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
Enhanced Simultaneous Nitrogen and Phosphorus Removal in a Continuous-Flow Granular Sludge System under Gradient-Controlled Hydraulic Loading
Water 2024, 16(11), 1510; https://doi.org/10.3390/w16111510 (registering DOI) - 24 May 2024
Abstract
The feasibility of the aerobic granulation of activated sludge was investigated in a continuous-flow anaerobic–anoxic–oxic system under gradient-controlled hydraulic loading on the surface of a cyclone separator. Concentrated domestic sewage was used. After 80 days of operation, 80% of activated sludge in the
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The feasibility of the aerobic granulation of activated sludge was investigated in a continuous-flow anaerobic–anoxic–oxic system under gradient-controlled hydraulic loading on the surface of a cyclone separator. Concentrated domestic sewage was used. After 80 days of operation, 80% of activated sludge in the system was in the form of granular sludge with an average particle size of 373 μm. High removal efficiency was achieved for chemical oxygen demand (94.40%), NH4+-N (99.93%), total nitrogen (89.44%), and total phosphorus (96.92%). A batch study revealed that Pseudomonas (1.34%) and Dechloromonas (1.05%) as the main denitrifying phosphorus-accumulating organisms could efficiently remove phosphorus using nitrate as an electron acceptor, which improved the utilization efficiency of carbon sources and achieved simultaneous denitrification and phosphorus removal. Overall, the study demonstrates the feasibility of enhanced denitrification and phosphorus removal in a continuous-flow granular sludge system. The sludge system enables simultaneous nitrogen and phosphorus removal under low carbon-to-nitrogen ratios.
Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
Open AccessArticle
Assessing the Effects of Environmental Flows on Water Quality for Urban Supply
by
Syrine Ghannem, Javier Paredes-Arquiola, Rafael J. Bergillos, Abel Solera and Joaquín Andreu
Water 2024, 16(11), 1509; https://doi.org/10.3390/w16111509 (registering DOI) - 24 May 2024
Abstract
This paper analyses the effects of environmental flows on water quality within a highly regulated basin, focusing on the Turia River basin in the eastern Iberian Peninsula. Through water management and water quality models, a series of simulations were conducted, introducing variations in
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This paper analyses the effects of environmental flows on water quality within a highly regulated basin, focusing on the Turia River basin in the eastern Iberian Peninsula. Through water management and water quality models, a series of simulations were conducted, introducing variations in the outflows of the Loriguilla reservoir to evaluate the effects of different environmental flow scenarios on water quality, particularly at the location of the intake for the water supply to Valencia. Three environmental flow scenarios were analyzed, alongside an alternative management scenario, considering their implications on water quality and reliability of water demand. The findings of this paper, particularly the nitrate (NO3−) concentration evolution, highlight the influence of minimum e-flow and e-flow regimes on water quality within the basin. These results suggest that while modifying the current flow regime can lead to some improvements in nitrate concentrations at the Valencia supply intake point, the primary cause of high nitrate concentrations is attributed to irrigation return flow and the pre-existing contamination of the aquifer. This analysis offers valuable insights into the complexities of water quality management in regulated basins, emphasizing the need for a multi-faceted approach to address the diverse factors influencing water quality and demand supply reliability.
Full article
(This article belongs to the Section Water Resources Management, Policy and Governance)
Open AccessArticle
Spring Meteorological Drought over East Asia and Its Associations with Large-Scale Climate Variations
by
Meng Gao, Ruijun Ge and Yueqi Wang
Water 2024, 16(11), 1508; https://doi.org/10.3390/w16111508 - 24 May 2024
Abstract
East Asia is a region that is highly vulnerable to drought disasters during the spring season, as this period is critical for planting, germinating, and growing staple crops such as wheat, maize, and rice. The climate in East Asia is significantly influenced by
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East Asia is a region that is highly vulnerable to drought disasters during the spring season, as this period is critical for planting, germinating, and growing staple crops such as wheat, maize, and rice. The climate in East Asia is significantly influenced by three large-scale climate variations: the Pacific Decadal Oscillation (PDO), the El Niño–Southern Oscillation (ENSO), and the Indian Ocean Dipole (IOD) in the Pacific and Indian Oceans. In this study, the spring meteorological drought was quantified using the standardized precipitation evapotranspiration index (SPEI) for March, April, and May. Initially, coupled climate networks were established for two climate variables: sea surface temperature (SST) and SPEI. The directed links from SST to SPEI were determined based on the Granger causality test. These coupled climate networks revealed the associations between climate variations and meteorological droughts, indicating that semi-arid areas are more sensitive to these climate variations. In the spring, PDO and ENSO do not cause extreme wetness or dryness in East Asia, whereas IOD does. The remote impacts of these climate variations on SPEI can be partially explained by atmospheric circulations, where the combined effects of air temperatures, winds, and air pressure fields determine the wet/dry conditions in East Asia.
