https://arww.razi.ac.ir/ Journal of Applied Research in Water and Wastewater en daily 1 Mon, 01 Dec 2025 00:00:00 +0330 Mon, 01 Dec 2025 00:00:00 +0330 https://arww.razi.ac.ir/article_3881.html Hydraulic structures have a long history, with weirs being among the earliest developed; a notable example of these is the side weir. Side weirs are of different shapes, including a nonlinear weir installed on the dam crest. Weirs with nonlinear designs come in various forms, like labyrinth and piano key weirs; these are used when weir length is restricted, to maximize crest length, which subsequently increases discharge capacity. This study examines and contrasts how piano key and labyrinth weirs function as side weirs, since there has been little research on piano key side weirs. Within this study, the experimental models incorporated trapezoidal, rectangular, and triangular Labyrinth weirs, alongside piano key weirs, each characterized by four distinct heights 5, 10, 15, and 20 cm and three cycles, where the piano key weirs were classified as A-type. At a certain Ht/P ratio, weirs with a smaller height had the maximum discharge coefficient and vice versa for weirs with a larger height. When a straight piano key weir and a rectangular labyrinth weir are both placed at a right angle to the stream, the piano key weir performs better. Conversely, the present study, which evaluated the aforementioned weirs as side weirs, yielded contrasting results; the rectangular labyrinth weir exhibited superior efficiency to the piano key weir. The study’s findings revealed triangular labyrinth side weirs exhibited a superior discharge coefficient (maximum 0.689), while rectangular labyrinth weirs outperformed piano key weirs by up to 24.85 % in side-channel arrangements. https://arww.razi.ac.ir/article_3882.html The aim of this research was to separate mercury from gold refining wastewater using activated carbon (AC) from natural shells. To this end, walnut and coconut shells were used as the main source of AC. The characterizations of both ACs were compared by FTIR, BET, and SEM analyses. The FTIR results revealed interactions between the solute and the functional groups on the adsorbent surface. According to the BET results, the mean pore diameter (MPD) of AC from coconut shells (CSAC) was smaller than that derived from walnut shells (WSAC). The specific surface areas for CSAC and WSAC were 1069.1 and 119.6 m2/g, respectively. SEM results revealed that the porous texture of ACs emanates from their cellular structure. This research further studied the impact of operational parameters “adsorbent dose” (0.3-3.8 g/L), “pH” (2-9), and “residence time” (10-120 min) on mercury removal. Under optimal operational conditions, the mercury removal rate reached 97% (for WSAC) and 93% (for CSAC). Kinetic model assessments revealed the highest agreement between the experimental data and the pseudo-first-order (PFO) model. Both adsorbents were regenerable, with their performance (compared to fresh adsorbents) exceeding 90% after each regeneration. https://arww.razi.ac.ir/article_3890.html The study aims to show the role of pH value and the feasible mechanisms that affect the adsorption capacity by the theoretical concept and experimental work. The protonation, ionization, hydrophobicity, dissociation, precipitation, hydrolysis, hydroxylation, electrical repulsion or interaction, ion exchange, and complexation and chelating are effective mechanisms that have been studied theoretically to show their essential role in the absorption process and how they are affected by the pH value. Moreover, using varied pH values (2, 4, 6.5, 9, 11, and 13) to verify experimentally the role of the studied mechanisms on the adsorption capacity utilizing the recycled bentonite waste as adsorbent to adsorb the heavy metals, methylene blue dye, and engine oil as adsorbates from aqueous solution. It was apparent that the pH solution has an influential role in the adsorption capacity and from the difficulty in predicting the effect without making the experimental investigations due to the nature of the adsorbent and adsorbate that affected the ten mechanisms where the pH of the high adsorption capacity for heavy metal was alkaline (>11) and for the methylene blue and engine oil was neutral(≈ 6.5). https://arww.razi.ac.ir/article_3960.html Oily pollutants, such as 4-nitrophenol, are unavoidable problems. One of the methods employed for treating wastewater polluted with 4-nitrophenol is the use of moving bed biofilm reactors (MBBRs). The present research compared, for the first time, the two common types of media (Kaldness K1 and Bee Cell 2000) in MBBR for treating wastewater polluted with 4-nitrophenol, and determined and reported the optimum conditions for media types and heat. A biofilm layer was first formed on the surface of the media in each reactor, and then the microorganisms were acclimatized to the contaminants. Following that, changes in efficiency with variations in initial COD concentration (400-2,500 mg/l), retention time (8, 12, 24, and 48 h), and filling ratio (30, 50, and 70 %) in the two reactors were determined and compared. The highest efficiencies (84 and 80 percent for the reactor with Bee Cell 2000 media and that with Kaldness K1 media, respectively) were observed. Both reactors containing Bee Cell 2000 media and Kaldness K1 media were very capable of treating wastewater polluted with 4-nitrophenol at 20 °C. Still, the reactor that included the Bee Cell 2000 media yielded better results compared to that containing the Kaldness K1 media. https://arww.razi.ac.ir/article_4012.html In this study, 5 wt. %Cu-doped TiO₂ nanoparticles (NPs) were synthesized through a green and sustainable method, utilizing Cannabis sativa leaf extract as a reducing agent to promote eco-friendly wastewater treatment. The NPs were characterized using XRD, FESEM, BET, EDAX, and TEM, revealing uniform dispersion, an average particle size of approximately 20.5 nm, and a high surface area of 92 m²/g. These NPs were employed for adsorption of Methylene Blue (MB) and Rhodamine B (RhB) dyes from aqueous solutions at initial concentrations of 1–10 mg/L. Adsorption experiments, conducted over 150 min, showed equilibrium data best fitting the Freundlich isotherm (R² = 0.9979 for MB, 0.9995 for RhB), indicating multilayer adsorption. Kinetic studies confirmed that the Elovich models provided the best fit (R² > 0.997), suggesting chemisorption-dominated processes. The NPs exhibited high adsorption efficiency, offering a cost-effective and sustainable solution for treating textile wastewater, addressing critical environmental challenges posed by industrial dyes. https://arww.razi.ac.ir/article_4016.html Hydro-climatic research and water resource management in arid, data-scarce regions depend fundamentally on precise precipitation data. This study presents the first comprehensive, multi-scale evaluation of four prominent gridded precipitation products (GPPs)—TRMM, CHIRPS, GSMaP, and ERA5—in the climatically challenging and sparsely gauged South Khorasan province of Iran (2010–2019). Using ground-based observations as a reference, GPP performance was evaluated across multiple