water and stations with high human and economic densities (implantation and decomposition of acadja, agricultural activities, etc.). These internal and external factors contribute to the morphological dynamics of Lake Nokoué, thus hindering the socio-economic development of populations dependent on Lake Nokoué. Faced with this situation, measures have been proposed for better management of this ecosystem, which is essential to the survival of its population.

Response of Lake Dynamics to Climate Change in the Qilian Mountains from 1990 to 2020

Response of Lake Dynamics to Climate Change in the Qilian Mountains from 1990 to 2020

Remote‐sensing‐based monitoring the dynamics of Kyagar Glacial Lake in the upstream section of Yarkant River, north Karakoram

AbstractLong‐term monitoring of ice‐dammed lakes is important for understanding the process of lake storage, development, and glacial outburst flood (GLOF). Based on remote sensing observations for the period 1972–2020, we obtained what is so far the most detailed reconstruction of the filling and draining of Kyagar Lake, a typical annually ice‐dammed lake in the north Karakoram. We show that annually repeated lake fillings‐drainings were detected by satellite observations during two periods: 1996–2009 and 2015–2020, while between 2009 and 2015 no obvious cycle occurred. These two intermitted periods with regular annual revival of lake outburst were likely related to the long‐term cycle of glacier surge dynamics, namely two remarkable surge‐induced terminus accelerations during 1995–1997 and 2014–2016. Following each surge, the maximum lake areas decreased by about 33% from 1996 to 2009 and by about 88% from 2015 to 2020. Combined with climatic warming and the thinning of the ice‐dam, the storage capacity of Kyagar Lake will likely continue to decrease in the future, and the risk of lake outburst flood thus becomes lower. Repeated drainage following filling exacerbates the depletion of mass at the glacier terminal, leading to the cessation of storage and creating the conditions for the next glacial surge to occur, creating a long‐term iteration of the surge process. Considering the uncertainty and intensified climate changes, it suggests that a close monitoring of the glacial lake development and glacier dynamics would be still important.

Greenhouse gas emissions from Daihai Lake, China: Should eutrophication and salinity promote carbon emission dynamics?

Greenhouse gases (GHGs) emitted or absorbed by lakes are an important component of the global carbon cycle. However, few studies have focused on the GHG dynamics of eutrophic saline lakes, thus preventing a comprehensive understanding of the carbon cycle. Here, we conducted four sampling analyses using a floating chamber in Daihai Lake, a eutrophication saline lake in Inner Mongolia Autonomous Region, China, to explore its carbon dioxide (CO2) and methane (CH4) emissions. The mean CO2 emission flux (FCO2) and CH4 emission flux (FCH4) were 17.54 ± 14.54 mmol/m2/day and 0.50 ± 0.50 mmol/m2/day, respectively. The results indicated that Daihai Lake was a source of CO2 and CH4, and GHG emissions exhibited temporal variability. The mean CO2 partial pressure (pCO2) and CH4 partial pressure (pCH4) were 561.35 ± 109.59 µatm and 17.02 ± 13.45 µatm, which were supersaturated relative to the atmosphere. The regression and correlation analysis showed that the main influencing factors of pCO2 were wind speed, dissolved oxygen (DO), total nitrogen (TN) and Chlorophyll a (Chl.a), whereas the main influencing factors of pCH4 were water temperature (WT), Chl.a, nitrate nitrogen (NO3−-N), TN, dissolved organic carbon (DOC) and water depth. Salinity regulated carbon mineralization and organic matter decomposition, and it was an important influencing factor of pCO2 and pCH4. Additionally, the trophic level index (TLI) significantly increased pCH4. Our study elucidated that salinity and eutrophication play an important role in the dynamic changes of GHG emissions. However, research on eutrophic saline lakes needs to be strengthened.

