Water

31 pages, 6573 KB

Open AccessArticle

Integrating Deep Learning and Copula Models for Flood–Drought Compound Analysis in Iran

by Saeed Farzin, Mahdi Valikhan Anaraki, Mojtaba Kadkhodazadeh and Amirreza Morshed-Bozorgdel

Water 2025, 17(24), 3479; https://doi.org/10.3390/w17243479 - 8 Dec 2025

This study aims to forecast the combined impacts of drought and flood in the future using an integrated framework. This framework integrates U-Net++, quantile mapping (QM), Copula models, and ISIMIP3b gridded large-scale discharge data (1985–2014, 2021–2050, and 2071–2100). Copula models analyze compound effects [...] Read more.

This study aims to forecast the combined impacts of drought and flood in the future using an integrated framework. This framework integrates U-Net++, quantile mapping (QM), Copula models, and ISIMIP3b gridded large-scale discharge data (1985–2014, 2021–2050, and 2071–2100). Copula models analyze compound effects in four dimensions to determine return periods for droughts and floods. The standalone U-Net++ and its integration with multiple linear regression, multiple nonlinear regression, M5 model tree, multivariate adaptive regression splines, and QM downscaled ISIMIP3b model river flows. U-Net++QM outperformed other models, with a 58% lower RRMSE. Ensemble GCMs showed less uncertainty than other models in river flow downscaling. For the Ensemble model, the highest drought severity was −300, the maximum duration was 300 months, flood peak flow reached 12,000 m³/s, and intervals lasted up to 22 months. Moreover, the return periods of compound events for this model ranged from 50 to 3000 years. Future river flow projections, using the Ensemble model and emission scenarios (SSP126, SSP370, and SSP585), showed increased vulnerability in 2071 and 2025 versus the observed period. Introducing an integrated framework serves as a management tool for addressing extreme combined phenomena under climate change. Full article

(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)

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17 pages, 1840 KB

Open AccessArticle

Humic Acid Enhances Ciprofloxacin Sorption in a Typical Loess Soil: Implications for the Fate of Veterinary Antibiotics in Soil–Water Systems

by Chuanji Qin, Yunfei Wang, Yifan Yao, Lingxiao Zhang, Zanzan Gao and Yufeng Jiang

Water 2025, 17(24), 3478; https://doi.org/10.3390/w17243478 - 8 Dec 2025

Abstract

Studies have shown that natural organic matter can regulate pollutant behavior through multiple pathways; however, research on the environmental behavior of veterinary antibiotics (VAs) in typical alkaline calcareous loess soil under the influence of exogenous organic matter remains limited. This study investigated the [...] Read more.

Studies have shown that natural organic matter can regulate pollutant behavior through multiple pathways; however, research on the environmental behavior of veterinary antibiotics (VAs) in typical alkaline calcareous loess soil under the influence of exogenous organic matter remains limited. This study investigated the influence of humic acid (HA), as a representative of natural organic matter, on the sorption behavior of ciprofloxacin (CIP) in sierozem—a typical alkaline calcareous loess soil. Using the batch equilibrium method, we examined how HA affects CIP sorption under various environmental conditions to better understand the environmental fate of VAs in soil–water systems with low organic matrix content. Results showed that CIP sorption onto sierozem involved both fast and slow processes, reaching equilibrium within 2 h, with sorption capacity increasing as HA concentration increased. Kinetic data were well described by the pseudo-second-order model regardless of HA addition, suggesting multiple mechanisms governing CIP sorption, such as chemical sorption reaction, intraparticle diffusion, film diffusion, etc. Sorption decreased with increasing temperature both before and after HA amendment, indicating an exothermic process. Isotherm analysis revealed that both the Linear and Freundlich models provided excellent fits (R² ≈ 1), implying multilayer sorption dominated by hydrophobic distribution. In ion effect experiments, cations at concentrations above 0.05 mol/L consistently inhibited CIP sorption, with inhibition strength following the order: Mg²⁺ > K⁺ > Ca²⁺ > NH₄⁺, and intensifying with increasing ionic strength. However, HA addition significantly mitigated this inhibition, likely due to complexation between HA’s functional groups (e.g., carboxyl and hydroxyl) and cations, which reduced their competitive effect and enhanced CIP sorption. pH-dependent experiments indicated stronger CIP sorption under acidic conditions. HA addition increased soil acidity, further promoting CIP retention. In summary, HA enhances CIP sorption in sierozem by providing additional sorption sites and modifying soil surface properties. These findings improve our understanding of how exogenous organic matter influences the behavior of emerging contaminants such as antibiotics in soil–water systems, offering valuable insights for environmental risk assessment in semi-arid agricultural regions. Full article

(This article belongs to the Special Issue Occurrence and Fate of Emerging Contaminants in Soil-Water Systems)

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19 pages, 2862 KB

Open AccessArticle

Hydrological Sensitivity to Land-Use and Climate Change in the Asa Watershed, Nigeria

by Ismail Adebayo Adigun, Shiksha Bastola, Beomgu Kim, Chi Young Kim and Younghun Jung

Water 2025, 17(24), 3477; https://doi.org/10.3390/w17243477 - 8 Dec 2025

Abstract

Understanding the interaction between land use and climate variability in regulating the hydrology of tropical watersheds remains a significant scientific and policy challenge, particularly in regions with limited data. This study applied the InVEST Annual Water Yield model to assess hydrological dynamics in [...] Read more.

