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
Analysis of Unsteady Internal Flow and Its Induced Structural Response in a Circulating Water Pump
Water 2024, 16(9), 1294; https://doi.org/10.3390/w16091294 (registering DOI) - 02 May 2024
Abstract
As critical equipment in nuclear power systems, the stability of circulating water pumps (CWP) directly impacts the efficiency of power plants. To investigate the impact mechanisms of the unsteady flow characteristics and flow-induced forces on the rotation system, numerical simulation methods were employed
[...] Read more.
As critical equipment in nuclear power systems, the stability of circulating water pumps (CWP) directly impacts the efficiency of power plants. To investigate the impact mechanisms of the unsteady flow characteristics and flow-induced forces on the rotation system, numerical simulation methods were employed to calculate the internal flow of a volute mixed-flow CWP under different flow rates (0.8Qd, 1.0Qd, 1.2Qd). The flow field results indicate that, under the part-load condition, the flow within the volute is chaotic with high energy losses, while under the over-load condition, there is a significant velocity gradient within the impeller, leading to relatively severe flow losses. Additionally, the rotor–stator interface is a major factor in flow-induced pulsations, and the asymmetric pressure distribution within the volute results in radial force imbalance. The finite element method (FEM) results indicate that the position of maximum stress on the pump shaft is closely related to the ratio of radial and axial force. Increasing the flow rate appropriately has been noted to be advantageous in reducing flow-induced forces and their amplitude, consequently diminishing the forces on the rotation system and improving the long-term operational stability of the CWP.
Full article
(This article belongs to the Section Hydraulics and Hydrodynamics)
►
Show Figures
Open AccessCommunication
Modeling of Biofoam Destabilization by Biodefoamers in Poultry Slaughterhouse Wastewater Treatment Activated Sludge
by
Cynthia Dlangamandla, Ncumisa Mpongwana, Seteno K. O. Ntwampe, Moses Basitere and Boredi S. Chidi
Water 2024, 16(9), 1293; https://doi.org/10.3390/w16091293 - 01 May 2024
Abstract
Biofoam formation in wastewater treatment is a challenge globally. Previously, we successfully proposed the use of biodefoamers instead of synthetic defoamers for environmental protection. In this study, we report on biodefoamation modeling using activated sludge organisms. Overall, the rate law model was determined
[...] Read more.
Biofoam formation in wastewater treatment is a challenge globally. Previously, we successfully proposed the use of biodefoamers instead of synthetic defoamers for environmental protection. In this study, we report on biodefoamation modeling using activated sludge organisms. Overall, the rate law model was determined to adequately describe foam drainage including collapse while applying biodefoamers. The target industry is the poultry processing industry whereby foam formation during wastewater treatment is an ongoing challenge.
Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
►▼
Show Figures
Figure 1
Open AccessArticle
Mine Wastewater Effect on the Aquatic Diversity and the Ecological Status of the Watercourses in Southern Poland
by
Krzysztof Mitko, Piotr Dydo, Andrzej K. Milewski, Joanna Bok-Badura, Agata Jakóbik-Kolon, Tomasz Krawczyk, Anna Cieplok, Mariola Krodkiewska, Aneta Spyra, Grzegorz Gzyl, Anna Skalny, Beata Kończak, Maria Bałazińska, Paweł Łabaj, Anna Tetłak, Maria Kyriazi and Stavroula Klempetsani
Water 2024, 16(9), 1292; https://doi.org/10.3390/w16091292 - 01 May 2024
Abstract
►▼
Show Figures
Coal mining activity contributes to energy security and employment occupation, but is associated with environmental deterioration. Coal combustion leads to GHG emissions, while coal mining results in the generation of saline effluents. These effluents are discharged in inland surface waters, applying significant pressure
[...] Read more.
Coal mining activity contributes to energy security and employment occupation, but is associated with environmental deterioration. Coal combustion leads to GHG emissions, while coal mining results in the generation of saline effluents. These effluents are discharged in inland surface waters, applying significant pressure on their quality, with a negative impact on aquatic life and the economy of a region. This study includes water samples that were analyzed in order to investigate the organic compounds, heavy metals, and other physicochemical parameters. Biological monitoring was done according to the Water Framework Directive methodology. The results from an aquatic area in Southern Poland, which indirectly receives coal mine effluents, indicate elevated salinity with excessive chlorides, sulfates, and sodium ions. The water quality of another non-polluted aquatic area was also assessed to examine the impact of indirect coal mine wastewater discharge on this area. The high salinity levels hinder the use of river water for drinking, agricultural, or industrial purposes. The results obtained show high pressure on the ecological status of streams and rivers that receive mine effluents, and on the density and diversity of aquatic invertebrates. This pressure is clearly visible in the structure of benthic communities and in invertebrate diversity. It also contributes to the appearance of invasive species and increasing water salinity. Limiting discharges of mine water transporting large loads of saline substances would reduce the negative impact on the quality of river waters and biological life.