Lake dynamics in an Early Jurassic desert: Evidence from the Clarens Formation in southern Africa

ABSTRACTInterdune deposits are sensitive to climatic fluctuations and ancient interdune lacustrine systems can reveal the drivers of erg dynamics through time and space. This southern African study details the dynamics of interdune deposition in a vast ancient desert system that was active over Pangaea in the Middle Mesozoic and formed part of one of the largest known sand seas in Earth's history. Focusing on the Sinemurian to Pliensbachian Clarens Formation in the main Karoo Basin (south‐west Gondwana), three facies associations were identified that formed in meso‐scale and macro‐scale lakes amongst aeolian dunes and sand sheets of the Clarens erg system. The northern facies association is restricted to interdune hollows within an actively climbing dune system. High‐sediment availability and high‐wind speeds limited the space available for these meso‐scale lakes to expand. Here, migrating dunes outpaced the water table rise promoting the formation of discontinuous lenses of lake deposits, as is typical in erg centres. The southern facies associations developed both in spatially isolated meso‐scale lakes, where flooding was controlled by groundwater inundation (water table rise), as well as in macro‐scale lakes, where flooding was related to groundwater inundation and floods (surface runoff) that induced terminal splays. Relative to the north, the southern facies associations, with their more significant thickness and lateral extent, show that, here, the basin was characterized by a higher rate of relative subsidence. Moreover, the southern lake systems were established along the erg's margin, where the interdunes expanded during pluvial phases. Ultimately, the facies associations in the Clarens Formation show that the widespread arid conditions in the Early Jurassic of south‐west Gondwana were subjected to prolonged and repeated pluvial phases in an otherwise harsh environment. Given the prominence of Jurassic aeolianites across Pangea, this study provides a southern African perspective on global palaeo‐erg dynamics and Early Jurassic climatic shifts.

Interdisciplinary strategy to assess the impact of meteorological variables on the biochemical composition of the rain and the dynamics of a small eutrophic lake under rain forcing

Abstract. We present an interdisciplinary investigation of the links between the macro and microphysical properties of rain, the biochemical composition of rain, meteorological parameters, and their impacts on the phytoplankton dynamics of a mountain lake. In order to document this interdisciplinary scientific question, Lake Aydat in the French Massif Central mountains was fitted with a set of high-resolution atmospheric radars, a disdrometer, and a precipitation collector in 2020. In parallel, the lake was monitored via sensors and water sampling. To illustrate the potential of this novel experimental setup, we present a case study of a rain event that occurred in September 2020 and during which, three contrasting sub-periods were identified based on the type of rain (convective or stratiform). Using our high-temporal resolution monitoring, we show that the origin of the air mass mainly influences the chemical composition of the rain, which depends on the rain type. In contrast, the photosynthetic cell concentration in the rain is mainly influenced by meteorological variables, predominantly below-cloud scavenging. The very low concentrations of photosynthetic cells found in rain events cannot directly impact the lake's phytoplankton abundance. In contrast, the rain rate directly impacted the lake's thermal stratification during the convective event. The response of the phytoplankton depends on the genus and, interestingly, three cyanobacteria, Microcystis, Coelomoron, and Merismopedia, showed a systematic response to rain events with a sudden decrease in abundance at the lake surface immediately after rain events. In contrast, the abundance of green algae (Elakatothrix), picocyanobacteria (Synechocystis and Synechococcus), and diatoms (Asterionella and Melosira) gradually increased following the rain events, but with a lower intensity compared to the cyanobacteria species. These different phytoplankton responses to the same rainfall event could play a key role in phytoplankton dynamics in the temperate zone. Our results highlight the importance of high-frequency and time resolution monitoring of both atmosphere and lake to better understand the adaptive strategies of cyanobacteria following rain events.

Tracking the dynamics of a local-scale lake using GRACE from a hydrogeological perspective

Tracking the dynamics of a local-scale lake using GRACE from a hydrogeological perspective

Non-charismatic waterbodies and ecosystem disservices: Mine pit lakes are underrepresented in the literature.

