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Sediment Transport Constraints for Restoration of the Ebro Delta
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Comparative Analysis of Livestock Wastewater Reuse Under Summer and Winter Conditions at a Scale-Down Microalgae Culture
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Insights to Estimate the Largest 1/3, 1/10, and 1/100 of Offshore Wave Heights and Periods Under Fetch-Limited Conditions in the Central Aegean Sea
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Waterway Regulation Effects on River Hydrodynamics and Hydrological Regimes: A Numerical Investigation
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Asymmetric Impacts of Urbanization on Extreme Hourly Precipitation Across the Yangtze River Delta Urban Agglomeration During 1978–2012
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 (Aquatic Science)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 19.1 days after submission; acceptance to publication is undertaken in 2.6 days (median values for papers published in this journal in the first half of 2025).
- 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.
- Journal Clusters of Water Resources: Water, Journal of Marine Science and Engineering, Hydrology, Resources, Oceans, Limnological Review, Coasts.
Impact Factor:
3.0 (2024);
5-Year Impact Factor:
3.3 (2024)
Latest Articles
Strategic Planning for Nature-Based Solutions in Heritage Cities: Enhancing Urban Water Sustainability
Water 2025, 17(14), 2110; https://doi.org/10.3390/w17142110 (registering DOI) - 15 Jul 2025
Abstract
Nature-Based Solutions (NBSs) offer promising pathways to enhance ecological resilience and address urban water challenges, particularly in heritage cities where conventional gray infrastructure often fails to balance environmental needs with cultural preservation. This study proposes a strategic framework for the integration of NBSs
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Nature-Based Solutions (NBSs) offer promising pathways to enhance ecological resilience and address urban water challenges, particularly in heritage cities where conventional gray infrastructure often fails to balance environmental needs with cultural preservation. This study proposes a strategic framework for the integration of NBSs into historic urban landscapes by employing Internal–External (IE) matrix modeling and an impact–uncertainty assessment, grounded in a structured evaluation of key internal strengths and weaknesses, as well as external opportunities and threats. The Internal Factor Evaluation (IFE) score of 2.900 indicates a favorable internal environment, characterized by the multifunctionality of NBS and their ability to reconnect urban populations with nature. Meanwhile, the External Factor Evaluation (EFE) score of 2.797 highlights moderate support from policy and public awareness but identifies barriers such as funding shortages and interdisciplinary coordination. Based on these findings, two strategies are developed: an SO (Strength–Opportunity) strategy, promoting community-centered and policy-driven NBS design, and a WO (Weakness–Opportunity) strategy, targeting resource optimization through legal support and cross-sectoral collaboration. This study breaks new ground by transforming theoretical NBS concepts into actionable, culturally sensitive planning tools that enable decision-makers to navigate the unique challenges of implementing adaptive stormwater and environmental management in historically constrained urban environments.
Full article
(This article belongs to the Special Issue Sustainable Water Treatment Systems: Green Infrastructure and Bioremediation)
Open AccessArticle
Predictive Sinusoidal Modeling of Sedimentation Patterns in Irrigation Channels via Image Analysis
by
Holger Manuel Benavides-Muñoz
Water 2025, 17(14), 2109; https://doi.org/10.3390/w17142109 (registering DOI) - 15 Jul 2025
Abstract
Sediment accumulation in irrigation channels poses a significant challenge to water resource management, impacting hydraulic efficiency and agricultural sustainability. This study introduces an innovative multidisciplinary framework that integrates advanced image analysis (FIJI/ImageJ 1.54p), statistical validation (RStudio), and vector field modeling with a novel
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Sediment accumulation in irrigation channels poses a significant challenge to water resource management, impacting hydraulic efficiency and agricultural sustainability. This study introduces an innovative multidisciplinary framework that integrates advanced image analysis (FIJI/ImageJ 1.54p), statistical validation (RStudio), and vector field modeling with a novel Sinusoidal Morphodynamic Bedload Transport Equation (SMBTE) to predict sediment deposition patterns with high precision. Conducted along the Malacatos River in La Tebaida Linear Park, Loja, Ecuador, the research captured a natural sediment transport event under controlled flow conditions, transitioning from pressurized pipe flow to free-surface flow. Observed sediment deposition reduced the hydraulic cross-section by approximately 5 cm, notably altering flow dynamics and water distribution. The final SMBTE model (Model 8) demonstrated exceptional predictive accuracy, achieving RMSE: 0.0108, R2: 0.8689, NSE: 0.8689, MAE: 0.0093, and a correlation coefficient exceeding 0.93. Complementary analyses, including heatmaps, histograms, and vector fields, revealed spatial heterogeneity, local gradients, and oscillatory trends in sediment distribution. These tools identified high-concentration sediment zones and quantified variability, providing actionable insights for optimizing canal design, maintenance schedules, and sediment control strategies. By leveraging open-source software and real-world validation, this methodology offers a scalable, replicable framework applicable to diverse water conveyance systems. The study advances understanding of sediment dynamics under subcritical (Fr ≈ 0.07) and turbulent flow conditions (Re ≈ 41,000), contributing to improved irrigation efficiency, system resilience, and sustainable water management. This research establishes a robust foundation for future advancements in sediment transport modeling and hydrological engineering, addressing critical challenges in agricultural water systems.