Understanding the interaction between land use and climate variability in regulating the hydrology of tropical watersheds remains a significant scientific and policy challenge, particularly in regions with limited data. This study applied the InVEST Annual Water Yield model to assess hydrological dynamics in the Asa watershed, Nigeria, over the period 1991–2020, using three decades of precipitation and land-use/land-cover (LULC) data, along with uncertainty quantification. The results revealed a non-linear trend in water yield, with total annual yield increasing by 6.89% between 2000 and 2010, despite declining precipitation and rising evaporative demand, primarily driven by land-use modifications. Between 2010 and 2020, yield declined by 5.39% under further precipitation reduction, where precipitation sensitivity increased eightfold, marking a shift from land-use-dominated to precipitation-dominated hydrological controls. Surrogate modeling further confirmed precipitation as the dominant driver after 2010, highlighting that cumulative land degradation weakened the watershed’s natural buffering capacity and amplified climatic responses. These findings establish a threshold at which cumulative land degradation transforms watershed hydrology from land-use-dominated to climate-sensitive regimes, providing a transferable framework for identifying vulnerability thresholds in data-scarce African tropical watersheds. Full article

(This article belongs to the Section Hydrology)

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23 pages, 5245 KB

Open AccessArticle

The Spontaneous Potential Log as an Aid in Establishing Electrical–Hydraulic Conductivity Relations in Complex Sedimentary Rock Environments: A Case Study in Taiwan

by Shih-Meng Hsu, Zi-Jie You and Jie-Ru Lin

Water 2025, 17(24), 3476; https://doi.org/10.3390/w17243476 - 8 Dec 2025

Abstract

Hydraulic conductivity estimation in fractured and clay-rich sedimentary rocks remains challenging due to substantial heterogeneity and drilling disturbances. This study evaluates the capability of borehole electrical logs—particularly spontaneous potential (SP) and single-point resistance (SPR)—to improve hydraulic conductivity prediction in Taiwan’s mountainous sedimentary formations. [...] Read more.

Hydraulic conductivity estimation in fractured and clay-rich sedimentary rocks remains challenging due to substantial heterogeneity and drilling disturbances. This study evaluates the capability of borehole electrical logs—particularly spontaneous potential (SP) and single-point resistance (SPR)—to improve hydraulic conductivity prediction in Taiwan’s mountainous sedimentary formations. Integrating 124 double-packer test intervals with high-resolution electrical logs facilitates the examination of electrical–hydraulic relationships under complex lithologic conditions. The analysis shows that formation factor approaches perform poorly because drilling mud invasion alters pore–water resistivity and clay content disrupts Archie-type assumptions. An SP-assisted screening workflow was developed to identify intervals with stable electrochemical behavior, which substantially strengthened the relationship between SPR and hydraulic conductivity. The regression models developed in this study estimate hydraulic conductivity (K) from single-point resistance (SPR). The general model achieves R² = 0.716, while the high-precision model yields R² = 0.946 after SP-based data refinement. These results indicate that SP screening markedly improves the predictive reliability of resistivity-based K estimation. The findings highlight a practical and cost-effective framework for generating continuous hydraulic conductivity profiles in fractured sedimentary environments and for supporting groundwater evaluation and engineering investigations in data-limited settings. Full article

(This article belongs to the Special Issue Advances in Hydrogeological Investigations: Field Monitoring, GIS, AI, Remote Sensing, Geophysical Techniques, and Hydrochemical Analysis)

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12 pages, 2387 KB

Open AccessArticle

Sustainable Water Use in Banana Export Systems: A Water Footprint Analysis of Bananas in Guayas, Ecuador

by Freddy Carlos Gavilánez Luna and Fanny del Rocío Rodriguez Jarama

Water 2025, 17(24), 3475; https://doi.org/10.3390/w17243475 - 8 Dec 2025

Abstract

The lack of knowledge regarding the water footprint (WF) of bananas in the Guayas province of Ecuador, assessed in local terms, creates an information gap concerning the consumptive and sustainable use of water. Therefore, this study aimed to determine the WF of the [...] Read more.