Pit lakes are one of the greatest legacies of open-cut mining. Despite the potential hazards of these lakes, they represent newly formed ecosystems with great scientific and ecological potential. Although thousands of pit lakes occur on every inhabited continent, with more being created, the microbial ecology of pit lakes is relatively under-researched. We evaluated the current state of microbial research in pit lakes by performing a Web of Science search and creating a literature database. Study lakes were categorized according to location and water quality (pH and conductivity) which is a key community and environmental concern. Research technology employed in the study was also categorized. We compared research effort in lakes, rivers, and streams which are the more "charismatic" inland aquatic ecosystems. Pit lake publications on microbes from 1987 to 2022 (n = 128) were underrepresented in the literature relative to rivers and streams (n = 321) and natural lakes (n = 948). Of the 128 pit lake publications, 28 were within the field of geochemistry using indirect measures of microbial activity. Most pit lake microbial research was conducted in a few acidic lakes in Germany due to social pressure for remediation and government initiative. Relatively few studies have capitalized on emerging technology. Pit lake microbial research likely lags other more charismatic ecosystems given that they are viewed as performing "ecosystem disservices," but this is socially complex and requires further research. Improving understanding of microbial dynamics in pit lakes will allow scientists to deliver safer pit lakes to communities.

Daily water‐level forecasting for multiple polish lakes using multiple data‐driven models

AbstractWater level in lakes fluctuates frequently due to the impact of natural and anthropogenic forcing. Frequent fluctuations of water level will impact lake ecosystems, and it is thus of great significance to have a good knowledge of water‐level dynamics in lakes. However, forecasting daily water‐level fluctuation in lake systems remains a tough task due to its non‐linearity and complexity. In this study, two deep data‐driven models, including gated recurrent unit (GRU) and long short‐term memory (LSTM), were coupled with attention mechanism for the forecasting of daily water level in lakes for the first time. Daily water‐level times series in five lowland lakes in Poland were used to evaluate the models. Root mean squared error (RMSE) and mean average error (MAE) were used for the evaluation of model performance. The modelling results were compared with the traditional feed‐forward neural networks (FFNN), GRU, LSTM, and zero‐order forecast. The modelling results showed that sequential deep learning models do not outperform feed‐forward models in all cases. In most cases, LSTM with attention mechanism (average RMSE = 0.88 cm, average MAE = 0.69 cm) outperforms GRU with attention mechanism (average RMSE = 1.00 cm, average MAE = 0.81 cm). However, attention mechanism did not help to improve the accuracy of the GRU and LSTM for most cases. Based on the average performance in different lakes, GRU performs the best among the deep learning models (average RMSE = 0.84 cm, average MAE = 0.66 cm). Zero‐order forecast models perform better than deep learning models for predicting tomorrow (average RMSE = 0.71 cm, average MAE = 0.39 cm), while deep learning models perform better as the horizon of prediction increases.

How Many Pan-Arctic Lakes Are Observed by ICESat-2 in Space and Time?

High-latitude lakes are sensitive indicators of climate change. Monitoring lake dynamics in high-latitude regions (e.g., pan-Arctic regions) is essential to improving our understanding of the impacts of climate change; however, the lack of in situ water level measurements limits comprehensive quantification of the lake hydrologic dynamics in high-latitude regions. Fortunately, the newly launched ICESat-2 laser altimeter can provide finer footprint measurements and denser ground tracks, thus enabling us to measure the water level changes for more lakes than with conventional radar altimeters. This study aims to comprehensively assess the number and frequency of pan-Arctic lakes (>1 km2, north of 60°N) observable by the ICESat-2 in space and time over the past three years. Further, we analyze the spatial and temporal characteristics of the ICESat-2-based water level observations of these pan-Arctic lakes based on our customized classification of seasonal coverage patterns (wet/dry season, monthly, and ten-day). We find that the ICESat-2 observed 80,688 pan-Arctic lakes (97% of the total). Among the observed lakes, the ICESat-2 retrieved the seasonal coverage patterns for 40,192 lakes (~50% of observed lakes), accounting for nearly 84% of the area and 95% of the volumetric capacity. Most lakes (99%) have seasonal water-level fluctuation amplitudes within a range of 0–1 m. The latitudinal zonality analysis demonstrates that the seasonal change in pan-Arctic lake levels gently fluctuates around 0.5 m between 60°N and 74°N and becomes intense (range of level change from 1 m to 2 m) beyond 74°N. Our results are expected to offer an overall reference for the spatio-temporal coverage of the ICESat-2’s observations of pan-Arctic lakes, which is crucial for comprehending the hydrologic response of high-latitude lakes to ongoing climate change.

Carbon, nitrogen, and phosphorus dynamics in China's lakes: climatic and geographic influences.

