Journal Description
Water
Water
is a peer-reviewed, open access journal on water science and technology, including the ecology and management of water resources, and is published semimonthly online by MDPI. Water collaborates with the International Conference on Flood Management (ICFM) and Stockholm International Water Institute (SIWI). In addition, the American Institute of Hydrology (AIH), The Polish Limnological Society (PLS) and Japanese Society of Physical Hydrology (JSPH) are affiliated with Water and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, GEOBASE, GeoRef, PubAg, AGRIS, CAPlus / SciFinder, Inspec, and other databases.
- Journal Rank: JCR - Q2 (Water Resources) / CiteScore - Q1 (Water Science and Technology)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.5 days after submission; acceptance to publication is undertaken in 2.9 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Companion journals for Water include: GeoHazards and Hydrobiology.
Impact Factor:
3.4 (2022);
5-Year Impact Factor:
3.5 (2022)
Latest Articles
Effects of Three Antibiotics on Nitrogen-Cycling Bacteria in Sediment of Aquaculture Water
Water 2024, 16(9), 1256; https://doi.org/10.3390/w16091256 (registering DOI) - 28 Apr 2024
Abstract
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Antibiotics are commonly used to prevent and control aquaculture diseases. However, long-term overuse of antibiotics not only leaves residues but also leads to changes in the nitrogen cycle in water, which threatens the survival of aquaculture organisms. The current results showed that sulfamethoxazole
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Antibiotics are commonly used to prevent and control aquaculture diseases. However, long-term overuse of antibiotics not only leaves residues but also leads to changes in the nitrogen cycle in water, which threatens the survival of aquaculture organisms. The current results showed that sulfamethoxazole had no significant effect on the nitrogen cycle process in the actual aquaculture concentration. The inhibitory effect of 1.05 mg/L norfloxacin on ammonia-oxidizing bacteria was significantly greater than that on ammonia-oxidizing archaea, and the gene abundance of AOB amoA on the 14th day increased by 2.48 times compared with the 7th day. Under the influence of 3.9 mg/L oxytetracycline, the gene abundance of AOB amoA decreased significantly, while the number of AOA amoA genes increased, suggesting that there may be functional redundancy between AOA and AOB. At the genus level in the norfloxacin group, the relative abundance of Sva0485 increased by 14.0% on the 7th day compared with the control group but decreased 12.77% in the addition group. The relative abundance of Firmicutes, another dominant species in the oxytetracycline group, was 25.9%. This study shows that the addition of antibiotics may have a negative effect on the nitrogen-cycling microorganisms in aquaculture water.
Full article
Open AccessArticle
Vine Copula-Based Multivariate Distribution of Rainfall Intensity, Wind Speed, and Wind Direction for Optimizing Qatari Meteorological Stations
by
Hassan Qasem, Niels-Erik Joergensen, Ataur Rahman, Husam Abdullah Samman, Sharouq Al Malki and Abdulrahman Saleh Al Ansari
Water 2024, 16(9), 1257; https://doi.org/10.3390/w16091257 (registering DOI) - 27 Apr 2024
Abstract
This study employs copula functions to establish the dependency structure of the joint distribution among rainfall intensity, wind speed, and wind direction in Qatar. Based on a Vine Copula, the trivariate distribution between rainfall intensity, wind speed, and wind direction is found to
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This study employs copula functions to establish the dependency structure of the joint distribution among rainfall intensity, wind speed, and wind direction in Qatar. Based on a Vine Copula, the trivariate distribution between rainfall intensity, wind speed, and wind direction is found to exhibit a root-mean-square error (RMSE) of 0.0072 on the observed vs. modeled cumulative probabilities using ranked normalized observations. It is also found that the winter Shamal winds are most pronounced during rainfall. However, a secondary component of easterly winds known as the Kaus winds is also found to exert an important influence. This wind pattern is observable during rainfall at all the selected stations, albeit with minor variations. It is also found that rainfall stations where the rainfall is obstructed in any way from northwest to north and from east to southeast significantly influence the rainfall measurements. Specific rain gauges in Qatar are found to be situated in disrupted surroundings, such as meteorological stations close to passing traffic, where road spray could infiltrate the rain gauge funnel, impacting the accuracy of rainfall measurements. The study results necessitated the relocation of approximately half of these roadside gauges to mitigate wind-induced biases from road spray. An evaluation of operations is recommended for approximately 80 meteorological stations responsible for measuring rainfall in Qatar. The methodology devised in this study holds potential for application to other Middle Eastern countries and regions with similar climates.
Full article
(This article belongs to the Section Water and Climate Change)
Open AccessArticle
Flexural-Gravity Waves in a Channel with a Compressed Ice Cover
by
Evgeniy Batyaev and Tatiana Khabakhpasheva
Water 2024, 16(9), 1255; https://doi.org/10.3390/w16091255 (registering DOI) - 27 Apr 2024
Abstract
The characteristics of linear hydroelastic waves propagating in a channel covered with compressed ice are investigated. The channel has a rectangular cross-section and is assumed to be infinite in length. The fluid in the channel is non-viscous and incompressible; its flow is potential.
