Pub Date : 2026-02-01DOI: 10.1016/j.jconhyd.2026.104865
Yuta Fukatsu , Tomomi Oguri , Takafumi Hamamoto , Keisuke Ishida , Andrew Martin , Yukio Tachi
For long-term safety assessments of deep geological disposal, evaluating effective diffusion coefficients (De) and distribution coefficients (Kd) under in-situ conditions remains a critical yet challenging task due to practical limitations. This study aims to establish a methodology for evaluating these parameters under realistic geological conditions through an integrated analysis of a long-term in-situ diffusion (LTD-II) experiment and complementary laboratory through-diffusion experiments in Grimsel granodiorite. The proposed approach combines (i) post analysis of cored samples to characterize spatial variations in pore connectivity and anisotropic transport, (ii) numerical modeling that accounts for the borehole disturbed zone (BDZ), and (iii) laboratory diffusion experiments to verify the consistency and reliability of in-situ parameter estimation.
The modeling reproduced both the depletion curves and the tracer concentration profiles observed in the LTD-II experiment, particularly the sharp gradients within a few millimeters from the injection hole, which were attributed to BDZ. The derived De and Kd values for sorbing tracers (Na+, Cs+, and Ba2+) were consistent between laboratory and in-situ conditions for transport distances up to several centimeters, confirming the reliability of the parameter derivation approach for sorbing species over short distances. In contrast, non-sorbing tracers (HTO and 36Cl−) exhibited depth-dependent concentration variations extending ∼50 cm from the injection hole. The De values of non-sorbing tracers were two to three times higher than those obtained in laboratory tests, yet remained within the same order of magnitude. These variations of non-sorbing tracers could be qualitatively explained by anisotropic transport along foliation and minor advection over several tens of centimeters, highlighting the importance of accounting for local structural and hydraulic variations when interpreting in-situ diffusion data.
These results demonstrate that integrating in-situ diffusion data with laboratory verification and spatial profiling provides a methodology for deriving diffusion and sorption parameters representative of in-situ conditions, and clarifies the practical limitations and applicable range of transport modeling in crystalline rocks.
{"title":"Methodology for evaluating matrix diffusion and sorption parameters in crystalline rocks: Application to laboratory and in-situ diffusion experiments at the Grimsel Test Site","authors":"Yuta Fukatsu , Tomomi Oguri , Takafumi Hamamoto , Keisuke Ishida , Andrew Martin , Yukio Tachi","doi":"10.1016/j.jconhyd.2026.104865","DOIUrl":"10.1016/j.jconhyd.2026.104865","url":null,"abstract":"<div><div>For long-term safety assessments of deep geological disposal, evaluating effective diffusion coefficients (<em>D</em><sub>e</sub>) and distribution coefficients (<em>K</em><sub>d</sub>) under in-situ conditions remains a critical yet challenging task due to practical limitations. This study aims to establish a methodology for evaluating these parameters under realistic geological conditions through an integrated analysis of a long-term in-situ diffusion (LTD-II) experiment and complementary laboratory through-diffusion experiments in Grimsel granodiorite. The proposed approach combines (i) post analysis of cored samples to characterize spatial variations in pore connectivity and anisotropic transport, (ii) numerical modeling that accounts for the borehole disturbed zone (BDZ), and (iii) laboratory diffusion experiments to verify the consistency and reliability of in-situ parameter estimation.</div><div>The modeling reproduced both the depletion curves and the tracer concentration profiles observed in the LTD-II experiment, particularly the sharp gradients within a few millimeters from the injection hole, which were attributed to BDZ. The derived <em>D</em><sub>e</sub> and <em>K</em><sub>d</sub> values for sorbing tracers (Na<sup>+</sup>, Cs<sup>+</sup>, and Ba<sup>2+</sup>) were consistent between laboratory and in-situ conditions for transport distances up to several centimeters, confirming the reliability of the parameter derivation approach for sorbing species over short distances. In contrast, non-sorbing tracers (HTO and <sup>36</sup>Cl<sup>−</sup>) exhibited depth-dependent concentration variations extending ∼50 cm from the injection hole. The <em>D</em><sub>e</sub> values of non-sorbing tracers were two to three times higher than those obtained in laboratory tests, yet remained within the same order of magnitude. These variations of non-sorbing tracers could be qualitatively explained by anisotropic transport along foliation and minor advection over several tens of centimeters, highlighting the importance of accounting for local structural and hydraulic variations when interpreting in-situ diffusion data.</div><div>These results demonstrate that integrating in-situ diffusion data with laboratory verification and spatial profiling provides a methodology for deriving diffusion and sorption parameters representative of in-situ conditions, and clarifies the practical limitations and applicable range of transport modeling in crystalline rocks.</div></div>","PeriodicalId":15530,"journal":{"name":"Journal of contaminant hydrology","volume":"277 ","pages":"Article 104865"},"PeriodicalIF":4.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146073940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01DOI: 10.1016/j.jconhyd.2026.104870
Chunlu Jiang , Yuqun Zhang , Qianqian Wang
Groundwater discharge and associated dissolved carbon fluxes are essential parameters in wetland ecosystems of coal mining subsidence lakes. Previous studies have shown that groundwater discharge considerably contributes to isolated coal mining subsidence lakes. However, groundwater discharge and associated dissolved inorganic carbon (DIC) flux into open-type subsidence lakes remain poorly understood. In this study, radioactive (222Rn) and stable water isotopes (18O) were used as tracers to establish isotope mass balance models, and to quantify groundwater discharge into an open-type coal mining subsidence lake. The results showed that the estimated lacustrine groundwater discharge (LGD) rates using the 222Rn and 18O mass balance models were 38.54 ± 21.05 mm/d and 27.89 ± 3.53 mm/d, respectively, which accounted for 15.56% and 12.30% of the total source of lake water. On this basis, combined with a DIC end-member mixing model and CO2 diffusion model, DIC flux from LGD was 70.33 ± 1.41 mmol/(m2·d), accounting for 19.10% of the total lake DIC inventory and 65.60% of the total CO2 evasion from the lake. The results suggest that CO2 escape from freshwater lakes may be an important source of atmospheric carbon, which should be included in the carbon budget of lake budgets. The results provide a theoretical basis for accurate assessment of groundwater discharge and the carbon budget in open-type subsidence lakes. This is important for local water environment protection and the utilization of water resources.
