Heavy metals, including arsenic, lead, cadmium, chromium, mercury, copper, nickel, and zinc, are common contaminants in global water resources. Their occurrence stems from both natural geogenic and anthropogenic sources, such as industrial, mining, or urban activities. Heavy metals can be found in groundwater due to geogenic mobilization and leaching from ore deposits. They can also be found in streams and lakes impacted by mine drainage, industrial effluents, agricultural runoff, and urban stormwater. Elevated concentrations pose risks to human health and ecosystems, necessitating monitoring, remediation, and the safe management of generated residuals. A variety of technologies exist for heavy-metal removal. The selection and use of these technologies depend on contaminant concentration, speciation, and available resources. In this review article, the latest technologies for heavy-metal removal are presented and discussed. The availability and maturity of each technique, energy demand, management of generated residual, environmental impact, and recommended applications are discussed. Algal bioremediation and constructed wetlands are the most sustainable techniques due to their ecosystem benefits, carbon capture, and lowest energy consumption, while the most efficient industrial techniques are membrane technologies and ion-exchange systems due to their high metal selectivity and purity; however, the main restrictions are high cost and an energy-intensive nature. The most distinctive approach involves hybrid systems, which offer a more resilient and sustainable alternative by integrating complementary mechanisms that enhance flux stability, improve selectivity, and reduce energy consumption, such as the combination of Reverse Osmosis with Membrane Distillation (RO-MD) and Reverse Osmosis with Pressure Retarded Osmosis (RO-PRO). The hybrid approach, in various sequences, enhances efficiency, scalability, and ecological restoration.
Mathematical model-based accurate evaluation of the remediation process at organic pollution sites serves as an efficient approach to the management and remediation of contaminant source zones. Numerical and upscaled analytical solution models are effective mathematical methods for reproducing the Dense Nonaqueous Phase Liquid (DNAPL) remediation process. However, in the current design of pollutant removal schemes, effective mass transfer models for characterizing the elution behaviors of contaminants remain lacking. In this study, two mathematical methods integrated with improved mass transfer models were employed to simulate the multi-stage contaminant elution behaviors under two distinct scenarios: A mixed-source region subjected to continuous water flushing and a residual DNAPL source treated with shorter-duration pulse flushing of the ethanol solution. Both the improved numerical model and upscaled analytical solution model demonstrated enhanced accuracy, which was attributed to the incorporation of solubilization mechanisms into mass transfer processes and the adoption of a multi-source region division method. The Mean Absolute Errors (MAE) of the numerical simulation for the two scenarios were 20.68 mg/L and 6.93 mg/L, respectively, whereas those of the upscaled model were 33.29 mg/L and 8.60 mg/L, respectively. Comparing the two improved models, the numerical model exhibited higher accuracy, while the upscaled model was characterized by faster computation speed and fewer input parameters.
A typical high-temperature metamorphic rock geothermal reservoir was newly discovered in the Tianzhen geothermal field in Datong City, China. However, due to the complex geological structure and thermal properties, the seepage heat transfer mechanism of metamorphic rock reservoirs is still unclear, seriously impeding the efficient development and sustainable utilization of geothermal resources. This study established a percolation-heat transfer model through tracer testing and numerical simulation to reveal the percolation mode and heat transfer mechanism of high-temperature metamorphic rock reservoirs during the reinjection process. We also predicted the distribution characteristics of various physical fields in the geothermal reservoir after the geothermal system has been in operation for 100 a, analyzed the influence of different reinjection schemes on seepage heat transfer in the geothermal reservoir, and proposed an optimization strategy for the reinjection scheme. The results show that: (1) The connectivity between production and injection wells is poor, and there are water-conducting fractures connecting the shallow and bottom layers; (2) The seepage channels through fractures guide the migration of the reinjected fluid and form a cold front surface with a protruding shape towards the mining well in the temperature field, resulting in temperature changes in the production well; (3) Seepage heat transfer in thermal reservoirs is greatly affected by the reinjection flow rate and the distance between production and reinjection wells, but less by the reinjection temperature. As the reinjection temperature drops, the flow rate increases, the well spacing decreases, and the temperature variation range of the production well becomes greater; (4) Under the current reinjection test conditions, the temperature of the mining well decreased by approximately 4u00B0C after 100 a of geothermal reinjection operation, and a thermal breakthrough occurred at 78 a. Under the condition of maintaining a reinjection flow rate of 60 m3/h and a reinjection temperature of 80u00B0C unchanged, the well spacing should be no less than 470 m to ensure that the well temperature does not cause a thermal breakthrough during the reinjection operation for 100 a. This research provides a theoretical basis and optimization methods for the efficient development of high-temperature metamorphic rock thermal reservoirs.
