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 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 first half of 2024).
- 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.
Impact Factor:
3.0 (2023);
5-Year Impact Factor:
3.3 (2023)
Latest Articles
Study of Enrichment and Conversion Mechanisms of Heavy Metal Elements in Mines in Cold Regions Under Freezing and Thawing
Water 2024, 16(24), 3715; https://doi.org/10.3390/w16243715 (registering DOI) - 23 Dec 2024
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In cold-region mines, the dual effects of heat islands and cold islands, caused by cycling of hot and cold temperature extremes, facilitate the outward dispersion of heavy metal dust. Freeze–thaw cycles occurring in ice provide a conducive environment for the enrichment and conversion
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In cold-region mines, the dual effects of heat islands and cold islands, caused by cycling of hot and cold temperature extremes, facilitate the outward dispersion of heavy metal dust. Freeze–thaw cycles occurring in ice provide a conducive environment for the enrichment and conversion of heavy metals, allowing them to enter downstream rivers with meltwater. This process significantly impacts human activities and ecosystems in areas traversed by these rivers. This study is conducted in the typical alpine mining area in Xinjiang, China, and focuses on the impact of freeze–thaw cycles on the enrichment and conversion of heavy metals in alpine mining regions. It employs a comprehensive approach combining field measurements, environmental simulations, theoretical analysis, and laboratory experiments. The findings indicate that the environmental behavior of heavy metals is influenced not only by the freeze–thaw cycles themselves but also by factors such as temperature, pH, and redox conditions. Heavy metal elements may enter water bodies during the melting process and pose risks to downstream ecosystems and human health.
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Open AccessArticle
Fostering Public Participation in Watershed Pollution Governance: A Case Study of Civilian Environmental Supervisors in Guiyang’s Dual River Chief System
by
Xuan Huang and Junqing Xu
Water 2024, 16(24), 3714; https://doi.org/10.3390/w16243714 (registering DOI) - 23 Dec 2024
Abstract
The complexity of watershed pollution governance necessitates the involvement of multiple stakeholders, with increasing emphasis on public participation. In response, China introduced the river chief system and gradually established civilian river chiefs and environmental supervisors as channels for public engagement. However, questions remain
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The complexity of watershed pollution governance necessitates the involvement of multiple stakeholders, with increasing emphasis on public participation. In response, China introduced the river chief system and gradually established civilian river chiefs and environmental supervisors as channels for public engagement. However, questions remain about how to effectively and sustainably engage the public while addressing watershed pollution. To explore this, we employed an action research approach, focusing on a case from Guiyang, which pioneered the “Dual River Chief System” and introduced civilian environmental supervisors, significantly mobilizing public involvement and controlling pollution. By analyzing the selection background, criteria, responsibilities, training, support mechanisms, and fieldwork of civilian environmental supervisors, we found that their primary tasks were monitoring watershed conditions and mobilizing broader public participation, with selection criteria focusing on interest in watershed governance and regional influence. At the same time, training and expert support were provided to enhance their investigative capabilities and ensure accurate results. This also fostered greater commitment and confidence among the supervisors, further promoting public participation in watershed governance. Despite its success, the approach relied heavily on the groundwork and local networks of civilian river chiefs and required significant time and effort in the early stages, posing certain limitations.
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(This article belongs to the Special Issue Water Governance: Current Status and Future Trends)
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Hydraulic Reconstruction of Paleolandslide-Dammed Lake Outburst Flood Using Water–Sediment Mixture Flow Modeling: A Case Study of Xuelongnang, Upstream Jinsha River
by
Hanfang Lv, Jian Chen and Ruichen Chen
Water 2024, 16(24), 3713; https://doi.org/10.3390/w16243713 (registering DOI) - 23 Dec 2024
Abstract
Debris content plays an important role in controlling erosion capacity and sedimentation characteristics during outburst floods. Numerical models should incorporate sediments in hazard analyses to obtain more accurate assessments of outburst flood magnitudes and downstream behaviors. In this paper, we propose a novel
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Debris content plays an important role in controlling erosion capacity and sedimentation characteristics during outburst floods. Numerical models should incorporate sediments in hazard analyses to obtain more accurate assessments of outburst flood magnitudes and downstream behaviors. In this paper, we propose a novel water–sediment mixture flow model to reconstruct the ancient outburst floods at Xuelongnang and demonstrate the performance of this model through comparisons with field evidence. The simulated outburst flood reaches a maximum breach discharge of 10,697.35 m3/s and a peak sediment discharge of 65.29 m3/s, traveling downstream for 87 km within 5.43 h. Based on simulations of riverbed changes, inundation depth, velocity, shear stress, and Froude number, our findings suggest that topographic controls influence hydraulic patterns, which subsequently affect erosional and depositional processes and contribute to landscape evolution. During the downstream propagation of the outburst flood in narrowed valley sections, simulated sediment-simulated deposition occurs downstream while erosion occurs upstream, coinciding with the maximum inundation depths attributed to hydraulic jump phenomena. We also discuss the formation processes of the outburst deposits, identifying areas of greatest channel aggradation. Calculated bed shear stress suggests that sediment transport by the flood deposits on the riverbed decreases as the flood stage wanes, forming the rhythmite-interbedded structures observed in field investigations. This work provides a viable and promising approach to understanding hydro-sediment-morphodynamic processes in flood pathways and the erosional and depositional features left by outburst floods, supporting modern outburst flood hazard prevention and mitigation.