{"title":"Groundwater discharge and dissolved inorganic carbon flux into an open-type coal mining subsidence lake in eastern China","authors":"Chunlu Jiang , Yuqun Zhang , Qianqian Wang","doi":"10.1016/j.jconhyd.2026.104870","DOIUrl":"10.1016/j.jconhyd.2026.104870","url":null,"abstract":"<div><div>Groundwater discharge and associated dissolved carbon fluxes are essential parameters in wetland ecosystems of coal mining subsidence lakes. Previous studies have shown that groundwater discharge considerably contributes to isolated coal mining subsidence lakes. However, groundwater discharge and associated dissolved inorganic carbon (DIC) flux into open-type subsidence lakes remain poorly understood. In this study, radioactive (<sup>222</sup>Rn) and stable water isotopes (<sup>18</sup>O) were used as tracers to establish isotope mass balance models, and to quantify groundwater discharge into an open-type coal mining subsidence lake. The results showed that the estimated lacustrine groundwater discharge (LGD) rates using the <sup>222</sup>Rn and <sup>18</sup>O mass balance models were 38.54 ± 21.05 mm/d and 27.89 ± 3.53 mm/d, respectively, which accounted for 15.56% and 12.30% of the total source of lake water. On this basis, combined with a DIC end-member mixing model and CO<sub>2</sub> diffusion model, DIC flux from LGD was 70.33 ± 1.41 mmol/(m<sup>2</sup>·d), accounting for 19.10% of the total lake DIC inventory and 65.60% of the total CO<sub>2</sub> evasion from the lake. The results suggest that CO<sub>2</sub> escape from freshwater lakes may be an important source of atmospheric carbon, which should be included in the carbon budget of lake budgets. The results provide a theoretical basis for accurate assessment of groundwater discharge and the carbon budget in open-type subsidence lakes. This is important for local water environment protection and the utilization of water resources.</div></div>","PeriodicalId":15530,"journal":{"name":"Journal of contaminant hydrology","volume":"277 ","pages":"Article 104870"},"PeriodicalIF":4.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146073935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01DOI: 10.1016/j.jconhyd.2026.104855
Aronne Dell'Oca , Davide Abu El Khair , Chiara Ferré , Roberto Comolli , Monica Riva
The toxicity and long-term persistence of heavy metals pose a major threat across environmental compartments. Heavy metal contamination of soils poses long-term risks to groundwater resources, particularly in urban environments where rainfall-driven infiltration under unsaturated conditions can promote contaminant migration toward underlying aquifers. The aim of this study is to assess how uncertainty in soil hydraulic and sorption properties affects predictions of heavy metals migration from urban soils to groundwater. To this aim, we cast our work in a stochastic framework that integrates column scale drainage experiments and batch sorption tests to estimate key parameters governing water flow and heavy metal sorption dynamic, along with their associated uncertainty. Monte Carlo simulations are then performed to mimic the rainfall-induced drainage of heavy metals from metal-enriched soils through sewage sludge application. We consider two representative urban soil types and five heavy metals commonly detected in urban environments, i.e. lead (Pb), copper (Cu), chromium (Cr), nickel (Ni) and zinc (Zn). Our results indicate that Cr is highly mobile, while Ni, Zn, Cu exhibit consistently low mobility across both soils. Lead displays a strong soil-dependent behavior, transitioning from high to low mobility depending on the substrate. Outputs of a rigorous global sensitivity analysis reveal that, for highly mobile metals, flow and transport parameters have significant influence on metals migrations, reflecting the strong interplay of unsaturated flow and reactive transport processes. On the other hand, for low mobile heavy metals, parameters defining the initial contamination conditions and soil water content dominate the temporal evolution of metals retention in the soil. These findings indicate that parameter uncertainty and flow-transport processes in the vadose zone should be explicitly considered in groundwater contamination risk assessment protocols for urban environments.
