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 (Geography, Planning and Development)
- 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
Study on the Impact of Closed Coal Mines on Groundwater in the Panlong River Basin (Shangdong Province, China) Based on Sulfur and Oxygen Isotopes
Water 2024, 16(11), 1634; https://doi.org/10.3390/w16111634 (registering DOI) - 6 Jun 2024
Abstract
To deeply investigate the impact of closed coal mines on groundwater sulfate contamination in the Panlong River basin, Zaozhuang, Shandong Province, China, the hydrochemical characteristics and controlling factors of groundwater were analyzed based on 64 surface water and groundwater samples. The sources of
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To deeply investigate the impact of closed coal mines on groundwater sulfate contamination in the Panlong River basin, Zaozhuang, Shandong Province, China, the hydrochemical characteristics and controlling factors of groundwater were analyzed based on 64 surface water and groundwater samples. The sources of sulfate contamination were identified by sulfur and oxygen isotope analysis. The results indicate that the sulfate content in the pore groundwater exceeds the Standard for Groundwater Quality (China) Category III (250 mg/L), with a maximum content of 666.2 mg/L. Specifically, the exceedance rate of sulfate in pore water near the western boundary of the Taozao coal field is directly related to mine water. The exceedance rate of sulfate in karst groundwater is 28%, peaking at 1131 mg/L, and is mainly distributed outside the western boundary of the Taozao coalfield and near the Dingzhuang water source in the southeast of the coalfield, indicating a significant influence from high-sulfate mine water in the coal-bearing strata. The sulfur and oxygen isotope differences are significant between surface water, mine water, karst water, and pore water. Through Bayesian end-member analysis, it was determined that 40–83% of sulfate in the downstream pore water of the Taozao coal field originated from mine water, while 48–86% of the sulfate in the karst water originated from mine water, which greatly affects the groundwater in the western and southeastern parts of the Taozao coalfield. Therefore, measures should be taken as soon as possible to control the risk of sulfate pollution of neighboring groundwater, especially karst groundwater, by mine water from closed coal mines.
Full article
(This article belongs to the Section Hydrogeology)
Open AccessArticle
Development of a Lightweight Floating Object Detection Algorithm
by
Rundong Xian, Lijun Tang and Shenbo Liu
Water 2024, 16(11), 1633; https://doi.org/10.3390/w16111633 (registering DOI) - 6 Jun 2024
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YOLOv5 is currently one of the mainstream algorithms for object detection. In this paper, we propose the FRL-YOLO model specifically for river floating object detection. The algorithm integrates the Fasternet block into the C3 module, conducting convolutions only on a subset of input
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YOLOv5 is currently one of the mainstream algorithms for object detection. In this paper, we propose the FRL-YOLO model specifically for river floating object detection. The algorithm integrates the Fasternet block into the C3 module, conducting convolutions only on a subset of input channels to reduce computational load. Simultaneously, it effectively captures spatial features, incorporates reparameterization techniques into the feature extraction network, and introduces the RepConv design to enhance model training efficiency. To further optimize network performance, the ACON-C activation function is employed. Finally, by employing a structured non-destructive pruning approach, redundant channels in the model are trimmed, significantly reducing the model’s volume. Experimental results indicate that the algorithm achieves an average precision value (mAP) of 79.3%, a 0.4% improvement compared to yolov5s. The detection speed on the NVIDIA GeForce RTX 4070 graphics card reaches 623.5 fps/s, a 22.8% increase over yolov5s. The improved model is compressed to a volume of 2 MB, representing only 14.7% of yolov5s.
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Open AccessArticle
Reflection of Daily, Seasonal and Interannual Variations in Run-off of a Small River in the Water Isotopic Composition (δ2H, δ18O): A Case of the Ala-Archa Mountain River Basin with Glaciation (Kyrgyzstan, Central Asia)
by
Igor Tokarev, Evgeny Yakovlev, Sergey Erokhin, Tamara Tuzova, Sergey Druzhinin and Andrey Puchkov
Water 2024, 16(11), 1632; https://doi.org/10.3390/w16111632 (registering DOI) - 6 Jun 2024
Abstract
Small intermountain river basins are most suitable for developing new methods to estimate water balance due to their well-defined catchment boundaries, relatively rapid runoff processes, and accessible landscapes for study. In general terms, dissecting the hydrograph of a small mountain river requires calibration
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Small intermountain river basins are most suitable for developing new methods to estimate water balance due to their well-defined catchment boundaries, relatively rapid runoff processes, and accessible landscapes for study. In general terms, dissecting the hydrograph of a small mountain river requires calibration of the flow model against multi-year data sets, including (a) glacier mass balance and snow water content, (b) radiation balance calculation, (c) estimation of the groundwater contribution, and (d) water discharge measurements. The minimum primary data set is limited to the precipitation and temperature distributions at the catchment. This approach postulates that the conditions for the formation of all components of river flow are known in advance. It is reduced to calculating the dynamic balance between precipitation (input part) and runoff, ablation, and evaporation (output part). In practice, accurately accounting for the inflow and outflow components of the balance, as well as the impact of regulating reservoirs, can be a challenging task that requires significant effort and expense, even for the extensively researched catchments. Our studies indicate the potential benefits of an approach based on one-time, but detailed, observations of stable isotope composition, temperature, and water chemistry, in addition to standard datasets. This paper presents the results of the 2022–2023 work conducted in the basin of the small mountain river Ala-Archa, located on the northern slope of the Kyrgyz Range in Tien-Shan, which was chosen as an example due to its well-studied nature. Our approach could identify previously unknown factors of flow formation and assess the time and effectiveness of work in similar conditions.