The lack of knowledge regarding the water footprint (WF) of bananas in the Guayas province of Ecuador, assessed in local terms, creates an information gap concerning the consumptive and sustainable use of water. Therefore, this study aimed to determine the WF of the cultivation and packaging process of this fruit. The Hoekstra methodology was followed, using the evaporation pan procedure for crop evapotranspiration based on a 43-year historical record (1980–2023) and the USDA method for effective precipitation, selecting nine banana farms within the zone. The grey WF was assessed following two approaches: a simple procedure assuming a 10% leaching rate of agrochemicals was followed during the rainy season, and water losses through percolation were accounted for during the dry season. Nitrogen was considered as the pollutant element, while for the grey WF assessment in packaging, active chlorine in wastewater was measured. The WF was determined to be 351.4 m³ t⁻¹, distributed as 45.0% green WF, 49.0% blue WF, and 6.0% grey WF. The grey WF is distributed as 74.7% in the field and 25.3% in the packaging process. Consequently, a moderate impact on groundwater and surface water resources is inferred; however, the irrigation management applied in the zone contributes to reduced contamination of these sources. Full article

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

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13 pages, 1315 KB

Open AccessArticle

Efficiency of a DAF System in Removing Organic Matter and Lipid Compounds from Municipal Effluent

by Luis R. Paredes-Quiroz, Hermógenes Ccasani-Dávalos, Dagnith L. Bejarano-Luján, Ruth M. Ccopa-Flores and Franklin Lozano

Water 2025, 17(24), 3474; https://doi.org/10.3390/w17243474 - 8 Dec 2025

Abstract

Oil and grease (O&G) pollution in municipal effluents represents a critical environmental challenge. This study contributes a novel experimental assessment of how pressure and recirculation time influence oxygen transfer, microbubble generation, and pollutant removal in a pilot-scale DAF system, providing new insights into [...] Read more.

Oil and grease (O&G) pollution in municipal effluents represents a critical environmental challenge. This study contributes a novel experimental assessment of how pressure and recirculation time influence oxygen transfer, microbubble generation, and pollutant removal in a pilot-scale DAF system, providing new insights into process optimization for municipal wastewater treatment. This study evaluated the efficiency of a DAF system in removing organic pollutants and solids from municipal effluent by varying gauge pressure (1–5 bar) and recirculation time (1–20 min). The initial concentrations present in the effluent were 800 mg/L total solids (TS), 590 mg/L total suspended solids (TSS), 450 mg/L oil and grease (O&G), 360 mg/L biochemical oxygen demand (BOD₅), and 710 mg/L chemical oxygen demand (COD). The concentration of dissolved air (interpreted as dissolved oxygen supersaturation) reached 102.3 mg/L and removal efficiencies of 84.4% for O&G, 88.9% for BOD₅, 88.7% for COD, and 85% for TSS were achieved, while pH and dissolved solids (DS) remained stable. The saturation factor (f = 0.8) confirmed efficient oxygen-liquid transfer, attributed to the use of Raschig rings in the absorption column. The significance of this work lies in demonstrating that operating conditions directly enhance oxygen dissolution and flotation performance, highlighting an optimization pathway rarely reported for municipal effluents. The results demonstrate that DAF is a robust, stable, and energy-efficient technology capable of effectively removing organic and lipid loads from municipal effluent, providing a sustainable alternative for the pretreatment and reuse of urban wastewater. Full article

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

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16 pages, 3305 KB

Open AccessArticle

Effects of SDS Surfactant on Oxygen Transfer in a Fine-Bubble Diffuser Aeration Column

by Oscar Prades-Mateu, Guillem Monrós-Andreu, Salvador Torró, Raúl Martínez-Cuenca and Sergio Chiva

Water 2025, 17(24), 3473; https://doi.org/10.3390/w17243473 - 7 Dec 2025

Abstract

Aeration is one of the most energy-intensive operations in wastewater treatment plants, with its efficiency strongly affected by the presence of surfactants. This study investigates the impact of Sodium Dodecyl Sulphate (SDS) on oxygen mass transfer using a commercial fine-bubble diffuser. Oxygen transfer [...] Read more.

Aeration is one of the most energy-intensive operations in wastewater treatment plants, with its efficiency strongly affected by the presence of surfactants. This study investigates the impact of Sodium Dodecyl Sulphate (SDS) on oxygen mass transfer using a commercial fine-bubble diffuser. Oxygen transfer experiments were performed under varying air flow rates and SDS concentrations. Key parameters, including the volumetric mass transfer coefficient (

k_{L} a

), gas holdup, bubble size, and interfacial area, were experimentally measured and analysed. SDS reduces the average bubble diameter by up to 50%; above 4 mg/L, further increases in concentration do not change the bubble size. Gas holdup increases by approximately 2% per mg L⁻¹ of SDS, and a new empirical correlation was proposed to predict gas holdup as a function of air flow rate and surfactant concentration, achieving an R² of 0.97 with deviations below 10%. Despite the increase in interfacial area, SDS strongly suppresses interfacial turbulence, reducing the liquid-side mass transfer coefficient (

k_{L}

) by up to 70%, which ultimately leads to a significant loss of overall oxygen transfer efficiency. The Sardeing model, originally developed for single bubbles, successfully predicted

k_{L}

within ±15% of the experimental values, demonstrating its potential as a practical tool for estimating oxygen transfer in aeration systems. These findings highlight the substantial impact of surfactants on fine-bubble aeration performance and underscore the need to account for their effects in the design and operation of industrial aeration systems. Full article

(This article belongs to the Special Issue Eco-Engineered Solutions for Industrial Wastewater)

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22 pages, 1112 KB

Open AccessArticle

Electrolyte-Driven Oxidant Generation on Ti/IrO₂–SnO₂–Sb₂O₅ Electrodes for the Efficient Removal of Alachlor and Isoproturon from Water

by Nelson Bravo-Yumi, Isabel Oller, Ana Ruiz-Delgado, Martin O. A. Pacheco-Álvarez and Juan M. Peralta-Hernández

Water 2025, 17(24), 3472; https://doi.org/10.3390/w17243472 - 7 Dec 2025

Abstract

In this study, anodic oxidation (AO) was evaluated using Ti/IrO₂–SnO₂–Sb₂O₅ electrodes in chloride, sulfate, and mixed electrolytes, along with electro-Fenton (EF) and photoelectro-Fenton (PEF) at pH 3.0, for the degradation of alachlor and isoproturon, each 50 [...] Read more.

