Applied Water Science最新文献

This research aimed to ascertain the Manning roughness coefficient (n) and explore the impact of various factors on it across different phases and irrigation events. The Manning’s n for furrow irrigation was determined in the advance, storage, and whole irrigation phases utilizing the SIPAR_ID model, Manning equation, and WinSRFR software, respectively. Parameters affecting the Manning’ n were identified through Pearson and Kendall tests. The study involved measuring the Manning’s n under six distinct inflow rates, classified as low and high flows. Three irrigation events (first to third), advance and storage phases, two irrigation intervals, and two soil textures (Clay loam and Silty clay loam) were considered. Results indicated that the Manning’s n ranged from 0.017 to 0.636, 0.015 to 0.317, and 0.015 to 0.34 in the advance, storage, and whole irrigation phases during the first to third irrigation events, with mean values of 0.083, 0.054, and 0.055, respectively. Higher roughness coefficients were observed in the advance phase. Additionally, findings suggested that if the advance phase is short relative to the total irrigation time, the Manning’s n from the advance phase can be applied to the whole irrigation event without separate consideration for storage phase roughness. Pearson and Kendall statistical tests revealed that the Manning roughness coefficient during the entire irrigation event was strongly correlated with advance time (r = 0.65, p < 0.01) and moderately correlated with inflow and outflow rates, as well as initial soil moisture and cross-sectional flow area. A weak correlation was observed between the roughness coefficient and the furrow slope (r = 0.238). During the storage phase, advance time had the strongest positive correlation with roughness, while inflow rate had a weak negative correlation (r = −0.31).

The Yangtze River Delta (YRD) occupies 2.1% of China's territory but accounts for 1/4 of its GDP. Boosting efficiency of industrial water resources in YRD will drastically decrease water pollution and resource constraints. The current paper employed Network Super-SBM and the Global Malmquist-Luenberger index to evaluate industrial water use efficiency and wastewater treatment efficiency of YRD’ cities. Furthermore, digital inclusive finance and green innovation are introduced to investigate the mechanisms underlying their influence on the overall industrial water resources efficiency. The empirical findings posts that: (1) there is still room to improve the overall efficiency, especially the water treatment efficiency; (2) the MI value of each stages in most samples is greater than 1, indicating that the water treatment efficiency and water use efficiency are improving. It is mainly driven by the improvement of the efficiency of the management; (3) there are substantial differences in water resource efficiency among metropolitan areas, with Nanjing-metropolitan areas and Hefei-metropolitan areas having higher water use efficiency and water treatment efficiency for both stages, while Hangzhou-metropolitan areas and Shanghai-metropolitan areas have lower water treatment efficiency. As shown by the Kernel density Estimation, the degree of efficiency dispersion within same metropolitan area is reducing; and (4) digital inclusive finance will boost overall efficiency and water treatment efficiency, with green innovation as a mediating factor. The findings herein offer compelling evidence that financial development increases the effectiveness of water resources, introduce fresh perspectives for the government to put forward water-related policies, and provide ideas for high-quality economy.

Assessing water quality is essential for acquiring a better understanding of the importance of water in human society. In this study, the quality of groundwater resources in Jiroft city, Iran, using artificial intelligence methods to estimate the groundwater quality index (GWQI) was evaluated. The analysis of hydrochemical parameters, including arsenic (As), fluoride (F), nitrate (NO₃), and nitrite (NO₂), in 408 samples revealed that concentrations of F, NO₃, and NO₂ were below the WHO standard threshold, but levels of As exceeded the permissible value. The random forest model with the highest accuracy (R² = 0.986) was the best prediction model, while logistic regression (R² = 0.98), decision tree (R² = 0.979), K-nearest neighbor (R² = 0.968), artificial neural network (R² = 0.955), and support vector machine (R² = 0.928) predicted GWQI with lower accuracy. The non-carcinogenic risk assessment revealed that children had the highest hazard quotient for oral and dermal intake, with values ranging from 0.47 to 13.53 for oral intake and 0.001 to 0.05 for dermal intake. The excess lifetime cancer risk of arsenic for children, adult females, and males was found to be from 2.5 × 10^–4 to 7.2 × 10^–3, 1.2 × 10^–4 to 3.6 × 10^–3, and 4.3 × 10^–5 to 1.2 × 10^–3, respectively. This study suggests that any effort to reduce the arsenic levels in the Jiroft population should take into account the health hazards associated with exposure to arsenic through drinking water.

