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
Storage Scale Assessment of a Low-Impact Development System in a Sponge City
Water 2024, 16(10), 1427; https://doi.org/10.3390/w16101427 (registering DOI) - 17 May 2024
Abstract
A sponge city is an established urban stormwater management approach that effectively reduces urban runoff and pollutant discharges. In order to plan and design, estimate costs, and evaluate the performance of urban sponge city systems, it is essential to calculate the storage scale.
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A sponge city is an established urban stormwater management approach that effectively reduces urban runoff and pollutant discharges. In order to plan and design, estimate costs, and evaluate the performance of urban sponge city systems, it is essential to calculate the storage scale. In this context, a sponge city storage scale and calculation method based on a multifactor spatial overlay was designed, utilising the starting area of the Dafeng Hi-tech Development Zone in Yancheng City, China, as an illustrative example. The indicators for assessing the impact of sponge city systems on river plain networks are constructed based on four aspects: land planning, building density, water surface rate and green space rate. The relative importance of each indicator was determined based on the necessity of controlling runoff from land parcels and the appropriateness of facility construction. The annual runoff control rate of the 39 low-impact development control units in the study area was calculated using ArcGIS through multifactor spatial overlay mapping and weighting. The results showed that (1) the Geographic Information System (GIS)overlay technology can effectively assist in the decomposition of LID scales; (2) data can be derived, including the design storage volume and other basic control scale indicators for each unit. The study results are expected to serve as a reference for the preparation of special low-impact development plans in the river plain network area of China and the promotion of the construction of a sustainable blue–green system in the city.
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(This article belongs to the Special Issue Urban Stormwater Harvesting, and Wastewater Treatment and Reuse)
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The Main Impact Factors for the Propagation from Meteorological Drought to Socio-Economic Drought from the Perspective of a Small Area, Based on a Practical Survey
by
Chenkai Cai, Changhuai Wu, Jing Wang, Helong Wang, Ruotong Wang, Lei Fu and Jinhua Wen
Water 2024, 16(10), 1426; https://doi.org/10.3390/w16101426 - 16 May 2024
Abstract
Drought is one of the most frequent types of natural disasters in the world, and it has been classified into several different categories. Generally, meteorological drought is considered to be the beginning of a drought disaster, while socio-economic drought is the possible ultimate
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Drought is one of the most frequent types of natural disasters in the world, and it has been classified into several different categories. Generally, meteorological drought is considered to be the beginning of a drought disaster, while socio-economic drought is the possible ultimate result. However, controversy remains around the main impact factors in the propagation from meteorological drought to socio-economic drought over the past decades. In this study, a comprehensive investigation of the 2022 drought event in the city of Lishui, China was conducted to build a model for analyzing the main impact factors in the propagation from meteorological drought to socio-economic drought. The results showed that the 2022 drought event had a great impact on the city’s socio-economic activities. According to governmental reports on socio-economic drought and basic information on water sources, a random forest attribution analysis model was built. The model demonstrated a great performance in distinguishing whether a socio-economic drought had occurred, with an accuracy of 0.9935, a true positive rate of 0.9489 and a false positive rate of 0.0021. Additionally, the variables related to water sources—including drainage area, covered population and daily water supply volume—were found to be more important than the other variables related to meteorological conditions in the model, meaning that the capacity of water sources is the main impact factor in the propagation between meteorological drought and socio-economic drought. In other words, it is feasible to prevent the propagation of meteorological drought to socio-economic drought through water conservancy engineering construction.
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(This article belongs to the Section Hydrology)
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Exploring Endogenous Processes in Water Supply Systems: Insights from Statistical Methods and δ18O Analysis
by
Nikolina Novotni-Horčička, Tamara Marković, Ivan Kovač and Igor Karlović
Water 2024, 16(10), 1425; https://doi.org/10.3390/w16101425 - 16 May 2024
Abstract
Water used for water supply undergoes numerous changes that affect its composition prior to entering the water supply system (WSS). Once it enters the WSS, it is subject to numerous influences altering its physical and chemical composition, redox potential, and microbial quality. Observations
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Water used for water supply undergoes numerous changes that affect its composition prior to entering the water supply system (WSS). Once it enters the WSS, it is subject to numerous influences altering its physical and chemical composition, redox potential, and microbial quality. Observations of water quality parameters at different locations within the WSS indicate that it is justified to assume that these processes take place from the source to the end user. In this study, we used the results of routine everyday analyses (EC, T, pH, ORP, chloride, nitrate, nitrite, ammonium, and bacteria) supplemented by experimental data from a one-year sampling campaign assessing the main cations and anions and stable isotopes δ2H and δ18O. Through these data, the statistical significance of the differences between the concentrations of the basic water quality parameters among different WSS locations was determined, together with the water retention time in the system. The results indicate minor changes in water chemical composition within the observed WSS, remaining below the prescribed Maximum Contaminant Level (MCL) for human consumption. However, factors such as water retention time, CaCO3 deposition, pH fluctuations, and bacterial growth may influence its suitability, which necessitates further investigation into potential risks affecting water quality.
