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.
Accurate and reliable water level measurement is a critical task in hydrology, water resource management, irrigation systems, and automated industrial processes. This paper presents a comprehensive study of modern ultrasonic methods and tools for non-contact water level measurement, supported by mathematical modeling of liquid level dynamics in reservoirs. Typical mathematical models describing ultrasonic level measurement systems are developed and analyzed. The principles of operation of ultrasonic sensors, the formation of the detection zone, and the influence of geometric and physical parameters on measurement accuracy are discussed in detail. Particular attention is paid to sensor installation rules, operational constraints, and signal reflection characteristics. As a practical case study, the technical and metrological parameters of the UDM-110 ultrasonic level meter are analyzed. Mathematical models based on mass balance equations are derived to describe transient and steady-state variations of liquid level in reservoirs. The obtained models enable analytical evaluation of system dynamics and provide a foundation for the design and optimization of automated level control systems. The results confirm that ultrasonic level measurement combined with mathematical modeling ensures reliable, accurate, and cost-effective monitoring of water levels in open and closed reservoirs.
This study investigates hybrid energy installations that integrate micro-hydropower and solar systems as a sustainable approach to water-based and renewable energy resource management in decentralized mining regions. The key challenge addressed is the high dependence on diesel generators, which leads to significant environmental impacts (800-900 tons of CO₂ emissions annually) and economic inefficiency. As a result of the research, an optimized system configuration consisting of a 50 kW micro-hydropower plant, 40 kW solar photovoltaic panels, and a 25 kWh battery storage system was developed. The proposed hybrid system generates approximately 670000 kWh of electricity per year, reduces diesel dependency by 58-62%, saves 170-185 thousand liters of fuel annually, and decreases CO2 emissions by 450-500 tons. The reliability of the system reaches 92-95%, with an availability coefficient of 0,985-0,991. These results were obtained through mathematical modeling (Equations (8)-(12), AI- and IoT-based forecasting techniques, and laboratory prototyping. A distinctive feature of the proposed solution is its adaptation to unstable load profiles and region-specific climatic and hydrological conditions typical of mining operations. From the perspective of water conservation and environmental management, the use of micro-hydropower ensures efficient utilization of local water resources without large-scale hydrological disturbance. The practical applicability of the results is focused on mining enterprises with limited access to centralized electricity supply. The system operates effectively in regions with stable water flow rates of 50-70 L/s and solar radiation levels of 5,5-6,0 kWh/m2, demonstrating that industrial-scale implementation can significantly reduce diesel consumption, lower CO2 emissions, and enhance overall environmental and economic sustainability. The study also discusses operational limitations (seasonal variability, PV soiling, and component degradation) and outlines maintenance and economic risk considerations for long-term industrial deployment.
Improving energy dissipation and efficiency in hydraulic structures such as spillways, sluices, and weirs, is important to prevent downstream erosion and structural damage under high velocity (supercritical) flows. However, conventional stilling basin designs often fail to optimize hydraulic jump characteristics, particularly under strong hydraulic jump conditions. This study experimentally evaluates the hydraulic performance of single sill and double sill configurations of stilling basin in a laboratory-scale stilling basin under strong hydraulic jump conditions (11 < F_{1} < 13.2) A series of physical model experiments was conducted by varying sill geometry, height, and spacing. The results showed that the double sill configuration in Series DS-5, combination of an ogee sill (Z_{1} = 6cm) and a trapezoidal prism sill (Z_{2} = 4.5cm) spaced at L_{1} = 80 cm, L2 = 0.5L1 (40 cm), provides superior hydraulic performance compared to single sill and horizontal apron configurations. Series DS-5 achieved the lowest y2 and yj, the highest relative energy dissipation ((Eo-E2)/Eo = 81.42%), and average energy efficiency (E_{2} / E_{1} = 51.31%) The enhanced performance is attributed to intensified turbulence interaction and improved hydraulic jump control induced by combined sill geometry. Regression based relationships between dimensionless hydraulic variables were also developed to support predictive design. This research contributes a practical and compact stilling basin design for high energy flow conditions, offering improved efficiency and potential application in hydraulic structure design.