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(This article belongs to the Section Hydraulics and Hydrodynamics)
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A Systematic Investigation on Contamination of Pesticides and Relevant Metabolites in Pre- and Post-Treatment Drinking Water from the Yangtze River Delta, China
by
Yuhang Chen, Chao Feng, Sunyang Le, Yuanjie Lin, Xinlei Qiu, Qian Xu, Xinyu Wang, Hailei Qian, Zixin Qian, Dasheng Lu, Guoquan Wang and Ping Xiao
Water 2024, 16(24), 3712; https://doi.org/10.3390/w16243712 (registering DOI) - 23 Dec 2024
Abstract
This study aimed to investigate the distribution of commonly used pesticides and their metabolites in drinking water before and after treatment at drinking water treatment plants (DWTPs) in the Yangtze River Delta and to assess the health risks from the perspective of non-carcinogenicity
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This study aimed to investigate the distribution of commonly used pesticides and their metabolites in drinking water before and after treatment at drinking water treatment plants (DWTPs) in the Yangtze River Delta and to assess the health risks from the perspective of non-carcinogenicity and carcinogenicity. A total of 85 pesticides and their metabolites were analyzed in source, finished, and tap water using online solid-phase extraction coupled with liquid chromatography–tandem mass spectrometry. Across 91 water samples, 31 parent compounds and 9 metabolites were detected, with the median total concentrations of 62.2 (range: 6.20 to 392) ng/L. Atrazine, 2-hydroxyatrazine, and S-metolachlor were detected in all samples. Advanced treatment processes at DWTPs effectively reduced the residues of pesticides and their metabolites (removal rates 51.5~95.2%), with removal rates for metabolites significantly lower than those for parent compounds (p = 0.03). Regarding health risks, the estimated carcinogenic risk for pesticides and metabolites detected in tap water was within acceptable limits and the non-carcinogenic risk was insignificant. However, it is important to note that both of the two compounds with the relatively highest non-carcinogenic risks are pesticide metabolites. Overall, this study showed that despite dozens of pesticides and metabolites being detected in water from the Yangtze River Delta, their health risks were assessed to be insignificant. The lower effectiveness of current advanced treatments in removing pesticide metabolites indicates the necessity of technique improvement in DWTPs.
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(This article belongs to the Section Water Quality and Contamination)
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Open AccessArticle
The Analysis of the Spatial–Temporal Evolution and Driving Effect of Land Use Change on Carbon Storage in the Urban Agglomeration in the Middle Reaches of the Yangtze River
by
Shenglin Li, Peng Shi, Xiaohuang Liu, Jiufen Liu, Run Liu, Ping Zhu, Chao Wang and Yan Zheng
Water 2024, 16(24), 3711; https://doi.org/10.3390/w16243711 (registering DOI) - 22 Dec 2024
Abstract
Studying the temporal and spatial variation characteristics and driving factors of carbon reserves in the middle reaches of the Yangtze River urban agglomeration is crucial for achieving sustainable development and regional ecological conservation against the backdrop of the “double carbon” plan. Based on
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Studying the temporal and spatial variation characteristics and driving factors of carbon reserves in the middle reaches of the Yangtze River urban agglomeration is crucial for achieving sustainable development and regional ecological conservation against the backdrop of the “double carbon” plan. Based on three periods of land use data from 2000 to 2020, combined with the InVEST model(Version 3.14.2), the spatiotemporal changes in carbon storage in the urban agglomeration in the middle reaches of the Yangtze River were analyzed. The PLUS model (Version 1.3.5) was used to predict three scenarios of natural development, urban development, and eco-development in the urban agglomeration in the middle reaches of the Yangtze River in 2035 and estimate the carbon storage of the ecosystems under different scenarios, and it used optimal parameter GeoDetectors (Version 4.4.2) to reveal the driving factors affecting the spatiotemporal differentiation of carbon storage. The results show that farmland and construction land area increased and forestland area continued to decrease from 2000 to 2020. Carbon storage decreased by 1 × 106 t, with forestland conversion to farmland and construction land being the main decreasing drivers. The carbon storage of natural and urban developments decreased by 0.26 × 106 t and 0.32 × 106 t, while it increased by 0.16 × 106 under ecological development. The results of the factor detector showed that the NDVI (Normalized Difference Vegetation Index) had the highest explanatory power on the spatiotemporal variation in carbon storage (q = 0.588), followed by the slope (q = 0.454) and elevation (q = 0.391), and the explanatory power of natural environmental factors on the spatiotemporal variation in of carbon storage was dominant. The interaction detector results showed that the spatiotemporal variation in carbon storage was affected by multiple factors, the interaction intensity between each driving factor was stronger than that of a single factor, and the synergy between the NDVI and slope was the strongest, at q = 0.646.
