2026: Special Issue N1 (270)

On the occasion of the Professional Days of Forester, Hydrologist and Meteorologist, at the initiative of the Faculty of Geography and Geology of YSU, with the financial support of the Committee on Higher Education and Science of the RA Ministry of Environment (Research Project No. 24WS-1E035), an international  conference entitled "Current Issues in Hydrometeorology and Environmental Monitoring in a Changing Climate: Adaptation, Sustainability and Production Process" was held from May 04 to 07, 2026. The purpose of the conference is to discuss achievements and prospects for the development of fundamental and applied scientific research in the field of hydrometeorology, environmental monitoring, and environmental safety, to identify and highlight the main problems, development patterns, and prospects in the field of hydrometeorology, to assess its role in solving the region's socio-economic problems, to analyze and evaluate the current state of the environment, climate change issues, interdisciplinary problems in the development of scientific ecological-geographical and tourist-recreational research to enhance their effectiveness, demand, and practical significance in the context of modern scientific and technological development. During the conference, they will also discuss the development of modern society and issues of economic management, legal regulation of the ecosystem, as well as problems of environmental and hydrometeorological education in the Republic of Armenia.

Climate change leads to the restructuring of geosystems, creating risks for the environment and infrastructure. Therefore, the climate forecast should include information about extreme events. The rare largest and most intense extremes are not fully reproduced in the Earth system models (ESM). They stand out among others not only for their power, but also because they do not fit into the basic probability distribution function (PDF). Such events are sometimes called "black swans" or "dragon." The reason why these events are not recreated during modeling is, as can be assumed, the lack of spatial resolution of the ESM. Therefore, it is necessary to develop a special approach, in which the results of climate modeling would be integrated into the methodology of the statistical theory of nonstationary extremes. The classical statistical theory describing the PDF of extremes can be generalized to the case of unsteady processes. In climate forecasting, the parameters of non-stationary PDFs are estimated based on climate modeling data. However, this approach ensures that only the "correct" extremes of the basic PDF are predicted, that is, it does not eliminate the problem of "black swans" (or "dragons"). An alternative option is to use time-averaged (or space-averaged) indicators for which the occurrence of rare events is not critical for their PDF. This is possible due to the physics of climate processes, in which anomalies do not turn out to be as significant as they are, for example, in financial mathematics.

The main results of the acoustic remote sensing of the atmosphere in Moscow are presented. The MODOS Doppler SODAR produced by METEK (Germany) operates at Moscow University since 2004. Its operation frequency is 2000 Hz, the sounding range is from 40 to 500 m, temporal and spatial resolution is 10 min and 20 m, respectively. As a result of long-term sounding, data sampling during 20 years involves more than 7 millions of individual values of wind speed and wind direction at each level. The annual course of wind speed demonstrates the maximal values in autumn and winter, and the minimal ones, in summer; this is explained by frequent intense gradient currents during the cold period in Moscow. The diurnal course of the wind speed V is characterized by the daytime maximum and night-time minimum in the layer up to 40–60 m and, vice versa, the daytime minimum and night-time maximum are observed at heights above 140–160 m. Thus, the layer from 80 to 120 m approximately corresponds to the height of the wind rotation; the diurnal course there is poorly pronounced and characterized by the minimum in the morning. The maximum wind speed over Moscow on average of 10 min in the air layer up to 500 m may reach 30–35 m/s in rare cases if two conditions concur: Moscow is located on the periphery of deep cyclones and the local low-level jet stream exists. The top of quasi-linear section of the average long-term profile of V in semi-logarithmic coordinates is 40–60 m (it may be accepted as the surface air layer height if average conditions are close to neutral stratification); the roughness length is ~5 m. According to the criterion of the constant wind direction in the surface air layer, its height in the monthly averaged wind direction profiles over the "dead zone" (40 m) is in approximately one out of three cases and usually amounts to 60 m (sometimes 80 or even 100 m). Following this approach, the average height of the surface layer is probably a little less than 50 m, which is close to the first estimation. The wind direction has a stable southwestern mode in 20 years on average. The rarest wind direction over Moscow is the North-Northeastern one. The average right wind shear in the air layer of 40–500 m is 20°. This work is supported by Russian Science Foundation, project No 26-27-20046.

The article examines the physical, geographical and climatic conditions of changes in wind speed over Western Siberia. The direction and speed of wind in the troposphere are the result of the influence of atmospheric circulation and regional characteristics of the territory. Variability trends vary in different directions in different regions of the globe. A change in the wind regime may indicate a change in the radiation balance, accompanied by a change in the pressure in the atmospheric column above the region under study. This paper presents long-term variability of tropospheric wind speed in Western Siberia. Data were analyzed at the ground surface and at standard isobaric surfaces of 850, 700, 500, and 300 hPa at four stations in Western Siberia ("Aleksandrovskoye", "Barabinsk", "Novosibirsk", and "Kolpashevo") for the period 1975–2020. The study showed that temporal variability is synchronous across all tropospheric layers and is due to variations in macrocirculation processes. All stations demonstrate a tendency toward decreasing wind speed at all levels. Moreover, in the Northern part of Western Siberia, the decrease in wind speed is statistically significant throughout the troposphere. In the Northern Region at altitudes of 850–700 hPa, wind speed decreased more than in the Southern territory. The correlation coefficients of wind speed at the ground and in the troposphere are high and statistically significant with a probability of at least 99% at three of the stations under consideration. The decrease in wind speed in the troposphere at Northern latitudes may be due to ongoing climate warming, particularly noticeable in the Northern Regions, which has resulted in a decrease in pressure gradients between the northern and central regions of Western Siberia. In the Southern part of Western Siberia, the decrease in wind speed is more pronounced near the surface. Such variability in wind speed may influence climate change in the study region.

Modern climate change is characterized by a rapid increase in global mean temperature, which has already risen by approximately 1.3–1.5℃ compared to pre-industrial levels. Alongside this warming, the frequency and intensity of extreme weather events, including heatwaves and heavy precipitation, have increased significantly. Although climate variability is influenced by natural factors such as orbital forcing, solar activity, volcanic eruptions and ocean circulation, increasing atmospheric concentrations of greenhouse gases (GHG), primarily CO₂ and CH₄, are recognized as the main drivers of current climate change. This study analyses the dynamics of CO₂ and CH₄ emissions and uptake by terrestrial and oceanic ecosystems in the 21st century, focusing on recent estimates, spatial and temporal variability, and major trends. Particular attention is given to methods for assessing GHG fluxes and to the role of climate mitigation and adaptation strategies. The IPCC inventory methodology applies a bottom-up approach based on statistical data on land use, agriculture, industry and energy consumption combined with standardized emission factors. Biogeochemical models, including CESM, LPJ, ORCHIDEE and JULES, simulate interactions between vegetation, soils, oceans and the atmosphere. Inversion modelling uses satellite observations from OCO-2, GOSAT and TROPOMI together with atmospheric transport models to estimate surface GHG fluxes. Machine learning approaches are increasingly used to identify non-linear relationships between GHG fluxes and environmental drivers using large observational datasets. Modern GHG monitoring systems combine observations across multiple spatial scales. Local-scale measurements of CO₂ and CH₄ fluxes are obtained using eddy covariance techniques, chamber methods and UAV-based observations, providing essential data for model calibration and validation. Regional and global estimates are derived using biogeochemical and inversion modelling approaches based on satellite observations. Integrating ground-based measurements, remote sensing and modelling significantly improves our understanding of GHG exchange between the atmosphere, terrestrial ecosystems and the oceans. According to the Global Carbon Budget, the global ocean absorbed approximately 2.2–3.0 GtC per year of anthropogenic CO₂ between 2006 and 2023, while terrestrial ecosystems absorbed on average 2.5–3.5 GtC per year, although with much higher interannual variability related to climate conditions, disturbances and land-use change. This study emphasizes the importance of nature-based solutions, including the protection and restoration of forests, wetlands and grasslands, for climate mitigation and carbon sequestration.

The numerical atmosphere modeling is the basis of all weather previsions from hours until seasons, as well of the climate changes. For every-day operational weather forecasting the special technological systems of high-resolution modeling and data proceeding were developed in different countries with using of huge supercomputer powers. Following the World Meteorological organization (WMO) destinations, the world (WMC) and regional specialized meteorological centers (RSMC) provide the numerical forecasts. The Moscow Center (as Hydrometeorological Center of Russia) has the both destinations – as the world and the regional center. In the competence of the RSMC, the multy-scale forecasting system COSMO-Ru has been developed at the RSMC Moscow for almost 20 years. A series of forecasts are issued 4 times a day for waste domain, including whole Russia and neighboring regions (since 2025 for all non-tropical area of Northern Hemisphere – after implementation into COSMO-Ru system of the configuration of model ICON) with grid-space 6.6 km until 120 h and for area of European part of Russia and neighboring regions on the grid 2.2 km until 48 h. The presentation provides a short description of the current state and development trends of numerical atmospheric modeling in the leading WMO centers for numerical weather forecasting. The COSMO/ICON-Ru high resolution forecasting system, developed at the Hydrometeorological Center of Russia based on the ICON and COSMO models, as well it development for a some computational domains, including the region of the Republic of Armenia, are considered. The importance of using non-hydrostatic approximation and convective-resolving grids in regional configurations is emphasized, as well as the specifics of interpreting of high-resolved modeling products.

The Universal Thermal Climate Index (UTCI) was used to assess the bioclimatic conditions on the territory of Russia in the middle of the 21st century. Seasonal and regional features of the UTCI were studied under future climate conditions (2040–2059), for "soft" (SSP1-2.6) and "hard" (SSP5-8.5) scenarios. The BioKlima 2.6 software package was used to calculate average daily UTCI values. Daily data from three models participating in CMIP6 (Coupled Model Intercomparison Project) were used for the calculation: the Marchuk Institute of Numerical Mathematics RAS, the Met Office Hadley Centre and the Max Planck Institute for Meteorology. Cold stress conditions will continue to prevail on the territory of Russia under the future climate conditions for both scenarios. In winter (January), cold stress of various gradations will be observed in almost the whole territory. In summer (July), conditions without heat stress will be observed in most of Russia, and comfort in the South. The assessment of possible future changes in bioclimatic conditions in Russia in the middle of the 21st century (2040–2059) showed that for both scenarios there will be a noticeable trend towards a reduction in the number of days with severe cold stress and an increase in the number of days with heat stress in the south of the European territory and in the South and in center of Siberia, especially according to the SSP5-8.5 scenario. The percentage of days with the UTCI "no thermal stress" gradation will increase over most of Russia. The emerging trends will contribute to the improvement of the bioclimate in the regions with the worst conditions, in the North and East of the country, and to the deterioration of conditions in the most favorable regions in the South, due to an increase in the number of days with heat stress.

Current understanding of the natural environment of the North Caucasus is the result of centuries of extensive observation. Expeditions of the 18th century made a significant contribution to the study of the climate of the North Caucasus. Information on the climate of the North Caucasus began to be actively covered in the notes and reports of the Caucasian Section of the Imperial Russian Geographical Society in the 19th century (in the characteristics of the climate of individual regions of the Caucasian Mineral Waters, in works devoted to atmospheric precipitation in the regions of the Ciscaucasia, etc. [1, 2]. In the 19th century, measures were proposed to improve and preserve nature, to establish numerous meteorological stations to observe the weather and prevent possible natural anomalies. A significant contribution to the study of the climate of the North Caucasus and the Caucasus as a whole was made by the first Russian climatologist A.I. Voeikov (1842–1916). The founder of scientific soil science V.V. Dokuchaev (1846–1903) in his works on the soils of the Caucasus, he provides information on the climatic features relevant to the North Caucasus. Based on 20 years of observations at the end of the 19th century, an atlas of precipitation distribution in the river basins of European Russia by month and year was prepared, based on the results of 20 years of observations (A.A. Tillo, 1839–1899). The study of the climate of the North Caucasus before and during the 19th century was primarily descriptive and partly generalizing. However, the available observational results laid the foundation for a comprehensive study of the climate. The Caucasian Section of the Imperial Russian Geographical Society made an important contribution to climate research, providing the scientific community with the opportunity to become acquainted with pioneering research on the climate of the North Caucasus.