The purpose of this study is to examine the current state of water quality in the Nura-Sarysu river basin and predict its future trends. To achieve this purpose, a comprehensive monitoring approach has been used, including satellite imagery and machine learning. For instance, Sentinel-2 (10 m resolution) and Landsat 8/9 (30 m resolution) satellite imagery have been used for estimating the Normalized Difference Water Index (NDWI). This index has helped in identifying water bodies in the study area. In addition, the study has used critical water quality parameters, including heavy metals (Cd 0,15 mg/L, Pb 0,10 mg/L), biochemical oxygen demand (BOD5 10-15 mg/L), and salinity (0,5 g/L). It has been found that there are significant changes in the water quality parameters in the Nura-Sarysu river basin compared with the natural state. A significant correlation (R2 ≈ 0,82-0,87) has been found between satellite imagery and sensor-based estimations. In addition, a machine learning model has also been used for estimating temporal changes in water quality parameters. This model has shown high accuracy (R2 ≈ 0,88, RMSE ≈ 0,09-0,12). This study has shown the potential of the proposed approach for improving the assessment of water quality parameters in the Nura-Sarysu river basin in Kazakhstan.
Quantitative water balance assessments of traditional irrigation systems remain scarce, particularly for systems experiencing chronic water deficits driven by institutional rather than climatic factors. This study applied the F.J. Mock rainfall-runoff model to Subak Balangan, which has experienced a 20-year-long continuous water shortage due to an inter-district allocation dispute. Using 10-year climate data (2015-2024) and independent field validation measurements (March-July 2025, 10 half-monthly periods), the model achieved moderate-to-good performance (NSE = 0.521, R ^ 2 = 0.833 RMSE = 0.01 m³/s). Water availability at 80% reliability ranged from 0.001 to 0.012 m³/s across 24 half-monthly periods. A comparative water balance analysis of two crop rotations revealed that the existing flower-cassava rotation experienced deficits in 75% of periods (maximum 0.017 m³/s), while a hypothetical paddy-paddy-maize rotation would produce deficits in 91.7% of periods, with 2.96-fold higher peak demand (maximum 0.074 m³/s). These results quantify the magnitude of water stress under existing institutional constraints and demonstrate the limitations of paddy-based crop intensification as a water management strategy in this specific context. Beyond empirical findings, the study advances two theoretical contributions: Institutional Hydro-Decoupling (IHD), extending Ostrom’s common-pool resource theory to conceptualise conditions where governance failure structurally severs the link between catchment hydrology and effective irrigation supply; and Hydro-Adaptive Cropping Moderation (HACM), extending autonomous adaptation theory to identify farmer-led rotation adjustment as an endogenous demand-side mechanism that partially compensates for institutionally-suppressed water availability. The findings provide a baseline water balance reference for ongoing allocation dispute resolution and highlight the need for multi-Subak comparative studies to establish broader patterns.
Denpasar City faces increasing flood risks due to rapid urbanization and population growth (0.12% per year; density 5,870 people/km²), which reduce infiltration areas, while Nusa Penida experiences chronic drought influenced by El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), threatening Bali’s tourism sector that contributes approximately 60% of regional GDP. This imbalance in water resources requires an integrated, adaptive approach to water conservation. This study aims to develop a sustainable rainwater harvesting (RWH) model by integrating geospatial analysis, hydrological assessment, and the local wisdom of Tri Hita Karana (THK). Rooftop rainwater harvesting systems were installed on Nusa Penida to address water scarcity in karst areas. In contrast, infiltration wells were installed in Denpasar to reduce surface runoff and enhance groundwater recharge. The results indicate that rainwater harvesting in Nusa Penida generates a surplus of approximately 184.9 million litres, covering about 16% of total domestic water demand. In Denpasar, infiltration well effectiveness ranges from 23.26% to 59.91%, with lower effectiveness observed in South Denpasar due to shallow groundwater levels (±1.5 m). These findings demonstrate that a GIS-based RWH system integrated with Tri Hita Karana values provides a practical, context-sensitive solution to address water inequality in Bali. The proposed model supports green economy-based water conservation policies and offers a replicable framework for sustainable water management in tropical island regions.