Full article
(This article belongs to the Special Issue Drought Monitoring and Risk Assessment)
Open AccessArticle
SLEM (Shallow Landslide Express Model): A Simplified Geo-Hydrological Model for Powerlines Geo-Hazard Assessment
by
Andrea Abbate and Leonardo Mancusi
Water 2024, 16(11), 1507; https://doi.org/10.3390/w16111507 - 24 May 2024
Abstract
Powerlines are strategic infrastructures for the Italian electro-energetic network, and natural threats represent a potential risk that may influence their operativity and functionality. Geo-hydrological hazards triggered by heavy rainfall, such as shallow landslides, have historically affected electrical infrastructure networks, causing pylon failures and
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Powerlines are strategic infrastructures for the Italian electro-energetic network, and natural threats represent a potential risk that may influence their operativity and functionality. Geo-hydrological hazards triggered by heavy rainfall, such as shallow landslides, have historically affected electrical infrastructure networks, causing pylon failures and extensive blackouts. In this work, an application of the reworked version of the model proposed by Borga et al. and Tarolli et al. for rainfall-induced shallow landslide hazard assessment is presented. The revised model is called SLEM (Shallow Landslide Express Model) and is designed to merge in a closed-from equation the infinite slope stability with a simplified hydrogeological model. SLEM was written in Python language to automatise the parameter calculations, and a new strategy for evaluating the Dynamic Contributing Area (DCA) and its dependence on the initial soil moisture condition was included. The model was tested for the case study basin of Trebbia River, in the Emilia-Romagna region (Italy) which in the recent past experienced severe episodes of geo-hydrological hazards. The critical rainfall ratio (rcrit) able to trigger slope instability prediction was validated against the available local rainfall threshold curves, showing good performance skills. The rainfall return time (TR) was calculated from rcrit identifying the most hazardous area across the Trebbia basin with respect to the position of powerlines. TR was interpreted as an index of the magnitude of the geo-hydrological events considering the hypothesis of iso-frequency with precipitation. Thanks to its fast computing, the critical rainfall conditions, the temporal recurrence and the location of the most vulnerable powerlines are identified by the model. SLEM is designed to carry out risk analysis useful for defining infrastructure resilience plans and for implementing mitigation strategies against geo-hazards.
Full article
(This article belongs to the Special Issue Geological Hazards: Landslides Induced by Rainfall and Infiltration)
Open AccessArticle
Optimizing Sampling Strategies for Estimating Riverine Nutrient Loads in the Yiluo River Watershed, China
by
Guoshuai Zhang, Yanxue Xu, Min Xu, Zhonghua Li and Shunxing Qin
Water 2024, 16(11), 1506; https://doi.org/10.3390/w16111506 - 24 May 2024
Abstract
Accurately estimating nutrient loads is crucial for effective management and monitoring of aquatic ecosystems. This study evaluated the uncertainty in different sampling frequencies and calculation methods for estimating total nitrogen (TN) and total phosphorus (TP) loads in the Yiluo
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Accurately estimating nutrient loads is crucial for effective management and monitoring of aquatic ecosystems. This study evaluated the uncertainty in different sampling frequencies and calculation methods for estimating total nitrogen (TN) and total phosphorus (TP) loads in the Yiluo River watershed, a tributary of the Yellow River in China. Using daily TN and TP concentration data from 2019 to 2020, we conducted a bootstrapping analysis to evaluate the accuracy of nine different load estimation methods at different sampling frequencies. Our results showed that Method 3 (M_3, constant concentration interpolation) and Method 7 (M_7, flow-weighted concentration method), when used with a biweekly sampling frequency, had the lowest Standard Deviation of the Percentage errors (STD) (7.70% and 8.60% for TN, 12.0% and 18.8% for TP, respectively) and Mean Relative Error (MRE) values (0.078% and −1.60% for TN, 0.305% and 2.33% for TP, respectively) on an annual scale. For monthly TN and TP load estimates, M_7 can control the MRE within ±20% at a biweekly sampling frequency. Furthermore, the uncertainty in TN and TP load estimates was generally larger during the summer months (June–September), emphasizing the important role of storm events in nutrient export. Extreme events (<10% of the time) contributed approximately 50% of the annual nutrient loads. The findings of this study provide a scientific basis for optimizing water quality monitoring schemes and management strategies in agricultural watersheds.
