This article examines the development of a methodology for monitoring geodynamic processes during the construction of the Almaty metro using an integrated approach that incorporates geodetic methods, laser scanning, and aerospace technologies. The study aims to enhance the safety of underground structures in the context of complex engineering-geological conditions and high-density urban environments. Monitoring was conducted at the "Saryarka" and "Bauyrzhan Momyshuly" stations, employing underground polygonometry, aerial surveys with unmanned aerial vehicles (DJI Mavic 3 multispectral), laser scanning (Faro Focus 3D X), and finite element numerical modeling (PHASE 2, AutoCAD Civil 3D). The geodetic work covered a 3201-meter section with the installation of 34 benchmarks, ensuring a relative measurement error of no more than 1:30,000. Laser scanning achieved an average point cloud density of 7 mm, enabling the creation of precise 3D tunnel models, identification of deviations from the design axis, and determination of critical stress zones. The study revealed that at a depth of 32.28 m, the maximum vertical stress reached 11.2 MPa, and horizontal stress was 2.7 MPa. At a depth of 19.58 m, the vertical stress reached 10.5 MPa, while the horizontal stress was 2.47 MPa. The maximum concentration of stresses in critical zones reached 20 MPa. The use of UAVs and aerospace technologies facilitated the creation of a highly accurate digital terrain model and the identification of potential deformation zones. The findings confirm the necessity of regular monitoring in dense urban and seismically active areas and demonstrate the potential of integrating modern technologies to improve the precision and efficiency of geodynamic assessments. The proposed methodology can be applied not only to metro construction but also to other underground structures, including mining industry facilities, both in Kazakhstan and internationally.

Floods are among the most frequent and destructive natural hazards in Kazakhstan, particularly in the Abai Region, Kazakhstan, where topographic, hydrological, and climatic factors strongly influence flood occurrence. This study presents a comprehensive spatial assessment of flood susceptibility in the Abai Region using a multi-criteria Geographic Information System (GIS) approach. The analysis integrates twelve flood-conditioning factors representing hydrological, topographic, environmental, and anthropogenic variables. The relative importance of these factors was determined using the Analytical Hierarchy Process (AHP). The results indicate that distance to rivers (20%) and precipitation (16%) are the most influential drivers of flood susceptibility, followed by Height Above Nearest Drainage (HAND) (11%) and drainage density (9%). The resulting flood susceptibility map classifies the study area into five susceptibility levels. Approximately 56.6% of the study area falls within the moderate susceptibility class, while 25.0% is categorized as high susceptibility, mainly concentrated in low-lying floodplains and foothill regions. Low-susceptibility areas account for 18.1% of the region, whereas the very high and very low susceptibility classes together represent less than 1% of the territory. Model performance was evaluated using Receiver Operating Characteristic (ROC) analysis, yielding an Area Under the Curve (ROC–AUC) value of 0.893, indicating strong agreement between predicted susceptibility patterns and observed flood occurrences. Additional validation metrics derived from the confusion matrix show an overall accuracy of 83.3%, precision of 0.75, recall of 1.0, and a Kappa coefficient of 0.67, confirming reliable predictive performance. Sensitivity analysis with ±10% variation in factor weights further demonstrated the spatial stability of the susceptibility results. The resulting susceptibility map provides an important spatial basis for infrastructure planning, flood mitigation, and disaster preparedness in the Abai Region and offers a transferable framework for flood-susceptibility assessment in other semi-arid regions of Central Asia.