Climate change greatly influences ecosystems, communities, and economies, the effects of climate change on water supplies, environmental conditions, and weather patterns will typically have both abrupt and gradual impacts on all three categories, in Iraq, the geographical analysis focused on the annual concentration of precipitation, the high-resolution climate grid (0.5×0.5) used in this analysis provided information for the period of 1956 to 2025, it used an initial 5-year period and the final 5-year period within each decade, the use of Geographic Information Systems (GIS) enabled the study to achieve the objectives of this analysis, rainfall figures reflect great variability among the rainfalls recorded within the different decades of the second millennium, in the 6th decade of the 20th century, annual rainfall ranged from 21–1047 mm, in the seventh decade between 32–1080 mm, in the 8th decade between 105–1082 mm, in the 9th decade between 110–1037 mm, and in the 10th decade between 98–1091 mm, even though there were large fluctuations from one rainy season to another, both 5-year periods within each of the three decades had relatively consistent rainfall amounts, while there was a pronounced decrease from monthly to long-term intensity during the first and second decades of the third millennium, the total volume of precipitation recorded was significantly lower than the previous two decades; for example, during the first decade of the 3rd millennium total amount of precipitation was 114–986 mm, and during the second decade total amount of precipitation was 89–987 mm, precipitation has been highest near those regions which experience the most rainfall (northeast and north), while precipitation amounts are substantially less in southern and southwest Iraq, the annual rainfall averages are well below those seen at the end of the twentieth century and over the last few decades as a consequence of climate change, the average annual precipitation amounts from the rainfall maps vary from 76 mm to 1,014 mm, while the average annual precipitation amount for the 2010’s was 1,065 mm, the northern areas have consistently received more precipitation than the southern areas, which are mostly dry, therefore, Iraq is already suffering from decreased precipitation due to the ongoing effects of variability in rainfall patterns, as a result, there is an urgent need to examine different sources of water and the efficient use of what falls as precipitation.
Water quality typically determines diarrhea incidence rates, but findings vary widely across studies. This study want to synthesize those findings to find the relationship between water quality and diarrhea incidence. Method which utilized in this meta-analysis following PRISMA guidelines. The included study is observational studies (both case-control and cross-sectional studies) from databases including PubMed, ScienceDirect, Scopus, and Google Scholar. Only studies that report adjusted odds ratios (aOR) are included. Random-effects model was applied due to high heterogeneity. The results showed that water quality and diarrhea incidence are not significant ( a0R = 0.63; 95% CI: 0.23-1.74; I ^ 2 = 91.4% ) Same results also found in subgroup analyses. This means that the relationship between water quality and diarrhea is not simple as it seems. Other factors such as sanitation, hygiene habits, and food contamination also influence diarrhea. Therefore, improving only on water quality to reduce diarrhea may not be sufficient. More integrated approach is needed to address diarrhea sustainably.
The study investigated how suspended sediment concentration (SSC) and environmental factors relate in the coastal waters of Lhok Paroy in Aceh Besar, Indonesia. Samples were taken from ten sampling locations at high and low tide. SSC varied from 150 mg/1 to 220 mg/l when the tides went out and had a similar range of 110 mg/l to 220 mg/l when it came in. Higher SSC were found near the mouth of the river as well as in areas of high human activity. The other environmental variables also had considerable variability that was dependent on tidal phase as well as location. Luminosity ranged from 4.6 m to 8.9 m; salinity ranged from 28 ppt to 31 ppt; temperature ranged from 30 °C to 33 °C; dissolved oxygen (DO) ranged from 5.5 mg/l to 11 mg/l; and pH ranged from 6.5 to 7.9. Through Principal Component Analysis (PCA), PCA identified the strongest relationships between SSC and pH (Station 2) and SSC and temperature (Stations 3 and 4). And, negative correlations were also found between SSC and DO, and SSC and luminosity. As a result, the amount, or concentration of SSC is affected by tidal hydrodynamics, sediment resuspension and mineral interactions. The work provides insight into the complex interaction between physicochemical factors that impact water quality in tropical coastal ecosystems and helps form a scientific basis for future sediment management and environmental monitoring plans for the Lhok Paroy area.