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(This article belongs to the Section Urban Water Management)
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Spatiotemporal Variation, Meteorological Driving Factors, and Statistical Models Study of Lake Surface Area in the Yellow River Basin
by
Li Tang and Xiaohui Sun
Water 2024, 16(10), 1424; https://doi.org/10.3390/w16101424 - 16 May 2024
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The surface area changes of 151 natural lakes over 37 months in the Yellow River Basin, based on remote sensing data and 21 meteorological indicators, employing spatial distribution feature analysis, principal component analysis (PCA), correlation analysis, and multiple regression analysis, identify key meteorological
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The surface area changes of 151 natural lakes over 37 months in the Yellow River Basin, based on remote sensing data and 21 meteorological indicators, employing spatial distribution feature analysis, principal component analysis (PCA), correlation analysis, and multiple regression analysis, identify key meteorological factors influencing these variations and their interrelationships. During the study period, lake area averages were from 0.009 km2 to 506.497 km2, with standard deviations ranging from 0.003 km2 to 184.372 km2. The coefficient of variation spans from 3.043 to 217.436, indicating considerable variability in lake area stability. Six primary meteorological factors were determined to have a significant impact on lake surface area fluctuations: 24 h precipitation, maximum daily precipitation, hours of sunshine, maximum wind speed, minimum relative humidity, and lakes in the source region of the Yellow River generally showed a significant positive correlation. For maximum wind speed (m/s), 28 lakes showed significant correlations, with five positive and twenty-three negative correlations, correlation coefficients ranging from −0.34 to −0.63, average −0.47, indicating an overall negative correlation between lake surface area and maximum wind speed. For maximum daily precipitation (mm), 36 lakes had 21 showing a positive correlation, indicating a positive correlation between lake surface area and daily precipitation in larger lakes. Furthermore, of the 117 lakes with sufficient data to model, the predictive capabilities of various models for lake surface area changes showcased distinct advantages, with the random forest model outperforming others in a dataset of 65 lakes, Ridge regression is best for 28 lakes, Lasso regression performs best for 20 lakes, Linear model is only best for 4 cases. The random forest model provides the best fit due to its ability to handle a large number of feature variables and consider their interactions, thereby offering the best fitting effect. These insights are crucial for understanding the influence of meteorological factors on lake surface area changes within the Yellow River Basin and are instrumental in developing predictive models based on meteorological data.
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Open AccessArticle
A Study of Precipitation Forecasting for the Pre-Summer Rainy Season in South China Based on a Back-Propagation Neural Network
by
Bing-Zeng Wang, Si-Jie Liu, Xin-Min Zeng, Bo Lu, Zeng-Xin Zhang, Jian Zhu and Irfan Ullah
Water 2024, 16(10), 1423; https://doi.org/10.3390/w16101423 - 16 May 2024
Abstract
In South China, the large quantity of rainfall in the pre-summer rainy season can easily lead to natural disasters, which emphasizes the importance of improving the accuracy of precipitation forecasting during this period for the social and economic development of the region. In
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In South China, the large quantity of rainfall in the pre-summer rainy season can easily lead to natural disasters, which emphasizes the importance of improving the accuracy of precipitation forecasting during this period for the social and economic development of the region. In this paper, the back-propagation neural network (BPNN) is used to establish the model for precipitation forecasting. Three schemes are applied to improve the model performance: (1) predictors are selected based on individual meteorological stations within the region rather than the region as a whole; (2) the triangular irregular network (TIN) is proposed to preprocess the observed precipitation data for input of the BPNN model, while simulated/forecast precipitation is the expected output; and (3) a genetic algorithm is used for the hyperparameter optimization of the BPNN. The first scheme reduces the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the simulation by roughly 5% and more than 15 mm; the second reduces the MAPE and RMSE by more than 15% and 15 mm, respectively, while the third improves the simulation inapparently. Obviously, the second scheme raises the upper limit of the model simulation capability greatly by preprocessing the precipitation data. During the training and validation periods, the MAPE of the improved model can be controlled at approximately 35%. For precipitation hindcasting in the test period, the anomaly rate is less than 50% in only one season, and the highest is 64.5%. According to the anomaly correlation coefficient and Ps score of the hindcast precipitation, the improved model performance is slightly better than the FGOALS-f2 model. Although global climate change makes the predictors more variable, the trend of simulation is almost identical to that of the observed values over the whole period, suggesting that the model is able to capture the general characteristics of climate change.