Groundwater constitutes the primary freshwater resource in semi-arid regions, where low and erratic rainfall combined with high evapotranspiration limit effective recharge. Jaipur, a rapidly expanding metropolitan city in western India, is experiencing increasing groundwater stress due to the combined influence of climatic variability and anthropogenic pressures. While groundwater depletion in Rajasthan is well documented, the extent to which interannual climatic variability, particularly rainfall fluctuations, translates into measurable groundwater-level response in urban fractured hard-rock aquifer systems remains uncertain. This study evaluates groundwater-level dynamics (2013u20132023) in relation to climatic variability and examines the apparent decoupling between climatic signals and groundwater response under combined hydrogeological and anthropogenic influences in Jaipur. Groundwater and gridded climatic datasets were analyzed using geospatial mapping, kriging-based spatial interpolation, and correlation-based statistical approaches. Pearson, Spearman, and Kendall correlation methods were employed to assess statistical relationships. Interannual groundwater variations were further analyzed to characterize temporal depletion patterns. In addition, event-based proxy analysis using extreme precipitation indices (Ru00D71d and Ru00D75d) was conducted to evaluate the influence of short-duration and cumulative rainfall events on groundwater response. Results indicate weak and spatially inconsistent relationships between climatic variables and groundwater levels, suggesting that groundwater response cannot be adequately explained by linear climatic relationships alone and is influenced by non-linear and lagged recharge processes. A strong inverse correlation between relative humidity and evapotranspiration (r = u22120.9272, p u0026lt; 0.0001) highlights the dominant role of atmospheric moisture conditions in regulating evapotranspiration fluxes, with implications for reduced effective recharge. These findings suggest that groundwater dynamics in the study area exhibit partial decoupling from climatic variability, likely driven by hydrogeological constraints and sustained anthropogenic pressures. This underscores the importance of adopting integrated groundwater management strategies that account for both climatic variability and anthropogenic pressures.
Karst landforms are renowned for their unique characteristics, and investigating karst development characteristics is of great significance for groundwater regulation and ecological management. This study aims to interpret karst distribution under different topographic conditions in a watershed using Electrical Resistivity Tomography (ERT). Taking the Chenqi small watershed in Southwest China as the study area, 10 ERT survey lines were deployed across three topographic settings (dip slopes, anti-dip slopes, and high-lying depressions). By combining 2D/3D ERT inversion, geological drilling, and outcrop verification, the subsurface karst distribution was revealed. The results show that ERT effectively detects karst features with high heterogeneity and discontinuity. Conduit-type karst appears in the middle section of both slopes, indicating groundwater migration pathways. Karst water is dominated by runoff on dip slopes, whereas infiltration dominates on anti-dip slopes; continuous low-resistivity aquicludes in high-lying depressions control local groundwater levels. The average karst zone thickness is 2.0u20134.0 m, with a maximum of 12 m. These findings demonstrate a coupled relationship between karst structure and groundwater runoff under topographic differentiation, providing a quantitative reference for watershed-scale groundwater processes and practical value for karst water exploration, resource regulation, and slope stability assessment.