Full article
(This article belongs to the Section Water Erosion and Sediment Transport)
Open AccessArticle
Quantitative Assessment of Flood Risk Through Multi Parameter Morphometric Analysis and GeoAI: A GIS-Based Study of Wadi Ranuna Basin in Saudi Arabia
by
Maram Hamed AlRifai, Abdulla Al Kafy and Hamad Ahmed Altuwaijri
Water 2025, 17(14), 2108; https://doi.org/10.3390/w17142108 (registering DOI) - 15 Jul 2025
Abstract
The integration of traditional geomorphological approaches with advanced artificial intelligence techniques represents a promising frontier in flood risk assessment for arid regions. This study presents a comprehensive analysis of the Wadi Ranuna basin in Medina, Saudi Arabia, combining detailed morphometric parameters with advanced
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The integration of traditional geomorphological approaches with advanced artificial intelligence techniques represents a promising frontier in flood risk assessment for arid regions. This study presents a comprehensive analysis of the Wadi Ranuna basin in Medina, Saudi Arabia, combining detailed morphometric parameters with advanced Geospatial Artificial Intelligence (GeoAI) algorithms to enhance flood susceptibility modeling. Using digital elevation models (DEMs) and geographic information systems (GISs), we extracted 23 morphometric parameters across 67 sub-basins and applied XGBoost, Random Forest, and Gradient Boosting (GB) models to predict both continuous flood susceptibility indices and binary flood occurrences. The machine learning models utilize morphometric parameters as input features to capture complex non-linear interactions, including threshold-dependent relationships where the stream frequency impact intensifies above 3.0 streams/km2, and the compound effects between the drainage density and relief ratio. The analysis revealed that the basin covers an area of 188.18 km2 with a perimeter of 101.71 km and contains 610 streams across six orders. The basin exhibits an elongated shape with a form factor of 0.17 and circularity ratio of 0.23, indicating natural flood-moderating characteristics. GB emerged as the best-performing model, achieving an RMSE of 6.50 and an R2 value of 0.9212. Model validation through multi-source approaches, including field verification at 35 locations, achieved 78% spatial correspondence with documented flood events and 94% accuracy for very high susceptibility areas. SHAP analysis identified the stream frequency, overland flow length, and drainage texture as the most influential predictors of flood susceptibility. K-Means clustering uncovered three morphometrically distinct zones, with Cluster 1 exhibiting the highest flood risk potential. Spatial analysis revealed 67% of existing infrastructure was located within high-risk zones, with 23 km of major roads and eight critical facilities positioned in flood-prone areas. The spatial distribution of GBM-predicted flood susceptibility identified high-risk zones predominantly in the central and southern parts of the basin, covering 12.3% (23.1 km2) of the total area. This integrated approach provides quantitative evidence for informed watershed management decisions and demonstrates the effectiveness of combining traditional morphometric analysis with advanced machine learning techniques for enhanced flood risk assessment in arid regions.
Full article
(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources—an Issue of Environmental Global Safety)
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Open AccessReview
Integrated Application of Biofloc Technology in Aquaculture: A Review
by
Changwei Li, Zhenbo Ge, Limin Dai and Yuan Chen
Water 2025, 17(14), 2107; https://doi.org/10.3390/w17142107 (registering DOI) - 15 Jul 2025
Abstract
Although biofloc technology (BFT) currently offers advantages such as improving aquaculture water quality, providing natural bait for cultured animals, and reducing pests and diseases, single BFT systems face technical bottlenecks, including the complex regulation of the carbon–nitrogen ratio, accumulation of suspended substances, and
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Although biofloc technology (BFT) currently offers advantages such as improving aquaculture water quality, providing natural bait for cultured animals, and reducing pests and diseases, single BFT systems face technical bottlenecks, including the complex regulation of the carbon–nitrogen ratio, accumulation of suspended substances, and acidification of the bottom sludge. Therefore, constructing a composite system with complementary functions through technology integration, such as with aquaponics, biofilm technology, integrated multi-trophic aquaculture systems (IMTAs), and recirculating aquaculture systems (RASs), has become the key path to breaking through industrialization barriers. This paper systematically reviews the action mechanisms, synergistic effects, and challenges of the four mainstream integration models incorporating BFT, providing theoretical support for the environmental–economic balance of intensive aquaculture.