{"title":"Heavy metals in unsaturated urban soils: Experimental insights and stochastic forecasting","authors":"Aronne Dell'Oca , Davide Abu El Khair , Chiara Ferré , Roberto Comolli , Monica Riva","doi":"10.1016/j.jconhyd.2026.104855","DOIUrl":"10.1016/j.jconhyd.2026.104855","url":null,"abstract":"<div><div>The toxicity and long-term persistence of heavy metals pose a major threat across environmental compartments. Heavy metal contamination of soils poses long-term risks to groundwater resources, particularly in urban environments where rainfall-driven infiltration under unsaturated conditions can promote contaminant migration toward underlying aquifers. The aim of this study is to assess how uncertainty in soil hydraulic and sorption properties affects predictions of heavy metals migration from urban soils to groundwater. To this aim, we cast our work in a stochastic framework that integrates column scale drainage experiments and batch sorption tests to estimate key parameters governing water flow and heavy metal sorption dynamic, along with their associated uncertainty. Monte Carlo simulations are then performed to mimic the rainfall-induced drainage of heavy metals from metal-enriched soils through sewage sludge application. We consider two representative urban soil types and five heavy metals commonly detected in urban environments, i.e. lead (Pb), copper (Cu), chromium (Cr), nickel (Ni) and zinc (Zn). Our results indicate that Cr is highly mobile, while Ni, Zn, Cu exhibit consistently low mobility across both soils. Lead displays a strong soil-dependent behavior, transitioning from high to low mobility depending on the substrate. Outputs of a rigorous global sensitivity analysis reveal that, for highly mobile metals, flow and transport parameters have significant influence on metals migrations, reflecting the strong interplay of unsaturated flow and reactive transport processes. On the other hand, for low mobile heavy metals, parameters defining the initial contamination conditions and soil water content dominate the temporal evolution of metals retention in the soil. These findings indicate that parameter uncertainty and flow-transport processes in the vadose zone should be explicitly considered in groundwater contamination risk assessment protocols for urban environments.</div></div>","PeriodicalId":15530,"journal":{"name":"Journal of contaminant hydrology","volume":"277 ","pages":"Article 104855"},"PeriodicalIF":4.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146073939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Corrigendum to 'Magnetic biochar prepared by co-pyrolysis of sludge and organic medical solid waste for pH-universal removal of ciprofloxacin' [Journal of Contaminant Hydrology 277 (2026) 104862].","authors":"Junping Meng, Binbin Yao, Jinsheng Liang, Xinhui Duan, Xiangying Wei","doi":"10.1016/j.jconhyd.2026.104873","DOIUrl":"https://doi.org/10.1016/j.jconhyd.2026.104873","url":null,"abstract":"","PeriodicalId":15530,"journal":{"name":"Journal of contaminant hydrology","volume":" ","pages":"104873"},"PeriodicalIF":4.4,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146097122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ensuring reliable river-water quality assessment is increasingly important in North Africa, where pollution pressures and data limitations complicate monitoring. Therefore, the research developed a principal-component-analysis-based water quality index (WQI_P) that is designed to address eclipsing, multicollinearity, and subjectively assigned weights that affect traditional indices such as the weighted-arithmetic WQI (WA_WQI). The objective of the research is to evaluate whether PCA-derived weights and objective parameter selection improve reliability, uncertainty, and classification stability. A dataset of 159 river-water samples from the Skikda region (Algeria) was analyzed. After screening correlated variables and extracting PCA contributions, WQI_P was constructed from the retained components. Eight machine-learning algorithms and a stacked ensemble were used under 10-fold cross-validation to compare the prediction performance and uncertainty of WQI_P and WA_WQI. Agreement metrics, PREI scores, confidence intervals, and class-transition analysis were used to assess the differences between the two indices, Predictive uncertainty was quantified using a Gaussian Monte Carlo simulation, which propagates variability by repeatedly perturbing model residuals to generate distributions of index predictions. The WQI_P consistently produced lower prediction errors (stacked RMSE = 2.74; MAE = 1.75) than the WA_WQI (RMSE = 3.16; MAE = 2.21), together with narrower 95% confidence intervals and reduced predictive uncertainty. The classification outcomes shifted toward a stricter and more balanced assessment: the proportion of samples classified as "Excellent" decreased (30 to 7), "Good" increased (55 to 88), and "Unsuitable" declined (40 to 12). These results indicated that grounding weights in the multivariate structure enhances stability and reduces dependence on a small set of dominant parameters. The findings demonstrated that the WQI_P can improve transparency, objectivity, and monitoring efficiency by focusing on the most informative variables. The index is applicable to data-scarce regions where objective weighting and uncertainty control are essential. Future work should test WQI_P across larger and more heterogeneous basins, extend validation using spatial-temporal blocking, and explore its integration into operational monitoring frameworks.