timescales with a suite of statistical metrics. The evaluation framework leverages diagnostic visualizations, such as Taylor and performance diagrams, to provide deeper insights into error structures than can be achieved through traditional map-based assessments. The analysis revealed a clear performance ranking: the satellite-based TRMM and GSMaP consistently performed best, showing higher accuracy (median RMSE ≈ 2.91–3.05 mm/day), stronger correlation (median CC ≈ 0.63–0.65), and a more balanced detection skill (median CSI ≈ 0.43–0.45). In contrast, the ERA5 reanalysis product, despite achieving the highest probability of detection (POD ≈ 0.78), suffered from notable systematic biases and the largest random errors. Performance for all products degraded during the arid summer, and estimation errors systematically increased in wetter regions. We conclude that the gauge-adjusted satellite products, GSMaP and TRMM, provide the most dependable precipitation estimates for the study area. These findings offer a critical, evidence-based guide for selecting appropriate GPPs in this vulnerable environment and provide insights for future algorithm development. https://arww.razi.ac.ir/article_4017.html Phosphorus is one of the main limiting factors for eutrophication in water resources. According to the increasing population and the worsening of the healthy water shortage crisis in recent years, it is necessary to control the concentration of this element (phosphorus) in water resources. This study was performed with the aim of phosphorus removal efficiency (PRE) and sludge volumetric index (SVI) modeling in the chemical precipitation process, and by using poly-aluminum chloride as a precipitator. In this study, the response surface method (RSM) was used based on the central composite design (CCD) to model the effects of pH, the precipitator concentration, mixing time, mixing speed, settling time, and phosphorus initial concentration on the two desired answers including PRE and SVI. Analysis of variances (ANOVA) of the responses showed that among the above factors, precipitator concentration, phosphorus initial concentration, and settling time on phosphorus removal efficiency has been significant. Also, the most important parameters affecting the sludge volume index were precipitator concentration, settling time, and pH. Phosphorus removal efficiency and sludge volume index under optimal condition (pH=7.46, poly-aluminum chloride concentration=104.85 mg/L, mixing time=133 s, mixing speed=152 rpm, settling time=36 min and phosphorus initial concentration= 6.33 mg/L) was predicted to be 84.68% and 151.79 mL/g, respectively. Based on the average responses obtained from three times experiment under predicted optimized conditions, the phosphorus removal efficiency was 80.03%, the sludge volumetric index was 200.07 mL/g. The predicted and obtained data from the experiments showed conformity, which indicates the accuracy of modeling. The findings of this study showed that the factors of precipitator concentration, settling time, and pH should be well controlled to manage the chemical precipitation process using poly-aluminum chloride. https://arww.razi.ac.ir/article_4044.html A wide range of applied fluid mechanics problems are related to transient flows. In conventional analyses, the relationship between wall shear stress and average cross-sectional velocity — valid for steady flow — is often assumed to hold under unsteady conditions. This simplification, typically implemented through the Darcy–Weisbach or Hazen–Williams formulations, leads to an underestimation of frictional losses in rapid transients by up to 15–25% according to experimental studies. Unsteady friction formulations incorporate an additional term to account for acceleration effects, thereby improving prediction accuracy. For instance, Zielke’s convolution-based model achieves less than 2% error in laminar regimes, while simplified approaches such as Trikha’s approximation reduce computational demand by approximately 60% with only a minor accuracy loss (<5%) for low-Reynolds turbulent flows. Instantaneous acceleration-based (IAB) models, such as Brunone’s, can reduce pressure attenuation discrepancies by 10–18% compared to quasi-steady models, and two-coefficient IAB variants further improve waveform agreement by separating temporal and spatial acceleration contributions. This review critically examines the major classes of unsteady friction models outlining their theoretical basis, computational performance, and applicability domains. Furthermore, classification schemes, practical implementation aspects, challenges, and future research directions, including hybrid physics–machine learning approaches, are discussed in detail. https://arww.razi.ac.ir/article_4086.html Nanostructured semiconductors have emerged as promising photocatalysts for sustainable wastewater purification. Among them, TiO₂–P25 (commercial TiO₂) is widely used; however, its wide band gap restricts visible light activity. A simple and eco friendly approach to overcome this limitation is the formation of heterostructures. In this work, TiO₂–P25/WO₃ heterostructures were synthesized via a rapid, additive free aqueous sonochemical route (10 min ultrasonication). The structural characteristics of the composites were examined by XRD, FTIR, Raman spectroscopy and FESEM, while their optical and interfacial properties were assessed by DRS, ζ potential and EIS analyses. These characterizations confirmed that the anatase–rutile TiO₂–P25 and monoclinic WO₃ phases remained intact without the appearance of new interfacial bonds, while close physical contact between the two oxides improved visible light absorption and facilitated interfacial charge transfer. The photocatalytic performance was evaluated in a spherical quartz reactor under real sunlight using methylene blue (MB) as a model pollutant. Response surface methodology with a central composite design was employed to investigate the effects of catalyst dose (0.5–1.5 mg/L), initial MB concentration (20–40 mg/L), and pH (5–9). Under the optimized conditions (20 mg/L MB, 1.5 mg/L catalyst, pH 9), 69.5% of MB was removed by dark adsorption within 30 min, and subsequent sunlight irradiation resulted in 94.6% total removal after 70 min, with a reaction rate constant of 0.042 min⁻¹. Taken together, these results demonstrate that this simple aqueous synthesis provides an efficient and eco friendly pathway to prepare TiO₂–P25/WO₃ photocatalysts for large scale wastewater remediation under real sunlight. https://arww.razi.ac.ir/article_4087.html In this paper the influence of the operational and geometrical parameters on the mixing and flow uniformity within an anaerobic digester is investigated. Anaerobic digestion is classified as single or multiphase flow reactor to produce biogas from processed organic waste. Within the digesters, mass transfer is a key component to obtain an optimal process which is highly dependent on uniformity and turbulence of the flow. Two quantitative mixing criteria namely uniformity index and turbulence intensity are assessed to investigate the possibility of improving mixing characteristics of an operating