Flood modelling in snow-fed river basins is critical for understanding the impacts of climate change on hydrological extremes. The Zhabay River in northern Kazakhstan exemplifies a basin highly vulnerable to seasonal floods, which pose significant risks to infrastructure, livelihoods, and water resource management. Traditional flood forecasting in Central Asia still relies on statistical models developed during the Soviet era, which are limited in their ability to incorporate non-stationary climate and anthropogenic influences. This study addresses this gap by applying the Soil and Water Integrated Model (SWIM) to project climate-driven changes in the hydrological regime of the Zhabay River. The study employs a process-based, high-resolution hydrological model to simulate flood dynamics under future climate conditions. Historical hydrometeorological data were used to calibrate and validate the model at the Atbasar gauge station. Future flood scenarios were simulated using bias-corrected outputs from an ensemble of General Circulation Models (GCMs) under Representative Concentration Pathways (RCPs) 4.5 and 8.5 for the periods 2011–2040, 2041–2070, and 2071–2099. This approach enables the assessment of seasonal and interannual variability in flood magnitudes, peak discharges, and their potential recurrence intervals. Findings indicate a substantial increase in peak spring floods, with projected discharge nearly doubling by mid-century under both climate scenarios. The study reveals a 1.8-fold increase in peak discharge between 2010 and 2040, and a twofold increase from 2041 to 2070. Under the RCP 4.5 scenario, extreme flood events exceeding a 100-year return period (2000 m³/s) are expected to become more frequent, whereas the RCP 8.5 scenario suggests a stabilization of extreme event occurrences beyond 2071. These findings underscore the growing flood risk in the region and highlight the necessity for adaptive water resource management strategies. This research contributes to the advancement of climate-resilient flood forecasting in Central Asian river basins. The integration of process-based hydrological modelling with climate projections provides a more robust framework for flood risk assessment and early warning system development. The outcomes of this study offer crucial insights for policymakers, hydrologists, and disaster management agencies in mitigating the adverse effects of climate-induced hydrological extremes in Kazakhstan.

The research was carried out as part of the preparation “Water Resources” section of the 4th National Communication of the Kyrgyz Republic to the UNFCCC. The article presents extensive information on the current state and changes over a long period of observations of water resources, climate and glaciation in Kyrgyzstan (Syr-Darya and Amu-Darya river basins). The representative rivers were selected as the main objects, which are transboundary between Kyrgyzstan, Uzbekistan, Kazakhstan and Tajikistan. The study aims to assess the inter-annual and intra-annual dynamics of the flow of the rivers for the period from 2020 to 2080, based on the climate projections CMIP5 (RCP4.5 and RCP8.5) and CMIP6 (SSP2-4.5 and SSP5-8.5) (IPCC WG II Report, 2022). The hydrological modeling method in the HBV light and HBV EHT models and the inertial mean annual flow change method were used to estimate changes in water resources. On the rivers of the northern part of the Fergana Valley, the average annual runoff is expected to increase by 1-19%, in the Amudarya river basin (Kyzyl-Suu river) – by 27-64% of the values for 2006-2019. In the Naryn river, water discharge for this period will remain within the current values for 2006-2019. The method of inertial change in the average annual runoff showed an increase in runoff for 2030 and 2040 for all the studied catchment areas by 6-19% of the current values for 2006-2020. The results of the study are intended for decision-makers on the rational use and long-term planning of water resources under climate change.