Full article
(This article belongs to the Special Issue Water Quality Studies: Assessing the Presence of Nutrients and Pollutants)
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Open AccessArticle
Assessing the Impacts of Changing Connectivity of Hydropower Dams on the Distribution of Fish Species in the 3S Rivers, a Tributary of the Lower Mekong
by
Peter-John Meynell, Marc J. Metzger and Neil Stuart
Water 2024, 16(11), 1505; https://doi.org/10.3390/w16111505 - 24 May 2024
Abstract
Hydropower plants (HPPs) create barriers across rivers and fragment aquatic ecosystems, river reaches and habitats. The reservoirs they create slow the flowing water and convert the riverine into lacustrine ecosystems. The barriers created by HPPs interrupt the seasonal migrations of many fish species,
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Hydropower plants (HPPs) create barriers across rivers and fragment aquatic ecosystems, river reaches and habitats. The reservoirs they create slow the flowing water and convert the riverine into lacustrine ecosystems. The barriers created by HPPs interrupt the seasonal migrations of many fish species, while the reservoirs drive away fish species that are dependent on flowing water habitats. This paper assesses the distribution of fish species in the 3S rivers—Sekong, Sesan and Sre Pok, in Cambodia, Laos and Viet Nam—using IUCN Red List-assessed species distribution by HydroBasin Level 8 from the freshwater reports of the Integrated Biodiversity Assessment Tool (IBAT) and their connectivity with the Mekong. There are currently 61 commissioned dams in the 3S basins and a further 2 under construction, 23 of which are larger than the 30 MW installed capacity. A further 24 HPPs are proposed or planned in these basins. The changes in connectivity caused by the dams are measured by adapting the River Class Connectivity Index (RCICLASS); the original connectivity of the 3S basin taking into account the two major waterfalls in the Sesan and Sre Pok rivers was estimated at 80.9%. With existing dams, the connectivity has been reduced to 23.5%, and with all planned dams, it is reduced further to 10.9%. The resulting re-distribution of fish species occurring throughout the 3S basins is explored, by focusing on migratory guilds and threatened and endemic fish species. With all dams built, it is predicted that the total numbers of species in HydroBasins above the dams will be reduced by 40–50%. The Threatened Species Index is estimated to fall from over 30 near the confluence of the three rivers to less than 10 above the lowest dams on the 3S rivers. The analysis demonstrates how widely available global and regional datasets can be used to assess the impacts of dams on fish biodiversity in this region.
Full article
(This article belongs to the Special Issue Assessment of Hydropower Sustainability in River Habitats and Aquatic Biota)
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Open AccessArticle
CuFeS2/MXene-Modified Polyvinylidene Fluoride Membrane for Antibiotics Removal through Peroxymonosulfate Activation
by
Dongyang Zhang, Kunfu Li, Lei Fang and Huishan Chen
Water 2024, 16(11), 1504; https://doi.org/10.3390/w16111504 - 24 May 2024
Abstract
In this research, the CuFeS2/MXene-modified polyvinylidene fluoride (PVDF) membrane was prepared to activate peroxymonosulfate (PMS) to remove moxifloxacin (MOX) and its morphology; surface functional groups and hydrophilicity were also studied. The parameters of the catalytic membrane/PMS system were optimized, with an
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In this research, the CuFeS2/MXene-modified polyvinylidene fluoride (PVDF) membrane was prepared to activate peroxymonosulfate (PMS) to remove moxifloxacin (MOX) and its morphology; surface functional groups and hydrophilicity were also studied. The parameters of the catalytic membrane/PMS system were optimized, with an optimal loading of 4 mg/cm2 and a PMS dosage of 0.20 mM. High filtration pressure, alkaline conditions, and impurities in water could inhibit MOX removal. After continuous filtration, the removal efficiency of MOX using the catalytic membrane/PMS system and PVDF membrane was 68.2% and 9.9%, respectively. Batch filtration could remove 87.8% MOX by the extra 10 min contact time between the catalytic membrane and solution. During the filtration process, CuFeS2/MXene on the surface of the catalytic membrane activated PMS to produce SO4•−, HO•, and 1O2, and MOX was removed through adsorption and degradation. Taking humic acid (HA) as the model foulant, reversible fouling resistance in the catalytic membrane/PMS system was 22.8% of the PVDF membrane. The catalytic membrane/PMS system weakened the formation of the cake layer by oxidizing HA into smaller pollutants and followed the intermediate blocking cake filtration model. The novelty of this research was to develop a CuFeS2/MXene–PVDF membrane-activated PMS system and explore its application in antibiotics removal.