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The characteristics of linear hydroelastic waves propagating in a channel covered with compressed ice are investigated. The channel has a rectangular cross-section and is assumed to be infinite in length. The fluid in the channel is non-viscous and incompressible; its flow is potential. The ice cover is modelled by an elastic plate of constant thickness frozen to the channel walls. Principal attention is paid to the investigation of the influence of ice compression on the parameters of hydroelastic waves. The problem is solved in a coupled hydroelastic formulation. The profiles of propagating waves in the channel are sought in the form of series on the normal modes of a dry plate. The modes are defined analytically through trigonometric and hyperbolic functions. It is shown that compression in the longitudinal and transverse directions has different effects on the dispersion relations of these hydroelastic waves, their shape and phase, as well as on the critical velocities and strains distribution.
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(This article belongs to the Special Issue Hydraulic and Transient Performances of Pumped-Storage Units)
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Open AccessFeature PaperArticle
Definition of Exergetic Efficiency in the Main and Emerging Thermal Desalination Technologies: A Proposal
by
Nenna Arakcheeva El Kori, Ana M. Blanco-Marigorta and Noemi Melián Martel
Water 2024, 16(9), 1254; https://doi.org/10.3390/w16091254 (registering DOI) - 27 Apr 2024
Abstract
Increasing attention is being given to reduce the specific energy consumption in desalination processes, which translates into greater use of exergy analysis. An exergetic analysis provides relevant information related to the influence of the efficiency of a single component in the global plant
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Increasing attention is being given to reduce the specific energy consumption in desalination processes, which translates into greater use of exergy analysis. An exergetic analysis provides relevant information related to the influence of the efficiency of a single component in the global plant performance and in the exergy cost of the product. Therefore, an exergy analysis identifies the main improvement potentials in a productive thermodynamic process. Related to desalination technologies, many previous papers deal with the calculation of the parameters involved in the exergy analysis, the exergetic efficiency of different processes, plants, and technologies among them. However, different approaches for formulating the exergetic efficiency have been suggested in the literature, often without sufficient understanding and consistency. In this work, these formulations, applied to the main desalination components and processes, are compared and critically reviewed. Two definitions of exergy efficiency are applied to the desalination components of the three main thermal desalination processes (multieffect distillation–thermal vapour compression, multistage flash distillation, and direct-contact membrane distillation). The results obtained for the exergy efficiency of the MED-TVC, MSF, and DCMD processes for the input–output approach are 21.35%, 17.08%, and 1.28%, respectively, compared to the consumed–produced approach that presented 3.1%, 1.58%, and 0.37%, respectively. The consumed–produced approach seems to better fit the thermodynamic behaviour of thermal desalination systems.
Full article
(This article belongs to the Special Issue Advanced Desalination Technologies for Water Treatment)
Open AccessArticle
Multi-Objective Design of a Horizontal Flow Subsurface Wetland
by
Jhonatan Mendez-Valencia, Carlos Sánchez-López and Eneida Reyes-Pérez
Water 2024, 16(9), 1253; https://doi.org/10.3390/w16091253 (registering DOI) - 27 Apr 2024
Abstract
An artificial wetland is used to treat gray, waste, storm or industrial water. This is an engineering system that uses natural functions of vegetation, soil and organisms to provide secondary treatment to gray water. In the physical design of each artificial wetland, there
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An artificial wetland is used to treat gray, waste, storm or industrial water. This is an engineering system that uses natural functions of vegetation, soil and organisms to provide secondary treatment to gray water. In the physical design of each artificial wetland, there are various action factors that must meet certain characteristics so that the level of gray-water pollution is reduced. In this sense, several design methodologies have been developed and reported in the literature, but some are customized designs and often do not meet the required decontamination objectives. This challenge increases as the complexity of the task in its structure also increases. Particularly in this work, a multi-objective evolutionary algorithm is used to optimize the physical design of a horizontal flow subsurface wetland (HFSW) for gray-water treatment. The study aims to achieve two objectives: first, to minimize the physical volume, and second, to maximize the contaminant removal efficiency. The defined objective functions depend on six design variables called hydraulic retention time, width, length, water depth inside the wetland, substrate depth and slope. Three constraint functions are also defined: removal efficiency greater than 95%, physical volume below 500 m and compliance with a length–width ratio is 3:1, varying the population size and number of generations equal to 200, 400, and 600. The set of solutions according to the number of generations as well as the Pareto front corresponds to the best solution that complies with the constraints of the problem of oversizing the HFSW, and the Pareto front shows the interaction between the objectives and their behavior, reflecting the problem’s nature as minimization–maximization.