Full article
(This article belongs to the Section Urban Water Management)
Open AccessArticle
Real-Time Control of A2O Process in Wastewater Treatment Through Fast Deep Reinforcement Learning Based on Data-Driven Simulation Model
by
Fukang Hu, Xiaodong Zhang, Baohong Lu and Yue Lin
Water 2024, 16(24), 3710; https://doi.org/10.3390/w16243710 (registering DOI) - 22 Dec 2024
Abstract
Real-time control (RTC) can be applied to optimize the operation of the anaerobic–anoxic–oxic (A2O) process in wastewater treatment for energy saving. In recent years, many studies have utilized deep reinforcement learning (DRL) to construct a novel AI-based RTC system for optimizing the A2O
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Real-time control (RTC) can be applied to optimize the operation of the anaerobic–anoxic–oxic (A2O) process in wastewater treatment for energy saving. In recent years, many studies have utilized deep reinforcement learning (DRL) to construct a novel AI-based RTC system for optimizing the A2O process. However, existing DRL methods require the use of A2O process mechanistic models for training. Therefore they require specified data for the construction of mechanistic models, which is often difficult to achieve in many wastewater treatment plants (WWTPs) where data collection facilities are inadequate. Also, the DRL training is time-consuming because it needs multiple simulations of mechanistic model. To address these issues, this study designs a novel data-driven RTC method. The method first creates a simulation model for the A2O process using LSTM and an attention module (LSTM-ATT). This model can be established based on flexible data from the A2O process. The LSTM-ATT model is a simplified version of a large language model (LLM), which has much more powerful ability in analyzing time-sequence data than usual deep learning models, but with a small model architecture that avoids overfitting the A2O dynamic data. Based on this, a new DRL training framework is constructed, leveraging the rapid computational capabilities of LSTM-ATT to accelerate DRL training. The proposed method is applied to a WWTP in Western China. An LSTM-ATT simulation model is built and used to train a DRL RTC model for a reduction in aeration and qualified effluent. For the LSTM-ATT simulation, its mean squared error remains between 0.0039 and 0.0243, while its R-squared values are larger than 0.996. The control strategy provided by DQN effectively reduces the average DO setpoint values from 3.956 mg/L to 3.884 mg/L, with acceptable effluent. This study provides a pure data-driven RTC method for the A2O process in WWTPs based on DRL, which is effective in energy saving and consumption reduction. It also demonstrates that purely data-driven DRL can construct effective RTC methods for the A2O process, providing a decision-support method for management.
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(This article belongs to the Section Wastewater Treatment and Reuse)
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Open AccessArticle
Assessing the Vulnerability of Lakes in Western Kazakhstan to Climate Change and Anthropogenic Stressors
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Kairat M. Kulebayev, Sayat K. Alimkulov, Aisulu A. Tursunova, Lyazzat K. Makhmudova, Elmira K. Talipova, Assel A. Saparova, María-Elena Rodrigo-Clavero and Javier Rodrigo-Ilarri
Water 2024, 16(24), 3709; https://doi.org/10.3390/w16243709 (registering DOI) - 22 Dec 2024
Abstract
The global water crisis, which intensifies each year, underscores the urgent need for accurate assessment and sustainable management of freshwater resources. Lakes, as significant components of surface water systems, are particularly vulnerable to human activities and climate change due to their slow renewal
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The global water crisis, which intensifies each year, underscores the urgent need for accurate assessment and sustainable management of freshwater resources. Lakes, as significant components of surface water systems, are particularly vulnerable to human activities and climate change due to their slow renewal rates. Western Kazakhstan, a region affected by economic development and intensive mining activities, faces acute water scarcity. A reliable water supply is crucial to meeting the requirements of industrial operations and the needs of the region’s population. Understanding the dynamics of lake systems and implementing effective conservation and restoration strategies are essential to addressing this challenge. This study, employing cartographic and remote sensing techniques, identified 323 lakes in Western Kazakhstan, covering a total area of 1944 km2. Comparative analysis with historical data from the 1960s and 1970s revealed a 23% decrease in the number of lakes exceeding 1 km2. The most significant decline was observed in the Atyrau and Mangystau Regions, where the number of such lakes diminished by a factor of three. These findings highlight the pressing need for an integrated, interdisciplinary approach to water resource management in Western Kazakhstan.