Full article
(This article belongs to the Special Issue Advances in Water and Stormwater Networks: Modelling and Pollutant Degradation)
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Open AccessArticle
Development and Application of the Snow, Soil Water and Water Balance Model, an Online Model for Daily Estimation of Snowpack Processes, Soil Water Content and Soil Water Balance
by
Serban Danielescu
Water 2024, 16(11), 1503; https://doi.org/10.3390/w16111503 - 24 May 2024
Abstract
SNOSWAB (Snow, Soil Water and Water Balance) is a unique online deterministic model built using tipping-bucket approaches that allows for the daily estimation of (i) snowpack processes; (ii) soil water content; and (iii) soil water budget. SNOSWAB is most suitable for modeling field-scale
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SNOSWAB (Snow, Soil Water and Water Balance) is a unique online deterministic model built using tipping-bucket approaches that allows for the daily estimation of (i) snowpack processes; (ii) soil water content; and (iii) soil water budget. SNOSWAB is most suitable for modeling field-scale processes for vertically and horizontally homogeneous soils, and its applicability is not limited to specific climate zones or geographical areas. The model is freely available, and its streamlined online interface integrates powerful calibration, visualization and data export routines. In this study, SNOSWAB development and a conceptual model, as well as an example of its application using data collected during a 12-year (2008–2019) field study conducted at the Agriculture and Agri-Food Canada Harrington Experimental Farm (HEF) on Prince Edward Island (PEI), Canada, are presented. Input data consisting of daily air temperature, total precipitation, rainfall and evapotranspiration were used in conjunction with soil properties and daily soil water content, snowpack thickness, surface runoff and groundwater recharge to calibrate (2010–2014) and validate (2015–2019) the model. For both the calibration and validation simulations, the statistical indicators used for evaluating model performance indicated, in most cases, high model fitness (i.e., R2 > 0.5, NRMSE < 50% and −25% < PBIAS < 25%) for the various time intervals and parameters analyzed. SNOSWAB fills an existing gap in the online environment and, due to its ease of use, robustness and flexibility, shows promise to be adopted as an alternative for more complex, standalone models that might require extensive resources and expertise.
Full article
(This article belongs to the Special Issue Understanding Soil Water Content for Irrigation Management)
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Open AccessArticle
Monitoring of Extreme Drought in the Yangtze River Basin in 2022 Based on Multi-Source Remote Sensing Data
by
Mingxiao Yu, Qisheng He, Rong Jin, Shuqi Miao, Rong Wang and Liangliang Ke
Water 2024, 16(11), 1502; https://doi.org/10.3390/w16111502 - 24 May 2024
Abstract
The Yangtze River Basin experienced a once-in-a-century extreme drought in 2022 due to extreme weather, which had a serious impact on the local agricultural production and ecological environment. In order to investigate the spatial distribution and occurrence of the extreme drought events, this
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The Yangtze River Basin experienced a once-in-a-century extreme drought in 2022 due to extreme weather, which had a serious impact on the local agricultural production and ecological environment. In order to investigate the spatial distribution and occurrence of the extreme drought events, this study used multi-source remote sensing data to monitor the extreme drought events in the Yangtze River Basin in 2022. In this study, the gravity satellite data product CSR_Mascon was used to calculate the GRACE Drought Intensity Index (GRACE-DSI), which was analyzed and compared with the commonly used meteorological drought indices, relative soil humidity, and soil water content data. The results show that (1) terrestrial water storage change data can well reflect the change in water storage in the Yangtze River Basin. Throughout the year, the average change in terrestrial water storage in the Yangtze River Basin from January to June is higher than the average value of 33.47 mm, and the average from July to December is lower than the average value of 48.17 mm; (2) the GRACE-DSI responded well to the intensity and spatial distribution of drought events in the Yangtze River Basin region in 2022. From the point of view of drought area, the Yangtze River Basin showed a trend of extreme drought increasing first, and then decreasing in the area of different levels of drought, and the range of drought reached a maximum in September with a drought area of 175.87 km2, which accounted for 97.71 per cent of the total area; at the same time, the area of extreme drought was the largest, with an area of 85.69 km2; (3) the spatial and temporal variations of the GRACE-DSI and commonly used meteorological drought indices were well correlated, with correlation coefficients above 0.750, among which the correlation coefficient of the SPEI-3 was higher at 0.937; (4) the soil moisture and soil relative humidity products from the CLDAS, combined with soil moisture products from the GLDAS, reflect the starting and ending times of extreme drought events in the Yangtze River Basin in 2022 well, using the information from the actual stations. In conclusion, gravity satellite data, analyzed in synergy with data from multiple sources, help decision makers to better understand and respond to drought.
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(This article belongs to the Special Issue Application of Spatiotemporal Data in Hydrological Hazards of Drought, Flood and Water Pollution Assessment and Monitoring)
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Open AccessEditorial
Recent Advances in Modern Hydrogeology: Promoting Harmony between Nature and Humanity
by
Peiyue Li, Jianhua Wu and Vetrimurugan Elumalai
Water 2024, 16(11), 1501; https://doi.org/10.3390/w16111501 - 24 May 2024
Abstract
Hydrogeology is a crucial branch of Earth science dedicated to deciphering the complex interactions between groundwater and the lithosphere, hydrosphere, atmosphere, and biosphere [...]