Full article
(This article belongs to the Special Issue Precipitation under Climate Change: Observation, Analysis and Forecasting)
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A Combined Seasonal Mann–Kendall and Innovative Approach for the Trend Analysis of Streamflow Rate in Two Croatian Rivers
by
Mehmet Berkant Yıldız, Fabio Di Nunno, Bojan Đurin, Quoc Bao Pham, Giovanni de Marinis and Francesco Granata
Water 2024, 16(10), 1422; https://doi.org/10.3390/w16101422 - 16 May 2024
Abstract
Climate change profoundly impacts hydrological systems, particularly in regions such as Croatia, which is renowned for its diverse geography and climatic variability. This study examined the effect of climate change on streamflow rates in two Croatian rivers: Bednja and Gornja Dobra. Using seasonal
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Climate change profoundly impacts hydrological systems, particularly in regions such as Croatia, which is renowned for its diverse geography and climatic variability. This study examined the effect of climate change on streamflow rates in two Croatian rivers: Bednja and Gornja Dobra. Using seasonal Mann–Kendall (MK) tests, overall streamflow trends were evaluated. Additionally, innovative polygon trend analysis (IPTA), innovative visualization for innovative trend analysis (IV-ITA), and Bayesian changepoint detection and time series decomposition (BEAST) algorithms were used to assess the trends’ magnitudes and transitions. The seasonal MK analysis identified significant decreasing trends, primarily during summer. The results of IPTA and IV-ITA revealed consistent decreasing trends throughout most months, with a notable increase in September, especially at high flow values. The rivers’ behavior differed between the first and second halves of the month. BEAST analysis detected abrupt changes, including earlier shifts (1951–1968) in the Bednja and more recent ones (2013–2015) in both the Bednja and, to a lesser extent, the Gornja Dobra rivers. This comprehensive approach enhances our understanding of long-term streamflow trends and short-term fluctuations induced by climate change.
Full article
(This article belongs to the Special Issue Advances in Hydrology: Flow and Velocity Analysis in Rivers)
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Water Quality and the First-Flush Effect in Roof-Based Rainwater Harvesting, Part II: First Flush
by
Jessica J. Lay, Jason R. Vogel, Jason B. Belden, Glenn O. Brown and Daniel E. Storm
Water 2024, 16(10), 1421; https://doi.org/10.3390/w16101421 - 16 May 2024
Abstract
Rainwater runoff samples from a range of roofing materials were temporally collected from 19 small-scale roof structures and two commercial buildings through simulated and actual storm events, and the concentrations of polycyclic aromatic hydrocarbons (PAHs), phosphorus flame retardants (PFLs), and pyrethroid insecticides and
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Rainwater runoff samples from a range of roofing materials were temporally collected from 19 small-scale roof structures and two commercial buildings through simulated and actual storm events, and the concentrations of polycyclic aromatic hydrocarbons (PAHs), phosphorus flame retardants (PFLs), and pyrethroid insecticides and other water quality parameters were analyzed. In Part I of this research, the concentrations of these contaminants in roof runoff and soils receiving runoff from a range of roofing materials were evaluated. In Part II, recommendations have been developed for a first-flush exclusion to improve the quality of water harvesting for nonpotable uses. Recommendations focus on a first-flush diversion based on mass removals of total suspended solids (TSS) and PAHs linked to conductivity measurements throughout a storm event. Additionally, an upper-confidence limit (UCL) was constructed to determine the minimum diversion required to obtain 50, 75, 90, and 95% mass removal of TSS and PAH contaminants. The majority of TSS were produced during the initial 1.2 mm of runoff. Likewise, the majority of PAHs were removed during the initial 1.2 mm of runoff, except for the asphalt shingle roofs, where high PAHs were observed after 6 mm of runoff. The Texas Water Development Board (TWDB)-recommended first-flush diversion of one gallon for every 100 square feet of rooftop was not always adequate for removing 50% of TSS and PAHs from the roofs. Rainwater runoff conductivity decreased drastically between 1.2 to 2.4 mm of rainwater runoff. Diverting the first flush based on conductivity has the potential to also divert the majority of TSS and PAHs in roof runoff.