Given the differences in geomorphology, climate, hydrology, and human activities in various regions, lake chemometrics may also vary. However, the spatial distribution of lake chemistry and the factors affecting such pattern are still unclear. Here, we collected data for carbon, nitrogen, and phosphorus from published literature and databases in 224 lakes and calculated the trophic status index to represent the nutrient classification state of lakes. We found that lakes with high carbon concentrations were located in the Tibet-Qinghai Limnetic Region of western China, whereas lakes with high nitrogen and phosphorus concentrations were located in the Inner Mongolia-Xinjiang Limnetic Region and Northeast Limnetic Region of northern China. Areas with larger cropland and urban residential land (such as the junction of the three lake regions, i.e., the Northeast Limnetic Region, East Limnetic Region, and Inner Mongolia-Xinjiang Limnetic Region) tended to have lakes with high nitrogen and phosphorus concentrations. Our analysis suggested that spatial distribution of carbon, nitrogen, and phosphorus concentrations reflect the effect of climate, geomorphology, and land use in each lake region and nationwide.

Supervised Classifications of Optical Water Types in Spanish Inland Waters

Remote sensing of lake water quality assumes there is no universal method or algorithm that can be applied in a general way on all inland waters, which usually have different in-water components affecting their optical properties. Depending on the place and time of year, the lake dynamics, and the particular components of the water, non-tailor-designed algorithms can lead to large errors or lags in the quantification of the water quality parameters, such as the suspended mineral sediments, dissolved organic matter, and chlorophyll-a concentration. Selecting the most suitable algorithm for each type of water is not a simple matter. One way to make selecting the most suitable water quality algorithm easier on each occasion is by knowing ahead of time the type of water being handled. This approach is used, for instance, in the Lake Water Quality production chain of the Copernicus Global Land Service. The objective of this work is to determine which supervised classification approach might give the most accurate results. We use a dataset of manually labeled pixels on lakes and reservoirs in Eastern Spain. High-resolution images from the Multispectral Instrument sensor on board the ESA Sentinel-2 satellite, atmospherically corrected with the Case 2 Regional Coast Colour algorithm, are used as the basis for extracting the pixels for the dataset. Three families of different supervised classifiers have been implemented and compared: the K-nearest neighbor, decision trees, and support vector machine. Based on the results, the most appropriate for our study area is the random forest classifier, which was selected and applied on a series of images to derive the temporal series of the optical water types per lake. An evaluation of the results is presented, and an analysis is made using expert knowledge.

Application of concentration and 2-dimensional stable isotope measurements of methane to constrain sources and sinks in a seasonally stratified freshwater lake

Methane (CH4) emissions from aquatic systems have recently been comprised to account for up to 50% of global CH4 emissions, with lakes representing one of the largest CH4 sources within this pool. However, there is large uncertainty associated with CH4 emissions from freshwater environments to the atmosphere, because of a lack of understanding in the spatial and temporal dynamics of CH4 sources and sinks, as well as underlying mechanisms and processes. In this study, we investigated the concentrations and stable carbon (δ13C-CH4) and hydrogen (δ2H-CH4) isotope composition of CH4 in a small eutrophic lake (Lake Willersinnweiher) with seasonal stratification and its spatial and temporal variation. We found that while supersaturation of CH4 in the entire water column was present throughout the whole year, the isotopic composition of CH4 in sediment and water column varied depending on lake stratification, physiochemical conditions, and lake depth. During the stratification period, isotopic characteristics of pelagic surface water CH4 differed from littoral and sedimentary CH4, suggesting likely mixing of CH4 from different sources including vertical and lateral input as well as groundwater input and potentially oxic methane production in the mixed surface water layer. Aerobic CH4 oxidation indicated by a strong increase in both δ13C-CH4 and δ2H-CH4 values at the bottom of the oxycline was found to significantly reduce upward migrating CH4 released at the sediment-water interface. In the sediment, stable isotope characteristics of CH4 showed an increasing dominance of the acetoclastic CH4 formation pathway from the pelagic towards the littoral area. Furthermore, the occurrence of sulfate-dependent anaerobic methane oxidation in the sediment was suggested by an increase in δ13C-CH4 and δ2H-CH4 values. During the mixing period, the isotopic CH4 composition of the water column was distinctively less negative than during the stratification period potentially resulting from a greater impact of groundwater CH4 input compared to the stratification period. Our findings implicate that the application of concentrations and dual isotope measurements of CH4 is a promising approach for constraining CH4 sinks and sources in Lake Willersinnweiher and potentially other small lakes to clearly disentangle the complex CH4 dynamics in lakes both spatially and seasonally.