Full article
(This article belongs to the Special Issue Recent Advances in Hydrogeology: Featured Reviews)
Open AccessArticle
Utilizing Data-Driven Approaches to Forecast Fluctuations in Groundwater Table
by
Majid Mirzaei and Adel Shirmohammadi
Water 2024, 16(11), 1500; https://doi.org/10.3390/w16111500 - 24 May 2024
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Accurate forecasting of fluctuations in groundwater table is crucial for the effective management of regional water resources. This study explores the potential of utilizing remotely sensed satellite data to predict and forecast water table variations. Specifically, two Artificial Neural Network (ANN) models were
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Accurate forecasting of fluctuations in groundwater table is crucial for the effective management of regional water resources. This study explores the potential of utilizing remotely sensed satellite data to predict and forecast water table variations. Specifically, two Artificial Neural Network (ANN) models were developed to simulate water table fluctuations at two distinct well sites, namely BA Ea 18 and FR Df 35 in Maryland. One model leveraged the relationship between variations in brightness temperature and water table depth, while the other model was founded on the association between changes in soil moisture and water table depth. These models were trained and validated using recorded water table depths from the aforementioned wells, brightness temperature data acquired from the Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E), and soil moisture information generated using the Land Data Assimilation System (LDAS). All models exhibited strong performance in predicting and forecasting water table fluctuations, with root mean square errors ranging from 0.043 m to 0.047 m for a 12-month forecasting horizon. Sensitivity tests revealed that the models displayed greater sensitivity to uncertainties in water table depth compared to uncertainties in both brightness temperature and soil moisture content. This underscores the feasibility of constructing an ANN-based water table prediction model, even in cases where high-resolution remotely sensed data is unavailable. In such situations, the model’s efficacy is contingent on the compatibility of the time series trends in data, such as brightness temperature or soil moisture, with those observed at the study site.
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Open AccessArticle
Investigation of Kinetic, Equilibrium, and Thermodynamic Modeling of Perfluorooctanoic Acid (PFOA) Adsorption in the Presence of Natural Organic Matter (NOM) by Dielectric Barrier Discharge Plasma-Modified Granular Activated Carbon (GAC)
by
Thera Sahara, Doonyapong Wongsawaeng, Kanokwan Ngaosuwan, Worapon Kiatkittipong, Peter Hosemann and Suttichai Assabumrungrat
Water 2024, 16(11), 1499; https://doi.org/10.3390/w16111499 - 24 May 2024
Abstract
Perfluorooctanoic acid (PFOA) contamination in water sources poses significant environmental and health concerns. The kinetic, equilibrium, and thermodynamic features of PFOA adsorption in the existence of natural organic matter (NOM) were thoroughly investigated in this work using granular activated carbon (GAC) modified by
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Perfluorooctanoic acid (PFOA) contamination in water sources poses significant environmental and health concerns. The kinetic, equilibrium, and thermodynamic features of PFOA adsorption in the existence of natural organic matter (NOM) were thoroughly investigated in this work using granular activated carbon (GAC) modified by dielectric barrier discharge (DBD) plasma. The impacts of DBD plasma parameters on the adsorption process were systematically examined. The results demonstrated that GAC modified by DBD plasma exhibited enhanced adsorption performance for PFOA, even in the presence of NOM. The optimal condition for plasma-treated GAC was achieved with 20 min of plasma treatment time and 100 W of plasma power, resulting in 92% PFOA removal efficiency in deionized water (DIW) and 97% removal efficiency in Chao Phraya River water (CPRW). A kinetic investigation using the pseudo-first-order model (PFOM), the pseudo-second-order model (PSOM), and the Elovich model (EM) indicated that plasma treatment time and NOM presence influenced the adsorption capacity and rate constants of PFOA with the PSOM having emerged as the most fitting kinetic model. The Langmuir isotherm model indicates monolayer adsorption of PFOA on plasma-treated GAC, with higher maximum adsorption capacity while NOM is present. The Redlich–Peterson and Sips isotherm models indicated varying adsorption capacity and heterogeneity in the adsorption system. The Sips model was determined as the most fitting isotherm model. Furthermore, the favorable and spontaneous character of PFOA adsorption onto plasma-treated GAC was validated by thermodynamic analysis, with endothermic heat absorption during the process. Overall, this comprehensive investigation provides valuable insights into the adsorption characteristics of PFOA in the existence of NOM using GAC modified by DBD plasma.
