Applied Water Science最新文献

Water scarcity poses major constraints to sustainable rural development, particularly in arid regions. In Egypt, limited freshwater resources are increasingly prioritized for domestic use, compelling proposed large-scale land reclamation projects to rely on brackish groundwater. However, marginal water quality restricts cultivation to salt-tolerant crops, undermining the long-term profitability of ongoing agribusiness activities. This study is the first to evaluate the techno-economic viability of integrating decentralized desalination systems into the Moghra development area. A systematic hydrochemical assessment of 73 wells, using the Irrigation Water Quality Index (IWQI), classified 49 as “Severe Restriction” and 24 as “High Restriction”, confirming widespread concerns about groundwater suitability. A two-stage reverse osmosis (RO) desalination system powered by photovoltaic (PV) energy was designed to achieve a 70% recovery rate. An optimization model identified blending ratios that maximize post-treatment water quality while minimizing the desalinated water volume. Results showed substantial improvements: the average sodium adsorption ratio (SAR) decreased by 66%, and IWQI increased from 34 to 77. Consequently, 68 wells were reclassified as “Low Restriction” and 5 as “Moderate Restriction”, enabling a shift from salt-tolerant olives to higher-value crops (e.g., wheat–maize rotation). A cost–benefit analysis assessed trade-offs between desalination costs and resulting economic returns. Under the abstraction limit, the proposed RO–PV blending strategy yielded a 35% higher net present value (NPV) and a 15.7% internal rate of return (IRR), demonstrating both technical and financial viability. These findings provide actionable insights for policymakers, stakeholders, and investors to enhance water productivity and agricultural sustainability in arid regions.

Water scarcity and pollution are pressing challenges in arid regions where conventional wastewater treatment systems are often impractical. Constructed wetlands (CWs) offer a sustainable, low-cost alternative; however, the comparative mineral uptake capacities of key wetland species under arid conditions remain underexplored. This study reports a two-year field experiment in eastern Saudi Arabia comparing two species, Typha latifolia L. (T. latifolia) and Phragmites australis (P. australis) (Cav.) Trin. ex Steud. (P. australis), for their capacity to accumulate heavy metals and macronutrients when irrigated with wastewater. Plants were cultivated in controlled CW systems, and aboveground biomass was analyzed at multiple intervals. Results reveal that P. australis accumulated higher levels of trace metals, notably manganese, with concentrations of 161.47 mg·kg⁻¹ compared to 83.65 mg·kg⁻¹ in T. latifolia). This difference corresponds to a statistically significant 48.2% increase (p ≤ 0.05) relative to T. latifolia. Although aluminum (+ 14.5%) and vanadium (+ 25.5%) uptake was slightly higher in P. australis, these differences were not statistically significant. Uptake varied widely among elements, reflecting species-specific and temporal dynamics. In contrast, T. latifolia demonstrated a much stronger affinity for macronutrients, particularly for sodium (12,476 vs. 1065 mg·kg⁻¹) and potassium (13,475 vs. 4308 mg·kg⁻¹), exceeding P. australis by over 1000% and 200%, respectively (p ≤ 0.05), with highly significant differences (p ≤ 0.05). Magnesium uptake was also consistently higher in T. latifolia compared with P. australis (1823 vs. 1442 mg·kg⁻¹; p ≤ 0.05). These findings reveal complementary roles between the two macrophytes: P. australis is more effective at trace metals removal, while T. latifolia excels in macronutrient uptake and biomass production. Integrating both species in CWs can enhance multipollutant removal efficiency and long-term treatment performance. The study provides practical guidance for designing phytoremediation systems in arid regions and support the development of decentralized wastewater treatment solutions for small and rural communities where conventional infrastructure is limited.

Because of its ease of use, affordability, effectiveness, and environmental friendliness, adsorption phenomenon is a widely used separation technique in wastewater treatment and environmental remediation. In a process known as an adsorption isotherm, the amount of material adsorbed by a substrate is frequently described as a function of the equilibrium concentration at a constant temperature. Understanding the layout and functionality of adsorption systems, the understanding of adsorption isotherms is required. This review study aims to provide an understanding of the concept and applications of adsorption isotherm models by highlighting the general knowledge and applications of the isotherm model to date. There has also been emphasis on the isotherm model’s classification. Furthermore, a range of isotherm models with respect to the quantity of parameters have been talked about in depth. It has also been covered how to choose the right model and the latest developments in modeling methodology. These models’ adsorption isotherm constants and goodness of fit characteristics were calculated. This review article also covers the mechanics of adsorption, several single and multi-component isotherm models, their importance, and their limitations, as well as the factors influencing competitive adsorption.

