The Taganrog Bay is the most ecologically vulnerable water area of the Sea of Azov, subjected to significant anthropogenic impact from the ports of Mariupol and Taganrog, as well as the Don River discharge. This paper analyzes the processes of potential pollution transfer from the bay into the Sea of Azov using a three-dimensional Princeton Ocean Model hydrodynamic model and Lagrangian modeling of passive particle trajectories. Model circulation was calculated for 2020 with high spatial resolution, followed by numerical tracking of 7,350,000 virtual particles placed in the main pollution zones. Lagrangian analysis identified key transport pathways, accumulation and retention zones for pollutants, and seasonal variability of water exchange through the Dolzhansky Strait. It is shown that the transfer of potential pollution is determined by a combination of wind forcing, Don discharge, and local circulation. Comparison of model results with MODIS satellite data (2000–2024) confirms the spatial patterns of organic matter distribution and the identified transport directions. The obtained results can be used to assess ecological risks associated with the outflow of pollution into the Sea of Azov and to justify environmental protection measures in the region.
Kamchatka is one of the promising gold-mining provinces of Russia. As deposits in the South Kamchatka and Central Kamchatka ore districts are being exploited, the potential for industrial development of the North Kamchatka (Ossora) ore district increases. For a fundamental understanding of Kamchatka’s metallogeny and for prospecting and exploration, it is important to study the age and forming duration of ore objects and their relationship to magmatic events. Based on the K–Ar isotope ages of adularia-quartz veins from the Tutkhlivayam ore occurrence, this article presents the first data on the age of epithermal mineralization in the Ossora ore district of Kamchatka. The formation of the Tutkhlivayam ore occurrence took place in the interval of 7.9–5.3 Ma, which is comparable with the ages of products of the Tolyatovayam volcanic complex (10.2–4.0 Ma) and may indicate a relationship between the ore-forming processes and its emplacement. The chronological sequence of ages for the adularia-quartz veins supports the hypothesis that the Tutkhlivayam ore occurrence formed as a result of a single hydrothermal system operating for ∼ 2.6 million years, which is comparable with similar epithermal deposits in suprasubduction zones. The data obtained can be used to predict mineralization in similar settings.
The mixing of waterbodies and mixing efficiency estimates for different forcing mechanisms remain one of the main challenges in limnological studies, with a deep theoretical background and a wide range of practical applications. This paper examines the mixing that is triggered by surface cooling during the period of open water. The cooling often occurs at night and is largely determined by infrared radiation fluxes, in this regard, this type of forcing is usually positioned as the radiative mixing mechanism. To calculate the mixing efficiency η, an integral energy method was used, within which this parameter is defined as that portion of the external forcing that is spent on mixing itself, as opposed to viscous dissipation. Specific features of energy fluxes between different energy pools have been revealed for radiative type of forcing. For each identified mixing episode the changes of background potential energy were assessed, together with energy sink due to dissipation. Long-term temperature series for different depths at two small water bodies – a forest lake and a city pond – were used as initial data. Calculations carried out for several hundred mixing episodes showed that the mixing efficiency value, on average, significantly exceeds the canonical threshold 0.17. The correlation has also been identified between efficiency and CML thickness: vertical mixing resistance increases with CML deepening. This result introduces a new challenge to the “universality vs variability” dilemma: the efficiency may depend not only on the type and intensity of forcing, but also on the parameters of the initial temperature profile.
The magnitude of the Kamchatka earthquake of July 29, 2025, was significantly higher than the estimated maximum possible earthquake in the region. At the same time, despite its high magnitude, the intensity of shaking in Petropavlovsk-Kamchatsky was significantly lower than predicted. This article explores one possible explanation for this phenomenon, which involves the nonlinear relationship between stress and deformation caused by seismic vibrations in the soil. The results of computer modeling of seismic processes in dispersed soils are presented. The calculations are based on assumptions about the properties of soils and the parameters of seismic impact. The obtained results have practical significance for seismic microzonation.
