Water source and quality is the most important factor for region sustainable development, especially in the water-scarce arid agricultural regions. In the agricultural area of arid Qaidam Basin, water quality remains inadequately studied. Focusing on the Xiangride River Watershed in the southeastern Qaidam Basin, this research explores the recharge sources, hydrogeochemical evolution, and quality of river water and groundwater integrating correlation analysis, principal component analysis (PCA), and inverse geochemical modeling. Stable isotopic analysis indicates that river water and groundwater are derived from mountainous precipitation, and groundwater is recharged by lateral runoff and river seepage in the plain area. Most river water and groundwater samples exhibit relatively low TDS values of < 1000 mg/L, and groundwater exhibits more complex hydrochemistry compared with river water. Along the flow path, the hydrochemical types are marked by the HCO3·Cl·SO4-Na·Mg type for river water, which groundwater shows an evolution from Cl·HCO3-Na·Mg to Cl·HCO3·SO4-Na·Ca·Mg and ultimately to HCO3·Cl·SO4-Na·Ca·Mg. The comprehensive analysis by PCA, major ions relationships and inverse geochemical modeling identifies that water-rock interactions including dissolution and precipitation of evaporites, carbonates, and silicates, together with cation exchange and mixing control the hydrochemical compositions. Water quality assessment based on EQWI, SAR, and Na% values classifies most river water and groundwater as "good" without obvious spatial variation, indicating that the overall water quality is adequate for domestic and agricultural uses. The attention needs to be made in certain area with relatively elevated groundwater NO3 -. These findings provide a basis for the sustainable management of water resource in arid agricultural zones.
The unique karst geological background in the southwest China karst area is the main obstacle for achieving carbon neutrality and environmental sustainability. In the future, there is an urgent need for professionals with expertise, logical thinking ability, and knowledge integration skills. The knowledge covered in the hydrogeology course is closely related to carbon neutrality and environmental sustainability. However, through the author's comprehensive analysis of extensive teaching experience, industry research, and policy guidance, it has been found that there are several issues in the teaching of the hydrogeology course. These include a disconnect between the teaching content and the needs of real societal development, low logical thinking ability among students, lack of ability to integrate knowledge from different fields, and insufficient practical case studies and project analysis exercises. These issues seriously hinder teaching effectiveness. This teaching reform proposes three measures closely related to the policy guidance, industry demands, and research development dynamics of carbon neutrality and environmental sustainability. These measures are as follows: (1) a teaching content reform based on "logical thinking," (2) an innovative teaching model based on "case-based practical training," and (3) an exploratory teaching practice based on "knowledge integration." In addition, logical analysis practices such as dialectics, contradictions, and systems theory are conducted during the teaching process. The teaching reform innovatively categorizes the content of hydrogeology into six logical chains of problems in accordance with the connotation of carbon neutrality and sustainability processes one by one. Finally, a practical training program based on case projects has been developed to provide students with real-world experience and analysis skills. On this basis, a teaching practice base for karst carbon sinks has been constructed in Guizhou Province. It enables students to gain an in-depth understanding of karst development, hydrochemical measurement, carbon flux calculation, and other processes involved in karst carbon sink cycles and master the hydrochemical evolution laws in karst areas as well as the fundamental mechanisms of karst aquatic photosynthetic carbon sinks. These efforts will cultivate excellent reserve talent for achieving carbon neutrality and environmental sustainability in the karst area of Guizhou Province and even nationwide.
Water resource recovery facilities (WRRFs) invariably question the timing and the advantages of modifying their biosolids dewatering systems from belt filter presses to centrifuges, as this change can reduce the water content from about 80% to 70%. The upgrade makes perfect sense keeping in mind the ever-increasing distances of transporting the biosolids to end users. However, a factor of concern that needs to be considered, besides the investment capital, is the alleged sharp increase of emitted odors by centrifuge dewatering, causing a negative public impact. This paper compares the chemical and sensory odor results from a large WRRF that originally dewatered its anaerobically digested biosolids through belt filter presses and then replaced this process with dewatering centrifuges. No major changes in the wastewater characteristics or in the unit operations occurred in the interval, which provides a unique opportunity to observe the changes in odor emissions. The results show that there is a change in the predominant chemical odorants emitted as well as a sharp increase in the variety of odor characters and intensities corresponding with the change in dewatering technology. Worst-case odorant concentrations (the maximum value observed) from belt filter press to centrifuge dewatering significantly increased from 52 to 4980 ppb for hydrogen sulfide, increased from 390 to 1100 ppb for methyl mercaptan, increased from 520 to 3200 ppb for dimethyl sulfide, and increased from 27 to 270 ppb for dimethyl disulfide. At the same time, whereas the worst-case rotten vegetable odor intensity remained the same, and earthy/musty decreased by one order of magnitude, the fecal and manure odor intensities increased by two orders of magnitude. Keeping in mind that odor intensity is reported in a log scale, these changes are significant, especially as they peak at the top end of the odor intensity scale.
