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.

Groundwater in Kazakhstan is becoming an increasingly vital resource for ensuring long-term water and food security in the face of climate change, growing population demands, seasonal variability, and limited surface water availability. This study evaluates groundwater quality and soil infiltration capacity in Eastern Kazakhstan to assess the potential for implementing Managed Aquifer Recharge (MAR) as a sustainable water management approach. Hydrochemical analysis revealed predominantly calcium–magnesium bicarbonate waters with low mineralization, suitable for both irrigation and domestic use, indicating generally good groundwater quality. Field tests conducted using the Boldyrev infiltration method demonstrated moderate to high soil permeability in alluvial and sandy-gravel deposits, confirming favorable recharge conditions. Among the areas studied, the Zharbulak, Katynsuy, and Kuraylin deposits were identified as the most promising sites for MAR pilot projects. Overall, the results highlight MAR as a practical, cost-effective, and climate-resilient tool for strengthening regional water security and supporting sustainable agricultural development in Kazakhstan.

Climate change has a significant impact on water resources worldwide, leading to more unpredictable weather conditions and revealing the shortcomings of traditional water management methods. Prolonged droughts, increased storm activity, reduced snow cover, and changes in runoff dynamics pose additional challenges to ensuring water security. Traditional hydraulic structures, including dams and reservoirs, play an important role but are less likely to effectively distribute water at the local level, especially in arid regions. Agricultural irrigation methods such as AgMAR not only enable efficient water use but also replenish groundwater reserves, reducing dependence on surface sources. This study explores the potential implementation of Agricultural Managed Aquifer Recharge (AgMAR) in Kazakhstan. For modeling soil layers, water flow dynamics, and MAR principles, 3D visualization created with the PyVista library is used. The research results indicate that AgMAR has significant potential for irrigation and water resource management in rural areas. Key benefits include groundwater level stabilization, aquifer recharge during seasonal precipitation, improved groundwater quality, and increased freshwater availability.

The study is dedicated to analyzing the economic efficiency of Managed Aquifer Recharge (MAR) systems as a method of sustainable water supply under the conditions of climate change and water resource scarcity. The work explores the fundamental principles of MAR, its advantages in reducing water supply costs, minimizing water losses, improving resilience to extreme climatic conditions, and maintaining ecosystem balances. Special attention is given to the economic and social benefits that the use of MAR can provide to agriculture and local communities. The research methodology includes an analysis of existing practices, economic modeling, and an assessment of the impact of implementing MAR technologies at the regional level. The results demonstrate that MAR is an effective and economically advantageous strategy for water supply, promoting sustainable use of water resources and improving quality of life. The scientific novelty lies in justifying the economic feasibility of applying MAR systems in the context of climate change, while the practical significance of the study lies in the potential to implement the findings into real-world water resource management practices.

The sustainable management of balneological resources is vital for the development of eco-friendly health tourism and regional economic stability. This study presents a comprehensive physicochemical and eco-toxicological characterization of the therapeutic peloids (mud) from Lake Maly Akkol, which is located in the Zhambyl region of Kazakhstan. Utilizing an integrated approach of laboratory analysis and Python-based statistical modeling, we evaluated the resource’s clinical potential and environmental safety. The results identify the deposit as a high-quality sulfide–silt peloid with a mean humidity of 66.91% (95% CI: [65.21, 68.60]) and a mineralization level of 11.21 g/dm³ (95% CI: [10.84, 11.57]). Statistical validation using one-sample t-tests confirmed that critical therapeutic indicators, including shear strength ($\mu$ = 2593.72 dyne/cm²) and total sulfide content ($\mu$ = 0.079%), are significantly aligned with international balneological standards (p < 0.05). Eco-toxicological screening for heavy metals revealed that Lead (37.03 mg/kg) and Cadmium (0.06 mg/kg) remain well below safety thresholds, ensuring the resource’s “clean” environmental profile. These findings establish a statistically robust “Digital Quality Passport” for the Lake Maly Akkol deposit, providing the scientific foundation necessary for its sustainable industrial utilization and long-term ecological preservation.