Petroleum products can contaminate groundwater through dissolution of their Water-Soluble Fractions (WSFs), yet the composition and dissolution behavior of WSFs from different refined products remain insufficiently understood. In this study, oil-water equilibrium WSFs of 25 refined petroleum products from the same refinery were generated using a slow-stirring method and analyzed for Total Organic Carbon (TOC), Total Petroleum Hydrocarbons (TPH), Volatile Petroleum Hydrocarbons (VPH), Extractable Petroleum Hydrocarbons (EPH), and Ooxygen-Containing Organic Compounds (OCOCs). The results showed that the dissolved organic concentrations of WSFs varied by 1u20132 orders of magnitude among different product types. Gasoline, naphtha, and atmospheric residues produced WSFs with relatively high TOC and TPH concentrations, dominated by C6-C9 aromatic hydrocarbons. In contrast, kerosene, diesel, and most gasoline blending components exhibited much lower dissolved hydrocarbon concentrations. In several gasoline-related products, oxygenated additives such as Methyl Tert-Butyl Ether (MTBE) and Tert-Amyl Methyl Ether (TAME) were detected at high levels and dominated the dissolved organic composition, resulting in elevated OCOCs/TPH ratios. In addition, butane was identified as a characteristic dissolved compound in the WSF of alkylated oil. These results demonstrate pronounced differences in the chemical composition and distribution patterns of dissolved constituents among refined petroleum products.
Multi-scale characterization of karst media is a fundamental prerequisite for accurate stability evaluation and collapse risk assessment in karst terrains, especially for the safety control of urban metro engineering. Taking the Huaxi South Parking Lot of Guiyang metro line 3 as a case study, this paper proposes an integrated framework for karst collapse risk assessment by coupling multi-scale geological characterization, hydrodynamic-mechanical coupling simulation, and spatial multi-factor analysis. A comprehensive dataset, including 339 borehole records, core CT scanning results, long-term hydrogeological monitoring data, and laboratory test results, was collected to conduct multi-scale characterization of karst media across macro, meso and micro scales, reveal the vertical zonation of karst structures, clarify the hydrodynamic triggering mechanism of karst collapse, determine the critical instability threshold, and reproduce the entire evolution process of collapse. The results show that negative-pressure suffusion induced by rapid groundwater level decline, with a critical pressure difference of u2264 u2212190 kPa, is the dominant trigger of karst collapse in the study area. The lowest stratum stability and highest collapse risk occur in the strata with an overburden thickness of 2u20135 m and a karst cavity diameter of u2265 3 m. The high-risk zones account for 2.3% of the total study area, and are mainly distributed in the southern part, while the overall site remains stable under normal hydrodynamic conditions. This study can provide theoretical support and technical reference for karst collapse risk prevention and control in urban metro engineering.
Natural Background Levels (NBLs) play a pivotal role in groundwater management. Ammonia nitrogen exceeding national standards is a significant concern in the alluvial fan area of Tuzuoqi, Hohhot, Inner Mongolia. The commonly used pre-selection method relies on empirical judgment with predefined pollution thresholds, making it highly subjective and less adaptable. In this study, an improved pre-selection approach was used to assess the NBLs of ammonia nitrogen and chlorides in the study area, complemented by pollution indices to evaluate the extent and scope of contamination. The improved method first employed Hierarchical Clustering Analysis (HCA) to identify characteristic pollution indicators, including NH4+, Cl-, TDS, Ca2+, Na+, NO3-, and Chlorinated HydroCarbons (CHCs). Subsequently, the contamination levels of these indicators were analyzed to establish pollution thresholds and remove contaminated samples, thereby completing the pre-selection of original samples. The pre-selection criteria for the study area were: For ammonia nitrogen, NH4+-N > 0.5 mg/L combined with Cl- > 250 mg/L; for chloride, Cl- > 250 mg/L and Cl- > 100 mg/L with simultaneous detection of CHCs. Pre-selected samples were further analyzed using Grubbs' test to identify NBLs samples. The validity of the NBLs samples was confirmed through significance tests based on historical data. The 95th percentile of the NBLs samples was used to calculate a unified NBLs for pollution indices. The results indicate that ammonia nitrogen contamination is concentrated in the central-southern part of the industrial park, with a limited spatial extent and severe pollution near pollution sources. The exceedances of ammonia nitrogen in water source wells are due to high NBLs, which are attributed to organic-rich alluvial-lacustrine interbedded deposits. Chloride pollution has spread from the central-southern to the northern areas, causing slight contamination in some wells over a broader region. Compared to other alluvial fans, elevated chloride NBLs are related to the high content of water-soluble salts in the lacustrine sediments within the strata. This study validates the effectiveness of the improved preselection method in determining groundwater NBLs and emphasizes the role of NBLs in identifying sources and contamination levels of exceeding components.