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(This article belongs to the Section Water Quality and Contamination)
Open AccessArticle
Elevational Patterns of Forest Evapotranspiration and Its Sensitivity to Climatic Variation in Dryland Mountains
by
Hongyu Li, Xiaohuang Liu, Wenbo Zhang, Haoyang Zhu, Xiaofeng Zhao, Jiufen Liu, Xinping Luo, Ran Wang, Honghui Zhao and Chao Wang
Water 2024, 16(9), 1252; https://doi.org/10.3390/w16091252 (registering DOI) - 27 Apr 2024
Abstract
Elevational climatic heterogeneity, complex terrains, and varying subsurface properties affect the sensitivity of evapotranspiration (ET) in dryland mountain forests to hydrometeorological changes. However, the elevational distribution of ET sensitivity and its major influencing factors remain poorly understood. This study focused on the mid-altitude
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Elevational climatic heterogeneity, complex terrains, and varying subsurface properties affect the sensitivity of evapotranspiration (ET) in dryland mountain forests to hydrometeorological changes. However, the elevational distribution of ET sensitivity and its major influencing factors remain poorly understood. This study focused on the mid-altitude zone (1000–3500 m) forests in the Chinese Western Tianshan Mountains and assessed ET sensitivity to multiple climate variables, including precipitation (P) and potential evapotranspiration (PET), from 2000 to 2020. To evaluate the multi-year mean and trends in ET sensitivity, multi-source remote sensing data and regional survey data were analyzed using Spearman’s correlation coefficient, the sliding window method, and Kendall’s test. Furthermore, the relative importance of environmental variables (topography, geology, soil, and vegetation) was investigated. P and PET showed no significant trends, while ET exhibited a significant increasing trend (5.81 mm/yr, p < 0.01), particularly at elevations above 2000 m. Most forests (93.5%) showed a positive sensitivity of ET to P, and 70.0% showed a positive sensitivity of ET to PET, mainly at elevations of 1500–2500 m. Additionally, the trend in ET sensitivity to P decreased with an increasing elevation, with 64.5% showing a positive trend. Meanwhile, the trend in ET sensitivity to PET increased with elevation, with 88.1% showing a positive trend. Notably, 53.2% of the forests showed increasing ET sensitivity trends to both P and PET, primarily at elevations of 2000–3000 m with a mean normalized difference vegetation index (NDVI) of 0.56. Geological factors, particularly the hydrological properties of weathered bedrock, contributed the most (~47%) to mean sensitivity. However, geological and vegetative factors, including the NDVI and root zone water availability, were the main contributors (35% each) to the sensitivity. This study highlights the elevation-dependent sensitivity of dryland mountain forests to hydrothermal changes, with higher-elevation forests (>2000 m) being more sensitive to global warming.
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(This article belongs to the Topic Hydrology and Water Resources Management)
Open AccessArticle
Assessment of Leachate Generated by Sargassum spp. in the Mexican Caribe: Part 1 Spatial Variations
by
Rosa Maria Leal-Bautista, Juan Carlos Rodriguez-Garcia, Gilberto Acosta-González, Rubi Chablé-Villacis, Raul Tapia-Tussell, Jose Epigmenio Bautista-García, Edgar Olguìn-Maciel, Liliana Alzate-Gaviria and Gloria González-López
Water 2024, 16(9), 1251; https://doi.org/10.3390/w16091251 (registering DOI) - 27 Apr 2024
Abstract
In this study, we evaluate the degradation by Sargassum spp. as a consortium in 2020 and 2021, and by species during 2021, collected at different distances from a coastline and in land deposits. The year 2021 had the largest leachate volume and the
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In this study, we evaluate the degradation by Sargassum spp. as a consortium in 2020 and 2021, and by species during 2021, collected at different distances from a coastline and in land deposits. The year 2021 had the largest leachate volume and the offshore site with the highest volume (60 mL/day) among five sites of collection. In relation to species’ leachate generation, S. fluitans reached 47.67 mL/day as its peak, which is earlier than S. natans (41.67 mL/day 14 days after S. fluitans). pH shows alkaline behavior and EC reflects the saline condition in the leachate, the consortium and species reaching values of pH 7.5 to 8.3 and 80 to 150 mS/cm of EC; the results do not show significant differences among sites, or between species. Despite a BOD/COD ratio of less than 0.1, the degradation process occurs as evidenced by the presence of leachate. The results confirm the existence of a variability in leachate production and the composition of Sargassum under the influence of factors such as the periodicity, site of collection, and proportions of species. Thus, even though these results emphasize leachate generation, knowing the limitations of leachate generation is crucial information for decision making on Sargassum storage and environmental management.