The high-amplitude seismic waves generated by the earthquakes with magnitudes similar to that of the July 29, 2025 Kamchatka event (MW 8.8) create the background noise that can potentially mask any post-seismic activity during the first few minutes following the mainshock. Detection of signals from potential aftershocks buried in the coherent noise can be enhanced using a matched filter detector based on waveform cross-correlation with high-quality waveform templates obtained from historical events in the same region. The array stations of the International Monitoring System (IMS) located at regional and teleseismic distances provide one of the most effective networks for detecting seismic events globally. However, the coherence between noise signals and the sought signals, as generated by very similar sources in the same area, makes less efficient the detection methods based on noise suppression by velocity filtering such as beamforming. For the event on July 29, 2025 near Kamchatka Peninsula, the noise reduction method based on adding stochastic noise to the actual data was tested. During the initial 10-minute period following the mainshock, several reliable event hypotheses were created. These hypotheses are similar to those reported by the International Data Centre (IDC) and are based on the data from the same IMS stations. The IDC and the International Seismological Centre had not reported any events during this time frame, despite extended automatic and interactive analyses.
Kodinka Formation mudstones (mainly silty claystones) in the Middle Urals are the main research subject. They have source rocks from Upper Frasnian accretionary orogen in the East European Platform (EEP) east margin. We studied mineral and chemical (major oxides and some trace elements) composition of the claystones for source rocks and watersheds climate reconstructions. During that we traced back to multiple source shift, which was the key to physical weathering improvement and chemical weathering weaking, which, in turn, facilitated delta progradation to the discharge area, also led to the presence of a more distinct geochemical signal of mafic and ultramafic rocks in the erosion products: an increase in the amount of Ni, Cr, Mg and Na in mud deposits. Most likely, this phenomenon was associated with episodes of tectonic activity (and not, for example, with the mountain glaciers buildup), which “obscured” climatic factors, rather than with something else. In this reason, deltaic and associated deposits were excluded from dataset as unreliable when reconstructing climate using the equation of K. Deng et al. and the chemical index of alteration, as well as the robust weathering index and mafic index of alteration. The near-surface mean annual air temperatures values (about 15–20 ∘C) calculated for samples taken from littoral and sublittoral facies, and the characteristics of titanium accumulation in them allow us to assume the existence of a warm humid low latitude climate for the catchment areas of the Kodinka Formation. Apparently, such a climate on the eastern periphery of the EEP began to exist not from the Tournaisian age, as shown on global paleoclimatic maps, but somewhat earlier.
In April 2024, an engineering seismometric station was installed in a residential building in Severo-Kurilsk (Paramushir Island, Sakhalin Oblast) to obtain information about the vibrations of structures and adjacent ground areas during earthquakes as part of seismic observations conducted by the Sakhalin Branch of the Geophysical Survey of the Russian Academy of Sciences. Based on the obtained data on the intensity of the Kamchatka earthquake of July 29 (30), 2025, MW = 8.8, in residential buildings in Severo-Kurilsk, the development of the seismic process before and after the earthquake was analyzed. The obtained data were compared with data from a stationary seismic station in Severo-Kurilsk, located 900 m from the residential building. Both stations are equipped with strong vibration sensors installed in different conditions. Of the 1,790 earthquakes (with a magnitude of M ≥ 3.5) recorded by the regional seismic network from July 29 to October 15, 2025, 195 events with an intensity of I ≥ 3.6 impacted residential buildings. Of these 195 earthquakes, 14 had an impact magnitude of I ≥ 6.0, and the main directions of the axes of maximum impact on residential buildings were east–west and north–south. The study results demonstrate that integrating engineering and technical monitoring into the urban environment is an important element of seismic risk reduction strategies and operational decision-making after strong earthquakes.