Full article
(This article belongs to the Special Issue Natural and Engineered Phenomena Impacting the Fate, Transport and Treatment of Environmental Contaminants)
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Monsoons and Tide-Induced Eddies Deflect the Dispersion of the Thermal Plume in Nan Wan Bay
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Hung-Jen Lee, Shih-Jen Huang, Pei-Jie Meng, Chung-Chi Chen, Chia-Ying Ho and Yi-Chen Tsai
Water 2024, 16(10), 1420; https://doi.org/10.3390/w16101420 - 16 May 2024
Abstract
The present work employs a three-dimensional ocean model (MITgcm) driven by tidal and climatological forcings to assess the range of impacts of thermal wastewater discharge from the Third Nuclear Power Plant (NP_No.3) in Nan Wan Bay on the local ecosystem. Tides and daily
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The present work employs a three-dimensional ocean model (MITgcm) driven by tidal and climatological forcings to assess the range of impacts of thermal wastewater discharge from the Third Nuclear Power Plant (NP_No.3) in Nan Wan Bay on the local ecosystem. Tides and daily wind forcings are incorporated into the MITgcm to examine their effects on thermal plume dispersion and water circulation in Nan Wan Bay. The model results reveal that the thermal plume is most likely to disperse to the southwest in the summer; it is unlikely to drift to the southeast or northeast because of the presence of the gentle southwesterly monsoon. In the winter, the thermal plume is most likely to be directed to the southwest and is unlikely to be directed to the northeast or southeast because of the prevailing northeasterly monsoon. Additionally, it is worth emphasizing that strong tidal currents generate a pair of counter-rotating eddies that significantly influence the dispersion of the thermal plume. However, seasonal monsoons also play an essential role in modifying the thermal plume’s direction and dispersion.
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(This article belongs to the Special Issue Monitoring and Forecasting Technologies for Marine Environments and Hazards)
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Slope Gradient Effects on Sediment Yield of Different Land Cover and Soil Types
by
Yu War Nang, Shin-ichi Onodera, Kunyang Wang, Yuta Shimizu and Mitsuyo Saito
Water 2024, 16(10), 1419; https://doi.org/10.3390/w16101419 - 16 May 2024
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Water majorly contributes to soil erosion. Considering Japan’s humid and rainy climate, severe soil erosion challenges persist even though forests are the country’s dominant land type. Although numerous studies have emphasized the impact of factors such as land use, soil type, and slope
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Water majorly contributes to soil erosion. Considering Japan’s humid and rainy climate, severe soil erosion challenges persist even though forests are the country’s dominant land type. Although numerous studies have emphasized the impact of factors such as land use, soil type, and slope steepness on sediment yield, the synergetic effects of slope gradient with varying land cover and soil types are underexplored. Herein, we used the Soil and Water Assessment Tool (SWAT) on a steep catchment to identify high sediment yield areas—as well as factors influencing high sediment yield—and evaluate the effect of slope gradient on the sediment yield of different land cover and soil types. The findings reveal an average annual sediment yield of 0.55 tons ha−1 yr−1 in the Takahashi catchment, with yields tripling in some western subbasins under heavy rainfall. Furthermore, the slope gradient effect is most considerable in bare land, agriculture, and rice land cover, with the average sediment yield of bare land resulting in 2.2 tons ha−1 yr−1 at slope > 45%. Meanwhile, deciduous forests on steep slopes exhibit extreme sediment yield, peaking at 7.2 tons ha−1 yr−1 at slope > 45%. The regosol soil type has one of the highest sediment yield variations in all soil types due to slope gradient.
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Exploring the Impact of Climate Change on Water Resources for Vegetation Covers in Extremadura (Spain)
by
Javier Lozano-Parra and José Manuel Sánchez-Martín
Water 2024, 16(10), 1418; https://doi.org/10.3390/w16101418 - 16 May 2024
Abstract
Mediterranean areas will likely undergo climate shifts in the near future that modify the water resources for vegetation. However, in some regions of southwestern Spain, such as Extremadura, the impact of different future scenarios on the water resources for vegetation has not been
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Mediterranean areas will likely undergo climate shifts in the near future that modify the water resources for vegetation. However, in some regions of southwestern Spain, such as Extremadura, the impact of different future scenarios on the water resources for vegetation has not been studied extensively. This study focused on the quantification and spatial distribution of water resources for vegetation covers in Extremadura and analyzed the impact of future climate change scenarios on those water resources. For this, five downscaled global climate models from Coupled Model Intercomparison Project phase 6 (CMIP6) were used in four future periods (from 2021 to 2100) following two Shared Socioeconomic Pathways (SSP-2.45 and SSP-5.85). These projections were compared with a historical baseline period (1970–2000) to obtain the variation of water resources. The results showed decreases in the water resources for all the scenarios and periods analyzed compared to those observed in the historical baseline period. The smallest decreases were noted over 2041–2060 for SSP2-4.5, with almost 74% of the region decreasing between 15 and 18% (with an average of 16.4%). The greatest decreases were over 2081–2100 for SSP5-8.5, in which 90% of the region displayed water resource declines of greater than 50%. In this last situation, the three more widespread vegetation covers (agrosilvopastoral systems of dehesas, grasslands, and crops) underwent similar declines of around 55% of their water resources (from ≈203 to ≈93 mm), while the fourth widely spread vegetation cover, forests, declined by 49% (from ≈261 to ≈133 mm). If any of these future projections occur, the decline in water resources could modify the forest composition and structure of these water-dependent ecosystems, compromising their maintenance and ecological, cultural, and economic functions.