Desalination of water is a crucial step in the process of obtaining potable water. One of the main challenges for the researchers is its efficient application and affordable preparation. It was planned to prepare the flat sheet membranes using cellulose acetate as a base polymer, and polyvinyl alcohol (PVA) as an additive with dosing of (0.1, 0.3, 0.5, and 0.7 wt%) from zirconium oxide (ZrO₂) nanoparticle. SEM, TEM, and XRD analyses were used to characterize the generated ZrO₂ nanoparticle in order to confirm its nano-size and crystal structure. The surface morphologies and existence of the dense layer, which is the typical property of the RO membrane capable of salt separation, were identified on the manufactured RO membranes by SEM. Membranes prepared by embedding 0.5 wt%ZrO₂ with PVA/CA proved efficient as RO membranes using 2000 ppm NaCl and exhibited high salt rejection of 97% and water permeability of 12.5 LMH. Also, there is a decrease in the NaCl removal tendency was observed with the excessive dosages of ZrO₂ with 0.7 wt%, which was due to the concentration polarization, which blocks the pores on the surfaces of the membranes. The antifouling behavior of the prepared membranes was tested using bovine serum albumin (BSA), the results indicate the low irreversible resistance, total fouling resistance, and high flux recovery ratio compared to the neat membrane. The prepared membranes have a stable salt rejection and water productivity even after demonstrating with chlorine (25–100 mg l⁻¹ of NaOCl for 120 min).

This study evaluates sustainable water management strategies using TOPSIS and Fuzzy TOPSIS (FTOPSIS) to address global water scarcity by comparing rainwater harvesting, water recycling, and desalination across five criteria: water efficiency, cost-effectiveness, environmental impact, social equity, and technological feasibility. The results show Rainwater Harvesting as the most balanced option with a relative closeness value of ({C}_{i}^{+})=0.640, excelling in social equity and environmental sustainability. Water Recycling ranks closely behind (({C}_{i}^{+})=0.608), highlighting its adaptability and technological feasibility, while Desalination, though highly efficient, is hindered by lower cost-effectiveness (({C}_{i}^{+})=0.578). By integrating TOPSIS and FTOPSIS, the study addresses uncertainties and subjective criteria, providing a robust multi-dimensional assessment framework for resource management. This methodology aids decision-makers in identifying strategies that align with sustainable development goals and adapt to regional priorities. Future work can expand this framework to include stakeholder engagement and policy factors, enhancing water management strategies for resilient, long-term solutions.

Chromium contamination of water is a severe environmental problem due to the potential carcinogenicity of Cr(VI). In this work, magnetic cork powder was used as a porous material, and its removal efficiency for Cr(VI) was compared to that of natural cork powder through two mechanisms: adsorption and reduction. Adsorption isotherms and adsorption kinetics were utilized to calculate the reaction rate using a pseudo-first-order model, pseudo-second-order model, and intraparticle diffusion. After adsorption, the powder was characterized by scanning electronic microscopy with energy-dispersive X-ray analysis (EDAX), Fourier transform infrared spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy (XPS). EDAX allowed to see a mapping distribution of Fe and Cr, and XPS revealed the presence of Cr₂O₃ and Cr(OH)₃, confirming the reduction of Cr(VI) to Cr(III). All the Cr was efficiently reduced and adsorbed onto the surface of the magnetic cork at 20 °C, 27 °C, and 50 °C within 120 min with stirring. The relative efficiencies to the total milligrams of added adsorbent were 98, 98.6, and 99.7 mg, respectively. This is comparable to the adsorption on the natural cork surface at the same temperatures, which measured 97.8, 98.5, and 99.6 mg, respectively, of 100 mg/L Cr(VI) solution. Furthermore, the magnetic cork offers the advantage of being removable by applying a magnetic field.

The aims of this study are capability assessment of the SWAT model and SWAT-CUP software in hydrological simulation and evaluation of uncertainty of SWAT model in estimating runoff. In the modeling process, the basin was divided into 12 sub-basins and 294 hydrological units (HRUs). Model calibration and uncertainty analysis were performed using the sequential uncertainty fitting (SUFI2) algorithm for 2000–2006 and 2007–2010, respectively. Based on the sensitivity analysis results, the parameters are the USLE_P soil protection factor, wet soil density (SOL_BD), and CN among the most important parameters in determining the amount of output runoff. Among these factors, SCS-CN was recognized as the most sensitive parameter. Based on the results, the coefficients R², bR², and Nash–Sutcliffe index (NS) were 0.75, 0.59, and 0.67 for calibration period and 0.46, 0.24, and 0.42 for validation period. The results of the model showed the model performance is weak in the stage of calibration. This is due to the lack of accuracy and precision in the statistics available in the region, the lack of statistics on the amount of water collected from the upstream gardens of the area, as well as the lack of statistics on the existing springs. The model is therefore recommended for applications in arid and semiarid catchments within Iran with similar data. Due to the limited availability of hydrological data in Iran, this study has not assessed and compared the uncertainty related to the SWAT model of future runoff.