Full article
Open AccessReview
Review of the Mechanism and Methodology of Water Demand Forecasting in the Socio-Economic System
by
Xudong Fang, Jinhua Liu, Min Zhou, Hui Zhang and Jing Zhao
Water 2024, 16(11), 1631; https://doi.org/10.3390/w16111631 (registering DOI) - 6 Jun 2024
Abstract
As global water scarcity becomes increasingly acute, water demand forecasting has emerged as a critical component in water resource management and planning. This review aims to comprehensively survey and analyze the current state of research, existing issues, and development trends in the field
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As global water scarcity becomes increasingly acute, water demand forecasting has emerged as a critical component in water resource management and planning. This review aims to comprehensively survey and analyze the current state of research, existing issues, and development trends in the field of water demand forecasting. Presently, there are numerous studies on water demand forecasting; however, most of the forecasting results tend to be overestimated. On the mechanistic level, research has gradually shifted from considering single factors to accounting for the complex influences of multiple factors. This paper summarizes the mechanism of water demand from the three levels of agriculture, industry, and residential life. In terms of forecasting methods, various techniques have been explored and applied, particularly new methods based on artificial intelligence and machine learning, which have demonstrated significant advantages in improving forecasting accuracy and handling nonlinear relationships. Despite the notable progress and practical achievements in water demand forecasting, several challenges and issues remain. Future research should focus on diversifying methodologies, comprehensively considering multiple influencing factors, further refining forecasting models and technical systems, strengthening uncertainty and risk management, and emphasizing practical applications and policy guidance.
Full article
(This article belongs to the Special Issue Socio-Economics of Water Resources Management)
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Open AccessArticle
Conceptual Model Based on Groundwater Dynamics in the Northern Croatian Dinaric Region at the Transition from the Deep Karst and Fluviokarst
by
Ivana Boljat, Josip Terzić, Željko Duić, Jasmina Lukač Reberski and Ana Selak
Water 2024, 16(11), 1630; https://doi.org/10.3390/w16111630 (registering DOI) - 6 Jun 2024
Abstract
The Dinaric karst in the north differs from the rest of the karst in Croatia in terms of karstification depth. The infiltrating precipitation drains in cascades from deeply karstified mountainous areas to the shallow or fluviokarst, forming the tributaries of the Kupa River.
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The Dinaric karst in the north differs from the rest of the karst in Croatia in terms of karstification depth. The infiltrating precipitation drains in cascades from deeply karstified mountainous areas to the shallow or fluviokarst, forming the tributaries of the Kupa River. Time series analyses were conducted on a 5-year dataset to elucidate the hydrogeological conceptual model of the area and clarify disparate findings from tracer tests under varying hydrological conditions. The flow duration curve, autocorrelation functions, and recession curves were used to evaluate the spring discharge variability, the karstification degree, and the karst aquifer’s size. The crosscorrelation function and temperature dynamics were employed to assess the spring’s response to recharge and the hydrogeological system behavior. Comparative analysis with previous studies was conducted to contextualize the obtained results. The research outcomes delineated several key findings: (i) the deep karst zone is less developed than the shallow karst zone; (ii) groundwater exchange is significantly faster in shallow karst; (iii) groundwater divides in the Kapela Mountain are zonal; (iv) the homogenization of groundwater occurs during periods of high water levels; (v) fast water exchange transpires without concurrent groundwater temperature homogenization; and (vi) a definition of the boundary between deep and fluviokarst in Croatia.
Full article
(This article belongs to the Special Issue Research on Hydrogeology and Hydrochemistry: Challenges and Prospects)
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Open AccessArticle
Operating Energy Needed for Desalination Systems in Cogeneration Plants
by
Obida Zeitoun
Water 2024, 16(11), 1629; https://doi.org/10.3390/w16111629 (registering DOI) - 6 Jun 2024
Abstract
This study investigated the energy requirement for running desalination units coupled to cogeneration plants. Various cogeneration systems were explored using power- and heat-allocated approaches. The specific work and heat necessary for operating different desalination systems were determined. The investigation revealed that the specific
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This study investigated the energy requirement for running desalination units coupled to cogeneration plants. Various cogeneration systems were explored using power- and heat-allocated approaches. The specific work and heat necessary for operating different desalination systems were determined. The investigation revealed that the specific work and heat remain consistent regardless of the desalination daily capacity. It was observed that the energy demand for operating a desalination system mainly relies on power plant efficiency. The investigation revealed that the energy demand for a plain multi-effect desalination system was lower than that for multi-effect desalination with thermal vapor compression. Additionally, the energy requirement for a multi-effect desalination system with preheaters was lower than that for plain multi-effect desalination. Comparisons also indicated that the energy demand of multi-stage flash exceeds that of different multi-effect desalination systems. Based on the primary thermal energy input, a universal performance ratio was used to evaluate the desalination unit performance. Furthermore, a new correlation was proposed to predict the universal performance ratio.
