Heavy metal (HMe) pollution in regions with mining and metallurgy activities is known to be a serious environmental problem worldwide. Hydrological processes contribute to the dissemination of HMes (drainage, precipitation, flow rate). The aim of the present study is to investigate the microbial community structure in ten river sediments sampled in different regions of East Kazakhstan, which are contaminated with HMes. The overall degree of sediment contamination with HMes (Cr, Cu, Zn, Pb, and Cd) was assessed using the pollution index Zc, which ranged from 0.43 to 21.6, with the highest in Ridder City (Zc = 21.6) and Ust-Kamenogorsk City, 0.8 km below the dam of the hydroelectric power station (Zc = 19.6). The tested samples considerably differed in organic matter, total carbon, nitrogen, and phosphorus content, as well as in the abundance of HMe-related functional gene families and antibiotic resistance genes. Metagenomic analysis of benthic microorganisms showed the prevalence of Proteobacteria (88.84–97.61%) and Actinobacteria (1.21–5.98%) at the phylum level in all samples. At the class level, Actinobacteria (21.68–57.48%), Betaproteobacteria (19.38–41.17%), and Alphaproteobacteria (10.0–39.78%) were the most common among the classified reads. To the best of our knowledge, this is the first study on the metagenomic characteristics of benthic microbial communities exposed to chronic HMe pressure in different regions of East Kazakhstan.

This study investigates the trace-element geochemistry of rare-metal pegmatites from the Kalba–Narym Batholith, Eastern Kazakhstan, to establish geochemical indicators of zonation and subtype differentiation within pegmatite fields. Detailed ICP-MS analyses of muscovite and K-feldspar reveal systematic variations in Li, Cs, Rb, Ta, Nb, P, and Ga contents that reflect progressive melt fractionation during the evolution of granitic magmas. These data allow the identification of four main pegmatite subtypes, including barren, beryl, albite–spodumene, and albite, representing successive stages of LCT (Li-Cs-Ta) pegmatite evolution. Both vertical and lateral geochemical zonation are recognized across the Kalba–Narym Batholith, controlled by magmatic differentiation and volatile enrichment. The results highlight the diagnostic value of trace-element systematics in rock-forming minerals as reliable indicators of fractionation and ore potential, and they provide quantitative criteria for the classification and exploration of rare-metal pegmatites within the Kalba–Narym Batholith.

Rare-metal pegmatite–greisen systems are commonly small, structurally controlled, and difficult to delineate using conventional mapping alone. This study proposes a multiscale remote-sensing workflow for prospecting Li–Nb–Ta–Cs mineralisation in the Kalba–Narym rare-metal belt (East Kazakhstan) by integrating Sentinel-2 multispectral imagery, UAV-derived centimeter-scale orthomosaics, structural (lineament) analysis, and field-based mineralogical–geochemical validation. Sentinel-2 responses were first calibrated using known occurrences to derive alteration proxies related to greisenisation, silicification, Na-metasomatism, and oxidation. These proxies were combined into an Integrated Hydrothermal Alteration Index (IHAI) to highlight areas where multiple alteration processes overlap. Lineament mapping from Sentinel-2 and DEM products indicates dominant NW–SE and NE–SW structural trends, zones of elevated lineament density and intersection systematically coincide with high IHAI values. UAV orthomosaics refine satellite-scale anomalies by resolving quartz-vein networks, fracture corridors, and surface-alteration textures that are not detectable at 10–20 m resolution. Mineralogical and geochemical data confirm that high-IHAI targets correspond to albitised pegmatites and greisenised rocks enriched in Li, Nb, Ta, and Cs. The results demonstrate that combining freely available Sentinel-2 data with UAV observations and targeted ground validation provides a cost-effective and transferable framework for reducing false positives and prioritising exploration targets in structurally complex granitoid terranes.

The article explores the potential of remote sensing (RS) applications for identifying patterns of rare metal mineralization in the studied area of Eastern Kazakhstan. An analysis of the technical parameters related to RS data is conducted to highlight the structural and lithological features, which allows for a deeper understanding of the geological environment and the region's potential resources. The research is based on multispectral satellite data obtained within potentially promising magmatogenic ore systems. The authors emphasize the identification of areas with a high probability of discovering rare metal mineralization, which can play a crucial role in the exploration and development of deposits. A key element of the study is the analysis of spectral characteristics of rare metal pegmatites and their constituent minerals, enabling the establishment of their unique signatures in the spectral data. The article also discusses the methods for processing and interpreting multispectral images, which are essential for accurately identifying minerals and assessing their distribution. Modern machine learning techniques are applied in the research, significantly increasing the efficiency of data analysis and allowing for the automation of mineral identification and classification processes. As a result, meaningful conclusions are drawn about the region's potential for rare metal extraction, opening new prospects for further research and practical applications in geological exploration.