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(This article belongs to the Section Hydrology)
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Open AccessArticle
Algal Pigment Estimation Models to Assess Bloom Toxicity in a South American Lake
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Lien Rodríguez-López, David Francisco Bustos Usta, Lisandra Bravo Alvarez, Iongel Duran-Llacer, Luc Bourrel, Frederic Frappart, Rolando Cardenas and Roberto Urrutia
Water 2024, 16(24), 3708; https://doi.org/10.3390/w16243708 (registering DOI) - 22 Dec 2024
Abstract
In this study, we build an empirical model to estimate pigments in the South American Lake Villarrica. We use data from Dirección General de Aguas de Chile during the period of 1989–2024 to analyze the behavior of limnological parameters and trophic condition in
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In this study, we build an empirical model to estimate pigments in the South American Lake Villarrica. We use data from Dirección General de Aguas de Chile during the period of 1989–2024 to analyze the behavior of limnological parameters and trophic condition in the lake. Four seasonal linear regression models were developed by us, using a set of water quality variables that explain the values of phycocyanin pigment in Lake Villarrica. In the first case, we related chlorophyll-a (Chl-a) to phycocyanin, expecting to find a direct relationship between both variables, but this was not fulfilled for all seasons of the year. In the second case, in addition to Chl-a, we included water temperature, since this parameter has a great influence on the algal photosynthesis process, and we obtained better results. We discovered a typical seasonal variability given by temperature fluctuations in Lake Villarrica, where in the spring, summer, and autumn seasons, conditions are favorable for algal blooms, while in winter, the natural seasonal conditions do not allow increases in algal productivity. For a third case, we included the turbidity variable along with the variables mentioned above and the statistical performance metrics of the models improved significantly, obtaining R2 values of up to 0.90 in the case of the model for the fall season and a mean squared error (MSE) of 0.04 µg/L. In the last case used, we added the variable dissolved organic matter (MOD), and the models showed a slight improvement in their performance. These models may be applicable to other lakes with harmful algal blooms in order to alert the community to the potential toxicity of these events.
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(This article belongs to the Special Issue Technological and Mechanism Research on Algal Bloom Mitigation and Resource Recycling)
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Open AccessArticle
Numerical Simulation of the Hydrodynamic Behavior of an Offshore Platform Supported by a Jacket Structure in Waves
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Chongzhong Wu, Xianlin Jia, Tiaojian Xu and Wo Zhang
Water 2024, 16(24), 3707; https://doi.org/10.3390/w16243707 (registering DOI) - 22 Dec 2024
Abstract
The offshore jacket structure has the advantages of suitable stiffness, convenient construction, anti-collision, and strong fatigue resistance, and it is the main structural form of offshore converter station. By constructing a numerical wave tank for the hydrodynamic response analysis of the offshore jacket
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The offshore jacket structure has the advantages of suitable stiffness, convenient construction, anti-collision, and strong fatigue resistance, and it is the main structural form of offshore converter station. By constructing a numerical wave tank for the hydrodynamic response analysis of the offshore jacket structure, the wave field distribution around and the wave slamming load on the offshore jacket structure for the converter station under the action of waves are analyzed based on the Star CCM+ software 2206. In addition, the effects of wave height and wave period on its hydrodynamic loads are discussed. The results indicated that: (1) A thin jet layer can be formed on the wave-facing side of the square box when the waves attack the box, and the height of the jet is not the maximum when the horizontal load generated by the jet at the front of the box reaches the maximum value. (2) The pressure distribution on the wave-facing side of the square box for the converter station is relatively discrete, with the pressure in the middle part being slightly larger than that on both sides. At the bottom of the box, the pressure in the middle and back part is significantly larger than that in the front part. (3) When the waves attack the box for the converter station, it caused significant energy dissipation, and the horizontal load on the offshore jacket is less than that when no wave slamming occurs.
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(This article belongs to the Section Oceans and Coastal Zones)
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Open AccessReview
Regulating Denitrification in Constructed Wetlands: The Synergistic Role of Radial Oxygen Loss and Root Exudates
by
Haishu Sun, Yuan Zhou and Cancan Jiang
Water 2024, 16(24), 3706; https://doi.org/10.3390/w16243706 (registering DOI) - 22 Dec 2024
Abstract
Constructed wetland (CW) is a critical ecological engineering for wastewater treatment and improvement of water quality. Nitrogen (N) removal is one of the vital functions of CWs during operation, and N treatment in CWs is mainly affected by aquatic plants and denitrification carried
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Constructed wetland (CW) is a critical ecological engineering for wastewater treatment and improvement of water quality. Nitrogen (N) removal is one of the vital functions of CWs during operation, and N treatment in CWs is mainly affected by aquatic plants and denitrification carried out by microbes. However, due to their low efficiency and instability in N removal, further applications of CWs are limited. The review provides a view of two basic characteristics of aquatic plants, radial oxygen loss (ROL) and root exudates, and their coupled effect on denitrification processes in CWs. First, the role of aquatic plants in denitrification is presented. The individual roles of ROL and root exudates in regulating denitrification, as well as their interaction in this process, have been discussed. Also, the limitation of conventional techniques to reveal interaction between the plant and the microbes has been highlighted. Further research on coupling regulatory mechanisms of ROL and root exudates may be conducted to develop an optimal wetland design and improve biological N removal. This review offers new insights and directions for improving N removal in CWs by utilizing the synergistic effects of plant ROL and root exudates.