Northern Pakistan is highly susceptible to debris flows due to its complex geomorphic structure, steep topography, climate change, glaciation, monsoonal rainfall, active seismicity, deforestation, and human activities. Despite this, high-resolution, quantitative assessments of debris flow hazards are limited, constraining effective disaster risk management. This study aims to model a representative debris flow event in the Ghizer District to predict potential deposition areas and support emergency preparedness and sustainable land-use planning in this hazard-prone region. High-resolution Unmanned Aerial Vehicle (UAV)-derived topographic data were integrated with the Rapid Mass Movement Simulation (RAMMS-DF) model to simulate debris flow runout for three release scenarios, representing distinct and combined initiation zones. Satellite images and field validation were used to delineate release and erosion zones, while vulnerability and risk were assessed by mapping exposed elements including 210 buildings and a population of 1,500 and applying spatial multi-criteria analysis within a Geographic Information System (GIS) framework. The numerical simulation for the most critical event, Scenario 3 (representing simultaneous dual-source initiation), yielded the highest magnitude results with a total flow volume of 193,717 m3, a peak flow height of 12.96 m, and a maximum impact pressure of 992.28 kPa. Vulnerability mapping identified infrastructure and agricultural land as the most exposed. Risk assessment showed that the combined scenario posed the greatest threat to local assets and communities. The study demonstrates that debris flow dynamics in high-mountain environments are non-linearly sensitive to initial release volumes and the interaction between multiple flow sources. Topographic controls such as channel confinement and slope variations are the primary drivers of flow intensity and energy dissipation. This research establishes a replicable, data-driven framework for quantitative risk assessment in data-limited mountainous regions. The resulting high-resolution hazard and risk maps provide a scientific basis for defining land-use restrictions, prioritizing slope stabilization, and guiding the placement of emergency infrastructure to support disaster-resilient development in northern Pakistan.
This study evaluates the suitability of irrigation water in the semi-arid region of Aksum, northern Ethiopia. An integrated approach combining the Irrigation Water Quality Index (IWQI) and ArcGISbased spatial analysis was applied to assess the spatial variability of irrigation water quality. Twenty-five groundwater samples were collected and analyzed for key physicochemical parameters and heavy metals using standard laboratory techniques. Exceedances of recommended irrigation water limits were recorded for magnesium (16%), nitrate (32%), salinity hazard (12%), total dissolved solids (20%), total hardness (60%), residual sodium carbonate (16%), kelly index (4%), and magnesium ratio (32%). Based on the Irrigation Water Quality Index (IWQI), 36% of the samples fell under high restriction, 32% under moderate restriction, 24% under severe restriction, and 8% under low restriction for irrigation use. Although most of groundwater sources are suitable based on individual water quality parameters, the IWQI indicates that a significant portion of samples requires restricted use for irrigation. This highlights the need for targeted groundwater management strategies to mitigate localized risks associated with salinity and sodicity. The integrated IWQI-GIS approach demonstrated in this study is readily transferable to other arid and semi-arid regions, providing a robust tool for sustainable irrigation management and climate-resilient agricultural planning.
The extensive fill engineering slopes formed by major projects such as "managing the ditch and creating land" in the Loess Plateau region face severe challenges of rainfall-induced instability. Inspired by the self-stable structure of natural loess-paleosol sequences and the Nature-based Solutions (NbS) concept, the water-control structure for loess fill slopes was propose, which is a composite of erosion-resistant surface layer (modified cellulose-treated) and low-permeability layers (mimicking paleosol properties using lime-improved loess). Indoor soil mechanics tests (liquid/plastic limits, compaction, permeability, shear strength) and Scanning Electron Microscopy (SEM) analysis revealed that both modified materials significantly enhance soil strength and reduce permeability (e.g., lime treatment reduced saturated permeability by 95.18%). Artificial rainfall model experiments demonstrated that slopes with water-control structure exhibit delayed infiltration response (up to 1,565 minutes), reduced erosion volume (71.6% less than untreated slopes), and shifted failure modes from fluidized collapse to gradual shear-slip. Numerical simulations (GeoStudio) further optimized the low-permeability layer configuration, identifying a 3 m-thick, 2 degrees- inclined layer as optimal for maximizing stability. This study reveals that the NbS structure effectively regulates rainfall infiltration and erosion processes, significantly reducing erosion volume and altering failure modes. Consequently, the NbS-based water-control structure provides a theoretical basis and key technical support for the prevention and control of instability in loess fill slopes.