Global and regional climate change and their water-related impacts are a key component in future development scenarios to guide sustainable water management. Climatic changes may lead to an undesirable redistribution of water supplies and potentially harmful extremities in river flows throughout the year. If we add to this the uneven spatial distribution of water resources in Kazakhstan, the importance of assessment of the intra-annual distribution of river flows under historical and present climatic conditions becomes evident. The presented scientific study analyzes decadal regional trends from 1985 to 2022 in the intra-annual distribution of river runoff in selected catchments in Kazakhstan, including Buktyrma River, Zhabay River, and Ulken-Kobda River. The river basins were selected to cover diverse regions in terms of geographical features and hydrological conditions, significantly affected by climate change. We applied statistical analysis methods using multiyear values of mean monthly and mean annual river flows, mean monthly air temperatures, and mean monthly precipitation. To analyze the intra-annual distribution of annual river flow in the context of climate change, a computational method was used, in which the actual current river flow (modern river flow taking into account non-stationarity of climatic changes) was compared with the conditionally natural flow obtained by modeling and corresponding to the natural regime of the river. The long-term dynamics of flow-forming factors and runoff parameters with regard to phases of different water content (25%, 50%, and 75%) were considered. Statistical analysis of seasonal changes in water content of modeled and actual river flow, taking into account climatic non-stationarity, allowed us to identify significant trends of flow redistribution within the year: indicating a decrease in the volume of spring floods, an increase in winter flow and increase in seasonal variability, especially for the Ulken Kobda River. It appears that atmospheric circulation significantly affects annual and seasonal variations of water availability. The shift in western circulation type (W) contributes to increased average annual river flow, while the shift in eastern circulation type (E) is associated with amplification of extreme flood-type events. The results obtained are important for adapting sustainable water management practices under a changing climate, helping to anticipate the availability of water resources and allowing pro-active measures to mitigate hydrological extremes.

The article presents an analysis of current (during the period 1985–2022) and projected (during the period 2025–2099) changes in the hydrological regime of the Buktyrma, Yesil, and Zhaiyk river basins in Kazakhstan under the conditions of global climate change. This study is based on the integration of data from General Circulation Models (GCMs) of the sixth phase of the CMIP6 project, socio-economic development scenarios SSP2-4.5 and SSP5-8.5, as well as the results of hydrological modelling using the SWIM model. The studies were carried out with an integrated approach to hydrological change assessment, taking into account scenario modelling, uncertainty analysis and the use of bias correction methods for climate data. A calculation method was used to analyse the intra-annual distribution of runoff, taking into account climate change. Detailed forecasts of changes in runoff and intra-annual water distribution up to the end of the 21st century for key water bodies in Kazakhstan were obtained. While the projections of river flow and hydrological parameters under CMIP6 scenarios are actively pursued worldwide, few studies have explicitly focused on forecasting intra-annual flow distribution in Central Asia, calculated using a methodology appropriate for this region and using CMIP6 ensemble scenarios. There have been studies on changes in the intra-annual distribution of runoff for individual river basins or local areas, but for the historical period, there have also been studies on modelling runoff forecasts using CMIP6 climate models, but have been very few systematic publications on the distribution of predicted intra-annual runoff in Central Asia, and this issue has not been fully studied. The projections suggest an intensification of flow seasonality (1), earlier flood peaks (2), reduced summer discharges (3) and an increased likelihood of extreme hydrological events under future climatic conditions. Changes in the seasonal structure of river flow in Central Asia are caused by both climatic factors—temperature, precipitation and glacier degradation—and significant anthropogenic influences, including irrigation and water management structures. These changes directly affect the risks of flooding and water shortages, as well as the adaptive capacity of water management systems. Given the high level of water management challenges and interregional conflicts over water use, the intra-annual distribution of runoff is important for long-term planning, the development of adaptation measures, and the formulation of public policy on sustainable water management in the face of growing climate challenges. This is critically important for water, agricultural, energy, and environmental planning in a region that already faces annual water management challenges and conflicts due to the uneven seasonal distribution of resources.

The surface water resources of the West Kazakhstan Region (WKR) face escalating vulnerability due to the synergistic effects of a sharply continental climate, which intensifies climate change impacts, and rapidly increasing anthropogenic water demand. This study aims to quantify and project the future water stress on WKR’s surface waters, assessing the combined influence of climate change and socio-economic development over the critical period of 2030–2050. This study presents a comprehensive quantitative assessment and future projection of water stress on the region’s surface waters, integrating state-of-the-art CMIP6 climate scenarios (SSP2-4.5 and SSP5-8.5) with a novel model of water consumption growth accounting for regional demographic and economic developments. Employing advanced bias-corrected ensemble climate projections alongside physically interpretable water balance models, we estimate changes in river flows and lake volumes through mid-century. A newly developed Water Stress Index (WSI), supplemented by the Falkenmark Index, reveals an alarming increase in water stress, with projections indicating that over 70% of the WKR territory may face severe resource limitations by 2050. The analysis underscores significant spatial heterogeneity driven by climatic variability and socio-economic factors, emphasizing the urgent need for regionally tailored adaptation and water management strategies. These findings provide a robust scientific basis to guide policy decisions aimed at mitigating future water scarcity under evolving climate and development scenarios.