Full article
(This article belongs to the Special Issue Water and Energy Synergies)
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Open AccessArticle
Effect of Green Infrastructure with Different Woody Plant Root Systems on the Reduction of Runoff Nitrogen
by
Bei Zhang, Liang Chen and Taolve Gao
Water 2024, 16(11), 1628; https://doi.org/10.3390/w16111628 (registering DOI) - 6 Jun 2024
Abstract
Rainfall-runoff nitrogen (N) pollution has emerged as the primary source of water contamination due to rapid urbanization. Green infrastructure (GI), as the representative measure, is widely used in controlling N pollution in runoff. However, there is limited research on the impact of woody
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Rainfall-runoff nitrogen (N) pollution has emerged as the primary source of water contamination due to rapid urbanization. Green infrastructure (GI), as the representative measure, is widely used in controlling N pollution in runoff. However, there is limited research on the impact of woody plants on N reduction in GIs. Therefore, this study aimed to investigate the influence and relationship of Sophora japonica (with tap root) and Malus baccata (with fibrous root) on N removal in GIs. Utilizing the advanced root analysis software WinRHIZO (version 4.0b), a meticulous examination of the morphological traits of plant roots was conducted. The findings unveiled a striking contrast between the root systems of two species: S. japonica primarily boasts a vertically oriented root configuration, whereas M. baccata’s root system is characterized by an extensively lateral, or horizontal, growth pattern. Specifically, in comparison to S. japonica, the horizontal roots of M. baccata demonstrated a substantial superiority, with their total root length measuring 10.95 times longer, the surface area spanning 6.25 times wider, and the cumulative volume being 3.93 times greater. For comparing the load reduction rates on runoff NH3-N, NO3-N, and TN of the different root morphologies’ GIs, S. japonica GI had the highest purification effect on the three pollutants, and the average load reduction rates of three pollutants reached 67.74%, 33.83%, and 38.96%, respectively, which were 11.42%, 27.46%, and 6.16% higher than those of the control. The variance contribution rate of vertical root and horizontal root characteristics on runoff nitrogen load reduction accounted for 86.47% of the total root contribution rate. The volume of vertical roots emerged as the most crucial characteristic factor affecting the reduction of N load.
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(This article belongs to the Section Urban Water Management)
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Open AccessArticle
Antibiotics in Wastewater Treatment Plants in Tangshan: Perspectives on Temporal Variation, Residents’ Use and Ecological Risk Assessment
by
Zhuo Dong, Jian Hu, Pengjie Wang, Gengtao Han and Zheng Jia
Water 2024, 16(11), 1627; https://doi.org/10.3390/w16111627 - 6 Jun 2024
Abstract
In 2023, this study monitored nine types of antibiotics in the influent and effluent of wastewater treatment plants (WWTPs) in the urban and suburban areas of Tangshan. The total antibiotics concentration detected in influent WWTPs was highest in winter, followed by spring, summer,
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In 2023, this study monitored nine types of antibiotics in the influent and effluent of wastewater treatment plants (WWTPs) in the urban and suburban areas of Tangshan. The total antibiotics concentration detected in influent WWTPs was highest in winter, followed by spring, summer, and autumn. The antibiotics concentration in influent and effluent urban WWTPs was higher than that in the suburban WWTPs in spring, summer, and winter, while the trend was reversed in autumn. Roxithromycin and oxytetracycline had a risk quotient (RQ) value of ≥0.1 in the effluent of WWTPs in winter, indicating that they are medium-risk antibiotics that pose a risk to the aquatic ecosystem after discharge. In the study area, the per capita pollution load of antibiotics was highest in spring, summer, and autumn for sulfamethoxazole, while it was highest in winter for ofloxacin. In the urban area, the use of roxithromycin, sulfamethoxazole, sulfamethoxazole, and ofloxacin was highest in spring, summer, autumn, and winter, respectively, while in suburban areas, the use of sulfamethoxazole, norfloxacin, sulfamethoxazole, and ofloxacin was highest during the same period. The use of antibiotics in the urban area was one order of magnitude higher than that in suburban areas, indicating a possible overuse of antibiotics in urban environments.