Evapotranspiration (ET) is a core parameter of the hydrology and carbon cycles, and its accurate estimation is crucial for water resource management. Satellite-based ET products provide an effective means for large-scale monitoring. However, due to limitations in the spatial and temporal resolution, the use of these products at regional and field scales is limited. In this study, daily ET in the Baoding Plain-a key groundwater resource recharge area-was estimated at a 500 m spatial resolution using the Bayesian Model Averaging (BMA) method. The model was driven by a synthesis of remote sensing datasets, reanalysis products, and interpolated data from meteorological stations. Validation results from in-situ observations indicated that the BMA ET had better performance (R=0.83, RMSE=1.25 mm/d) than each model in the BMA scheme. The spatiotemporal analysis revealed that the average annual BMA ET in the Baoding Plain was 683 mm/year from 2000 to 2019. Seasonal and monthly variations in the BMA ET captured the irrigation and water consumption patterns of the local crop rotation systems. A significant increasing trend of BMA ET (2.40 mm/year2) was observed in the Baoding Plain over the study period. At the regional scale, ET over more than 50% of the plain exhibited a significant positive trend. Further analysis identified water availability, solar radiation, and temperature as the primary drivers of ET variation. The BMA ET product generated in this study is characterized by high spatiotemporal resolution and accuracy. This reliable, high-resolution dataset offers valuable support for precision agricultural water management and hydrological studies, including groundwater investigations, in this predominantly agricultural region.
Groundwater resources are vital for sustaining agricultural productivity and ecological balance, particularly in regions facing increasing water demand and climatic variability. This study investigates the response of groundwater levels to different withdrawal scenarios in the Talesh aquifer, northern Iran, using MODFLOW (Modular Finite-Difference Groundwater Flow Model) integrated with the Groundwater Modeling System (GMS) software (Version 10.4). The model was calibrated and validated using observed data from 2005 to 2018 under both steady and transient conditions. Seven scenarios of groundwater extraction were simulated, including 5%, 10% and 15% increases and decreases relative to the baseline withdrawal rates, to evaluate potential impacts on groundwater storage and sustainability from 2019 to 2024. Statistical indices such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Error (ME) confirmed the model's reliability in reproducing observed groundwater levels. Results indicated that maintaining current groundwater withdrawal rates leads to continued groundwater level declines of up to approximately 3.12 m in localized areas of the aquifer, whereas a 15% reduction in groundwater withdrawals can result in substantial groundwater recovery, with water level rises exceeding 2.40 m at specific locations during the simulation period. The results of this study highlight the critical necessity of groundwater withdrawal management policies to balance groundwater withdrawal with natural recharge, ensure water security and support sustainable agriculture.
Nitrate contamination in water represents a significant threat to both public health and the environment. While ultrasonic technology has emerged as an eco-friendly approach with potential for enhancing nitrate removal, its full capacity remains underexplored. This study aims to assess the effectiveness of ultrasound in improving nitrate removal from aqueous solutions using biochar derived from rice straw, modified with Fe3+ and Zn2+ as cationic bridges. Conducted at the water quality laboratory of Sari Agricultural Sciences and Natural Resources University, the experiments revealed that iron-coated biochar treatments (BF and BFU) exhibited outstanding performance in nitrate removal. Ultrasound application significantly enhanced nitrate removal efficiency, with the combination of ultrasonic waves and iron-coated biochar (BFU) achieving a maximum adsorption capacity (q(m)) of 3.664 mg/g, which surpassed non-sonicated treatments (BF: 3.345 mg/g) and reduced equilibrium time by 92% (from 60 min to 5 min). Furthermore, ultrasonic treatment improved the performance of Zn2+-coated biochar (BZU), boosting removal rates by more than 25% through cavitation-induced particle fragmentation and enhanced mass transfer. Mechanistic analysis indicated that ultrasound facilitates the homogenization of the adsorption surface, favoring Langmuir-type monolayer adsorption (R-2 > 0.95), while the cationic bridges (Fe3+/Zn2+) strengthened electrostatic interactions with nitrate ions. Under optimized conditions, the combination of ultrasound and cation-modified biochar achieved over 90% nitrate removal, presenting a promising, energy-efficient, and sustainable solution for water treatment. These findings demonstrate the potential of ultrasonic-assisted, cation-modified biochar as a highly effective strategy for mitigating nitrate contamination in water systems.
