Water

20 pages, 20196 KB

Open AccessArticle

Tile-Based CNN with Combined Optimizer for Urban Flood Prediction Under Various Deterministic Rainfall Scenarios

by Yong Min Ryu and Eui Hoon Lee

Water 2026, 18(13), 1655; https://doi.org/10.3390/w18131655 - 7 Jul 2026

Viewed by 408

Urban flooding poses increasing risks globally due to climate change and urbanization, yet physics-based hydraulic models suffer from high computational costs that limit their application to flood analysis under various rainfall conditions. This study proposes an optimizer-improved tile-based convolutional neural network framework for [...] Read more.

Urban flooding poses increasing risks globally due to climate change and urbanization, yet physics-based hydraulic models suffer from high computational costs that limit their application to flood analysis under various rainfall conditions. This study proposes an optimizer-improved tile-based convolutional neural network framework for efficient prediction of two-dimensional peak flooding maps under various rainfall scenarios. The framework integrates tile-based spatial learning for efficient localized flood-response learning and a combined Adam-VCA optimizer to mitigate local optimum convergence. The framework was applied to the Dorim basin in Seoul, South Korea, using 22 rainfall scenarios ranging from 10 to 800 mm, of which 20 scenarios were used for model training and 2 scenarios (500 mm and 700 mm) were reserved as independent test scenarios for performance evaluation. Prediction accuracy was evaluated using F1-score and critical success index (CSI), and Verification period based accuracy (VAC) and Peak flooding based accuracy (PAC) as study-specific depth-incorporated metrics. The proposed optimizer-improved CNN substantially outperformed the conventional CNN, achieving F1-score of 83.84%, CSI of 72.24%, VAC of 90.39%, and PAC of 70.93%, compared to 51.03%, 34.25%, 63.39%, and 47.29%, respectively. The results confirm the framework’s potential for efficient flooding assessment and urban flood risk management under diverse rainfall conditions. Full article

(This article belongs to the Special Issue Urban Drainage Systems and Stormwater Management, 2nd Edition)

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27 pages, 5638 KB

Open AccessArticle

Data-Driven Monitoring for Thermal Water Quality Control: Anomaly Detection from Predictive Forecasting in the AQUAPRED Project

by Abel Pampín Rodríguez, Elena Hernández Pereira, María Lourdes Mourelle and José Luis Legido Soto

Water 2026, 18(13), 1654; https://doi.org/10.3390/w18131654 - 7 Jul 2026

Viewed by 337

Abstract

To control the quality of mineral-medicinal waters and ensure their therapeutic benefits, spas often rely on periodic discrete sampling to analyze the physico-chemical properties of their pools. The AQUAPRED project aims to digitize this process by deploying IoT systems within the spa facilities, [...] Read more.

To control the quality of mineral-medicinal waters and ensure their therapeutic benefits, spas often rely on periodic discrete sampling to analyze the physico-chemical properties of their pools. The AQUAPRED project aims to digitize this process by deploying IoT systems within the spa facilities, enabling real-time data acquisition via calibrated multi-parameter probes. Using data collected by these pilot systems, we develop and validate a predictive machine learning model capable of forecasting the short-term evolution of the thermal water properties. Historical data from each facility allow the model to learn the specifics dynamics of each spa. As a practical application, we propose an anomaly detection module based on residual analysis from predicted and observed values. Significant discrepancies signal events of interest and emergent trends, such as anomalous readings, contamination or sensor drift. The methodology is evaluated using real data from six spas associated with the AQUAPRED project. The results demonstrate the model’s effectiveness and support its feasibility for deployment in other thermal establishments. Full article

(This article belongs to the Special Issue Groundwater for Health and Well-Being)

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26 pages, 3604 KB

Open AccessReview

Review of the Effectiveness of Current Water Treatment Technologies for PFAS Removal

by Duncan Gill and Ali El Hanandeh

Water 2026, 18(13), 1653; https://doi.org/10.3390/w18131653 - 7 Jul 2026

Viewed by 882

Abstract

PFAS form a class of synthetic chemicals that has become an area of increasing concern because of its impact on the environment and the threat it poses to human health. The structure of PFAS makes them highly resistant to degradation. As a result, [...] Read more.

PFAS form a class of synthetic chemicals that has become an area of increasing concern because of its impact on the environment and the threat it poses to human health. The structure of PFAS makes them highly resistant to degradation. As a result, they are highly effective at bioaccumulation. Certain water treatment technologies have been proven to remove PFAS from contaminated water sources. This study reviews the most promising treatment technologies used for the treatment of PFAS-contaminated waters. Well-established treatment technologies, such as granular activated carbon, ion exchange resin, reverse osmosis, and nanofiltration, were quantitatively compared. The removal efficiency was assessed by collecting the data of individual PFAS species from the literature and grouping them into five groups: PFAS (all species), PFSA, PFCA, long chain, and short chain. The results identified that, for all PFAS groups, the most effective treatment technologies were in the following order: reverse osmosis, nanofiltration, ion exchange resin, and granular activated carbon. The performance of reverse osmosis and nanofiltration did not appear to significantly differ between the different PFAS groups, as opposed to ion exchange resin and granular activated carbon, where there was a greater degree of variation in performance between different PFAS groups. Overall, it was identified that membrane technologies outperformed adsorbent technologies. However, the cost associated with membrane technologies may limit its economic viability when compared with adsorbent technologies, which are typically a more viable option except under specific circumstances. For example, contaminated water with high concentrations of other contaminants that need to be treated simultaneously. Lack of standardised experimental and operational conditions limited the available data. While this work provides guidance on which treatment is more likely to be appropriate based on the concentration and composition of different species of PFAS, more data are needed to conduct a more accurate statistical analysis and enable accurate modelling of treatment performance. Full article

(This article belongs to the Special Issue Electrochemical and Bioelectrochemical Technologies for Sustainable Water Treatment)

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5 pages, 146 KB

Open AccessEditorial

Application of Artificial Intelligence in Hydraulic Engineering, 2nd Edition

by Chunhui Ma, Jie Yang and Lin Cheng

Water 2026, 18(13), 1652; https://doi.org/10.3390/w18131652 - 7 Jul 2026

Viewed by 383

Abstract

Hydraulic engineering plays an indispensable role in flood control, water supply, irrigation, hydropower generation, ecological restoration, and water environment protection [...] Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Hydraulic Engineering, 2nd Edition)

21 pages, 6493 KB

Open AccessArticle

Dynamics of Dissolved Carbon Dioxide, Methane, and Nitrous Oxide in Karst Groundwater Settings Under Agricultural Land Use

by Stacy W. Antle, Jason S. Polk, Edwin L. Ritchey, Karamat R. Sistani and John H. Loughrin

Water 2026, 18(13), 1651; https://doi.org/10.3390/w18131651 - 7 Jul 2026

Viewed by 409

Abstract

The dynamics of methane (CH₄), nitrous oxide (N₂O) and carbon dioxide (CO₂) in groundwater have rarely been investigated. As dissolved gases they may be transported to distant sites and, hence, to the atmosphere. Crumps Cave (CC) is [...] Read more.