Full article
(This article belongs to the Special Issue Impacts of Environmental Change and Human Activities on Aquatic Ecosystems)
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Open AccessArticle
Photocatalytic Degradation of Algal Organic Matter Using TiO2/UV and Persulfate/UV
by
Luan de Souza Leite, Maria Teresa Hoffmann, Danilo Vitorino dos Santos and Luiz Antonio Daniel
Water 2024, 16(11), 1626; https://doi.org/10.3390/w16111626 - 6 Jun 2024
Abstract
Eutrophication in water reservoirs releases algal organic matter (AOM), a key precursor to the formation of disinfection by-products (DBPs) during the disinfection process. Typical drinking water treatment is not efficient for AOM removal, and advanced treatments are necessary for the removal of residual
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Eutrophication in water reservoirs releases algal organic matter (AOM), a key precursor to the formation of disinfection by-products (DBPs) during the disinfection process. Typical drinking water treatment is not efficient for AOM removal, and advanced treatments are necessary for the removal of residual AOM before chlorination. UV-based technology with PS and TiO2 is widely used as a pre-oxidation step in water treatment; however, no publications have focused on them for AOM degradation. In this context, this work investigated the effect of oxidant concentration (0.1 to 0.5 g∙L−1) and pH (6 to 10) on AOM degradation with TiO2/UV and persulfate (PS)/UV using response surface methodology. In general, PS/UV was more effective in removing protein, while TiO2/UV was more effective in carbohydrate degradation. TiO2/UV removals varied from 27 to 57% for protein and from 48 to 86% for carbohydrates. The optimal condition (57% for protein and 86% for carbohydrates) was obtained using 0.5 g∙L−1 TiO2 at pH 10. PS/UV removals varied from 33 to 81% for protein and from 24 to 53% for carbohydrates. The optimal condition (81% for protein and 53% for carbohydrates) was obtained using 0.5 g∙L−1 PS concentration at pH 8. Degradation kinetics showed a good fit to the pseudo-first-order model (R2 > 95%) for both processes. The DBP formation reductions observed with TiO2/UV—trihalomethane (THM) (85 to 86%) and chloral hydrate (CH) (94 to 96%)—were similar to the efficiencies observed for PS/UV—THM (87 to 89%) and CH (83 to 88%). These results show the efficiency of UV-based technology for AOM degradation and the control of DBP formation.
Full article
(This article belongs to the Special Issue Application of Photocatalysis in Water/Wastewater Treatment: Latest Advances and Prospects)
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Open AccessArticle
Denitrification Mechanism of Heterotrophic Aerobic Denitrifying Pseudomonas hunanensis Strain DC-2 and Its Application in Aquaculture Wastewater
by
Xinya Sui, Xingqiang Wu, Bangding Xiao, Chunbo Wang and Cuicui Tian
Water 2024, 16(11), 1625; https://doi.org/10.3390/w16111625 - 6 Jun 2024
Abstract
A novel heterotrophic aerobic denitrifying Pseudomonas hunanensis strain DC-2 was screened from the sediments of Lake Dianchi and identified with high nitrification/denitrification ability. Within 30 h, the removal efficiency of ammonium-N and nitrate-N could reach 98.8% and 88.4%, respectively. The results of the
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A novel heterotrophic aerobic denitrifying Pseudomonas hunanensis strain DC-2 was screened from the sediments of Lake Dianchi and identified with high nitrification/denitrification ability. Within 30 h, the removal efficiency of ammonium-N and nitrate-N could reach 98.8% and 88.4%, respectively. The results of the single-factor experiments indicated that strain DC-2 exhibited excellent denitrification ability under the conditions of using sodium citrate as the nitrogen source, with an initial pH of 7, a C/N ratio of 10, and a temperature of 30 °C. Nitrogen balance experiments suggested that this strain removed N mainly via assimilation. Moreover, the N removal pathway was explored by genome and enzymatic assays, and a complex nitrogen metabolism pathway was established, including heterotrophic nitrification-aerobic denitrification (HN-AD), assimilatory reduction of nitrate (ANRA), and ammonia assimilation. Additionally, strain DC-2 was immobilized into particles for denitrification, demonstrating excellent efficacy in continuous total nitrogen removal (84.8% for TN). Hence, strain DC-2 demonstrated significant potential in treating real aquaculture wastewater.
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(This article belongs to the Section Wastewater Treatment and Reuse)
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Open AccessArticle
Demonstration of Proactive Algaecide Treatments Targeting Overwintering Cyanobacteria in Sediments of an Urban Pond
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Alyssa Calomeni-Eck, Andrew McQueen, Ciera Kinley-Baird, Elizabeth Smith, Benjamin Growcock, Katlynn Decker, Schad Hampton, Anthony Stahl, Marvin Boyer and Gerard Clyde, Jr.