Full article
(This article belongs to the Special Issue Aquaculture Productivity and Environmental Sustainability)
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Open AccessArticle
Developing a Remote Sensing-Based Approach for Agriculture Water Accounting in the Amman–Zarqa Basin
by
Raya A. Al-Omoush, Jawad T. Al-Bakri, Qasem Abdelal, Muhammad Rasool Al-Kilani, Ibraheem Hamdan and Alia Aljarrah
Water 2025, 17(14), 2106; https://doi.org/10.3390/w17142106 (registering DOI) - 15 Jul 2025
Abstract
In water-scarce regions such as Jordan, accurate tracking of water flows is critical for informed water management. This study applied the Water Accounting Plus (WA+) framework using open-source remote sensing data from the FAO WaPOR portal to develop agricultural water accounting (AWA) for
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In water-scarce regions such as Jordan, accurate tracking of water flows is critical for informed water management. This study applied the Water Accounting Plus (WA+) framework using open-source remote sensing data from the FAO WaPOR portal to develop agricultural water accounting (AWA) for the Amman–Zarqa Basin (AZB) during 2014–2022. Inflows, outflows, and water consumption were quantified using WaPOR and other open datasets. The results showed a strong correlation between WaPOR precipitation (P) and rainfall station data, while comparisons with other remote sensing sources were weaker. WaPOR evapotranspiration (ET) values were generally lower than those from alternative datasets. To improve classification accuracy, a correction of the WaPOR-derived land cover map was performed. The revised map achieved a producer’s accuracy of 15.9% and a user’s accuracy of 86.6% for irrigated areas. Additionally, ET values over irrigated zones were adjusted, resulting in a fivefold improvement in estimates. These corrections significantly enhanced the reliability of key AWA indicators such as basin closure, ET fraction, and managed fraction. The findings demonstrate that the accuracy of P and ET data strongly affects AWA outputs, particularly the estimation of percolation and beneficial water use. Therefore, calibrating remote sensing data is essential to ensure reliable water accounting, especially in agricultural settings where data uncertainty can lead to misleading conclusions. This study recommends the use of open-source datasets such as WaPOR—combined with field validation and calibration—to improve agricultural water resource assessments and support decision making at basin and national levels.
Full article
(This article belongs to the Special Issue Remote Sensing Application in Support of Water-Soil-Plant Relationships)
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Open AccessArticle
Tracing Sulfate Sources of Surface Water and Groundwater in Liuyang River Basin Based on Hydrochemistry and Environmental Isotopes
by
Lei Wang, Yi Li, Yanpeng Zhang, Wei Liu and Hongxin Zhang
Water 2025, 17(14), 2105; https://doi.org/10.3390/w17142105 (registering DOI) - 15 Jul 2025
Abstract
Sulfate as a potential pollution source in the water environment of the basin, identifying sulfate sources and migration mechanisms is essential for protecting the water environment and ensuring sustainable water management. Liuyang River is a primary tributary of the Xiangjiang River. It has
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Sulfate as a potential pollution source in the water environment of the basin, identifying sulfate sources and migration mechanisms is essential for protecting the water environment and ensuring sustainable water management. Liuyang River is a primary tributary of the Xiangjiang River. It has experienced progressively intensifying anthropogenic influences in recent decades, manifested by sustained sulfate concentration increases. However, the sulfate sources and their contributions were not clear. This study used hydrochemistry and multi-isotopes methods combined with Simmr model to study the hydrochemical characteristics, sulfate sources, and migration–transformation processes of surface water and groundwater. The results showed that the hydrochemical types of surface water were HCO3-Ca and HCO3·SO4-Ca·Mg, and groundwater were HCO3-Ca, HCO3-Ca·Mg, and HCO3·SO4-Ca. Ions in the water primarily originated from carbonate and silicate rocks dissolution and sulfide oxidation, augmented by mining operations, sewage discharge, and chemical production. The analyses of hydrochemistry, isotopes, and Simmr model revealed that surface water sulfate originated from soil sulfate (35.70%), sulfide oxidation (26.56%), sewage (16.58%), and atmospheric precipitation (12.45%). Groundwater sulfate was derived predominantly from sewage (34.96%), followed by soil sulfate (28.09%), atmospheric precipitation (17.35%), and sulfide oxidation (12.25%). Sulfate migration and transformation were controlled by the natural environment and anthropogenic impacts. When unaffected by human activities, sulfate mainly originated from soil and atmospheric precipitation, relating to topography, geological conditions, agricultural activities, and precipitation intensity. However, in regions with intense human activities, contributions from sewage and sulfide oxidation significantly increased due to the influences of mining and industrial activities.
Full article
(This article belongs to the Special Issue Groundwater Quality and Contamination at Regional Scales)
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Anticipating Future Hydrological Changes in the Northern River Basins of Pakistan: Insights from the Snowmelt Runoff Model and an Improved Snow Cover Data
by
Urooj Khan, Romana Jamshed, Adnan Ahmad Tahir, Faizan ur Rehman Qaisar, Kunpeng Wu, Awais Arifeen, Sher Muhammad, Asif Javed and Muhammad Abrar Faiz
Water 2025, 17(14), 2104; https://doi.org/10.3390/w17142104 (registering DOI) - 15 Jul 2025
Abstract
The water regime in Pakistan’s northern region has experienced significant changes regarding hydrological extremes like floods because of climate change. Coupling hydrological models with remote sensing data can be valuable for flow simulation in data-scarce regions. This study focused on simulating the snow-
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The water regime in Pakistan’s northern region has experienced significant changes regarding hydrological extremes like floods because of climate change. Coupling hydrological models with remote sensing data can be valuable for flow simulation in data-scarce regions. This study focused on simulating the snow- and glacier-melt runoff using the snowmelt runoff model (SRM) in the Gilgit and Kachura River Basins of the upper Indus basin (UIB). The SRM was applied by coupling it with in situ and improved cloud-free MODIS snow and glacier composite satellite data (MOYDGL06) to simulate the flow under current and future climate scenarios. The SRM showed significant results: the Nash–Sutcliffe coefficient (NSE) for the calibration and validation period was between 0.93 and 0.97, and the difference in volume (between the simulated and observed flow) was in the range of −1.5 to 2.8% for both catchments. The flow tends to increase by 0.3–10.8% for both regions (with a higher increase in Gilgit) under mid- and late-21st-century climate scenarios. The Gilgit Basin’s higher hydrological sensitivity to climate change, compared to the Kachura Basin, stems from its lower mean elevation, seasonal snow dominance, and greater temperature-induced melt exposure. This study concludes that the simple temperature-based models, such as the SRM, coupled with improved satellite snow cover data, are reliable in simulating the current and future flows from the data-scarce mountainous catchments of Pakistan. The outcomes are valuable and can be used to anticipate and lessen any threat of flooding to the local community and the environment under the changing climate. This study may support flood assessment and mapping models in future flood risk reduction plans.