The dynamics of methane (CH₄), nitrous oxide (N₂O) and carbon dioxide (CO₂) in groundwater have rarely been investigated. As dissolved gases they may be transported to distant sites and, hence, to the atmosphere. Crumps Cave (CC) is located on a perched aquifer in south-central Kentucky. Water was sampled at a waterfall within the cave located 15 m below the surface, at two adjacent surface wells 15 m and 50 m deep, providing samples from the epikarst and regional aquifer, respectively. Dissolved gases and geochemistry parameters were analyzed for seasonal changes across three years of weekly monitoring (2015–2017) using Kruskal–Wallis H tests and Bonferroni-corrected pairwise comparisons. Dissolved CO₂ concentrations are mainly controlled by percolation through the epikarst, influenced by soil respiration, and vary with rainfall and seasonal temperature fluctuations. CH₄ showed a site-dependent pattern: concentrations were significantly elevated in warm seasons at the shallow and deep wells, where anaerobic conditions and agriculturally derived organic matter promote methanogenesis; no seasonal variation was detected at the cave site, where oxic conditions limit CH₄ year-round. N₂O was significantly elevated in cold seasons at all three sites, driven by cold-season denitrification of agriculturally derived nitrates. N₂O did not differ between sites, indicating seasonal temperature-driven denitrification as the primary control rather than site hydrology, with cold-season denitrification of agriculturally derived nitrates from fertilizer application. Indirect gas emissions are characteristic of karst systems and may be transported or stored in aquifers through complex interactions of groundwater recharge, microbial activity, and seasonal land-use variability. Full article

(This article belongs to the Special Issue Advancing Applications in Hydrogeochemical Processes in Groundwater Systems)

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24 pages, 3329 KB

Open AccessArticle

Water Quality Trends and Remote Sensing Model Development in Portuguese Reservoirs Using Sentinel-2 Imagery

by Geissielen A. Lauriuchi, Catarina Guimarães, Giorgio Pace, Gabriel R. Caballero, Xavier Sòria-Perpinyà, Marcelo Pompêo, Jesús Delegido and Sara C. Antunes

Water 2026, 18(13), 1650; https://doi.org/10.3390/w18131650 - 7 Jul 2026

Viewed by 422

Abstract

Iberian reservoirs are highly vulnerable to droughts, warming temperatures, and agricultural runoff, which accelerate eutrophication. Monitoring these dynamics is crucial for sustainable management. This study investigated long-term trends in chlorophyll-a (Chl-a) and water transparency Secchi depth and developed empirical models for the Alto [...] Read more.

Iberian reservoirs are highly vulnerable to droughts, warming temperatures, and agricultural runoff, which accelerate eutrophication. Monitoring these dynamics is crucial for sustainable management. This study investigated long-term trends in chlorophyll-a (Chl-a) and water transparency Secchi depth and developed empirical models for the Alto Rabagão (Rb) and Aguieira (Ag) reservoirs in Portugal. We used Sentinel-2 Level-2A reflectance data coupled with 153 in situ observations (2014–2024) for model calibration (n = 95) and validation (n = 58). Temporal trends were assessed using linear regression and Mann–Kendall analyses. Empirical models based on spectral indices (TBDO1, TBDO, MCI, NDWI) were evaluated using walk-forward time-series cross-validation. Results revealed a significant Chl-a increase (0.38 µg L⁻¹ year⁻¹; p = 0.016) and a simultaneous decline in transparency (p < 0.001) in Rb, indicating progressive eutrophication. In contrast, no significant trends were detected in Ag. Reservoir-specific models achieved moderate-to-high predictive performance, particularly for Chl-a (R² up to 0.75; cross-validated R² = 0.67–0.68, RMSE = 1.1 µg L⁻¹, MAE = 0.82 µg L⁻¹). Models using combined datasets showed lower accuracy, highlighting the importance of site-specific calibration. Wilcoxon signed-rank tests confirmed the absence of systematic bias between observed and predicted values. Ultimately, Sentinel-2 imagery combined with time-series cross-validation provides a reliable and cost-effective framework for the long-term monitoring of inland water quality. Full article

(This article belongs to the Section Water Quality and Contamination)

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43 pages, 2643 KB

Open AccessArticle

Toward a General Analytical Formulation for the Hydrodynamic Behavior of Tesla Valves

by Mauricio De la Cruz-Ávila, Mario Ivan Estrada-Delgado, Francisco Javier Castillo Guerrero and Rosanna Bonasia

Water 2026, 18(13), 1649; https://doi.org/10.3390/w18131649 - 7 Jul 2026

Viewed by 462

Abstract

Tesla valves are passive hydraulic devices capable of producing directional flow resistance without moving components, making them attractive for applications in microfluidics, thermal systems, and high-reliability hydraulic circuits. Despite extensive experimental and numerical studies, an analytical formulation capable of describing the hydrodynamic behavior [...] Read more.

Tesla valves are passive hydraulic devices capable of producing directional flow resistance without moving components, making them attractive for applications in microfluidics, thermal systems, and high-reliability hydraulic circuits. Despite extensive experimental and numerical studies, an analytical formulation capable of describing the hydrodynamic behavior of Tesla valves under varying operating and geometric conditions remains limited. In this work, a comprehensive analytical model is developed to describe the pressure losses, flow redistribution, and diodicity behavior of Tesla valves through a physics-based formulation derived from conservation laws, dimensional analysis, and inertial scaling principles. The proposed model incorporates the influence of Reynolds number, flow partition, geometric ratios, branch inclination angle, and number of diode stages within a unified nonlinear framework. A closed structural equation is obtained that relates hydraulic losses and directional asymmetry to the internal geometry of the valve. The formulation reveals the existence of geometric and energetic constraints governing rectification efficiency, including bounds associated with stage number, channel scaling, and angular momentum exchange. The results show that Tesla valve performance emerges from a delicate balance between inertial amplification and dissipative mechanisms, providing an analytical framework for the design and optimization of Tesla-type hydraulic systems across multiple scales. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

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20 pages, 3750 KB

Open AccessArticle

Application of Citrus paradisi Extract as a Natural Alternative for the Disinfection of Contaminated Surface Waters

by Luis Cabanillas-Chirinos, Moisés Gallozzo-Cárdenas, Magaly De La Cruz-Noriega, Víctor Sánchez-Araujo and Pedro Palomino-Pastrana

Water 2026, 18(13), 1648; https://doi.org/10.3390/w18131648 - 7 Jul 2026

Viewed by 394

Abstract

Microbiological contamination of surface water represents a critical public health concern, while conventional disinfectants face limitations such as the generation of toxic by-products and the emergence of microbial resistance. In this study, the application of an ethanolic peel extract of Citrus paradisi (grapefruit), [...] Read more.

Microbiological contamination of surface water represents a critical public health concern, while conventional disinfectants face limitations such as the generation of toxic by-products and the emergence of microbial resistance. In this study, the application of an ethanolic peel extract of Citrus paradisi (grapefruit), obtained by sonication at 40 kHz for 90 min at 55 °C using a 1:4 (w/v) solvent-to-solid ratio, was evaluated as a natural alternative for bacterial reduction in contaminated waters. The Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) of the extract were first determined against Staphylococcus aureus and Escherichia coli. The extract was then applied to samples of slightly contaminated surface water with bacterial loads between 10³–10⁴ CFU/mL and turbidity of 150 NTU, as well as to highly contaminated surface water with bacterial loads ≥10⁵ CFU/mL and turbidity of 250 NTU. Bacterial removal was assessed at 6, 12, and 24 h. FTIR and UV-Vis characterization of the extract confirmed the presence of flavonoids (naringin), terpenes (limonene), and phenolic compounds. Results showed MIC/MBC values of 2.5/5.0 mg/mL for S. aureus and 5.0/10.0 mg/mL for E. coli. In slightly contaminated water, the extract at 5.0 mg/mL achieved complete (100%) removal of both microorganisms after 12 h, whereas in highly contaminated water, removals ranged from 80–90% for Staphylococcus spp. and E. coli. Statistical analysis (ANOVA, Bonferroni) demonstrated significant differences (p < 0.05) between the extract and ethanol. These findings indicate that Citrus paradisi extract constitutes an effective, sustainable, and low-cost natural alternative for bacterial reduction in surface waters, contributing to the valorization of agro-industrial residues and to the achievement of Sustainable Development Goal (SDG) 6. Full article

(This article belongs to the Special Issue The Oxidation and Disinfection Processes in Water Treatment)

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16 pages, 21029 KB

Open AccessArticle

Effects of Iron Shavings Addition on the Performance of AOA-SBR Biochemical System

by Hanjiang Wu, Lei Cai, Zengrui Pan, Jianan Wei, Jun Li and Anqi Yan

Water 2026, 18(13), 1647; https://doi.org/10.3390/w18131647 - 7 Jul 2026

Viewed by 429

Abstract

To explore a new approach to reducing the use of external carbon sources and phosphorus removal chemicals in conventional wastewater treatment, this study developed an anaerobic–oxic–anoxic sequencing batch reactor (AOA-SBR) system (Rf) with iron shavings addition (180 g, 60 g/L), using a blank [...] Read more.