In this study, anodic oxidation (AO) was evaluated using Ti/IrO₂–SnO₂–Sb₂O₅ electrodes in chloride, sulfate, and mixed electrolytes, along with electro-Fenton (EF) and photoelectro-Fenton (PEF) at pH 3.0, for the degradation of alachlor and isoproturon, each 50 mg L⁻¹. Active chlorine species were monitored using UV–Vis, while the removal of both herbicides was quantified using High Performance Liquid Chromatography (HPLC), along with the reduction in Total Organic Carbon (TOC), mineralization current efficiency (MCE), and specific energy per TOC removed (EC_TOC). The results show that electrolyte composition influences AO more than current density. In a chloride medium, isoproturon was eliminated within minutes, whereas alachlor required mixed electrolytes of Cl⁻/SO₄²⁻, allowing simultaneous combination of HClO/ClO⁻, ^●OH, and S₂O₈²⁻/SO₄^●−, or coupling with EF. An optimal current density of ~30 mA cm⁻² limited voltage rise and radical scavenging. EF introduced measurable mineralization (15% TOC), whereas PEF achieved rapid alachlor reduction and TOC reductions of up to 76% at low Fe²⁺. Overall, sequential AO followed by PEF maximized mineralization per unit of energy, and the mixed electrolytes provided a controllable pathway to scale up oxidant speciation generation. Full article

(This article belongs to the Special Issue Applications of Advanced Oxidation Technologies in Water and Wastewater Treatment)

23 pages, 19595 KB

Open AccessArticle

The Global 9 km Soil Moisture Estimation by Downscaling of European Space Agency Climate Change Initiative Data from 1978 to 2020

by Hongtao Jiang, Hao Liu, Huanfeng Shen, Xinghua Li, Jingan Wu, Tianyi Song and Sanxiong Chen

Water 2025, 17(24), 3471; https://doi.org/10.3390/w17243471 - 7 Dec 2025

Abstract

The spatial resolution of current microwave remote sensing soil moisture (SM) data is about 25 km in global scale. The coarse scale hinders the application of SM product at regional scale. The global 9 km SM can be released by radar observations of [...] Read more.

The spatial resolution of current microwave remote sensing soil moisture (SM) data is about 25 km in global scale. The coarse scale hinders the application of SM product at regional scale. The global 9 km SM can be released by radar observations of Soil moisture Active and Passive (SMAP) satellite since 2015. For the failed radar sensor, SMAP 9 km SM is less than three months. Therefore, European Space Agency Climate Change Initiative (CCI) SM data is downscaled to 9 km using spatial temporal fusion model in the study. And the 43-year 9 km SM is downscaled by CCI data from 1978 to 2020. Results display that downscaled 9 km SM gets more detailed spatial information than CCI data. Moreover, temporal variation of CCI data in anomaly can be well captured by downscaled data. The evaluations against in-situ data indicate that temporal accuracies of downscaled data (r = 0.676, μbRMSE = 0.069 m³/m³) are comparable with CCI data (r = 0.670, μbRMSE = 0.070 m³/m³). Overall, downscaled data improves the spatial resolution of CCI data and inherits the temporal accuracy with slight improvement. Higher spatial resolution SM offers greater application potential. Additionally, the model herein enriches SM downscaling techniques. Full article

(This article belongs to the Section Soil and Water)

36 pages, 7466 KB

Open AccessArticle

Prediction and Uncertainty Quantification of Flow Rate Through Rectangular Top-Hinged Gate Using Hybrid Gradient Boosting Models

by Pourya Nejatipour, Giuseppe Oliveto, Ibrokhim Sapaev, Ehsan Afaridegan and Reza Fatahi-Alkouhi

Water 2025, 17(24), 3470; https://doi.org/10.3390/w17243470 - 6 Dec 2025

Abstract

Accurate estimation of flow discharge, Q, through hydraulic structures such as spillways and gates is of great importance in water resources engineering. Each hydraulic structure, due to its unique characteristics, requires a specific and comprehensive study. In this regard, the present study [...] Read more.