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(This article belongs to the Topic Removal of Hazardous Substances from Water Resources)
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Open AccessArticle
Hydraulic Connectiveness Metric for the Analysis of Criticality in Water Distribution Networks
by
Malvin S. Marlim and Doosun Kang
Water 2024, 16(11), 1498; https://doi.org/10.3390/w16111498 - 24 May 2024
Abstract
Capturing the criticality of a water distribution network (WDN) is difficult because of its many constituent factors. In terms of operation, the arrangement of demand nodes and how they connect have a significant influence. This study aims to integrate hydraulic and topologic aspects
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Capturing the criticality of a water distribution network (WDN) is difficult because of its many constituent factors. In terms of operation, the arrangement of demand nodes and how they connect have a significant influence. This study aims to integrate hydraulic and topologic aspects into a single criticality measure by adapting the structural hole influence matrix concept. This method applies the nodal demand to the corresponding pipes to construct a weighted network. The matrix stores each node’s local and global connection information, and the criticality value is then assigned based on the adjacency information. The criticality value can reveal the locations in terms of nodes or pipes that are vital for maintaining a network’s level of service. By analyzing pipe-failure scenarios, the criticality value can be related to the loss of performance. Assessing the nodal criticality change behavior under an increased stress scenario can help uncover the impacted areas. The metric for district metered area (DMA) creation demonstrates its potential as a weighting to be considered. This unified criticality metric enables the evaluation of nodes and pipes in a WDN, thereby enabling resilient and sustainable development planning.
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(This article belongs to the Special Issue Sustainable Management of Water Distribution Systems)
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Open AccessArticle
Spatial Distribution Patterns of Phytoplankton and Their Relationship with Environmental Factors in the Jinjiang River, China
by
Yanping Zhong, Mingjiang Cai, Jin Cui, Xinping Chen, Shuhua Wang, Zhenguo Chen and Shanshan Zhang
Water 2024, 16(11), 1497; https://doi.org/10.3390/w16111497 - 24 May 2024
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Our study aims to investigate the water quality and distribution patterns of phytoplankton communities in the Jinjiang River Basin in Quanzhou, as well as their relationship with environmental factors. We integrated data from the national water quality databases of the two main tributaries
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Our study aims to investigate the water quality and distribution patterns of phytoplankton communities in the Jinjiang River Basin in Quanzhou, as well as their relationship with environmental factors. We integrated data from the national water quality databases of the two main tributaries of the West and East Jinjiang Rivers between 2020 and 2023, supplemented by field surveys. Redundancy analysis was used to explore the effect of environmental factors on phytoplankton communities. Our findings revealed that the West Jinjiang River experienced a significant influence from excessive fertilizer use in tea cultivation, leading to an increase in TN concentrations compared to the East Jinjiang River. The abundance of phytoplankton in the Jinjiang River Basin was 105 cells·L−1, with phytoplankton being dominated by Chlorophyta, Cyanphyta, and diatoms, accounting for an average of 50%, 20%, and 19% of the total phytoplankton abundance, respectively. Redundancy analysis indicated that temperature, pH, and nutrient concentrations were important factors influencing the phytoplankton communities. With increasing temperature and nutrients concentrations, the abundance of Chlorophyta and Dinophyta significantly increased. This study provides a solid foundation for the regular “health diagnosis” of crucial rivers and lakes in Quanzhou and supports the establishment of a health guarantee system for rivers and lakes.
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Open AccessArticle
Socio-Spatial Analysis of Water Affordability at Small Scales: A Needs-Based Approach
by
Gustavo Romero-Gomez, Elena Domene, Xavier Garcia, Hyerim Yoon and David Saurí
Water 2024, 16(11), 1496; https://doi.org/10.3390/w16111496 - 24 May 2024
Abstract
Water affordability as a dimension of water poverty is becoming an increasing source of concern in cities of the Global North. Studies on water affordability are either based on water wants and not needs or tend to use spatial scales too large for
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Water affordability as a dimension of water poverty is becoming an increasing source of concern in cities of the Global North. Studies on water affordability are either based on water wants and not needs or tend to use spatial scales too large for effective analyses of local inequities that can truly guide policy actions. In this contribution, we calculate and map a Water Affordability Index (WAI) based on the minimum water requirement of 100 litres/person/day at the scale of the census tract for the Metropolitan Area of Barcelona. We also apply global and local spatial autocorrelation analyses to investigate spatial relationships between the WAI and poverty-related sociodemographic variables. Results show that, even though average WAI values are moderate, the distribution pattern of higher and lower values tends to be clustered in some districts and neighbourhoods of the study area. Bivariate correlations indicate that water affordability is not only related to poverty variables but also to the diversity of water prices. Findings exemplify how the constructed index can complement existing affordability indicators, revealing and mapping important risk groups struggling to meet the costs of essential water needs. Water affordability could be mitigated by supportive water pricing policies for vulnerable households in water poverty hotspots.