Full article
Figure 1
Open AccessArticle
Evaluating the Water Quality of the Keddara Dam (Algeria) Using Water Quality Indices
by
Tosin Sarah Fashagba, Madani Bessedik, Nadia Badr ElSayed, Chérifa Abdelbaki and Navneet Kumar
Water 2024, 16(9), 1291; https://doi.org/10.3390/w16091291 - 01 May 2024
Abstract
Dams are regarded as crucial pieces of structure that store water for irrigation and municipal uses. Given their vital role, the dam’s water quality assessment is considered to be an important criterion and requires constant monitoring. In this research, we attempted to use
[...] Read more.
Dams are regarded as crucial pieces of structure that store water for irrigation and municipal uses. Given their vital role, the dam’s water quality assessment is considered to be an important criterion and requires constant monitoring. In this research, we attempted to use two water quality indices (WQIs) methods to assess the water quality of the Keddara Dam, which is located on the Boudouaou River, Algeria, using eleven water quality parameters (temperature, pH, conductivity, turbidity, total suspended solids (TSS), full alkalimetric title (TAC), hydrometric title (TH), nitrite ions (NO2−), nitrate ions (NO3−), ammonium ions (NH4+), and phosphate ions (PO43−)) for data recorded from 29 December 2018 to 3 June 2021. Application of The Canadian Council of Ministers of the Environment (CCME) WQIs and the Weighted Arithmetic Method (WAM) indicated that the Keddara Dam’s water quality parameters were within the WHO’s permissible level, except for the conductivity and turbidity values. The results of the CCME WQI ranged from acceptable (81.92) to excellent (95.08) quality, whereas the WAM WQI ranged from 9.52 to 17.77, indicating excellent quality. This demonstrates that the Keddara Dam is appropriate for agriculture and municipal use. The water quality indices (WQIs) methods are recommended as valuable tools that allow both the public and decision-makers to comprehend and manage the water quality of any aquatic environment by providing flexibility in choosing variables.
Full article
(This article belongs to the Special Issue Water Quality Assessment of River Basins)
►▼
Show Figures
Figure 1
Open AccessArticle
Methods for Constructing a Refined Early-Warning Model for Rainstorm-Induced Waterlogging in Historic and Cultural Districts
by
Jing Wu, Junqi Li, Xiufang Wang, Lei Xu, Yuanqing Li, Jing Li, Yao Zhang and Tianchen Xie
Water 2024, 16(9), 1290; https://doi.org/10.3390/w16091290 (registering DOI) - 30 Apr 2024
Abstract
Against the backdrop of increasingly severe global climate change, the risk of rainstorm-induced waterlogging has become the primary threat to the safety of historic and cultural districts worldwide. This paper focuses on the historic and cultural districts of Beijing, China, and explores techniques
[...] Read more.
Against the backdrop of increasingly severe global climate change, the risk of rainstorm-induced waterlogging has become the primary threat to the safety of historic and cultural districts worldwide. This paper focuses on the historic and cultural districts of Beijing, China, and explores techniques and methods for identifying extreme rainstorm warnings in cultural heritage areas. Refined warning and forecasting have become important non-engineering measures to enhance these districts’ waterlogging prevention control and emergency management capabilities. This paper constructs a rainstorm-induced waterlogging risk warning model tailored for Beijing’s historical and cultural districts. This model system encompasses three sets of models: a building waterlogging early-warning model, a road waterlogging early-warning model, and a public evacuation early-warning model. During the construction of the model, the core concepts and determination methods of “1 h rainfall intensity water logging index” and “the waterlogging risk index in historical and cultural districts” were proposed. The construction and application of the three models take into full account the correlation between rainfall intensity and rainwater accumulation, while incorporating the characteristics of flood resilience in buildings, roads, and the society in districts. This allows for a precise grading of warning levels, leading to the formulation of corresponding warning response measures. Empirical tests have shown that the construction method proposed in this paper is reliable. The innovative results not only provide a new perspective and method for the early-warning of rainstorm-induced waterlogging, but also offer scientific support for emergency planning and response in historical and cultural districts.
Full article
(This article belongs to the Section Urban Water Management)
Open AccessArticle
Optimizing the Extraction of Sugars from Sewage Sludge Using Ultrasound Combined with Thermal–Alkali
by
Yujie Fan, Qunshuai Li, Frederico Gomes Fonseca, Jianyang Song and Miao Gong
Water 2024, 16(9), 1289; https://doi.org/10.3390/w16091289 (registering DOI) - 30 Apr 2024
Abstract
The extraction and utilization of sugars from readily available and cost-effective sewage sludge increases the economic potential of this residue, contributing to sustainable urban development. The work presented here presents a novel method in which sugars can be directly extracted from sewage sludge
[...] Read more.