Full article
(This article belongs to the Special Issue ANAMMOX Based Technology for Nitrogen Removal from Wastewater)
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Open AccessArticle
Tolerance of the Marine Anammox Candidatus Scalindua to High Nitrate Concentrations: Implications for Recirculating Aquaculture Systems
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Jonathan Armand Charles Roques, Ebuka Unegbu, Naoki Fujii, Amélie Marqué, Federico Micolucci, Kristina Snuttan Sundell and Tomonori Kindaichi
Water 2024, 16(24), 3705; https://doi.org/10.3390/w16243705 (registering DOI) - 22 Dec 2024
Abstract
Recirculating aquaculture systems (RAS) hold significant potential for sustainable aquaculture by providing a stable, controlled environment that supports optimal fish growth and welfare. In RAS, ammonium (NH4+) is biologically converted into nitrate (NO3−) via nitrite (NO2
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Recirculating aquaculture systems (RAS) hold significant potential for sustainable aquaculture by providing a stable, controlled environment that supports optimal fish growth and welfare. In RAS, ammonium (NH4+) is biologically converted into nitrate (NO3−) via nitrite (NO2−) by nitrifying bacteria. As a result, NO3− usually accumulates in RAS and must subsequently be removed through denitrification in full RAS, or by regular water exchanges in partial RAS. The marine anammox bacteria Candidatus Scalindua can directly convert toxic NH4+ and NO2− into harmless nitrogen gas (N2) and has previously been identified as a promising alternative to the complex denitrification process or unsustainable frequent water exchanges in marine RAS. In this study, we evaluated the impact of high NO3− levels typically encountered in RAS on the performance and abundance of Ca. Scalindua in a laboratory-scale bioreactor. The bacterial composition of the granules, including the relative abundance of key nitrogen-cycling taxa, was analyzed along with the functional profile (i.e., NH4+ and NO2− removal efficiencies). For this purpose, a bioreactor was inoculated and fed a synthetic feed, enriched in NH4+, NO2−, minerals and trace elements until stabilization (Phase 1, 52 days). NO3− concentrations were then gradually increased to 400 mg·L−1 NO3−-N (Phase 2, 52 days), after which the reactor was followed for another 262 days (Phase 3). The reactor maintained high removal efficiencies; 88.0 ± 8.6% for NH4+ and 97.4 ± 1.7% for NO2− in Phase 2, and 95.0 ± 6.5% for NH4+ and 98.6 ± 2.7% for NO2− in Phase 3. The relative abundance of Ca. Scalindua decreased from 22.7% to 10.2% by the end of Phase 3. This was likely due to slower growth of Ca. Scalindua compared to heterotrophic bacteria present in the granule, which could use NO3− as a nitrogen source. Fluorescence in situ hybridization confirmed the presence of a stable population of Ca. Scalindua, which maintained high and stable NH4+ and NO2− removal efficiencies. These findings support the potential of Ca. Scalindua as an alternative filtering technology in marine RAS. Future studies should investigate pilot-scale applications under real-world conditions.
Full article
(This article belongs to the Special Issue Advanced Use of Anammox Process in Wastewater Treatment)
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Open AccessArticle
Evaluation of the Effects of Rainfall Infiltration Boundaries on the Stability of Unsaturated Soil Slopes Using the Particle Flow Code
by
Jian Zhang, Fangrui Hu, Qi Zhang, Jun Wang, Wenting Deng, Li Zhang and Xiaoquan Shao
Water 2024, 16(24), 3704; https://doi.org/10.3390/w16243704 (registering DOI) - 22 Dec 2024
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Rainfall infiltration is the primary triggering factor for the instability of unsaturated slopes. At present, rainfall-induced landslides are mainly considered to be influenced by the overall infiltration conditions, while few investigations have been conducted on the influence of infiltration boundaries on slope instability.
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Rainfall infiltration is the primary triggering factor for the instability of unsaturated slopes. At present, rainfall-induced landslides are mainly considered to be influenced by the overall infiltration conditions, while few investigations have been conducted on the influence of infiltration boundaries on slope instability. This study proposes a rainfall infiltration method using a discrete element model (DEM), which is based on saturated–unsaturated seepage theory. The influence of three infiltration boundaries on the instability of homogeneous unsaturated soil slopes was studied. The results showed that the infiltration rate of a rainfall-covered slope crest was faster than that of rainfall-covered slope surfaces. A transient saturated zone was formed on the slope surface after a certain duration of rainfall. Rain infiltration boundary conditions significantly impact the saturation distribution, seepage field, failure mode, and failure period. The safety and stability factors for the rainfall-covered slope crest and full area decreased monotonically with the increase in rainfall duration, while there was a brief increase at the initial stage of rainfall before a quick decline for rainfall-covered slope surfaces. This research provides a preliminary exploration of the impact of rainfall boundary conditions on the instability of slopes, offering a reference basis for DEM simulations that consider slope stability under the influence of rainfall infiltration.