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(This article belongs to the Section Water and Climate Change)
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Enhanced Low-Energy Chemical Oxygen Demand (COD) Removal in Aeration-Free Conditions through Pulse-Rotating Bio-Contactors Enriched with Glycogen-Accumulating Organisms
by
Liang Cheng, Guihuan Deng, Chaoqun Zhang, Yao Yang, Abdallah Abdelfattah, Reham Eltawab and Hui Jia
Water 2024, 16(10), 1417; https://doi.org/10.3390/w16101417 - 16 May 2024
Abstract
This study presents an innovative pulse-rotating biological contactor (P-RBC) designed to enrich glycogen-accumulating organisms (GAOs), thereby facilitating low-energy chemical oxygen demand (COD) removal. It then investigates the impact of rotational speed and hydraulic retention time (HRT) on GAO enrichment and COD removal efficiency.
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This study presents an innovative pulse-rotating biological contactor (P-RBC) designed to enrich glycogen-accumulating organisms (GAOs), thereby facilitating low-energy chemical oxygen demand (COD) removal. It then investigates the impact of rotational speed and hydraulic retention time (HRT) on GAO enrichment and COD removal efficiency. Optimized conditions at lower speeds and longer HRTs significantly enhance GAO proliferation and Polyhydroxyalkanoate (PHA) synthesis, the key to COD removal. Noteworthy findings include a maximum GAO abundance of 21.34% at a half round per hour (rph) rotating speed, which correlates with a 90.2% COD removal rate and an HRT of 6 h, yielding a 21.23% GAO abundance and 89.8% COD removal. This study also explores various carbon sources for PHA synthesis, with sodium acetate proving the most effective. Compared to other wastewater treatment methods, P-RBC demonstrates minimal energy consumption (0.09 kWh per ton of wastewater), highlighting its potential as a sustainable and effective approach for wastewater treatment.
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(This article belongs to the Section Wastewater Treatment and Reuse)
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Multi-Objective Synergetic Operation for Cascade Reservoirs in the Upper Yellow River
by
Kunhui Hong, Wei Zhang, Aixing Ma, Yucong Wei and Mingxiong Cao
Water 2024, 16(10), 1416; https://doi.org/10.3390/w16101416 - 16 May 2024
Abstract
The Yellow River, a critical water resource, faces challenges stemming from increasing water demand, which has led to detrimental effects on hydropower generation and ecological balance. This paper will address the complex task of balancing the interests of hydropower generation, water supply, and
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The Yellow River, a critical water resource, faces challenges stemming from increasing water demand, which has led to detrimental effects on hydropower generation and ecological balance. This paper will address the complex task of balancing the interests of hydropower generation, water supply, and ecology within the context of cascade reservoirs, specifically Longyangxia and Liujiaxia reservoirs. Employing a systemic coupling coordination approach, we constructed a multi-objective synergetic model of the upper Yellow River in order to explore synergies and competitions among multiple objectives. The results reveal that there is a weak competitive relationship between hydropower generation and water supply, a strong synergy between hydropower generation and ecology, and a strong competitive relationship between water supply and ecology. The Pareto solution set analysis indicates a considerable percentage (59%, 20%, and 8% in wet, normal, and dry years, respectively) exhibiting excellent coordination. The probability of excellent coordination decreases with diminishing inflow. The optimization scheme with the highest coupling coordination demonstrates significant improvements in power generation, water supply, and ecological benefits in the upper Yellow River without compromising other objectives, fostering the sustainable operation of hydropower generation, water supply, and ecology in the upper Yellow River.
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(This article belongs to the Section Water Resources Management, Policy and Governance)
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Monitoring and Assessment of the Quality of Chlorinated Water in Schools
by
Vanessa Stein, Alessandro Cazonatto Galvão, Alexandre Tadeu Paulino, Alex Molina Manfredi, Edmar Martendal, Tainara Vieira and Weber da Silva Robazza
Water 2024, 16(10), 1415; https://doi.org/10.3390/w16101415 - 16 May 2024
Abstract
All water destined for human consumption must be subjected to disinfection processes via chlorination with the aim of eliminating the risk of the transmission of waterborne diseases. However, the treatment of water using this method leads to the formation of trihalomethanes (THMs), which
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All water destined for human consumption must be subjected to disinfection processes via chlorination with the aim of eliminating the risk of the transmission of waterborne diseases. However, the treatment of water using this method leads to the formation of trihalomethanes (THMs), which are toxic compounds that may be ingested, inhaled, or absorbed by the skin, increasing the risk of carcinogenic and mutagenic processes. High trihalomethane concentrations in water may be directly related to physicochemical properties, such as temperature, pH, hardness, and potentially toxic metal concentrations. In this work, physicochemical characterization was performed and water quality was assessed with regard to the presence of trihalomethanes in 17 samples collected from points before and after storage in reservoirs. Atomic absorption spectroscopy to determine potentially toxic metals and the measurement of physicochemical properties demonstrated that all results were in accordance with the standards established by Brazilian legislation. Gas chromatography–mass spectrometry was used to determine levels of trihalomethanes in the water samples (trichloromethane, bromodichloromethane, chlorodibromomethane, and bromoform), which were also in accordance with the limits established by Brazilian legislation. Hierarchical clustering on principal components confirmed changes in the water quality depending on location. This work constitutes a paradigm for future studies on the monitoring of toxic organic compounds in water to avoid health problems in humans and animals.