Conventional wastewater flow-control strategies often fail to respond effectively to rapidly changing hydraulic conditions, resulting in increased overflow events, excessive energy consumption, and reduced operational resilience. Existing AI-based approaches primarily focus on prediction or process-level optimization, offering limited capability for autonomous, system-wide flow management. To overcome these limitations, this study introduces AquaFlowNet, a reinforcement learning–driven framework designed for real-time wastewater flow optimization across interconnected sewer networks. The proposed RL-DFC agent dynamically learns optimal valve and pump actions from environmental feedback, enabling adaptive control under uncertain inflow conditions. Simulation results demonstrate that AquaFlowNet achieves substantial improvements over existing rule-based and machine learning controllers, including a 52% reduction in total overflow volume, up to 90% reduction in overflow events, 35–40% improvement in peak-flow attenuation, and 230 kWh reduction in aeration-related energy demand. These findings indicate that AquaFlowNet can transform wastewater management from prediction-centric approaches into autonomous, resilient, and scalable network-level control, supporting the development of next-generation smart wastewater infrastructure.

Effective underwater pollution monitoring depends on reliable wireless communication technologies capable of transmitting data in challenging aquatic environments. This study evaluates three communication technologies, acoustic, optical, and radio frequency (RF), using input from 35 experts across five criteria: data rate, power efficiency, range, cost, and environmental impact. Results show that acoustic communication is the top choice, excelling in range and energy efficiency. RF ranks second for its balanced performance and cost-effectiveness, while optical communication scores lowest due to limited range and adaptability. The study highlights the usefulness of multi-criteria decision-making for selecting technologies for marine environmental monitoring, while noting limitations, such as subjective inputs and context-specific findings.

A ternary TiO₂/BiVO₄/activated carbon (AC) heterostructure was synthesized and evaluated for photocatalytic degradation of phenol and methylene blue (MB) under UVA and visible light. Structural and optical analyses confirmed an S-scheme TiO₂–BiVO₄ junction uniformly distributed on porous AC, with reduced band gap (2.41 eV). AC incorporation enhanced adsorption, light absorption, and charge separation. The composite achieved up to 99% phenol removal and 96% MB degradation under UVA, retained ~ 81% efficiency after five cycles, and showed broad-spectrum activity. Radical scavenging indicated valence band holes and superoxide radicals as dominant species. The synergistic charge separation, adsorption, and extended photoresponse make TiO₂/BiVO₄/AC a promising photocatalyst for water purification.

Due to limited water and soil resources in arid and semi-arid regions, improving irrigation efficiency and both physical and economic water productivity is essential. Proper study, design, implementation, operation, and maintenance of modern irrigation systems, together with water management on farms, are key approaches to achieve Precision Agriculture and Sustainable Development. This research aimed to present a hybrid method to identify suitable areas for implementing modern irrigation systems, and to propose the most appropriate system type by developing a hybrid MCDM-GIS framework. To comprehensively assess the main influencing factors, 16 sub-criteria were selected under six criteria: water resources, soil, climate, social, economic, and cropping patterns. Five irrigation system options were considered: Fixed Classic with movable sprinklers, Wheel Move and Gun sprinklers (SpCWG), Center Pivot and Linear irrigation machines (SpCL), Surface Trickle Irrigation (TrGT), Gated Pipes (SuGP), and Subsurface Trickle Irrigation (TrSS). The criteria and sub-criteria were defined using the Delphi method and validated with the CVR index. The AHP-TOPSIS hybrid model was then applied to determine the weight of the sub-criteria. Classification and information layers were prepared for each sub-criterion, and after applying the weighting coefficients, and overlaying the layers, a map of suitable areas for each irrigation system was generated. Finally, for each well and aqueduct water source, irrigation systems were identified in order of priority. A case study was conducted in Arak County, central Iran, with an arid and semi-arid climate and irrigation-based agriculture. The results from the AHP-TOPSIS integrated framework showed that in the SpCWG system, water resources and climate had the highest weights (0.472 and 0.246, respectively). Water electrical conductivity, chlorine, and long-term maximum wind speed strongly influenced the SpCWG system. For the SuGP, SpCL, TrSS, and TrGT systems, the soil criterion had the highest weights (0.514, 0.45, 0.315, and 0.31, respectively), followed by water resources (0.175, 0.229, 0.315, and 0.31, respectively). In the soil criterion, soil texture and land slope were the most important sub-criteria, while in the water resources criterion, water electrical conductivity and chlorine were most significant. The TrGT system was most frequent as the first priority for lands irrigated by 600 wells (44%) and 78 aqueducts (46%). Overall, the proposed hybrid method effectively identified suitable areas for modern irrigation systems and recommended the appropriate system type.