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(This article belongs to the Special Issue Marine Ecological Monitoring, Assessment and Protection)
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Open AccessArticle
Investigating the Impact of Large Lakes on Local Precipitation: Case Study of Lake Urmia, Iran
by
Hossein Mousavi, Amir Hossein Dehghanipour, Carla S.S. Ferreira and Zahra Kalantari
Water 2024, 16(9), 1250; https://doi.org/10.3390/w16091250 (registering DOI) - 27 Apr 2024
Abstract
Large lakes face considerable challenges due to human activities and climate change, impacting local weather conditions and ecosystem sustainability. Lake Urmia, Iran’s largest lake and the world’s second-largest saltwater lake, has undergone a substantial reduction in water levels, primarily due to drought, climate
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Large lakes face considerable challenges due to human activities and climate change, impacting local weather conditions and ecosystem sustainability. Lake Urmia, Iran’s largest lake and the world’s second-largest saltwater lake, has undergone a substantial reduction in water levels, primarily due to drought, climate change, and excessive irrigation. This study focuses on the potential repercussions on local climate conditions, particularly investigating the impact of moisture sources, evaporation from lake surfaces, and evapotranspiration from agricultural activities, on local convection rainfall. The prevailing westerly winds in the basin suggest a hypothesis that this moisture is transported eastward within the basin, potentially leading to local precipitation as it ascends to higher altitudes near the eastern basin border. To validate this hypothesis, climate data from 1986 to 2017 from the Sarab meteorological station (east of the lake basin, influenced by local precipitation) and Saqez meteorological station (south of the basin, unaffected by local precipitation) were analyzed. The impact of lake water level reduction was assessed by categorizing data into periods of normal lake conditions (1986–1995) and water level reduction (1996–2017). Additionally, the MSWEP global precipitation product was used to examine the precipitation distribution in the entire basin over the entire period and sub-periods. The findings indicate Lake Urmia’s significant influence on convective rainfall in the eastern basin, especially during the summer. Despite decreasing lake levels from 1996 to 2017, convective rainfall in the eastern basin increased during the summer, suggesting intensified agricultural irrigation, particularly in hot seasons.
Full article
(This article belongs to the Section Hydrology)
Open AccessArticle
The Treatment of Antibiotic Excess Sludge via Catalytic Wet Oxidation with Cu-Ce/γ-Al2O3 and the Production of a Carbon Source
by
Shangye Chu, Hai Lin and Xu Zeng
Water 2024, 16(9), 1249; https://doi.org/10.3390/w16091249 (registering DOI) - 27 Apr 2024
Abstract
In the present study, the effectiveness of catalytic wet oxidation triggered by using Cu-Ce/γ-Al2O3 to degrade antibiotic excess sludge was investigated, during which some small molecule carboxylic acids were produced, which are valuable in biological wastewater treatment as an organic
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In the present study, the effectiveness of catalytic wet oxidation triggered by using Cu-Ce/γ-Al2O3 to degrade antibiotic excess sludge was investigated, during which some small molecule carboxylic acids were produced, which are valuable in biological wastewater treatment as an organic carbon source. The influence of reaction parameters on the degradation efficiency was explored through single-factor and orthogonal experiments, including catalyst amount, reaction temperature and time, and oxygen supply amount. The results illustrated that the treatment system can achieve 81.2% COD and 93.8% VSS removal rates under optimized reaction conditions. Carboxylic acids produced after the sludge degradation mainly included acetic acid, propanoic acid, etc. The results of wastewater biological treatment experiments exhibited that the degraded solution after catalytic wet oxidation has potential to be used as a carbon source to meet the demand of biological treatment, which helps the removal of COD and TN. This work confirms the effectiveness of catalyst for enhancing antibiotic excess sludge treatment, which provided a new idea for the rational disposal of antibiotic excess sludge.
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(This article belongs to the Special Issue New Insights in Catalytic Oxidation Processes for Water Treatment)
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Open AccessArticle
Forecasting the River Water Discharge by Artificial Intelligence Methods
by
Alina Bărbulescu and Liu Zhen
Water 2024, 16(9), 1248; https://doi.org/10.3390/w16091248 (registering DOI) - 26 Apr 2024
Abstract
The management of water resources must be based on accurate models of the river discharge in the context of the water flow alteration due to anthropic influences and climate change. Therefore, this article addresses the challenge of detecting the best model among three
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The management of water resources must be based on accurate models of the river discharge in the context of the water flow alteration due to anthropic influences and climate change. Therefore, this article addresses the challenge of detecting the best model among three artificial intelligence techniques (AI)—backpropagation neural networks (BPNN), long short-term memory (LSTM), and extreme learning machine (ELM)—for the monthly data series discharge of the Buzău River, in Romania. The models were built for three periods: January 1955–September 2006 (S1 series), January 1955–December 1983 (S2 series), and January 1984–December 2010 (S series). In terms of mean absolute error (MAE), the best performances were those of ELM on both Training and Test sets on S2, with MAETraining = 5.02 and MAETest = 4.01. With respect to MSE, the best was LSTM on the Training set of S2 (MSE = 60.07) and ELM on the Test set of S2 (MSE = 32.21). Accounting for the R2 value, the best model was LSTM on S2 (R2Training = 99.92%, and R2Test = 99.97%). ELM was the fastest, with 0.6996 s, 0.7449 s, and 0.6467 s, on S, S1, and S2, respectively.