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Open AccessArticle
Production and Characterization of Graphene Oxide for Adsorption Analysis of the Emerging Pollutant Butylparaben
by
Lorena Maihury Santos Tsubouchi, Edson Araujo de Almeida, Diego Espirito Santo, Evandro Bona, Gustavo Leite Dias Pereira, Veeriah Jegatheesan, Lucio Cardozo-Filho, Ana Paula Peron and Osvaldo Valarini Junior
Water 2024, 16(24), 3703; https://doi.org/10.3390/w16243703 (registering DOI) - 22 Dec 2024
Abstract
Emerging pollutants such as butylparaben (BP) are often difficult to remove via conventional wastewater treatment. Therefore, this study aimed to produce and characterize graphene oxide (GO) and evaluate the adsorption of BP on this adsorbent. The GO was made using the Hummers method
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Emerging pollutants such as butylparaben (BP) are often difficult to remove via conventional wastewater treatment. Therefore, this study aimed to produce and characterize graphene oxide (GO) and evaluate the adsorption of BP on this adsorbent. The GO was made using the Hummers method and characterized by TGA/DTA, XRD, XRF, BET, point of zero charge (pHpzc), SEM, and the Boehman method. Adsorption experiments were performed in a batch system. The removal efficiency from a Box–Behnken experimental design was 84.3% at a BP concentration 600 µg∙L−1, adsorbent five g∙L−1, and pH 7 in solution. The first-order (PFO) kinetics obtained the best fit to the experimental data compared to the other models tested in this study: pseudo-second-order (PSO), Elovich (ELC), and intra-particle diffusion (IPD). The Langmuir isotherm provided the best fit compared to the Freundlich isotherm. The temperature effect showed that the system has a spontaneous adsorption process, with a Gibbs energy lower than zero, and that increasing the temperature increases the adsorption capacity. The ionic effect showed that increasing the salt concentration of 1 M increased the repulsive forces but did not decrease the adsorption capacity. The regeneration cycle showed a rate of 85% up to the second cycle. The toxicity analysis confirmed the efficiency of the adsorption process using GO before and after BP adsorption on GO.
Full article
(This article belongs to the Special Issue Water Treatment Technology for Emerging Contaminants)
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Open AccessArticle
DFMM-Precip: Deep Fusion of Multi-Modal Data for Accurate Precipitation Forecasting
by
Jinwen Li, Li Wu, Jiarui Liu, Xiaoying Wang and Wei Xue
Water 2024, 16(24), 3702; https://doi.org/10.3390/w16243702 (registering DOI) - 22 Dec 2024
Abstract
Weather forecasting is a classical problem in remote sensing, in which precipitation is difficult to predict accurately because of its complex physical motion. Precipitation significantly impacts human life, work, and the ecological environment. Precise precipitation forecasting is vital for water resource management, ecological
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Weather forecasting is a classical problem in remote sensing, in which precipitation is difficult to predict accurately because of its complex physical motion. Precipitation significantly impacts human life, work, and the ecological environment. Precise precipitation forecasting is vital for water resource management, ecological protection, and disaster mitigation through precise precipitation forecasting. This study introduces an innovative deep learning-based precipitation-forecasting method DFMM-Precip that integrates reanalysis of precipitation data and satellite data using a multi-modal fusion layer and predicts future precipitation details through a global–local joint temporal-spatial attention mechanism. By effectively combining satellite infrared data with reanalysis data, the approach enhances the accuracy of precipitation forecasting. Experimental results for 24 h precipitation forecasts show that DFMM-Precip’s multi-modal fusion layer successfully integrates multi-modal data related to precipitation, leading to improved forecast accuracy. In particular, the global–local joint temporal-spatial attention mechanism provides precise, detailed forecasting of spatial and temporal precipitation patterns, outperforming other state-of-the-art models. The MSE of the forecasting results is 10 times lower than that of the advanced RNN model and 2.4 times lower than that of the advanced CNN model with single-modal data input. The probability of successful rainfall prediction is improved by more than 10%.
Full article
(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)
Open AccessArticle
Urban Single Precipitation Events: A Key for Characterizing Sources of Air Contaminants and the Dynamics of Atmospheric Chemistry Exchanges
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Maciej Górka, Aldona Pilarz, Magdalena Modelska, Anetta Drzeniecka-Osiadacz, Anna Potysz and David Widory
Water 2024, 16(24), 3701; https://doi.org/10.3390/w16243701 (registering DOI) - 22 Dec 2024
Abstract
The chemistry of atmospheric precipitation serves as an important proxy for discriminating the source(s) of air contaminants in urban environments as well as to discuss the dynamic of atmospheric chemistry exchanges. This approach can be undertaken at time scales varying from single events
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The chemistry of atmospheric precipitation serves as an important proxy for discriminating the source(s) of air contaminants in urban environments as well as to discuss the dynamic of atmospheric chemistry exchanges. This approach can be undertaken at time scales varying from single events to seasonal and yearly time frames. Here, we characterized the chemical composition of two single rain episodes (18 July 2018 and 21 February 2019) collected in Wrocław (SW Poland). Our results demonstrated inner variations and seasonality (within the rain event as well as between summer and winter), both in ion concentrations as well as in their potential relations with local air contaminants and scavenging processes. Coupling statistical analysis of chemical parameters with meteorological/synoptic conditions and HYSPLIT back trajectories allowed us to identify three main factors (i.e., principal components; PC) controlling the chemical composition of precipitation, and that these fluctuated during each event: (i) PC1 (40%) was interpreted as reflecting the long-range transport and/or anthropogenic influences of emission sources that included biomass burning, fossil fuel combustion, industrial processes, and inputs of crustal origin; (ii) PC2 (20%) represents the dissolution of atmospheric CO2 and HF into ionic forms; and (iii) PC3 (20%) originates from agricultural activities and/or biomass burning. Time variations during the rain events showed that each factor was more important at the start of the event. The study of both SO42− and Ca2+ concentrations showed that while sea spray inputs fluctuated during both rain events, their overall impact was relatively low. Finally, below-cloud particle scavenging processes were only observed for PM10 at the start of the winter rain episode, which was probably explained by the corresponding low rain intensity and an overlap from local aerosol emissions. Our study demonstrates the importance of multi-time scale approaches to explain the chemical variability in rainwater and both its relation to emission sources and the atmosphere operating processes.