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(This article belongs to the Special Issue Socio-Economics of Water Resources Management)
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Open AccessArticle
Soil Hydrothermal Dynamics in the Hengduan Mountains of Southeast Tibet and Associated Influencing Factors
by
Lingling Meng, Zhaofeng Li, Qiang Zhang and Xinpeng Zhang
Water 2024, 16(11), 1495; https://doi.org/10.3390/w16111495 - 24 May 2024
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Soil water and soil temperature are important ecological factors and driving forces for ecosystem restoration and sustainable development, possessing great significance for climate modeling and prediction. The Hengduan Mountains in southeastern Tibet, China, are located in a climate-change-sensitive area, and the study of
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Soil water and soil temperature are important ecological factors and driving forces for ecosystem restoration and sustainable development, possessing great significance for climate modeling and prediction. The Hengduan Mountains in southeastern Tibet, China, are located in a climate-change-sensitive area, and the study of soil hydrothermal dynamics in this area is of great significance for local and global climatic change and water resource utilization. This study, based on the soil hydrothermal and meteorological data of the Hengduan Mountain area in Southeast Tibet, analyzes the dynamic change patterns of soil hydrothermal and meteorological factors and explores their influencing relationships. It was found that the dynamic change in soil water content affected by precipitation was “bimodal” type. Among the meteorological factors, soil water content has the strongest correlation with relative humidity. The intra-annual variation curve of soil temperature is similar to that of the atmospheric temperature, showing a “unimodal” type, and has the highest correlation with atmospheric temperature. Specifically, it takes 70 mm and 170 mm of precipitation to change the soil water content and soil temperature at the 150 cm depth. For every 20 °C change in atmospheric temperature, soil temperature above 150 cm changes by an average of 7.2 °C.
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Open AccessArticle
Evaluation of Algal Control Measures in Eutrophic Reservoirs Based on Aquatic Ecosystem Models
by
Zhen Zheng, Tingting Liao, Yafeng Lin, Xueyi Zhu and Haobin Meng
Water 2024, 16(11), 1494; https://doi.org/10.3390/w16111494 - 24 May 2024
Abstract
The frequency of freshwater cyanobacterial blooms is increasing globally due to climate change and eutrophication, particularly in reservoirs. Reservoir ecosystems exhibit unique characteristics, and there is a complex relationship between factors such as light, temperature, nutrient salts, hydrology, and algal growth. The impact
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The frequency of freshwater cyanobacterial blooms is increasing globally due to climate change and eutrophication, particularly in reservoirs. Reservoir ecosystems exhibit unique characteristics, and there is a complex relationship between factors such as light, temperature, nutrient salts, hydrology, and algal growth. The impact of the other factors on algal growth varies significantly among different reservoirs. Thus, it is crucial to assess the effectiveness of various algal control measures implemented in different reservoirs. This study conducted a comprehensive assessment by establishing a eutrophication model for the Shanzi Reservoir in Fuzhou City. The model incorporated meteorology, hydrology, carbon dynamics, nutrient cycling, and biological communities. The effectiveness of diverse management measures was systematically evaluated. The findings demonstrate that increasing the water level, reducing nutrient salts in sediments, and implementing ecological fish stocking effectively suppressed algal growth to varying degrees and improved nitrogen and phosphorus levels. Lower water levels and ecological fish stocking had a significant impact on algal reproduction, while sediment reduction had a minimal effect. Conversely, lower water levels and ecological fish stocking did not significantly improve nitrogen and phosphorus concentrations in the reservoir, whereas sediment reduction had a noticeable effect. Consequently, the management strategies for the Shanzi Reservoir should prioritize external control measures and the implementation of ecological fish stocking.
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(This article belongs to the Special Issue The Management of Eutrophication, Harmful Algal Bloom and Ecological Health in Freshwater Ecosystems)
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Open AccessArticle
Optimization of the Coupling between Water and Energy Consumption in a Smart Integrated Photovoltaic Pumping Station System
by
Zuping Xu and Xing Chen
Water 2024, 16(11), 1493; https://doi.org/10.3390/w16111493 - 23 May 2024
Abstract
Agricultural irrigation requires significant consumption of freshwater resources and energy. The integration of photovoltaic power generation into irrigation systems has been extensively investigated in order to save the cost of energy. However, current research often neglects the coupling relationship between photovoltaic power generation
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Agricultural irrigation requires significant consumption of freshwater resources and energy. The integration of photovoltaic power generation into irrigation systems has been extensively investigated in order to save the cost of energy. However, current research often neglects the coupling relationship between photovoltaic power generation and irrigation schemes. This study presented a novel smart integrated photovoltaic pump station system to effectively address the issue associated with water and energy consumption in irrigation. An optimization model was proposed to synchronize the energy consumption of irrigation pump stations with photovoltaic power generation, accurately meeting the irrigation water demand while maximizing solar energy utilization. The optimization model incorporates power balance, grid-connected power, and total water demand as constraints while considering pump speed as the decision variable and aiming to minimize daily operational costs. Finally, a high-standard farmland was used as a case study to validate the efficacy of the optimization strategy through two photovoltaic grid-connected policies—one allowing for the sale of surplus power and the other prohibiting it. An improved dynamic programming method was employed to solve for optimal energy consumption schemes under different water demand conditions; the results were compared against traditional methods, revealing potential cost savings ranging from 6.2% to 30.5%. The optimization model and method propose a new operational concept for the irrigation system with photovoltaic generation, effectively utilizing the distinctive features of both irrigation and photovoltaics to optimize water and energy resources.