Mountain regions are highly climate-sensitive, yet long-term observational evidence of elevation and seasonal climate dynamics in Central Asia remains limited. This study examines spatiotemporal trends in temperature (Tmean, Tmax, Tmin, and diurnal temperature range [DTR]) and precipitation across Kazakhstan’s transmountain regions using 74 meteorological stations (1981–2023). Data were analyzed using the Mann–Kendall test and Sen’s slope estimator, stratified across six elevation zones from lowlands (1500 m). Results reveal a robust, spatially coherent warming signal across all zones. Annual Tmean increased at a median rate of ~0.30 °C decade⁻¹, peaking at 0.36 °C decade⁻¹ above 1500 m, corresponding to an absolute increase exceeding 1.5 °C. Warming exhibited strong seasonal and diurnal asymmetries. Spring warmed most rapidly, with Tmean increasing >0.60 °C decade⁻¹ (approaching 3 °C total). Winter warming was driven by Tmin increases (up to 0.44 °C decade⁻¹), causing widespread DTR contraction, whereas summer warming was driven by Tmax increases, expanding DTR at higher elevations. Tmin showed the strongest elevation amplification overall. In stark contrast, precipitation trends were weak, spatially heterogeneous, and largely non-significant. Annual changes ranged from −6.63 to +14.35 mm decade⁻¹, with seasonal tendencies indicating modest, non-significant winter/spring wetting and summer drying. Ultimately, the results demonstrate a profound decoupling between strong, elevation-dependent warming and weak precipitation changes. The acute amplification of temperature, particularly during spring and summer at high elevations, has severe implications for snowmelt timing, glacier mass balance, evapotranspiration demand, and long-term water security in Kazakhstan.

Для рационального использования богарных земель юго-востока Казахстана изучены влияние разных способов обработки почвы на ее водно-физические свойства почвы. Запас продуктивной влаги в почве в среднем за три года весной при вспашке на 20-22 см составила по всем изучаемым культурам 115,9-139,1 мм, при минимальной обработке на 8-10 см – 126,2-158,1 мм, при нулевой обработке –118,2-161,5 мм. Из-за незначительного количества осадков в начале июля к уборке урожая наблюдалось уменьшение запасов продуктивной влаги по всем обработкам почвы и изучаемым культурам за счет испарения и транспирации растениями и составили при вспашке на 20-22 см 12,3-22,5 мм, при минимальной обработке на 8-10 см 11,6-28,3 мм, при нулевой обработке 9,6-27,9 мм. Плотность почвы под изучаемые культуры в пахотном слое почвы 0-30 см показала значительное ее варьирование по способам обработки почвы, весной она находилась в рыхловатом и слабо уплотненном состоянии 1,17-1,21 г/см3, а уборке увеличивалась и становилась плотной 1,28-1,32 г/см3, особенно при нулевой обработке почвы. Наивысшая урожайность в среднем за три года исследований при минимальной обработке почвы на посевах ячменя 25,3 ц/га, а наименьшая урожайность зерна отмечена при вспашке на посевах суданской травы 6,6 ц/га, а на минимальной и нулевой обработках почвы 7,3 и 9,0 ц/га соответственно. В результате трехлетних изучении, показали, что высокую урожайность зерна составили при минимальной обработке почвы по яровому ячменю, гороху и сафлору, а по суданской траве по нулевой обработке почв.

In Kazakhstan’s Akmola Region, rural households face heightened vulnerability from climate change, driven by reliance on weather-dependent resources and amplified risks of extreme precipitation events, prolonged dry spells, and progressive soil degradation—further intensified by limited adaptive capacity and inequities affecting women-led or ethnic minority families. This study conducted stratified household surveys across four agricultural districts, developed a tailored Livelihood Vulnerability Index (LVI) incorporating shelterbelt presence, condition, and perceived effects, alongside readiness for hydrological surface recovery (contour–strip organisation, swales/valokany, and tree–shrub planting). Results revealed an average LVI of 0.45–0.55, which was higher (+10–15%) in marginalized groups; testing pathways showed correlations (r = 0.65, p < 0.05) with water security, soil condition, income stability, and hazard reduction, with potential LVI reductions of 15–25% through integrated measures. District-specific recommendations include implementing the Potapenko–Lukin method on slopes <5% with valokany (width 80 cm, depth 1.5 m, spacing 100–500 m), endemic plantings, and biomaterial, supported by subsidies (488,028 tenge/ha/year) and GIS monitoring, to enhance resilience and equity in steppe and forest–steppe farming.