The extraction and utilization of sugars from readily available and cost-effective sewage sludge increases the economic potential of this residue, contributing to sustainable urban development. The work presented here presents a novel method in which sugars can be directly extracted from sewage sludge following an ultrasound + thermal–alkali pretreatment. The best results indicated that by subjecting the sludge to a 240 W ultrasound for 20 min, followed by alkali digestion using 6 mL of a 2 M NaOH solution at 48 °C for 60 min, it was possible to maximize the yield of crude sugar (34.22 wt.% dry) with the purity of crude sugar at 46.80%, reaching an extraction efficiency of 99.84%. Response surface methodology was used to optimize the crude sugar yields based on experimental data, reaching a value of 34.67 wt.% dry when employing an ultrasound exposure time of 12.5 min and 6 mL of the NaOH solution for a digestion time of 57.5 min; these results were considered consistent with the experimental data.
Full article
(This article belongs to the Special Issue Sewage Sludge: Treatment and Recovery)
►▼
Show Figures
Graphical abstract
Open AccessArticle
Water Stable Isotopes in the Central Altai Mountainous Rivers as Indicator of Glacier Meltwater Fraction in Runoff
by
Dmitrii Bantcev, Valeriia Rasputina, Anaiit Ovsepian, Semyon Griga, Anna Kozachek, Kirill Tchikhatchev and Dmitrii Ganyushkin
Water 2024, 16(9), 1288; https://doi.org/10.3390/w16091288 - 30 Apr 2024
Abstract
We used stable water isotopes (δ 18O and δ 2H) to identify the fractions of glacier meltwater and summer precipitation in the runoff in the Taldura River in the Altai mountains. The mean isotopic characteristics of glacier ice, snow, summer precipitation
[...] Read more.
We used stable water isotopes (δ 18O and δ 2H) to identify the fractions of glacier meltwater and summer precipitation in the runoff in the Taldura River in the Altai mountains. The mean isotopic characteristics of glacier ice, snow, summer precipitation and river water were obtained. Using isotopic separation of hydrographs, we determined that glacier feeding completely prevails throughout the Taldura River in the middle of the ablation season. In general, the fraction of glacier meltwater in the Taldura River’s runoff in the ablation season varies from 80% to 95% depending on local weather conditions.
Full article
(This article belongs to the Topic Analysis and Separations of Trace Elements in the Environment)
Open AccessArticle
A Deformation Analysis Method for Sluice Structure Based on Panel Data
by
Zekai Ma, Benxing Lou, Zhenzhong Shen, Fuheng Ma, Xiang Luo, Wei Ye, Xing Li and Dongze Li
Water 2024, 16(9), 1287; https://doi.org/10.3390/w16091287 (registering DOI) - 30 Apr 2024
Abstract
Deformation, as the most intuitive index, can reflect the operation status of hydraulic structures comprehensively, and reasonable analysis of deformation behavior has important guiding significance for structural long-term service. Currently, the health evaluation of dam deformation behavior has attracted widespread attention and extensive
[...] Read more.
Deformation, as the most intuitive index, can reflect the operation status of hydraulic structures comprehensively, and reasonable analysis of deformation behavior has important guiding significance for structural long-term service. Currently, the health evaluation of dam deformation behavior has attracted widespread attention and extensive research from scholars due to its great importance. However, given that the sluice is a low-head hydraulic structure, the consequences of its failure are easily overlooked without sufficient attention. While the influencing factors of the sluice’s deformation are almost identical to those of a concrete dam, nonuniform deformation is the key issue in the sluice’s case because of the uneven property of the external load and soil foundation, and referencing the traditional deformation statistical model of a concrete dam cannot directly represent the nonuniform deformation behavior of a sluice. In this paper, we assume that the deformation at various positions of the sluice consist of both overall and individual effects, where overall effect values describe the deformation response trend of the sluice structure under external loads, and individual effect values represent the degree to which the deformation of a single point deviates from the overall deformation. Then, the random coefficient model of panel data is introduced into the analysis of sluice deformation to handle the unobservable overall and individual effects. Furthermore, the maximum entropy principle is applied, both to approximate the probability distribution function of individual effect extreme values and to determine the early warning indicators, completing the assessment and analysis of the nonuniform deformation state. Finally, taking a project as an example, we show that the method proposed can effectively identify the overall deformation trend of the sluice and the deviation degree of each measuring point from the overall deformation, which provides a novel approach for sluice deformation behavior research.
Full article
(This article belongs to the Special Issue Remote Sensing, Artificial Intelligence and Deep Learning in Hydraulic Structure Safety Monitoring)
►▼
Show Figures
Figure 1
Open AccessArticle
Flood Water Depth Prediction with Convolutional Temporal Attention Networks
by
Priyanka Chaudhary, João P. Leitão, Konrad Schindler and Jan Dirk Wegner
Water 2024, 16(9), 1286; https://doi.org/10.3390/w16091286 - 30 Apr 2024
Abstract
►▼
Show Figures
Robust and accurate flood hazard maps are essential for early warning systems and flood risk management. Although physically based models are effective in estimating pluvial flooding, the computational burden makes them difficult to use for real-time flood prediction. In contrast, data-driven models can
[...] Read more.