To explore a new approach to reducing the use of external carbon sources and phosphorus removal chemicals in conventional wastewater treatment, this study developed an anaerobic–oxic–anoxic sequencing batch reactor (AOA-SBR) system (Rf) with iron shavings addition (180 g, 60 g/L), using a blank reactor (R0) as the control. Synthetic wastewater with a C/N ratio of 7.5 was used as the influent. The operating cycle of the AOA-SBR reactor consisted of a 120 min anaerobic phase, a 120 min aerobic phase, and a 60 min anoxic phase, with a hydraulic retention time (HRT) of 12 h. Results showed that the SVI₃₀ of Rf remained at approximately 35 mL/g. The average removal efficiencies of TN and TP in Rf reached 70% and 96%, respectively, which were higher than those of the control. The addition of waste iron shavings improved sludge settleability and nitrogen and phosphorus removal performance of the biochemical system. Fe-C microelectrolysis significantly enriched Candidatus_Competibacter and Candidatus_Nitrocosmicus while inhibiting nitrite-oxidizing bacteria (NOB). This triggered persistent low-level nitrite accumulation within the system, diversified nitrogen-removal pathways, and ultimately improved the total nitrogen-removal efficiency. The extended anaerobic period in the anaerobic–oxic–anoxic (AOA) mode enriched phosphate-accumulating organisms, achieving synergistic chemical and biological phosphorus removal. This study provides a novel strategy for advanced wastewater treatment without external carbon sources or phosphorus additives. Full article

(This article belongs to the Special Issue Advanced Chemical and Biological Technologies for Water Purification and Contaminant Degradation)

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18 pages, 27813 KB

Open AccessArticle

Synergism or Antagonism in Toxicity Induced by Co-Exposure to Polyamide Microplastics and Cadmium Is Dose-Dependent in the Submerged Macrophyte Vallisneria natans

by Yuqi Feng, Xuerong Wang, Ruiming Han, Pengcheng Zhou, Jiakang Mu, Qinghui Jiang, Shaoting Chen, Jiasheng Ma, Lilin Zheng, Wei Wei and Mingxi Zhou

Water 2026, 18(13), 1646; https://doi.org/10.3390/w18131646 - 6 Jul 2026

Viewed by 382

Abstract

The contamination of microplastics (MPs) and heavy metals (HMs) in water has caused widespread concern, while their effects on submerged macrophytes have rarely been reported. Experiments were carried out to investigate the toxic effects of polyamide microplastics (PAMPs; 0.1%, 0.3%, and 1.0% w [...] Read more.

The contamination of microplastics (MPs) and heavy metals (HMs) in water has caused widespread concern, while their effects on submerged macrophytes have rarely been reported. Experiments were carried out to investigate the toxic effects of polyamide microplastics (PAMPs; 0.1%, 0.3%, and 1.0% w/w) and cadmium (Cd; 0.3 and 1.0 mg/L), alone or in combination, on the submerged macrophyte Vallisneria natans (V. natans). The results showed that PAMPs significantly reduced Cd accumulation in leaves (decrease of 2.38%~26.12%) but elevated Cd accumulation in roots. Both Cd exposure and high PAMP exposure alone inhibited plant growth. The combined stress showed concentration-dependent effects: the low Cd concentration (0.3 mg/L) and PAMPs synergistically exacerbated toxicity (synergism, MDR > 1.3), as PAMPs disrupted the sediment structure and enhanced the bioavailability of Cd, whereas when V. natans was co-exposed to the high Cd concentration (1.0 mg/L) and PAMPs, the PAMPs blunted the toxicity of Cd by efficiently adsorbing it (antagonism, MDR < 0.7). Both individual and combined exposures decreased chlorophyll a and chlorophyll b synthesis and increased superoxide dismutase (SOD) and peroxidase (POD) activities as well as malondialdehyde (MDA) content in plant tissues. However, exposure to low and medium concentrations of MPs (0.1% and 0.3% w/w) alone had positive effects on plant growth and photosynthesis systems, while combined exposures exacerbated the damaging effects of PAMPs on the antioxidant defense system in V. natans. These results allow for a better understanding of the synergistic effect of co-contamination of microplastics and heavy metals in freshwater ecosystems, and highlight the necessity of ecological risk assessment during phytoremediation using submerged macrophytes. Full article

(This article belongs to the Special Issue Water Pollution Control and Ecological Restoration: 2nd Edition)

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18 pages, 2329 KB

Open AccessArticle

Long-Term Performance of Hybrid Green-Gray Infrastructure for CSO Reduction and Water Quality Improvement in a Dense Urban Watershed, Zhenjiang, China

by Zhentao Xie, Nian She, Kang Zhou, Yezhao Cai, Weimin Zhou and Dong Luo

Water 2026, 18(13), 1645; https://doi.org/10.3390/w18131645 - 6 Jul 2026

Viewed by 560

Abstract

Urban combined sewer systems are increasingly challenged by climate-intensified rainfall, combined sewer overflows, and receiving-water degradation. This study presents a retrospective evaluation of a hybrid green-gray retrofit program implemented in the Zhenjiang Sponge City pilot watershed, China, where green stormwater infrastructure, drainage network [...] Read more.

Urban combined sewer systems are increasingly challenged by climate-intensified rainfall, combined sewer overflows, and receiving-water degradation. This study presents a retrospective evaluation of a hybrid green-gray retrofit program implemented in the Zhenjiang Sponge City pilot watershed, China, where green stormwater infrastructure, drainage network upgrades, and a centralized deep tunnel system were integrated within a densely developed watershed constrained by limited space, low native-soil permeability, shallow groundwater, and aging infrastructure. System performance was evaluated using long-term operational observations, representative hydraulic and water-quality monitoring, municipal operational records, and supporting engineering analyses at both facility and watershed scales. The results demonstrated sustained hydraulic functionality after 7–10 years of operation, with approximately 90% of the monitored bioretention systems maintaining effective infiltration rates greater than 80 mm h⁻¹. Event-based monitoring indicated substantial reductions in runoff volume and pollutant loads, including TSS, COD, NH₃–N, and TP. Following implementation, annual combined sewer overflow occurrence at major outfalls decreased from 318 to 24 events, representing a 92.5% reduction. Supporting engineering analyses indicated that green stormwater infrastructure retrofits alone reduced overflow frequency by approximately 41.8% and overflow volume by approximately 61.1%, while integration with deep tunnels increased reductions to approximately 58.8% and 85.3%, respectively. Official receiving-water monitoring records further indicated that Class III or better water-quality conditions were maintained during approximately 74.7% of the monitored days between 2021 and 2026. These findings provide long-term watershed-scale evidence that hybrid green-gray retrofit strategies can integrate green stormwater infrastructure with centralized overflow regulation to achieve sustained overflow reduction and receiving-water improvement in highly constrained urban watersheds. Full article

(This article belongs to the Special Issue Climate Change Adaptation in Water Resource Management)

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36 pages, 7020 KB

Open AccessArticle

MODIS–Sentinel-2 Data Fusion for Cloud-Robust Crop Evapotranspiration Estimation in a Nitrate-Sensitive Irrigated Maize System: Evaluating Gap-Filling Strategies for Evidence-Based Irrigation Scheduling

by Gift Siphiwe Nxumalo, Fehér Zsolt Zoltán, János Tamás and Attila Nagy

Water 2026, 18(13), 1644; https://doi.org/10.3390/w18131644 - 6 Jul 2026

Viewed by 441

Abstract

Reliable quantification of crop evapotranspiration (ET_c) at field resolution is a prerequisite for evidence-based irrigation scheduling in agricultural systems subject to nitrate leaching constraints. This study presents and evaluates a multi-sensor data fusion framework integrating MODIS Terra (500 m, daily) and [...] Read more.