Accurate estimation of flow discharge, Q, through hydraulic structures such as spillways and gates is of great importance in water resources engineering. Each hydraulic structure, due to its unique characteristics, requires a specific and comprehensive study. In this regard, the present study innovatively focuses on predicting Q through Rectangular Top-Hinged Gates (RTHGs) using advanced Gradient Boosting (GB) models. The GB models evaluated in this study include Categorical Boosting (CatBoost), Histogram-based Gradient Boosting (HistGBoost), Light Gradient Boosting Machine (LightGBoost), Natural Gradient Boosting (NGBoost), and Extreme Gradient Boosting (XGBoost). One of the essential factors in developing artificial intelligence models is the accurate and proper tuning of their hyperparameters. Therefore, four powerful metaheuristic algorithms—Covariance Matrix Adaptation Evolution Strategy (CMA-ES), Sparrow Search Algorithm (SSA), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA)—were evaluated and compared for hyperparameter tuning, using LightGBoost as the baseline model. An assessment of error metrics, convergence speed, stability, and computational cost revealed that SSA achieved the best performance for the hyperparameter optimization of GB models. Consequently, hybrid models combining GB algorithms with SSA were developed to predict Q through RTHGs. Random split was used to divide the dataset into two sets, with 70% for training and 30% for testing. Prediction uncertainty was quantified via Confidence Intervals (CI) and the R-Factor index. CatBoost-SSA produced the most accurate prediction performance among the models (R² = 0.999 training, 0.984 testing), and NGBoost-SSA provided the lowest uncertainty (CI = 0.616, R-Factor = 3.596). The SHapley Additive exPlanations (SHAP) method identified h/B (upstream water depth to channel width ratio) and channel slope, S, as the most influential predictors. Overall, this study confirms the effectiveness of SSA-optimized boosting models for reliable and interpretable hydraulic modeling, offering a robust tool for the design and operation of gated flow control systems. Full article

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

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20 pages, 8016 KB

Open AccessArticle

Meter-Scale Redox Stratification Drives the Restructuring of Microbial Nitrogen Cycling in Soil-Sediment Ecotone of Coal Mining Subsidence Area

by Yingjia Cao, Yuanyuan Li, Xi Zhang, Ruihao Cui, Lingtong Meng, Xuyang Jiang, Lijun Hao and Zhenqi Hu

Water 2025, 17(24), 3469; https://doi.org/10.3390/w17243469 - 6 Dec 2025

Abstract

The coal mining subsidence area constitutes a distinct ecotone in the transition from agricultural soil to sediment, yet the microbially mediated nitrogen cycle within it remains inadequately understood. This investigation comprehensively analyzed physicochemical properties, microbial communities, functional genes, and co-occurrence networks along a [...] Read more.

The coal mining subsidence area constitutes a distinct ecotone in the transition from agricultural soil to sediment, yet the microbially mediated nitrogen cycle within it remains inadequately understood. This investigation comprehensively analyzed physicochemical properties, microbial communities, functional genes, and co-occurrence networks along a 0–6500 mm depth gradient. Results indicated that pH transitioned from acidic to alkaline, while TN, TP, OM, and NH₄⁺–N accumulated with depth. NO₃⁻–N decreased rapidly within 1000 mm and then stabilized. Alpha-diversity showed an S-shaped increase in richness, with Shannon index peaking at 1500 mm. Beta-diversity shifted along PC1, and the shallow subsidence area (SS) influenced by NO₃⁻–N; the transition zone (TZ) regulated by OM, TN, and NH₄⁺–N; deep subsidence area (DS) was constrained by TP and pH. Microbial communities transitioned from aerobic/facultative to strictly anaerobic phyla, yet Pseudomonadota remained dominant (24–32%) across depths. With increasing depth, gene abundances for denitrification, assimilatory nitrate reduction to ammonium (ANRA), and nitrate assimilation declined, while those for dissimilatory nitrate reduction to ammonium (DNRA) and nitrification increased; nitrogen fixation remained weak. Co-occurrence networks shifted from highly connected, short-pathlength, and clustered in TZ to highly modular and long-pathlength in DS, with Aminicenantes, Syntrophus, and Methanoregula as key taxa. Overall, the thick and stable reducing zone in the subsidence area restructured the nitrogen cycle, shifting terminal products from N₂ removal to NH₄⁺ retention. These findings advance the understanding of nitrogen transformation in soil-sediment ecotones and provide a mechanistic framework for nitrogen cycling in mining-affected ecosystems. Full article

(This article belongs to the Section Soil and Water)

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23 pages, 2048 KB

Open AccessArticle

Robust Ensemble-Based Model and Web Application for Nitrogen Content Prediction in Hydrochar from Sewage Sludge

by Esraa Q. Shehab, Nadia Moneem Al-Abdaly, Mohammed E. Seno, Hamza Imran and Antonio Albuquerque

Water 2025, 17(24), 3468; https://doi.org/10.3390/w17243468 - 6 Dec 2025

Abstract

Hydrochar is a carbon-rich material produced through the hydrothermal carbonization (HTC) of wet biomass such as sewage sludge. Its nitrogen content is a critical quality parameter, influencing its suitability for use as a soil amendment and its potential environmental impacts. This study develops [...] Read more.