Robust and accurate flood hazard maps are essential for early warning systems and flood risk management. Although physically based models are effective in estimating pluvial flooding, the computational burden makes them difficult to use for real-time flood prediction. In contrast, data-driven models can provide faster flood predictions if trained offline. While most studies have focused on predicting maximum water depth, in this study, we predict pixel-wise water depth maps for entire catchments at a lead time of 2 h. To that end, we propose a deep learning approach that uses a sequence encoding network with temporal self-attention. We also adapt the popular hydrological performance metric Nash–Sutcliffe efficiency (NSE) as our loss function. We test the effectiveness and generalizability of our method using a new dataset called SwissFlood, which consists of 100 catchments and 1500 rainfall events extracted from real observations in Switzerland. Our method produces 2 m spatial resolution flood maps with absolute error as low as 27 cm for water depth exceeding 1 m.
Full article
Figure 1
Open AccessArticle
A Case Study and Numerical Modeling of Post-Wildfire Debris Flows in Montecito, California
by
Diwakar K. C., Mohammad Wasif Naqvi and Liangbo Hu
Water 2024, 16(9), 1285; https://doi.org/10.3390/w16091285 - 30 Apr 2024
Abstract
Wildfires and their long-term impacts on the environment have become a major concern in the last few decades, in which climate change and enhanced anthropogenic activities have gradually led to increasingly frequent events of such hazards or disasters. Geological materials appear to become
[...] Read more.
Wildfires and their long-term impacts on the environment have become a major concern in the last few decades, in which climate change and enhanced anthropogenic activities have gradually led to increasingly frequent events of such hazards or disasters. Geological materials appear to become more vulnerable to hazards including erosion, floods, landslides and debris flows. In the present study, the well-known 2017 wildfire and subsequent 2018 debris flows in the Montecito area of California are examined. It is found that the post-wildfire debris flows were initiated from erosion and entrainment processes and triggered by intense rainfall. The significant debris deposition in four major creeks in this area is investigated. Numerical modeling of the post-wildfire debris flows is performed by employing a multi-phase mass flow model to simulate the growth in the debris flows and eventual debris deposition. The debris-flow-affected areas estimated from the numerical simulations fairly represent those observed in the field. Overall, the simulated debris deposits are within 7% error of those estimated based on field observations. A similar simulation of the pre-wildfire scenario indicates that the debris would be much less significant. The present study shows that proper numerical simulations can be a promising tool for estimating post-wildfire erosion and the debris-affected areas for hazard assessment and mitigation.
Full article
(This article belongs to the Special Issue Flowing Mechanism of Debris Flow and Engineering Mitigation)
►▼
Show Figures
Figure 1
Open AccessArticle
Daily Streamflow Forecasting Using Networks of Real-Time Monitoring Stations and Hybrid Machine Learning Methods
by
Yue Zhang, Zimo Zhou, Ying Deng, Daiwei Pan, Jesse Van Griensven Thé, Simon X. Yang and Bahram Gharabaghi
Water 2024, 16(9), 1284; https://doi.org/10.3390/w16091284 - 30 Apr 2024
Abstract
Considering the increased risk of urban flooding and drought due to global climate change and rapid urbanization, the imperative for more accurate methods for streamflow forecasting has intensified. This study introduces a pioneering approach leveraging the available network of real-time monitoring stations and
[...] Read more.
Considering the increased risk of urban flooding and drought due to global climate change and rapid urbanization, the imperative for more accurate methods for streamflow forecasting has intensified. This study introduces a pioneering approach leveraging the available network of real-time monitoring stations and advanced machine learning algorithms that can accurately simulate spatial–temporal problems. The Spatio-Temporal Attention Gated Recurrent Unit (STA-GRU) model is renowned for its computational efficacy in forecasting streamflow events with a forecast horizon of 7 days. The novel integration of the groundwater level, precipitation, and river discharge as predictive variables offers a holistic view of the hydrological cycle, enhancing the model’s accuracy. Our findings reveal that for a 7-day forecasting period, the STA-GRU model demonstrates superior performance, with a notable improvement in mean absolute percentage error (MAPE) values and R-square ( ) alongside reductions in the root mean squared error (RMSE) and mean absolute error (MAE) metrics, underscoring the model’s generalizability and reliability. Comparative analysis with seven conventional deep learning models, including the Long Short-Term Memory (LSTM), the Convolutional Neural Network LSTM (CNNLSTM), the Convolutional LSTM (ConvLSTM), the Spatio-Temporal Attention LSTM (STA-LSTM), the Gated Recurrent Unit (GRU), the Convolutional Neural Network GRU (CNNGRU), and the STA-GRU, confirms the superior predictive power of the STA-LSTM and STA-GRU models when faced with long-term prediction. This research marks a significant shift towards an integrated network of real-time monitoring stations with advanced deep-learning algorithms for streamflow forecasting, emphasizing the importance of spatially and temporally encompassing streamflow variability within an urban watershed’s stream network.
