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
Assessment of Groundwater Quality Using the Pollution Index of Groundwater (PIG), Nitrate Pollution Index (NPI), Water Quality Index (WQI), Multivariate Statistical Analysis (MSA), and GIS Approaches: A Case Study of the Mnasra Region, Gharb Plain, Morocco
Water 2024, 16(9), 1263; https://doi.org/10.3390/w16091263 (registering DOI) - 28 Apr 2024
Abstract
Groundwater, an invaluable resource crucial for irrigation and drinking purposes, significantly impacts human health and societal advancement. This study aims to evaluate the groundwater quality in the Mnasra region of the Gharb Plain, employing a comprehensive analysis of thirty samples collected from various
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Groundwater, an invaluable resource crucial for irrigation and drinking purposes, significantly impacts human health and societal advancement. This study aims to evaluate the groundwater quality in the Mnasra region of the Gharb Plain, employing a comprehensive analysis of thirty samples collected from various locations, based on thirty-three physicochemical parameters. Utilizing tools like the Pollution Index of Groundwater (PIG), Nitrate Pollution Index (NPI), Water Quality Index (WQI), Irrigation Water Quality Index (IWQI), as well as Multivariate Statistical Approaches (MSA), and the Geographic Information System (GIS), this research identifies the sources of groundwater pollution. The results revealed Ca2+ dominance among cations and Cl− as the primary anion. The Piper and Gibbs diagrams illustrated the prevalent Ca2+-Cl− water type and the significance of water–rock interactions, respectively. The PIG values indicated that 86.66% of samples exhibited “Insignificant pollution”. NPI showed notable nitrate pollution (1.48 to 7.06), with 83.33% of samples rated “Good” for drinking based on the WQI. The IWQI revealed that 80% of samples were classified as “Excellent” and 16.66% as “Good”. Spatial analysis identified the eastern and southern sections as highly contaminated due to agricultural activities. These findings provide valuable insights for decision-makers to manage groundwater resources and promote sustainable water management in the Gharb region.
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(This article belongs to the Special Issue Water Quality Assessment and Modelling)
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Open AccessArticle
Multi-Dimensional Collaborative Optimization Model for Agricultural Water Rights Based on Water Price Reform under Changing Environment
by
Linlin Song, Hongshu Wang and Liang Ding
Water 2024, 16(9), 1262; https://doi.org/10.3390/w16091262 (registering DOI) - 28 Apr 2024
Abstract
Agricultural water rights trading has become an effective means to solve the shortage of agricultural water. However, in the context of uncertainty, the key elements of the water rights trading system and their interactions remain unclear. Therefore, this study constructs a multi-dimensional collaborative
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Agricultural water rights trading has become an effective means to solve the shortage of agricultural water. However, in the context of uncertainty, the key elements of the water rights trading system and their interactions remain unclear. Therefore, this study constructs a multi-dimensional collaborative optimization model for agricultural water rights based on water price reform under a changing environment. The model quantitatively characterizes the synergistic effects of resource, economic, social, environmental, and ecological objectives on initial water rights allocation and trading. At the same time, the model uses a system dynamics model and intuitionistic fuzzy number to reflect the impact of a changing environment and uncertainty of the management system on water rights allocation and trading. The results show that through water rights trading, the overall coordinated development of farms has been improved, and the economic benefits and water resources utilization efficiency have been improved.
Full article
(This article belongs to the Special Issue Hydro-Economic Models for Sustainable Water Resources Management)
Open AccessArticle
Determining the Relevance of Commonly Used Hydraulic Parameters for Representing the Water Erosive Force in Rock Mass Erosion within Dam Spillways
by
Aboubacar Sidiki Koulibaly, Ali Saeidi, Alain Rouleau and Marco Quirion
Water 2024, 16(9), 1261; https://doi.org/10.3390/w16091261 (registering DOI) - 28 Apr 2024
Abstract
Spillways are essential control structures in hydroelectric dams for evacuating excess water during periods of high-water flow. These structures are generally excavated within a rock mass, without lining, and they take the form of a flow channel or a plunge pool. Rock mass
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Spillways are essential control structures in hydroelectric dams for evacuating excess water during periods of high-water flow. These structures are generally excavated within a rock mass, without lining, and they take the form of a flow channel or a plunge pool. Rock mass erosion is an important issue facing engineers when designing unlined spillways. Methods commonly used to analyze this phenomenon are based on the threshold line concept, i.e., the correlation between rock mass resistance and its destruction against the erosive force of water. Multiple indices have been proposed for both rock mass quality and water energy (or erosive force) to assess rock mass erosion. The selection of appropriate indices is critical when evaluating hydraulic erosion. The erosive force of water is often represented by energy dissipation; however, other parameters, including average flow velocity and shear stress at the bottom of the flow channel, may also be relevant. Thus, a critical question is framed: which index best represents the erosive force of water? Here, we develop an approach to assess the applicability of the various indices used to represent the erosive force of water by relying on erosional events at more than 100 study sites. We determine that the most relevant parameters are linked to water pressure, as pressure head and flow velocity better explain the erosive force of the water than shear stress and water dissipation energy.
