Applied Water Science最新文献

The study was conducted at Bontanga irrigation scheme in Northern Region of Ghana to know the extent of water losses in the scheme, identify deficiencies leading to water losses, propose solutions for reduction of water losses, and project the impact of water losses on water demand using Water Evaluation and Planning (WEAP) model. Assessment of water losses was based on conveyance, distribution, in-field, and total water losses. Out of the seasonal irrigation water supply of 8,391,118.37 m³, total water losses of 5,766,524.23 m³ (conveyance losses: 1,208,321.04 m³, distribution losses: 2,657,635.02 m³, and in-field losses: 1,900,568.17 m³) were recorded, representing 68.70% of the seasonal inflow into the irrigation system. Total water losses were beyond the acceptable limit of 40% for the surface irrigation system. Such significant water losses were attributed to lack of proper maintenance on canals, under-utilization of flow measuring structures, excessive lateral canal tailwater losses, and poor water management at field level. Without efforts to reduce water losses, WEAP model results revealed that unmet water demands are likely to reach 2,482,519 m³ by 2030. However, by reducing total water losses from 68.70 to 40%, an average seasonal water saving of 3,894,597.86 m³ is projected to be achieved during the simulation period from 2024 to 2030.The study has enlightened the significance of effective water loss management to meet competing water demands in the face of a changing climate. Future studies should investigate an in-depth synergy between crop water productivity and system’s water losses in the study area.

Water insecurity poses a significant challenge to sustainable urban development in eThekwini, South Africa, where many communities face prolonged water shortages and unreliable municipal supply. This study evaluates the economic and technical feasibility of implementing Independent Water Producers (IWPs) to deliver 100 000 L of potable water per day using modular reverse osmosis (RO) systems. The methodology employed combined hydrogeological assessment, process design, and economic modelling. Groundwater from boreholes was selected as the primary water source, and hydrogeological data from regional studies and the National Groundwater Archive were used to estimate potential yields and quality. The treatment system was designed for a worst-case feedwater scenario (Class 4 quality), incorporating pre-treatment units (sand, activated carbon, softening, and iron removal) followed by a high-rejection reverse osmosis unit. The process configuration was developed based on standard RO design principles and verified using supplier specifications. Economic feasibility was assessed using discounted cash flow (DCF) and net present value (NPV) analyses, with cost assumptions derived from current quotations, municipal tariffs, and local construction indices. Sensitivity analyses were then performed to evaluate the effects of variations in feedwater quality, capital cost, and land acquisition on project viability. Results indicate that IWPs using modular RO systems are economically feasible, with an NPV of R460 000 and an internal rate of return (IRR) of 10.7% under highly conservative assumptions. Sensitivity analyses reveal that the project’s profitability improves significantly when using better-quality feedwater or when capital costs are reduced through land leasing or pre-existing infrastructure. This study demonstrates that decentralized water supply using modular RO technology can provide a viable and scalable solution for enhancing water security in underserved urban areas. It offers a framework for future implementation of IWPs, supporting resilience, public-private partnerships, and reduced dependence on centralized municipal systems.

Under increasing climate change pressures and growing freshwater scarcity, the textile industry urgently needs innovative, low-cost, and sustainable wastewater treatment technologies. This study explores the use of palm waste, an abundant lignocellulosic by-product in arid regions, as an eco-friendly adsorbent for textile effluent purification. A pilot-scale prototype was developed and tested under dynamic flow conditions to evaluate treatment performance, regeneration behavior, and economic feasibility. Results showed pollutant removal efficiencies exceeding 85–95.7%, with total suspended solids and organic loads effectively reduced over three to five regeneration cycles using a simple ethanol–water washing step. The system also achieved a 90% reduction in water costs, confirming its strong potential for industrial water reuse. Complementary kinetic modeling with cationic and anionic model pollutants validated the chemisorption-driven mechanism. Overall, this work demonstrates the technical, economic, and environmental viability of palm-waste-based filters, aligning with national water reuse strategies and circular economy goals for sustainable resource management.

The presence of pharmaceutical compounds such as efavirenz and levonorgestrel in water resources has become an issue of great social and scientific concern in recent years due to their considerable effects on aquatic ecosystems and human health. This study aims to address this concern by synthesizing sulphur-doped carbon nanotubes (S-CNT) from macadamia nutshells for use in the efavirenz (EFA) and levonorgestrel (LVG) from an aqueous solution. The synthesized S-CNT was characterized for its functional groups, surface morphology, and crystallinity using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and X-ray diffractogram (XRD) techniques. SEM micrographs showed tubular features on the material’s surface. The efficiency of the synthesized S-CNT towards EFA and LVG removal was assessed using batch experiments in the presence of 250 nm UV. The maximum removal efficiencies for EFA and LVG were 99 and 98%, respectively, at optimum conditions of pH 2, dosage of 0.3 g/50 mL, and initial concentration of 2.5 ppm after 90 min agitation time. The removal of FEA and LVG involved both photodegradation and adsorption, wherein the EFA and LVG were degraded into C₁₄H₈ClF₃NO^± and C₁₃H₁₀ClF₃N^±; C₁₅H₂₁O₃‾ and C₂₁H₂₉O₃‾, respectively, by the UV light followed by their subsequent adsorption onto the surface of the S-CNT. The adsorption kinetics data yielded R² ≥ 0.98 for both pseudo-first-order and pseudo-second-order reaction kinetics models for both EFA and LVG, indicating the possibility of physisorption and chemisorption processes. The isotherm data fitted better to the Freundlich isotherm model, indicating that the removal occurred on a heterogeneous surface. Based on these findings, S-CNT can potentially remove EFV and LVG from wastewater.