Full article
(This article belongs to the Special Issue Managing Impacts on Baseflows in Streams and the Associated Impacts on Ecosystems and Water Quality)
►▼
Show Figures
Figure 1
Open AccessArticle
The Use of Boosted Regression Trees to Predict the Occurrence and Quantity of Staphylococcus aureus in Recreational Marine Waterways
by
Bridgette F. Froeschke, Michelle Roux-Osovitz, Margaret L. Baker, Ella G. Hampson, Stella L. Nau and Ashley Thomas
Water 2024, 16(9), 1283; https://doi.org/10.3390/w16091283 - 30 Apr 2024
Abstract
Microbial monitoring in marine recreational waterways often overlooks environmental variables associated with pathogen occurrence. This study employs a predictive boosted regression trees (BRT) model to predict Staphylococcus aureus abundance in the Tampa Bay estuary and identify related environmental variables associated with the microbial
[...] Read more.
Microbial monitoring in marine recreational waterways often overlooks environmental variables associated with pathogen occurrence. This study employs a predictive boosted regression trees (BRT) model to predict Staphylococcus aureus abundance in the Tampa Bay estuary and identify related environmental variables associated with the microbial pathogen’s occurrence. We provide evidence that the BRT model’s adaptability and ability to capture complex interactions among predictors make it invaluable for research on microbial indicator research. Over 18 months, water samples from 7 recreational sites underwent microbial quantitation and S. aureus isolation, followed by genetic validation. BRT analysis of S. aureus occurrence and environmental variables revealed month, precipitation, salinity, site, temperature, and year as relevant predictors. In addition, the BRT model accurately predicted S. aureus occurrence, setting a precedent for pathogen–environment research. The approach described here is novel and informs proactive management strategies and community health initiatives in marine recreational waterways.
Full article
(This article belongs to the Section Oceans and Coastal Zones)
►▼
Show Figures
Figure 1
Open AccessArticle
Proper Orthogonal Decomposition Based Response Analysis of Inlet Distortion on a Waterjet Pump
by
Puyu Cao, Rui Yue, Jinfeng Zhang, Xinrui Liu, Gang Wu and Rui Zhu
Water 2024, 16(9), 1282; https://doi.org/10.3390/w16091282 - 29 Apr 2024
Abstract
This study addresses the challenge of performance degradation in waterjet pumps due to non-uniform suction flow. Utilizing the Proper Orthogonal Decomposition (POD) method, it decomposes and reconstructs the flow features within a waterjet pump under non-uniform inflow into a series of modes ranked
[...] Read more.
This study addresses the challenge of performance degradation in waterjet pumps due to non-uniform suction flow. Utilizing the Proper Orthogonal Decomposition (POD) method, it decomposes and reconstructs the flow features within a waterjet pump under non-uniform inflow into a series of modes ranked in descending order of energy. By analyzing the modes with dominant energy, which contain complex information about the flow field, it is revealed that modes 1 and 2 predominantly represent the formation of a concentrated vortex, whereas modes 3 and 4 illustrate its spatial offset. Notably, in the hub section, mode 3 exhibits a delayed flow separation caused by the reduction of circumferential vortex (CV), with a consequent lift in blade loading at the leading edge and a higher head compared to mode 1. In the shroud section, the delayed flow separation in mode 3 suppressed reverse flow and the concentrated separation vortex (CSV) and then increased the blade loading, ultimately enhancing the pump head. The findings provide significant insights into optimizing waterjet pump performance by detailing the interactions between various flow structures and pump components, effectively filling a knowledge gap in applying dimensionality reduction techniques within the distorted flow fields of water jet pumps.
Full article
(This article belongs to the Special Issue Design and Optimization of Fluid Machinery)
Open AccessArticle
Effective Degradation of 1,4-Dioxane by UV-Activated Persulfate: Mechanisms, Parameters and Environmental Impacts
by
Xiuneng Zhu, Jie Qiu, Yexing Wang, Yulin Tang and Yongji Zhang
Water 2024, 16(9), 1281; https://doi.org/10.3390/w16091281 - 29 Apr 2024
Abstract
There is more and more research focusing on the removal of dioxane by advanced oxidation technology at this stage, and this study investigated the efficacy of an advanced oxidation system with UV-activated persulfate (UV/PDS). This method had the advantages of fast reaction rate,
[...] Read more.
There is more and more research focusing on the removal of dioxane by advanced oxidation technology at this stage, and this study investigated the efficacy of an advanced oxidation system with UV-activated persulfate (UV/PDS). This method had the advantages of fast reaction rate, simple equipment and convenient operation. Free radical quenching test and electron paramagnetic resonance (EPR) analysis showed that the main active radicals in the reaction system were and ·OH. This study also investigated that the optimal parameters were the initial PDS dosage of 3 mM, the UV intensity of 0.190 mM/cm2, the pH between 5 and 7 and the initial dioxane concentration of 50 mg/L. Additionally, after a reaction time of 150 min, the total organic carbon (TOC) content still remained at 83.53%, which revealed that the mineralization degree of organic matter was not fully achieved through UV/PDS treatment. The concentration of in the reaction system was 74.69 mg·L−1, which complied with the standard concentration specified. Furthermore, the cytotoxicity of the system exhibited an initial increase followed by a subsequent decrease, under the influence of the intermediates. It showed that the technology could efficiently degrade organic pollutants.