The regional atmospheric modeling systems, which refine the results of global models, are currently actively used as a means of numerical weather forecasting for the coming days and hours. Using non-hydrostatic approach and grid spacing of several kilometers or less, these systems not only take into account complex geographical features of the terrain in detail but can also realistically predict complex weather formation mechanisms, including those associated with convection. Thе presentation is devoted to the description and results analysis of a continuously operating system for regional data assimilation and hourly numerical forecast updates for the next 12 h.  It is based on the convective-resolving model configuration with a 2,2 km horizontal grid spacing COSMO-Ru2By, developed at the Russian Hydrometeorological Center [1]. Observations from meteorological stations and Doppler radars are used, many of which are not exchanged internationally with WMO [2]. The implemented approach was carried out in accordance with the worldwide practice in developing similar systems: High Resolution Rapid Refresh (HRRR) at the US National Centers for Environmental Prediction (NCEP) and Rapid Update Cycle (RUC) at the German Weather Service (DWD). The developed system has proven effective for forecasting rapidly developing hazardous events, as well as for monitoring the state of a meteorological fields with a resolution significantly higher than that of the observation network (which can serve as the basis for creating high-resolution reanalyses).

The article presents the results of a study on the interannual variability of carbon dioxide (CO₂ fluxes in a mixed coniferous-deciduous forest located within the Educational and Experimental Soil and Ecological Center of Lomonosov Moscow State University. To simulate the ecosystem's carbon balance for the period 2010–2025, the Forest-DNDC dynamic model was used, which allowed for the analysis of the influence of climatic factors (temperature and precipitation) on the carbon exchange between soil, vegetation, and the atmosphere. The model's adequacy was verified by comparing it with the results of eddy covariance measurements, which confirmed its applicability for calculating integral CO₂ fluxes in forest ecosystems. Model calculations revealed a consistent trend of organic carbon accumulation in the soil, averaging 170 to 230 kg C/ha per year, accompanied by a slight decline in the forest ecosystem's net carbon uptake capacity. An increase in temperature weakens carbon uptake by an average of 1% per year. In some years, the ecosystem serves as a source of CO₂, releasing 400 to 800 kg C/ha per year.

Numerical weather prediction systems require the initial data, including information about the state of the earth's surface. Snow cover data is mandatory, among which the position of the snow line is crucial for the numerical weather forecasting for the coming days. Currently, these data are based on satellite measurements, adjusted by daily snow depth data from weather stations located in open terrains. This does not allow for a reliable assessment of the extent of snow cover. In forests, tree canopies may be free of the snow, as the snow can be moved beneath tree branches and partially melted. This can cause the canopies to heat up and warm the surrounding air. The processes of snow accumulation and vertical redistribution in forest landscapes are generally not taken into account in forecast models and initial data proceeding. This sometimes leads to significant model temperature errors for lower atmospheric levels. The presentation provides the examples of the influence of initial snow cover data (using the COSMO/ICON-Ru forecasting system) on the behavior of calculated meteorological parameters for some next days. Near-surface air temperature, cloudiness (especially low level), precipitation, and their phases were found to be most sensitive to this factor. Indicators of a decrease of forecasts skill in the spring, when the described factors are most noticeable, are presented. In these cases, it is typical for the forecast of near-surface temperature to "stick" at 0℃ (all the heat goes to the snow melting on the surface of the model cell) if the factor of snow-free tree canopies is not taken into account when forming the initial data. Proposals for algorithms for correcting snow boundary data are considered.

Mathematical modeling of species climatic ranges is regarded as a key tool for assessing potential impacts of climate change on ecosystems and agriculture. In the present work, the RANGES system is employed, which, on the basis of observed climate data or climate model outputs together with climate predictor values, estimates the probability of a geographic point belonging to the climatic area of distribution or climatic range of a certain species. In contrast to approaches based on multi year mean characteristics, the limitations of the climate predictors are tested separately for each year within the considered time interval. The climatic ranges of the Italian locust and Mediterranean fruit fly, two insect pests of agricultural crops, are evaluated for the climatic conditions of 1990–1999, 2030–2039, 2050–2059 under a set of climate change scenarios. Among the large number of insect pests affecting crop production, these two species are considered to be dangerous or potentially dangerous under the climatic conditions of Russia. The calculations are carried out using climate data produced by the global climate model developed at the Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences, providing a basis for assessing possible future shifts in the spatial distribution and risk levels of these pests. According to the obtained results, an overall expansion of the climatic range of the Italian locust towards the north, especially in the European part of Russia, can be noted. However, under some climate change scenarios, a slight decrease in the probability of belonging to the climatic range is projected for parts of the Central Black Earth Region. For the Mediterranean fruit fly, whose current climatic range in Russia is mainly confined to the Black Sea coast, an expansion of the climatic range to the North and East is expected by the middle of the twenty first century.

The data of long-term monitoring of the floristic composition of five sample plots of dry post-forest meadow ecosystems located in different parts of Valdai National Park were presented. These meadows formed as a result of centures-old agricultural practices, then under reservation conditions and climate warming. It has been shown that in the absence of haymaking, grazing, and burning, the meadows exhibit relatively stable floristic composition and abundance of herb layer, a lack of visible successional processes, and resistance to the invastions of alien species. Correlations are found between the number of species, maximum of herb layer height, projective cover of meadow phytocenoses, and weather conditions of a concrete year: seasonal temperature, precipitation amount, and snow depth. It is revealed that different combinations of temperature and precipitation parameters associated with heat and moisture availability are decisive for the formation of plant cover species diversity in all five meadow sample plots. Significant negative correlations with temperature and positive correlations with moisture conditions predominate. Maximum species diversity, maximum of the herb height and projective cover are observed in years with good moisture and temperatures without extreme values.

The report contains a study of the impact of the degree of moisture on the runoff off rivers in various regions of Belarus and the arid area of the Tarim Province (China). The objects of the study are three hydrological regions of Belarus with different levels of moisture: humid (Zapadnodvinsky), moderately humid (Nemansky), and dry (Zapadnobugsky), as well as the desert basin of the Tarim River. Widespread climate warming leads to a widespread increase in average annual, air temperatures. Against the backdrop of a general decrease in precipitation (except for the Zapadnobugsky Region), there is a decrease in the average annual water discharge of rivers. A noticeable annual increase in precipitation in the Zapadnodvinsky Region leads to a slight rise in the average annual water discharge of the Regions main river. There is trend towards a decrease in average annual water discharge with a reduction in precipitation and an increase in average air temperature. Trends in air temperature changes from 1980 to 1922, the average annual precipitation from 1960 to 2014, and correlation coefficients the relationship between average annual discharge and average annual air temperature and precipitation over the period from 1960 to 2014 have been obtained. The closest relationship exists between the average annual water discharge of the studied rivers and precipitation in the catchment area. The Tarim River basin is a typical inland river basin of an arid region, where the formation of water resources has regional characteristics. Minimal precipitation and high evaporation determine the arid conditions of the basin. The inflow of water is provided by the melting of snow and glaciers bordering the basin. Amid overall variability in global and regional climate changes, there is a trend of decreasing average monthly precipitation from 1990 to the minimum of 1945–1950. Lacking inflow in the middle and lower reaches, the Tarim River is prone to summer floods against the backdrop of minimal flow and a deficit of surface water. The flow regime is subject to sharp fluctuations. With decreasing humidity and increasing aridity of river basins, the variability of flow increasing, there is a trend toward a decrease in its average annual values, and the likelihood of extreme hydrological events increases.

An assessment of the dynamics of moisture conditions is necessary to solve problems associated with the development of adaptation to drought phenomena, reducing their economic damage, as well as identifying patterns and trends in the occurrence, development, and course of droughts for the purpose of their possible forecasting. This study analyzes the meteorological indicators of droughts – hydro-thermal coefficient of Selyaninov (HTC) and the standardized precipitation evapotranspiration index (SPEI) in Belarus during warm seasons (April–September) for the period 1994–2024. The monthly values of the SPEI index were obtained from the Global SPEI database (https://soton.eead.csic.es/spei/database.html) for the regions of Belarus, the data of the state climatic base of the Ministry of Natural Resources and Environmental Protection of the Republic of Belarus on average daily air temperature and precipitation were used to calculate the HTC. It was revealed that during the vegetation season of 1994–2024 in Belarus there was a tendency to worsen moisture conditions in almost all regions of the republic, especially in April, June and September. The most significant downward trend in the values of HTK and SPEI was noted in June and ranged from –1.0 to –1.5 in the regions of the country. In the remaining months, the moisture conditions remained virtually unchanged. The frequency of years with droughts of varying intensity has increased, and since the 2010s, there has been a trend towards reducing the frequency of years with excessive moisture in the territory. The most unfavorable period according to the values of the HTK and SPEI indices was August and September, in these months the number of years with slightly drought conditions prevailed over the number of years with good moisture conditions. The evaluation of the relationship between HTK and SPEI showed a high correlation coefficient and Pearson covariance, both for individual months and for the entire vegetation season. In relation to each other, these indicators are significant and have a high correlation between variables, as they reflect similar meteorological values, which makes it possible to use them both for rapid assessment of the moisture conditions of the territory, and for forecasting through the use of remote sensing data and the integration of model calculations.

Air quality monitoring remains a significant challenge in developing countries, particularly in cities like Yerevan, the capital of Armenia. Located in the Ararat Valley, surrounded by mountains, and characterized by limited green spaces, Yerevan is particularly vulnerable to air pollution. The city faces high concentrations of airborne dust, along with fine particulate matter such as PM_2.5 and PM₁₀, which have become key indicators of air quality. However, the available air quality data are often fragmented, incomplete, and inconsistent. This study presents a comparative analysis of airborne dust data obtained from multiple monitoring platforms, including independent data sources. The data collected during the winter and summer periods of 2025–2026 were examined, with particular attention to the influence of climatic factors. The results show that Yerevan experiences high concentrations of total suspended particles (TSP), as well as PM_2.5 and PM₁₀, especially during the winter months. Pollution levels worsen during winter due to thermal inversion conditions characteristic of the Ararat Valley, which contribute to the accumulation of suspended particles in the air. Furthermore, discrepancies between air quality indicators reported by different monitoring platforms for the same observation periods are evident. These inconsistencies are primarily attributed to significant gaps in monitoring systems and the absence of scientifically robust and standardized methodologies. The findings highlight the urgent need for coordinated and strategic approaches to improving air quality management in the city.

Today, many scientists are exploring the application of computer technologies and their adaptation for atmospheric analysis across territories of varying scales. The state of the atmosphere over a specific territory and at a specific time is determined by various geophysical, geographical, and atmospheric factors, which collectively determine the weather in the studied area. Computer models are used for atmospheric forecasting and analysis, allowing for the rapid and effective resolution of these problems at the appropriate scientific and methodological level. Modern numerical atmospheric models adequately describe the qualitative structure of global circulation, which is reflected in changes in climate system parameters. The ability of models to forecast climate over a given period of time builds confidence in the physical reliability of the calculated data. The use of numerical analysis, computer processing, machine learning, and neural network analysis allows for the processing of large volumes of information and the automation of data processing and analysis systems, improving the quality and lead time of forecasts. Recent advances in atmospheric science and technology create favorable conditions for improving the accuracy of weather forecasts and forecasts of hazardous atmospheric phenomena that negatively impact people and economic sectors. Particularly noteworthy is the use of supercomputer systems, whose capabilities allow the creation and application of highly complex mathematical models of atmospheric circulation for weather forecasting. This study analyzes several cases of hazardous atmospheric phenomena that occurred in Belarus and the potential of using computer technologies in their analysis. It also discusses the potential of modern technologies for recognizing hazardous atmospheric phenomena in a specific region.