Full article
(This article belongs to the Special Issue Hydrological Simulation and Forecasting Based on Artificial Intelligence)
Open AccessArticle
Rainfall-Runoff Parameter Estimation from Ungauged Flat Afforested Catchments Using the NRCS-CN Method
by
Szymon Kobus
Water 2024, 16(9), 1247; https://doi.org/10.3390/w16091247 - 26 Apr 2024
Abstract
Of the numerous methods applied in rainfall-runoff models, the most common is the NRCS-CN method that is applied to calculate raised-water runoffs and compare them with the runoff values measured for 12 selected rainfall-runoff events. This study was conducted on three experimental forest
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Of the numerous methods applied in rainfall-runoff models, the most common is the NRCS-CN method that is applied to calculate raised-water runoffs and compare them with the runoff values measured for 12 selected rainfall-runoff events. This study was conducted on three experimental forest catchments with an area ranging from 67.6 to 747 ha. Total rainfall values ranging from 22.2 to 84.1 mm were analysed. Relatively low effective rainfall values were obtained for the lowest average for catchment 1 (Pe = 0.23 mm) and the runoff coefficient (α = 0.40%) and for the highest average for catchment 3 (Pe = 1.35 mm) and an average runoff coefficient (α = 3.12%). The maximum potential retention Si value, corresponding to each pair of P-Pe events, was the effect of the catchment’s moisture and absorptive capacity conditions. The lowest retention S value was calculated for catchment 3. The highest average retention value was calculated for catchment 1, in which the lightest soils were found. The best fit of the initial loss coefficient for the majority of rainfall-runoff events occurred for the λ coefficient values of 0.05 and 0.075. At higher λ, the effective rainfall Pe was not generated. LAG times calculated using 10 methods yielded diverse values. The fit of a specific formula was largely influenced by the size of the catchment, as well as the number and type of parameters considered during model calibration. The method based on catchment width demonstrated the best fit for all catchments, with R² ranging from 0.77 to 0.78 and RMSE from 0.52 for catchment 2 to 1.11 for catchment 1.
Full article
(This article belongs to the Special Issue Water Resources Science and Management in Forested and Mixed-Land-Use Watersheds)
Open AccessArticle
Precipitation Modeling Based on Spatio-Temporal Variation in Lake Urmia Basin Using Machine Learning Methods
by
Sajjad Arbabi, Mohammad Taghi Sattari, Nasrin Fathollahzadeh Attar, Adam Milewski and Mohamad Sakizadeh
Water 2024, 16(9), 1246; https://doi.org/10.3390/w16091246 - 26 Apr 2024
Abstract
The amount of rainfall in different regions is influenced by various factors, including time, place, climate, and geography. In the Lake Urmia basin, Mediterranean air masses significantly impact precipitation. This study aimed to model precipitation in the Lake Urmia basin using monthly rainfall
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The amount of rainfall in different regions is influenced by various factors, including time, place, climate, and geography. In the Lake Urmia basin, Mediterranean air masses significantly impact precipitation. This study aimed to model precipitation in the Lake Urmia basin using monthly rainfall data from 16 meteorological stations and five machine learning methods (RF, M5, SVR, GPR, and KNN). Eight input scenarios were considered, including the monthly index, longitude, latitude, altitude, distance from stations to Lake Urmia, and distance from the Mediterranean Sea. The results revealed that the random forest model consistently outperformed the other models, with a correlation rate of 0.968 and the lowest errors (RMSE = 5.66 mm and MAE = 4.03 mm). This indicates its high accuracy in modeling precipitation in this basin. This study’s significant contribution is its ability to accurately model monthly precipitation using spatial variables and monthly indexes without measuring precipitation. Based on the findings, the random forest model can model monthly rainfall and create rainfall maps by interpolating the GIS environment for areas without rainfall measurements.
Full article
(This article belongs to the Section Water and Climate Change)
Open AccessArticle
Occurrence and Risk Assessment of Perfluoroalkyl Substances in Surface Water of Hefei City, Southeast China
by
Yu Zhang, Chuanjun Jiang, Liangpu Zhang, Hua Cheng and Ning Wang
Water 2024, 16(9), 1245; https://doi.org/10.3390/w16091245 - 26 Apr 2024
Abstract
In this work, the spatial distribution, potential sources, and risk assessment of perfluoroalkyl substances (PFASs) were investigated at 22 surface water sampling sites in Hefei City. The study encompassed 11 distinct types of PFASs, which included 7 perfluoroalkyl carboxylic acids (PFCAs) and 4
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In this work, the spatial distribution, potential sources, and risk assessment of perfluoroalkyl substances (PFASs) were investigated at 22 surface water sampling sites in Hefei City. The study encompassed 11 distinct types of PFASs, which included 7 perfluoroalkyl carboxylic acids (PFCAs) and 4 perfluoroalkyl sulfonic acids (PFSAs). The findings indicated that the overall concentration of PFASs varied between 12.96 to 545.50 ng/L, with perfluorooctanoic acid (PFOA), perfluorobutanesulfonic acid (PFBS), perfluorobutyric acid (PFBA), and perfluorohexanoic acid (PFHxA) being the most prevalent, contributing to an average of 71% of the total PFASs concentration. Principal component analysis (PCA) elucidated the primary sources of PFASs, which included industrial emissions, fluoropolymer production and treatment, textile processing, and the impact of the electroplating industry. Employing the risk quotient (RQ) method facilitated the assessment of ecological risks associated with PFASs in surface water within the study area, suggesting that the current concentrations of PFASs in Hefei’s surface water pose a relatively low ecological risk. However, the long-term ecological effects of PFASs cannot be overlooked due to their potential for long-range transport and the cumulative nature of biological food chains.