Hydrochar is a carbon-rich material produced through the hydrothermal carbonization (HTC) of wet biomass such as sewage sludge. Its nitrogen content is a critical quality parameter, influencing its suitability for use as a soil amendment and its potential environmental impacts. This study develops a high-accuracy ensemble machine learning framework to predict the nitrogen content of hydrochar derived from sewage sludge based on feedstock compositions and HTC process conditions. Four ensemble algorithms—Gradient Boosting Regression Trees (GBRTs), AdaBoost, Light Gradient Boosting Machine (LightGBM), and eXtreme Gradient Boosting (XGBoost)—were trained using an 80/20 train–test split and evaluated through standard statistical metrics. GBRT and XGBoost provided the best performance, achieving R² values of 0.993 and 0.989 and RMSE values of 0.169 and 0.213 during training, while maintaining strong predictive capabilities on the test dataset. SHAP analyses identified nitrogen content, ash content, and heating temperature as the most influential predictors of hydrochar nitrogen levels. Predicting nitrogen behaviour during HTC is environmentally relevant, as the improper management of nitrogen-rich hydrochar residues can contribute to nitrogen leaching, eutrophication, and disruption of aquatic biogeochemical cycles. The proposed ensemble-based modelling approach therefore offers a reliable tool for optimizing HTC operations, supporting sustainable sludge valorisation, and reducing environmental risks associated with nitrogen emissions. Full article

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

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34 pages, 9895 KB

Open AccessArticle

Assessment of Drinking Water Quality from the Dobromierz Reservoir During the Treatment Process: Collection, Distribution and Future Challenges

by Magdalena Szewczyk, Paweł Tomczyk and Mirosław Wiatkowski

Water 2025, 17(24), 3467; https://doi.org/10.3390/w17243467 - 6 Dec 2025

Abstract

Drinking water contamination during the treatment process remains a major problem for decision-makers responsible for the collection and supply of water to recipients. This article presents measurements of 33 parameters of drinking water quality in the years 2009–2023, taken from the Dobromierz reservoir [...] Read more.

Drinking water contamination during the treatment process remains a major problem for decision-makers responsible for the collection and supply of water to recipients. This article presents measurements of 33 parameters of drinking water quality in the years 2009–2023, taken from the Dobromierz reservoir in Poland, with particular emphasis on the stages of raw water, water undergoing treatment, and utility water. The results showed that the raw water tested is contaminated microbiologically (presence of coliform bacteria), organoleptically (worse turbidity, odor, color), and chemically (increased PAHs, nitrites, benzo(α)pyrene). This indicates improper maintenance of the areas around the reservoir, i.e., agricultural areas (the existing nutrient runoff), residential areas (the lack of stringent records of cesspools and septic tanks), and roadside (improper maintenance of ditch slopes). In most cases, water at the treatment stage and at the end recipients was effectively purified (in most cases, the analyzed parameters achieved a degree of compliance with drinking water standards of at least 95%). Only for the turbidity in the network, the standards did not reach the adopted minimum level. This suggests the need to conduct systematic investment activities in order to reduce failures in the network (average system failure rate of 34%). Moreover, the statistical analysis of the results showed significant changes in the parameters between raw water and water in the water supply network and at end recipients (p < 0.05). Therefore, it is necessary to focus on protecting the quality of raw water resources for more effective treatment and ensuring human health safety. Full article

(This article belongs to the Special Issue Monitoring and Assessment of Water Quality in Drinking Water Distribution Systems)

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18 pages, 15647 KB

Open AccessArticle

Numerical Assessment of the Long-Term Dredging Impacts on Channel Evolution in the Middle Huai River

by Jin Ni, Hui Zhang, Kai Cheng, Haitian Lu and Peng Wu

Water 2025, 17(24), 3466; https://doi.org/10.3390/w17243466 - 6 Dec 2025

Abstract

Large-scale dredging in the middle Huai River has induced complex geomorphic responses that compromise the long-term stability of river regulation infrastructure. To evaluate these impacts, a one-dimensional numerical model was employed, calibrated and validated using field measurements and physical modeling, to simulate 30-year [...] Read more.

Large-scale dredging in the middle Huai River has induced complex geomorphic responses that compromise the long-term stability of river regulation infrastructure. To evaluate these impacts, a one-dimensional numerical model was employed, calibrated and validated using field measurements and physical modeling, to simulate 30-year channel evolution under both baseline and dredged scenarios. Results indicate that dredging reversed the reach-scale sediment budget from net erosion (69.80 × 10⁴ m³) to net deposition (87.67 × 10⁴ m³), while eliciting highly heterogeneous local responses. In the Liufangdi Reach, dredging produced a tripartite pattern: depositional amplification in the south branch of the Upper-Liufangdi Reach, an erosion-to-deposition transition in the Erdaohe Reach, and intensified erosion in the north branch of the Lower-Liufangdi Reach. The main channel accounted for over 84% of net volumetric changes, driving the observed morphological adjustments, while dredging promoted synchronization between main channel and floodplain evolution and established stable flow redistribution within branching channels. These findings indicate the importance of implementing spatially differentiated dredging strategies informed by sediment availability, offering critical guidance for reconciling flood control objectives with long-term morphological stability in engineered river systems. Full article