Full article
(This article belongs to the Special Issue Extreme Rainfall and Hydrological Extremes: Monitoring and Prediction Using Machine Learning and Physical Modeling)
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Open AccessArticle
Coupled Simulation of the Water–Food–Energy–Ecology System Under Extreme Drought Events: A Case Study of Beijing–Tianjin–Hebei, China
by
Huanyu Chang, Naren Fang, Yongqiang Cao, Jiaqi Yao and Zhen Hong
Water 2025, 17(14), 2103; https://doi.org/10.3390/w17142103 (registering DOI) - 15 Jul 2025
Abstract
The Beijing–Tianjin–Hebei (BTH) region is one of China’s most water-scarce yet economically vital areas, facing increasing challenges due to climate change and intensive human activities. This study develops an integrated Water–Food–Energy–Ecology (WFEE) simulation and regulation model to assess the system’s stability under coordinated
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The Beijing–Tianjin–Hebei (BTH) region is one of China’s most water-scarce yet economically vital areas, facing increasing challenges due to climate change and intensive human activities. This study develops an integrated Water–Food–Energy–Ecology (WFEE) simulation and regulation model to assess the system’s stability under coordinated development scenarios and extreme climate stress. A 500-year precipitation series was reconstructed using historical drought and flood records combined with wavelet analysis and machine learning models (Random Forest and Support Vector Regression). Results show that during the reconstructed historical megadrought (1633–1647), with average precipitation anomalies reaching −20% to −27%, leading to a regional water shortage rate of 16.9%, food self-sufficiency as low as 44.7%, and a critical reduction in ecological river discharge. Under future recommended scenario with enhanced water conservation, reclaimed water reuse, and expanded inter-basin transfers, the region could maintain a water shortage rate of 2.6%, achieve 69.3% food self-sufficiency, and support ecological water demand. However, long-term water resource degradation could still reduce food self-sufficiency to 62.9% and ecological outflows by 20%. The findings provide insights into adaptive water management, highlight the vulnerability of highly coupled systems to prolonged droughts, and support regional policy decisions on resilience-oriented water infrastructure planning.
Full article
(This article belongs to the Special Issue Advanced Perspectives on the Water–Energy–Food Nexus)
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Open AccessArticle
Ice Avalanche-Triggered Glacier Lake Outburst Flood: Hazard Assessment at Jiongpuco, Southeastern Tibet
by
Shuwu Li, Changhu Li, Zhengzheng Li, Lei Li and Wei Wang
Water 2025, 17(14), 2102; https://doi.org/10.3390/w17142102 (registering DOI) - 15 Jul 2025
Abstract
With ongoing global warming, glacier lake outburst floods (GLOFs) and associated debris flows pose increasing threats to downstream communities and infrastructure. Glacial lakes differ in their triggering factors and breach mechanisms, necessitating event-specific analysis. This study investigates the GLOF risk of Jiongpuco Lake,
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With ongoing global warming, glacier lake outburst floods (GLOFs) and associated debris flows pose increasing threats to downstream communities and infrastructure. Glacial lakes differ in their triggering factors and breach mechanisms, necessitating event-specific analysis. This study investigates the GLOF risk of Jiongpuco Lake, located in the southeastern part of the Tibetan Plateau, using an integrated approach combining remote sensing, field surveys, and numerical modeling. Results show that the lake has expanded significantly—from 2.08 km2 in 1990 to 5.43 km2 in 2021—with the most rapid increase observed between 2015 and 2016. InSAR data and optical imagery indicate that surrounding moraine deposits remain generally stable. However, ice avalanches from the glacier terminus are identified as the primary trigger for lake outburst via wave-induced overtopping. Mechanical and geomorphological analyses suggest that the moraine dam is resistant to downcutting erosion, reinforcing overtopping as the dominant failure mode. To assess potential impacts, three numerical simulation scenarios were conducted based on different avalanche volumes. Under the extreme scenario involving a 5-million m3 ice avalanche, the modeled peak discharge at the dam site reaches approximately 19,000 m3/s. Despite the high flood magnitude, the broad and gently sloped downstream terrain facilitates rapid attenuation of flood peaks, resulting in limited impact on downstream settlements. These findings offer critical insights for GLOF hazard assessment, disaster preparedness, and risk mitigation under a changing climate.