Water 2024, 16(11), 1624; https://doi.org/10.3390/w16111624 - 6 Jun 2024
Abstract
Most cyanobacteria that form harmful algal blooms (HABs) in inland waterbodies can overwinter in sediments. This field demonstration within an urban pond was conducted to bolster a database on the novel use of algaecide treatments to proactively target overwintering cyanobacteria located in sediments
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Most cyanobacteria that form harmful algal blooms (HABs) in inland waterbodies can overwinter in sediments. This field demonstration within an urban pond was conducted to bolster a database on the novel use of algaecide treatments to proactively target overwintering cyanobacteria located in sediments prior to HAB formation. In March 2023, a peroxide-based algaecide was applied to sediments of a water feature located in urban Kansas City, Kansas, and cyanobacteria responses were measured over subsequent weeks and months. Multiple lines of evidence were used to discern the impacts of proactive treatments on overwintering cells in sediments and HAB severity throughout the growing season. Although results of the measured cyanobacterial responses were mixed, three of five lines of evidence indicated proactive algaecide treatments were effective at decreasing the transfer of cyanobacteria to the water column and HAB severity during months when HABs tended to occur. Microcystin concentrations immediately post-treatment (hours) remained at the analytical detection limit (0.10 µg/L) and were below USEPA risk-based thresholds, highlighting the benefits of application prior to the exponential growth phase of toxin-producing cyanobacteria. These results expand the dataset and methodology for field-scale proactive algaecide applications targeting overwintering cyanobacterial cells in sediment to mitigate and delay HAB development.
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(This article belongs to the Topic Natural Hazards and Environmental Challenges in the Anthropocene Age)
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Open AccessArticle
Research on Intelligent Chemical Dosing System for Phosphorus Removal in Wastewater Treatment Plants
by
Xi Lu, Song Huang, Haichen Liu, Fengwei Yang, Ting Zhang and Xinyu Wan
Water 2024, 16(11), 1623; https://doi.org/10.3390/w16111623 - 6 Jun 2024
Abstract
Whether the phosphorus removal chemical in wastewater treatment plants (WWTPs) can be accurately dosed not only affects the compliance of the effluent total phosphorus but also has a huge impact on sludge production and energy consumption during the wastewater treatment process. For the
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Whether the phosphorus removal chemical in wastewater treatment plants (WWTPs) can be accurately dosed not only affects the compliance of the effluent total phosphorus but also has a huge impact on sludge production and energy consumption during the wastewater treatment process. For the effluent from the secondary sedimentation tank of a wastewater treatment plant in southern China, based on experimental screening of the optimal pH value, chemical types and concentrations of chemicals, coagulation time, etc., a dynamic dosage prediction feedforward model for chemical phosphorus removal agents in the effluent from the secondary sedimentation tank of the WWTPs was developed to predict the most economical dosage of the chemicals. Meanwhile, combined with the adaptive fuzzy neural network P feedback control algorithm, dynamic real-time control of chemical dosing was achieved. Through micro-control design, a software model for signal collection and feedback in a specific phosphorus removal scenario was formed, and an automatic control system for chemical dosing was ultimately developed for a WWTP in a city in southern China. After stable operation for two months, the system achieved a 100% compliance rate for effluent total phosphorus (TP) concentration and a 67% improvement in effluent stability, helping the wastewater treatment plant achieve stable and precise control of the phosphorus removal process in the secondary sedimentation tank effluent, which is conducive to further promoting its implementation of low-carbon pathways.
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(This article belongs to the Special Issue Occurrence, Risk Assessment and Removal of Emerging Contaminants in Aquatic Environment)
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Open AccessArticle
Factors Controlling the Formation and Evolution of a Beach Zone in Front of a Coastal Cliff: The Case of the East Coast of Evia Island in the Aegean Sea, Eastern Mediterranean
by
Serafeim Poulos, Stamatina Lesioti, Aikaterini Karditsa and Christos Angelopoulos
Water 2024, 16(11), 1622; https://doi.org/10.3390/w16111622 - 5 Jun 2024
Abstract
The present study examines the recent evolution of a cliff coast along the Aegean Sea, considering its geotectonic context, oceanographic factors, sediment dynamics, and human impact. Initially, the formation of this coastal stretch was influenced by neotectonic faults, oriented both semi-parallel and diagonally
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The present study examines the recent evolution of a cliff coast along the Aegean Sea, considering its geotectonic context, oceanographic factors, sediment dynamics, and human impact. Initially, the formation of this coastal stretch was influenced by neotectonic faults, oriented both semi-parallel and diagonally relative to the present coastline orientation (NE–SW). Subsequently, the delivery of terrestrial sediment from ephemeral rivers and cliff erosion, along with nearshore wave-induced hydrodynamics have played a secondary role in shaping its current configuration, which includes a beach zone along the base of the cliff. This secondary phase of coastal evolution occurred over the past 4–5 thousand years, coinciding with a period of slow sea level rise (approximately 1 mm/year). Evidence such as uplifted notches and beachrock formations extending to around 5 m water depth suggests intervals of relative sea level stability, interrupted by episodic tectonic events. Anthropogenic interventions, related to both changes in coastal sediment budget and coastal engineering projects, have caused beach erosion, particularly in its central and northern sectors.