Rapid climate warming in the Arctic significantly affects permafrost stability, creating increasing risks for natural ecosystems and critical infrastructure. The Yamalo-Nenets Autonomous Okrug represents one of the key regions where rising air and soil temperatures contribute to ongoing degradation of permafrost. This study evaluates the ability of modern climate datasets and numerical models to reproduce long-term thermal conditions of soil horizons using observational records, ERA5 reanalysis data, and data from the CMIP6 climate model. The analysis covers the period from 1980 to 2020 and includes comparisons between meteorological station measurements, borehole observations, and gridded datasets. ERA5 reanalysis shows strong agreement with observational air temperature dynamics, confirming its applicability for regional climate assessments; however, its performance decreases when reproducing soil temperatures, particularly at greater depths, where systematic underestimation and reduced sensitivity to extreme events are observed. To assess model reliability, 45 CMIP6 climate models were evaluated using statistical performance metrics, including mean bias, root-mean-square error, and trend consistency relative to ERA5 data. Five models TaiESM1, GFDL-CM4, FGOALS-g3, GISS-E2-1-G-CC, and BCC-ESM1 satisfied the established selection criteria and were further analyzed for their capability to simulate soil thermal regimes across multiple depths. The comparison with borehole measurements revealed substantial spatial and depth-dependent variability in model performance. Model simulations demonstrate the highest agreement with observations near the surface, where indices of agreement reach 84–98%, while accuracy decreases within the active layer and deeper soil horizons. Among the evaluated models, GFDL-CM4 provides the most consistent reproduction of annual soil temperature cycles and long-term thermal gradients. Overall, the identified model performance differences are critical for improving projections of permafrost response to climate change and for assessing future risks to Arctic ecosystems and infrastructure systems in the Yamalo-Nenets Region.

This article presents the results of a comprehensive assessment of the climate vulnerability of the territory of the Republic of Belarus, based on the application of dimensionless climate indices adapted to national natural and climatic conditions. The aim of the study is to identify territorial differences in Belarus's climate vulnerability and to determine the key climatic factors shaping its spatial structure. The study was based on long-term observation series from 45 meteorological stations of the State Climate Cadastre of the Republic of Belarus for the period 1989–2024. The methodological basis employed was the technique for calculating climate vulnerability based on dimensionless indices, proposed by V.V. Oganesyan and modified by the authors to account for the density of the meteorological observation network and the objectives of regional analysis. The calculations took into account indicators of the extremity of temperature, precipitation and wind regimes. For spatial analysis and the transition from point station estimates to a continuous territorial distribution of the index, GIS analysis and spline interpolation methods were applied in the ArcGIS environment. It has been established that precipitation extremes make the greatest contribution to the composite climate vulnerability index, whilst wind plays a secondary role and temperature indicators have a comparatively smaller influence. A marked spatial heterogeneity of climate vulnerability has been identified: the highest values are characteristic of a number of Northern, North-Eastern and South-Western Regions of Belarus, whilst lower values are recorded in certain parts of the central and South-Western Regions. Based on the calculated indices, administrative districts have been classified into four categories of climate vulnerability, and maps have been produced reflecting the territorial variations of the indicator under study. The scientific novelty of the work lies in the adaptation of the dimensionless climate indices method to the conditions of Belarus, as well as in the transition from station-level analysis to regional climate zoning. The practical significance of the study lies in the potential to use the results obtained in the development of regional strategies for adaptation to climate change, the improvement of spatial planning, the assessment of climate risks, and the justification of measures to enhance the resilience of the country's natural and socio-economic systems.

Climate change in hot and arid regions like Abadan poses a serious threat to food security and water resources. Accurate projections of future conditions are essential for developing effective adaptation strategies. In this study, the LARS-WG 8 model was applied using meteorological data from Abadan station (Iran) under three climate scenarios, SSP1-2.6, SSP2-4.5, and SSP5-8.5, for the year 2040. Interpretation of the climate data for 2023 and 2024 compared to future scenarios for 2040 (SSP1-2.6, SSP2-4.5, SSP5-8.5) at Abadan station reveals a clear trend of warming and seasonal shifts in precipitation. In July, maximum temperature rises from 47.2℃ (2024) to 48.7℃ (SSP5-8.5), while evapotranspiration drops from 393.5 mm to around 291–294 mm, a 25% reduction. December precipitation increases dramatically from 0.8 mm to 25.7 mm in SSP5-8.5, over 30 times higher. In contrast, rainfall in June remains zero across all scenarios. March precipitation declines from 45.0 mm to 19.1 mm in SSP2-4.5 (a 58% drop), while minimum temperature rises from 13.9℃ to 16.0–16.5℃ (about 15% increase). These shifts indicate higher temperatures, reduced summer evapotranspiration, and a concentration of rainfall in cooler months, directly affecting crop water needs and irrigation scheduling. Based on the results obtained, it is recommended that agricultural planning in Abadan move towards climate change-resistant cropping patterns, improve irrigation efficiency, and revise water allocation plans to take into account the increasing temperature and increasing concentration of precipitation in the cold months of the year.

This brief study provides a comprehensive understanding of the impact of global climate change on processes in the cryolithosphere. At the same time, attention is paid to the initial and dependent phenomena and processes, which include solar activity, the degradation of permafrost, and the loosening of buildings and structures that make up the infrastructure. Taking into account specific extreme events arranged according to a cascade scenario, the vulnerability factor of industrial and social infrastructure located in territories affected by exogenous geocryological processes is indicated. The originality of this material is determined by a comprehensive understanding of the consistent mutual connection of exogenous events in nature and the technosphere, which is the environment for the emergence and development of a natural-technogenic emergency. The main conclusion of this study is the proven statement about the need to form an objective understanding of climate processes as part of a comprehensive predictive assessment of the state of social and industrial infrastructure, as a prerequisite for ensuring the sustainable state of a given territory.

Siberia (60–140° E and 48–70° N) is annually exposed to wildfires. In our study, a number of days with high wildfire danger conditioned by weather was calculated using the correlation model of Malevsky-Malevich et al. (2005) that relates the Nesterov index higher than 1000 (high wildfire danger) with a monthly hydrothermal coefficient (HTC) for the vegetation period. We calculated HTC based on data derived from weather stations in current climate and from the climate model INM-CM5-0 in warming climates by the mid-century. Potential areas of major Siberian trees: Siberian pine (Pinus sibirica Du Tour), Siberian fir (Abies sibirica Ledeb.), Siberian spruce (Picea obovata Ledeb.), Scots pine (Pinus sylvestris L.), Siberian larches (Larix sibirica Ledeb., L. gmelinii (Rupr.) Rupr. and L. cajanderi Mayr) were predicted in current and future climates based on our bioclimatic envelope models of their ranges that take into account permafrost thaw impacts.  Potential areas of major Siberian trees were then paired with wildfire danger days to evaluate risks of disturbances caused by both permafrost and wildfire that are the most powerful environmental drivers over the Siberian boreal forest in a warming climate. The basic climate layers (1961–1990) were derived from climate data of 500 weather stations across Siberia using the spline interpolation procedure ANUSPLIN. The 2050s climate layers were derived from output data of the Russian climate model INM-CM5-0 for two IPCC climate change scenarios ssp126 и ssp585 (Parfenova et al., 2024). Coupling areas of major forest-forming trees with fire danger days, forest disturbance risks were mapped in space and time over Siberia in warming climate by the mid-century. The total number of days of high wildfire danger during the growing season in the forested area in Siberia increases by 5–10 days under the mild scenario and by 15–20 days under the severe scenario. The "hot spots" of wildfire-caused disturbances were found in Southern zonobiomes (forest-steppe, subtaiga, and Southern taiga); least disturbed – in Northern zonobiomes (Northern taiga and forest-tundra); and moderately disturbed – between them in middle taiga. This work is supported by Russian Science Foundation, project No FWES-2024-0023.

The paper presents the results of a comprehensive comparative analysis regarding the historical development, modern definitions, and quantification methods of heat waves during the cold season of the year. The key theoretical approaches to identifying extreme temperature phenomena, formed within the framework of climatological, medico-biological, and socio-ecological research directions, are thoroughly considered. The study summarizes the extensive experience of applying various statistical criteria – ranging from absolute deviations and standard anomaly indices to modern percentile-based methods – within the synoptic practice of the CIS countries, the Belarusian meteorological school, and the official recommendations of the WMO. Special attention is paid to the regional ecological and economic consequences of winter warming in Belarus, where sharp temperature transitions above zero degrees disrupt snow cover stability, damage winter crops, complicate ground and air transport operations through dense fog and black ice, and increase public health risks, particularly regarding cardiovascular diseases. The study revealed a significant variability in methodological standards, which often leads to substantial discrepancies in assessing the frequency, duration, and territorial extent of extreme climatic events. Based on the detailed analysis of the Belarusian meteorological observation network, which includes 54 stations, the paper establishes that the most informative and contextually appropriate parameter for monitoring winter heat waves is the daily maximum temperature exceeding the 90th percentile, calculated individually for each month of the cold season from November to March. The authors propose a specific threshold framework, where a winter heat wave is identified when this percentile level is exceeded for 3 or more consecutive days. Implementing this unified methodology provides a scientifically sound basis for developing targeted climate change adaptation strategies, optimizing agricultural planning, and reinforcing regional public safety measures in accordance with the international commitments under the Paris Agreement.

Climate change is profoundly altering the ice regimes of mountain rivers, making long-term monitoring essential for understanding hydrological responses to warming. This study assesses long-term changes in river ice regimes, including the duration of ice cover and other ice phenomena, over the period 1938–2024 based on observations from 34 hydrological stations operated by the Hydrometeorology and Monitoring Center of the Ministry of Environment of the Republic of Armenia and distributed across different natural zones of the Lake Sevan basin. The rivers exhibit a wide range of ice phenomena, including bank ice, ice cover, slush, ice drift, ice jams, and ice dams. The timing and duration of these phenomena are strongly controlled by altitude, with higher-elevation rivers experiencing earlier freezing and later ice breakup. Based on these characteristics, the rivers were classified into four ice-regime categories: stable ice cover, unstable ice cover, absence of observable ice phenomena, and rivers where ice formations have disappeared, primarily because of anthropogenic alterations. The results reveal a consistent reduction in the duration of ice phenomena across the basin throughout the study period. Moreover, since the early 1940s, the rate of change in river ice-regime characteristics has accelerated markedly, indicating increasingly rapid climate-related changes. Analysis of long-term variations in freezing and ice-breakup dates, together with air-temperature variability, demonstrates a clear trend toward later freezing and earlier ice breakup, providing robust observational evidence of the impacts of ongoing climate change on river ice dynamics in the Lake Sevan basin. These findings establish an important scientific baseline for future hydrological assessments and climate change impact studies in high-mountain river systems.

Glacial crevasses, as well as periglacial and englacial lakes in the cryolithozone, are of interest as potential hazards for logistics operations and safety reason. The sizes of Antarctic crevasses can reach several dozen meters and more. They presenting near stations and field bases are very dangerous. Outbursting of periglacial and englacial lakes is a special danger because the sudden water releases can cause significant damage to infrastructure. In 2017 outbursting the englacial Dålk Lake comes to formation of a depression 200×200 m with up to 40 m deep and destroyed the road connected the Russian and Chinese stations with the airfield. Current climatic conditions lead to intensive snow melting. It come to increasing the lake outbursts and formation of new crevasse zones. Thus, monitoring, detection and prediction of these processes has become one of the most important scientific research. The most effective tool to identify crevasses and hidden objects is ground penetrating radar (GPR) method. Mathematical modelling provides significant assistance in interpreting GPR data. However, nowadays, artificial intelligence (AI) methods are been used for automated processing of GPR data. We first apply signal processing techniques to enhance extracted GPR frames, improving image clarity and reducing noise. In subsequent stages, machine learning (ML) and deep learning (DL) methods are used to detect hyperbolic reflections in GPR images, which are related with crevasses. Preliminary results indicate that the AI based methods is effective for detection tasks. These technologies enable automated data processing and improve the accuracy of hazard zone forecasting. AI training is carried out using both field GPR data and synthetic data generated with the gprMax software package.