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(This article belongs to the Section Urban Water Management)
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Open AccessArticle
Machine Learning-Based Model Prediction of an Adsorption Desalination System and Investigation of the Impact of Parameters on the System’s Outputs
by
Taleb Zarei, Masoud Chatavi, Masoud Nazari, Amirhossein Amirfakhraei, Mohsen Salimi and Majid Amidpour
Water 2024, 16(24), 3700; https://doi.org/10.3390/w16243700 (registering DOI) - 22 Dec 2024
Abstract
Adsorption desalination (AD) has emerged as a novel technique for desalination, which works cyclically and via switching, and various variables have an effect on its performance. This study uses machine learning procedures to present a model predictive approach for adsorption desalination systems. The
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Adsorption desalination (AD) has emerged as a novel technique for desalination, which works cyclically and via switching, and various variables have an effect on its performance. This study uses machine learning procedures to present a model predictive approach for adsorption desalination systems. The adsorption desalination system will be modeled through the utilization of multilayer perceptron (MLP) and radial-based function (RBF) neural network approach hes. The purpose of this research is to provide valuable insights into optimizing system efficiency and expanding the applicability of adsorption desalination technologies by investigating the strengths and limitations of each model. Hence, the Specific Daily Water Production (SDWP), coefficient of performance (COP), and specific cooling power (SCP) are determined. There are 55 instances in the dataset, each with five input variables: temperatures of the evaporator and condenser, adsorption beds, and inlet hot saltwater. Additionally, three output variables are recorded: COP, SCP, and SDWP. The results of this investigation show that the MLP is more effective for simulating the AD system, and the Roots of Mean Square Error of COP, SCP, and SDWP are 0.002, 0.5921, and 0.0465, respectively. Then, the impact of input factors on output parameters was examined. The results show that the inlet hot saltwater temperature parameter affected the output parameters the most. Subsequently, the COP parameter is mainly affected by the adsorption beds, evaporator, and condenser temperature. The SCP parameter is primarily influenced by the inlet hot saltwater temperature, condenser temperature, temperatures of the two adsorption beds, and evaporator temperature.
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(This article belongs to the Section Oceans and Coastal Zones)
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Open AccessArticle
Combining Physical Hydrological Model with Explainable Machine Learning Methods to Enhance Water Balance Assessment in Glacial River Basins
by
Ruibiao Yang, Jinglu Wu, Guojing Gan, Ru Guo and Hongliang Zhang
Water 2024, 16(24), 3699; https://doi.org/10.3390/w16243699 (registering DOI) - 22 Dec 2024
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The implementation of accurate water balance assessment in glacier basins is essential for the management and sustainable development of water resources in the basins. In this study, a hybrid modeling framework was constructed to enhance runoff prediction and water balance assessment in glacier
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The implementation of accurate water balance assessment in glacier basins is essential for the management and sustainable development of water resources in the basins. In this study, a hybrid modeling framework was constructed to enhance runoff prediction and water balance assessment in glacier basins. An improved physical hydrological model (SEGSWAT+) was combined with a machine learning model (ML) to capture the relationship between runoff residuals and water balance components through the Shapley additive explanations (SHAP) method. Based on the enhancement of the runoff fitting results of the existing model, the runoff residuals are decomposed and used to correct the hydrological process component values, thus improving the accuracy of the water balance results. We evaluated the performance and correction results of the method using various ML methods. We analyzed the results for two consecutive periods from 1959 to 2022 for the glacial sub-basins of three tributaries of the Upper Ili River Basin in central Asia. The results show that the hybrid framework based on extreme gradient boosting (XGBoost) with an average NSE value of 0.93 has the best performance, and the bias based on the evapotranspiration component and soil water content change component is reduced by 3.2–5%, proving the effectiveness of the water balance correction. This study advances the interpretation of ML models for hydrologic assessment of areas with complex hydrodynamic characteristics.