This paper studies the influence of meteorological factors on avalanche occurrence in East Kazakhstan using modern data analysis methods. A dataset of 111 avalanche events in nine avalanche-prone areas of the region, recorded between 2012 and 2023, was compiled. Primary data on avalanche dates were obtained from the Department of Emergency Situations of East Kazakhstan Region (DES EKR), and meteorological data were sourced from the Kazhydromet website. Descriptive statistics, correlation analysis, principal component analysis (PCA), as well as K-means clustering and DBSCAN algorithms, were used for the analysis. During the analysis of meteorological conditions preceding avalanches at nine avalanche-prone areas in Eastern Kazakhstan, using PCA (Principal Component Analysis), the main weather factors affecting avalanche formation were determined. Clustering of 111 avalanches using the K-Means method allowed the identification of four scenario types: gradual snow accumulation without wind (33 cases), upper layer thawing due to warming (34), high snow cover (28), and storm impact (16). The DBSCAN method revealed two anomalous cases related to extreme snow depth. Correlation analysis revealed significant relationships between avalanches and meteorological parameters such as air temperature, snow cover depth, wind speed and direction, precipitation, and relative humidity. Correlation analysis revealed both negative and positive relationships between meteorological parameters. Principal component analysis identified the most significant variables affecting avalanche activity, with temperature, snow cover height, and wind making the greatest contributions. Cluster analysis demonstrated that avalanches could occur under different combinations of weather conditions within the same areas, confirming the complex nature of avalanche-forming processes. The results emphasize the need for an integrated approach to avalanche forecasting that accounts for the multi-parametric interactions of meteorological factors, and may contribute to the improvement of avalanche risk monitoring and mitigation systems in mountain regions.

Мақала гетерогенді геологиялық графикалық материалдарды өңдеу және соның негізінде географиялық ақпараттық жүйeлерінің (ГАЖ) мәліметтер базасын құрудың техникалық және технологиялық шешімдері қарастырылады. Нысан ретінде Шығыс Қазақстанда орналасқан, Қалба-Нарым металлогенді зонасы және оның құрылымдық бөлігі – Асубулақ кен өрісі алынған. ГАЖ мәліметтер базасын құру барысында құрамы және масштабы бойынша түрлі геологиялық деректер қолданылды, атап айтқанда: геологиялық, геофизикалық (гравиметриялық және магниттік аномалия карталары), геохимиялық және пайдалы қазбалар карталары. Дәлдігі мен ақпарат толықтығын жақсарту үшін векторизацияланған сандық карталар қашықтықтан зондтау мәліметтерімен толықтырылған. Біріккен ГАЖ жүйесі арқылы геологиялық сипаттамаларға кешенді кеңістіктік талдау жүргізуге мүмкіндік алынды This article discusses technical and technological solutions for processing heterogeneous Geological graphic materials and creating databases of geographic information systems (GIS) based on them. As a sample, the Kalba-Narym Metallogenic zone and its structural part – the Asubulak ore field, located on the territory of Eastern Kazakhstan, were taken. In the process of creating the GIS database, various geological data were used in terms of composition and scale, in particular: geological, geophysical (gravimetric and magnetic anomaly maps), geochemical and mineral maps. Vectorized digital maps are supplemented with remote sensing data to improve accuracy and informativeness. Through the combined GIS system, we have the opportunity to conduct a comprehensive spatial analysis of geological characteristics В статье рассматриваются технические и технологические решения по обработке неоднородных геологических графических материалов и созданию на их основе базы данных географических информационных систем (ГИС). В качестве объекта взята Калба-Нарымская металлогеническая зона и ее структурная часть – Асубулакское рудное поле, расположенное на территории Восточного Казахстана. При создании базы данных ГИС использовались различные геологические данные по составу и масштабу, а именно: геологические, геофизические (гравиметрические и магнитные карты аномалий), геохимические и карты полезных ископаемых. Векторизованные цифровые карты дополнены данными дистанционного зондирования для улучшения точности и информативности. Благодаря объединенной системе ГИС получена возможность проводить комплексный пространственный анализ геологических характеристик