Reliable quantification of crop evapotranspiration (ET_c) at field resolution is a prerequisite for evidence-based irrigation scheduling in agricultural systems subject to nitrate leaching constraints. This study presents and evaluates a multi-sensor data fusion framework integrating MODIS Terra (500 m, daily) and Sentinel-2 (10–20 m, 5-day revisit) imagery to generate cloud-robust, daily ET_c maps for an 87.5 ha irrigated maize field in Nyírbátor, Hungary, during the 2020 and 2021 growing seasons. Three gap-filling strategies for missing Sentinel-2 NDVI observations were systematically compared: (i) co-regionalisation with cokriging, (ii) local time series interpolation of MODIS pixel centres using ordinary kriging, and (iii) a median time series of cotemporal MODIS pixels—a novel approach developed to suppress sub-pixel spectral contamination from roads and irrigation infrastructure. For field-mean temporal reconstruction, the median approach consistently outperformed the alternatives (adjusted R² = 0.81, NRMSE = 0.15–0.17; pixel-wise correlation 0.70–0.85), effectively filtering heterogeneous landscape artefacts. Daily crop coefficients (K_c) derived from fused NDVI time series via the FAO-56 framework yielded ET_c ranging from 0.99 mm day⁻¹ (initial stage) to 6.40 mm day⁻¹ (peak crop development). Seasonal precipitation–ET_c deficit analyses revealed contrasting patterns: near balance in 2020 versus an 85 mm mid-season deficit at critical nodes in 2021, demonstrating the potential utility of spatially explicit daily ET_c monitoring for irrigation scheduling. These deficit estimates represent irrigation demand indicators; a complete water balance would additionally require measured irrigation volumes, soil water storage changes, deep percolation, and surface runoff data. The methodology provides a proof-of-concept framework for EU Nitrates Directive compliance monitoring, relying solely on freely available satellite data. Independent ET_c validation is required before operational deployment, and transferability to other crops and regions requires validation across contrasting pedoclimatic conditions. Full article

(This article belongs to the Special Issue Sustainable and Efficient Water Use in the Face of Climate Change)

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29 pages, 43065 KB

Open AccessArticle

Numerical Simulation Research on Landslide Instability Mechanism Under Periodic Precipitation Conditions

by Ziang Liu, Lianxia Ma, Qihang Liu, Liang Song and Xiaomin Dai

Water 2026, 18(13), 1643; https://doi.org/10.3390/w18131643 - 6 Jul 2026

Viewed by 355

Abstract

Slope stability has consistently been a critical concern in mountainous road sections, with precipitation being the most significant factor precipitating slope instability. This study aims to elucidate the mechanism of slope instability under precipitation conditions and the extent of the impact of internal [...] Read more.

Slope stability has consistently been a critical concern in mountainous road sections, with precipitation being the most significant factor precipitating slope instability. This study aims to elucidate the mechanism of slope instability under precipitation conditions and the extent of the impact of internal disaster-causing factors. To achieve this objective, a numerical simulation analysis method combining GeoStudio2018R2 and FLAC3D7.0 software was employed to conduct a comprehensive analysis of an unstable slope in Xinjiang. Regarding research methodology, cyclic precipitation and seasonal snowmelt were considered as external influencing factors. Initially, a two-dimensional model was constructed using GeoStudio software to analyze the spatial and temporal variations in pore water pressure and moisture content within the slope, elucidating their dynamic characteristics at different temporal and spatial scales. Subsequently, a three-dimensional numerical model was established using FLAC3D software to conduct a detailed analysis of the stress–strain state of the slope under various conditions, thereby obtaining disaster parameters such as displacement and sliding velocity in different directions. Through further comparison and verification of the overall stability analysis results of the slope obtained from both software packages, it was observed that they exhibited a consistent trend. The research findings indicate that under conditions of high-intensity short-term precipitation, the safety factor of the slope decreases to the lowest level, potentially leading to shallow landslides with smaller displacement but faster sliding velocity. Conversely, seasonal snowmelt and long-term localized precipitation have a more profound impact on the internal structure of the slope, with the sliding zone potentially penetrating into the deep bedrock. Although the occurrence frequency is low, the impact range is extensive. By combining two-dimensional and three-dimensional analyses, a comprehensive assessment of the different disaster-causing factors of the slope was conducted, enhancing the accuracy of the analysis results. The research findings provide a scientific basis and reference value for the formulation of subsequent slope protection and monitoring plans. Full article

(This article belongs to the Special Issue Landslide on Hydrological Response)

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21 pages, 1085 KB

Open AccessArticle

The Social Dimensions of Changing Water Levels in the Mackenzie River Basin

by Kristine Wray, Brenda Parlee, MRBB Traditional Knowledge and Strengthening Partnerships Steering Committee and Tracy Howlett

Water 2026, 18(13), 1642; https://doi.org/10.3390/w18131642 - 6 Jul 2026

Viewed by 489

Abstract

Hydrological conditions in the Mackenzie River Basin (MRB) are becoming increasingly variable due to climate change, permafrost degradation, and cumulative industrial impacts. While scientific assessments have documented many of these trends, far less is known about how changing water levels and flow patterns [...] Read more.

Hydrological conditions in the Mackenzie River Basin (MRB) are becoming increasingly variable due to climate change, permafrost degradation, and cumulative industrial impacts. While scientific assessments have documented many of these trends, far less is known about how changing water levels and flow patterns affect the daily lives, livelihoods, and cultural responsibilities of Indigenous Peoples across the Basin. This paper synthesizes basin wide Indigenous Knowledge related to water level and flow variability, drawing on 31 Indigenous-led research projects. The analysis highlights shared concerns across regions, including reduced travel safety, restricted access to harvesting areas, shifting river and lake behaviour, and emotional and spiritual impacts associated with hydrological extremes. These observations align with scientific evidence of earlier breakup, prolonged low-water periods, and increased hydrological unpredictability, while also revealing social and cultural dimensions not captured through conventional monitoring. By synthesizing basin wide Indigenous Knowledge of water level and flow variability, this study provides new insight into the cumulative social ecological consequences of freshwater change in the MRB and underscores the importance of Indigenous-led research and governance in responding to accelerating hydrological variability. Full article

(This article belongs to the Section Hydrology)

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32 pages, 15519 KB

Open AccessArticle

Long-Term Supervised Ensemble Forecasting of Monthly Flows of Cetina River, Croatia

by Jadran Berbić, Eva Ocvirk and Gordon Gilja

Water 2026, 18(13), 1641; https://doi.org/10.3390/w18131641 - 6 Jul 2026

Viewed by 481

Abstract

Modelling and prediction of mean monthly flow are of particular importance for long-term planning in hydrology and water resources management. Therefore, a simplified and robust modelling procedure, derived from clearly and concisely established methodology, can benefit both researchers and practitioners. The main objective [...] Read more.

Modelling and prediction of mean monthly flow are of particular importance for long-term planning in hydrology and water resources management. Therefore, a simplified and robust modelling procedure, derived from clearly and concisely established methodology, can benefit both researchers and practitioners. The main objective of this study is to develop a robust yet simple model, capable of producing predictions of satisfactory accuracy on previously unseen data. Two chronological data allocation strategies (C1 and C2), differing in the proportions of training, calibration, and verification subsets, were evaluated to analyze their influence on model accuracy and reliability. Chain and ensemble modelling techniques were applied, resulting in several stacking regressors with different combinations of base models and final estimators. The best-performing ensemble (C2) consisted of a support vector machine, histogram gradient boosting regressor, elastic net, and two dummy regressors as base models, with an artificial neural network as the final estimator. Within the ensemble structure, dummy regressors and histogram gradient boosting regressor were used to extend the predictive range, while elastic net and support vector machine captured the overall flow bias and fundamental flow dynamics. The artificial neural network final estimator was used to integrate these components into the final flow prediction. Compared to C1, the C2 allocations strategy achieved improved generalization capability and narrower confidence intervals due to the larger training subset, indicating higher model reliability for long-term monthly flow forecasting. The study additionally emphasizes the importance of appropriate methodological workflow, careful dataset treatment, and comprehensive model evaluation using complementary statistical and hydrological analysis tools. Full article

(This article belongs to the Special Issue Application of Machine Learning in Hydrologic Sciences, 2nd Edition)

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23 pages, 13521 KB

Open AccessArticle

A Cross-Domain Optimization Framework for Wastewater Aeration Coupling Transfer Learning and Physics-Informed Constraints

by Shiming Shen, Zixu Li, Yanbo Jiang, Liyi Guo, Xiangyang Liu and Rui Xu

Water 2026, 18(13), 1640; https://doi.org/10.3390/w18131640 - 6 Jul 2026

Viewed by 410

Abstract

Data-driven aeration optimization is an effective approach for reducing energy consumption in wastewater treatment plants (WWTPs). However, in information-limited scenarios, newly established or emerging-market WWTPs often lack historical labels for aeration actions, making it difficult to construct high-precision surrogate models. Conventional cross-plant model [...] Read more.