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(This article belongs to the Special Issue Water Quality Monitoring and Public Health)
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Synergistic Removal of Nitrogen and Phosphorus in Constructed Wetlands Enhanced by Sponge Iron
by
Yiwei Shen, Meijia Hu, Yishen Xu, Mengni Tao, Lin Guan, Yu Kong, Shiwei Cao and Zhaoqian Jing
Water 2024, 16(10), 1414; https://doi.org/10.3390/w16101414 - 16 May 2024
Abstract
Insufficient denitrification and limited phosphorus uptake hinder nitrogen and phosphorus removal in constructed wetlands (CWs). Sponge iron is a promising material for the removal of phosphorus and nitrogen because of its strong reducing power, high electronegativity, and inexpensive cost. The influence of factors
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Insufficient denitrification and limited phosphorus uptake hinder nitrogen and phosphorus removal in constructed wetlands (CWs). Sponge iron is a promising material for the removal of phosphorus and nitrogen because of its strong reducing power, high electronegativity, and inexpensive cost. The influence of factors including initial solution pH, dosage, and the Fe/C ratio was investigated. A vertical flow CW with sponge iron (CW-I) was established, and a traditional gravel bed (CW-G) was used as a control group. The kinetic analysis demonstrated that for both nitrogen and phosphorus, pseudo-second-order kinetics were superior. The theoretical adsorption capacities of sponge iron for nitrate ( -N) and phosphate ( -P) were 1294.5 mg/kg and 583.6 mg/kg, respectively. Under different hydraulic retention times (HRT), CW-I had better total nitrogen (TN) and total phosphorus (TP) removal efficiencies (6.08–15.18% and 5.00–20.67%, respectively) than CW-G. The enhancing effect of sponge iron on nitrogen and phosphorus removal was best when HRT was 48 h. The increase in HRT improved not only the nitrogen and phosphorus removal effects of CWs but also the reduction capacity of iron and the phosphorus removal effect. The main mechanisms of synergistic nitrogen and phosphorus removal were chemical reduction, ion exchange, electrostatic adsorption, and precipitation formation.
Full article
(This article belongs to the Special Issue Constructed Wetlands for Water Treatment and Reuse)
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The DPSIR Model-Based Sustainability Assessment of Urban Water Resources: A Comparative Study of Zhuhai and Macao
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Yang Bai, Jiaman Qin, Wenjing Liu, Linhan Li, Yang Wu and Peng Zhang
Water 2024, 16(10), 1413; https://doi.org/10.3390/w16101413 - 16 May 2024
Abstract
Based on the driving force-pressure-state-impact-response (DPSIR) model, 19 indicators were selected to construct a comparison between Zhuhai and Macao, two adjacent cities at the estuary of the Pearl River in China, which have different development models and water resource sustainable development strategies. Factors
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Based on the driving force-pressure-state-impact-response (DPSIR) model, 19 indicators were selected to construct a comparison between Zhuhai and Macao, two adjacent cities at the estuary of the Pearl River in China, which have different development models and water resource sustainable development strategies. Factors that may affect the sustainability of water resources were screened and placed according to the relationships of the five subsystems in the DPSIR model, establishing a sustainable evaluation model for water resources in the two cities. The results analyzed by Principal Component Analysis and Entropy methods showed that (1) Zhuhai City was greatly affected by the driving force, while Macao was greatly affected by the state system from 2012 to 2021. (2) From the trend changes, it can be seen that, in recent years, the water resources of the two cities have been moving towards sustainable development, and the management and protection of water resources have achieved remarkable results. From the evaluation results, it can be seen that implementing urban water-saving activities, strengthening the proportion of environmental water conservancy, public measures in public investment, upgrading sewage treatment machinery to improve sewage treatment rates, and other measures can effectively improve the current situation of water resources in both regions. In the future, the Zhuhai and Macao cities may continue to face a series of water resource pressures brought on by socio-economic developments. Therefore, an active adjustment of the development of the measurement of controlling wastewater discharge and saving water resources was proposed, adhering to the direction of sustainable development, and ensuring the benign development of socio-economic conditions and the ecological environment. This study can provide data to support regional water resource security and policy formulation with different political systems.
