• Energy Research

AbstractWe employ a high‐resolution Köppen climate classification dataset to examine shifts in Tundra zones within the Alps and Asia. Our analysis shows substantial reductions in Tundra areas by the mid‐21st century under different Shared. Socioeconomic pathways (SSP1‐2.6, SSP3‐7.0, SSP5‐8.5). Tundra zones in the Alps and the Tibetan Plateau are crucial for their unique climates and role as water reservoirs. Characterized by short, mild summers and long, severe winters, these zones are vital for the glaciers and perennial snow. The projected climate instability may significantly reduce alpine snow cover by mid‐century with irreversible consequences. A 2°C temperature increase from the 1981–2010 baseline could eliminate the Tundra climate in the Alps and reduce it by over 70% in Asia. This is particularly concerning given that rivers from the Tibetan Plateau sustain nearly 40% of the global population.

Study region: To provide a picture of hydrological impact of climate change across different climatic zones in Europe, this study considers eight river basins: Tagus in Iberian Peninsula; Emån and Lule in Scandinavia; Rhine, Danube and Teteriv in Central and Eastern Europe; Tay on the island of Great Britain and Northern Dvina in North-Eastern Europe. Study focus: In this study the assessment of the impacts of moderate and high-end climate change scenarios on the hydrological patterns in European basins was conducted. To assess the projected changes, the process-based eco-hydrological model SWIM (Soil and Water Integrated Model) was set up, calibrated and validated for the basins. The SWIM was driven by the bias-corrected climate projections obtained from the coupled simulations of the Global Circulation Models and Regional Climate Models. New hydrological insights for the region: The results show robust decreasing trends in water availability in the most southern river basin (Tagus), an overall increase in discharge in the most northern river basin (Lule), increase in the winter discharge and shift in seasonality in Northern and Central European catchments. The impacts of the high-end climate change scenario RCP 8.5 continue to develop until the end of the century, while those of the moderate climate change scenario RCP 4.5 level-off after the mid-century. The results of this study also confirm trends, found previously with mostly global scale models. Keywords: European rivers, Climate change, Hydrology, Eco-hydrological modelling, Climate change impact, High-end scenarios

Study region: Eight river catchments within Central Asia. Study focus: The limited amount of water resources is already an issue in the Central Asian region, and climate change may be crucial for water availability and development of countries in the region. This study investigates potential climate change impacts on water resources in Central Asia to the end of the century by focusing on eight river catchments with diverse natural conditions located in different countries. The eco-hydrological model SWIM was setup, calibrated and validated for all selected catchments under study. Scenarios from five bias-corrected GCMs under Representative Concentration Pathways 4.5 and 8.5 were used to drive the hydrological model. New hydrological insights for the region: The results show an increase of mean annual temperature in all catchments for both RCPs to the end of the century. The projected changes in annual precipitation indicate a clear trend to increase in the Zhabay and to decrease in the Murghab catchments, and for other catchments, they were smaller.The projected trends for river discharge are similar to those of precipitation, with an increase in the north and decrease in the south of the study region. Seasonal changes are characterized by a shift in the peak of river discharge up to one month, shortage of snow accumulation period, and reduction of discharge in summer months.

AbstractCentral Asia (CA) is among the world's most vulnerable regions to climate change. Increasing anthropogenic greenhouse gas concentrations (GHGs) are the primary forcing of the current and future climate system for the time scale of a century. By analysing observation datasets, we show that a warming of 1.2°C led to a decrease of 20% in snow‐depth CA during the last 70 years, especially over the mountains. In recent decades, longer summer times and fewer icing days (more than 20 days·year−1) have exposed unprecedented shock to CA's climate system's components. Furthermore, we analyse 442 model simulations from Coupled Model Inter‐comparison Project Phase 5 and 6 (CMIP5, CMIP6) and show that CMIP6 simulations are generally warmer and wetter than the CMIP5 ones in CA. For instance, under the highest emission scenarios (RCP8.5 and SSP5‐8.5), CMIP6 projects a 6.1°C increase, while CMIP5 projects a 5.3°C increase, suggesting CMIP6 anticipates greater warming with high emissions. In contrast to CMIP6, the CMIP5 precipitation trends suggest a potential nonlinear relationship between increased greenhouse gas emissions and changes in precipitation, though the impact is much less pronounced than the temperature changes. Our analysis shows that CMIP6 models are more sensitive to temperature rise than CMIP5 ones. Both simulation sets' ensemble means capture well the observed warming trend. The imposed snow‐melting leads to an increase in the run‐off in the vicinity of glaciers. Such climatic shifts lead to more flooding events in CA. Given the projected warming range of 2–6°C in CA at the end of the century in various scenarios and models, such warming trends might be catastrophic in this region. The seasonal cycle of the temperature change indicates an extension of the glacier's melting period under future scenarios with fossil‐fueled development. The models' uncertainty increases for the far‐future time‐slice, and warming larger than 4°C in CA is very likely among all the models and during all the seasons if no sustainable action is taken. This study also incorporates a detailed Köppen climate classification analysis, revealing significant shifts towards warmer climate categories in Central Asia, which may have profound implications for regional hydrological cycles and water resource management, particularly in the Amu Darya and Syr Darya river basins under warmer scenario by the end of the century. The Tundra and ice cap climate categories will lose more than 60% of their coverage at the end of the century compared to the historical period in the Amu Darya and Syr Darya river basins.

Study region: Eight main river basins covering the major part of Ukraine. Study focus: The main aim of this study was to provide an assessment of climate change impacts on water availability across Ukraine using global hydrological models. Six global hydrological models were evaluated for their performance in the historical period in the basins under study. Future river discharge was simulated by using the best performing model and all available models driven by bias-corrected GCM projections from the ISIMIP project under the RCP 2.6 and RCP 8.5 scenarios. New hydrological insights for the region: The results show precipitation increase up to 10 % under RCP 2.6, and variable changes from -14 % to +10 % under RCP 8.5 by the end of the century. The projections show the decreasing mean annual river discharge in the majority of basins for the middle (2040–2070) and far future (2071–2100) periods under both RCPs, and the decrease is stronger under RCP 8.5. The seasonal changes are characterised by a decrease in summer and a small to moderate increase in winter months in most of the basins. The highest reduction of mean annual discharge was projected for the Pripyat, Southern Bug and Dniester basins, reaching up to -30 % to the end of the century under RCP 8.5.

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.

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