Hydraulic conductivity is an important hydrogeological parameter that characterizes the hydraulic properties of subsurface media, and the pattern of its variation with depth is of great significance for groundwater system simulation and resource evaluation. However, the applicability of some existing theoretical and empirical models describing how hydraulic conductivity varies with depth in salt lake areas still lacks systematic validation and evaluation based on measured data. In this study, seven typical boreholes in the West Taijinar Lake area of the Qaidam Basin were selected as the study objects. Several previous representative models describing the decay of hydraulic conductivity with depth, together with a newly proposed model using the geometric square root method, were selected for comparative analysis. The applicability of these models in a salt lake depositional environment was evaluated using the coefficient of determination (R2) and root mean square error (RMSE). The results show that hydraulic conductivity in the study area generally exhibits a significant decreasing trend with depth. Different models for the decay of hydraulic conductivity with depth show different levels of applicability among the boreholes in the study area, and each model can reflect the variation characteristics of hydraulic conductivity with depth to a certain extent. Among them, the model using the geometric square root method shows the strongest applicability for all types of boreholes, although it requires the largest number of parameters. The model of Zhang et al. (2026) and the model of Kuang and Jiao (2014) rank next, and both can better describe the characteristic pattern of hydraulic conductivity in the complex salt lake depositional environment, with rapid decline in shallow layers and gradually slower change in deeper layers. The results of this study can provide a reference for the characterization of hydrogeological parameters and groundwater flow simulation in salt lake areas and also provide a scientific basis for the evaluation of deep brine resources in the Qaidam Basin.
Fluoride (F-) enrichment in coastal groundwater poses a persistent threat to drinking water safety, yet its controlling mechanisms under seawater intrusion remain incompletely understood, particularly in northern coastal China. This study integrates hydrogeochemical analysis, Bayesian-optimized random forest modeling, and positive matrix factorization (PMF) to elucidate the sources and enrichment processes of F- in shallow groundwater of the Qinhuangdao coastal plain. Results demonstrate that elevated F- concentrations are not directly driven by seawater mixing. Instead, maximum F- levels occur under mild seawater intrusion, while severely intruded zones exhibit lower and less variable F- concentrations. PMF results further reveal that F- enrichment is dominated by geogenic sources related to fluorite dissolution, accompanied by contributions from silicate weathering and evaporation-leaching processes. Geochemical evidence indicates that seawater intrusion indirectly promotes F- release by increasing groundwater alkalinity, enhancing ionic strength, and reducing Ca2+ activity through carbonate precipitation, thereby facilitating fluorite dissolution. However, end-member mixing analysis confirms that the direct contribution of seawater-derived F- is limited. These findings clarify the nonlinear relationship between seawater intrusion intensity and groundwater F- enrichment and emphasize that seawater intrusion acts primarily as an amplifying factor rather than a primary source of fluoride. This study provides a process-based understanding of fluoride enrichment in coastal aquifers and offers scientific guidance for groundwater management and drinking water risk mitigation in seawater-intruded coastal regions.