Phytoplankton assemblage shifts with dissolved organic matter properties: A functional perspective for sentinel lakes

Abstract Climate change is altering both dissolved organic matter (DOM) properties and phytoplankton dynamics in lakes. High‐altitude lakes are good sentinels of global change. However, their value as sentinels depends on how well we understand their functioning. This study analysed physical, chemical and biological data during three pre‐defined periods running from complete ice‐cover right to the end of the ice‐free season, in a high‐altitude oligotrophic lake. A functional approach was used to assess how relationships between DOM and the planktonic community vary over time. Phytoplankton functional change was found to occur with shifts in DOM. During the ice‐influenced period, from February to the end of the thaw, the phytoplankton community was dominated by small autotrophs and mixotrophic flagellates and DOM from sediment and terrestrial origin dominated the DOM pool of the lake. Phytoplankton diversity and richness increased during the post‐snowmelt overturn period, when terrestrial DOM dominated the DOM pool. Finally, large siliceous autotrophs, competitive under low nitrogen concentrations and high temperature, dominated almost exclusively during the late summer period (LSP). Increased phytoplankton biomass meant that phytoplankton‐derived DOM was dominant during the LSP. These phenological changes in the phytoplankton community resulted in functional shifts at the base of the food web. Based on the relationships between the variables in the study, it can be deduced that the nature of the relationship between phytoplankton and bacteria progressively shifted from strong top‐down control exerted by phytoplankton over bacteria towards predominantly bottom‐up control at the end of the ice‐free season. Synthesis. Using a field survey starting from complete ice‐cover and lasting right to the end of the ice‐free season in a sentinel lake, we show seasonal shifts in the link between DOM properties and plankton community traits. Differences in environmental conditions and DOM origin explained variation in phytoplankton community structure and function, pointing to seasonal shifts in microbial food web interactions. Our research suggests that, under climate change, the balance between mixotrophy and autotrophy and the control exerted by phytoplankton over bacterioplankton will change in oligotrophic high‐altitude lakes with large, vegetated catchments.

Dynamic Monitoring and Ecological Risk Analysis of Lake Inundation Areas in Tibetan Plateau

Lake inundation is one of the most important hydrological factors affecting lake ecosystems. In order to accurately and timely grasp the spatio-temporal pattern of the lake inundation area, and reveal the ecological evolution of the lake landscape, this paper quantifies the inundation dynamics of lakes on the Tibetan Plateau in the past 20 years and analyzes the spatio-temporal characteristics of the inundation area from four aspects: the region, type, altitude and recharge mode of the lake. Combined with the water inundation frequency, the landscape inundation frequency index is constructed and applied to the landscape ecological risk index to explore the spatio-temporal dynamic changes of landscape ecological risk in the inundation area. The results show that the change of the lake-inundated area first decreases and then increases in 2000–2020, the salt lakes and low-altitude lakes have the largest inundation areas, accounting for 83.2% and 55.6% of the total inundated area, respectively; the change intensity of lake inundation frequency is relatively large, and the alternate changes of the lake water–land junction area are enhanced, and the area of permanent lake increases; inundation has the greatest impact on bare land and grassy landscapes; the study area is dominated by lower-risk and lowest-risk areas, accounting for 84.9% of the total area of risk areas, but most areas are transformed from lower-lowest risk to medium-higher risk. This study provides a case of dynamic monitoring of lake inundation areas, which is helpful to formulate ecological restoration and risk prevention measures in lake inundation areas, and can also be used for ecological risk research in similar areas.