Full article
(This article belongs to the Special Issue Water-Related Landslide Hazard Process and Its Triggering Events)
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Open AccessArticle
Synthesizing a Tolerant Nitrogen Reduction Microbial Community Using Response Surface Methodology
by
Lei Chen, Danhua Wang, Lieyu Zhang, Ao Li, Xu Wang, Shishun Sun and Huijuan Feng
Water 2025, 17(14), 2101; https://doi.org/10.3390/w17142101 (registering DOI) - 15 Jul 2025
Abstract
Nitrogen-metabolizing microbes are the keystone drivers of reducing nitrogen pollutants in wastewater and natural waters, but the one-way experiment with fixed screening factors fails to discover the optimal scope of nitrogen-metabolizing microbes performing nitrogen reduction. This study novelly combines the one-way experiment and
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Nitrogen-metabolizing microbes are the keystone drivers of reducing nitrogen pollutants in wastewater and natural waters, but the one-way experiment with fixed screening factors fails to discover the optimal scope of nitrogen-metabolizing microbes performing nitrogen reduction. This study novelly combines the one-way experiment and response surface methodology (RSM) modeling to synthesize an effective nitrogen reduction microbial community, with the RSM model showing high goodness-of-fit (R2 = 0.83, p = 0.01) for optimizing the strain combination. Eight bacterial strains were isolated from contaminated sediment and activated sludge. Three efficient strains, arranged to Ignatzschieria indica, Staphylococcus epidermidis, and Acinetobacter baumannii by 16S rDNA sequencing, were screened using the above combination method to synthesize a nitrogen reduction microbial community. Within the synthetic microbial community, Ignatzschieria indica and Staphylococcus epidermidis possessed denitrification abilities, and Acinetobacter baumannii contributed to nitrification with 99% of ammonium oxidation. This synthesis microbial community displayed synchronous nitrification and denitrification under interval aeration and possessed wide pH tolerance from 6 to 10, with a steady >80% total inorganic nitrogen reduction. This research managed to synthesize a tolerant nitrogen reduction microbial community and provides novel insight for constructing synthetic microbial consortia.
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(This article belongs to the Section Water Quality and Contamination)
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Open AccessArticle
Effect of Fe2O3 Nanoparticles on the Efficiency of Anammox Process
by
Anna Rabajczyk, Songkai Qiu and Xinmin Zhan
Water 2025, 17(14), 2100; https://doi.org/10.3390/w17142100 (registering DOI) - 14 Jul 2025
Abstract
Nanotechnology plays an increasingly important role in the economy and human life, which means that more and more amounts of nanosubstances, including nanoparticles of metal oxides, together with wastewater, end up in the environment. This study aimed to study the impact of iron(III)
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Nanotechnology plays an increasingly important role in the economy and human life, which means that more and more amounts of nanosubstances, including nanoparticles of metal oxides, together with wastewater, end up in the environment. This study aimed to study the impact of iron(III) oxide nanoparticles (n-Fe2O3), which have magnetic properties, on the efficiency of the Anammox wastewater treatment process. The results indicate that n-Fe2O3 in the range of low concentrations may have a positive effect on nitrogen metabolism, increasing the efficiency of NH4-N removal to 98% in 120 min and at 30 °C. During the first 30 min of the process, when almost anaerobic conditions arose, nanoparticles of Fe2O3, stabilized the system by producing ROS. However, a constant control of TOC and pH is necessary because of the constant increase in the amount of organic compounds and H+ ions during the reaction. However, a longer contact of n-Fe2O3 with biomass causes the efficiency to decrease, and, as a result, the efficiency is lower compared to the system containing only Anammox.
Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
Open AccessReview
Recovery of Nutrients from the Aqueous Phase of Hydrothermal Liquefaction—A Review
by
Barbara Camila Bogarin Cantero, Yalin Li, Prasanta Kalita, Yuanhui Zhang and Paul Davidson
Water 2025, 17(14), 2099; https://doi.org/10.3390/w17142099 (registering DOI) - 14 Jul 2025
Abstract
Hydrothermal liquefaction (HTL) is a thermochemical conversion process that converts wet biomass into biocrude oil, a gas phase, a solid phase, and an aqueous phase (HTL-AP). An obstacle to the development and scaling of HTL is the volume of HTL-AP produced during the
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Hydrothermal liquefaction (HTL) is a thermochemical conversion process that converts wet biomass into biocrude oil, a gas phase, a solid phase, and an aqueous phase (HTL-AP). An obstacle to the development and scaling of HTL is the volume of HTL-AP produced during the process, which has high concentrations of nitrogen and carbon and cannot be disposed of in the environment without treatment. The HTL-AP is enriched with organic compounds, particularly light polar organics and nitrogenous compounds, which are inhibitory to microbial treatment in wastewater treatment plants. For this reason, the valorization of the HTL-AP is significant for the circular economy of HTL. This review synthesizes published findings on different types of treatment of the HTL-AP for the recovery of valuable nutrients and the removal of toxic compounds. This work outlines the trade-offs of the treatments to serve as a guide for future research to address these weaknesses and improve the valorization of the HTL-AP. Furthermore, this work uniquely focuses on HTL-AP treatment for recovering plant-available nitrogen, targeting its potential use as a fertilizer. The literature highlights the importance of increasing nitrogen bioavailability in HTL-AP through two-step treatments and by selecting HTL-AP derived from protein-rich feedstocks, which offer higher initial nitrogen content. According to the current state of research, further work is needed to optimize chemical and biological treatments for nutrient recovery from HTL-AP, particularly regarding treatment scale and duration. Additionally, economic analyses across different treatment types are currently lacking, but are essential to evaluate their feasibility and practicality.