Agricultural drought poses an escalating threat to crop production and on-farm water management across the semi-arid Mediterranean basin, yet Al-driven spatially explicit prediction frameworks remain scarce for North African drylands. This study develops an explainable artificial intelligence (XAI) framework for agricultural drought prediction across five semi-arid governorates of central Tunisia over the 2001-2022 period. A multi-source dataset of 154,704 pixel-month observations (586 pixels at 0.05° spatial resolution) was assembled by integrating 15 predictor variables spanning meteorological, topographic, edaphic, and socioeconomic domains relevant to crop stress assessment. The drought target variable (Standardized Soil Moisture Index, SSMI) was derived exclusively from GLEAM v4.2a, while soil moisture predictors were drawn from the independent NASA POWER MERRA-2 atmospheric reanalysis to ensure methodological rigor and preclude mathematical circularity. Six machine learning models were evaluated (XGBoost, LightGBM, CatBoost, RF, BPNN, and LSTM) using a strict temporal split (training: 2001-2014; testing: 2015-2020; validation: 2021-2022) focused on an unprecedented multi-year drought episode. Results show that BPNN achieved the highest predictive performance on the test set ( R ^ 2 = 0.86 , SDI = 0.626), whereas XGBoost demonstrated superior generalization during the extreme 2021-2022 validation period (R ^ 2 = 0.696, SDI = 0.448) establishing it as the most robust architecture for drought-stress prediction under extreme climate conditions. TreeSHAP interpretability analysis identifies MERRA-2 soil moisture as the dominant predictor (26.0%), followed by temperature (14.2%), sand content (10.0%), and precipitation (8.6%), revealing that edaphic conditions strongly modulate drought severity and crop water stress in the Tunisian interior. These findings provide an operational smart decision-support tool for drought early-warning and precision irrigation planning in semi-arid agricultural regions.
This study examined the factors influencing household access to domestic water across four Local Government Areas (LGAs) in Oyo Zone, Oyo State, Nigeria, using exploratory factor analysis. Data were collected through structured questionnaires administered to residents and analysed using principal component extraction with varimax rotation. Results showed that five to six dominant factors explained more than 60% of the total variance in water accessibility in each LGA, indicating strong explanatory power. Key shared determinants across the zone included proximity to water sources, reliability of supply, and water quality, reflecting the importance of availability, consistency, and safety in household water access. Distance was the most influential factor in Atiba (Rotated Component Matrix value = 90.0), while water quality had the strongest effect across Oyo Zone (RCM = 87.2) Household preferences also significantly shaped access patterns, particularly in Oyo Zone (RCM = 92.3) driven by affordability, convenience, and cultural considerations. Distinct local challenges were identified, including high patronage levels in Afijio, physical access constraints in Atiba and Oyo Zone, and limited piped water connectivity in Oyo Zone. The findings reveal considerable spatial variation in water access conditions within the same geopolitical region. The study concludes that improving equity in water access requires location-specific interventions. Recommended actions include expanding piped water infrastructure, improving supply reliability and quality, reducing travel distance to water points, and addressing physical access barriers. Incorporating household preferences into water planning can enhance sustainability and user acceptance while strengthening water governance and equitable domestic water provision.