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(This article belongs to the Special Issue Coastal Geomorphological Changes from Past to Present)
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Open AccessArticle
Seepage–Deformation Coupling Analysis of a Core Wall Rockfill Dam Subject to Rapid Fluctuations in the Reservoir Water Level
by
Xueqin Zheng, Bin Yan, Wei Wang, Kenan Du and Yixiang Fang
Water 2024, 16(11), 1621; https://doi.org/10.3390/w16111621 - 5 Jun 2024
Abstract
Core wall rockfill dams are susceptible to cracking at the dam’s crest, as well as collapse and settlement of the rockfill during storage and operation periods, particularly due to rapid fluctuations in the water level in pumped storage power stations. Most studies on
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Core wall rockfill dams are susceptible to cracking at the dam’s crest, as well as collapse and settlement of the rockfill during storage and operation periods, particularly due to rapid fluctuations in the water level in pumped storage power stations. Most studies on the impact of fluctuations in the reservoir’s water level on dam deformation have considered fluctuations of less than 5 m/d, while pumped storage power stations experience much larger fluctuations. Additionally, the seepage and stress fields within the dam’s rock and soil interact and influence each other. Few studies have used the coupling theory of seepage and stress to analyze seepage and deformation in core wall rockfill dams. To address these issues, a finite element model using seepage–stress coupling theory was utilized to investigate the variations in the phreatic line, earth pressure, and deformation of a core wall rockfill dam due to rapid fluctuations in the reservoir’s water level. Additionally, the results of the finite element simulation were compared with and analyzed alongside safety monitoring data. The results indicated that, upon a sudden decrease in the reservoir’s water level, there was a lag in the decline of the phreatic line in Rockfill I, which created a large hydraulic gradient, resulting in a reverse seepage field on the dam’s slope surface and generating a drag force directed upstream. Consequently, a significant concentration of stress occurred on one-third of the upstream slope surface of the dam and the seepage curtain, and the increase in horizontal displacement was substantially greater than the increase in settlement from one-third of the rockfill’s height to the dam’s foundation. The deformation was more sensitive to the lowest water level of the reservoir rather than to the fastest rate of decline. Sudden rises in the reservoir’s water level result in decreased horizontal displacements and settlement of the dam. Amid rapid fluctuations of the reservoir’s water level, changes in the vertical earth pressure were more pronounced at the bottom of the core wall than in its midsection. Compared with the core wall, variations in the vertical earth pressure in the upstream and downstream filter layers were minor at similar elevations. A peak horizontal displacement of 6.5 mm was noted at one-third the height of Rockfill I, with the greatest increase in settlement of 3.5 mm at the dam’s crest. To ensure a project’s safety, it is crucial to control the elevation of the lowest point during a sudden drop in the reservoir’s level and to carefully monitor for cracks or voids within approximately one-third of the dam’s height in Rockfill I and at the dam crest. This study’s results provide a scientific basis for assessing core wall rockfill dams’ health and securing long-term safety at pumped storage power facilities.
Full article
(This article belongs to the Special Issue Remote Sensing, Artificial Intelligence and Deep Learning in Hydraulic Structure Safety Monitoring)
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Open AccessReview
A Mini-Review on Safe Treatment and Valorization of Salt Waste in Chemical Production Processes in China
by
Yang Lv, Yi Wang, Dapeng Zhang, Chaoyue Wu, Jun Zhang, Zehua Zhao, Mohammad Nabi, Xuan Luo and Keke Xiao
Water 2024, 16(11), 1620; https://doi.org/10.3390/w16111620 - 5 Jun 2024
Abstract
In chemical production processes in China, a huge volume of salt waste is produced, contributing to environmental pollution due to the lack of proper treatment procedures to manage this waste effectively. With the current lack of proper treatment methods for salt waste disposal,
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In chemical production processes in China, a huge volume of salt waste is produced, contributing to environmental pollution due to the lack of proper treatment procedures to manage this waste effectively. With the current lack of proper treatment methods for salt waste disposal, landfill emerges as the predominant disposal approach adopted in China, exacerbating environmental concerns associated with the accumulation of such waste. In addition, this method fails to reuse and recycle salt waste. This review paper presents pertinent research on the safe disposal and utilization of salt waste in China. Well-known valorization methods, such as oxidation, thermal treatment, washing separation, precipitation, and evaporation crystallization, are comprehensively reviewed. The current technologies for recovering resources from salt waste and recommendations for its treatment and valorization are analyzed. This research work offers a reference for future resource utilization of industrial salt waste.