Climate change is altering the thermal regimes of mountain rivers, making long-term monitoring essential for understanding their hydrological responses to warming. This study evaluates long-term changes in the thermal regime of rivers flowing into Lake Sevan using water temperature records from 12 hydrological monitoring stations operated by the Hydrometeorology and Monitoring Center of the Ministry of Environment of the Republic of Armenia. Spatial and temporal patterns of river water temperature were analysed to characterize thermal variability across the basin and to assess long-term changes under climate change conditions. The results show that maximum water temperatures occur in July–August, whereas minimum values are recorded in January–February. Absolute maximum water temperatures range from 15.6℃ to 29.4℃. River water temperatures exhibit marked spatial variability, with seasonal thermal regimes strongly influenced by altitude and river feeding conditions. During the warm season, water temperatures generally decrease with increasing altitude, while the duration of the warm period varies according to elevation and river feeding conditions. Long-term analyses reveal significant increases in both annual and winter water temperatures, accompanied by a progressive reduction in the duration of ice phenomena. These findings provide robust observational evidence of the impacts of ongoing climate change on the thermal and ice regimes of rivers in the Lake Sevan basin and establish an important scientific baseline for future hydrological assessments and climate change impact studies in high-mountain river systems.

Thermal regime of rivers plays a great role in rivers ecological state. However, there are a lot of gaps in our knowledge about thermal regime of rivers and about long-term changes of water temperatures and a river heat flow due to the scare of open-source water temperature data. During past decade study of thermal regime of rivers is focused on Arctic region, primarily on North-East of Russia. Nowadays, we are expanding the spatial coverage of river thermal regime studies on the permafrost (PF) areas as regions with most dynamic climate and landscape changes. Studied area includes territory of Russia Northerner of 60 N, Russia parts of Baikal Lake and Amur River basins, basin of Okhotsk Sea and Russia part of Caucasus. For all these regions, except the Arctic and Caucasus, our investigations of the thermal regime of rivers are first ones for the past 5–6 decades. We used monthly average water temperature data from more than 400 gauges on rivers in different landscape conditions for 1961–2022. Annual and monthly heat flux was estimated for data from 200 gauges. Change-point years for all studied characteristics, mean and standard deviations, changes as after change-point years as in 1991–2020 in comparison with 1961–1990 were estimated. Although, the analysis of air and water temperature relations was carried out. Results are compared for different parts of PF zone and compared with Arctic non-PF areas. The magnitude of changes of river water temperature in the continuous PF zone is significantly lower than in areas with discontinuous PF and in areas without PF. Very low values of the thermal runoff of the North Caucasus are shown. The regions in which local factors play a major role in shaping water temperature compared to climatic ones have been identified, the Baikal basin, for example. For the first time in more than 50 years, riverine heat flux to the Pacific Ocean seas has been estimated. It is shown that the heat flux of the Amur is comparable to that of the Lena, despite its more southerly position, due, apparently, to the mountainous left tributaries in the PF zone.

This study aims to identify spatial-temporal patterns and recent trends in the thermal regime of rivers in Belarus. Input data includs water temperature (T_w) observations at 48 representative hydrological stations belonged to the state observational network of Belhydromet. The analysis covers the period 1951–2025. Descriptive statistics and linear trend calculations were performed, with spatial analysis conducted in ArcGIS. Results show that after 1990, a clear increasing trends in T_w  are observed across most rivers, linked to regional climate warming. The long-term average T_w for 1951–1989 ranged from 7.6℃ to 11.1℃, while for 1990–2025 it increased to 8.1–13.0℃. The most notable increases occurred in the Pripyat, Neman, and Western Bug basins (West and South of the country), where average T_w rose by 1.0–1.9℃. In the Dnieper basin, the increase was 0.8–1.5℃, and in the Western Dvina basin – 0.5–1.0℃. Trends in annual maximum T_w for 1951–2025 are positive, ranging from 0.2°C to 3.8℃. The highest increases by 1.5–3.8℃ are observed on the rivers in the Southern and Central parts of the country: 2.8℃ in Oressa River (Pripyat basin), 3.8℃ in Sluch River (Pripyat basin). The smallest increases by 0.2–0.40℃ occur in Northern Rivers of the Western Dvina basin and partly in Southwestern areas by 0.02–0.60℃. Spring transition of T_w through 0.2℃ has shifted earlier by an average of 12 days. In the Pripyat, Neman, and Western Bug basins, this now occurs in the third decade of March; in the Dnieper and Western Dvina basins – in the first decade of April. Autumn transition through 0.2℃ to the cooling has shifted later by an average of 8 days. In conclusion, the study reveals significant spatiotemporal changes in the thermal regime of Belarusian Rivers, including increases in mean and maximum T_w (mean from 7.6–11.1℃ to 8.1–13.0℃; positive trends up to 3.8℃), earlier spring warming by 12 days, and delayed autumn cooling by 8 days. These changes are directly linked to ongoing climate warming observed since 1989 in Belarus.

Ensuring safe navigation, protecting hydraulic structures, minimizing economic damage from hazards: all these tasks are priorities in the field of ice study at water bodies. Among the most important types of ice forecasts is the determination of the start and end dates of ice formation, which is a complex process, but substantially different in terms of factors of formation. Therefore, the aim of the study is to introduce machine learning methods (decision tree methods and Naive Bayes classifier) into the practice of modeling ice processes on the rivers of the Lake Sevan basin. The suggested algorithms are based on the probabilistic inclusion of individual traits in a particular class (group). Five hydrological sites of the Sevan basin, where ice phenomena are observed, were chosen for the study: Dzknaget River (observation point (OP) Tsovagyugh), Drakhtik River (OP Drakhtik), Pambak River (OP Pambak), Vardenis River (OP Vardenik), Bakhtak (OP Tsakkar). The work used hydro-meteorological data from 2015 to 2023 ("Hydrometeorology and Monitoring Center" SNCO of MOE of RA). Also, for quality check of methods, the source samples were divided into instructional (from 2015 to 2022) and test (2023) parts. Decision trees and the Naive Bayes classifier method were considered. An analysis of ice phenomena for the rivers of the Lake Sevan basin is presented. Testing of the proposed methods showed that the actual onset of ice phenomena begins later than the forecast dates. Also, the models are worse at determining the end date of ice phenomena. When comparing the relative number of correct forecasts for the entire period of the test sample, the Naive Bayes classifier method has a slight advantage in accuracy.

This article examines the spatial transferability of a gradient boosting model (CatBoost) for forecasting extreme hydrological events on small rivers with a lead time of 1–7 days. Climate data, precipitation aggregates, running discharge statistics, snowmelt indices, and seasonal variables were used as predictors. To assess inter basin generalization, a leave-one-river-out spatial cross-validation scheme was used, in which the model was trained on a set of basins and tested on an independent river. Classification quality was assessed using precision, recall, and the F1 score. To interpret the factors determining model transferability, SHAP analysis was used, revealing differences in the contributions of precipitation and temperature regimes for basins with different conditions for the formation of extreme water discharges. It was found that the quality of inter basin transfer depends on the hydrological similarity of the rivers, the type of recharge, and seasonal characteristics (January–March, November–December). SHAP analysis demonstrated the key role of aggregated water discharge values and revealed differences in the contributions of these factors between the basins. The practical significance of the study lies in the applicability of the developed model to basins with limited or no long-term observational data, provided standard climate data are available. The use of an inter-basin cross-validation scheme (Leave-One-River-Out) allows for an early assessment of the model's generalizability before its implementation in new areas, while SHAP analysis ensures forecast transparency and helps identify key risk factors for each basin. Thus, the obtained results can be used to develop effective and adaptive early warning systems under various hydrological conditions. This study confirms the potential of using machine learning methods to develop portable early warning systems for extreme hydrological events on small rivers, especially in conditions of limited observations. The proposed approach can serve as a basis for developing forecasting systems in regions with insufficient hydrometeorological knowledge.

The removal of chemicals from the catchment and the external load on the reservoir or watercourse are the main causes of their pollution. Mathematical modeling methods are one of the promising areas of research on the ecological state of the water bodies. At the same time, the mathematical approximation of the removal pollutants processes in dissolved form and in the form adsorbed on soil erosion products is complicated by the lack of observational data on the flows of matter from the catchment area and the assessment of water quality and the bottom soil chemical composition.  In addition, the large spatial variability of the underlying catchment area, namely the heterogeneity of the soil composition, significantly complicates the optimization of algorithms for evaluating sorption/desorption processes. On the other hand, the situation is aggravated by the discrepancy between the characteristic time of individual processes – sorption/desorption of heavy metals in the underlying surface of the catchment and the formation of water and solid runoff in the catchment. That is, algorithms that significantly generalize the processes of sorption/desorption of matter should correspond to time-generalized models of matter flows from the catchment. Institute of Limnology of the Russian Academy of Sciences has developed a modeling system for the external heavy metals load on the water object. This system makes it possible to evaluate the removal of dissolved forms and heavy metal products adsorbed on the surface into a water body. The system is based on a model of soil erosion and an external load model, has a balanced basis, takes into account the processes of sorption/desorption in the soil layer, the retention of plant roots in the catchment and the transformation of the flow of heavy metal solutions in a water object due to the unconservativeness of the latter. As a result, the calculation results make it possible to determine guidelines for optimizing economic activity in the catchment aimed at reducing the load.

Monitoring water levels in water bodies is essential for flood forecasting, water resource management, and coastal safety. Traditional measurement methods require regular maintenance, limiting their use in remote areas. Existing alternative approaches are often complex to operate and expensive. Therefore, the development of an affordable, autonomous, and reliable level meter is urgently needed. The aim of the study is to develop and field test an autonomous water level measurement system, substantiating decisions on component selection, calibration, adaptation to field conditions, and processing of the obtained data. To achieve this goal, the following tasks were completed: 1) develop a device design that minimizes component costs compared to existing analogs; 2) ensure autonomous operation through a combined power supply; 3) implement data transmission via SMS for real-time monitoring; 4) conduct field testing of the device. The implemented system is based on the hydrostatic method of liquid level measurement. The design is based on a perforated metal support, supporting three functional units and a measuring sensor. The lower unit houses a battery compartment with lithium-titanate batteries, the middle unit houses a SIM800C communication module for data transmission, and the upper unit houses an atmospheric tube outlet for pressure compensation. To protect against damage, one cable segment is routed through a sealed polypropylene tube. Calibration was performed by comparing the readings from the measuring sensor with those from the calibration sensor and the marked hydrometric rod. Level conversion was performed using theoretical and empirical coefficients, taking into account the maximum output voltage of the sensor and the voltage drop in the system. The system is also equipped with an air temperature sensor. The received data is transmitted every three hours in two ways: via SMS and to a MySQL database. After recalculation, the information is sent to the website and displayed as graphs, allowing for convenient remote monitoring. As a result of this work, an autonomous hydrostatic level gauge was developed and field-tested on the Oredezh River. The proposed design demonstrated operability with a combined power supply, reliable data transmission via SMS, and the ability to integrate with a web interface.

This paper explores the impact of global climate change and basin-wide urbanization on the hydrochemical cycles of the Amur River, viewed through the lens of channel processes during extreme flood events. Despite significant advancements in understanding floods as a primary driver of the rivers hydrochemical regime, a comprehensive synthesis of research in this field has been lacking. Our analysis demonstrates a clear upward trend in regional climate shifts: from 1989 to 2024, the average annual air temperature rose by 1.3℃, with a total increase of 2.0–2.1℃ since the beginning of instrumental records. This warming has fundamentally altered the frequency of high-magnitude floods, accelerated channel transformations, and reshaped geochemical cycles within the river discharge. The Amur River is characterized by a unique hydrological regime. Recurring catastrophic floods in recent years (2013, 2019–2021) demonstrate the impact of hydrodynamic factors on the dispersion of contaminants. Turbulence during peak discharge activates resuspension processes, leading to the re-entry of heavy metals from benthic sediments into the water column, effectively turning the riverbed from a sink into a major pollution source. The study details the mechanisms of channel processes and the periodicity of geochemical cycles, establishing a definitive link between these phenomena. Particular emphasis is placed on the transboundary transport of pollutants from major industrial hubs in China and the Russian Federation, as well as the role of background chemical compounds. Large tributaries of the Sungari and Ussuri rivers are the main sources of anthropogenic trace elements in the Amur. Urbanization contributes to the local accumulation of lead and cadmium in bottom sediments of coastal areas, creating zones of potential secondary pollution. We describe the migration pathways of heavy metals, finding that their concentration increases 2.5–3.5 times during flood stages. Furthermore, flow turbulence and channel dynamics intensify chemical interactions, creating pronounced spatiotemporal heterogeneity in geochemical fluxes. The paper assesses the synergistic effect of anthropogenic pressure and natural factors on water quality, while analyzing how temperature and chemical variables (metal compounds, organic matter) influence the self-purification capacity of aquatic ecosystems.