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(This article belongs to the Section Water-Energy Nexus)
Open AccessArticle
Application of RNN-LSTM in Predicting Drought Patterns in Pakistan: A Pathway to Sustainable Water Resource Management
by
Wilayat Shah, Junfei Chen, Irfan Ullah, Muhammad Haroon Shah and Irfan Ullah
Water 2024, 16(11), 1492; https://doi.org/10.3390/w16111492 - 23 May 2024
Abstract
Water is a fundamental and crucial natural resource for human survival. However, the global demand for water is increasing, leading to a subsequent decrease in water availability. This study addresses the critical need for improved water resource forecasting models amidst global water scarcity
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Water is a fundamental and crucial natural resource for human survival. However, the global demand for water is increasing, leading to a subsequent decrease in water availability. This study addresses the critical need for improved water resource forecasting models amidst global water scarcity concerns exacerbated by climate change. This study uses the best weather and water resource forecasting model for sustainable development. Employing a Recurrent Neural Network–Long Short-Term Memory (RNN-LSTM) approach, the research enhances drought prediction capabilities by integrating secondary data of the rainfall, temperature, and ground and surface water supplies. The primary objective is to forecast water resources under changing climatic conditions, facilitating the development of early warning systems for vulnerable regions. The results from the LSTM model show an increased trend in temperature and rainfall patterns. However, a relatively unstable decrease in rainfall is observed. The best statistical analysis result was observed with the LSTM model; the model’s accuracy was 99%, showing that it was quite good at presenting the obtained precipitation, temperature, and water data. Meanwhile, the value of the root mean squared error (RMSE) was about 13, 15, and 20, respectively. Therefore, the study’s results highlight that the LSTM model was the most suitable among the artificial neural networks for forecasting the weather, rainfall, and water resources. This study will help weather forecasting, agriculture, and meteorological departments be effective for water resource forecasting.
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(This article belongs to the Section Hydrology)
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Open AccessArticle
Research and Application of the Mine 3D DC Resistivity Method for Detecting Grouting in the Floor of an Ultrawide Working Face, Taking the Yongmei Xinqiao Coal Mine in Henan Province as an Example
by
Ning Li, Maofei Li, Xuhong Wang, Xuerui Tong and Ruosong Sun
Water 2024, 16(11), 1491; https://doi.org/10.3390/w16111491 - 23 May 2024
Abstract
Generally, ground grouting is used to treat confined water areas before mining at the working face, but there is a lack of testing methods for determining the effectiveness of such a grouting treatment on the floor of ultrawide working faces. Therefore, we propose
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Generally, ground grouting is used to treat confined water areas before mining at the working face, but there is a lack of testing methods for determining the effectiveness of such a grouting treatment on the floor of ultrawide working faces. Therefore, we propose a 3D DC resistivity method for mines and apply it to the detection of the effect of grouting on the mine floor. This study took the Yongmei Xinqiao Coal Mine in Henan Province as the research object and used a combination of theoretical analysis, numerical simulation, and measured data analysis to study the effect of the 3D resistivity method on detecting the effect of grouting on the floor of an ultrawide working face in the mine. The research results indicated that compared with the 2D observation mode of same-side power supply and reception, the 3D observation mode of opposite-side power supply and reception using the tunnels on both sides of the working face was more sensitive to the response of the water-rich area 60 m below the coal seam’s floor. Regarding the model’s set-up in this article, when traditional apparent resistivity calculations were used, the apparent resistivity obtained by the 3D observation mode was opposite to the model’s setting, and accurate electrical information of anomalous bodies must be obtained through 3D inversion. The measured data showed that although the ground grouting treatment effectively reduced the water volume in the floor, the treatment’s result was affected by human factors, and the water in the floor was redistributed.
Full article
(This article belongs to the Special Issue Mine Water Safety and Environment, 2nd Edition)
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