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(This article belongs to the Special Issue Dissolved Organic Matter in Sludge)
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An Index Used to Evaluate the Applicability of Mid-to-Long-Term Runoff Prediction in a Basin Based on Mutual Information
by
Shuai Xie, Zhilong Xiang, Yongqiang Wang, Biqiong Wu, Keyan Shen and Jin Wang
Water 2024, 16(11), 1619; https://doi.org/10.3390/w16111619 - 5 Jun 2024
Abstract
Accurate and reliable mid-to-long-term runoff prediction (MLTRP) is of great importance in water resource management. However, the MLTRP is not suitable in each basin, and how to evaluate the applicability of MLTRP is still a question. Therefore, the total mutual information (TMI) index
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Accurate and reliable mid-to-long-term runoff prediction (MLTRP) is of great importance in water resource management. However, the MLTRP is not suitable in each basin, and how to evaluate the applicability of MLTRP is still a question. Therefore, the total mutual information (TMI) index is developed in this study based on the predictor selection method using mutual information (MI) and partial MI (PMI). The relationship between the TMI and the predictive performance of five AI models is analyzed by applying five models to 222 forecasting scenarios in Australia. This results in over 222 forecasting scenarios which demonstrate that, compared with the MI, the developed TMI index can better represent the available information in the predictors and has a more significant negative correlation with the RRMSE, with a correlation coefficient between −0.62 and −0.85. This means that the model’s predictive performance will become better along with the increase in TMI, and therefore, the developed TMI index can be used to evaluate the applicability of MLTRP. When the TMI is more than 0.1, the available information in the predictors can support the construction of MLTRP models. In addition, the TMI can be used to partly explain the differences in predictive performance among five models. In general, the complex models, which can better utilize the contained information, are more sensitive to the TMI and have more significant improvement in terms of predictive performance along with the increase in TMI.
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(This article belongs to the Special Issue Application of Big Data and Deep Learning in Hydrological Modelling, Flood and Drought Monitoring)
Open AccessArticle
Application of a Bayesian-Based Integrated Approach for Groundwater Contamination Sources Parameter Identification Considering Observation Error
by
Xueman Yan and Yongkai An
Water 2024, 16(11), 1618; https://doi.org/10.3390/w16111618 - 5 Jun 2024
Abstract
Groundwater contamination source (GCS) parameter identification can help with controlling groundwater contamination. It is proverbial that groundwater contamination concentration observation errors have a significant impact on identification results, but few studies have adequately quantified the specific impact of the errors in contamination concentration
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Groundwater contamination source (GCS) parameter identification can help with controlling groundwater contamination. It is proverbial that groundwater contamination concentration observation errors have a significant impact on identification results, but few studies have adequately quantified the specific impact of the errors in contamination concentration observations on identification results. For this reason, this study developed a Bayesian-based integrated approach, which integrated Markov chain Monte Carlo (MCMC), relative entropy (RE), Multi-Layer Perceptron (MLP), and the surrogate model, to identify the unknown GCS parameters while quantifying the specific impact of the observation errors on identification results. Firstly, different contamination concentration observation error situations were set for subsequent research. Then, the Bayesian inversion approach based on MCMC was used for GCS parameter identification for different error situations. Finally, RE was applied to quantify the differences in the identification results of each GCS parameter under different error situations. Meanwhile, MLP was utilized to build a surrogate model to replace the original groundwater numerical simulation model in the GCS parameter identification processes of these error situations, which was to reduce the computational time and load. The developed approach was applied to two hypothetical numerical case studies involving homogeneous and heterogeneous cases. The results showed that RE could effectively quantify the differences caused by contamination concentration observation errors, and the changing trends of the RE values for GCS parameters were directly related to their sensitivity. The established MLP surrogate model could significantly reduce the computational load and time for GCS parameter identification. Overall, this study highlights that the developed approach represents a promising solution for GCS parameter identification considering observation errors.
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(This article belongs to the Section Water Quality and Contamination)
Open AccessArticle
Using the AIEM and Radarsat-2 SAR to Retrieve Bare Surface Soil Moisture
by
Chengshen Yin, Quanming Liu and Yin Zhang
Water 2024, 16(11), 1617; https://doi.org/10.3390/w16111617 - 5 Jun 2024
Abstract
Taking the Jiefangzha irrigation area of the Inner Mongolia Autonomous Region as the research area, the response relationships between the backscattering coefficient and radar frequency, radar incidence angle, root-mean-square height, correlation length, and soil water content under different conditions were simulated using advanced
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Taking the Jiefangzha irrigation area of the Inner Mongolia Autonomous Region as the research area, the response relationships between the backscattering coefficient and radar frequency, radar incidence angle, root-mean-square height, correlation length, and soil water content under different conditions were simulated using advanced integral equations. The backscattering characteristics of exposed surfaces in cold and dry irrigation areas were discussed, and the reasons for the different effects were analyzed. Based on this, surface roughness models and statistical regression moisture inversion models were constructed through co-polarized backscatter coefficients and combined surface roughness. The correlation between the inverted surface roughness values and the measured values was R2 = 0.7569. The correlation between the soil moisture simulation values and the measured values was R2 = 0.8501, with an RMSE of 0.04. The findings showed a strong correlation between the values from the regression simulation and the measured data, indicating that the model can be applied to soil moisture inversion and has a good inversion accuracy. Compared with previous studies in the same area, the inversion model proposed in this paper has a higher accuracy and is more suitable for the inversion of soil moisture in the Jiefangzha irrigation area. These findings can support research on the water cycle and water environment assessment in the region.