Water pipes face significant aging and degradation problems due to several pipe-related, soil-related, operational, and environmental factors. Hence, the paramount objective of this research paper is to prioritize the criticality of the factors affecting the deterioration of water pipes in Hong Kong. The framework of the developed model is envisioned based on two main modules, namely weight computation and weight aggregation. The first module incorporates identifying and categorizing water deterioration factors. Then, the relative importance priorities of water deterioration factors are scrutinized using seven weight computation methods. These methods encompass analytical hierarchy process (AHP), Monte Carlo AHP, fuzzy AHP, magnitude-based fuzzy AHP, total difference-based fuzzy AHP, spherical fuzzy AHP and Pythagorean fuzzy AHP. In this regard, fuzzy-based and Monte Carlo-based methods are leveraged to circumvent the critical shortcomings of classical AHP. The performances of weight computation methods are analyzed using statistical evaluation indicators of satisfactory index (SAT) and distance between weights (WD). The second module is a hybrid meta-heuristic-based game theory model designated for compiling the importance weights of deterioration factors obtained from the first module. In this context, a set of widely acclaimed meta-heuristics are exploited and examined for optimizing the significance of deterioration factors. Analytical results exemplified that soil-related factors implicate the deterioration process more than pipe-related, operational-related, and environmental-related factors. It was also inferred that water pressure (6.64%) is the most significant factor influencing water pipe deterioration followed by internal corrosion and protection method (6.11%), and then soil corrosivity (6.05%). On the other hand, length (1.93%), rain deficit (1.97%), and street block length (2.33%) constitute the least influencers on water pipe deterioration. Results also demonstrated that spherical FAHP outperformed other variants of AHP accomplishing SAT and WD of 0.065 and 0.057, respectively. Comparative analysis revealed that particle swarm optimization-based game theory is a better mechanism than the remainder of meta-heuristic-based game theory models in obtaining a more accurate compromised-based weighting vector to the experts’ judgments. It is envisaged that this research can assist the water supplies department in identifying, assessing, and prioritizing the impairment causes of water pipelines in Hong Kong. It can also aid in establishing more accurate deterioration models and more cost-effective maintenance intervention programs.

One method for estimating floods in areas lacking statistical data is the use of regional frequency analysis based on machine learning. In this study, statistical and clustering-based approaches were evaluated for flood estimation in the Karkheh watershed. The hydrological homogeneity of the obtained zones was then assessed using linear moments and heterogeneity adjustment methods proposed by Hosking and Wallis. Then, the ZDIST statistic was used to calculate the three-parameter distributions for stations within each hydrologically homogeneous cluster. These parameters were computed using linear moments, and floods with different return periods at each station were estimated using regional relationships. The results indicated the creation of two clusters in this area, with five stations in cluster one and 11 stations in cluster two. The statistical homogeneity values for clusters one and two were calculated as 0.33 and 0.17, respectively, indicating the homogeneity of each region. Generalized Pearson type III and generalized extreme value distributions were selected as the best regional distributions for clusters 1 and 2, respectively. The results also showed that floods could be estimated for return periods of 2, 5, 25 years, and more. The highest estimated flood is predicted at the Jelugir-e Majin station, where the flood with a 2-year return period reaches 1034 m³ s⁻¹. This increases to 5360 m³ s⁻¹ for a 100-year return period. The approach presented in this study is recommended for similar regions lacking complete information.

Published results on rainwater management systems revealed a lack of holistic science-based design principles. A new approach to rainwater management is proposed. Its necessity and feasibility are discussed. It is demonstrated that quantitatively harvesting rainfall and infiltrating a fraction should be mandatory. Thus, the primary site-specific parameter is the intensity of rainfall. Clearly, rainwater should be harvested and used everywhere as a valuable resource. Under arid semi-arid conditions large tanks maximize water storage for the long dry season while under humid conditions the same helps to minimize the frequency of emptying to avoid flooding. The new approach separates rainwater (and stormwater) from sewage and has the potential to maintain the natural hydrological cycle in urban areas despite urbanization. In already crowded slums, rainwater harvesting (RWH) can also be used to restore the hydrological cycle. The new approach advocates for decentralized RWH infrastructures to harvest, infiltrate, and store rainwater in individual residences, while piping overflows to semi-centralized cluster-scale tanks. Rooting integrated water resource management on RWH appears to be the missing puzzle in: (i) restoring the natural hydrological cycle where it has been disturbed (landscape restoration), (ii) avoiding flooding, and (i) mitigating soil erosion. This is essential for sustainable development.