Polyethylene glycols (PEGs) are increasingly found in wastewater due to their use in the production of non-ionic surfactants, pharmaceuticals, antifreeze agents, water soluble lubricants, and cosmetics. This has led to increased interest in determining the fate of this chemical species in wastewater treatment plants. For the first time, a detailed practical and theoretical study on the fate of PEG has been conducted at the Aoun sewage treatment plant (ASTP) and modeled using the TOXCHEM model. Data were collected and entered into the TOXCHEM model, after calibration and validation, and root mean square error (RMSE) and correlation coefficient (R) were 0.04 and 0.82, respectively, which is within acceptable limits. A sensitivity analysis showed that the most sensitive parameters were the wastewater influent flow rate, temperature, air flow rate, MBBR biofilm thickness, specific surface area of the MBBR media, and MBBR media fill fraction. The TOXCHEM model showed that emission of PEG varied according to the season. Emissions were greatest during the warmer months and summer and spring emissions were found to be 24% and 18.4%, respectively. During spring and summer 24% and results of the TOXCHEM model indicated that the fate of PEG during spring and summer (35°C) and autumn and winter (12°C) was that about 24 and 18.4%, 10 and 10%, 53.5 and 46.6%, and 12.5 and 25% was fated to be emitted into atmosphere, sorbed to sludge, biodegraded, and discharged with the outlet, respectively. The highest emission was 3.3 mg/m³ during the summer season in the aeration basin. Excessive flow rate affects biodegradation and reduces treatment efficiency. Reducing air flow rate, and the effects of MBBR biofilm thickness, specific surface area of MBBR media, and MBBR media fill fraction all increase the biodegradation process, reduce emission rates, and improve the treatment process. Increasing temperatures increase biodegradation, but also increase emissions. Practically, air flow rate, MBBR media fill fraction, and return activated sludge (RAS) were chosen for their ease of application at ASTP. The practical enhancement contributed to the reduction of the concentrations of chemical oxygen demand (COD), biological oxygen demand (BOD), total suspended solid (TSS), nitrate (NO₃₎, phosphate (PO₄–P), ammonia (NH₄), hydrogen sulfide (H₂S), PEG in summer, and PEG in winter, from 44, 35, 15, 35, 3, 0.15, 0.18, 0.8, and 1.9 to 20,11, 9, 8, 2, 0.12, 0.1, 0.35, and 0.6 mg/L, respectively. Overall improvements increased biodegradability from 47 to 75.4% and reduced emissions from 18 to 5.6%. The TOXCHEM model used in this study was found to be an excellent predictor of the enhancement process.

The growing environmental pollution caused by organic contaminants and the limitations of conventional treatment methods have made the development of sustainable degradation strategies increasingly urgent. This study proposes a green synthesis as an eco-friendly alternative to the traditional solvent-based preparation of photocatalysts. Ag/Ag₃O₄/CuO nanocomposites were successfully synthesized using Inula viscosa leaf extract, a natural reducing and stabilizing agent. Physicochemical analyses confirmed the formation of crystalline heterostructures (50.0–57.6 nm) with band gap energies ranging from 1.76 to 2.81 eV. The AAC-4 sample, containing 30% silver, achieved 99.3% degradation of Safranin O dye within 100 min under visible light and in the presence of 10 mM potassium persulfate (PDS). The synthesized catalyst maintained good efficiency over five reuse cycles. Machine learning (DT_LSBOOST) accurately predicted the degradation results (R = 0.9981, RMSE = 0.1116), and the dragonfly algorithm identified optimal conditions with only a 0.34% deviation from experimental data. These results highlight the synergistic effect of green nanomaterials and artificial intelligence for cost-effective and eco-friendly wastewater treatment.