Data-driven aeration optimization is an effective approach for reducing energy consumption in wastewater treatment plants (WWTPs). However, in information-limited scenarios, newly established or emerging-market WWTPs often lack historical labels for aeration actions, making it difficult to construct high-precision surrogate models. Conventional cross-plant model deployments face severe data distribution shifts, and standard multi-objective optimization algorithms are prone to generating non-physical extrapolation errors, such as achieving compliance with “zero aeration” under low-concentration conditions. To break through inter-plant data barriers, this study proposes an intelligent aeration decision-making framework that integrates cross-domain transfer learning with physics-informed constraints. First, this study designs an adversarial network incorporating a state-action decoupling bypass. By employing a gradient reversal layer (GRL) to extract domain-invariant representations while the decoupling bypass preserves the physical sensitivity of control commands, this network achieves robust cross-plant knowledge transfer. Second, this study proposes a physics-informed multi-objective particle swarm optimization (PI-MOPSO) algorithm, which embeds the theoretical oxygen demand as a physical penalty into the fitness function, ensuring the physical reliability of the optimization decisions. Experiments demonstrate that the surrogate model restricts the prediction errors for effluent chemical oxygen demand (COD) and effluent ammonium nitrogen removal rates to within 1%. Validated by statistical tests, the improved algorithm effectively circumvents non-physical prediction biases. Its Pareto front achieves a spacing metric of 0.0027, outperforming baseline algorithms in hypervolume stability. This framework provides reliable aeration scheduling references conforming to biochemical dynamics for target WWTPs lacking historical action labels, offering a promising theoretical foundation for future practical engineering applications. Full article

(This article belongs to the Section Wastewater Treatment and Reuse)

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39 pages, 7538 KB

Open AccessArticle

Calibration of Channel Manning’s Roughness Coefficients Using Population Simplex Evolution, Finite Volume Method, and Their Integration with Convolutional Neural Networks and Transformer

by Yixin Shen, Junqi Wang, Yulong Zhu, Bing Mao and Xizhong Shen

Water 2026, 18(13), 1639; https://doi.org/10.3390/w18131639 - 6 Jul 2026

Viewed by 425

Abstract

The roughness coefficient is a vital parameter in river dynamics calculations, and its accuracy is crucial for simulating water flow. Various factors contribute to channel roughness, and the underlying mechanisms are quite complex. There is a strong spatiotemporal correlation, which complicates the calculations, [...] Read more.

The roughness coefficient is a vital parameter in river dynamics calculations, and its accuracy is crucial for simulating water flow. Various factors contribute to channel roughness, and the underlying mechanisms are quite complex. There is a strong spatiotemporal correlation, which complicates the calculations, particularly when hydrological data is lacking or insufficient. In this study, we solved the two-dimensional shallow-water equations using the Population Simplex Evolution (PSE) with the Finite Volume Method (FVM). This approach allowed us to obtain samples for calibrating channel roughness coefficients. To enhance the analysis, we introduced a Convolutional Neural Network (CNN) to reduce the dimensionality of input parameters and extract the temporal characteristics of the flow series. Notably, we integrated a Transformer to capture the spatial characteristics of the time series. By combining the PSE-FVM with the CNN-Transformer, we effectively calibrated the roughness coefficients. Our findings indicated that the integrated PSE-FVM and CNN-Transformer model achieved high accuracy and efficiency in this calibration process. Specifically, the cross-correlation coefficients exceeded 0.90 for calibration results from September to December 2020. We recorded an average absolute deviation of 7 cm between the calculated and measured maximum water levels, and the average calibration runtime ratio was approximately 0.19% when comparing the CNN-Transformer to the PSE-FVM. Importantly, this approach could be used for rivers with incomplete hydrological data. Our work highlighted spatiotemporal correlations between roughness coefficients and their influencing factors, thereby facilitating the integration of river dynamics models with intelligent algorithms. Therefore, these findings may serve as a valuable reference for river numerical analysis, flood impact assessment, and the development of digital twins and information systems for water-related engineering projects. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

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20 pages, 2239 KB

Open AccessArticle

Cumulative Drawdown as a Primary State Variable: The Absement Method for Leaky-Aquifer Pumping-Test Analysis

by Cem B. Avcı

Water 2026, 18(13), 1638; https://doi.org/10.3390/w18131638 - 6 Jul 2026

Viewed by 356

Abstract

This study extends the Absement Method to leaky-aquifer pumping-test analysis by time integrating the Hantush–Jacob governing equation and deriving four complementary operators. Time integrating the Hantush–Jacob equation yields S·s = T∇²A − C·A, with storativity [...] Read more.

This study extends the Absement Method to leaky-aquifer pumping-test analysis by time integrating the Hantush–Jacob governing equation and deriving four complementary operators. Time integrating the Hantush–Jacob equation yields S·s = T∇²A − C·A, with storativity S, drawdown s, transmissivity T, the time (t)-integrated drawdown A(t) (absement), and leakance C. The four operators, A(t), time-averaged A(t)/t, windowed ΔA/Δt, and the normalized absement derivative (NAD), are applied jointly across all available observation wells. In a homogeneous aquifer, the fitted operators and NAD diagnostic provide mutually consistent parameter and flow-regime signatures. In a heterogeneous aquifer, systematic differences between operators become part of the interpretation: T-related variation appears as changes in the ΔA/Δt sliding profile across wells, whereas the leakage factor B = √(T/C)-related variation is identified by divergent A(t)/t asymptotes and NAD type-curve crossing. Monte Carlo assessment under composite noise (N = 50) confirms near-zero parameter bias, with T and S standard deviations approximately 3–4 times smaller for A(t)/t and ΔA/Δt than for A(t). The three field cases are identified: a 14% outward T decline with spatially uniform B (sandstone aquifer); approximately homogeneous T with outward-declining B flagged by NAD type-curve crossing before fitting (sandy aquifer); and T–B coupling resolution through the windowed ΔA/Δt profile (medium-grained sandstone aquifer). The outputs supported sustainable-yield assessment directly from routine pumping-test records. Full article

(This article belongs to the Section Hydrogeology)

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27 pages, 16924 KB

Open AccessArticle

Fly Ash as a Catalyst for the Heterogenous Fenton Process in a Hybrid Oxidation Membrane Reactor: Optimization of Wastewater Treatment in the Winery Industry

by Fadhila Malahayati Kamal, Sucipta Laksono, Sandyanto Adityosulindro, Lucas Landwehrkamp and Stefan Panglisch

Water 2026, 18(13), 1637; https://doi.org/10.3390/w18131637 - 6 Jul 2026

Viewed by 432

Abstract

The growing global population has increased energy and food demand, leading to a higher production of waste streams such as fly ash from the energy sector and wastewater from food and beverage industries. Without proper treatment, these wastes pose significant environmental concerns. One [...] Read more.