Tidal dynamics play an important role in Kara Sea circulation, influencing currents, sea ice formation, and biogeochemical processes. However, accurate numerical simulation of these processes in regional models depends on the choice of tidal forcing at open lateral boundaries. This study evaluates the performance of three tidal models – TPXO9, FES2014, and Arc2kmTM as sources of boundary forcing for a high-resolution regional Kara Sea model based on MITgcm numerical kernel. The goal is to identify the optimal tidal forcing that best aligns with observations from coastal stations. Numerical experiments have revealed significant discrepancies in tidal energy estimates among the models. The FES2014 model has shown the closest agreement to observations, while Arc2kmTM exhibits the largest errors. However, when used as boundary forcing in the regional Kara Sea model, Arc2kmTM yields the smallest errors in simulated tidal amplitude and phase. Overall, the regional model reproduces M2 tidal amplitudes well but introduces slight phase shifts in the southwestern part of the Kara Sea. Our findings emphasize that no single tidal model can be considered universally optimal. The choice depends on regional conditions and modeling objectives. For our regional model, Arc2kmTM is recommended as a source of tidal forcing at the open boundaries of the regional model, though global models like FES2014 remain viable alternatives. This work emphasizes the need for improved validation methods and highlights the challenges posed by limited observational data in the Arctic region.
On July 29, 2025, an earthquake with a moment magnitude of MW = 8.8 occurred in the Kuril–Kamchatka Trench to the east of Petropavlovsk-Kamchatsky. This earthquake ranks among the ten strongest instrumentally recorded seismic events in the world. For the first time, a megathrust earthquake of such magnitude (greater than 8.5) caused no human casualties or mass destruction. This was largely due to the advanced implementation of preventive measures on the territory of Kamchatka Krai. These measures included the targeted strengthening of the seismic resistance of buildings and structures, as well as the enhancement of alert and population evacuation algorithms. The scientific basis for planning these seismic safety measures was provided by the long-term earthquake prediction carried out by Academician of the Russian Academy of Sciences Sergey A. Fedotov. This paper is devoted to a contemporary reassessment of the results of long-term earthquake prediction for the Kuril–Kamchatka island arc by S. A. Fedotov in the context of the 2025 Kamchatka megathrust earthquake. The paper details the development and evolution of the method, which is grounded in the concepts of seismic gaps and the seismic cycle. The cycles of seismic activity and seismic energy release in the source area of the strongest earthquake, as constructed by S. A. Fedotov, together with the foreshock–aftershock scenario, are presented. The paper describes the long-term earthquake predictions for five-year periods and provides an overall assessment of their reliability. It is shown that, since 1965, the sources of all earthquakes with M ≥ 7.75 have occurred within the seismic gaps that S. A. Fedotov had identified as the most probable areas of the future strongest earthquakes. The source of the 2025 megathrust earthquake originated in a region that, as early as the beginning of the 1980s, had been identified as one of the segments of the Kuril–Kamchatka Arc where the next strongest earthquakes were expected. According to a refined prediction made in 2019, the probability of a megathrust earthquake occurring in that area within the following five-year period was estimated at 50.4%. Thus, the long-term earthquake prediction method by S. A. Fedotov has been successfully verified by a planetary-scale event. The 2025 Kamchatka megathrust earthquake has convincingly confirmed its fundamental tenets, indicating the high predictive efficiency of the method.
Using a complex of tools for data recording and analysis, the paper investigates ionospheric parameter dynamics during a strong earthquake in Kamchatka on July 29, 2025 (magnitude M = 8.8). The data of the ionospheric critical frequency foF2 of Paratunka observatory (Kamchatka, IKIR FEB RAS), and the data of the regional GNSS receiver network, located near the earthquake source, were under analysis. Using data from GNSS receivers, the values of absolute vertical total electron content (TEC) and disturbance indices of vertical TEC variations (WTEC) were studied. Data detailed analysis was realized using a new method based on wavelet transform. For the estimates, anomaly intensity measure, characterizing weak, moderate and strong ionospheric disturbances, was used. Before and during the earthquake on July 29, 2025, anomalous changes were distinguished in ionospheric parameter time series. They characterize moderate and intensive oscillation processes in the ionosphere exceeding the background level. A large-scale long (about 2 days) negative anomaly was detected three days and a half before the earthquake against the background of low geomagnetic activity according to the data of Paratunka observatory and GNSS receivers. During the development of the aftershock process, according to data from the Paratunka observatory and data from all GNSS receivers, a large-scale positive anomaly was identified, exceeding in intensity the background variations in ionospheric parameters by three times and more. The positive anomaly lasted for about 2 days. In the region of PAUJ station, the ionospheric disturbances were the most intensive and significantly exceeded in amplitude the disturbances, observed during the period under analysis when geomagnetic activity increased.