digester. The effect of inlet velocity, draft tube flow presence, draft tube velocity magnitude and direction and inlet tube position have been investigated and compared to a validated base case. According to the finding both inlet velocity and inlet pipe position can noticeably affect the operation of the digester and proper tuning of the inlet velocity and also optimized pipe position can enhance the uniformity of the flow while inducing high turbulence within the digester. Furthermore, by adjusting the inlet pipe position, it is possible to improve the uniformity index and turbulence intensity by 44% and 40% respectively. https://arww.razi.ac.ir/article_4088.html Distilleries produce substantial amounts of wastewater containing high concentrations of organic and inorganic pollutants, leading to serious environmental concerns. In Sindh, Pakistan, water resources are at risk owing to the inappropriate disposal of industrial distillery effluents, contaminating land resources, water bodies, and groundwater. This has led to a notable increase in skin diseases and other health problems in Sindh, Pakistan. Therefore, effective and sustainable treatment strategies are required. We comprehensively reviewed the characteristics of sugar distillery wastewater from the Sindh region and highlighted its chemical composition, toxicity, and environmental impact. Conventional treatment methods often fail to achieve complete pollutant removal, necessitating the development of advanced alternatives. Nanomaterials, including nanoparticles, nanocomposites, and Nano-catalysts, have emerged as promising alternatives owing to their high surface areas, superior adsorption capacities, and reusability. This analysis examined a range of nanomaterials, such as metal oxides, carbon-based materials, and bio-inspired nanoparticles, and evaluated their potential for treating wastewater locally. This study aims to bridge the knowledge gaps and promote sustainable approaches for mitigating water pollution in the Sindh sugar distillery industry. https://arww.razi.ac.ir/article_4089.html Multinational corporations, seeking to reconcile economic goals with environmental stewardship, have found themselves at the center of an engaging academic discourse; one that has increasingly examined the role of ethical governance in promoting corporate environmental sustainability. This study analyses whether ethical integration positively correlates with proxies of environmental performance, including greenhouse gas (GHG) emissions mitigation, waste reduction, energy efficiency, and renewable energy adoption. Using a mixed research design—comprising descriptive statistics, multiple regression analysis, and structural equation modelling (SEM)—we find that organizations with strong ethical frameworks achieve significantly better environmental outcomes. Specifically, the Ethical Integration Index (EII) shows astrong correlation with waste reduction (r = 0.72), GHG emissions reduction (r =0.68), and energy efficiency improvement (r = 0.66). Regression results further indicate that EII explains up to 76% of the variance in waste reduction and 71% inGHG mitigation. SEM analysis confirms both direct effects and indirect effects mediated by innovation (λ = 0.52, p < 0.01) and regulatory compliance (λ = 0.47, p < 0.01). These findings emphasize the crucial role of ethical decision-making indriving corporate environmental responsibility, suggesting that corporations should incorporate ethical governance into sustainability endeavors. The study offers actionable insights for corporate policymakers, environmental regulators, andsustainability practitioners concerned with long-term sustainability transformations. https://arww.razi.ac.ir/article_4018.html The present study outlines the production of AgNPs through a green synthesis method utilizing the water extract of Ferula assa-foetida leaves. In contrast to earlier studies that mainly focused on the plant's gum, this research used an ultrasonic-assisted extraction method for the leaf tissues. FTIR analysis validated the presence of different organic compounds, particularly phenolic groups, on the AgNPs surface, which is crucial for their stability and bioactivity. FE-SEM images displayed the nanoparticles' shapes, which were mainly spherical and cauliflower-like, with an average size of 86 nm. XRD analysis revealed that silver ions were reduced to create metallic nanoparticles in the following phase, as shown by distinctive peaks at 38.2°, 44.4°, and 64.51°. Synthesized nanoparticles were assessed for antibacterial properties against two bacterial models: Staphylococcus aureus (Gram-positive) and Escherichia coli (Gram-negative). A higher sensitivity was observed in Gram-positive bacteria. Therefore, AgNPs produced using Ferula leaf extract can be considered valuable alternatives for antibacterial and therapeutic purposes. https://arww.razi.ac.ir/article_4071.html Floods rank among the most destructive natural disasters worldwide, with their frequency and intensity amplified by climate change. This study presents an integrated approach combining hydraulic modeling and multi-sensor satellite data to improve floodplain mapping accuracy during the April 3, 2019 flood event in Kermanshah, western Iran. The research focuses on the confluence of the Gharasoo, Merek, and Razavar rivers, where combined flows created significant flood risks for Kermanshah city. The study makes several important methodological contributions to flood modeling. First, it demonstrates the value of simultaneous analysis of both steady and unsteady state conditions, providing a more comprehensive understanding of flood dynamics compared to conventional single-state approaches. Second, the integration of optical (Sentinel-2, Landsat) and radar (Sentinel-1) remote sensing data effectively overcomes the limitations of individual sensors, particularly in addressing cloud cover issues. Third, the implementation of Google Earth Engine enables near-real-time flood monitoring capabilities, significantly enhancing operational response potential. Finally, the development of robust validation metrics specifically adapted for flood model assessment represents an important step forward in model verification methodologies. HEC-Geo RAS simulations predicted extreme conditions with water levels rising up to 6 meters and flow velocities reaching 3m/s. Validation results showed strong agreement between unsteady state modeling and satellite observations (F1=0.73, F2=0.72), while steady-state conditions exhibited lower correlation (F1=0.41, F2=0.28). The model effectively tracked flood progression from inception to peak, while satellite imagery provided rapid regional coverage despite occasional cloud obstructions. https://arww.razi.ac.ir/article_4083.html This study presents a direct comparative and synergistic investigation of polyvinylpyrrolidone (PVP) and trimesic Acid (TMA) as additives for polyethersulfone (PES) membranes. Scanning electron microscopy (SEM) analysis revealed that PVP primarily acts as a pore-forming agent, while TMA induces a finer, sponge-like morphology. Water contact angle (WCA) measurements confirmed that TMA imparts higher surface hydrophilicity (37.5°) compared to PVP, attributed to its lower aqueous solubility and greater retention of hydrophilic carboxylic acid groups within the polymer matrix. Pure water flux (PWF) data, monitored at 4 bar pressure, showed that membranes embedded with TMA as a single additive had lower flux than the bare membrane, due to their sponge-like pore structure. A powerful synergistic effect was discovered in dual-additive formulations. The optimal membrane (M7), containing 1 wt.