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(This article belongs to the Special Issue Sustainable Water Management and Treatment)
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The Impact of 9 Years of Swine Wastewater Application on the Mineral and Organic Quality of Soil in Various Agricultural Crops
by
Ana Paula Almeida Castaldelli Maciel, Gabriela Medeiros, Amanda de Souza Machado, Maria Clara Pilatti, Ralpho Rinaldo dos Reis and Silvio Cesar Sampaio
Water 2024, 16(10), 1412; https://doi.org/10.3390/w16101412 - 16 May 2024
Abstract
This study evaluates the long-term effects of swine wastewater (SWW) on relevant parameters for soil fertility, including calcium (Ca), magnesium (Mg), potassium (K) cations, cation exchange capacity (CEC), and organic matter (OM) in an agricultural area with 9 years of crop cultivation. Three
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This study evaluates the long-term effects of swine wastewater (SWW) on relevant parameters for soil fertility, including calcium (Ca), magnesium (Mg), potassium (K) cations, cation exchange capacity (CEC), and organic matter (OM) in an agricultural area with 9 years of crop cultivation. Three types of SWW (raw, after leaving the biodigester, and after the manure plant) were analyzed with four application rates of SWW (0, 100, 200, and 300 m3.ha−1), associated or not with mineral fertilization, resulting in eight treatments. The study found that the long-term use of SWW had significant effects on soil parameters. Principal component analysis (PCA) was used to summarize the data. The soil’s calcium (Ca), magnesium (Mg), and cation exchange capacity (CEC) levels were higher in soybean compared to other crops and natural soil. Similarly, the treatment with 0 m3.ha−1 of pig manure and without mineral fertilization showed higher levels of these nutrients. In contrast, potassium (K) was found in greater quantities in oats, SWW from the biodigester, higher doses of manure, and with mineral fertilization. The crops had a higher organic matter (OM) content compared to the natural soil, with corn and raw SWW showing the most significant increase.
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(This article belongs to the Special Issue Water, Waste and Wastewater: Treatment and Resource Recovery, 2nd Edition)
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Open AccessArticle
Enhancing Oil–Water Flow Prediction in Heterogeneous Porous Media Using Machine Learning
by
Gaocheng Feng, Kai Zhang, Huan Wan, Weiying Yao, Yuande Zuo, Jingqi Lin, Piyang Liu, Liming Zhang, Yongfei Yang, Jun Yao, Ang Li and Chen Liu
Water 2024, 16(10), 1411; https://doi.org/10.3390/w16101411 - 16 May 2024
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The rapid and accurate forecasting of two-phase flow in porous media is a critical challenge in oil field development, exerting a substantial impact on optimization and decision-making processes. Although the Convolutional Long Short-Term Memory (ConvLSTM) network effectively captures spatiotemporal dynamics, its generalization in
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The rapid and accurate forecasting of two-phase flow in porous media is a critical challenge in oil field development, exerting a substantial impact on optimization and decision-making processes. Although the Convolutional Long Short-Term Memory (ConvLSTM) network effectively captures spatiotemporal dynamics, its generalization in predicting complex engineering problems remains limited. Similarly, although the Fourier Neural Operator (FNO) demonstrates adeptness at learning operators for solving partial differential equations (PDEs), it struggles with three-dimensional, long-term prediction. In response to these limitations, we introduce an innovative hybrid model, the Convolutional Long Short-Term Memory-Fourier Neural Operator (CL-FNO), specifically designed for the long-term prediction of three-dimensional two-phase flows. This model integrates a 3D convolutional encoder–decoder structure to extract and generate hierarchical spatial features of the flow fields. It incorporates physical constraints to enhance the model’s forecasts with robustness through the infusion of prior knowledge. Additionally, a temporal function, constructed using gated memory-forgetting mechanisms, augments the model’s capacity to analyze time series data. The efficacy and practicality of the CL-FNO model are validated using a synthetic three-dimensional case study and application to an actual reservoir model.