确保可靠的河流水质评估在北非日益重要，那里的污染压力和数据限制使监测复杂化。因此，研究开发了一个基于主成分分析的水质指数（WQI_P），该指数旨在解决影响加权算法WQI （WA_WQI）等传统指标的重叠、多重共线性和主观赋予的权重。研究的目的是评估pca衍生的权重和客观参数选择是否提高了可靠性、不确定性和分类稳定性。分析了来自Skikda地区（阿尔及利亚）的159个河水样本的数据集。筛选相关变量并提取主成分贡献后，利用保留分量构建WQI_P。在10倍交叉验证下，使用8种机器学习算法和堆叠集成来比较WQI_P和WA_WQI的预测性能和不确定性。使用一致性指标、PREI分数、置信区间和类别转换分析来评估两个指标之间的差异，预测不确定性使用高斯蒙特卡罗模拟进行量化，该模拟通过反复扰动模型残差来传播可变性，以生成指数预测的分布。WQI_P始终比WA_WQI （RMSE = 3.16; MAE = 2.21）产生更低的预测误差（堆叠RMSE = 2.74; MAE = 1.75），并且具有更窄的95%置信区间和更低的预测不确定性。分类结果转向更严格和更平衡的评估：分类为“优秀”的样本比例减少（30到7），“良好”的样本比例增加（55到88），“不合适”的样本比例下降（40到12）。这些结果表明，多变量结构中的接地权重增强了稳定性，减少了对一小组主导参数的依赖。研究结果表明，WQI_P通过关注信息量最大的变量，可以提高透明度、客观性和监测效率。该指标适用于数据稀缺地区，需要客观加权和不确定性控制。未来的工作应该在更大、更异构的盆地中测试WQI_P，使用时空阻塞扩展验证，并探索将其整合到运营监测框架中。
{"title":"Enhancing water quality assessment in Skikda, Algeria using the PCA-based weighted index (WQI_P) and its predictive performance: a comparison with traditional WA_WQI approaches.","authors":"Benacherine Mostefa, Hafid Hinda, Alejandro Martínez, Allaoua Noua, Satour Abdelatif, Fertas Fadila, Mir Talas Mahammad Diganta, Lyazid Mohamed Nadjib, Bouchra Debassi, Md Galal Uddin","doi":"10.1016/j.jconhyd.2026.104875","DOIUrl":"https://doi.org/10.1016/j.jconhyd.2026.104875","url":null,"abstract":"<p><p>Ensuring reliable river-water quality assessment is increasingly important in North Africa, where pollution pressures and data limitations complicate monitoring. Therefore, the research developed a principal-component-analysis-based water quality index (WQI_P) that is designed to address eclipsing, multicollinearity, and subjectively assigned weights that affect traditional indices such as the weighted-arithmetic WQI (WA_WQI). The objective of the research is to evaluate whether PCA-derived weights and objective parameter selection improve reliability, uncertainty, and classification stability. A dataset of 159 river-water samples from the Skikda region (Algeria) was analyzed. After screening correlated variables and extracting PCA contributions, WQI_P was constructed from the retained components. Eight machine-learning algorithms and a stacked ensemble were used under 10-fold cross-validation to compare the prediction performance and uncertainty of WQI_P and WA_WQI. Agreement metrics, PREI scores, confidence intervals, and class-transition analysis were used to assess the differences between the two indices, Predictive uncertainty was quantified using a Gaussian Monte Carlo simulation, which propagates variability by repeatedly perturbing model residuals to generate distributions of index predictions. The WQI_P consistently produced lower prediction errors (stacked RMSE = 2.74; MAE = 1.75) than the WA_WQI (RMSE = 3.16; MAE = 2.21), together with narrower 95% confidence intervals and reduced predictive uncertainty. The classification outcomes shifted toward a stricter and more balanced assessment: the proportion of samples classified as \"Excellent\" decreased (30 to 7), \"Good\" increased (55 to 88), and \"Unsuitable\" declined (40 to 12). These results indicated that grounding weights in the multivariate structure enhances stability and reduces dependence on a small set of dominant parameters. The findings demonstrated that the WQI_P can improve transparency, objectivity, and monitoring efficiency by focusing on the most informative variables. The index is applicable to data-scarce regions where objective weighting and uncertainty control are essential. Future work should test WQI_P across larger and more heterogeneous basins, extend validation using spatial-temporal blocking, and explore its integration into operational monitoring frameworks.</p>","PeriodicalId":15530,"journal":{"name":"Journal of contaminant hydrology","volume":"277 ","pages":"104875"},"PeriodicalIF":4.4,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146124979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-29DOI: 10.1016/j.jconhyd.2026.104853
Gholamheidari Hamideh, Entezari Mojgan
Using a machine learning framework, this study investigates the spatial distribution and key environmental factors of heavy metal contamination (iron, nickel, lead, copper) in four groundwater aquifers of Isfahan province during the water year 2023-2024. A total of 150 wells were sampled and metal concentrations were determined using ICP-MS, AAS, VGA, and Mercury Analyzer methods in accordance with WHO and Iranian standards. The maximum observed concentrations of iron, nickel, lead and copper were approximately 48, 44.1, 2.9 and 11.2 mg/L respectively, with the peak concentrations of iron and copper in the Damaneh - Daran aquifers, nickel in Bouin and lead in Chadegan. Random Forest (RF) and Support Vector Machine (SVM) models were used, and in RF, 100 trees were used for accurate predictions. Multiple collinearity between environmental predictors, including soil properties, unsaturated and saturated zones, hydraulic parameters, slope, groundwater level, and aquifer depth was assessed through variance inflation factor (VIF), all of which were below 10. Model interpretation showed that soil properties and groundwater level had the greatest influence in RF, while the unsaturated layer was dominant in SVM. Iron decreased with increasing aquifer depth, pore thickness, and water table, while soil permeability and slope increased iron accumulation. Nickel was higher in shallow, shallow, and low-conductivity areas, while lead increased with depth and slope, indicating a nonlinear dependence on hydraulic and soil properties. Copper was positively correlated with soil permeability and negatively correlated with water table. Spatial predictions showed that the Bouin aquifer showed the highest iron and nickel (more than 40 and more than 30 mg/L), lead reached about 44 mg/L in Chadegan, and copper peaked in Bouin from southeast to northwest. RF outperformed SVM by achieving an accuracy of 0.7874, sensitivity of 0.7448, and specificity of 0.8243, while SVM performed poorly. This study innovatively combines machine learning models with the parameters of the DRASTIC analytical model to assess and predict heavy metal contamination in the aquifers of Isfahan province. Overall, the results confirm the nonlinear hydrogeological controls on heavy metal distribution and demonstrate the high capability of RF for reliable prediction of groundwater contamination. This approach provides a transferable method for groundwater quality assessment and supports sustainable aquifer management in arid and semi-arid regions.