Full article
Open AccessArticle
Simultaneous Synthesis of Single- and Multiple-Contaminant Water Networks Using LINGO and Excel Software
by
Abeer M. Shoaib, Amr A. Atawia, Mohamed H. Hassanean, Abdelrahman G. Gadallah and Ahmed A. Bhran
Water 2024, 16(9), 1244; https://doi.org/10.3390/w16091244 - 26 Apr 2024
Abstract
Controlling the distribution of water and wastewater between industrial processes is vital to rationalize water usage and preserve the environment. In this paper, a mathematical technique is proposed to optimize water–wastewater networks, and a nonlinear program is introduced to minimize the consumption of
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Controlling the distribution of water and wastewater between industrial processes is vital to rationalize water usage and preserve the environment. In this paper, a mathematical technique is proposed to optimize water–wastewater networks, and a nonlinear program is introduced to minimize the consumption of freshwater and, consequently, the flowrate of wastewater discharge. A general mathematical model, able to handle industrial plants containing up to eight sources and eight sinks, is developed using LINGO optimization software to facilitate dealing with complex case studies. The introduced model can handle single-contaminant networks as well as multiple-contaminant ones. The optimal water network is synthesized through two steps; the first step involves the introduction of the case study data into the developed mathematical model. The second step considers using the optimal solution produced after running the developed LINGO model as feed data for a pre-designed Excel sheet able to deal with these results and simultaneously draw the optimal water–wastewater network. The proposed mathematical model is applied to two case studies. The first case study includes actual data from four fertilizer plants located in Egypt; the water resources and requirements are simultaneously integrated to obtain a sensible cutting in both freshwater consumption (lowered by 52.2%) and wastewater discharge (zero wastewater discharge). The second case study regards a Brazilian petrochemical plant; the obtained results show noticeable reductions in freshwater consumption by 12.3%, while the reduction percentage of wastewater discharge is 4.5%.
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(This article belongs to the Special Issue Contaminants in the Water Environment)
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Open AccessArticle
Determinants of Farmers’ Acceptance of the Volumetric Pricing Policy for Irrigation Water: An Empirical Study from China
by
Xuan Fang and Ying Zhu
Water 2024, 16(9), 1243; https://doi.org/10.3390/w16091243 - 26 Apr 2024
Abstract
Volumetric-based pricing for irrigation water was introduced as part of a comprehensive reform of agricultural water prices in China. However, operational deficiencies and farmers’ lack of willingness to adopt the volumetric pricing policy (VPP) hinder the coordinated implementation of the reform. To address
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Volumetric-based pricing for irrigation water was introduced as part of a comprehensive reform of agricultural water prices in China. However, operational deficiencies and farmers’ lack of willingness to adopt the volumetric pricing policy (VPP) hinder the coordinated implementation of the reform. To address these practical challenges, we employed a binary logistic regression model to analyse farmers’ acceptance of the VPP for agricultural irrigation water usage in Suqian City, Jiangsu Province. A variable set was formed by selecting potential variables from four types of influencing factors: the subject (water users), the object (water supply departments), natural condition factors, and social condition factors. Our results revealed seven factors that determine whether farmers accept the VPP: irrigation water measurement at the water inlet of a lateral canal, the irrigation water-saving rewards scale, enforcement efforts of charging by volume, the irrigation water source type, the use of agricultural water-saving for trade, financial investment in water-saving technology, and the level of irrigation water pricing. We determined the degree of influence of the seven determining factors, among which the irrigation water-saving rewards scale and enforcement efforts of charging by volume most influence farmers’ decisions on the VPP for irrigation water. The results of this study can be used as a reference for innovation of the agricultural water-saving system in Suqian City, optimisation of an accurate fiscal subsidy scale, quantification of irrigation water rights, optimisation of the measurement facility layout, and effective implementation of agricultural water rights trading. More broadly, this study provides a valuable reference for solving the difficulties faced in the comprehensive reform of agricultural water pricing in China, which includes irrigation water pricing mechanisms, management systems, subsidy mechanisms, and water-saving incentive measures.