Full article
(This article belongs to the Special Issue Emerging Technologies for Nutrient Recovery and Wastewater Treatment)
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Operation of a Zero-Discharge Evapotranspiration Tank for Blackwater Disposal in a Rural Quilombola Household, Brazil
by
Adivânia Cardoso da Silva, Adriana Duneya Diaz Carrillo and Paulo Sérgio Scalize
Water 2025, 17(14), 2098; https://doi.org/10.3390/w17142098 (registering DOI) - 14 Jul 2025
Abstract
Decentralized sanitation in rural areas urgently requires accessible and nature-based solutions to achieve Sustainable Development Goal 6 (clean water and sanitation for all). However, monitoring studies of such ecotechnologies in disperse communities remain limited. This study evaluated the performance of an evapotranspiration tank
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Decentralized sanitation in rural areas urgently requires accessible and nature-based solutions to achieve Sustainable Development Goal 6 (clean water and sanitation for all). However, monitoring studies of such ecotechnologies in disperse communities remain limited. This study evaluated the performance of an evapotranspiration tank (TEvap), designed with community participation, for the treatment of domestic sewage in a rural Quilombola household in the Brazilian Cerrado. The system (total area of 8.1 m2, with about 1.0 m2 per inhabitant) was monitored for 218 days, covering the rainy season and the plants’ establishment phase. After 51 days, the TEvap reached operational equilibrium, maintaining a zero-discharge regime, and after 218 days, 92.3% of the total system inlet volumes (i.e., 37.47 in 40.58 m3) were removed through evapotranspiration and uptake by cultivated plants (Musa spp.). Statistical analyses revealed correlations that were moderate to strong, and weak between the blackwater level and relative humidity (Pearson correlation coefficient, r = 0.75), temperature (r = −0.66), and per capita blackwater contribution (r = 0.28), highlighting the influence of climatic conditions on system efficiency. These results confirm the TEvap as a promising, low-maintenance, and climate-resilient technology for decentralized domestic sewage treatment in vulnerable rural communities, with the potential to support sanitation policy goals and promote public health.
Full article
(This article belongs to the Special Issue Research on Water Supply Systems and on the Treatment and Recovery of Wastewater and Stormwater)
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Open AccessArticle
An Advanced Ensemble Machine Learning Framework for Estimating Long-Term Average Discharge at Hydrological Stations Using Global Metadata
by
Alexandr Neftissov, Andrii Biloshchytskyi, Ilyas Kazambayev, Serhii Dolhopolov and Tetyana Honcharenko
Water 2025, 17(14), 2097; https://doi.org/10.3390/w17142097 (registering DOI) - 14 Jul 2025
Abstract
Accurate estimation of long-term average (LTA) discharge is fundamental for water resource assessment, infrastructure planning, and hydrological modeling, yet it remains a significant challenge, particularly in data-scarce or ungauged basins. This study introduces an advanced machine learning framework to estimate long-term average discharge
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Accurate estimation of long-term average (LTA) discharge is fundamental for water resource assessment, infrastructure planning, and hydrological modeling, yet it remains a significant challenge, particularly in data-scarce or ungauged basins. This study introduces an advanced machine learning framework to estimate long-term average discharge using globally available hydrological station metadata from the Global Runoff Data Centre (GRDC). The methodology involved comprehensive data preprocessing, extensive feature engineering, log-transformation of the target variable, and the development of multiple predictive models, including a custom deep neural network with specialized pathways and gradient boosting machines (XGBoost, LightGBM, CatBoost). Hyperparameters were optimized using Bayesian techniques, and a weighted Meta Ensemble model, which combines predictions from the best individual models, was implemented. Performance was rigorously evaluated using R2, RMSE, and MAE on an independent test set. The Meta Ensemble model demonstrated superior performance, achieving a Coefficient of Determination (R2) of 0.954 on the test data, significantly surpassing baseline and individual advanced models. Model interpretability analysis using SHAP (Shapley Additive explanations) confirmed that catchment area and geographical attributes are the most dominant predictors. The resulting model provides a robust, accurate, and scalable data-driven solution for estimating long-term average discharge, enhancing water resource assessment capabilities and offering a powerful tool for large-scale hydrological analysis.