{"title":"Assessment of groundwater vulnerability to heavy metals in four aquifers using machine learning algorithms.","authors":"Gholamheidari Hamideh, Entezari Mojgan","doi":"10.1016/j.jconhyd.2026.104853","DOIUrl":"https://doi.org/10.1016/j.jconhyd.2026.104853","url":null,"abstract":"<p><p>Using a machine learning framework, this study investigates the spatial distribution and key environmental factors of heavy metal contamination (iron, nickel, lead, copper) in four groundwater aquifers of Isfahan province during the water year 2023-2024. A total of 150 wells were sampled and metal concentrations were determined using ICP-MS, AAS, VGA, and Mercury Analyzer methods in accordance with WHO and Iranian standards. The maximum observed concentrations of iron, nickel, lead and copper were approximately 48, 44.1, 2.9 and 11.2 mg/L respectively, with the peak concentrations of iron and copper in the Damaneh - Daran aquifers, nickel in Bouin and lead in Chadegan. Random Forest (RF) and Support Vector Machine (SVM) models were used, and in RF, 100 trees were used for accurate predictions. Multiple collinearity between environmental predictors, including soil properties, unsaturated and saturated zones, hydraulic parameters, slope, groundwater level, and aquifer depth was assessed through variance inflation factor (VIF), all of which were below 10. Model interpretation showed that soil properties and groundwater level had the greatest influence in RF, while the unsaturated layer was dominant in SVM. Iron decreased with increasing aquifer depth, pore thickness, and water table, while soil permeability and slope increased iron accumulation. Nickel was higher in shallow, shallow, and low-conductivity areas, while lead increased with depth and slope, indicating a nonlinear dependence on hydraulic and soil properties. Copper was positively correlated with soil permeability and negatively correlated with water table. Spatial predictions showed that the Bouin aquifer showed the highest iron and nickel (more than 40 and more than 30 mg/L), lead reached about 44 mg/L in Chadegan, and copper peaked in Bouin from southeast to northwest. RF outperformed SVM by achieving an accuracy of 0.7874, sensitivity of 0.7448, and specificity of 0.8243, while SVM performed poorly. This study innovatively combines machine learning models with the parameters of the DRASTIC analytical model to assess and predict heavy metal contamination in the aquifers of Isfahan province. Overall, the results confirm the nonlinear hydrogeological controls on heavy metal distribution and demonstrate the high capability of RF for reliable prediction of groundwater contamination. This approach provides a transferable method for groundwater quality assessment and supports sustainable aquifer management in arid and semi-arid regions.</p>","PeriodicalId":15530,"journal":{"name":"Journal of contaminant hydrology","volume":"277 ","pages":"104853"},"PeriodicalIF":4.4,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146119118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-27DOI: 10.1016/j.jconhyd.2026.104872
Gaozhen Wang, Wenxian Guo
Few studies have evaluated variations in riverine Eco-Surpluses and Eco-Deficits (ES and ED) from the perspective of flow processes. Therefore, this study evaluated the river ES (ED) change from multiple time scales through the intra-annual flow process and assessed the synergistic change relationship between ES (ED) and various hydro-meteorological factors by combining the Copula model. The study also constructed a ES (ED) prediction system through the Variable Infiltration Capacity (VIC) and Light Gradient Boosting Machine (LightGBM), analyzing each influencing factor's role in the LightGBM simulation through the Shapley Additive exPlanations (SHAP) model. It was found that: the ES (ED) based on the river flow process was more in line with the actual situation of the river after the validation of the Dynamic Time Warping (DTW) and other methods; there were significant discrepancies in the joint return periods among ES (ED) and various hydro-meteorological factors by the two-dimensional and three-dimensional Copula models; the prediction system constructed by coupling the baseflow extracted from the VIC model with the LightGBM algorithm exhibits better performance, and the simulation accuracy (R2) exceeds 0.85; the results of SHAP model showed that base flow variations exert a significant influence on ES and ED dynamics, followed by the role of various hydro-meteorological factors. The study results can provide a reference basis for scheduling river cascade reservoirs and planning regional water resources.
