Our study examines the impact of climate change on the hydrology of the Charvak Lake watershed in Uzbekistan, focusing on streamflow from the Pskem, Chatkal, and Koksu rivers during the 1990–2022 period. The analysis evaluated the contributions of snowmelt and glaciers to river flows while addressing modelling limitations, including the absence of dedicated land classes for snow cover and glaciers. This study, conducted under the CGIAR NEXUS Policy Innovation initiative, focused on hydrological modeling using the QSWAT+ tool to better understand these dynamics. Calibration efforts improved model performance, with statistical parameters indicating a correlation coefficient (R) of 0.77, a coefficient of determination (R²) of 0.59, and a percent bias (PBIAS) of –15%, demonstrating reasonable agreement between observed and simulated data. However, the Nash–Sutcliffe Efficiency (NSE) was low at 0.27, highlighting challenges in accurately simulating extreme flows during peak and low-flow periods. Mann–Kendall and Sen’s slope tests showed no statistically significant trends in streamflow for both simulated and observed flows (p = 0.69 and p = 0.31, respectively), though observed data suggested a slight potential increase likely linked to glacier melt.
The key aspect of this study is the recommendations for prediction of pulsation loads and calculation of slabs of the drainage basin with energy-absorbing elements of a cavitation-resistant structure. Using computational analysis and hydrodynamic studies, the configuration of the basin was selected, which had not previously been encountered in the operated devices of the downstream of irrigation hydraulic structures. Optimization of the structural elements of the expanding spillway head will ensure reliable operation of the branch channel during the implementation of the modernized preliminary project. This ensures stable flow in the outlet channel below the spillway apron regardless of the stage of cavitation or changes in the spectrum and magnitude of pressure pulsations in individual attachment points and local sections of the damping pool.
This study presents an integrated approach to groundwater level monitoring in the Tashkent region, combining classical piezometric measurements, automated sensors, and satellite-based remote sensing. A regression model linking groundwater levels to monthly precipitation (P) and water abstraction volumes (Q) was developed using simulated 2024 data. The results reveal a clear seasonal pattern: groundwater levels peak during the wet season and decline sharply during the irrigation-intensive summer months. The model provides a scientific basis for adaptive water management policies under increasing climatic and anthropogenic pressures.
Southern Iraq, especially Wasit and Maysan governorates, is experiencing flash flooding and water shortages. Limited hydrological research and streamflow data limit runoff estimates, flood risk assessment, disaster preparation, and floodwater harvesting. Simulating the hydrological and hydraulic response of a 2,945.33 km² watershed during a March-May 2019 flood and modelling rainfall-runoff processes with 2019 daily rainfall data in ArcGIS, HEC-HMS, and 2D HEC-RAS highlights the potential for floodwater harvesting to address seasonal shortages. In the HEC-HMS software, the SCS-CN method for losses, the SCS Unit Hydrograph for transformation, and the Muskingum routing method were used to compute run-off in each watershed reach. The extracted discharge outputs were input as upstream boundary conditions to a 2D HEC-RAS model to estimate flood extent. Simulations revealed about 144.4 million m³ of runoff volume, with initial abstraction (la) having the greatest impact on volume. Qualitative comparison with Sentinel-2 satellite imagery from a similar flood occurrence indicated good spatial consistency for model validation. Because of their concentration on flood forecast accuracy, quantitative measures like CSI were evaluated but not employed as validation evidence. Although data is rare in ungauged arid basins, integrated modelling can improve water planning and flood risk management if monitored and regulated.
The rapid development of mineral water desalination technologies, particularly for pasture-based livestock farming in remote regions, has resulted in the generation of substantial volumes of highly concentrated brines and regenerating chemical solutions, the uncontrolled discharge of these waste streams poses serious environmental threats, including soil salinization and groundwater contamination, this study aims to develop and experimentally validate a sustainable technology for the disposal and reuse of brines and wash solutions produced during the desalination of mineralized water using a mobile reverse osmosis (RO) unit, to minimize environmental impacts, a comprehensive methodological framework combining analytical, experimental, functional, and statistical approaches was applied to identify weaknesses in existing desalination methods and to assess the performance of a vacuum evaporation system, the chemical composition of the treated mineral water was analyzed, and a bench-scale vacuum evaporator was designed and tested, the proposed process scheme for the mobile RO unit includes a vacuum evaporation module capable of achieving a vacuum of –0.7 bar and a heating temperature of up to 60 °C, enabling efficient brine concentration, regeneration of chemical solutions, complete liquid waste recycling, and recovery of dry residues, while returning distilled water to the desalination cycle, the developed technology can be applied for irrigation of remote pastures and to improve the environmental performance and cost efficiency of industrial water treatment systems.