(This article belongs to the Topic Applications of Algorithms in Risk Assessment and Evaluation)

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19 pages, 1830 KB

Open AccessArticle

Spectrophotometric Polyvinyl Alcohol Detection and Validation in Wastewater Streams: From Lab to Process Control

by Michael Toni Sturm, Anika Korzin, Pieter Ronsse, Kaspar Groot Kormelinck, Erika Myers, Oleg Zernikel, Dennis Schober and Katrin Schuhen

Water 2025, 17(24), 3465; https://doi.org/10.3390/w17243465 - 6 Dec 2025

Abstract

Polyvinyl alcohol (PVA) is increasingly encountered in wastewater, yet reliable quantification and effective removal remain challenging. A colorimetric method for PVA quantification was validated, demonstrating excellent linearity and recoveries of 100.6 ± 2.8%. Limits were established at a limit of detection (LOD) of [...] Read more.

Polyvinyl alcohol (PVA) is increasingly encountered in wastewater, yet reliable quantification and effective removal remain challenging. A colorimetric method for PVA quantification was validated, demonstrating excellent linearity and recoveries of 100.6 ± 2.8%. Limits were established at a limit of detection (LOD) of 1.28 mg/L and a limit of quantification (LOQ) of 1.8 mg/L. Accuracy was influenced by the PVA type, with errors reaching up to 42% due to variations in molecular weight and degree of hydrolyzation affecting the color complex. Consequently, polymer-specific calibration is advised. Analytical precision required strict temperature control and exact reaction times, and potential matrix interferences in wastewater should be assessed prior to application. PVA removal was evaluated using an AOP process based on hydrogen peroxide (H₂O₂) and UV-C irradiation. Increasing the H₂O₂/PVA ratio beyond 1:1 provided only marginal improvements, whereas increasing the UV-C dose was more impactful. A 1:1 H₂O₂/PVA ratio was sufficient even at PVA concentrations up to 5 g/L. Optimal UV-C doses were 7.5–12.5 kJ/m²; higher doses yielded only marginal additional removal. The colorimetric method was suitable for laboratory trials. A pilot-scale treatment of industrial wastewater applied microplastic agglomeration with organosilanes followed by granular activated carbon (GAC) treatment, which reduced PVA from an average of 24.2 mg/L to 7.4 mg/L, achieving ~65% removal, while microplastic removal reached 99.1%. Full article

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

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17 pages, 1272 KB

Open AccessArticle

Unravelling Metabolic Pathways and Evaluating Process Performances in Anaerobic Digestion of Livestock Manures

by Hangbae Jun, Rahul Kadam, Sangyeol Jo and Jungyu Park

Water 2025, 17(24), 3464; https://doi.org/10.3390/w17243464 - 6 Dec 2025

Abstract

Anaerobic digestion (AD) provides significant environmental benefits by converting livestock manures, such as cattle manure (CM) and pig manure (PM), into biogas and nutrient-rich digestate, supporting circular economy principles. However, challenges arise when feedstock overload disrupts microbial balance, leading to reduced methane (CH [...] Read more.

Anaerobic digestion (AD) provides significant environmental benefits by converting livestock manures, such as cattle manure (CM) and pig manure (PM), into biogas and nutrient-rich digestate, supporting circular economy principles. However, challenges arise when feedstock overload disrupts microbial balance, leading to reduced methane (CH₄) yields and process instability. This study examined the performance of AD using CM and PM with gradually increasing organic loading rates (OLR). At steady state, CH₄ yields were 120.32 mL-CH₄/g VS for CM and 229 mL-CH₄/g VS for PM. The lower yield for CM is attributed to its high cellulose and hemicellulose content, which exceeds 50% and is difficult to degrade. In contrast, PM showed more efficient carbohydrate degradation, resulting in higher CH₄ production. Key methanogens, including Methanocorpusculum, Methanosaeta, Methanosarcina, Methanobacterium, and Methanospirillum, were present in both reactors. Metagenomic analysis revealed that pathways for degrading cellulose and hemicellulose were poorly represented in CM, while PM exhibited enhanced total volatile fatty acid metabolism. This study offers valuable insights into the metabolic pathways associated with CM and PM in anaerobic digestion. Full article

(This article belongs to the Special Issue Advances in Biological Technologies for Drinking and Wastewater Treatment)

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19 pages, 6163 KB

Open AccessArticle

Analysis of Application of Design Standards for Future Climate Change Adaptive Agricultural Reservoirs Using Cluster Analysis

by Dong-Hyuk Joo, Ra Na, Hayoung Kim, Seung-Hwan Yoo and Sang-Hyun Lee

Water 2025, 17(24), 3463; https://doi.org/10.3390/w17243463 - 5 Dec 2025

Abstract

This study aimed to assess the impact and vulnerability of climate change by classifying 26 clusters of meteorologically homogeneous regions. To determine the optimal clustering method, both K-means and Gaussian Mixture Model (GMM) clustering were analyzed using the effective storage capacity to watershed [...] Read more.