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Open AccessArticle
Unsafe Havens: The Meaning and Use of Springs in the Central Region of Afar Province in Ethiopia
by
Roderick Fensham, Ali Ahmed Bil’a, Adem Mohammed Idris, Kflay Gebrehiwot, Tadesse Fetahi and Getacher Beyene Estifanos
Water 2024, 16(24), 3698; https://doi.org/10.3390/w16243698 (registering DOI) - 22 Dec 2024
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Background: We explore how springs and their pastures are utilised by nomadic pastoralists and how they influence interchange and conflict between the custodians of the springs and the society of pastoralists in the broader region. Methods: The custodians of three spring locations in
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Background: We explore how springs and their pastures are utilised by nomadic pastoralists and how they influence interchange and conflict between the custodians of the springs and the society of pastoralists in the broader region. Methods: The custodians of three spring locations in the Afar region of Ethiopia were interviewed to identify the advantages, and the challenges, of having springs on a pastoral estate. Results: The springs provide permanent water and health benefits, are used for cooking, and provide permanent pasture for livestock. In the Dobi Valley, the groundwater supporting the springs supports a population of the palm garayto (Hyphaene thebaica), which provides thatch and a liquor derived from the sap. The custodians of the springs are baaro-mara for their homelands and they welcome and provide access to the resources of the spring to Afar outsiders, gurro-mara. Recent invasions by the Somali Issa tribe have resulted in the deaths and displacement of Afar residents at Alalo-bad and Teo. The prickly shrub Prosopis juliflora has become another invasive threat with great impacts on the livelihood of the baaro-mara at two locations. Conclusions: Springs are oases where permanent water provides perennial resources in a semi-desert. However, the tenure of these precious havens can be subject to tribal contest and the resources of the springs have been recently undermined by invasion of a plant from another continent. The removal of the incipient population of Prosopis juliflora should be a priority before it proliferates further.
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Effects of Underwater Lighting Time on the Growth of Vallisneria spinulosa Yan and Its Water Restoration Process
by
Mengyi Wei, Jinshan Zhao, Xiaolin Zhou, Fengdan Li, Min Zhao, Xiangyong Zheng, Ye Tang, Chang Yang, Zhenmin Jin and Suqing Wu
Water 2024, 16(24), 3697; https://doi.org/10.3390/w16243697 (registering DOI) - 21 Dec 2024
Abstract
Submerged macrophytes play a crucial role in the ecological restoration of water bodies, and their restoration capacity is closely related to the underwater lighting conditions. This study explored the effects of underwater lighting time on the growth characteristics of Vallisneria spinulosa Yan (
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Submerged macrophytes play a crucial role in the ecological restoration of water bodies, and their restoration capacity is closely related to the underwater lighting conditions. This study explored the effects of underwater lighting time on the growth characteristics of Vallisneria spinulosa Yan (V. spinulosa) and its water restoration process. V. spinulosa achieved a higher Fv/Fm (0.64), ETRmax (10.43), chlorophyll content (0.85 mg/g), and removal efficiency of total phosphorus (0.37 × 10−3 g m−3 d−1) and a lower algal abundance with a longer lighting time (18 h every day). However, a higher removal efficiency of NH4+–N and TN was obtained with a shorter lighting time (6–12 h every day). The lighting time showed a significance influence on the microbial community of the V. spinulosa growth system, and the influence was significantly different in different regions. Temperature and electrical conductivity were the main environmental impact factors for the microbial community under different lighting times. The abundances of Proteobacteria, Bacteroidota, and Verrucomicrobia exhibited a great positive correlation with each other and a strong positive correlation with the two factors. In addition, the lighting time had a strongly significant correlation with the physical and chemical characteristics of the water environment (p < 0.001) and a significant correlation with the growth characteristics of V. spinulosa (p < 0.05).
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(This article belongs to the Special Issue Ecological Wastewater Treatment and Resource Utilization)
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Optimization of a Chlorella vulgaris-Based Carbon Sequestration Technique Using an Alkaline Medium of Wood Biomass Ash Extract
by
György Fekete, Szandra Klátyik, András Sebők, Anna Boglárka Dálnoki, Anita Takács, Miklós Gulyás, Imre Czinkota, András Székács, Csaba Gyuricza and László Aleksza
Water 2024, 16(24), 3696; https://doi.org/10.3390/w16243696 (registering DOI) - 21 Dec 2024
Abstract
Algae communities as primary producers are essential elements of aquatic ecosystems and contribute significantly to oxygen production, carbon dioxide fixation, and nutrient transport processes in water bodies. The use of algae-based carbon capture and storage technologies does not produce harmful by-products that require
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Algae communities as primary producers are essential elements of aquatic ecosystems and contribute significantly to oxygen production, carbon dioxide fixation, and nutrient transport processes in water bodies. The use of algae-based carbon capture and storage technologies does not produce harmful by-products that require disposal, and the resulting algal biomass can be valuable across various industrial sectors. In this study, model experiments were conducted to develop sequential absorption–microalgae hybrid CO2-capture methods. To facilitate CO2 capture from flue gases, wood biomass ash (WBA), an agricultural by-product, was utilized for its alkaline properties, while the flue gas scrubbing medium was regenerated by algae that restored alkalinity during their growth. In our experiments, one of our goals was to determine the optimal conditions for achieving maximum algal biomass growth in the shortest possible time. The suitability of WBA for flue gas cleaning was tested via simulation of CO2 introduction. Moreover, a method was developed to determine the dissolved inorganic carbon content with the use of an OxiTop device monitoring the changes in pressure. The applied device was a closed, static, and pressure-based respirometer originally designed to determine the biological activity of microorganisms in both solid and liquid samples. In addition, the effects of CO2-enriched WBA extract on algae cultivation were also analyzed, confirming that it imposed no growth inhibition and identifying the concentration (10% WBA) that optimally promoted algal growth. The optimal initial algal concentration and nutrient conditions for maximum growth were also determined.
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(This article belongs to the Special Issue Microalgae Control and Utilization: Challenges and Perspectives)
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