At present, there is currently a lack of unified standard methods for the determination of antimony content in groundwater in China. The precision and trueness of related detection technologies have not yet been systematically and quantitatively evaluated, which limits the effective implementation of environmental monitoring. In response to this key technical gap, this study aimed to establish a standardized method for determining antimony in groundwater using Hydride Generation-Atomic Fluorescence Spectrometry (HG-AFS). Ten laboratories participated in inter-laboratory collaborative tests, and the statistical analysis of the test data was carried out in strict accordance with the technical specifications of GB/T 6379.2-2004 and GB/T 6379.4-2006. The consistency and outliers of the data were tested by Mandel's h and k statistics, the Grubbs test and the Cochran test, and the outliers were removed to optimize the data, thereby significantly improving the reliability and accuracy. Based on the optimized data, parameters such as the repeatability limit (r), reproducibility limit (R), and method bias value (delta) were determined, and the trueness of the method was statistically evaluated. At the same time, precision-function relationships were established, and all results met the requirements. The results show that the lower the antimony content, the lower the repeatability limit (r) and reproducibility limit (R), indicating that the measurement error mainly originates from the detection limit of the method and instrument sensitivity. Therefore, improving the instrument sensitivity and reducing the detection limit are the keys to controlling the analytical error and improving precision. This study provides reliable data support and a solid technical foundation for the establishment and evaluation of standardized methods for the determination of antimony content in groundwater.
To address the deficiencies in comprehensive surface contamination prevention strategies within China's nitrate-affected regions, this research innovatively proposes the DITAPH model-a systematic framework integrating groundwater nitrate vulnerability assessment and Nitrate Vulnerable Zones (NVZs) delineation through optimization of hydrogeological parameters. Based on detailed hydrogeological and hydrochemical investigations, the DITAPH model was applied in the plain areas of Quanzhou to evaluate its applicability. The model selected hydrogeological parameters (depth of groundwater, lithology of the vadose zone, topographic slope, aquifer water yield property), one climatic parameter (precipitation), and two anthropogenic parameters (land use type and population density) as assessment indicators. The results of the groundwater nitrate vulnerability assessment showed that the low, relatively low, relatively high, and high groundwater nitrate vulnerability zones in the study area accounted for 5.96%, 35.44%, 53.74% and 4.86% of the total area, respectively. Groundwater nitrate vulnerability was most strongly influenced by human activities, followed by groundwater depth and topographic slope. The high vulnerability zone is mainly affected by domestic and industrial wastewater, whereas the relatively high groundwater nitrate vulnerability zone is primarily influenced by agricultural activities. Validation of the DITAPH model revealed a significant positive correlation between the DITAPH index (DI) and nitrate concentration (rho(NO3-)). The results of the NVZs delineated by the DITAPH model are reliable and can serve as a tool for water resource management planning, guiding the development of targeted measures in the NVZs to prevent groundwater contamination.