Full article
(This article belongs to the Special Issue Evolution of Soil and Water Erosion)
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Open AccessArticle
Analyzing the Seasonal Vertical Displacement Fluctuations Using the Global Navigation Satellite System and Hydrological Load: A Case Study of the Western Yunnan Region
by
Pengfei Xu, Tao Jiang, Wanqiu Li, Gong Xu, Chuanyin Zhang, Wei Wang, Kunjun Tian and Jiandi Feng
Water 2024, 16(9), 1260; https://doi.org/10.3390/w16091260 (registering DOI) - 28 Apr 2024
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The non-tectonic deformation caused by hydrological loads is an important influencing factor in GNSS vertical displacement. Limited by the temporal and spatial resolution of global models and model errors, the hydrological load results calculated by traditional methods are difficult to meet the high
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The non-tectonic deformation caused by hydrological loads is an important influencing factor in GNSS vertical displacement. Limited by the temporal and spatial resolution of global models and model errors, the hydrological load results calculated by traditional methods are difficult to meet the high temporal and spatial resolution requirements of small to medium-scale regions. This paper introduces the idea of the remove–restore method, assimilates regional high-resolution hydrological data, and obtains higher temporal and spatial-resolution hydrological load results. Subsequently, utilizing data from 12 CORS observed in the western Yunnan region between January 2018 and December 2020, the quantitative relationship and variation characteristics between GNSS vertical displacement and hydrological load displacement were analyzed in detail. Furthermore, the annual signals of both were extracted using the SSA method for comparative analysis. After removing the effects of atmospheric load and non-tidal ocean load, the average correlation coefficient between GNSS vertical displacement and hydrological load displacement is 0.84, with an average reduction of WRMS (%) reaching 37.17%. The average correlation coefficient of the annual signals between GNSS vertical displacement and hydrological load deformation is 0.94, with an average reduction of WRMS (%) reaching 46.5%, indicating that the contribution of hydrological load to the GNSS non-tectonic vertical displacement annual signal is close to 50%. The research results provide scientific support and important references for studying surface tectonic deformation by removing non-tectonic deformations such as hydrological loads from GNSS vertical displacement. Additionally, it helps to explore the mechanisms of interaction between water storage migration and surface deformation.
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Open AccessArticle
Changes in Surface Water Quality of the El Salvador River in La Joya de los Sachas, Ecuadorian Amazon Region
by
Tannia Vargas-Tierras, Mirian Jiménez-Gutiérrez, Sandra Pastrano, Gino Chávez, Vanessa Morales-León, María Morales-León, Fernando Paredes and Wilson Vásquez-Castillo
Water 2024, 16(9), 1259; https://doi.org/10.3390/w16091259 (registering DOI) - 28 Apr 2024
Abstract
Water effluent pollution in the Ecuadorian Amazon occurs mainly due to the lack of sewage infrastructure, wastewater treatment plants in urban and rural areas, and agricultural and livestock activities. Consequently, understanding water quality is crucial because of its dynamic nature, influenced by various
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Water effluent pollution in the Ecuadorian Amazon occurs mainly due to the lack of sewage infrastructure, wastewater treatment plants in urban and rural areas, and agricultural and livestock activities. Consequently, understanding water quality is crucial because of its dynamic nature, influenced by various activities along its course. We evaluated and compared the water quality status of the El Salvador River with the current standards of the Ministry of the Environment, Water, and Ecological Transition in Ecuador and with Decree No. 115/2003 on water quality and water pollution management. The water quality index was determined through random sampling at seven locations along the river. The results show good water quality, with contamination indices ranging from 84 to 87. When comparing the results with the standards, all water quality parameters met the standards for recreational purposes. However, considering the river’s uses for agricultural activities, we compared the water with additional standards from legislation outlined by the Environment Ministry and found that the nitrate content exceeded permissible limits due to runoff from the surrounding crops, causing a potential risk to human health. Therefore, incorporating helophyte plants is a promising option that would promote the health of this aquatic ecosystem and others.
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(This article belongs to the Special Issue Assessment of Water Quality and Pollutant Behavior)
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Open AccessArticle
Burst Diagnosis Multi-Stage Model for Water Distribution Networks Based on Deep Learning Algorithms
by
Sen Peng, Yuxin Wang, Xu Fang and Qing Wu
Water 2024, 16(9), 1258; https://doi.org/10.3390/w16091258 (registering DOI) - 28 Apr 2024
Abstract
Pipe bursts in water distribution networks (WDNs) pose significant threats to the safety of distribution networks, driving attention to deep learning-based burst detection and localization. However, the applicability of different pressure features still needs to be compared and verified. A large number of
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Pipe bursts in water distribution networks (WDNs) pose significant threats to the safety of distribution networks, driving attention to deep learning-based burst detection and localization. However, the applicability of different pressure features still needs to be compared and verified. A large number of nodes challenges deep learning with the excessive number of classification categories and low recognition accuracy. To address these problems, this paper extracts different burst pressure features, including pressure value, pressure difference, and pressure fluctuation ratio, and inputs one of these features into a Burst Diagnosis Multi-Stage Model (BDMM) based on three CS-LSTMs (a combination of the Cuckoo Search algorithm and a long short-term memory network). The first model addresses a binary classification problem, outputting labels indicating whether a pipe burst has occurred. The second one solves a multi-classification problem, outputting the label of the burst partition, and the third model also solves a multi-classification problem, outputting the ID of the bursting junction. The model is tested on a real network and outperforms ELM. For basic burst identification tasks using CS-LSTM, differences among the three features are minimal, while pressure difference and pressure fluctuation ratio exhibit superior performance to pressure value when resolving more complex problems like burst junction localization.
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(This article belongs to the Special Issue Green and Low Carbon Development of Water Treatment Technology, 2nd Edition)
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Open AccessArticle
Effects of Three Antibiotics on Nitrogen-Cycling Bacteria in Sediment of Aquaculture Water
by
Zhu Li, Huan He, Jianhe Ding, Zhizhong Zhang, Yifei Leng, Mingjun Liao and Wen Xiong
Water 2024, 16(9), 1256; https://doi.org/10.3390/w16091256 (registering DOI) - 28 Apr 2024
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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.
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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.
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(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.
Full article
(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.
Full article
(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
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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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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.
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(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.
Full article
(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.
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(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%.
Full article
(This article belongs to the Special Issue Contaminants in the Water Environment)
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