The growing global population has increased energy and food demand, leading to a higher production of waste streams such as fly ash from the energy sector and wastewater from food and beverage industries. Without proper treatment, these wastes pose significant environmental concerns. One promising strategy is to repurpose industrial byproducts for wastewater treatment. Winery wastewater, for instance, contains acidic organic compounds and alcohol that are difficult to remove using conventional methods, while large amounts of fly ash remain underutilized. This study, therefore, examines a hybrid system that combines fly ash-assisted Fenton oxidation with membrane filtration for winery wastewater treatment. The process involved sequential Fenton pre-treatment followed by lab-scale nanofiltration using a 1 kg/mol ceramic membrane (13.1 cm²). A Design of Experiments approach was applied to evaluate system performance under varying H₂O₂ dosages (10–30 mL/L), fly ash loadings (1–3 g/L), and membrane fluxes (40–80 LMH). Filtration was performed through multiple constant-flux cycles, with energy requirements ranging from 400 to 800 kWh/m³ for the flux variations calculated from the lab-scale pump operating at a constant power supply. The hybrid method showed strong performance, achieving 70% TOC removal and 90% reduction of color and iron. However, considerable membrane fouling was observed, likely due to increased retention and deposition of organic matter, iron, and fly ash during filtration. Full article

(This article belongs to the Section Wastewater Treatment and Reuse)

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24 pages, 6322 KB

Open AccessArticle

Daily Runoff Prediction Using a BiLSTM–XGBoost Residual-Correction Framework with SHAP-Based Hydrological Interpretation in the Andi Reservoir Basin, China

by Yang Zhang, Jiasheng Zhang, Jinxiao Li, Bochao Bi and Bin Ran

Water 2026, 18(13), 1636; https://doi.org/10.3390/w18131636 - 6 Jul 2026

Viewed by 548

Abstract

Accurate daily runoff prediction is essential for flood control, reservoir operation, and scientific water resources management. However, runoff processes are increasingly affected by climate change and human activities, leading to pronounced nonlinearity and nonstationarity that limit the performance of single data-driven models. This [...] Read more.

Accurate daily runoff prediction is essential for flood control, reservoir operation, and scientific water resources management. However, runoff processes are increasingly affected by climate change and human activities, leading to pronounced nonlinearity and nonstationarity that limit the performance of single data-driven models. This study aims to improve the reliability and hydrological credibility of daily runoff prediction by systematically evaluating recurrent neural network (RNN) structures and explicitly modeling prediction residuals. Three commonly used RNN architectures—long short-term memory (LSTM), gated recurrent unit (GRU), and bidirectional long short-term memory (BiLSTM)—are systematically compared for daily runoff prediction in the Andi Reservoir watershed under identical hydrometeorological conditions. Based on the comparative results, BiLSTM is selected as the base model to capture dominant temporal dependencies. To further address systematic prediction errors under complex hydrological conditions, a residual-learning framework is constructed by integrating BiLSTM with extreme gradient boosting (XGBoost), in which XGBoost is employed to model and correct the nonlinear residuals of BiLSTM predictions. In addition, the Shapley Additive Explanations (SHAP) method is applied to interpret the contributions of input variables and to examine the learning mechanisms of both the base model and the residual-correction stage. Results indicate that BiLSTM performs better than LSTM and GRU for daily runoff prediction and that residual correction using XGBoost further enhances prediction accuracy and robustness, particularly under nonstationary conditions and peak-flow scenarios. The contribution of this study lies in providing a systematic modeling framework that combines model comparison, residual learning, and interpretability analysis to support more reliable daily runoff prediction in complex watersheds. Full article

(This article belongs to the Special Issue Application of Machine Learning in Hydrological Monitoring)

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26 pages, 13577 KB

Open AccessArticle

Foundations for Water Governance: Action Typology of Water Resources Plans Based on Deliverable-Oriented Classification

by Ticiana Marinho de Carvalho Studart, Lívia de Oliveira Lima, Francisco de Assis de Souza Filho, Maria Aparecida Melo Rocha, Paulo Ricardo Menezes Soares and Eduardo Sávio Passos Rodrigues Martins

Water 2026, 18(13), 1635; https://doi.org/10.3390/w18131635 - 6 Jul 2026

Viewed by 423

Abstract

Water Resources Plans (WRPs) are foundational policy instruments globally, yet implementation rates remain persistently low. Without consistent action classification, policymakers cannot define what to measure, track outcomes systematically, or generate evidence for adaptive learning. This study develops and validates a comprehensive typology of [...] Read more.

Water Resources Plans (WRPs) are foundational policy instruments globally, yet implementation rates remain persistently low. Without consistent action classification, policymakers cannot define what to measure, track outcomes systematically, or generate evidence for adaptive learning. This study develops and validates a comprehensive typology of water resources actions, positioning it as a foundational framework for systematic performance measurement and international transferability. The typology was constructed through a rigorous multi-phase methodology: initial consolidation and unification of actions from Ceará’s hydrographic plans (serving as a methodological foundation due to the state’s comprehensive participatory water resources planning process, 2021–2024), expert consensus via focal group discussions, and empirical validation across the entire Brazilian national context. Validation encompassed 53 Water Resources Plans (20 Brazilian state plans, 14 Brazilian river basin plans, and 19 international plans), achieving 99.6% applicability. The typology operationalizes action classification through 13 first-order categories and 160 subtypes, organized around the concept of ‘deliverable’—a governance-neutral principle that permits instantiation across diverse institutional arrangements. The identified action categories reflect universal principles of water management maturity recognized in international planning contexts (European Water Framework Directive, Turkish and Moroccan water governance systems), demonstrating that the typology captures generalizable patterns of adaptive planning behavior rather than Brazil-specific peculiarities. Furthermore, the typology’s governance-agnostic design—based on deliverable-centered logic rather than institutional-specific procedures—enables its adaptation to diverse water governance models, from highly decentralized (Brazil’s basin committees) to centralized systems (as in other countries). By offering a structured and comprehensive categorization, this typology functions as a valuable menu of action types for future Water Resources Plans development, ensuring a holistic consideration of potential interventions. Its dual role—as a precursor to robust indicator development and as a guide for future planning—underscores its transformative potential for both assessing past actions and informing prospective water management. Full article

(This article belongs to the Special Issue Water Governance and Sustainable Water Resources Management, 2nd Edition)

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27 pages, 3113 KB

Open AccessArticle

Microplastic Transport Within and Downstream of Circular Porous Vegetation: A Numerical Study in Open-Channel Flow

by Prateek Kumar Singh, Joao Nuno Fernandes, Xiaonan Tang and Maria Teresa Viseu

Water 2026, 18(13), 1634; https://doi.org/10.3390/w18131634 - 6 Jul 2026

Viewed by 481

Abstract

This study numerically investigates how a finite, circular patch of emergent vegetation alters microplastic (MP) transport, concentration, and retention in open-channel flow. A validated numerical model was developed to represent the vegetation patch as a porous zone and simulate MP transport. The framework [...] Read more.

This study numerically investigates how a finite, circular patch of emergent vegetation alters microplastic (MP) transport, concentration, and retention in open-channel flow. A validated numerical model was developed to represent the vegetation patch as a porous zone and simulate MP transport. The framework was validated against laboratory data for two configurations: a low-blockage case and a high-blockage case. After validation, 36 MP cases, comprising four polymer densities, three particle diameters ranging from 0.1 to 0.5 mm, and two categories of shape factors (elongated and spherical), were released upstream and tracked over 180–420 s. Results show that vegetation density, represented by the blockage parameter and solid volume fraction, primarily controls the interception of microplastics. Dense patches create persistent recirculation and low-velocity zones that increase residence time and trapping, whereas sparse patches induce only transient disturbances, allowing rapid downstream advection. Quantitatively, retention in the dense configuration was ≈62% for the smaller MP sizes (0.1–0.2 mm) versus ≈35% in the sparse configuration at 300 s. Polymer density, particle shape, and particle size had only secondary effects under the tested moderate flow conditions. Smaller microplastics and elongated particles showed slightly higher retention. The findings identify dense vegetation as a selective hydrodynamic filter, demonstrating that vegetation-induced flow restructuring is the dominant control on MP fate. These effects should be considered in river restoration and pollution mitigation strategies. Full article

(This article belongs to the Special Issue Complex Vegetated Flows in Riverine Open-Channel: Turbulence, Morphology, and Multi-Scale Particle Transport)

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17 pages, 1117 KB

Open AccessArticle

Total Dissolved Gas Supersaturation as a System-Level Constraint on Flexible Hydropower Dispatch: An Engineering Assessment Within the Water–Energy–Environment Nexus

by Guilherme Martinez Figueiredo Ferraz, Carlos Barreira Martinez, Dieimys Santos Ribeiro, Guilherme Sousa Bastos, Andrey Leonardo Fagundes de Castro, Lorena Bettinelli Nogueira, Juliano Mafra Neves, Liandro Rosa, Bruno Correia Macedo and Ramon Rodrigues Vieira de Carvalho

Water 2026, 18(13), 1633; https://doi.org/10.3390/w18131633 - 6 Jul 2026

Viewed by 402

Abstract

The increasing contribution of non-dispatchable renewable energy sources has changed the operating patterns of hydropower plants, especially in run-of-river schemes with limited storage capacity. Under intermittent dispatch, turbine shutdowns may occur while environmental-flow requirements must still be maintained. In these situations, spillway releases [...] Read more.