Excessive levels of Fluoride (F-) and Cadmium (Cd) in drinking groundwater may pose health risks. This study assessed the health risks associated with F- and Cd contamination in rural drinking groundwater sources in Wutai County, Shanxi Province, China, to support population health protection, water resource management, and environmental decision-making. Groundwater samples were collected and analyzed, and a Human Health Risk Model (HHRA) was applied to evaluate groundwater quality. The results showed that both contents of F- and Cd in groundwater exceeded the Class III limits of China's national groundwater quality standard (GB/T 14848-2024). Fluoride levels met the Class V threshold, with enrichment area mainly located in the east part of the study area. Cadmium levels reached Class IV, with elevated concentrations primarily observed in the western and northwestern regions. Correlation analysis revealed that F- showed weak or no correlation with other measured substances, indicating independent sources. Health risk assessment results indicated that F- poses potential health risks to rural residents, while cadmium, due to its relatively low concentrations, does not currently present a significant health risk. Among different demographic groups, the health risk levels of F- exposure followed the order: Infants >children >adult females >adult males. The findings highlight that fluoride is the primary contributor to health risks associated with groundwater consumption in the study area. Strengthened monitoring and prevention of F- contamination are urgently needed. This research provides a scientific basis for the prevention and control of fluoride pollution in groundwater and offers practical guidance for safeguarding drinking water safety in rural China.
To elucidate the geographical differentiation characteristics and driving mechanisms of Dissolved Organic Matter (DOM) in typical rivers, this study conducted a multi-spectral investigation on three representative river types within Shandong Province: The mountainous Dawen River, the plain Tuhai River, and the artificial East Grand Canal. The DOM composition was analyzed using Ultraviolet-Visible (UV-Vis) absorption spectroscopy, Excitation-Emission Matrix (EEM) fluorescence spectroscopy, and parallel factor analysis (PARAFAC), while Principal Component Analysis (PCA) was employed to quantify the synergistic effects of natural processes and anthropogenic activities. Results revealed significant spatial heterogeneity in DOM composition and sources. The plain river exhibited the highest aromaticity (humic-like components: 43.3%) due to long-term agricultural non-point source inputs and urban wastewater discharge. The mountain stream, shaped by complex terrain and relatively intact ecosystems, was dominated by autochthonous DOM derived from microbial metabolism, with higher Fluorescence Index (FI = 2.12) and biological index (BIX = 1.35) than other river types. The artificial canal retained protein-like components (64.2%), largely attributed to winter hydrological stagnation and disturbances from shipping activities. Further analysis demonstrated that geographical settings (e.g., mountain terrain) and anthropogenic activities (e.g., agriculture, shipping) jointly regulated DOM composition by altering the balance between input and transformation processes. Integrated fluorescence parameters and PCA results suggested differentiated management strategies: protecting ecological integrity in mountain streams to sustain self-purification, enhancing non-point source interception in plain rivers, and mitigating shipping pollution in canals. This study systematically reveals the natural-anthropogenic coupling mechanisms driving DOM dynamics in northern China rivers, providing critical insights for precision water environment management at the watershed scale.
Groundwater modeling remains challenging due to heterogeneity and complexity of aquifer systems, necessitating endeavors to quantify Groundwater Levels (GWL) dynamics to inform policymakers and hydrogeologists. This study introduces a novel Fuzzy Nonlinear Additive Regression (FNAR) model to predict monthly GWL in an unconfined aquifer in eastern Iran, using a 19-year (1998-2017) dataset from 11 piezometric wells. Under three distinct scenarios with progressively increasing input complexity, the study utilized readily available climate data, including Precipitation (Prc), Temperature (Tave), Relative Humidity (RH), and Evapotranspiration (ETo). The dataset was split into training (70%) and validation (30%) subsets. Results showed that among three input scenarios, Scenario 3 (Sc3, incorporating all four variables) achieved the best predictive performance, with RMSE ranging from 0.305 m to 0.768 m, MAE from 0.203 m to 0.522 m, NSE from 0.661 to 0.980, and PBIAS from 0.771% to 0.981%, indicating low bias and high reliability. However, Sc2 (excluding ETo) with RMSE ranging from 0.4226 m to 0.9909 m, MAE from 0.3418 m to 0.8173 m, NSE from 0.2831 to 0.9674, and PBIAS from-0.598% to 0.968% across different months offers practical advantages in data-scarce settings. The FNAR model outperforms conventional Fuzzy Least Squares Regression (FLSR) and holds promise for GWL forecasting in data-scarce regions where physical or numerical models are impractical. Future research should focus on integrating FNAR with deep learning algorithms and real-time data assimilation expanding applications across diverse hydrogeological settings.