Full article
(This article belongs to the Section Water Quality and Contamination)
►▼
Show Figures
Figure 1
Open AccessArticle
Characterization of a Contaminated Site Using Hydro-Geophysical Methods: From Large-Scale ERT Surface Investigations to Detailed ERT and GPR Cross-Hole Monitoring
by
Mirko Pavoni, Jacopo Boaga, Luca Peruzzo, Ilaria Barone, Benjamin Mary and Giorgio Cassiani
Water 2024, 16(9), 1280; https://doi.org/10.3390/w16091280 - 29 Apr 2024
Abstract
This work presents the results of an advanced geophysical characterization of a contaminated site, where a correct understanding of the dynamics in the unsaturated zone is fundamental to evaluate the effective management of the remediation strategies. Large-scale surface electrical resistivity tomography (ERT) was
[...] Read more.
This work presents the results of an advanced geophysical characterization of a contaminated site, where a correct understanding of the dynamics in the unsaturated zone is fundamental to evaluate the effective management of the remediation strategies. Large-scale surface electrical resistivity tomography (ERT) was used to perform a preliminary assessment of the structure in a thick unsaturated zone and to detect the presence of a thin layer of clay supporting an overlying thin perched aquifer. Discontinuities in this clay layer have an enormous impact on the infiltration processes of both water and solutes, including contaminants. In the case here presented, the technical strategy is to interrupt the continuity of the clay layer upstream of the investigated site in order to prevent most of the subsurface water flow from reaching the contaminated area. Therefore, a deep trench was dug upstream of the site and, in order to evaluate the effectiveness of this approach in facilitating water infiltration into the underlying aquifer, a forced infiltration experiment was carried out and monitored using ERT and ground-penetrating radar (GPR) measurements in a cross-hole time-lapse configuration. The results of the forced infiltration experiment are presented here, with a particular emphasis on the contribution of hydro-geophysical methods to the general understanding of the subsurface water dynamics at this complex site.
Full article
(This article belongs to the Special Issue Application of Geophysical Methods for Hydrogeology)
Open AccessArticle
Prediction of Diffuse Attenuation Coefficient Based on Informer: A Case Study of Hangzhou Bay and Beibu Gulf
by
Rongyang Cai, Miao Hu, Xiulin Geng, Mohammed Khalil Ibrahim and Chunhui Wang
Water 2024, 16(9), 1279; https://doi.org/10.3390/w16091279 - 29 Apr 2024
Abstract
Marine water quality significantly impacts human livelihoods and production such as fisheries, aquaculture, and tourism. Satellite remote sensing facilitates the predictions of large-area marine water quality without the need for frequent field work and sampling. Prediction of diffuse attenuation coefficient (Kd), which describes
[...] Read more.
Marine water quality significantly impacts human livelihoods and production such as fisheries, aquaculture, and tourism. Satellite remote sensing facilitates the predictions of large-area marine water quality without the need for frequent field work and sampling. Prediction of diffuse attenuation coefficient (Kd), which describes the speed at which light decays as it travels through water, obtained from satellite-derived ocean color products can reflect the overall water quality trends. However, current models inadequately explore the complex nonlinear features of Kd, and there are difficulties in achieving accurate long-term predictions and optimal computational efficiency. This study innovatively proposes a model called Remote Sensing-Informer-based Kd Prediction (RSIKP). The proposed RSIKP is characterized by a distinctive Multi-head ProbSparse self-attention mechanism and generative decoding structure. It is designed to comprehensively and accurately capture the long-term variation characteristics of Kd in complex water environments while avoiding error accumulation, which has a significant advantage in multi-dataset experiments due to its high efficiency in long-term prediction. A multi-dataset experiment is conducted at different prediction steps, using 70 datasets corresponding to 70 study areas in Hangzhou Bay and Beibu Gulf. The results show that RSIKP outperforms the five prediction models based on Artificial Neural Networks (ANN, Convolutional Neural Networks (CNN), Gated Recurrent Unit (GRU), Long Short-Term Memory Recurrent Neural Networks (LSTM-RNN), and Long Short-Term Memory Networks (LSTM)). RSIKP captures the complex influences on Kd more effectively to achieve higher prediction accuracy compared to other models. It shows a mean improvement of 20.6%, 31.1%, and 22.9% on Mean Absolute Error (MAE), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE). Particularly notable is its outstanding performance in the long time-series predictions of 60 days. This study develops a cost-effective and accurate method of marine water quality prediction, providing an effective prediction tool for marine water quality management.
Full article
(This article belongs to the Special Issue Application of Satellite Remote Sensing in Water Quality Monitoring)
Open AccessArticle
Gas Fracturing Simulation of Shale-Gas Reservoirs Considering Damage Effects and Fluid–Solid Coupling
by
Enze Qi, Fei Xiong, Yun Zhang, Linchao Wang, Yi Xue and Yingpeng Fu
Water 2024, 16(9), 1278; https://doi.org/10.3390/w16091278 - 29 Apr 2024
Abstract
With the increasing demand for energy and the depletion of traditional resources, the development of alternative energy sources has become a critical issue. Shale gas, as an abundant and widely distributed resource, has great potential as a substitute for conventional natural gas. However,
[...] Read more.