Full article
(This article belongs to the Special Issue Research on Soil Moisture and Irrigation)
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Open AccessArticle
Spatiotemporal Assessment of Water Pollution for Beira Lake, Sri Lanka
by
Sangeeth Prasad, Yuansong Wei, Tushara Chaminda, Tharindu Ritigala, Lijun Yu, K. B. S. N. Jinadasa, H. M. S. Wasana, Suresh Indika, Isuru Yapabandara, Dazhou Hu, Madhubhashini Makehelwala, Sujithra K. Weragoda, Jianfeng Zhu and Zongke Zhang
Water 2024, 16(11), 1616; https://doi.org/10.3390/w16111616 - 5 Jun 2024
Abstract
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Beira Lake, located in Colombo, Sri Lanka, has suffered severe anthropogenic impacts, with previous restoration attempts failing due to a limited understanding of pollutant dynamics. Aiming to fill this gap, a comprehensive study was conducted during dry and wet seasons to assess the
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Beira Lake, located in Colombo, Sri Lanka, has suffered severe anthropogenic impacts, with previous restoration attempts failing due to a limited understanding of pollutant dynamics. Aiming to fill this gap, a comprehensive study was conducted during dry and wet seasons to assess the spatiotemporal water pollution of Beira Lake, employing key physicochemical parameters, numerical indices, and remote sensing analysis. The water pollution index (WPI) results categorize Beira Lake as highly polluted, with WPI values ranging from 2.38 ± 0.92 in the wet season to 2.53 ± 1.32 in the dry season. Comparatively higher COD levels recorded in the Beira Lake network, especially for Gangarama Lake show significant pollution levels during both the dry and wet seasons, e.g., the highest COD levels, at 306.40 mg/L, were observed during the wet season. The Trophic State Index (TSI) results indicate eutrophic and hypereutrophic conditions in Beira Lake, which are particularly pronounced during the wet season. The heavy metal pollution index (HPI) results suggest elevated heavy metal concentrations in Beira Lake, especially in the wet season. Combined with field investigation results, a remote sensing data analysis between 2016 and 2023 reveals significant improvements in water transparency, suggesting positive effects of recent management interventions. Parameters demanding attention include COD, nitrate, and total phosphate levels due to their consistent exceedance of permissible limits. The PCA results of indices correlations between wet and dry seasons offer valuable insights into the complex dynamics of Beira Lake’s water quality. The study makes recommendations for restoring Beira Lake, including stringent pollution controls, regular dredging, green infrastructure implementation, implementing new rules and regulations, and community engagement.
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Open AccessArticle
Integrated Assessment of Ecological Quality Combining Biological and Environmental Data in the Yellow River Estuary
by
Xin Gao, Wen Li, Yunlei Zhang, Hongjun Song, Ying Li and Hongjun Li
Water 2024, 16(11), 1615; https://doi.org/10.3390/w16111615 - 5 Jun 2024
Abstract
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The integrated assessment of ecological quality in estuarine ecosystems holds significant importance for environmental management. Previous monitoring programs predominantly focused on environmental data, lacking a comprehensive quality assessment approach. To address this gap, this study aimed to integrate environmental factors with macrofaunal community
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The integrated assessment of ecological quality in estuarine ecosystems holds significant importance for environmental management. Previous monitoring programs predominantly focused on environmental data, lacking a comprehensive quality assessment approach. To address this gap, this study aimed to integrate environmental factors with macrofaunal community information to evaluate the ecological quality status of the Yellow River Estuary. A total of 13 stations were routinely monitored in August for four consecutive years to collect environmental and biological data. Candidate indicators were screened based on variation coefficients, distribution ranges, and redundancy analysis, identifying 16 indicators belonging to three categories (i.e., seawater, sediment, and biology). The model fit and the interrelationship of the components were determined using structural equation modelling (SEM). The main results were as follows. (1) A total of 144 macrofaunal taxa, belonging to eight animal phyla and 98 families, were identified, with a dominance of Annelida (37.8%) and Mollusca (33.3%). The environmental variables most strongly correlated with the macrofaunal community were TOC, DO, Cd, and Md. (2) NO2 and heavy metals represented the two most direct factors of environmental pollution, while the factor load of biodiversity indices (H’, J, and D) was large in the biology category. (3) The evaluation results indicated that 78.85% of the total samples were between the average and upper levels of ecological quality, but only 7.69% of samples were at the “high” level. The framework system for the evaluation of ecological quality constructed in this study provides a theoretical and practical basis for the evaluation of the effectiveness of conservation management of the Yellow River Estuary.
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