This study presents a numerical assessment of groundwater flow and filtration properties of the Senonian-Lower Eocene aquifer complex within the Karakata artesian basin (Uzbekistan), based on the interpretation of long-term operational data, well test results, and regime observations obtained under conditions of incomplete and heterogeneous hydrogeological information, where key filtration, water conductivity, elasticity, and piezo conductivity parameters were estimated using analytical approaches and refined through inverse problem solutions, and a single-layer groundwater flow model with spatially heterogeneous hydraulic properties was developed using the MODFLOW code, incorporating major structural features of the basin including tectonic fault zones acting as pathways for additional groundwater recharge and discharge, with model calibration performed through stationary and transient inverse simulations achieving good agreement between observed and simulated piezometric heads with deviations generally within ±5 m, while the results indicate that the aquifer complex is predominantly confined and exhibits pronounced lateral heterogeneity in hydraulic conductivity, long-term exploitation has been sustained mainly by dynamic flow reserves and elastic storage with a significant contribution from fault-controlled inflow from the Paleozoic basement, the estimated dynamic groundwater reserves are lower than previously reported values, and the developed model provides a reliable framework for groundwater balance assessment, forecasting of aquifer response to pumping, and sustainable groundwater resource management in arid regions.
Groundwater is the main freshwater source in semi-arid areas, thus, needs protection from human pollution. The municipal solid waste landfill and an untreated wastewater disposal facility are located in Al-Lajjoun region of central Jordan which situated within the recharge zone of the Amman-Wadi Sir (A7/B2) carbonate aquifer, this study investigates the sustainability and the groundwater quality. for that reason, untreated wastewater and soil samples impacted by leachate, and eight production wells were observed in the summer and winter. Major ions, trace metals, and physicochemical properties were examined and compared with Jordanian drinking water standards. The results show that the groundwater hydrochemistry is mainly consistent during the year, where the majority of parameters falling within permitted limits. Nevertheless, chromium concentration in all wells continuously exceed drinking water regulation, indicating a recurring pollution problem. Meanwhile, the landfill leachate saturated soils demonstrated high concentrations of Fe, Cr, Cd, Pb, Ni, Zn, and Mn compared with baseline values. Untreated wastewater had high organic and nutrient concentrations. The high metal concentrations in leachate affected soils lead to a possible permanent risk to the aquifer sustainability even in the absence of direct hydraulic mixing between wastewater and groundwater, particularly, in structurally fractured carbonate systems. The findings demonstrate the aquifer’s resilience under current conditions, Also, shows the necessity for long-term hydrochemical monitoring, engineered barrier structures, and preventive management to ensure groundwater conservation in arid zones.
Reservoir sedimentation is continuing to be an essential obstacle to the long-term performance of dams and water infrastructure, with consequences for hydropower generation, flood control, and environmental integrity. This bibliometric study analyzes 118 peer-reviewed publications from 2014 to 2024, retrieved from Scopus, focusing on sediment flushing and reservoir sedimentation. Using Excel, VOSviewer, RStudio, and MapChart, the study maps publication trends, methodological diversity, co-authorship networks, and institutional contributions. The dataset reveals a marked increase in publication activity over the study period, with numerical modeling consistently leading in frequency and application. This upward trend reflects growing global attention to sediment-related challenges and the expanding role of computational strategies in addressing complex hydraulic phenomena. Further efforts could emphasize integrating field-based validation with existing models to enhance reliability. Expanding comparative studies across diverse regions may also improve the adaptability of sediment management strategies.
This study addresses the automation of a corona discharge-based drinking water disinfection system and its control using water quality monitoring tools. The research proposes an automated control system that dynamically adjusts the corona discharge parameters based on water quality parameters (pH, turbidity, electrical conductivity). The following key results were obtained: the system consistently maintained microorganism inactivation efficiency between 99,9% and 99,99%, even under fluctuating water quality conditions. For instance, at a turbidity level of 10 NTU, the disinfection efficiency dropped to 99,8%, while at pH values ranging from 6,5 to 8,5, the efficiency remained between 99,9% and 99,99%. The energy consumption was 20%-35% lower compared to traditional methods; for example, the energy consumption for UV irradiation methods ranged from 0,05 to 0,15 kWh/m3, while the corona discharge method remained between 0,5 and 2,0 kWh/m3. The initial models and control algorithms improved the system’s performance in real-time, ensuring stable operation despite changes in water quality parameters. The results demonstrate the significant advantages of the corona discharge method in terms of energy efficiency and stability, proving its ability to maintain high disinfection efficiency even with continuous variations in water quality. Furthermore, this system provides an environmentally friendly and energy-efficient solution for drinking water disinfection.