很少有研究从流量过程的角度评价河流生态盈余和生态赤字的变化。因此，本研究通过年内流量过程从多个时间尺度评价河流ES （ED）的变化，并结合Copula模型评估ES （ED）与各种水文气象因子之间的协同变化关系。通过变入渗能力（VIC）和光梯度增强机（LightGBM）构建ES （ED）预测系统，通过Shapley加性解释（SHAP）模型分析各影响因子在LightGBM模拟中的作用。结果表明：经过动态时间翘曲（Dynamic Time Warping， DTW）等方法的验证，基于河流水流过程的ES （ED）更符合河流的实际情况；二维和三维Copula模型显示ES （ED）与各水文气象因子的联合回归期存在显著差异；将VIC模型提取的基流与LightGBM算法耦合构建的预测系统表现出较好的性能，仿真精度（R2）超过0.85；SHAP模型结果表明，基流变化对ES和ED的影响显著，其次是各种水文气象因子的作用。研究结果可为河流梯级水库调度和区域水资源规划提供参考依据。
{"title":"Assessment of changes in river eco-surplus and eco-deficit based on variable infiltration capacity model and Shapley Additive exPlanations model of Jialing River, China.","authors":"Gaozhen Wang, Wenxian Guo","doi":"10.1016/j.jconhyd.2026.104872","DOIUrl":"https://doi.org/10.1016/j.jconhyd.2026.104872","url":null,"abstract":"<p><p>Few studies have evaluated variations in riverine Eco-Surpluses and Eco-Deficits (ES and ED) from the perspective of flow processes. Therefore, this study evaluated the river ES (ED) change from multiple time scales through the intra-annual flow process and assessed the synergistic change relationship between ES (ED) and various hydro-meteorological factors by combining the Copula model. The study also constructed a ES (ED) prediction system through the Variable Infiltration Capacity (VIC) and Light Gradient Boosting Machine (LightGBM), analyzing each influencing factor's role in the LightGBM simulation through the Shapley Additive exPlanations (SHAP) model. It was found that: the ES (ED) based on the river flow process was more in line with the actual situation of the river after the validation of the Dynamic Time Warping (DTW) and other methods; there were significant discrepancies in the joint return periods among ES (ED) and various hydro-meteorological factors by the two-dimensional and three-dimensional Copula models; the prediction system constructed by coupling the baseflow extracted from the VIC model with the LightGBM algorithm exhibits better performance, and the simulation accuracy (R<sup>2</sup>) exceeds 0.85; the results of SHAP model showed that base flow variations exert a significant influence on ES and ED dynamics, followed by the role of various hydro-meteorological factors. The study results can provide a reference basis for scheduling river cascade reservoirs and planning regional water resources.</p>","PeriodicalId":15530,"journal":{"name":"Journal of contaminant hydrology","volume":"277 ","pages":"104872"},"PeriodicalIF":4.4,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146137538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-20DOI: 10.1016/j.jconhyd.2026.104863
Yu-Ying Wang , Juan Yu , Rong-Ting Jiao , Li-Li He , Yao Su , Yun-Long Wang , Hui Lin , Yan Shi , Hao-Hao Lyu
Selenium (Se) is a vital micronutrient for humans health; however, elevated concentrations can result in numerous health problems and negatively impact ecosystems. This study examines the influence of two distinct modification approaches (pre- and post-treatment) on the physicochemical properties of biochar and its efficacy in removing selenite (Se(IV)) from water. A comprehensive characterization of unmodified biochar (BC), pre-treated biochar (Fe/Mn-impregnated biochar, F-Fe/Mn-BC), and post-treated biochar (Fe/Mn-oxide-loaded biochar, A-Fe/Mn-BC) was carried out using a suite of advanced analytical techniques. To determine the optimal parameters, a systematic key parameters affecting adsorption performance was conducted by varying the initial pH, contact time, initial Se(IV) concentration, and the presence of coexisting ions. The findings indicate that A-Fe/Mn-BC has a higher adsorption capacity for Se(IV). A-Fe/Mn-BC achieved a maximum adsorption capacity of 248.8 mg∙g−1, which is roughly threefold higher than that of both BC and F-Fe/Mn-BC. The removal mechanism involves surface adsorption accompanied by the reduction of Se(IV) to elemental selenium (Se(0)), with Fe(II) and Mn(II) species on the biochar surface acting as electron donors. Furthermore, the presence of common coexisting ions in solution had negligible effects on Se(IV) removal efficiency. These findings indicate that post-treatment modification enhances biochar performance more effectively than pre-treatment, and suggest that A-Fe/Mn-BC nanomaterial demonstrated remarkable potential for use in the treatment of Se(IV) contamination.