Protection of surface water objects from pollution and consumption currently remains one of the most important geo-ecological issues in the field of environmental protection and river basin development. The purpose of the work is to identify the quality of the water bodies of the discussed area at the given time and in the given location, to assess the effects of the mining industry on water quality. The work studies the features of the hydroecological and their problems in the Debed River Basin, taking into account the impact of mining activities. The Debed is one of the most important rivers in Armenia. Used methods statistical data analysis, hydrological calculations, as well as processing methods, comparison and contrast, geospatial information, ArcGIS, etc. It was found that the main sources of pressure on the waters in the Debed River are metal extraction (dispersed and non-point pollution), point pollution from untreated residential wastewater, agriculture and transport. The results showed that in the Debed River catchment basin, many rivers at multiple sites were polluted with various heavy metals originating from mining activities, which adversely affected macrozoobenthos development and posed risks to human health in areas where the water is used for drinking purposes. The obtained results have important scientific and practical significance; they can be used as a basis for a comprehensive analysis of environmental and economic studies of the current conditions of the Debed River basin.

Rivers are characterized with a natural self-purification capacity, defined as the ability of aquatic ecosystems to neutralize pollutants through interconnected physical, chemical, and biochemical processes. The persistence of pollutants within a natural water body results from the combined influence of these processes, which collectively determine the self-purification potential of the aquatic environment. However, this capacity is dynamic rather than static, varying across seasons, river stretches, and levels of anthropogenic pressure. When pollutant concentrations exceed critical thresholds, the self-purification capacity may collapse, leading to eutrophication and broader ecosystem degradation. Despite its increasing relevance for integrated water resources management, quantitative approaches for assessing self-purification capacity remain limited, and largely not designed for mountainous river typologies. Such rivers are characterized by rapid flow velocity, low water temperature, high dissolved oxygen concentrations, and pronounced seasonal variability associated with snowmelt and precipitation regimes. Compared with hydromorphological and hydrobiological components, the hydrochemical component of self-purification capacity can be more readily quantified and effectively assessed across different river sections and seasonal conditions. In this study, a new method for quantifying the hydrochemical self-purification capacity of mountain rivers is proposed. The methodology is based on seasonal hydrochemical parameters’ monitoring data combined with river water flow data. The hydrochemical indicators required for the assessment are classified into two categories: mandatory key parameters and supporting parameters. Validation of the proposed method was carried out using Armenian case studies and demonstrated a high level of representativeness and applicability. The proposed approach contributes to evidence-based water governance, supports climate change adaptation planning, and provides an early warning indicator for the eutrophication, which is of growing importance under conditions of increasing global freshwater scarcity.

The improvement of water balance calculation methods for large closed basins, such as the Caspian Sea, requires verification of traditional approaches using modern global databases. This study presents a comparative analysis of three evaporation estimation options for the Caspian Sea water area over the period 1990–2020. The first option is based on the standard methodology of the State Oceanographic Institute (SOI), where evaporation is calculated using empirical formulas based on meteorological observations from five key coastal stations. The second option reproduces the SOI algorithm but uses ERA5 reanalysis data interpolated to the locations of the same stations as input parameters (wind, temperature, humidity). The third option represents direct evaporation obtained from the ERA5 reanalysis, where this parameter results from the H-TESSEL land surface scheme, which describes turbulent heat and moisture transfer. It is shown that the traditional methodology, which provides point estimates, is sensitive to the heterogeneity of meteorological element distribution and to systematic errors of coastal measurements. In contrast, ERA5, through satellite data assimilation and a global grid structure, provides spatially continuous evaporation fields, including direct calculation of evaporation from open water surfaces. Statistical analysis shows that the traditional SOI method systematically overestimates annual evaporation (up to 1535 mm/year at "Tyuleniy" station) and exhibits higher variance and positive skewness compared to ERA5-based approaches. The best convergence between all three methods is observed at the "Ogurchinsky" station on the Eastern South Caspian, while the largest discrepancies occur at Western coastal stations (RMSE exceeding 1100 mm between methods 1 and 2). Correlation between the SOI method with ERA5 inputs and direct ERA5 evaporation reaches 0.55–0.82, confirming the systematic biases in ground-based observations likely caused by the transport of dry continental air masses from Central Asia under easterly wind conditions. A clear geographical pattern emerges: the convergence of methods progressively deteriorates from the Eastern shore of the South Caspian to the Western shore, reflecting regional atmospheric circulation features. The identified discrepancies between the empirical SOI method and the physically based ERA5 reanalysis highlight the need for careful validation of both approaches before updating operational water balance calculations for the Caspian Sea. The comparative analysis of the three options allows for quantitative assessment of discrepancies between empirical and physical approaches, identification of their appropriate application areas, and determination of the potential of using reanalysis data to refine long-term evaporation series, which is critically important for reliable reconstruction of the Caspian Sea water balance.

Groundwater composition is governed by natural factors such as water runoff that dissolves rocks and acquires organic content from soils. The expansion of urban and industrial areas has significantly altered groundwater formation processes, introducing technogenic salts content (Cl^–, SO₄^2–, NO₃^–, NH₄⁺) comparable to natural ions composition. Compliance with SanPiN and WHO guidelines for individual elements is insufficient for water quality characterization, as essential elements may be deficient or toxic elements may appear in bioavailable migration forms. This study presents ecological and geochemical characteristics of 23 springs in the Northeastern Moscow Region (2023–2025). Nearly all springs met Russian and WHO standards, except two exceeding nitrate or COD limits. Essential elements (Ca, Mg, Se) showed variable contributions to daily intake depending on mineralization. Modeling of non-essential elements (Ni, Co, Pb, Cd, Cu) indicated that higher organic content increases organic complexation, altering toxicity potential, with CdCl₂ posing particular risk due to high solubility and cellular uptake. A Water Quality Index (WQI) used in this study combines several key parameters, and, based on their role, establishes the range from excellent quality to unsuitable for consumption. The studied sources were divided into groups: with "good" WQI (30% of sources), with "excellent" WQI (70% of sources). Springs with "good" WQI are primarily located in the Klyazma River valley with its developed infrastructure. In these springs, concentrations of Cl^–, SO₄^2–, NO₃^–, Na⁺ are within the normal range, but consistently high. The composition of "excellent" WQI of most springs shows no significant seasonal dynamics. Generally, seasonal variations below 30% indicate stable hydrogeochemical conditions and their relative independence from anthropogenic influence. Comprehensive risk assessment should therefore consider elemental speciation, essential element adequacy, and seasonal dynamics.

Understanding the species composition and distribution of aquatic macrophytes in the Arctic and Subarctic has become increasingly important due to ongoing climatic and anthropogenic changes in the region. Information on the aquatic flora of water bodies in the Nenets Autonomous Okrug (NAO), Russian Federation, remains fragmentary, and targeted floristic surveys of water bodies in the region have remained extremely limited to date. Given the rapid dynamics of aquatic ecosystems, establishing a monitoring system is essential. To address this knowledge gap, an inventory of aquatic macrophytes (vascular plants, mosses, and macroalgae) is being carried out in the NAO. Herbarium specimens from 118 water bodies were analyzed, including those collected within the Nenets Nature Reserve; all specimens are deposited in the herbarium of the I.D. Papanin Institute for Biology of Inland Waters. The resulting checklist includes 105 taxa. One species and two hybrids, all new to the region, were recorded. Batrachospermum gelatinosum, a species listed in the Red Data Book of the NAO, was identified. The highest diversity was observed in the vicinity of Naryan-Mar (51 taxa). These data establish a baseline for long-term monitoring of aquatic flora and provide a foundation for the science-based conservation of European Russian Subarctic ecosystems.

The Kuibyshev Reservoir was created in 1957 after the Volga River was dammed near the cities of Zhigulevsk and Togliatti. Since Reservoir inception, heterotrophic bacterioplankton investigation have been conducting. These studies have yielded long-term data on changes in its abundance and biomass. However, until recently, its true taxonomic structure remained unexplored, as only a small portion of the bacterial community is culturable. In 2021, 2023, and 2024, we studied bacterioplankton in the lower part of the reservoir, including both classical methods and metabarcoding based on sequencing data from the hypervariable V4 region of the 16S rRNA gene. Over the entire study period, 3061 non-cyanobacterial OTUs were detected; individual samples contained between 327 and 1349 OTUs (average 782). The combined library recorded 45 phyla of the kingdom Bacteria according to Silva's taxonomy; nine of these included more than 100 OTUs each, but 17 minor phyla contained 5 or fewer OTUs. 283 OTUs remained unassigned even to the phylum level. Based on read abundance, the community was dominated by Pseudomonadota, Bacteroidota, Actinomycetota, Verrucomicrobiota, and Planctomycetota, which together accounted for 90% of non-cyanobacterial sequences. The large proportion of Verrucomicrobiota and Planctomycetota phyla is not typical for large freshwater lakes and reservoirs and is a specific feature of the Kuibyshev Reservoir. The 905 OTUs, whose abundance exceeded 0.1% in at least one sample, clearly constituted the bulk of the bacterioplankton in the studied reservoir. The dominant OTU complex included typical freshwater lineages: Planktophila, Nanopelagicus (Nanopelagicaceae: Actinomycetota), Fonsibacter (Pelagibacteriales: α-proteobacteria), Limnohabitans (Comamonadaceae: β-proteobacteria), Massilia and several other Oxalobacteraceae (β-proteobacteria). Additionally, taxa associated with various phytoplankton species and cyanobacterial blooms, such as strain UKL13-3 (NS11-12: Bacteroidota), proteobacteria Roseomonas and Sphingorhabdus, and members of Planctomycetaceae, were prominent. Spatiotemporal analysis revealed no distinct site- or date-specific clusters of bacterial OTUs. The PERMANOVA analysis showed that bacterioplankton taxonomic structure was approximately equally and independently affected by Chl-a concentration and sampling month. According to microscopy data, throughout the study period, bacterioplankton biomass (34–361 μg C/L) and abundance (1.5–12.7·106 cells/mL) varied significantly. On average, both indicators increased seasonally from May to August and decreased by September. Solitary free-living cells prevailed in bacteriaplankton. Bacteria associated to varying degrees with individual cells or colonies of phytoplankton, were recorded in July–August at all stations. The total bacterial biomass and abundance significantly correlated with the Chl-a concentration.

