The use of hydraulic models for carrying out flood simulations is a common practice globally. The current study used HEC-RAS (2D) in order to simulate different flood scenarios on the River Yesil (Ishim). Comparison of different mesh sizes (25, 50 and 75 m) indicated no significant difference in model performance. However, a significant difference was observed in simulation time. In addition, the inclusion of breaklines showed that there was a slight improvement in model performance and a shortening of the simulation time. Sensitivity analysis and the consequent manual calibration of sensitive parameters resulted in a slight improvement (an increase in the model accuracy from 58.4% for uncalibrated to 59.7% for calibrated). Following the simulations inundation maps for 10-, 20- and 100-year flood events were obtained. Hazard classification of the flood extents generated indicated that the settlements of Zhibek Zholy and Arnasay were flooded in all the simulated events. Volgodonovka village experienced flooding when a 100-year flood event was simulated. On the other hand, settlement No. 42 did not experience any flooding in any of the scenarios. The model results also demonstrate that the Counter-Regulator was not overtopped in the event of the 100-year hydrograph.

Water resources in Central Asia are scarce, so complicated issues arise from this. Kazakhstan is a Central Asian landlocked country, which has mostly closed drainage basins, characterized by endorheic lakes that do not drain to the oceans. These endorheic lakes are very sensitive to climate change and anthropogenic influences. Very few studies have been conducted on the hydrological cycle of the small endorheic lakes. This work reviews the endorheic lakes within Burabay National Nature Park (BNNP), Northern Kazakhstan. BNNP is a small ecozone consisting of terminal lakes watersheds covered by mixed forests and grasslands. These endorheic lakes have been drying out during the last one hundred years or so with the water level decrease accelerated in the past few decades. According to historical observations (1935–2014), on the one hand precipitation amounts did not significantly change, while on the other hand, air temperature steadily increased. The lake level decrease is most probably caused by a water budget deficit, with evaporation exceeding the precipitation inputs in the long term. The direct anthropogenic impact (water abstraction) plays a minor role in the deterioration of water levels, with most significant impacts through localized land‐use changes such as road and building construction in the catchments. The future of the park's sensitive ecosystems in a changing climate is uncertain; therefore, BNNP requires modern ecohydrological monitoring methods and analysis tools to improve our understanding of its hydrological cycle variability, and to enable us to develop adequate adaptation and mitigation measures. WIREs Water 2017, 4:e1227. doi: 10.1002/wat2.1227This article is categorized under: Engineering Water > Planning Water Water and Life > Stresses and Pressures on Ecosystems Science of Water > Water and Environmental Change

Flooding events have been negatively affecting the Republic of Kazakhstan, with higher occurrence in flat parts of the country during spring snowmelt in snow-fed rivers. The current project aims to assess the flood hazard reduction capacity of Alva irrigation system, which is located in the interfluve area of Yesil and Nura Rivers. The assessment is performed by simulating spring floods using HEC-RAS 2D and controlling the gates of the existing system. A digital elevation model of the study domain was generated by integration of Sentinel-1 radar images with the data obtained from bathymetrical survey and aerial photography. Comparison of the simulated inundation area with a remote sensing image of spring flood in April 2019 indicated that the main reason for differences was due to local snowmelt in the study domain. Exclusion of areas flooded by local snowmelt, which were identified using the updated DEM, from comparison increased the model similarity to 70%. Further simulations of different exceedance probability hydrographs enabled classification of the study area according to maximum flood depth and flood duration. Theoretical changes on the dam crest as well as additional gates were proposed to improve the system capacity by flooding agriculturally important areas, which were not flooded during the simulation of the current system. The developed model could be used by local authorities for further development of flood mitigation measures and assessment of different development plans of the irrigation system.

Yesil River is one of the longest transboundary rivers in Kazakhstan and is representative of northern Kazakh hydrology. Shared between Kazakhstan and Russia, it is the main water source in the region with high strategic importance. Regions with characteristics like Yesil River basin are underrepresented in the scientific literature. Review of climatic, hydrological and other basin characteristics is provided using global remote sensing and reanalysis datasets, historical recorded data and review of international and local research papers. Overall, the basin is characterised by very low runoff ratio (0.04–0.07) and moderate aridity index. Evapotranspiration dominates the water balance and warm season precipitation is fully consumed by this flux. Spring snowmelt generates most of the streamflow during a short period, storage of which controls water availability until the next spring. In addition, snowmelt causes devastating floods and controls groundwater recharge. Currently, water use in the basin accounts for 18% of annual runoff, although it is increasing. Future projections indicate significant warming and uncertain precipitation patterns, which might significantly increase runoff in spring and increase region’s aridity due to increased atmospheric water demand. Future transition to more arid climate zone poses a risk to local rain-dependent agriculture (covering half of the basin). As a result, irrigated agriculture in addition to continuing industrial and urban development might substantially increase future water use. Considering the current state and providing hydrological insights for the region, the key knowledge gaps for this basin and region are presented.

Numerical simulations of rainfall-runoff processes are useful tools for understanding hydrological processes and performing impact assessment studies. The advancements in computer technology and data availability have assisted their rapid development and wide use. This project aims to evaluate the applicability of a physically based, fully distributed rainfall-runoff model TOPKAPI-X for the simulation of flood events in two small watersheds of Saxony, Germany. The results indicate that the model was calibrated well for 4.88 km² Wernersbach catchment (NSE 0.89), whereas 276 km² Wesenitz catchment calibration was only satisfactory (NSE 0.7). The addition of the second soil layer improved the model’s performance in comparison to the simulations with only one soil layer for Wernersbach (NSE increase from 0.83 to 0.89). During the validation process, the model showed a variable performance. The best performance was achieved for Wernersbach for the year with the highest runoff (NSE 0.95) in the last decade. The lowest performance for the Wernersbach and Wesenitz catchments was 0.64 for both. The reasons for the model’s low performance in some years are discussed, and include: (i) input data quality and data insufficiency, (ii) methods used within the simulations (interpolation, ETP estimation, etc.), and (iii) assumptions made during the calibration (manual calibration, parameter selection, etc.).

This work presents the dataset of stable water isotopes of oxygen and hydrogen measured in water samples from different sources (precipitation, surface water, groundwater, tap water) across Kazakhstan from 2017 to 2018 and from 2020 to 2023. The dataset includes results on isotopic composition of 399 water samples, namely precipitation: event-based (n = 108), cumulative monthly (n = 22); surface water: lakes, reservoirs, brooks, rivers, channels (n = 175), groundwater: shallow and artesian groundwater, spring (n = 85), tapwater (n = 9). For each sample name of the source, location, latitude, longitude and date of sampling, measurement uncertainty (one standard deviation) are available. The samples were assessed by plotting the data in dual δ¹⁸O vs. δ²H isotope space with reference to values found in the published literature and fitting a linear regression equation for Astana (event) precipitation. Overall, this is the first dataset covering wide range of sources across Kazakhstan, which could be used by global and regional water resource assessments and studies such as tracing water sources, hydrograph separation and end-member analyses, isotope mass balance, evapotranspiration partitioning, residence time analysis and groundwater recharge.