% each of PVP and TMA, achieved an exceptional PWF of 103 kg/m²·h. This synergy is driven by accelerated co-leaching during phase inversion, which optimizes pore structure. From the antifouling test, single TMA-based membranes demonstrated the highest FRR values (approximate 100%). Meanwhile, the membranes containing both PVP and TMA showed compromised FRR. Nevertheless, M7 membrane maintained an acceptable FRR of 75%. The results indicate that combining PVP and TMA creates a synergistic effect, producing membranes with a superior balance of high permeability and antifouling resistance compared to those with a single additive. https://arww.razi.ac.ir/article_4115.html The Khersan River, the largest tributary of the Karun River, is regulated by the Khersan-3 Dam, constructed for flood control, irrigation management, and hydropower generation. Despite its strategic importance, no comprehensive study has previously assessed microbial water quality in this reservoir, particularly under the pressure of intensive agricultural activities in the watershed. This study investigated heterotrophic bacteria, total and fecal coliforms, and protozoan (Giardia and Cryptosporidium) contamination in the Khersan-3 sub-basin. Monthly sampling was carried out from November 2023 to October 2024 at five stations using sterile glass bottles (100 ml) from the surface layer (20 cm depth). For protozoan detection, 10 liter samples were collected at Station 5. Results showed seasonal and spatial variations in microbial indicators. The highest mean concentration of heterotrophic bacteria was observed in autumn 2023 (6.237 Log CFU/100 ml), while the lowest occurred in summer 2024 (4.507 Log CFU/100 ml) (p<0.05). Total coliforms reached their maximum in winter 2023 (3.822 Log CFU/100 ml) and decreased to a minimum of 2.509 Log CFU/100 ml in summer 2024 (p<0.05). However, seasonal variations in the mean density of fecal coliforms were not statistically significant (p>0.05). Across stations, the densities of heterotrophs, total coliforms, and fecal coliforms did not differ significantly (p>0.05). Cryptosporidium was undetected in all samples, whereas no significant difference was found in Giardia occurrence among seasons, despite detection in approximately 40% of spring samples (p>0.05). This study provides the first evidence of substantial temporal and spatial fluctuations in indicator bacteria across the Khersan-3 Dam watershed, highlighting the influence of hydrological and anthropogenic drivers. The findings emphasize the need for targeted management actions, including continuous microbial surveillance, stricter control of agricultural runoff, and improved water treatment practices to safeguard public health and aquaculture sustainability. https://arww.razi.ac.ir/article_4116.html Global waste production is estimated to increase to 3.4 billion metric tons by 2050, of which 69% of waste disposal, especially in Sub-Saharan Africa, is discharged through unlined landfills/open dumpsites. This study examines the toxic effects of unlined landfills/open dumpsites on environmental and public health. Based on geophysical and hydrochemical data from literature, the study reveals a low subsurface resistivity between 4.2 – 34 Ωm around dumpsite-affected areas, indicating severe groundwater contamination, while a high subsurface resistivity >120 Ωm noted at control points suggests little or no contamination, depending on the nature of the terrain. Samples from surface and groundwater registered elevated heavy metal (HM) levels beyond WHO limits, with groundwater varying between 0.005 – 2.430 mg/L, surface water recorded a higher concentration of HMs, with the highest concentration (≤7.5 mg/L) noted in the Challawa River, Nigeria, where waste materials are discharged into the river at will. Methane released from landfill gas amounts to 40 million metric tons annually, which accounts for 7.5% of global methane emissions. Temperatures observed with landfills ranged between 32°C and 60°C, increasing greenhouse gas emissions and global warming. Such practices result in the release of toxic gases and heavy metal leachates, which pose serious long-term threats to the environment as well as to public health. The adoption of clean technologies such as waste-to-energy solutions and sanitary landfills is a major constraint, but necessary in these fast-growing urban areas. In conclusion, the current unlined landfills/open dumpsites practice, especially in developing nations, is unsustainable. A need for a shift towards sanitary landfills, integrated waste management, recycling, and climate-resilient policies is imperative to mitigate this pervasive contamination and steer towards a sustainable, waste-conscious future https://arww.razi.ac.ir/article_4150.html Water quality in rivers is a critical concern in hydrology. This study examines the Gadar-Chai River, situated within Iran's Urmia Lake basin, utilizing data from four selected hydrometric stations: Oshnavieh, Polebahramlu, Bighaleh, and Naghadeh. An improved Water Quality Index (ImpWQI) was calculated for each station using data from 2003 to 2021. Trends in ImpWQI values and the used water quality parameters, including the annual time series of TDS, EC, pH, HCO₃⁻, Cl⁻, SO₄²⁻, Ca²⁺, Mg²⁺, Na⁺, K⁺, and TH, were analyzed in the period 2003–2021. Three significance levels, at 1%, 5%, and 10%, were used. The Mann-Kendall (MK), Mod-ified Mann-Kendall (MMK), and innovative trend analysis (ITA) methods, as well as Sen's slope estimator, were used for trend detection and calculating the slope of trend lines. The results showed both upward and downward trends in the time se-ries. MK, MMK, and ITA showed similar results in detecting the trend direction, but differed in estimating trend magnitude. MMK tended to show stronger trends than MK .However, unlike the MK and MMK methods, which only identify monotonic trends, the ITA method is capable of detecting sub-trends. Among all the water quality variables of the Gadar-Chai Basin, the pH parameter had the highest num-ber of positive trends. Trends in the Cl- parameter were negative in almost all the stations. Trends in the ImpWQI index were negative in the three stations, namely Oshnavieh, Polebahramlu, and Naghadeh; however, station Bighale witnessed an upward trend in ImpWQI. A negative trend line slope was observed for the EC pa-rameter in the station Polebahramlou, whereas a positive slope was obtained for the same parameter in the station Bighaleh. https://arww.razi.ac.ir/article_4169.html Providing safe and clean water for a rapidly growing population is a critical global challenge. Nanotechnology-based membranes, or nanomembranes, represent a promising pathway toward