The increasing contribution of non-dispatchable renewable energy sources has changed the operating patterns of hydropower plants, especially in run-of-river schemes with limited storage capacity. Under intermittent dispatch, turbine shutdowns may occur while environmental-flow requirements must still be maintained. In these situations, spillway releases become more frequent, creating hydraulic conditions that can lead to total dissolved gas (TDG) supersaturation downstream. This study evaluates TDG supersaturation as an operational constraint in an Amazonian run-of-river hydropower plant. This assessment combines field measurements with controlled laboratory exposure tests using representative native fish species. Total gas pressure (TGP) was measured in both field and laboratory settings and converted into TDG saturation percentages. A laboratory-scale TDG generation system was developed to reproduce supersaturation conditions associated with spillway operation. Field measurements recorded TDG levels above 130% during spillway-activation events associated with dispatch decisions. In the laboratory, exposure tests showed rapid loss of viability in native Amazonian fish at TDG levels of 115% and above. These results indicate operational warning ranges for sustained spillway use. The findings suggest that TDG supersaturation should not be treated solely as an environmental issue. Rather, it represents a technical constraint on hydropower dispatch in systems with increasing renewable penetration. Incorporating TDG-related limits into operational planning and spillway management may help preserve hydropower flexibility while supporting environmental compliance. Full article

(This article belongs to the Section Water-Energy Nexus)

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3 pages, 131 KB

Open AccessEditorial

Water Footprint and Energy Sustainability

by Winnie Gerbens-Leenes and Santiago D. Vaca-Jiménez

Water 2026, 18(13), 1632; https://doi.org/10.3390/w18131632 - 6 Jul 2026

Viewed by 330

Abstract

In many basins worldwide, high-quality freshwater is becoming increasingly scarce, while energy production increasingly requires freshwater [...] Full article

(This article belongs to the Special Issue Water Footprint and Energy Sustainability)

4 pages, 138 KB

Open AccessEditorial

From Earth Observation to Water Intelligence: Remote Sensing for Integrated and Sustainable Water Resource Management

by Anuj Tiwari

Water 2026, 18(13), 1631; https://doi.org/10.3390/w18131631 - 6 Jul 2026

Viewed by 312

Abstract

Sustainable water resource management requires actionable information on water availability, water quality, water-related hazards, and water use [...] Full article

(This article belongs to the Special Issue Use of Remote Sensing Technologies for Water Resources Management)

37 pages, 17500 KB

Open AccessArticle

Experimental Investigation of a Modified Towery Bio-Rack Constructed Wetland System for Domestic Wastewater Treatment

by Mahesh Lokhande, Popat Kumbhar, Dipak A. Jadhav, Mahesh Balasaheb Chougule and Chirag Yogendra Chaware

Water 2026, 18(13), 1630; https://doi.org/10.3390/w18131630 - 5 Jul 2026

Viewed by 472

Abstract

The growing urbanisation of India is a major contributor to the production of 72,368 million litres of wastewater daily. Unfortunately, not even 28 to 31% of the generated wastewater receives proper treatment before disposal, putting public health, water quality, and ecological conditions at [...] Read more.

The growing urbanisation of India is a major contributor to the production of 72,368 million litres of wastewater daily. Unfortunately, not even 28 to 31% of the generated wastewater receives proper treatment before disposal, putting public health, water quality, and ecological conditions at risk. Traditional wastewater treatment technologies have been proven effective, but they cannot be applied in decentralised settings due to excessive initial investment costs, continuous power needs, and the need for expert supervision. Constructed wetlands (CWs) provide an efficient and environmentally friendly option for decentralised treatment, but these systems suffer from a gradual loss of effectiveness associated with the problem of media-clogging in traditional setups. This research investigates the functioning and efficiency of the Modified Towery Bio-rack Constructed Wetland (MTBRCW) technology designed specifically to mitigate media-clogging issues. The MTBRCW is tested on the basis of its performance under continuous operating conditions for thirteen months (January 2025 to January 2026), as well as on the effectiveness of the treatment at eight different hydraulic retention times (days 1 to 8). A pilot-scale MTBRCW system was monitored through two periodic sampling events (S1 and S2) conducted during each month of operation. The pilot-scale MTBRCW unit is made up of an inlet storage tank (volume 0.099 m³) followed by two wetland containers (volume 0.034 m³ each) planted with Typha angustifolia and Chrysopogon zizanioides (vetiver grass). In continuous testing mode, influent–effluent paired samples are collected for eight days at each HRT (totalling eighty samples), and samples are analysed according to APHA Standard Methods for pH, BOD, COD, TN, and TP. In continuous testing mode, the MTBRCW exhibits high removal efficiencies at the levels of 89.8% for BOD, 87.5% for COD, 78.2% for TN, and 74.4% for TP. The BOD/COD of the effluent was within the prescribed CPCB discharge limits for all thirteen months of the study, and the TN levels were adhered to in 12 out of 13 months, with one non-compliance event recorded only in July 2025 (effluent TN = 10.8 mg/L), coinciding with the peak monsoon hydraulic loading rate of 0.28 m³/m²·d. TP remained within CPCB limits in all thirteen months. In batch testing mode, removal efficiencies are 94.9% for BOD and 89.9% for COD by day 8. In addition, there were no indications of clogging or any reduction in hydraulic performance during the entire period of the tests through the use of visual inspections and measurement of the outlet flows, but this can only be seen as an observation in a field operation, and not as proof of the hydraulic performance of the system, since no tracer test or measurement of hydraulic conductivity was conducted. Full article

(This article belongs to the Special Issue Water Quality, Wastewater Treatment and Water Recycling, 2nd Edition)

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51 pages, 7418 KB

Open AccessReview

Comparative Ecology and Management of Green and Red Planktothrix Blooms in European Freshwater

by Marcella Pasqualetti, Ajay Valiyaveettil Salimkumar, Martina Braconcini, Fabrizio Scialanca, Susanna Gorrasi and Massimiliano Fenice

Water 2026, 18(13), 1629; https://doi.org/10.3390/w18131629 - 5 Jul 2026

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Abstract

Planktothrix species are among the most widespread bloom-forming cyanobacteria in freshwater ecosystems and are of particular concern because of their ability to produce cyanotoxins and form persistent harmful algal blooms (HABs). Among them, Planktothrix agardhii and Planktothrix rubescens are the most extensively studied [...] Read more.