With the increasing demand for energy and the depletion of traditional resources, the development of alternative energy sources has become a critical issue. Shale gas, as an abundant and widely distributed resource, has great potential as a substitute for conventional natural gas. However, due to the low permeability of shale-gas reservoirs, efficient extraction poses significant challenges. The application of hydraulic fracturing technology has been proven to effectively enhance rock permeability, but the influence of environmental factors on its efficiency remains unclear. In this study, we investigate the impact of gas fracturing on shale-gas extraction efficiency under varying environmental conditions using numerical simulations. Our simulations provide a comprehensive analysis of the physical changes that occur during the fracturing process, allowing us to evaluate the effects of gas fracturing on rock mechanics and permeability. We find that gas fracturing can effectively induce internal fractures within the rock, and the magnitude of tensile stress decreases gradually during the process. The boundary pressure of the rock mass is an important factor affecting the effectiveness of gas fracturing, as it exhibits an inverse relationship with the gas content present within the rock specimen. Furthermore, the VL constant demonstrates a direct correlation with gas content, while the permeability and PL constant exhibit an inverse relationship with it. Our simulation results provide insights into the optimization of gas fracturing technology under different geological parameter conditions, offering significant guidance for its practical applications.
Full article
(This article belongs to the Section Hydraulics and Hydrodynamics)
Open AccessArticle
Denitrification Performance and Microbiological Mechanisms Using Polyglycolic Acid as a Carbon Source
by
Zhichao Wang, Chenxi Li, Wenhuan Yang, Yuxia Wei and Weiping Li
Water 2024, 16(9), 1277; https://doi.org/10.3390/w16091277 - 29 Apr 2024
Abstract
When treating municipal wastewater, nitrogen removal is often limited due to low C/N, which needs to be compensated for by additional carbon source injections. This study investigated the feasibility of using industrial-waste polyglycolic acid (PGA) as a carbon source for denitrification in an
[...] Read more.
When treating municipal wastewater, nitrogen removal is often limited due to low C/N, which needs to be compensated for by additional carbon source injections. This study investigated the feasibility of using industrial-waste polyglycolic acid (PGA) as a carbon source for denitrification in an SBR to obtain an economical carbon source. The results revealed that an optimal denitrification performance in a methanol-fed activated sludge system was achieved with a PGA dosage of 1.2 mL/L, a pH of 7–8, and a dissolved-oxygen (DO) concentration of 3 ± 0.5 mg/L. Under these conditions, all quality parameters for effluent water met the required criteria [COD < 50 mg/L; TN < 15 mg/L; NH4+-N < 5(8) mg/L]. PGA enhanced the variety and richness of microbial communities, thereby markedly increasing the relative abundance of major phyla such as Proteobacteria and Bacteroidota and major genera such as Paracoccus and Dechloromonas. Furthermore, PGA upregulated the expression of nitrogen-metabolism-related genera, including amo, hao, nar, and nor, which improved the denitrification performance of the system. This study provides a reference for applying PGA as a carbon source for low-C/N-wastewater treatment and solid-waste utilization.
Full article
(This article belongs to the Special Issue Biological Wastewater Treatment Process and Nutrient Recovery)
►▼
Show Figures
Figure 1
Open AccessArticle
HYPOSO Map Viewer: A Web-Based Atlas of Small-Scale Hydropower for Selected African and Latin American Countries
by
Petras Punys, Linas Jurevičius and Andrius Balčiūnas
Water 2024, 16(9), 1276; https://doi.org/10.3390/w16091276 - 29 Apr 2024
Abstract
In many countries, the advancement of hydropower resources has been hindered by economic factors and insufficient data on topography, streamflow, environmental sensitivity, power grid, and, most importantly, the location of potential hydropower sites. This challenge is particularly pronounced in certain African and Latin
[...] Read more.
In many countries, the advancement of hydropower resources has been hindered by economic factors and insufficient data on topography, streamflow, environmental sensitivity, power grid, and, most importantly, the location of potential hydropower sites. This challenge is particularly pronounced in certain African and Latin American river systems. Developing web-based maps of hydropower resources based on geographic information systems and advanced mapping technologies can facilitate the initial assessment of hydropower sites. This is especially relevant for developing sites in remote areas and data-scarce regions. The available geospatial datasets, remote sensing technologies, and advanced GIS modelling techniques can be used to identify potential hydropower sites and assess their preliminary characteristics. This paper reviews web-based hydropower atlases in African and Latin American countries. Their main features are represented and compared with the recently launched HYPOSO map viewer covering two African countries (Cameroon and Uganda) and three Latin American countries (Bolivia, Colombia, and Ecuador). This hydropower atlas consists of 20 spatial layers. Its particular focus is to present a geospatial dataset of new hydropower sites with concise information for potential investors. These so-called virtual hydropower atlases can be only one type of discovery at the early project stage, automatically identifying sites worthy of further investigation. A formal validation of the web-based atlases, including the HYPOSO hydropower atlas, is briefly considered. Creating open-access hydropower map viewers is anticipated to significantly enhance the hydropower development database in these nations, offering valuable insights for small and medium-scale projects.