Geofluid systems are unique geomechanical sensors, as they can generate earthquakes themselves and also respond to changes in Earth activity. The MW = 8.8 earthquake of July 29, 2025 in Kamchatka was accompanied by numerous geofluid anomalous phenomena: (1) regional seismogenic faults activity; (2) significant post-seismic decreases in water levels (the first meters) and rates in wells of low temperature geothermal fields (Vilyuchinsky, Paratunsky and Ketkinsky); (3) omissions of eruptions of the Bolshoy geyser (Valley of Geysers) and the emergence of a new geyser-well (Kumroch); (4) the beginning of volcanic eruptions (Krasheninnikov volcano for the first time in ∼600 years, Klyuchevskoy volcano) and volcanoes activity increase (Karymsky, Mutnovsky, Kambalny). In this study, the ability of geofluid systems to track seismic events was used to identify the activity of regional seismogenic faults and volcanic magmatic systems (the Frac-Digger method). This provides an explanation for the observed phenomena in terms of the geomechanical regional stretching of Kamchatka, which was associated with an MW = 8.8 earthquake followed by a decrease in geofluid pressure. In magma systems of volcanoes, this triggered boiling and gas-lift of magma with subsequent eruptions. In the fractured-type reservoirs of low-temperature hydrothermal systems, this led to a significant drop in water levels and a cessation of discharge. In the high-temperature and gas-rich Valley of the Geysers Field, this led to the disintegration of the caprock and the infiltration of water, resulting in the subsequent eruptions of the Grotto and the Great Geyser being skipped, while the Kumroch CO2 reached the hydrothermal reservoir, boiled, and began cycling eruptions. These phenomena are consistent with the models of the MW = 8.8 earthquake’s focal mechanism and satellite geodetic data from GNSS and InSAR.
This study presents the results of a spatiotemporal analysis of crustal movements and deformations obtained by processing regional GNSS network data for a five-year period prior to the 2025 Kamchatka megaquake. The control network consisted of twenty-two continuously operating GNSS stations. Station spacing varied from 100 to 2500 km. An assessment was made of the sparse regional network’s response capabilities to the preparation of one of the strongest seismic events in history. Kinematic models were obtained for the evolution of internal displacement deficits, horizontal shear strains, and dilatation. The area of accumulated displacement deficit is regularly distributed along the Kuril–Kamchatka Trench, demonstrating resistance to the unidirectional northwestward translational motion of the Pacific tectonic plate. The evolution of total shear strain is consistent with the hypothesis of a possible triggering effect on the mature seismic source of the Kamchatka megathrust. The spatial distribution of accumulated dilatational strain reflects regional tectonic features previously identified by geophysical and geological studies. The results demonstrate the effectiveness of using sparse continuous GNSS observation networks to assess general regional geodynamic and tectonic trends in preparation of the 2025 Kamchatka megathrust.
We consider four strong earthquakes with MW > 7.0 that occurred in 2025 near the Kamchatka Peninsula: the foreshock on July 20, mainshock on July 29, and two aftershocks on September 13 and 18. Their source parameters are estimated from teleseismic surface wave records in instant point and finite-fault (elliptical dislocation with a finite duration) source approximations. In addition, rupture planes are identified based on seismological data. The obtained rupture lengths of the study seismic events are discussed in detail as they are characterized by good resolution. They are compared to USGS finite-fault models, distributions of aftershocks, and some existing scaling relations between subsurface rupture length and magnitude. The July 29, 2025 mainshock is also compared to the November 4, 1952 earthquake with MW = 8.8–9.0. Two scaling relations, providing the best fitting for earthquakes with MW ≥ 8.0, are selected based on the obtained results and USGS data.