Temporal and Spatial Changes and GLOF Susceptibility Assessment of Glacial Lakes in Nepal from 2000 to 2020

Glacial lakes are a sensitive indicator of regional climate change and one of the initiators of glacier disasters. It is of great significance to understand the spatial distribution and change characteristics of glacial lakes for exploring their response patterns to climate change and assessing the glacial lake outburst flood (GLOF) susceptibility. Based on Gaofen-1/6 PMS, Sentinel-2A/2B MSI and Landsat TM/ETM+/OLI images from 2000 to 2020, we integrated geographic information technology and mathematical and statistical methods to analyze the spatial and temporal distribution of glacial lakes in Nepal and their dynamic changes, and further discriminated and evaluated the GLOF susceptibility of glacial lakes. The results show that there were 2420 glacial lakes in Nepal in 2020, mainly distributed within the 4500~5500 m, with an area of 87.21 km2 and a water storage of 1921.72 × 106 m3. The number and area of glacial lakes with each area above 0.01 km2 in Nepal showed an increasing trend from 2000 to 2020, while 499 new glacial lakes were born, 139 lakes disappeared, the area and water storage increased by 19.46 km2, 403.07 × 106 m3, respectively. Glacial lakes at altitudes <3000 m were relatively stable, while the number and area of glacial lakes at altitudes within 4500~5500 m increased rapidly. We assessed the GLOF susceptibility of 40 moraine-dammed glacial lakes with an area above 0.2 km2 in Nepal, and found that there were 8, 12, 14 and 6 glacial lakes with low, medium, high and very high susceptibility, respectively. Among glacial lakes with very high GLOF susceptibility, potential GLOF events of Tsho Rolpa glacial lake, Lower Barun glacial lake and glacial lake with code of GL87091E27797N will cause great harm to downstream regions. GLOFs in Nepal will be in an active status in the future, therefore, the dynamics of glacial lakes and their surroundings should be continuously monitored.

Studying the dynamics of thermokarst lakes in the West Siberian Arctic based on the analysis of time series of satellite measurements

Subject of research: article is the time series of changes in the area of thermokarst lakes in the Arctic under the conditions of modern climatic changes.
 Purpose of research: to analyze the time series of satellite measurements of lake areas for studying the dynamics of lakes in the West Siberian Arctic.
 Methods and objects of research: we present the results of formation and analysis of time series of lake areas intended for studying the dynamics of thermokarst lakes in the Arctic zone of Western Siberia over a 36-year period. The time series were obtained based on the results of remote measurements of the lake areas on the territory of 627 thousand km2 using 688 Landsat satellite images, sampled in the period 1985-2021. The study area was divided into three ecoregions to analyze the territorial features of the vast Arctic zone of Western Siberia. The analysis of the time series showed that the change in the average lake area in the territory of the Arctic zone of Western Siberia exhibits a marked negative linear trend.
 Main results of research: based on the comparison of the trends in the time series of lake areas in the territories of the three ecoregions of the West Siberian Arctic, it was found that the thermokarst lakes of Yamal exhibit the highest rate of change in the areas compared to the other Arctic ecoregions.

Characterization of a West African Coastal Lagoon System: Case of Lake Nokoué with Its Inlet (Cotonou, South Benin)

The purpose of this work was to investigate the physical and chemical dynamics of Lake Nokoué for its efficient management. For this purpose, two sampling campaigns per month from five stations (North, South, Central, East and West) were conducted for a period of one year (November 2020 to November 2021). Physic and chemical parameters (temperature, salinity, depth, water transparency, pH, dissolved oxygen and total dissolved solids) were measured and wet substrate samples were collected to study the granulometry. Data analysis revealed that Lake Nokoué is mainly affected by two regimes: flooding and low water. Flooding, which is not directly related to rainfall, did not begin until one month after the major rainy season in June. The sources that contributed to the flooding of Lake Nokoué were the freshwater tributaries coming mainly from the Ouèmé River and the flow of the Sô River from August to November. The inflow of fresh water contributed to the decrease in salinity and transparency of the lake from the east to the south. During the low water period (from December to July), Lake Nokoué is characterized by an increase in salinity and transparency from the south to the northeast due to the massive intrusion of sea water into the lake. The highest dissolved oxygen levels are observed in the south and center (5.92 ± 0.46 mg/L) while it varies greatly in the north and west (Eichhornia crassipes concentration zone) during flooding. The average annual depth of Lake Nokoué was 1.47 ± 0.66 m with an average annual pH of 6.85 ± 0.56.