Meromictic lakes are rare type of water bodies. They are characterized by stable vertical stratification caused by the difference in density between layers of water, which persists for many years, centuries, and even millennia. The first inventory of meromictic lakes mentioned 121, including 12 in the USSR. In 2009, the "Encyclopedia of Inland Waters" listed 224 meromictic lakes, 14 of which in Russia. Russia occupies one-seventh of the Earth’s land area, but the number of identified meromictic water bodies was disproportionately small. Having collected publications on meromictic water bodies in Russia from the late 19th century to the present, we compiled a new list of 54 water bodies. This list includes 31 coastal marine water bodies (excluding the Black Sea, which is the world’s largest meromictic body of water), 14 karst lakes, five glacial lakes, four endorheic saline meromictic water bodies in arid zone, and one artificial pond. The most common type of meromictic water body in Russia is coastal marine, where the layered structure arises from the covering of seawater by surface runoff. Seven bodies of water are found on the coast of the Barents Sea, 15 on the White Sea, one on the Bering Sea, three on the Sea of Japan, and three on the Sea of Okhotsk. In the White and Barents Seas, meromictic lakes separated from the surrounding seawater during postglacial coastal uplift; in the Far East, their formation is usually associated with coastal sediment dynamics. Most continental meromictic lakes are of karst origin, while the Northwest of the country many are of glacial origin with high iron and manganese contents in their bottom waters. The smallest group are endorheic salt lakes in arid regions, where during periods of high humidity a fresh upper layer may appear on top of the salt water, where during periods of high humidity a fresh upper layer may appear on top of the salt water. The ecosystem of meromictic lake consists of a vertical sequence of communities in different layers. In the bottom zone, there is an anoxic zone inhabited by ancient microorganisms. At the boundary between the aerobic and anaerobic zones (chemocline), there is a highly productive zone with autotrophic microorganisms: in the case of sulfide anoxia these are sulfur bacteria performing the most ancient anoxygenic photosynthesis; in iron-manganese anoxia, these are iron-oxidizing bacteria that help maintain the mineralization gradient. It is important to ensure all meromictic water bodies are protected along with and surrounding landscapes.

Persistent lake stratification is often accompanied by anoxia in the bottom layer, leading to pronounced vertical heterogeneity of microbial communities and their functional potential. We investigated the vertical distribution of bacterioplankton in two clear-water stratified lakes: Lake Palenoe (Southern boundary of the forest zone, 27 ha, 8 m deep) and Lake Prudovikov (forest-steppe zone, 6.5 ha, 5.5 m deep). Among the heterotrophic bacterioplankton, Planctomycetota and Verrucomicrobiota dominated in both lakes by relative read abundance, with Proteobacteria and Bacteroidota occupying the third and fourth positions. Common freshwater Actinomycetota and Pseudomonadota, e.g., Nanopelagicus and Planktophila (Nanopelagicales), Fonsibacter (Alphaproteobacteria), and Comamonadaceae (Betaproteobacteria), were present in both lakes at similar but low abundances. At lower taxonomic levels, the bacterioplankton of the two lakes differed substantially. Furthermore, while in the epilimnion the amplicon sequence variants (ASVs) present in one lake were substituted by different, but closely related sequences in the other, the differences between the samples from the anaerobic layers were more pronounced due to a more phylogenetically contrasting ASV structure. In general, the vertical structure of bacterioplankton in Lake Prudovikov was notably less diverse than that in Lake Palenoe. Cyanobacteria was the dominant phylum in the epilimnion of Lake Prudovikov but ranked fourth in the less productive Lake Palenoe. In both lakes, representatives of Cyanobiaceae were among the dominants. Besides, the cyanobacteria Dolichospermum spp. and Planktothrix isothrix were dominant in Lake Palenoe, while Pseudanabaena, Raphidiopsis, and Planktothrix agardhii prevailed in Lake Prudovikov. Different taxa of Cyanobacteria and Chlorobiota dominated among phototrophic bacteria in the chemocline of both lakes and the hypolimnion of Lake Palenoe; other groups were minor. Within Chromatiaceae, Thiodictyon syntrophicum was found in Lake Palenoe, whereas three ASVs belonging to Chromatium okenii (previously not recorded in this lake) and an undetermined ASV distantly related to both Thiodictyon and Lamprocystis were present in Lake Prudovikov. Despite clear differences in phylogenetic structure, analysis of PICRUSt2-predicted metabolic pathway abundances revealed functional similarities between the epilimnetic bacterial communities of both lakes. However, samples from the chemocline zone (3.5–4.0 m) and the lowest studied horizon of Lake Palenoe (6 m) differed most markedly from other samples and from each other. Our data demonstrate that functional structure remains considerably stable at high steps of the pathway hierarchy and rather contrasting at the level of predicted gene orthology structure.

The formation and development of the Spaso-Preobrazhensky Solovetsky Monastery on Bolshoy Solovetsky Island in the White Sea required ensuring its sustainable water supply. The final lake in the Western lake-canal system, which provides water for the needs of the monastery, is Potable. It is connected by a channel (originating from it) with a length of more than 2 km (a drinking canal) to the Lake Pityevoуe. Currently, for the water management needs of the monastery and the village. Solovetsky, which is located around the walls of this monastery, water intake is carried out approximately in the middle of the Drinking Canal. The lake under study is currently not under obvious anthropogenic influence. There are no residential buildings or industrial enterprises on its shores. The recreational impact of rowing boats and electric motors is currently negligible, but the tourist flow to the Solovetsky Islands is increasing every year. Studies of hydrochemical parameters of various reservoirs in Russia and abroad indicate that, in addition to anthropogenic effects, climatic changes can affect the properties of water. The purpose of this study was to summarize the data obtained on the hydrochemical parameters of Lake Potevoe over 5 years (2020–2024) and identify possible changes in their natural conditions. Drinking lake is located Northeast of the village Solovetsky. By origin, it is a glacial–tectonic reservoir. The shape of the lake is lobed. The basin stretches from Northwest to Southeast. Two deep depressions are clearly marked in the bottom relief: North and South, separated by an underwater threshold with a depth of 1.8 m above it. Water samples were taken from the boat in layers with a 2-liter horizontal polycarbonate bathometer at a 10 m deep-water station near the source of the Drinking Channel. The conducted studies have shown that climatic fluctuations in air temperature and precipitation led to fluctuations in temperature and water level in the studied reservoir. The combination of these changes influenced the variations in hydrochemical parameters. Chromaticity, electrical conductivity, dissolved iron content (increase) and pH, and mineralization (decrease) depended more on the amount of precipitation. The water temperature affected the oxygen content, and the creation of oxygen-free conditions in the bottom layers of the lake was observed. The occurrence of anaerobic processes in the bottom layers of the lake was accompanied by an increase in the degradation products of organic matter, in particular, bicarbonates. At the same time, there was no increase in the content of hydrogen sulfide, its concentrations for the entire study period did not exceed 5 mcg/L. The results obtained indicate the need for annual monitoring studies at drinking-water facilities, even though fluctuations in hydrochemical parameters are currently mainly associated with changes in climatic conditions.

This study focuses on the validation of a comprehensive geological and environmental diagnostics methodology for assessing the condition of decentralized drinking water sources (DS) in order to improve safety and reduce environmental risks to the health of the population in the Lipetsk Region. The methodological scheme of the study includes 4 consecutive stages: 1) preparatory (sampling of drinking water in water use sources); 2) experimental (own chemical and analytical studies); 3) computational and analytical (assessment of water quality and potential risks to public health); 4) forecast and recommendation (zoning of residential areas of the region in terms of water quality and the level of environmental risks of water use). The monitoring studies covered 63 settlements in 18 municipal districts of the Lipetsk Region. During field expeditions from 2025 to the winter of 2026, 119 water samples were collected from DS, including wells (39 samples), springs (21 samples), wells (12 samples) and columns (47 samples). A comprehensive assessment of the quality of the selected water samples was carried out based on the results of organoleptic (intensity of taste and odor, color, transparency, and presence of sediment) and chemical (12 indicators) analyses using classical and instrumental methods, including 6 indicators that are priority for Lipetsk water (total hardness, iron, manganese, boron, ammonia, and nitrate nitrogen). Organoleptic analysis showed that most often the quality of drinking water taken from DS does not meet the standards in terms of taste and odor intensity – 15.13% and 15.97%, respectively, as well as in terms of water color – 5.88% and the presence of unacceptable sediment in the water – 8.4%. The conducted studies have shown that, in general, for all 18 districts of the Lipetsk Region, the average concentrations of priority drinking water indicators meet the sanitary and hygienic standards for DS. However, in some samples, maximum concentrations of pollutants were recorded that exceed the multiplicity of standards by several times, reducing the quality of drinking water and the level of safety of its use: total hardness (1.01–1.9 MPC), iron (1.06–5.41 MPC), manganese (1.06–1.34 MPC), boron (1.02–3.6 MPC), ammonium (1.02–2.32 MPC) and nitrate nitrogen (1.01–1.85 MPC). The calculation of the population risk showed that about 3 210 people, mostly rural residents of the Lipetsk Region, are at risk of health problems due to the consumption of water of inadequate quality. Based on the results of the study, recommendations were made to improve the safety of drinking water in the Lipetsk Region.

Benthic communities were studied on the underwater slopes of the Valaam Archipelago in the Northern part of Lake Ladoga at depths of up to 30 m. The research involved the use of diving operations, diver-operated video, and remotely operated vehicles. In total, more than 160 invertebrate taxa were recorded. Depth proved to be the most significant factor determining the quantitative parameters of the communities at all studied sites. Wave activity affected zoobenthos abundance in the upper 10-meter layer. In a closed bay, the maximum values of zoobenthos abundance and biomass are observed in the littoral zone (up to 8 m). In a semi-closed bay and in open coastal areas, the peak of abundance shifts to the sublittoral zone (deeper than 8 m), where wave exposure diminishes. Substrate type significantly influenced only the species composition of the communities but not their quantitative characteristics. Large-scale changes are occurring in the lake’s littoral zone – numerous invasions of alien species and an increase in trophic status caused by water warming and pollution. At the same time, starting from a depth of 8 m (sublittoral and profundal zones), changes in the communities are practically unobserved, and the majority of the benthic biomass (more than 70%) is composed of cold-water relict crustaceans. The proposed integrated approach complements the initial survey with detailed work on the underwater slopes and provides the most reliable assessment of the fish forage base and the ecological state of the lake ecosystem. Taxonomic diversity was more fully determined; the biomass of forage benthos in coastal areas and on the underwater slopes was estimated; and the spatial distribution of key benthic species (including relict crustaceans) was determined in relation to topography, substrate, and wave conditions. Annual monitoring observations further enable comparison of changes in the ecological state and food supply of bottom fish across a significant area of the lake’s deep-water zone.

Due to the lack of a dedicated meteorological station in the Tambukan Lakes area, alternative approaches are required to obtain reliable climate data. This study addresses this gap by applying spatial interpolation techniques. The methodology is further complicated by the region's intricate topography, which significantly affects local temperature distribution. The article presents the results of reconstructing mean annual air temperatures in the Tambukan Lakes area due to the absence of local meteorological station (MS) data. Using geoinformation technologies based on the LLRA (Linear Lapse Rate Adjustment) method, observations from seven nearest MS (1955–2025), and the Shuttle Radar Topography Mission (SRTM) digital elevation model, the adjusted mean annual air temperatures for the lakes have been calculated. A comparison of the obtained values with the MS network data using Pearson's correlation coefficient has revealed the highest similarity with the station "Mineralnye Vody". Notably, the analysis demonstrated that despite the relatively short distance between the lakes and the "Mineralnye Vody" MS, systematic temperature differences persist due to elevation and local microclimatic conditions. This finding underscores the importance of elevation-based corrections rather than relying on raw station data. A detailed analysis has shown that the Tambukan Lakes area is systematically colder by 0.74℃, with a root mean square error of 0.8℃, which is considered acceptable. Annual precipitation totals have not been used as a primary criterion due to the complex relief of the Ciscaucasia Region, which influences air mass transport. The feasibility of using data from the "Mineralnye Vody" MS, for subsequent calculation of the water-salt balance of the lakes has been substantiated.

The study presents an overview of the distribution and changes of hydrological cycle's components across the territory of Belarus. In recent decades, precipitation dynamics show no significant trend; however, summer precipitation is decreasing by 2.4 mm per decade, accompanied by an increase in the frequency of heavy rainfall events over the last 25 years. Total evaporation shows a statistically significant shift toward rise occurred in the mid 2000s. This shift is driven by intense summer warming, altered humidity, and stabilizing wind conditions after 2010. Water resources, which correlate with precipitation strongly, have decreased by 17% over the last 10–15 years. River runoff trends include increased winter low flow and winter flood peaks, alongside decreased spring flow and fewer spring floods. In the warm season, rising aridity and more frequent heavy rainfall since the mid 1990s have increased summer autumn low flow minima and rainfall induced flood heights. Climate projections show continuing temperature rising for winter and spring, while in summer and autumn will be a modest increase in hot days. Precipitation shows both an increase in annual and summer totals and a rise in aridity during the growing season across the country. The projected hydrological trends include an increase in winter and summer–autumn low flows, a generally decreasing spring flood peak, and annual flow changes ranging from slight declines to moderate increases depending on the scenario. The average annual runoff will remain close to the historical norm, but the probability of extreme hydrological events rises.