Graphene-based nanocomposites have emerged as powerful photocatalysts because graphene’s unique 2D structure and chemistry dramatically improve light-driven reactions. In photocatalytic composites, graphene or its derivatives including graphene oxide (GO), reduced graphene oxide (rGO), and 3D graphene aerogels, serve as high-surface-area conductive scaffolds that promote charge separation, extend light absorption, and adsorb pollutants. As a result, graphene-supported catalysts exhibit greatly enhanced performance in environmental remediation (wastewater treatment and air purification), solar hydrogen evolution, and CO₂ photoreduction. This review surveys recent (2020–2025) advances in synthesis of graphene–semiconductor photocatalysts and elucidates the mechanisms by which graphene boosts activity. We discuss integration of graphene with common semiconductors (TiO₂, ZnO, and BiVO₄) and highlight representative applications in water purification, H₂ generation, and CO₂ conversion. Comparisons with other nanocomposite systems and key challenges (scalability, stability, and cost) are also addressed, drawing on findings from recent high-impact studies.

Mefenamic acid (MA) is described as a non-steroidal anti-inflammatory drug. In the study, improved electrooxidation of MA using a nanostructured sensor based on modification of the surface a bare electrode is described. Dysprosium stannate nanostructures (DSN) are used for designing a modified carbon paste electrode (CPE/DSN). The nanostructures were synthesized using an environmentally friendly process and characterized via various techniques. Then, the nanostructures were used to modify the CPE surface. The characterization of the nanostructures was accomplished using X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), and electrochemical techniques. Next, the nanostructured electrode was applied for electrochemical studies and the analysis of MA. For achieving the purpose, a strategy based on multivariate optimization was performed. The strategy caused to optimize all of the effective variables simultaneously. The voltammetric experiments showed an enhancement response for MA at the surface of CPE/DSN than the CPE. Therefore, linear dynamic range was obtained in two regions containing 0.01–20.0 and 20.0–650.0 μM for MA with 1.44 nM for detection limit. Finally, the suggested procedure was used for the monitoring of MA in complicated samples with reasonable results.

The Nag River, flowing through the highly urbanized core of Nagpur, Maharashtra, serves as the primary drainage system for the city and is critically polluted due to rapid urban development and uncontrolled industrial discharges. While conventional physicochemical assessments exist, they fail to provide the quantitative, spatially resolved source apportionment necessary for targeted remediation. This study integrates WQI with PCA and CA to provide a structured, data-driven assessment of pollution sources along the Nag River, specifically Principal Component Analysis (PCA) and Cluster Analysis (CA) within a spatial framework to provide the first systematic differentiation of pollution sources (e.g. municipal sewage vs. specialized industrial effluent) and link them directly to specific land-use zones along the river’s 17 km urban corridor. The aim was to holistically assess the surface water quality and quantitatively identify, map, and attribute pollution sources along this critical stretch. Nine (9) surface water samples (S1-S9) were systematically collected during the pre-monsoon season (February 2023), covering segments influenced by diverse residential, commercial, and industrial land use. Twenty physicochemical and biological parameters were analyzed, and the reliability of the hydrochemical data was confirmed using the Ionic Balance Error (IBE) validation. WQI values ranged severely from 47.05 (Good) at the upstream baseline (S1) to a maximum of 6440.38 (Unfit for all practical uses) at Yashwant Stadium (S5), confirming chronic heavy pollution. This degradation is primarily attributed to untreated municipal sewage, as indicated by extreme BOD levels up to 216.28 mg/l and non-compliant specialized industrial discharges. PCA identified three primary Varifactors (VFs) explaining 87.935% of the total variance. Varifactor 1 (44.088%) confirmed the overwhelming dominance of untreated municipal sewage (organic load, total dissolved solids, and microbiological parameters). Varifactor 2 (16.666%) was strongly associated with specialized heavy metals (Nickel and Cadmium), indicating a distinct point source industrial effluent. CA successfully categorized sampling sites into four spatial pollution clusters (C1-C4), enabling the identification of high-priority pollution hotspots that correlate directly with land use. The present study integrates the WQI-PCA-CA approach, combined with land use assessment, to provide critical insights to support evidence-based river restoration and sustainable watershed management planning.