Full article
(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)
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Multi-Layer and Profile Soil Moisture Estimation and Uncertainty Evaluation Based on Multi-Frequency (Ka-, X-, C-, S-, and L-Band) and Quad-Polarization Airborne SAR Data from Synchronous Observation Experiment in Liao River Basin, China
by
Jiaxin Qian, Jie Yang, Weidong Sun, Lingli Zhao, Lei Shi, Hongtao Shi, Chaoya Dang and Qi Dou
Water 2025, 17(14), 2096; https://doi.org/10.3390/w17142096 (registering DOI) - 14 Jul 2025
Abstract
Validating the potential of multi-frequency synthetic aperture radar (SAR) data for multi-layer and profile soil moisture (SM) estimation modeling, we conducted an airborne multi-frequency SAR joint observation experiment (AMFSEX) over the Liao River Basin in China. The experiment simultaneously acquired airborne high spatial
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Validating the potential of multi-frequency synthetic aperture radar (SAR) data for multi-layer and profile soil moisture (SM) estimation modeling, we conducted an airborne multi-frequency SAR joint observation experiment (AMFSEX) over the Liao River Basin in China. The experiment simultaneously acquired airborne high spatial resolution quad-polarization (quad-pol) SAR data at five frequencies, including the Ka-, X-, C-, S-, and L-band. A preliminary “vegetation–soil” parameter estimation model based on the multi-frequency SAR data was established. Theoretical penetration depths of the multi-frequency SAR data were analyzed using the Dobson empirical model and the Hallikainen modified model. On this basis, a water cloud model (WCM) constrained by multi-polarization weighted and penetration depth weighted parameters was used to analyze the estimation accuracy of the multi-layer and profile SM (0–50 cm depth) under different vegetation types (grassland, farmland, and woodland). Overall, the estimation error (root mean square error, RMSE) of the surface SM (0–5 cm depth) ranged from 0.058 cm3/cm3 to 0.079 cm3/cm3, and increased with radar frequency. For multi-layer and profile SM (3 cm, 5 cm, 10 cm, 20 cm, 30 cm, 40 cm, 50 cm depth), the RMSE ranged from 0.040 cm3/cm3 to 0.069 cm3/cm3. Finally, a multi-input multi-output regression model (Gaussian process regression) was used to simultaneously estimate the multi-layer and profile SM. For surface SM, the overall RMSE was approximately 0.040 cm3/cm3. For multi-layer and profile SM, the overall RMSE ranged from 0.031 cm3/cm3 to 0.064 cm3/cm3. The estimation accuracy achieved by coupling the multi-source data (multi-frequency SAR data, multispectral data, and soil parameters) was superior to that obtained using the SAR data alone. The optimal SM penetration depth varied across different vegetation cover types, generally falling within the range of 10–30 cm, which holds true for both the scattering model and the regression model. This study provides methodological guidance for the development of multi-layer and profile SM estimation models based on the multi-frequency SAR data.
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(This article belongs to the Special Issue Applications of Multi-Source Remote Sensing Technologies in Soil Moisture Monitoring)
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Open AccessArticle
Surface Water Mass Transformation in North Atlantic Based on NCEP CSFR Reanalysis
by
Vladimir Kukushkin and Sergey Gulev
Water 2025, 17(14), 2095; https://doi.org/10.3390/w17142095 (registering DOI) - 14 Jul 2025
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This paper focuses on the analysis of variability of density fluxes and water mass transformation in the North Atlantic, the quantities reflecting the intensity of intermediate and deep water formation. The authors assess the influence of atmospheric processes on the intensity of formation
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This paper focuses on the analysis of variability of density fluxes and water mass transformation in the North Atlantic, the quantities reflecting the intensity of intermediate and deep water formation. The authors assess the influence of atmospheric processes on the intensity of formation of subpolar modal waters, subtropical modal waters and Labrador Sea waters using the density fluxes and water mass transformation. This analysis is carried out on a seasonal and climatic time scale. The main result of the study is the seasonal and climatic dynamics of water mass transformation in the Labrador Sea, subtropical and subpolar modal waters based on CFSR reanalysis data. The results obtained help to understand the main factors influencing vertical circulation in the region, which can be used in further model experiments.
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Open AccessArticle
The Spatial Distribution and Risk Assessment of Nutrient Elements and Heavy Metal Pollution in Sediments: A Case Study of a Typical Urban Lake in the Middle and Lower Reaches of the Yangtze River
by
Ji Li, Menglu Zhu, Yong Zhang, Jun Zhang, Jiang Du, Yifan Wu, Zhaocai Zeng, Quan Sun, Hongxuan Li, Lei Zhang, Yajie Zheng and Bolin Li
Water 2025, 17(14), 2094; https://doi.org/10.3390/w17142094 (registering DOI) - 14 Jul 2025
Abstract
The ecological environment of urban lakes affected by human activities is deteriorating rapidly. As a source and sink of pollutants in the lake environment, sediments have become the focus of environmental assessments. At present, most of the studies only conduct pollution assessments on
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The ecological environment of urban lakes affected by human activities is deteriorating rapidly. As a source and sink of pollutants in the lake environment, sediments have become the focus of environmental assessments. At present, most of the studies only conduct pollution assessments on surface sediments. In this study, taking the typical urban lakes GanTang Lake and NanMen Lake (G&N Lake) as the background, not only is the planar spatial distribution of their nutrient elements, seven kinds of heavy metals, and As analyzed in detail, but risk assessments are also carried out on the pollution conditions at different depths. The causes of pollution at different depths are analyzed. It is found that in this lake, with the increase in depth, the pollution situation decreases slightly, but the pollution of nutrient elements is severe. There is severe pollution of nutrient elements at a depth of up to 1 m in the whole lake sediment. In the sediments with a depth of up to 1 m, more than 90% of the areas in the whole lake are at or above the moderate pollution level of Hg, and more than 70% of the areas are under slight pollution of Cd, resulting in the ecological risk level of the whole lake being at or above the high-risk level. Urban lake sediment management is inherently complex, driven by multifaceted factors where intensive anthropogenic activities constitute the primary pollution source. This research provides insights to guide restoration strategies and sustainable development policies for lacustrine ecosystems.