sustainable wastewater treatment. Their ultra-thin, highporosity structure can offer superior contaminant removal, enhanced flux, and lower energy consumption compared to conventional membranes. This review addresses both the fundamental principles and the latest advancements of nanomembranes, with an emphasis on the practical hurdles that currently impede widespread industrial adoption. Issues such as fouling, short operational lifespans, and cost barriers are discussed. In addition, the text highlights emerging materials and fabrication strategies, including two-dimensional (2D) nanosheets such asgraphene oxide and MXenes, as well as composite membranes integrated with metal-organic frameworks or covalent organic frameworks. Real-world applications are summarized, along with a discussion of how specialized membrane designs can reduce fouling in large-scale treatment plants. The review concludes by proposing future research directions that could make nanomembrane technologies both economically viable and environmentally safe, and by illustrating how these novel systems can be scaled up to help achieve global clean-water sustainability goals. https://arww.razi.ac.ir/article_4173.html Ciprofloxacin (CIP), as a commonly used fluoroquinolone antibiotic, is frequently detected in pharmaceutical effluents and aquatic environments and poses significant microbiological hazards due to low biodegradability and high stability. In this study, heterogeneous catalytic oxidation of ciprofloxacin was explored using a bimetallic CuFe/Al₂O₃ catalyst synthesized by wet impregnation method. FTIR, XRD, SEM, and BET analyses characterized the catalyst, showing Cu and Fe oxides uniformly distributed on the Al₂O₃ support and a mesoporous structure with a specific surface area of 91.9 m² g⁻¹. Subsequently, batch oxidization experiments determined the influence of operating parameters (catalyst dosage, initial pH and reaction time) on ciprofloxacin removal efficiency. Box–Behnken Design (BBD)of Response Surface Methodology (RSM) verified process optimum and variable interaction analysis. Maximum CIP degradation of 80.66 % was observed in aqueous solution at optimal operating conditions. Kinetic studies showed pseudo-first-order kinetics (k = 0.0191 min⁻¹ (R² = 0.9911); t₁/₂ = 36.3 min) confirmed rapid oxidation. CuFe/Al₂O₃ showed superior performance due to the redox cycle of Cu²⁺/Cu⁺ and Fe³⁺/Fe²⁺ species, advantageous generation of hydroxyl radicals from heterogeneous Fenton-like reactions. Therefore, the results support that CuFe/Al₂O₃ catalyst is a worthwhile and stable catalyst for antibiotic breakdown via advanced oxidation for sustainable pharmaceutical wastewater treatment. https://arww.razi.ac.ir/article_4178.html A significant source of water pollution, industrial effluents degrade water quality and jeopardize ecological equilibrium. In order to solve this problem, this study suggests an automated system that uses supervised learning techniques to anticipate the best places for wastewater disposal. The method makes use of statistical characteristics including mean, standard deviation, variance, and entropy in addition to two important water quality indicators: chemical oxygen demand (COD) and biological oxygen demand (BOD). We create and compare four classification models: ensemble classification, Extreme Learning Machine (ELM), Support Vector Machine (SVM), and k-Nearest Neighbour (k-NN). Accuracy, sensitivity, specificity, and computing time are all taken into consideration while evaluating performance. Experimental results show that whereas other approaches provide a balance between efficiency and efficacy, ensemble classification offers improved prediction accuracy at the expense of increased time consumption. In order to ensure adherence to pollution control regulations and assist sustainable water management, the suggested framework offers industry a useful decision-support tool for locating appropriate wastewater disposal sites. https://arww.razi.ac.ir/article_4186.html The discharge of sloped piano key weirs (PKWs) is proportionate to the upstream head, which allows for improving hydraulic performance under various conditions. This study experimentally investigates the discharge coefficient and hydraulic performance of sloped and non-sloped PKWs with rectangular and trapezoidal sections. The goal was to evaluate the effects of the crest slope of sidewalls on the discharge coefficient and performance of a PKW. Tests were performed in an experimental flume with a length of 15 m and a height of 60 cm. Rectangular and trapezoidal type-A PKWs with 0° and 15° inclinations were studied. This study also incorporated the effect of the Weber number on the discharge coefficient of PKWs by evaluating hydraulic data. It was found that sloped rectangular and trapezoidal PKWs, where over 75% of the crest length contributed to the discharge, had larger discharge coefficients than their non-sloped counterparts. Moreover, in light of their larger effective length, sloped trapezoidal PKWs had a 13% greater discharge coefficient than sloped rectangular PKWs on average. This suggests that sloped PKWs could improve flood management and water storage efficiency. https://arww.razi.ac.ir/article_4188.html This study evaluates four alternative water and wastewater management scenarios for Kerman City using Life cycle assessment based on the ReCiPe 2016 Midpoint (H) method and the World (2010) H normalization and weighting set. The scenarios include: (1) pre-industrial baseline without centralized sewage collection, (2) current practice where treated effluent is predominantly allocated to the steel industry, (3) partial reallocation of wastewater to green urban use, and (4) reduced industrial allocation with seawater substitution. The functional unit is the management of 1 m³ of urban wastewater. Results show that Scenario 1 has the lowest Global Warming Potential (0.36 kg CO₂-eq), followed by Scenario 3 (0.49 kg CO₂-eq), while Scenario 4 shows the highest impact (1.25 kg CO₂-eq) due to desalination energy use. In the water consumption category, Scenario 4 performs best (0.05 m³ water consumed), compared to 0.22 m³ in Scenario 2. Regarding freshwater eutrophication, Scenario 4 also outperforms other options, with an impact score of 0.0018 kg P-eq. Monte Carlo simulation was conducted for uncertainty analysis, indicating a high degree of robustness in the comparative rankings. The findings highlight the trade-offs between energy use, water reuse, and environmental burden, providing insights for sustainable water planning in arid urban regions. https://arww.razi.ac.ir/article_4189.html This research aims to develop an indigenous model for aligning urban water supply and demand strategies with a circular economy approach in Iran. The research methodology was qualitative, employing thematic analysis, with data collected through semi-structured interviews with 13 experts from Iran's water and wastewater industry. The thematic analysis results identified 6 dimensions, 27 components, and 109 indicators for the research conceptual model. The identified dimensions include: resource and infrastructure management strategies, circular