The impact of tsunamigenic earthquakes upon the Earth’s outer shells provides additional information about the advance approach of tsunamis to infrastructure facilities. This paper examines the measured impact of atmospheric internal gravity waves generated by tsunami propagating after the Kamchatka earthquake on July 29, 2025, upon the ionosphere. The measurements were made at a considerable distance from the earthquake’s epicenter (in the Hawaiian Islands). Tidal tsunami monitoring stations recorded the tsunami’s arrival, while variations in the ionospheric total electron content were recorded via GPS. Observations have shown that the arrival of tsunami-driven atmospheric waves significantly precedes the arrival of sea waves at the observation point. Attention is drawn to the specific type of variations of the total electron content in the ionosphere and their spectral features, which clearly indicate the early arrival of atmospheric waves at the observation point. Observations have shown that the characteristics of the ionosphere’s response to gravity waves generated by sea waves can be used in a tsunami early warning system.
On July 29, 2025, a major earthquake with a moment magnitude of MW = 8.8 occurred off the coast of Kamchatka. The most accurate and rapid estimation of the magnitude of such events is a crucial task in modern seismology, particularly in the context of earthquake and tsunami early warning systems. In this study, we propose and test an approach for rapid MW estimation from accelerometer records based on an empirical relationship between peak ground displacement (PGD) and moment magnitude. Unlike most similar studies, we rely exclusively on accelerometric data from 13 seismic stations on Sakhalin and the Kuril Islands, without the use of GNSS observations. The final MW estimate derived from all stations was 8.75 ± 0.2, which is consistent with values reported by international agencies. Simulating real-time data processing demonstrated that a first stable magnitude estimate of MW = 7.6 ± 1.3 could be obtained as early as 4.5 minutes after the earthquake origin time, with a value of MW = 8.65 ± 0.3 available after 8 minutes. The results indicate that, given an existing accelerometer network, this methodology can provide reliable and sufficiently rapid estimates of the moment magnitude of major earthquakes without the need for GNSS data. This opens possibilities for enhancing the timeliness of source parameter estimation and for improving tsunami early warning systems in regions with developed seismic infrastructure, without requiring major modifications to existing seismic data processing systems.
We present a data-driven model for tectonic zonation of the West Siberian Basin (WSB) based on K-means clustering applied to a multivariate geophysical dataset. The initial analysis incorporates lithospheric thickness, crustal thickness, sedimentary thickness, topography, surface heat flow, and S-wave velocity anomaly at 100 km depth. F-statistics and permutation feature importance analysis indicate that only four primary parameters are sufficient to achieve reliable zonation, yielding six clusters that correspond to distinct tectonic domains. These domains reflect the complex geodynamic evolution of the region, including Paleozoic accretion, Mesozoic rifting, and subsequent subsidence. Independent data on hydrocarbon field locations demonstrate that major oil accumulations are primarily associated with two of these clusters, supporting the validity of the approach. The resulting zonation provides a reproducible basis for lithospheric regionalization and resource assessment. This framework can be further developed by integrating supervised machine learning methods to predict a specific structure and thermal regimes in areas with limited data. The quantitative characterization of these domains provides an objective framework for future geodynamic models and resource assessments.
This study aimed to assess the contamination of sediments in Wadi Djedra and its tributaries by seven trace elements. The average concentrations of Mn, Pb, Zn, Cu, Ni, Cd, and Cr in the sediments ranged from 31.4 to 59.2, 1.2 to 18.4, 15.1 to 54.7, 11.2 to 19.7, 1.1 to 14.7, 0.1 to 0.3, and 0.1 to 4.3 mg/kg, respectively. Sediment contamination was evaluated using the enrichment factor (EF), geoaccumulation index (Igeo), and potential ecological risk index (Eri). The Igeo values for Cd indicated moderate contamination at sites S2, S4, S5, and S7, while for other sites and elements, the values were negative, indicating no contamination. The results revealed very high enrichment of Cd and Cu in the analyzed sediments, attributed to human activities. In contrast, chromium and manganese concentrations were comparable to those observed in the Earth's crust. Suggesting even a depletion of metals in the sediments (EF < 2). The Eri index measurements showed that the sediments in the Djedra basin exhibited moderate to high pollution levels for Cd at most study sites. Lithogenic sources, urban discharges, and agricultural activities were the main factors affecting the concentrations of Cd, Cu, Zn, and Pb in the studied sediments. Although the current contamination is not alarming in the short term, it should be considered in future monitoring and management efforts.