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(This article belongs to the Section Water Quality and Contamination)
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Open AccessArticle
Study on the Evolution and Predictive for Coordinated Development of Regional Water Resources, Economic Society, and Ecological Environment
by
Subing Lü, Cheng Lü, Tingyu Wang, Weiwei Shao and Fuqiang Wang
Water 2025, 17(14), 2093; https://doi.org/10.3390/w17142093 - 14 Jul 2025
Abstract
Water resources are strategic resources that support regional economic social development and maintain the health and stability of ecosystems. This study revealed the evolution of the coordinated development of China’s water resources–economic society–ecological environment system based on the coordination degree mode. The research
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Water resources are strategic resources that support regional economic social development and maintain the health and stability of ecosystems. This study revealed the evolution of the coordinated development of China’s water resources–economic society–ecological environment system based on the coordination degree mode. The research was conducted by integrating machine learning with traditional mathematical methods; by setting up the status quo development scenario, water resources priority scenario, economic society priority scenario, ecological environment priority scenario and balanced development scenario; and by using the Holt exponential smoothing–feedforward neural network prediction model, the coordinated development trends under different scenarios were predicted. The results showed that, analyzed from the perspective of the coordinated evolution type of the dual systems, the dominant development system during the study period gradually transformed from water resources–economic society to water resources–ecological environment. For the coordinated development of the complex system, the coordination degree showed “stepped leap—resilient fluctuation (from 0.7242 to 0.8238)”, and “better in the southeast than in the northwest, with significant advantages in the coast”. The most significant increase in the coordination degrees were observed in the balanced development scenario and economic society priority scenarios, where it increased by an average of around 5%, confirming the effective contribution of stable economic and social development to the level of coordination. This study provides theoretical support and practical guidance for regional water resources management.
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(This article belongs to the Section Water Resources Management, Policy and Governance)
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Open AccessArticle
Wholesale Destruction Inside a Marine Protected Area: Anchoring Impacts on Sciaphilic Communities and Coralligenous Concretions in the Eastern Mediterranean
by
Carlos Jimenez, Magdalene Papatheodoulou, Vasilis Resaikos and Antonis Petrou
Water 2025, 17(14), 2092; https://doi.org/10.3390/w17142092 - 14 Jul 2025
Abstract
The marine habitats of the world’s oceans are being driven beyond their resilience. The ongoing biodiversity crisis is happening fast, within the lifespan of researchers trying to produce the information necessary for the conservation of habitats and marine ecosystems. Here, we report on
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The marine habitats of the world’s oceans are being driven beyond their resilience. The ongoing biodiversity crisis is happening fast, within the lifespan of researchers trying to produce the information necessary for the conservation of habitats and marine ecosystems. Here, we report on the destruction of sciaphilic sessile communities and coralligenous concretions produced by the anchoring of a high-tonnage vessel inside a Marine Protected Area in Cyprus. The damage from the anchors and the chains consisted of the dislodgement of large boulders that were dragged or rolled over the seafloor, increasing the breakage and further dislodgement of more boulders; many were left upside-down. The biological communities that thrived in the dark environments below the boulders were directly exposed to high irradiance levels and went through a slow mortality and decaying process, most probably due to a combination of several deterioration agents, such as exposure to direct sunlight, predation, mucilage aggregates, and cyanobacterial blooms. The enforcement of regulatory measures for anchoring and transit in the MPA is necessary to prevent similar destruction. Given the extent of the irreversible damage to these sciaphilic communities, our study is, unfortunately, another environmental post-mortem contribution.
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(This article belongs to the Special Issue Effect of Human Activities on Marine Ecosystems)
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Open AccessArticle
Water Quality and Biological Response in the Deschutes River, Oregon, Following the Installation of a Selective Water Withdrawal
by
Joseph M. Eilers, Tim Nightengale and Kellie B. Vache
Water 2025, 17(14), 2091; https://doi.org/10.3390/w17142091 - 13 Jul 2025
Abstract
Selective water withdrawals (SWWs) are frequently used to minimize the downstream effects of dams by blending water from different depths to achieve a desired temperature regime in the river. In 2010, an SWW was installed on the outlet structure of the primary hydropower
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Selective water withdrawals (SWWs) are frequently used to minimize the downstream effects of dams by blending water from different depths to achieve a desired temperature regime in the river. In 2010, an SWW was installed on the outlet structure of the primary hydropower reservoir on the Deschutes River (Oregon, USA) to increase spring temperatures by releasing a combination of surface water and bottom waters from a dam that formerly only had a hypolimnetic outlet. The objective of increasing spring river temperatures was to recreate pre-dam river temperatures and optimize conditions for the spawning and rearing of anadromous fish. The operation of the SWW achieved the target temperature regime, but the release of surface water from a hypereutrophic impoundment resulted in a number of unintended consequences. These changes included significant increases in river pH and dissolved oxygen saturation. Inorganic nitrogen releases decreased in spring but increased in summer. The release of surface water from the reservoir increased levels of plankton in the river resulting in changes to the macroinvertebrates such as increases in filter feeders and a greater percentage of taxa tolerant to reduced water quality. No significant increase in anadromous fish was observed. The presence of large irrigation diversions upstream of the reservoir was not accounted for in the temperature analysis that led to the construction of the SWW. This complicating factor would have reduced flow in the river leading to increased river temperatures at the hydropower site during the measurement period used to develop representations of historical temperature. The analysis supports the use of numerical models to assist in forecast changes associated with SWWs, but the results from this project illustrate the need for greater consideration of complex responses of aquatic communities caused by structural modifications to dams.
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(This article belongs to the Section Hydrology)
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