economy strategies, demand and consumption management strategies, innovation and indigenous technology development strategies, water crisis resilience and management strategies, and financial and investment system strategies. The research findings indicate that the developed model, in addition to considering common concepts in global literature, pays special attention to indigenous characteristics and specific challenges of Iran in urban water management. By presenting a comprehensive model, this research provides a practical framework for policymakers and managers in the country's water industry to develop effective strategies for integrated urban water resource management with a circular economy approach. https://arww.razi.ac.ir/article_4227.html In this research, the capability of two improved photocatalytic (immobilized-suspended) and hybrid (Ozonation/Improved photocatalytic) method were studied to treat wastewater containing azo dye of Red 40. Hybrid process had the best efficiency for dye concentration of 50 mg/L with pH of 9 and TiO2 concentration of 40 gr/m3 with light source power of 120 W and ozone injection rate of 20 mg/min. In these conditions, dye and COD were removed completely after 65 minutes and 7 hours, respectively. Based on the kinetic studies, pseudo first order model was applied for dye degradation. According to the results, immobilization of nano materials not only solved their recovery problem, but also improved the efficiency of conventional photocatalytic process. Addition of ozonation to the photocatalytic system for the purpose of having hybrid process was also resulted in an increase of the efficiency to over 30 times and production of safe products. The results have been showed the advantages of hybrid process. https://arww.razi.ac.ir/article_4228.html In this study, by modeling water temperature and some quality parameters using the CE-QUAL-W2 numerical model during different months of the year in the Talvar Dam reservoir, the thermal stratification and mixing times were determined. According to the temperature profile in thermal stratification period, epilimnion, metalimnion and hypolimnion depths were determined. Water quality of the dam reservoir was evaluated using Iran Water Quality Index for Surface Water Resources - Common Parameters (IRWQISC) and Iran Water Quality Index for Surface Water Resources - Toxic Parameters (IRWQIST). For calculation of IRWQISC, some parameters were used including Fecal Coliform, Phosphate, Nitrate, Turbidity, BOD, COD, DO, EC, pH and for calculation of IRWQIST, some parameters were used including Arsenic, Iron, Chrome and Manganese. Considering the effects of thermal stratification on water quality in different points of dam reservoir (hypolimnion, epilimnion) and at different times, a new method was used to evaluate water quality in dam reservoirs based on water quality index. In this method, water quality index was calculated in hypolimnion and epilimnion at different times. In this way, during thermal stratification period of the dam reservoir, the water quality indices were calculated separately for the hypolimnion and epilimnion. Moreover, during mixing period, these indices were calculated for the entire reservoir. Results of the present study showed that water quality of the dam reservoir lied in the relatively good and good class in terms of common parameters (59.9 ≤ IRWQISC ≤ 77), and in the medium and relatively bad class in terms of toxic parameters (30.2 ≤ IRWQIST ≤ 50.2). https://arww.razi.ac.ir/article_4236.html This study presents a sustainable approach for converting waste sheep wool into high-performance activated carbon for Cr(VI) removal from aqueous solutions. Chemical (NaOH) and steam activation routes were evaluated, and steam activation at 900 °C for 3 h in a rotary furnace produced the optimal material. The resulting carbon exhibited a high specific surface area (1807 m²/g), a pore volume of 1.002 cm³/g, and a well-developed micro-mesoporous structure. The optimized adsorbent achieved 99% removal of Cr(VI) from a 400 mg/L solution within 45 min. Physicochemical characterization (BET, SEM, XRD, Raman) and adsorption analysis (ICP-OES) confirmed the material’s suitability for adsorption processes. Equilibrium behavior was best described by the Freundlich isotherm (R² = 0.976), while the Langmuir model yielded a monolayer capacity of 147 mg/g. Kinetic data closely followed the pseudo-second-order model (R² = 0.999), suggesting adsorption dominated by electrostatic interactions and surface complexation under acidic conditions. These findings demonstrate that wool waste can be effectively valorized as a low-cost, scalable, and efficient adsorbent for Cr(VI) remediation. https://arww.razi.ac.ir/article_4254.html Urban stormwater drainage networks in rapidly growing cities often suffer from undersized infrastructure, leading to frequent flooding and high rehabilitation costs. While evolutionary algorithms have been widely applied to optimize pipe diameters and layouts, existing approaches typically employ single-objective or global search methods, neglecting local topographic constraints and real-scale validation with high-resolution data.This study proposes a novel two-stage hybrid framework integrating SWMM, GIS, Cellular Automata (CA), and Genetic Algorithm (GA) for optimal redesign of urban surface water collection networks. In Stage 1, CA performs local refinement of node burial depths using neighborhood rules to minimize excavation costs while ensuring favorable hydraulic slopes. The resulting fixed vertical layout is then passed to Stage 2, where GA globally optimizes discrete pipe diameters and routing to minimize total construction costs under penalized hydraulic constraints, with dynamic evaluation. Applied to a real-world case study in District 7 of Tabriz, Iran (112 nodes, 168 pipes, 12.3 km²), the framework incorporates high-resolution DTM (±5 cm accuracy) and field-surveyed infrastructure data. Results demonstrate elimination of flooding under a 25-year design storm and a 32% reduction in total cost compared to conventional manual design, yielding practical recommendations including channel widening, dredging depths, and prioritized interventions. By decoupling local and global optimization and leveraging detailed topographic integration, the proposed methodology advances current stormwater network optimization practices, offering improved cost-efficiency, hydraulic performance, and applicability to large-scale urban systems. https://arww.razi.ac.ir/article_4259.html This study investigates the efficiency of the photo-Fenton process in removing Congo red dye from synthetic wastewater. Considering the importance of eliminating colored pollutants from the environment, this research examines the effect of key operational parameters, including Fe2O3 concentration (10, 30, and 50 mg/L), hydrogen peroxide concentration (100, 300, and 500 mg/L), process time (30, 60, and 90 min), and initial Congo red dye concentration (10, 30, and 50 mg/L), on the percentage of dye removal in the photo-Fenton process. The experiments were conducted in a glass reactor using a UV-C lamp as the radiation source, at ambient