Full article
(This article belongs to the Section Water Resources Management, Policy and Governance)
Open AccessReview
Harnessing the Potential of Extracellular Polymeric Substances in Enhancing ANAMMOX Processes: Mechanisms, Strategies, and Perspectives
by
Lijing Fan, Cancan Jiang, Xu Wang, Yang Yang, Yawen Xie, Jiaqi Su, Hong Sun, Shengjun Xu and Xuliang Zhuang
Water 2024, 16(9), 1242; https://doi.org/10.3390/w16091242 - 26 Apr 2024
Abstract
Anaerobic ammonium oxidation (ANAMMOX) has emerged as a promising sustainable nitrogen removal technology that offers significant advantages over conventional nitrification–denitrification processes, such as reduced energy consumption, a 60% reduction in oxygen demand, and a 90% reduction in sludge production. However, the practical application
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Anaerobic ammonium oxidation (ANAMMOX) has emerged as a promising sustainable nitrogen removal technology that offers significant advantages over conventional nitrification–denitrification processes, such as reduced energy consumption, a 60% reduction in oxygen demand, and a 90% reduction in sludge production. However, the practical application of ANAMMOX is hindered by several challenges, including the slow growth of ANAMMOX bacteria, long start-up periods, and high sensitivity to environmental disturbances. Recent studies have highlighted the crucial role of extracellular polymeric substances (EPSs) in the formation, activity, and stability of ANAMMOX biofilms and granules. An EPS is a complex mixture of high-molecular-weight polymers secreted by microorganisms, mainly composed of polysaccharides, proteins, nucleic acids, and lipids. The diverse physicochemical properties and functional groups of EPSs enable them to serve as a structural scaffold, protective barrier, sorption site, electron shuttle, and nutrient source for ANAMMOX bacteria. This review aims to provide an overview of the latest research progress on harnessing the potential of EPSs to enhance the ANAMMOX process. The characteristics, compositions, and extraction methods of ANAMMOX-derived EPSs are summarized. The mechanisms of how EPSs facilitate the enrichment, immobilization, aggregation, and adaptation of ANAMMOX bacteria are elucidated. The strategies and effects of EPS supplementation on improving the performance and robustness of ANAMMOX reactors under various stresses are critically reviewed. The challenges and future perspectives of the EPS-mediated optimization of the ANAMMOX process are also discussed. This review sheds new light on exploiting EPSs as a renewable bioresource to develop more efficient and stable ANAMMOX applications for sustainable wastewater treatment.
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(This article belongs to the Section Wastewater Treatment and Reuse)
Open AccessArticle
Novel Oxidation Strategies for the In Situ Remediation of Chlorinated Solvents from Groundwater—A Bench-Scale Study
by
Alicia Cano-López, Lidia Fernandez-Rojo, Leónidas Pérez-Estrada, Sònia Jou-Claus, Marta Batriu, Carme Bosch, Xavier Martínez-Lladó, Joana Baeta Trias, Ricard Mora Vilamaña, Mònica Escolà Casas and Víctor Matamoros
Water 2024, 16(9), 1241; https://doi.org/10.3390/w16091241 - 26 Apr 2024
Abstract
Industrial chlorinated solvents continue to be among the most significant issues in groundwater (GW) pollution worldwide. This study assesses the effectiveness of eight novel oxidation treatments, including persulfate (PS), ferrous sulfate, sulfidated nano-zero valent iron (S-nZVI), and potassium ferrate, along with their combinations,
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Industrial chlorinated solvents continue to be among the most significant issues in groundwater (GW) pollution worldwide. This study assesses the effectiveness of eight novel oxidation treatments, including persulfate (PS), ferrous sulfate, sulfidated nano-zero valent iron (S-nZVI), and potassium ferrate, along with their combinations, for the potential in situ remediation of GW polluted with chlorinated solvents (1,2-dichloroethylene, trichloroethylene, and tetrachloroethylene). Our bench-scale results reveal that the combined addition of PS and S-nZVI can effectively eliminate trichloroethylene (10 µg/L), achieving removal rates of up to 80% and 92% within 1 h, respectively, when using synthetic GW. In the case of real GW, this combination achieved removal rates of 69, 99, and 92% for cis-1,2-dichloroethylene, trichloroethylene, and tetrachloroethylene, respectively, within 24 h. Therefore, this proposed remediation solution resulted in a significant reduction in the environmental risk quotient, shifting it from a high-risk (1.1) to a low-risk (0.2) scenario. Furthermore, the absence of transformation products, such as vinyl chloride, suggests the suitability of employing this solution for the in situ remediation of GW polluted with chlorinated solvents.