Changes in the altitude profiles of the ionospheric electron density (Ne) and the total electron content (TEC) were detected using satellite navigation system data during the preparation and occurrence of a powerful M8.8 earthquake (July 29, 2025, UTC) and other strong earthquakes of M ≥ 6 that occurred near the Kamchatka Peninsula in June–September 2025. A 9–18% decrease in the ionospheric electron density was detected, occurred 1–5 days before the M8.8 earthquake. A gradual decrease in the total electron content (TEC) began 3 months before the earthquake, ceasing 15 days before the event. Using the Long Short-Term Memory and Autoencoder neural networks, anomalies were identified in the time series of normalized values of the total electron content (NTEC) of the ionosphere during the preparation of earthquakes of M ≥ 6 that occurred in June–September 2025 near the Kamchatka Peninsula. The pattern of the anomalous variations in ionospheric parameters identified in this research corresponds to the characteristics of ionospheric anomalies during the preparation and occurrence of strong seismic events presented in earlier works.
This study analyzes crustal movements and ionospheric response triggered by the powerful MW 8.8 earthquake of July 29, 2025, using continuous GNSS observations from open geodetic network stations located on the Kamchatka Peninsula, Sakhalin Island, the coast of the Sea of Okhotsk, and the Kuril Islands. Significant coseismic horizontal and vertical coordinate changes were detected at GNSS stations on the Kamchatka Peninsula near Petropavlovsk-Kamchatsky (up to 65 cm horizontally and 8 cm vertically), in Severo-Kurilsk city (168 cm horizontally and 19 cm vertically), and on Sakhalin Island (up to 3 cm horizontally). The time delay of surface deformation propagation was estimated for stations in Petropavlovsk-Kamchatsky and Severo-Kurilsk. The ionospheric response to the earthquake was investigated, revealing concentric ionospheric disturbances propagating southwestward from the earthquake epicenter. Two modes of this disturbance were identified: a fast mode with a propagation velocity of 800–1300 m/s detectable during the first ~20 minutes, and a slow mode with velocity of 180–330 m/s observed approximately 40 minutes after the main shock.
The results of the assessment of the current state of the Kizhi skerries of Lake Onego by the water chemical parameters compering to the background area of the open central part of Lake Onego were presented. The following parameters were considered: ionic composition, nutrients, organic matter, gas composition (CO2, O2), Fe, Mn, pollutants (heavy metals, oils, synthetic surface-active substance). It was found that the water of the Kizhi skerries area is weakly mineralized, mesotrophic with a low content of organic substances. A systematic excess of the maximum permissible concentration for oils (1.2–4.0 times), as well as for Fe (1.1–3.6 times) and Cu (1.1–5.8 times) was fixed. The first one was caused by intensive navigation in this part of the lake, while the second and third ones – by regional water characteristics of the humid zone, and not by anthropogenic influence. Currently, water in this part of the lake is of good quality. Using archival data, an assessment of water chemical composition changes of the Kizhi skerries for the last three decades has been conducted. The ionic composition was changed in the area of the Kizhi skerries and the central part of the lake, which was confirmed by the Pearson’s test. The concentration of all nitrogen forms and the values of Nmin/TP ratio were decreased, but at the same time, the color values and concentrations of oils and CO2 were increased. Apparently, intensive navigation due to the growing tourist flow has led to increasing of oil concentrations in the area of the Kizhi skerries. Other changes of chemical parameters were not caused by local anthropogenic influence and require further study. They may probably be associated with global processes, such as reducing industrial emissions of contaminants into the atmosphere or climate change.