temperature and with a stirring speed of 350 rpm. To optimize the process and examine the interaction of parameters, the Box-Behnken experimental design method was used, and 27 experiments were designed and performed randomly. Analysis of variance on the results showed that the proposed quadratic model has acceptable accuracy for predicting dye removal efficiency. Furthermore, examination of contour plots revealed that Fe2O3 concentration and initial Congo red dye concentration have the greatest impact on process efficiency. Finally, the optimal conditions for achieving the maximum percentage of dye removal from synthetic wastewater were determined. Under optimal conditions (process time of 30 min, hydrogen peroxide concentration of 100 mg/L, Fe2O3 concentration of 40.99 mg/L, and initial Congo red concentration of 30 mg/L), the maximum Congo red removal efficiency of 99.59% was achieved. https://arww.razi.ac.ir/article_4262.html Reliable multi-step-ahead forecasting of reference evapotranspiration (ETo) is critical for proactive water resource management, yet understanding the temporal memory of hydrological systems remains a challenge for black-box deep learning models. This study presents a novel, interpretable forecasting framework integrating temporal SHapley additive explanations (SHAP) with advanced recurrent neural networks to predict daily ETo up to 7 days in advance across three contrasting climatic zones in Iran; Birjand (arid), Mashhad (semi-arid), and Gorgan (humid). By benchmarking long short-term memory (LSTM), bidirectional LSTM (BiLSTM), and CNN-LSTM architectures, it is demonstrated that model complexity does not always guarantee superiority; the standard LSTM proved remarkably robust, achieving high short-term accuracy (R² > 0.93 for 1-day forecast) in arid regions. However, a distinct humid-climate penalty was observed, with forecast accuracy degrading more rapidly in Gorgan due to stochastic cloud dynamics. The application of temporal SHAP revealed climate-specific memory effects: in arid zones, wind speed exhibited a persistent influence extending back 5 days, acting as a long-term driver of evaporative demand, whereas humid regions were governed by short-term radiative pulses. Furthermore, analysis of extreme events and drought propagation showed that while the model successfully captures heatwave-driven peaks, its reliability decreases under severe evaporative stress (standardized ETo anomaly > 2). Cross-spatial generalization tests confirmed that models trained on arid data transfer effectively to humid regions (R² = 0.95), but the reverse transfer fails to capture extreme advective forcing. This study provides a transferable, physically interpretable blueprint for developing early warning systems in data-scarce regions. https://arww.razi.ac.ir/article_4285.html Despite concerted efforts to stabilize groundwater levels in arid regions through engineering interventions, aquifer depletion remains a critical challenge, often exacerbated by a disconnect between rigid top-down policies and local socio-economic realities. This study presents a forensic hydro-institutional analysis of the restoration and balancing plan in the hyper-arid Boshruyeh Plain, Iran, to evaluate the efficacy of technical controls versus economic instruments. By integrating a 27-year hydro-physical time series (1995–2023) with a tripartite stakeholder analysis (farmers, executive experts, and academic elites), the research reveals a complex paradox. Hydrological results indicate that while the implementation of smart metering post-2014 successfully induced a structural break in abstraction trends and enforced regulatory compliance, it failed to arrest the chronic annual deficit of ~62 MCM. Socio-institutional analysis exposes a significant perception gap; while academic elites emphasize participatory governance, executive experts identify technical and cultural barriers as primary causes of policy failure. However, a strategic consensus was found regarding the potential of water markets. Contrasting with common assumptions of resistance, 89% of farmers expressed willingness to participate in a regulated market, driven primarily by the need for operational flexibility and drought risk management rather than profit maximization. The study concludes that sustainable aquifer restoration requires a paradigm shift from a purely police-patrol model to a cap-and-trade system, utilizing existing metering infrastructure to facilitate inter-temporal water banking and cross-sectoral reallocation. https://arww.razi.ac.ir/article_4296.html This study explores agricultural drought variability by applying both classical and rank-based statistical methods within two distinct probabilistic frameworks, aiming to assess how distribution choice affects the interpretation of drought patterns. Monthly meteorological data from 1998 to 2022 were processed into four drought indices: SPI, aSPI, RDI, and eRDI. Effective precipitation was calculated using the United States Department of Agriculture (USDA) method and CROPWAT, and potential evapotranspiration (ET0) was determined with the FAO Penman-Monteith approach. Each index was standardized with both gamma and log-normal distributions in DrinC to evaluate the influence of distribution choice on trend detection. Trend analysis was conducted using linear regression with Pearson correlation for parametric tests and the Mann–Kendall test with Sen’s slope for non-parametric tests. Results from both methods and distributions were consistent: median Sen slopes were within ±0.03 index units per year, and Mann–Kendall Z scores ranged from −0.82 to 0.63, indicating no significant monotonic change. Regression slopes supported this, remaining below 0.03 with p-values above 0.25. The close agreement between parametric and non-parametric results, and between gamma and log-normal distributions, shows that model selection does not bias drought trend analysis. This multi-index, dual-distribution framework provides a robust and transferable methodology for drought monitoring, particularly in data-scarce and semi-arid regions worldwide. https://arww.razi.ac.ir/article_4337.html Optimal efficiency of dam reservoirs is considered as one of the important problems in water resources management. Evolution algorithms have been presented as an intelligent technique to establish a suitable trade-off between reservoir of water resources and their release rates. In this study, a new modified approach, called “Learning automata-based differential evolution algorithm (LADE)”, has been proposed for modeling a single reservoir system in Iran with the aim of evaluating development efforts to optimize allocation of water resources. To evaluate the efficiency of LADE, first, a set of mathematical benchmark functions has been tested successfully, and then, LADE has been applied to the problem of optimization of the reservoir allocation of Golestan Dam (Iran). In addition, different versions of LADE have been offered which only vary in the type of mutation strategy to explore the search space. Moreover, the best version of LADE (LADE/curr2rand) has been compared with some of state-of-the-art algorithms, including