This study aimed to assess the impact and vulnerability of climate change by classifying 26 clusters of meteorologically homogeneous regions. To determine the optimal clustering method, both K-means and Gaussian Mixture Model (GMM) clustering were analyzed using the effective storage capacity to watershed area ratio. The optimal number of clusters was derived based on several evaluation metrics, including the Silhouette Score, Calinski-Harabasz Index, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). Ultimately, GMM clustering was identified as the optimal method, with the best clustering results obtained at k = 4 for an effective storage capacity of 100,000 to 400,000 tons and k = 5 for an effective storage capacity of 400,000 to 10,000,000 tons. Additionally, standard reservoirs applicable to agricultural production infrastructure design standards were identified based on homogeneous weather region clusters, the optimal clustering method, and centroid results. The findings of this study can serve as fundamental data for the development and revision of design standards, contributing to more climate-resilient agricultural infrastructure. Full article

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17 pages, 3818 KB

Open AccessArticle

Water and Soil Salinization Mechanism in the Arid Barkol Inland Basin in NW China

by Ziyue Wang, Chaoyao Zan, Yajing Zhao, Bo Xu, Rui Long, Xiaoyong Wang, Jun Zhang and Tianming Huang

Water 2025, 17(24), 3462; https://doi.org/10.3390/w17243462 - 5 Dec 2025

Abstract

Identifying the dominant mechanisms of water and soil salinization in arid and semi-arid endorheic basins is fundamental for our understanding of basin-scale water–salt balance and supports water resources management. In many inland basins, mineral dissolution, evaporation, and transpiration govern salinization, but disentangling these [...] Read more.

Identifying the dominant mechanisms of water and soil salinization in arid and semi-arid endorheic basins is fundamental for our understanding of basin-scale water–salt balance and supports water resources management. In many inland basins, mineral dissolution, evaporation, and transpiration govern salinization, but disentangling these processes remains difficult. Using the Barkol Basin in northwestern China as a representative endorheic system, we sampled waters and soils along a transect from the mountain front through alluvial fan springs and rivers to the terminal lake. We integrated δ¹⁸O–δ²H with hydrochemical analyses, employing deuterium excess (d-excess) to partition salinity sources and quantify contributions. The results showed that mineral dissolution predominated, contributing 65.8–81.8% of groundwater salinity in alluvial fan settings and ~99.7% in the terminal lake, whereas direct evapoconcentration was minor (springs and rivers ≤ 4%; lake ≤ 0.2%). Water chemistry types evolved from Ca-HCO₃ in mountainous runoff, to Ca·Na-HCO₃·SO₄ in groundwater and groundwater-fed rivers, and finally to Na-SO₄·Cl in the terminal lake. The soil profiles showed that groundwater flow and vadose-zone water–salt transport control spatial patterns: surface salinity rises from basin margins (<1 mg/g) to the lakeshore and is extremely high near the lake (23.85–244.77 mg/g). In spring discharge belts and downstream wetlands, the sustained evapotranspiration of groundwater-supported soil moisture drives surface salt accumulation, making lakeshores and wetlands into terminal sinks. The d-excess-based method can robustly separate the salinization processes despite its initial isotopic variability. Full article

(This article belongs to the Special Issue Isotope Hydrology: Tracing Water’s Journey and Water–Rock Interactions in a Changing World)

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17 pages, 2381 KB

Open AccessArticle

Effects of Forest Thinning on Water Yield and Runoff Components in Headwater Catchments of Japanese Cypress Plantation

by Ibtisam Mohd Ghaus, Nobuaki Tanaka, Takanori Sato, Moein Farahnak, Yuya Otani, Anand Nainar, Mie Gomyo and Koichiro Kuraji

Water 2025, 17(24), 3461; https://doi.org/10.3390/w17243461 - 5 Dec 2025

Abstract

Forests play a key role in sustaining global water cycles by regulating precipitation partitioning, which in turn influences both water yield and ecosystem stability. Thinning is a silvicultural tool used to improve forest plantation productivity, but it is increasingly recognized as a means [...] Read more.

Forests play a key role in sustaining global water cycles by regulating precipitation partitioning, which in turn influences both water yield and ecosystem stability. Thinning is a silvicultural tool used to improve forest plantation productivity, but it is increasingly recognized as a means for water resource management. This study investigated hydrological changes following 40% thinning of tree density with contour-aligned log placement in paired headwater catchments of a Japanese cypress forest. Annual runoff in the treated catchment was 108.7 mm above the pre-thinning baseline in the thinning year (2020), followed by smaller increases of 99.7 mm, 43.7 mm, and 0.4 mm in 2021 to 2023, after which annual yields effectively returned to pre-thinning levels. Despite these temporary increases, peak discharge and storm quickflow metrics remained within the pre-thinning range. Flow duration curve analysis revealed a sustained enhancement of low-flow discharge and baseflow throughout the post-thinning period, indicating improved low-flow resilience without increased stormflow risk. These findings demonstrate that moderate thinning combined with contour felled logs can enhance water availability in plantation forests while maintaining flood protection. They also highlight the need for long-term, multi-site studies to test the persistence and generality of these low-flow benefits under varying forest and climate conditions. Full article

(This article belongs to the Section Hydrology)

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