硒（Se）是对人类健康至关重要的微量营养素；然而，浓度升高会导致许多健康问题，并对生态系统产生负面影响。本研究考察了两种不同的改性方法（预处理和后处理）对生物炭物理化学性质的影响及其去除水中亚硒酸盐（Se(IV)）的功效。采用一系列先进的分析技术，对未改性生物炭（BC）、预处理生物炭（Fe/ mn浸渍生物炭，F-Fe/Mn-BC）和后处理生物炭（Fe/ mn -氧化物生物炭，A-Fe/Mn-BC）进行了综合表征。通过改变初始pH、接触时间、初始Se（IV）浓度和共存离子的存在，对影响吸附性能的关键参数进行了系统研究，确定了最佳吸附参数。结果表明，a - fe /Mn-BC对Se（IV）具有较高的吸附能力。a - fe /Mn-BC的最大吸附容量为248.8 mg∙g−1，约为BC和F-Fe/Mn-BC的3倍。去除机制包括表面吸附，同时Se（IV）还原为元素硒（Se(0)），生物炭表面的Fe（II）和Mn（II）作为电子供体。此外，溶液中共同共存离子的存在对Se（IV）去除效率的影响可以忽略不计。这些发现表明，处理后改性比预处理更有效地提高了生物炭的性能，并表明A-Fe/Mn-BC纳米材料在处理Se（IV）污染方面具有显着的潜力。
{"title":"Exploring different modification methods of biochar for Se(IV) removal from water: Synergistic effect of adsorption and reduction","authors":"Yu-Ying Wang , Juan Yu , Rong-Ting Jiao , Li-Li He , Yao Su , Yun-Long Wang , Hui Lin , Yan Shi , Hao-Hao Lyu","doi":"10.1016/j.jconhyd.2026.104863","DOIUrl":"10.1016/j.jconhyd.2026.104863","url":null,"abstract":"<div><div>Selenium (Se) is a vital micronutrient for humans health; however, elevated concentrations can result in numerous health problems and negatively impact ecosystems. This study examines the influence of two distinct modification approaches (pre- and post-treatment) on the physicochemical properties of biochar and its efficacy in removing selenite (Se(IV)) from water. A comprehensive characterization of unmodified biochar (BC), pre-treated biochar (Fe/Mn-impregnated biochar, F-Fe/Mn-BC), and post-treated biochar (Fe/Mn-oxide-loaded biochar, A-Fe/Mn-BC) was carried out using a suite of advanced analytical techniques. To determine the optimal parameters, a systematic key parameters affecting adsorption performance was conducted by varying the initial pH, contact time, initial Se(IV) concentration, and the presence of coexisting ions. The findings indicate that A-Fe/Mn-BC has a higher adsorption capacity for Se(IV). A-Fe/Mn-BC achieved a maximum adsorption capacity of 248.8 mg∙g<sup>−1</sup>, which is roughly threefold higher than that of both BC and F-Fe/Mn-BC. The removal mechanism involves surface adsorption accompanied by the reduction of Se(IV) to elemental selenium (Se(0)), with Fe(II) and Mn(II) species on the biochar surface acting as electron donors. Furthermore, the presence of common coexisting ions in solution had negligible effects on Se(IV) removal efficiency. These findings indicate that post-treatment modification enhances biochar performance more effectively than pre-treatment, and suggest that A-Fe/Mn-BC nanomaterial demonstrated remarkable potential for use in the treatment of Se(IV) contamination.</div></div>","PeriodicalId":15530,"journal":{"name":"Journal of contaminant hydrology","volume":"277 ","pages":"Article 104863"},"PeriodicalIF":4.4,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146022906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, sludge biochar was prepared via the co-pyrolysis method using the compatibility of sewage sludge (SS) in different seasons with organic medical solid waste (OMSW) and activated by alkali conditions for the removal of ciprofloxacin (CIP) in water with different pH values. The maximum adsorption capacity of the two biochars (KS1MBC and KS2MBC) reached 83.49 mg/g and 86.19 mg/g, respectively. The structure of the biochars was characterized via XRD, BET and SEM, and the adsorption mechanism of the biochars was investigated by FTIR, Raman, and XPS. The adsorption processes of the modified biochar followed pseudo-second-order kinetics and the Langmuir isothermal adsorption model, were dominated by chemical adsorption and monolayer adsorption, and were controlled by both liquid film diffusion and intraparticle diffusion. The adsorption mechanisms included pore adsorption, electrostatic attraction, π-π interactions, hydrogen bonding, and surface complexation. After hydrothermal activation by KOH, the surface of the biochar was etched by alkali to produce a nanothin lamellar structure, which increased the specific surface area to more than 200 m2/g in both cases, thus greatly enhancing the adsorption performance of the biochar. Moreover, due to the iron-containing properties of the sludge, it can be recycled through magnetic separation, thereby reducing treatment costs and enhancing the material's overall sustainability. The alkali-modified biochar demonstrates significant potential for application in antibiotic contamination remediation and provides a theoretical foundation for advancing waste treatment and promoting green environmental protection.