artificial bee colony (ABC) algorithm, differential evolution (DE), imperialist competitive algorithm (ICA), genetic algorithm (GA), and particle swarm optimization (PSO). The best of numerical experimental results regarding the cases of mean and standard deviation (SD) of errors value, as well as the average runtime were associated with LADE/curr2rand. Furthermore, based on several tests including the evaluation of reliability and vulnerability indexes, release values relative to the total demand, the difference between release and demand values in an annual average, LADE/curr2rand yielded the highest performance compared to other algorithms. https://arww.razi.ac.ir/article_4338.html Reverse osmosis (RO) membrane fouling poses a significant challenge to sustainable water treatment operations, particularly in industrial applications. This study investigates the strategic synergy of an integrated ozonation-ultrafiltration (O₃-UF) pretreatment system utilizing a custom-fabricated ceramic membrane for effective fouling control and RO protection. The alumina-based membrane, characterized through FESEM and FTIR analysis, exhibited a homogeneous microstructure with a narrow pore size distribution centered at approximately 450 nm. The hybrid system demonstrated effective performance when treating complex surface water from the Maroon River, achieving a substantial reduction in the Silt Density Index (SDI) from 0.253 to 0, which corresponds to a significant decrease in colloidal fouling potential. Concurrently, turbidity was reduced by 71% while maintaining stable TDS levels. The membrane exhibited excellent hydraulic performance with an initial water flux of 1100 LMH. The integration of ozonation transforms the nature of the fouling layer from a compact, irreversible one to a loose, reversible one. The process also provided complete disinfection, removing total coliforms and E. coli. The results establish this synergistic pretreatment as a superior and robust solution for protecting RO membranes, ensuring operational stability and significantly reducing fouling-related challenges. https://arww.razi.ac.ir/article_4340.html Accurate forecasting of urban water demand is essential for effective water resources management, especially in arid and water-stressed regions. This study evaluates the performance of Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) models for forecasting monthly urban potable water demand in the Sistan region of Iran using data from April 2006 to March 2021. Two forecasting approaches are examined: a univariate approach based only on past water demand and a multivariate approach incorporating selected climatic and socioeconomic variables. A one-step-ahead monthly forecasting strategy is applied, with the dataset divided chronologically into training and testing subsets. The deep learning models are compared with two benchmark methods, Naïve and Seasonal Naïve, using MAE, RMSE, MAPE, and Pearson’s correlation coefficient. The results show that LSTM provides more stable predictions and higher correlation with observed demand than RNN. However, the simple benchmark models produce lower forecast errors overall, with the Naïve model achieving the best performance. Adding climatic and socioeconomic variables slightly improves correlation in some cases but does not consistently reduce errors. Overall, the findings suggest that urban water demand in the study area is strongly persistent and seasonal, indicating that simple forecasting methods can outperform more complex deep learning models under data-limited conditions. https://arww.razi.ac.ir/article_4341.html Concrete gravity dams must maintain adequate resistance against hydraulic and seismic loading to ensure structural safety and long-term operational performance. Reliable assessment of sliding, overturning, uplift pressure, and stress concentration is therefore essential, particularly under extreme flood and earthquake conditions. In this study, the stability behavior of the Bratsk concrete gravity dam was investigated using the CADAM computational platform under normal operation, flood loading, and pseudo-dynamic seismic conditions. The methodology involved two-dimensional static and pseudo-dynamic analyses based on rigid-body equilibrium and modal force combination principles. Hydrostatic, hydrodynamic, uplift, sediment, self-weight, and seismic inertia forces were incorporated into the numerical model, and safety factors were evaluated at multiple joints along the dam–foundation interface. In addition, a normalized sensitivity index (NSI) framework was developed and integrated with the CADAM outputs to quantify the relative influence of governing mechanical and hydraulic parameters, including foundation friction, uplift efficiency, and hydrodynamic shear forces, on the stability response of individual joints. The results showed that the dam remained stable under normal operating conditions, whereas flood loading generated the most critical response, with the minimum Sliding Safety Factor (SSF) decreasing to 0.856 at Joint 9 and the minimum Overturning Safety Factor (OSF) reaching 1.423 at Joint 10. Pseudo-dynamic analyses further indicated that inertial forces became concentrated near the dam base, where combined modal forces exceeded −16,000 kN. The NSI-based sensitivity analysis reveals that frictional resistance (NSI = +1.00) and hydrodynamic shear forces (NSI = –0.85) at Joint 9, as well as uplift pressure effects (NSI = –0.72) at Joint 10, are the dominant parameters affecting stability.. The proposed NSI-enhanced framework improves the interpretation of localized instability mechanisms and supports more effective prioritization of reinforcement and foundation treatment strategies in concrete gravity dams. https://arww.razi.ac.ir/article_4343.html Accurate precipitation estimation in hyper-arid regions is fundamentally challenged by sparse observational networks and complex atmospheric dynamics. This study evaluates and corrects the errors of IMERG (Final V07) and GSMaP satellite precipitation products using 18 years (2005–2023) of daily synoptic data from Birjand, representing the hyper-arid climate of eastern Iran. Baseline evaluations indicated that GSMaP outperformed IMERG in continuous metrics (RMSE = 3.25 vs. 4.40 mm/day); however, both exhibited systematic underestimation, primarily driven by sub-cloud evaporation (the Virga effect). Categorically, IMERG demonstrated higher detection sensitivity (POD = 0.763), whereas GSMaP more effectively minimized false alarms. Bivariate density analysis revealed a notable finding: absolute estimation errors are significantly driven by surface thermodynamic conditions (maximum temperature and relative humidity, P-value < 0.01), while the dynamic impact of wind speed was statistically insignificant. Finally, applying a multiple linear regression (MLR) bias correction framework incorporating these meteorological covariates successfully reduced IMERG's RMSE by 14.1%. The findings demonstrate that integrating surface thermodynamic data with satellite retrieval algorithms via regression models substantially mitigates precipitation uncertainties in data-scarce hyper-arid basins.