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(This article belongs to the Special Issue New Technologies for Soil and Groundwater Remediation)
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Open AccessArticle
Groundwater Chemical Trends Analyses in the Piedmont Po Plain (NW Italy): Comparison with Groundwater Level Variations (2000–2020)
by
Daniele Cocca, Manuela Lasagna and Domenico Antonio De Luca
Water 2024, 16(9), 1240; https://doi.org/10.3390/w16091240 - 26 Apr 2024
Abstract
The concentrations of chemicals in the groundwater chemical values in the Piedmont Po Plain (NW Italy) show significant temporal variability and need to be characterised due to the lack of regional-scale assessments. The aim of this study was to analyse the trends (period
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The concentrations of chemicals in the groundwater chemical values in the Piedmont Po Plain (NW Italy) show significant temporal variability and need to be characterised due to the lack of regional-scale assessments. The aim of this study was to analyse the trends (period 2000–2020) in the main physicochemical parameters and main ions in 227 wells in the shallow aquifer and to identify the potential causes. The identification of change points (points of sudden change) and comparisons with groundwater level variations were also performed. Results highlight general increasing trends for Na, Cl and HCO3, decreasing trends for SO4 and NO3, stationary conditions for pH and heterogeneous behaviours for electrolytic conductivity, Ca and Mg. Change points occurred in at least 50% of the monitoring wells, mainly during the 2008–2011 period. The comparison between groundwater levels and chemistry highlights a direct proportionality. Superimposed processes that induce an absence of proportionality are shown. The comparison of results with those of previous studies conducted under similar conditions revealed similar variations.. In conclusion, the potential responsible factors (e.g., road-salt dissolution and agricultural practices) and the relevant role of groundwater level variation were identified.
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(This article belongs to the Section Hydrogeology)
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Open AccessArticle
Identification of Trends in Dam Monitoring Data Series Based on Machine Learning and Individual Conditional Expectation Curves
by
Miguel Á. Fernández-Centeno, Patricia Alocén and Miguel Á. Toledo
Water 2024, 16(9), 1239; https://doi.org/10.3390/w16091239 - 26 Apr 2024
Abstract
Dams are complex systems that involve both the structure itself and its foundation. Rheological phenomena, expansive reactions, or alterations in the geotechnical parameters of the foundation, among others, result in non-reversible and cumulative modifications in the dam response, leading to trends in the
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Dams are complex systems that involve both the structure itself and its foundation. Rheological phenomena, expansive reactions, or alterations in the geotechnical parameters of the foundation, among others, result in non-reversible and cumulative modifications in the dam response, leading to trends in the monitoring data series. The accurate identification and definition of these trends to study their evolution are key aspects of dam safety. This manuscript proposes a methodology to identify trends in dam behavioural data series by identifying the influence of the time variable on the predictions provided by the ML models. Initially, ICE curves and SHAP values are employed to extract temporal dependence, and the ICE curves are found to be more precise and efficient in terms of computational cost. The temporal dependencies found are adjusted using a GWO algorithm to different function characteristics of irreversible processes in dams. The function that provides the best fit is selected as the most plausible. The results obtained allow us to conclude that the proposed methodology is capable of obtaining estimates of the most common trends that affect movements in concrete dams with greater precision than the statistical models most commonly used to predict the behaviour of these types of variables. These results are promising for its general application to other types of dam monitoring data series, given the versatility demonstrated for the unsupervised identification of temporal dependencies.
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(This article belongs to the Special Issue Managing Impacts on Baseflows in Streams and the Associated Impacts on Ecosystems and Water Quality)
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Open AccessArticle
A Novel Method for Anomaly Detection and Signal Calibration in Water Quality Monitoring of an Urban Water Supply System
by
Jincheng Liu, Di Wu, Hadi Mohammed and Razak Seidu
Water 2024, 16(9), 1238; https://doi.org/10.3390/w16091238 - 26 Apr 2024
Abstract
Water quality monitoring plays a crucial role in urban water supply systems for the production of safe drinking water. However, the traditional approach to water monitoring in Norway relies on a periodic (weekly/biweekly/monthly) sampling and analysis of biological indicators, which fails to provide
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Water quality monitoring plays a crucial role in urban water supply systems for the production of safe drinking water. However, the traditional approach to water monitoring in Norway relies on a periodic (weekly/biweekly/monthly) sampling and analysis of biological indicators, which fails to provide a timely response to changes in water quality. This research addresses this issue by proposing a data-driven solution that enhances the timeliness of water quality monitoring. Our research team applied a case study in Ålesund Kommune. A sensor platform has been deployed at Lake Brusdalsvatnet, the water source reservoir in Ålesund. This sensor module is capable of collecting data for 10 different physico-chemical indicators of water quality. Leveraging this sensor platform, we developed a CNN-AutoEncoder-SOM solution to automatically monitor, process, and evaluate water quality evolution in the lake. There are three components in this solution. The first one focuses on anomaly detection. We employed a recurrence map to encode the temporal dynamics and sensor correlations, which were then fed into a convolutional neural network (CNN) for classification. It is noted that this network achieved an impressive accuracy of up to . Once an anomaly is detected, the data are calibrated in the second component using an AutoEncoder-based network. Since true values for calibration are unavailable, the results are evaluated through data analysis. With high-quality calibrated data in hand, we proceeded to cluster the data into different categories to establish water quality standards in the third component, where a self-organizing map (SOM) is applied. The results revealed that this solution demonstrated significant performance, with a silhouette score of 0.73, which illustrates a small in-cluster distance and large intra-cluster distance when the water was clustered into three levels. This system not only achieved the objective of developing a comprehensive solution for continuous water quality monitoring but also offers the potential for integration with other cyber–physical systems (CPSs) in urban water management.
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(This article belongs to the Topic Hydrology and Water Resources Management)
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