{"title":"Magnetic biochar prepared by co-pyrolysis of sludge and organic medical solid waste for pH-universal removal of ciprofloxacin","authors":"Junping Meng , Binbin Yao , Jinsheng Liang , Xinhui Duan , Xiangying Wei","doi":"10.1016/j.jconhyd.2026.104862","DOIUrl":"10.1016/j.jconhyd.2026.104862","url":null,"abstract":"<div><div>In this study, sludge biochar was prepared via the co-pyrolysis method using the compatibility of sewage sludge (SS) in different seasons with organic medical solid waste (OMSW) and activated by alkali conditions for the removal of ciprofloxacin (CIP) in water with different pH values. The maximum adsorption capacity of the two biochars (KS1MBC and KS2MBC) reached 83.49 mg/g and 86.19 mg/g, respectively. The structure of the biochars was characterized via XRD, BET and SEM, and the adsorption mechanism of the biochars was investigated by FTIR, Raman, and XPS. The adsorption processes of the modified biochar followed pseudo-second-order kinetics and the Langmuir isothermal adsorption model, were dominated by chemical adsorption and monolayer adsorption, and were controlled by both liquid film diffusion and intraparticle diffusion. The adsorption mechanisms included pore adsorption, electrostatic attraction, π-π interactions, hydrogen bonding, and surface complexation. After hydrothermal activation by KOH, the surface of the biochar was etched by alkali to produce a nanothin lamellar structure, which increased the specific surface area to more than 200 m<sup>2</sup>/g in both cases, thus greatly enhancing the adsorption performance of the biochar. Moreover, due to the iron-containing properties of the sludge, it can be recycled through magnetic separation, thereby reducing treatment costs and enhancing the material's overall sustainability. The alkali-modified biochar demonstrates significant potential for application in antibiotic contamination remediation and provides a theoretical foundation for advancing waste treatment and promoting green environmental protection.</div></div>","PeriodicalId":15530,"journal":{"name":"Journal of contaminant hydrology","volume":"277 ","pages":"Article 104862"},"PeriodicalIF":4.4,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146022904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-19DOI: 10.1016/j.jconhyd.2026.104857
Qingxuan Wu , Rang Wang , Jing Yang , Hao Wang , Simin Li , Xin Jin
Non-point source phosphorus (P) transport is characterized by pronounced heterogeneity manifested in spatial clustering, temporal intermittency, and structural coupling, which together pose critical challenges for watershed management. Based on a systematic synthesis of existing studies, this review proposes a three-dimensional identification framework of hotspots-hot moments-critical source areas (H-M-C) and refines it into the concept of high-risk heterogeneous core units to characterize functional units that are co-activated by multidimensional conditions at the event scale and dominate phosphorus flux outputs. Methodologically, we trace the evolution of approaches from threshold-based criteria, distributed modeling, stable isotopes and geochemical fingerprinting, to intelligent data-driven methods, highlighting their complementarities and limitations in dimensional coverage, mechanistic interpretation, and cross-scale applicability. Furthermore, we summarize the “activation-amplification-regulation-feedback” mechanism chain from four perspectives: hydrological disturbances, land-use practices, geomorphic regulation, and multi-source feedbacks. This review emphasizes the necessity of perceiving non-stationary processes, developing scale-adaptive identification granularity, and constructing strategy-oriented feedback loops, thereby providing a structural framework and methodological pathways to bridge the gap between mechanistic understanding of phosphorus transport and practical management responses.
{"title":"Targeting critical zones: A review of heterogeneity identification methods and driving mechanisms of watershed phosphorus transport","authors":"Qingxuan Wu , Rang Wang , Jing Yang , Hao Wang , Simin Li , Xin Jin","doi":"10.1016/j.jconhyd.2026.104857","DOIUrl":"10.1016/j.jconhyd.2026.104857","url":null,"abstract":"<div><div>Non-point source phosphorus (P) transport is characterized by pronounced heterogeneity manifested in spatial clustering, temporal intermittency, and structural coupling, which together pose critical challenges for watershed management. Based on a systematic synthesis of existing studies, this review proposes a three-dimensional identification framework of hotspots-hot moments-critical source areas (H-M-C) and refines it into the concept of high-risk heterogeneous core units to characterize functional units that are co-activated by multidimensional conditions at the event scale and dominate phosphorus flux outputs. Methodologically, we trace the evolution of approaches from threshold-based criteria, distributed modeling, stable isotopes and geochemical fingerprinting, to intelligent data-driven methods, highlighting their complementarities and limitations in dimensional coverage, mechanistic interpretation, and cross-scale applicability. Furthermore, we summarize the “activation-amplification-regulation-feedback” mechanism chain from four perspectives: hydrological disturbances, land-use practices, geomorphic regulation, and multi-source feedbacks. This review emphasizes the necessity of perceiving non-stationary processes, developing scale-adaptive identification granularity, and constructing strategy-oriented feedback loops, thereby providing a structural framework and methodological pathways to bridge the gap between mechanistic understanding of phosphorus transport and practical management responses.</div></div>","PeriodicalId":15530,"journal":{"name":"Journal of contaminant hydrology","volume":"277 ","pages":"Article 104857"},"PeriodicalIF":4.4,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146022992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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