Full article
(This article belongs to the Section Water-Energy Nexus)
►▼
Show Figures
Figure 1
Open AccessArticle
Comparison between Hyperspectral and Multispectral Retrievals of Suspended Sediment Concentration in Rivers
by
Sung Hyun Jung, Siyoon Kwon, Il Won Seo and Jun Song Kim
Water 2024, 16(9), 1275; https://doi.org/10.3390/w16091275 - 29 Apr 2024
Abstract
Remote sensing (RS) is often employed to estimate suspended sediment concentration (SSC) in rivers, and the availability of hyperspectral imagery enhances the effectiveness of RS-based water quality monitoring due to its high spectral resolution. Yet, the necessity of hyperspectral imagery for SSC estimation
[...] Read more.
Remote sensing (RS) is often employed to estimate suspended sediment concentration (SSC) in rivers, and the availability of hyperspectral imagery enhances the effectiveness of RS-based water quality monitoring due to its high spectral resolution. Yet, the necessity of hyperspectral imagery for SSC estimation in rivers has not been fully validated. This study thus compares the performance of hyperspectral RS with that of multispectral RS by conducting field-scale experiments in shallow rivers. In the field experiments, we measured radiance from a water body mixed with suspended sediments using a drone-mounted hyperspectral sensor, with the sediment and riverbed types considered as controlling factors. We retrieved the SSC from UAV imagery using an optimal band ratio analysis, which successfully estimated SSC distributions in the sand bed conditions with both multispectral and hyperspectral data. In the vegetated bed conditions, meanwhile, the prediction accuracy decreased significantly due to the temporally varying bottom reflectance associated with the random movement of vegetation caused by near-bed turbulence. This is because temporally inhomogeneous bottom reflectance distorts the relationship between the SSC and total reflectance. Nevertheless, the hyperspectral imaging exhibited better prediction accuracy than the multispectral imaging, effectively extracting optimal spectral bands sensitive to back-scattered reflectance from sediments while constraining the bottom reflectance caused by the vegetation-covered bed.
Full article
(This article belongs to the Special Issue Contaminant Transport Modeling in Aquatic Environments)
►▼
Show Figures
Figure 1
Journal Menu
► ▼ Journal Menu-
- Water Home
- Aims & Scope
- Editorial Board
- Reviewer Board
- Topical Advisory Panel
- Instructions for Authors
- Special Issues
- Topics
- Sections & Collections
- Article Processing Charge
- Indexing & Archiving
- Editor’s Choice Articles
- Most Cited & Viewed
- Journal Statistics
- Journal History
- Journal Awards
- Society Collaborations
- Conferences
- Editorial Office
Journal Browser
► ▼ Journal BrowserHighly Accessed Articles
Latest Books
E-Mail Alert
News
Topics
Topic in
Materials, Minerals, Processes, Sustainability, Toxics, Water
Removal of Hazardous Substances from Water Resources
Topic Editors: Gujie Qian, Yan Zhou, Weifeng ChenDeadline: 20 May 2024
Topic in
Diversity, Environments, JMSE, Toxics, Water
Coastal Macro-, Meso-, and Microplastic Pollution: Effects on the Health of Humans and Ecosystems
Topic Editors: Alba Ardura Gutiérrez, Sara Fernandez FernandezDeadline: 30 May 2024
Topic in
Agronomy, Climate, Earth, Remote Sensing, Water
Advances in Crop Simulation Modelling
Topic Editors: Mavromatis Theodoros, Thomas Alexandridis, Vassilis AschonitisDeadline: 15 June 2024
Topic in
Applied Sciences, Bioengineering, Fermentation, Processes, Water
Bioreactors: Control, Optimization and Applications - 2nd Volume
Topic Editors: Francesca Raganati, Alessandra ProcenteseDeadline: 30 June 2024
Conferences
Special Issues
Special Issue in
Water
Aquaculture Water Safety
Guest Editors: Xingguo Liu, Jun Xie, Jie WangDeadline: 10 May 2024
Special Issue in
Water
Wastewater-Based Epidemiology (WBE) Research
Guest Editors: Peng Du, Phong ThaiDeadline: 25 May 2024
Special Issue in
Water
Nitrification-Denitrification Processes in Bioreactors for Wastewater and Sludge Treatment
Guest Editors: Antonio Albuquerque, Qiulai HeDeadline: 31 May 2024
Special Issue in
Water
Persistent and Emerging Organic Contaminants in Natural Environments
Guest Editors: Jasmin Rauseo, Francesca Spataro, Luisa PatroleccoDeadline: 20 June 2024
Topical Collections
Topical Collection in
Water
Water Policy Collection
Collection Editors: Meri Raggi, Davide Viaggi, Giacomo Zanni