Planktothrix species are among the most widespread bloom-forming cyanobacteria in freshwater ecosystems and are of particular concern because of their ability to produce cyanotoxins and form persistent harmful algal blooms (HABs). Among them, Planktothrix agardhii and Planktothrix rubescens are the most extensively studied species and are responsible for a large proportion of bloom events reported in European lakes. This review synthesizes current knowledge on the taxonomy, ecophysiology, toxin production, environmental drivers, species interactions, and management of Planktothrix blooms, with a particular focus on European freshwater ecosystems. The available evidence highlights marked ecological differences between the two dominant species. P. agardhii is primarily associated with shallow, eutrophic, and well-mixed lakes, whereas P. rubescens is typically found in deep, stratified, and relatively transparent water bodies, where it forms persistent metalimnetic populations. These contrasting ecological strategies influence bloom development, toxin dynamics, detection, and management. Nutrient availability, light climate, temperature, water column stability, and biological interactions all contribute to bloom establishment and persistence, while climate change is expected to further modify bloom frequency, duration, and geographic distribution. The review also examines current monitoring and mitigation approaches, highlighting the limitations of conventional surface-based surveys for detecting deep P. rubescens populations and emphasizing the need for integrated monitoring strategies combining depth-resolved sampling, molecular tools, and toxin analyses. Overall, understanding the ecological and physiological diversity of Planktothrix species is essential for improving risk assessment, developing effective management measures, and mitigating the impacts of cyanobacterial blooms in European freshwaters. Full article

(This article belongs to the Special Issue Biological and Ecological Protection in the Freshwater Ecosystems)

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32 pages, 14471 KB

Open AccessArticle

Surface-Water Wetness Regulates the Urban Heat Island: An Explainable GeoAI Framework for Blue–Green Cooling in Arid Riyadh, Saudi Arabia

by Mohammed Hazza Khalid Al-Otaibi, Abdulla Al Kafy and Hamad Ahmed Altuwaijri

Water 2026, 18(13), 1628; https://doi.org/10.3390/w18131628 - 5 Jul 2026

Viewed by 629

Abstract

Wetlands and surface-water features regulate the thermal environment of cities through evaporative cooling, yet in arid metropolitan regions these hydrological buffers are scarce and rarely quantified against urban heat. Here, we link satellite-derived surface-water wetness to land surface temperature (LST) and urban heat [...] Read more.

Wetlands and surface-water features regulate the thermal environment of cities through evaporative cooling, yet in arid metropolitan regions these hydrological buffers are scarce and rarely quantified against urban heat. Here, we link satellite-derived surface-water wetness to land surface temperature (LST) and urban heat island (UHI) intensity in Riyadh, Saudi Arabia, using an explainable Geospatial Artificial Intelligence (GeoAI) framework. We assembled 2000 cloud-masked Landsat 8/9 sample points for July 2014 and 2024 in Google Earth Engine and derived the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Built-up Index (NDBI), and two surface-water indices, the Modified Normalized Difference Water Index (MNDWI) and the Normalized Difference Water Index (NDWI), together with LST, UHI, terrain and population. Surface-water wetness was the strongest cool-side correlate of thermal stress: MNDWI related negatively to LST (r = −0.48) and to UHI intensity (r = −0.53), stronger than either vegetation or built-up density (both p < 0.001). Each 0.1 increase in MNDWI corresponded to a 2.2 °C reduction in LST. Five machine-learning algorithms predicted LST with test R² of 0.71–0.76 and UHI with R² of 0.68–0.72, and SHapley Additive exPlanations (SHAPs) identified MNDWI as the single most important thermal driver, ahead of elevation and vegetation. Point-level LST rose by 1.99 °C between 2014 and 2024 (p < 0.001), while open surface water was absent from all 2000 samples, indicating a hydrological deficit in the city’s thermal regulation. These findings suggest that protecting and expanding blue–green features along corridors such as Wadi Hanifah offers a measurable cooling lever for arid-city climate adaptation. Full article

(This article belongs to the Special Issue Advancements in Remote Sensing Techniques for Wetland Hydrology and Ecosystem Monitoring)

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27 pages, 2372 KB

Open AccessArticle

Synergistic Effect of Electrostatic Field Pretreatment and Microbial Degradation of Selected Pharmaceuticals in Real Wastewater

by Tomáš Sezima, Martina Ujházy, Radmila Kučerová, Adéla Příhodová, Nikola Drahorádová and David Chrastina

Water 2026, 18(13), 1627; https://doi.org/10.3390/w18131627 - 4 Jul 2026

Viewed by 406

Abstract

The increasing contamination of municipal wastewater by a broad spectrum of pharmaceuticals necessitates effective quaternary treatment stages. This pilot study evaluates an innovative combined technology: physical electrostatic pretreatment (conducted using experimental equipment based on a patented design (EP 2388068)) followed by biodegradation in [...] Read more.

The increasing contamination of municipal wastewater by a broad spectrum of pharmaceuticals necessitates effective quaternary treatment stages. This pilot study evaluates an innovative combined technology: physical electrostatic pretreatment (conducted using experimental equipment based on a patented design (EP 2388068)) followed by biodegradation in real secondary effluent samples (COD_(Cr) 22.0 mg·L⁻¹ to 32.0 mg·L⁻¹). A total of 17 selected micropollutants were subjected to an 8-h exposure in a high-intensity electrostatic field (20 kV) and a subsequent 20-day microbial degradation using a mixed culture of erythropolis, R. rhodochrous, and R. degradans. Results demonstrate high substance-specific efficiency. The most significant synergistic effect was observed for moderately biodegradable compounds, particularly venlafaxine (improvement up to ~44%), trimethoprim (25–36%), and tramadol (31–58%), representing a ~30–37% efficiency increase over standalone biodegradation. For readily biodegradable (e.g., metoprolol) or highly persistent substances, the impact was inconsistent. Physical pretreatment alone at 20 kV exhibited low to moderate efficiency (up to ~30%) without the biological stage. This combined approach represents a promising synergistic solution for wastewater treatment plant intensification. The primary mechanism involves enhancement of target compound bioavailability induced by the electrostatic field, which subsequently accelerates microbial metabolism. Full article

(This article belongs to the Special Issue Advanced Biotechnologies for Water and Wastewater Treatment, 3rd Edition)

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28 pages, 1842 KB

Open AccessReview

Biochar-Integrated Nature-Based Solutions for Pesticide Bioremediation in Urban Water Systems: Mechanisms, Applications, and Future Perspectives

by Yashika Raheja, Chandan Deosthali, Tasmia Falaque, Vivek Kumar Gaur and Sunita Varjani

Water 2026, 18(13), 1626; https://doi.org/10.3390/w18131626 - 4 Jul 2026

Viewed by 590

Abstract

Pesticide contamination in urban runoff, stormwater, and peri-urban drainage networks is an increasing concern because of the persistence, mobility, and ecological toxicity of many pesticide residues and their transformation products. Nature-based solutions (NBSs), including constructed wetlands, bioretention systems, biofilters, and permeable reactive bio-barriers, [...] Read more.

Pesticide contamination in urban runoff, stormwater, and peri-urban drainage networks is an increasing concern because of the persistence, mobility, and ecological toxicity of many pesticide residues and their transformation products. Nature-based solutions (NBSs), including constructed wetlands, bioretention systems, biofilters, and permeable reactive bio-barriers, provide low-energy and ecologically compatible platforms for urban water treatment; however, their performance is often constrained by limited sorption capacity, substrate saturation, variable hydraulic loading, and incomplete degradation of persistent pesticides. Biochar offers a multifunctional amendment for strengthening these systems because its tunable porosity, surface functionality, mineral composition, redox activity, and microbial habitat-forming capacity can support pesticide adsorption, catalytic transformation, and biodegradation. This review critically evaluates biochar-integrated NBSs for pesticide-contaminated urban water systems by linking biochar production and modification strategies with pesticide removal mechanisms, biochar–microbe interactions, engineered treatment configurations, and field-scale applicability. A comparative synthesis is provided across material-level mechanisms, system-level performance, machine learning-assisted prediction, techno-economic feasibility, life-cycle impacts, and environmental risk considerations. By integrating material properties, removal mechanisms, NBS configurations, predictive modeling, sustainability assessment, and risk considerations, this review provides a broader comparative basis than previous studies focused mainly on individual aspects of biochar-based pesticide remediation. Future priorities include standardized biochar production, long-term field validation, spent-biochar management, ecotoxicological assessment, and data-driven optimization of biochar-assisted NBSs. Full article

(This article belongs to the Special Issue Sustainable Urban Water Management: The Role of Nature-Based Solutions)

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