The purpose of the work is to evaluate the internal phosphorus load in Ivan'kovskoe reservoir based on the results of field observations and experimental studies and compare it with the inflow of phosphorus from the catchment area. It is an important source of additional nutrients even if pollution from the catchment area is diminished. The main factors influencing the flux of phosphorus from bottom sediments are: redox potential, pH and temperature, as well as microbiological activity. Ivan'kovskoe reservoir with seasonal flow regulation is under significant anthropogenic stress. Periods with anoxic conditions occur in summer and in winter periods. Bottom sediments are represented by a diverse type of material depending on the region and morphological parts of the flooded valley. External phosphorus load of the reservoir was calculated using results of monthly sampling in the mouths of 14 tributaries in 2022–2023. The phosphorus flux from bottom sediments was determined using a tube method during the period of surveys in 2020–2024. Mathematical quasi-two-dimensional hydrological reservoir model HRM-MSU model was used to clarify the periods with oxygen deficiency in the bottom layer, during which phosphorus is intensively released from sediments. According to the sampling data in 2022 and 2023, the total inflow of phosphates into the reservoir using data from Gorokhovo (downstream from Tver water treatment plant) amounted to 1 359 and 2 125 t. Phosphorus intake from basins of Lama, Shosha and other tributaries amounted to 160 and 246 t/year. In total, the inflow of phosphates into the reservoir with rivers is estimated at 1 519 and 2 371 t PO4/year or in terms of phosphorus 495 and 773 t P/year. By multiplying the amount of phosphorus flux from the sediments of the region on their area, it was obtained that in 2020–2022 the mineral phosphorus output amounted to 1 903, 1 717 and 1 646 t P/year, respectively. At the same time, the riverbed accounts for 36–38% of the total output due to its smaller area. So, the autochthonous load plays a significant role for the Ivan'kovskoe reservoir, exceeding the inflow with tributaries.

Meromictic water bodies of marine origin are most widespread across the territory of Russia; all of them have a unique structure and are the research subjects for scientists in various fields. All such lakes are characterized by a layered structure consisting of a mixing upper layer, a chemocline, and a monimolimnion, where sulfides and products of bacterial hydrogen sulfide transformation accumulate. Meromictic water bodies of the marine origin are formed as a result of the separation of small bays from the sea due to natural or anthropogenic processes. The transition from a stratified marine lagoon to a freshwater lake can take quite a long time, during which the hydrochemical structure and the composition of hydrobionts in the water bodies change significantly. The highly indented Karelian coast of the White Sea is rising as a result of the retreat of the last glacier. As a consequence of this process, stratified water bodies are formed from small bays and lagoons; over time, these may evolve into freshwater lakes. At the meromictic stage of separation, euxinic structure can develop in such water bodies. In the bottom layers, hydrogen sulfide accumulates in high concentrations (up to 600 mg/L), which is produced because of the sulfate reduction process. Various reduced sulfur compounds accumulate in the bottom sediments of the water bodies. Using several water bodies at different stages of separation from the sea as examples, it has been shown that as stable isolation from the sea develops, stratification of the water column forms and the amount of sulfides accumulated in the bottom layers increases. A sufficient amount of organic matter of various origins enters the bottom sediments (content in the upper layers up to 12%). As a result of bacterial sulfate reduction in lake sediments, various compounds of reduced sulfur are formed, namely sulfide, pyrite, elemental, and organic sulfur. At the initial stages of a lake separation from the sea, pyrite sulfur dominates in the total amount of reduced sulfur compounds, similar to marine bottom sediments. As the transition to freshwater lakes proceeds, organic sulfur begins to predominate, making the sediments similar in the distribution of reduced sulfur compounds to freshwater lake sediments. The study of meromictic lakes is a pressing issue in light of the changing climate. Research on such lakes is of great importance for understanding the processes occurring in water bodies formed not only naturally but also through anthropogenic (technogenic) means. It also provides an opportunity to predict the development of negative consequences associated with the artificial separation of marine areas.

Postglacial uplift along the White Sea coast has created numerous meromictic lagoons at various stages of isolation from the sea. Coastal meromictic water bodies at different stages of isolation from the sea are characterized by varying concentrations of chromophoric dissolved organic matter (CDOM) and different optical properties of the water column. In our previous studies, we showed that an increase in CDOM content leads to a shift in the spectral composition of underwater light toward the longer-wavelength region. Seasonal and diurnal changes in the sun’s altitude lead to changes in the spectrum of sunlight reaching the water’s surface. The aim of this study was to analyze the spectral composition of underwater light at different times of the day, as well as in different months of the summer season – in early July and early September. The lower position of the sun above the horizon causes the short-wavelength edge of the spectrum to shift 40–50 nm to the right. However, changes in the solar spectrum at the surface have little effect on the proportions of different colors in underwater spectra: they vary between seasons and within a 24-hour period only in the upper layers, but in water bodies with low CDOM content, these differences are more pronounced. This effect can be explained by the significant absorption of blue light by CDOM. In more isolated water bodies, blue light disappears at 0.5 m depth, which leads to more stable spectral composition in them at different times of the day and across different seasons. However, in the fall, the attenuation of blue light is less pronounced, which may be associated with seasonal changes in CDOM concentration in the upper layers and a decrease in phytoplankton proliferative activity. Despite slight differences in the spectral composition of light, the underwater light environment in summer and autumn has differences. In the morning and evening hours in autumn, illuminance is significantly lower than during the day: for example, the photon flux dencity in the chemocline on the depth of 3 m is around 2 μmol/m²‧s during the day, at 8 a.m. the same intencity is registered at 2.7 m, and at 8 p.m. it reaches only a depth of 0.3 m. Thus, during the different months of the White Sea summer, the underwater light conditions in highly isolated humic water bodies primarily vary in terms of daylight duration. In addition, in poorly isolated water bodies the underwater  changes of light spectral composition are registered when the Sun is low on the horizon.

Bol'shiye Khruslomeny and Bannoye Lakes on Oleniy Island (Kandalaksha Bay, White Sea) represent a unique example of anthropogenic transformation of marine bays into isolated water bodies. In the late 19th century, during sawmill construction, two bays were separated from the sea for fresh water supply, and passages between islands were filled with sawmill waste. After 130 years of isolation, contrasting hydrochemical conditions developed: Bannoye Lake became freshwater dimictic with seasonal anoxia, while Bol'shiye Khruslomeny Lake became meromictic with euxinic anoxia and up to 600 mg/L hydrogen sulfide in bottom layers. However, accumulated environmental damage from plant operations, including soil contamination with PCDD/PCDFs, has not been previously assessed. A pilot study was conducted in September 2025. Soil samples were collected layer-by-layer at a storage site for antiseptic-treated timber. Analysis of 17 toxic PCDD/PCDF congeners was performed by GC-MS with toxicity equivalent calculation (WHO-TEQ). Extremely high contamination levels were recorded in all soil horizons. In the 0–20 cm layer, total PCDDs reached 1449 ng/kg, PCDFs reached 335 ng/kg, and the WHO-TEQ value was 71.4 ng/kg, which exceeds the current Russian hygienic standards for residential areas (50 ng/kg) and agricultural land (5 ng/kg) (SanPiN 1.2.3685-21). Deep vertical penetration was observed: at a depth of 40–80 cm, total PCDDs remained at 1444 ng/kg, while PCDFs increased to 354 ng/kg. The PCDD/PCDF ratio > 4 and dominance of highly chlorinated congeners are typical for contamination from chlorophenol-based preservatives. This vertical distribution is atypical for aqueous antiseptic solutions (dioxins usually sorb in the upper 5–10 cm). The observed migration indicates an oily carrier (petroleum oils, creosote), increasing hydrophobic dioxin mobility. This hypothesis is supported by local testimonies about a red-colored preservative, characteristic of technical pentachlorophenol in oil. Thus, chronic pollutant input occurred for decades via dripping from timber and precipitation infiltration. Soils of the former sawmill represent a significant secondary dioxin source. The proximity of the lakes poses a high risk of supertoxicants entering aquatic ecosystems, with subsequent accumulation in bottom sediments and trophic chains. This pilot study substantiates the need for a detailed survey of the territory, including storage areas, runoff pathways, and lake water areas.

The activity of natural phytoplankton in the presence of adverse factors is actively studied using chlorophyll fluorescence. The effect of H₂S at different concentrations on the light-induced photo-synthesis of natural cryptophyte microalgae Rhodomonas sp. (meromictic waters of the White Sea) was studied using chlorophyll fluorescence induction curves. Fluorescence induction curves (OJIP curves) were recorded using an Aquapen–C 100 fluorometer (Photon System Instruments, Brno, Czech Republic). It was shown that exposure to H2S (8 mg/L) decreased the relative maximum electron transport rate (ETR_max) and the maximum light energy utilization coefficient (α), while non-photochemical fluorescence quenching), associated with a relative increase in the dissipation of excess energy, increased. Analysis of fluorescence induction curves revealed that incubation of microalgae for 10 min with H₂S at concentrations above 2.3 mg/L significantly reduced the functional activity of PSII (PI_ABS), expressed as high values of the quantum yield of PSII photochemistry (F_V/F_M), the proportion of active reaction centers (ABS/RC), and the quantum yield of electron transport in PSII (φE₀). A decrease in electron transport is accompanied by an increase in the dissipation of unused light energy (DI₀/RC). H₂S at concentrations above 2.3 mg/L reduced the amplitude of all phases, primarily shortening the I-P phase, indicating disruption of electron transport in the plastoquinone-cytochrome b₆f complex between photosystems. Thus, natural Rhodomonas sp. microalgae experience stress when exposed to 2.3 mg/L H₂S, which is significantly higher than the concentrations typical for the chemocline and anaerobic zones of water bodies where Rhodomonas sp. are found. The use of fluorescence methods is proposed for studying the state of phytoplankton in coastal meromictic water bodies with varying H2S concentrations.

The granulometric composition of bottom sediments of lakes reflects all processes occurring in the water body and within the catchment area. The GC of sediments is a function of the soil composition of the catchment, the dynamics of transport and sedimentation, and the physicochemical and biogeochemical conditions. Investigation of the GC is necessary to determine the nature of changes in the composition of BS along a section, with the aim of establishing the characteristics of the hydrological regime and changes in the water level regime of the lake in the past. To determine the GC, a method is applied for identifying six fractions of BS that determine the mechanism of organic and mineral material sedimentation in the aquatic environment. This is carried out using the pipette method in combination with the sieve method (FR.1.31.2018.29623). The calculation of fraction content is performed on an absolutely dry sample weight. The relative measurement error for all granulometric fractions ranges from 19% to 29%. Lake bottom sediments are classified according to N.A. Kachinsky. The study was conducted using the example of the poorly studied Bannoye Lake, which was separated from the White Sea by a stone dam during the construction of a timber mill on Oleniy Island in 1897 for the purpose of desalinating the lake water and using it to operate steam engines. Before the timber mill was built, this lake was a deep-sea bay extending far into the land. Within two years, the sea bay transformed into a fresh lake, which is still actively used today as a source of fresh water, domestic wastewater is discharged into Gorelaya Bay. Bannoye Lake did not attract the interest of scientists who had previously conducted research on a number of similar water bodies located at different stages of separation from the Kandalaksha Bay of the White Sea (E.D. Krasnova, 2021), and no studies of the lake have been carried out to date. The material for studying the current state of BS of the desalinated Bannoye Lake consisted of samples collected during the summer low water period of 2024 by employees of the Laboratory of Ecoаnalytical Research, using a gravity corer (sampling interval 5 cm). The isolation and desalination of the lake created conditions for the accumulation and mineralization of the organic matter formed there, which can be estimated by the loss on ignition (LOI) content. The ratio of mineral and organic components was also determined in the identified granulometric fractions of the studied sediment samples. The identified differences in the granulometric composition of the sediments likely reflect stratification features associated with variations in sediment accumulation in opposite parts of the lake and the high productivity of organic material within the water body itself.