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Open AccessArticle
Experimental Study on Near-Wall Laser-Induced Cavitation Bubble Micro-Dimple Formation on 7050 Aluminum Alloy
by
Yupeng Cao, Ranran Hu, Weidong Shi and Rui Zhou
Water 2024, 16(10), 1410; https://doi.org/10.3390/w16101410 - 15 May 2024
Abstract
To investigate the feasibility and formation laws of fabricating micro-dimples induced by near-wall laser-induced cavitation bubble (LICB) on 7050 aluminum alloy. A high-speed camera and a fiber-optic hydrophone system were used to capture pulsation evolution images and acoustic signals of LICB. Meanwhile, a
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To investigate the feasibility and formation laws of fabricating micro-dimples induced by near-wall laser-induced cavitation bubble (LICB) on 7050 aluminum alloy. A high-speed camera and a fiber-optic hydrophone system were used to capture pulsation evolution images and acoustic signals of LICB. Meanwhile, a three-dimensional profilometer was employed to examine the contour morphology of the surface micro-dimple on the specimen. The results show that at an energy level of 500 mJ, the total pulsation period for the empty bubble is 795 μs, with individual pulsation periods of 412.5 μs, 217 μs, and 165 μs for the first, second, and third cycles, respectively, with most energy of the laser and bubble being consumed during the first evolution period. Under the synergy of the plasma shock wave and collapse shock wave, a spherical dimple with a diameter of 450 μm is formed on the sample surface with copper foil as the absorption layer. A model of micro-dimple formed by LICB impact is established. As the energy increases, the depth of the surface micro-dimple peaks at an energy of 400 mJ and then decreases. The depth of the surface micro-dimple increases with the increase in the number of impacts; the optimal technology parameters for the micro-dimple formation by LICB impact are as follows: the absorption layer is copper foil, the energy is 400 mJ, and the number of impacts is three.
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(This article belongs to the Special Issue Hydraulics and Hydrodynamics in Fluid Machinery)
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Open AccessArticle
Study on Permeability Evolution Law of Rock Mass under Mining Stress
by
Pengpeng Zhang, Xuan Ji, Yanheng Li, Mingjing Xu, Bin Yao and Chenliang Zhang
Water 2024, 16(10), 1409; https://doi.org/10.3390/w16101409 - 15 May 2024
Abstract
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In order to study the stress–strain–permeability coefficient relationship of overlying strata in a fractured zone after coal mining, taking the Changcun coal mine in the Changzhi basin as an example, the permeability evolution law of coarse sandstone, fine sandstone, siltstone and mudstone during
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In order to study the stress–strain–permeability coefficient relationship of overlying strata in a fractured zone after coal mining, taking the Changcun coal mine in the Changzhi basin as an example, the permeability evolution law of coarse sandstone, fine sandstone, siltstone and mudstone during a stress–strain process was analyzed through a triaxial compression permeability test. The generalized model of the rock mass permeability evolution process under mining stress was summarized, and then a coupling model of the stress–water pressure–permeability coefficient of fractured rock was established based on the continuum model of rock mass. The results showed that the maximum permeability coefficient of different coal overburden types was quite different, and the peak strength of the rock mass preceded the maximum permeability coefficient during the rock mass failure process; the permeability coefficient first decreased and then increased, reaching its maximum value after the peak stress, which occurred during the strain-softening stage; the generalized model of rock mass permeability included the compaction stage, elasticity stage, stable fracture stage, unstable fracture stage, macroscopic failure stage and residual strength stage.
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Open AccessReview
Enhancing Flood Risk Management: A Comprehensive Review on Flood Early Warning Systems with Emphasis on Numerical Modeling
by
Diego Fernández-Nóvoa, José González-Cao and Orlando García-Feal
Water 2024, 16(10), 1408; https://doi.org/10.3390/w16101408 - 15 May 2024
Abstract
During recent decades there has been an increase in extreme flood events and their intensity in most regions, mainly driven by climate change. Furthermore, these critical events are expected to intensify in the future. Therefore, the improvement of preparedness, mitigation, and adaptation counterparts
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During recent decades there has been an increase in extreme flood events and their intensity in most regions, mainly driven by climate change. Furthermore, these critical events are expected to intensify in the future. Therefore, the improvement of preparedness, mitigation, and adaptation counterparts is mandatory. Many scientific fields are involved in this task, but from a meteorological and hydrological perspective, one of the main tools that can contribute to mitigating the impact of floods is the development of Early Warning Systems. In this sense, this paper presents a scientific literature review of some of the most representative Flood Early Warning Systems worldwide, many of which are currently fully operational, with a special focus on the numerical modeling component when it is developed and integrated into the system. Thus, from basic to technically complex, and from basin or regional to continental or global scales of application, these systems have been reviewed. In this sense, a brief description of their main features, operational procedures, and implemented numerical models is also depicted. Additionally, a series of indications regarding the key aspects of the newly developed FEWSs, based on recent trends and advancements in FEWSs development found in the literature, are also summarized. Thus, this work aims to provide a literature review useful to scientists and engineers involved in flood analysis to improve and develop supporting tools to assist in the implementation of mitigation measures to reduce flood damage for people, goods, and ecosystems and to improve the community resilience.
Full article
(This article belongs to the Special Issue Numerical Simulations and Modelling of Extreme Flood Events)
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