This study delineates groundwater recharge potential zones in a river basin using a GIS-based multi-criteria decision analysis integrated with the Analytical Hierarchy Process (AHP). Eleven thematic layers—including geology, lineament density, soil type and texture, hydrological soil groups, slope gradient, drainage density, curvature, and land use—were reclassified and weighted based on their influence on recharge. The weighted overlay technique produced a spatially explicit recharge potential map, categorizing the basin into five zones ranging from very poor to very good. Key findings reveal that colluvial and alluvial deposits, combined with gentle slopes and permeable soils, offer the highest recharge potential, while steep basaltic terrains exhibit minimal infiltration capacity. The integration of high-resolution geospatial data with AHP enhances the precision of hydrogeological assessments in data-scarce regions. These results provide a practical framework for targeted groundwater management, supporting sustainable resource planning aligned with the basin’s unique geological and topographic conditions.

Precise flood forecasting, both preceding and succeeding an event, is paramount for enacting effective management strategies to minimize potential damages. This study developed a comprehensive framework for predicting pre- and post-flood operations in a semi-arid basin in Iran by Multi-Model Integration; the Weather Research and Forecasting (WRF) model, the Hydrologic Component-Hydrologic Modeling System (HC-HMS) model, and the Hydraulic Engineering Center-River Analysis System (HEC-RAS) model. The WRF model was used for pre-flood operations, while a satellite product assessed post-flood damage. Among five precipitation prediction schemes, the Lin scheme showed the highest accuracy in forecasting 48-hour precipitation, achieving a True Skill Score (TS) of 0.93. The precipitation output from the Lin scheme was then inputted into the HC-HMS hydrological model. The coupled WRF-HC-HMS model demonstrated a simulation accuracy ranging from 0.33 to 0.93, as indicated by the Nash-Sutcliffe Efficiency (NSE) criterion. The hydrological model outputs were then incorporated into the HEC-RAS hydraulic model to generate two-dimensional flood inundation maps, with simulation accuracies between 0.60 and 0.83. Finally, MODIS satellite imagery was used to estimate pre- and post-flood damage in the study area. The integrated framework provides valuable insights for water resources and flood management decision-makers, enabling them to forecast 48-hour runoff/precipitation and issue flood warnings before an event. The generated flood hazard maps can also assist in estimating the area and extent of flood-affected zones. This holistic method improves the capability to prepare for and respond to flood disasters in the semi-arid basin.

Cadmium (Cd) contamination of aquatic ecosystems poses significant environmental and public health risks. Conventional wastewater treatment methods including ion exchange, coagulation, membrane filtration, chemical precipitation, and biological degradation exhibited operational limitations in Cd removal efficiency and cost-effectiveness. Consequently, adsorption-based technologies utilizing nanomaterials have gained prominence as advanced alternatives. Engineered nanomaterials, particularly metallic/metalloid oxides and carbon-based structures, offer superior Cd adsorption capabilities due to their exceptional surface area-to-volume ratios, tunable surface chemistry, and multifunctional reactivity. Among these, carbon nanotubes (CNTs), especially multi-walled variants (MWCNTs), present a cost-effective, scalable, and sustainable solution for heavy metals (HMs) remediation. This review critically evaluates the adsorption mechanisms of Cd onto MWCNTs, Synthesis and functionalization strategies to enhance adsorption capacities, and comparative efficacy of CNTs against emerging metallic oxide nanomaterials. Recent advances in nanomaterial design, including surface modification and composite synthesis, are highlighted for their role in optimizing Cd removal kinetics and selectivity. Future research directions emphasize assessing long-term ecotoxicological risks of nanomaterial deployment and developing encapsulation protocols to mitigate environmental release while advancing next-generation adsorbents.

This study aims to evaluate the potential use of clinoptilolite-type zeolite, leonardite, and diatomite, which have abundant reserves in Türkiye and can be mined more easily and economically compared to other mines, as water parameters regulators. The trial was conducted in seven groups in triplicate. The groups were assigned as the control (C), natural zeolite (NZ), natural leonardite (NL), natural diatomite (ND), conditioned zeolite (CZ), conditioned leonardite (CL), and conditioned diatomite (CD). The trial was initiated by adding 2 g of natural and conditioned zeolite, leonardite, and diatomite to their respective groups, excluding the control inside 500 ml tap water. Water parameters (temperature, dissolved oxygen, pH, and NH₄⁺) were measured daily for 14 days. In this study, as of the 4th day of the experiment, a decrease was observed in ammonia values originating from the feed in the groups treated with adsorbent compared to the control group. When all adsorbent groups were evaluated together, the ammonia values in the groups containing natural leonardite and conditioned leonardite remained at the recommended values for aquaculture throughout the experiment period (14 days). As a result of the study, it was concluded that leonardite (1.66 ± 0.001) and zeolite (0.71 ± 0.03) (4 g/l) could be used effectively in ammonia removal for aquaculture practices. The current study is one of the first studies to investigate the effect of natural adsorbents on ammonia removal and pH. Furthermore, it is the first study to demonstrate a reduction in fish feed-derived ammonia values compared to the unconditioned (natural) forms of conditioned diatomite and leonardite, based on a literature review.