Meromictic reservoirs are defined as aquatic systems in which the water column remains partially or completely unmixed during circulation periods. This leads to the formation of layers with varying densities and distinct ecological parameters. This feature makes meromictic lakes excellent model objects for studying the factors that determine the vertical structure of phytoplankton (PhP). Our study examines three meromictic lakes with different climatic and geomorphological characteristics. Lake Skurcha is connected to the Black Sea, while lakes Kislo-Sladkoe and Elovoe are partially isolated from the White Sea. Salinity, temperature, spectral characteristics of transmitted sunlight, and total illuminance were measured and the abundance of the dominant predatory dinoflagellates was assessed for the White Sea lakes. We then determined how these parameters affect the vertical distribution of PhP structure, specifically species composition and abundance. According to the multiple regression analysis the factors determining changes in PhP structure varied across water bodies. In Lake Skurcha, temperature was the most significant factor for overall PhP distribution (31.5%, p = 0.002). The 560–580 nm light spectral range was crucial for fucoxanthin-containing algae (45%, p = 0.003), and the 600–650 nm range for the phycobilin-containing Cryptista group (76%, p = 0.063). In Lake Kislo-Sladkoe, the 481–550 nm range was the leading factor for PhP distribution (54%, p = 0.034), due to the dominant species Rhodomonas sp. contains PE545. In Lake Elovoe, salinity and predators explained 79% of the variance in PhP structure (p < 0.05). The vertical changes in these environmental parameters led to development of distinct PhP communities in specific layers of each lake. In Lake Skurcha, diatoms and small algal species dominated the surface layer. Dinoflagellates prevailed at 2–3 m depth, and cryptophyte algae occupied the bottom of the photic zone. Cyanobacteria dominated in the upper layer of Lake Kislo-Sladkoe, and Rhodomonas sp. prevailed in the highly productive zone just above the chemocline. In Lake Elovoe, diatoms prevailed in the freshwater zone. The brackish zone contained two layers of small cryptophytes. These layers were separated by the thin zone dominated by the predatory dinoflagellates Oxyrrhis marina and the euglenoid alga Euglena proxima, which is likely too large for this presator.

The isolation of marine areas during the construction of various hydraulic structures may be accompanied by a reduction in their natural water exchange with the sea, the development of stratification, and the emergence of hydrogen sulfide in anaerobic waters. In the late 19th century, for the technical needs of a timber mill being built on Oleniy Island (Kovda Bay, Kandalaksha Bay of the White Sea), two nearby marine bays were isolated from the sea by stone dams. Over the relatively short period (about 130 years) that has passed since their isolation, lakes have formed in place of the marine bays: Bolshiye Khruslomeny (saline lake) and Bannoye (freshwater lake). The current state of both reservoirs was studied in August 2024. The main hydrochemical characteristics were determined directly on board the boat. In the field laboratory, the concentrations of hydrogen sulfide (determined by photometric and iodometric methods), dissolved iron forms (determined by photometric methods using ferrozin in water samples filtered through a 0.45 μm filter), and biogenic elements were determined using standard and validated methods. At the same time, analytical procedures were carried out taking into account all the subtleties of the selection and analysis of water with a high content of hydrogen sulfide, which made it possible to minimize its losses as much as possible and obtain correct results. The ionic composition of water was determined on a Shimadzu LC-20 Prominence liquid chromatograph with a conductometric detector. Bolshiye Khruslomeny Lake (maximum depth 19.5 m), although it has not yet completely lost its connection with the sea, is a saline meromictic water body with clearly expressed stratification and the presence of thermocline, chemocline, and halocline. The anaerobic waters of the monimolimnion contain hydrogen sulfide at concentrations of 500–600 mg/L, which is significantly higher than, for example, in the well known meromictic Mogilnoye Lake (200 mg/L). In the bottom waters, a decrease in sulfate concentrations is accompanied by a reduction in the sulfate to chloride ratio, which indirectly confirms the high intensity of the bacterial sulfate reduction process. In freshwater Bannoye Lake (maximum depth 5.5 m), stratification develops twice a year – in winter and summer. For instance, in August 2024, although the upper water layers were supersaturated with oxygen (up to 130%), hydrogen sulfide appeared in the bottom water layers (0.43–0.49 mg/L) with complete depletion of oxygen. A comparable contribution to the sum of the main ions in the salt composition, along with bicarbonate and calcium, is made by chloride and sodium. This most likely reflects both the island location of Bannoye Lake and the influence of White Sea marine aerosol on the composition of its waters, the marine past of this water body.

Northern ecosystems exhibit low resilience to diverse stressors and demonstrate extremely slow recovery rates. The White Sea waters and its coastal zone are exposed to anthropogenic pressures from both regional and global sources. Emissions of organochlorine compounds (OCs), particularly those classified as persistent organic pollutants (POPs), remain a significant environmental threat (Stockholm Convention, 2025). These compounds pose risks due to their resistance to degradation in natural ecosystems, high lipophilicity, bioaccumulative potential, and multifaceted toxic effects on biota. Notably, the presence of OCs (including chlorophenolic compounds, CPs) in natural ecosystems may also stem from non-anthropogenic sources. The ongoing uplift of the White Sea’s coastal zone gradually isolates small water bodies, fostering the development of unique hydrological and hydrochemical regimes. These regimes are shaped by morphometric characteristics, water exchange dynamics, and the freshwater-to-seawater ratio (Krasnova, 2021). Such factors steer the evolution of these water bodies toward salinization, desalination, or the establishment of a meromictic structure. As isolation progresses, the aquatic biota undergoes significant transformation: marine species are gradually replaced by a diverse assemblage of organisms capable of thriving across a wide salinity gradient, including fully freshwater conditions. Research on these isolating water bodies provides valuable insights for predicting the formation of OCs in larger natural systems, where direct study is often expensive. This study presents findings on the behavior of OCs (including POPs) in bottom sediments of small lakes at different stages of isolation from the White Sea. Analyses revealed the presence of persistent highly chlorinated benzenes and CPs in the lake sediments. The occurrence of POPs is attributed to long-range transport from low and temperate latitudes, as well as inputs from nearby regions. CPs are dominated by mono- and dichlorinated phenols. Furthermore, the study demonstrates that seawater influences both the composition and spatial distribution of OCs in the bottom sediments.

The main consequences of anthropogenic impacts include changes in the hydrological regime, anthropogenic eutrophication, pollution, toxicification, thermofication, acidification, and destruction of aquatic ecosystems. Recovering a water body from a pathological state and ecosystem degradation is extremely difficult. This area of activity is called restoration and eco-rehabilitation of aquatic ecosystems. Examples of lakes in a pathological state (with "extremely dirty" waters) include Lakes Nizhny (56 ha) and Sredny Kaban (119 ha) in Kazan. In the 1980s, they were essentially wastewater settling basins and were in a pathological state. The lakes were characterized by low transparency (0.1 m) and a black water color, a change in water type (from hydrocarbonate-calcium to sulfate), high water hardness, exceeding the maximum permissible concentration by tens and hundreds of times, elevated temperatures (they did not freeze), and a strong hydrogen sulfide odor. Sporadic species were observed in the plankton and benthos, and unnatural colors were observed in planktonic organisms. Between 1983 and 1987, they were brought out of their toxic state through the use of special measures (removal of the layer of contaminated bottom sediments, aeration of the water, cessation of wastewater discharges, etc.). As a result of studies to assess the ecological state, indicators characterizing the pathological state of the water body were identified. Restoration projects were carried out for a number of small lakes in Kazan (eutrophicated and polluted). Experiments with lake restoration projects have allowed us to propose several principles for the concept of eco-rehabilitation of water bodies: "consideration of the type of aquatic ecosystem", "consideration of the nature of anthropogenic impact", "consideration of the ecological state", "consideration of the type of water use", and others. The author understands that restoration is a natural process, during which the condition of a reservoir improves through self-purification processes or under the influence of special measures, and eco-rehabilitation is the use of special physical, chemical and biological measures to improve the condition of a reservoir.

Bottom sediments carry information about the processes occurring in water bodies. Sedimentation processes are one of the most significant factors in the formation of bottom sediments. The quantitative distribution of suspended matter in the few meromictic water bodies is poorly studied. One of such bodies of water is Trekhtsvetnoye Lake, located on the shore of Rugozerskaya Bay (Kandalaksha Bay). The area of the Trekhtsvetnoye Lake is 3.2 ha, and its maximum depth is 7.5 m. The study, conducted for exploratory purposes, examined the vertical distribution of suspended matter in the deep-water zone of the Trekhtsvetnoye Lake. Sampling was carried out in September 2023. Water samples were collected using a horizontal bathometer with a volume of 5 L. The suspended matter contained in the water was deposited onto pre-weighed nuclear track filters (pore diameter 0.45 µm) and GF/F glass-fiber filters (for the determination of suspended organic carbon using Euro EA 3000 elemental analyzer) by vacuum filtration. The suspended matter concentration in the Tretsvetnoye Lake does not exceed 5 mg/L down to a depth of 2 m and reaches a maximum of 49 mg/L in the chemocline zone. Below the chemocline, the suspended matter concentration increases from 21mg/L to 36 mg/L in the bottom layer.  Despite the increase in suspended matter with depth (after the chemocline zone), its organic enrichment decreases with depth (from 29% to 11%). At the same time, the organic carbon content slightly increases in the bottom layer (16%). Thus, based on the high concentration of organic matter in water layers, where the suspended matter content is highest (in the chemocline zone) we can conclude that the Trekhtsvetnoye meromictic Lake is highly productive (due to the high number of microorganisms in the chemocline, where labile autochthonous organic matter is concentrated). The identified features of suspended matter distribution in the Trekhtsvetnoye Lake differ from those in freshwater lakes without stratification. This confirms the importance of studying the behavior and distribution of suspended matter in meromictic lakes.

The Okhotsk Region holds a leading position in the Russian mineral resource sector for gold and platinum mining. This study was conducted at gold and platinum mining sites in the Ayano-Maysky district of the Khabarovsk Territory (Tas-Yuryakh, Ryabinovy, Muktana, and Konder). Mining operations in the extreme natural conditions of the Northern Khabarovsk Territory significantly impact the state of local soils and water bodies. Open-pit mining and traditional processing technologies lead to the accumulation of industrial waste and the intensification of exogenous processes in disturbed areas, which serve as the primary causes of soil and surface water pollution. Waste heaps, tailings facilities containing liquid pulp, and settling ponds pose the greatest environmental hazards during mineral extraction. The interaction of decomposition products with under-oxidized minerals contributes to the enrichment of wastewater. During periods of heavy rainfall, turbid enriched solutions are washed into the soil and surface watercourses via sheet erosion processes. Even after decommissioning, these sites remain long-term sources of local pollution for natural ecosystems, particularly affecting soil cover and natural waters. The technological methods used in mining involve the release of various heavy metal compounds into the environment, especially into surface soil layers and water bodies. This article examines the distribution patterns of chemical elements (Fe, Cu, Zn, S, Pb, Cd, Co, Ni) at various distances from operating enterprises and the conditions of their concentration depending on environmental factors. High concentrations of nickel and zinc, as well as elevated lead content, were detected in soil profiles, resulting from the dissolution of chemical compounds in ore-bearing rocks and the activation of exogenous processes. The distribution of element anomaly levels in soils revealed that the migration of chemical compounds within the soil space and subsequent soil pollution manifest at a distance of up to 300–500 m from waste heaps and tailings facilities. Elevated levels of iron, aluminum, manganese, and copper were also noted in watercourses. Finally, the core principles have been formulated for an environmentally adapted land-use regime tailored to the mountainous conditions of the northern Russian Far East.