This study evaluated the removal of contaminants present in wastewater from oil well drilling in the presence of three plant species: water hyacinth (Eichhornia crassipes), cattail (Typha domingensis), and purple fountain grass (Cenchrus setaceus "Rubrum"). The synthesized wastewater contained potentially toxic metals (Zn, Cu, and Cr) and representative hydrocarbons (naphthalene, hexane, and hexadecane) and it was applied in hydroponic systems operating in sequential batches. Agronomic, biochemical, and water quality variables were monitored periodically. The results indicated that C. setaceus had the best overall performance, indicating its absence of mortality, agronomic stability, and statistically significant removal of color, biochemical oxygen demand, total organic carbon, total carbon, and metals. The kinetics of chemical oxygen demand removal were faster in the presence of C. setaceus, with a higher reaction coefficient and better fit of the first-order model with residual (plateau) to the data. Although they promoted the removal of some pollutants, the performance of the treatments in the presence of T. domingensis and E. crassipes was inferior to that of the treatment with C. setaceus in terms of stability, vigor, and consistency of the results. It was concluded that C. setaceus has high tolerance to contaminated environments and potential for application in constructed wetland systems for the treatment of wastewater from well drilling and is a promising alternative for sustainable phytoremediation strategies.
Unraveling the integrated mechanisms governing groundwater hydrochemical evolution along a complete land-sea gradient is crucial for coastal water resource management and seawater intrusion prevention and control. This study focused on the Bailang River Basin (southern Laizhou Bay, Bohai Sea, China). Based on 45 systematically collected groundwater samples, we integrated hydrochemical statistics, Piper trilinear/Gibbs diagrams, and ion ratio analysis to clarify the hydrochemical evolution of the research area from mountains to coast. Results show: (1) The upstream reservoir area is dominated by low total dissolved solids (TDS) freshwater (360.1-1648.7 mg/L, HCO3-Ca·Mg type), which is mainly controlled by carbonate and silicate weathering; (2) midstream plain: transitional brackish-saline water (702.1-32,322.3 mg/L, shifting to Na-Ca-Cl type), affected by cation exchange, agricultural return flow, and weak evaporation; (3) coastal area: high-TDS brine (15,398.9-86,169.6 mg/L, Na-Cl type), driven by paleoseawater residual, modern seawater intrusion, and intense evaporation. This study identifies a "source-sink" evolutionary pattern controlled by the coupling of rock leaching, cation exchange, seawater intrusion, and evaporative concentration. This pattern explicitly links geomorphic gradients to hydrochemical differentiation. This work clarifies how natural processes and anthropogenic activities synergistically shape the coastal groundwater hydrochemical spatial pattern, providing a scientific basis for sustainable groundwater management and seawater intrusion control in similar regions.
The upper reaches of the Hanjiang River Basin (HJRB) are a crucial water source hub that connects the water resources between the south and north of China. Quantifying the spatiotemporal patterns and underlying drivers of vegetation dynamics in this region is indispensable for formulating targeted ecological management strategies. This study used MOD13Q1 (250 m) remote sensing data from May to September during 2000-2020, and comprehensively applied Theil-Sen + Mann-Kendall and Hurst index methods to analyze the spatiotemporal changes of NDVI, which was verified by stability analysis. When considering the impacts of natural and human driving forces, an innovative optimal parameter geographic detector (OPGD) model was utilized, effectively addressing the modifiable areal unit problem (MAUP) often overlooked by traditional methods, thereby enhancing the rigor of statistical evaluation and the precision of identifying NDVI drivers. It solves the deficiencies of traditional methods in handling spatially heterogeneous data and enhances the reliability of the model. The findings revealed the following: (1) The regional NDVI significantly increased from 2000 to 2020 (slope = 0.0033 a-1, p < 0.05) and is anticipated to maintain this upward trend going forward. (2) Altitude, surface temperature, slope, and air temperature are the main driving factors for NDVI changes (with q values uniformly surpassing 0.45). (3) The explanatory power of two-factor interactions on NDVI changes substantially exceeded that of single factors. Among these factors, the interaction between surface temperature and slope exerts the greatest influence on NDVI changes (q = 0.7266), and altitude interactions with other factors are dominant. (4) Except for specific combinations, the vast majority of the interactions of two factors have significant differences with NDVI. At the same time, the optimal threshold intervals or types of each factor conducive to vegetation growth have been determined.
Groundwater Quality (GWQ) presents a significant global concern owing to extensive agricultural and industrial activities, necessitating proficient management strategies, as it constitutes approximately half of the world's potable water supply. Traditional methods of monitoring water quality are valuable for identifying pollution sources, but they do not adequately provide an overall view of water quality trends. Machine learning (ML) technologies provide reliable predictions of water quality by learning complicated patterns from data without preconceived equations. This paper provides a meta-analysis and bibliographic review of ML applications in GWQ assessment, evaluating the accuracy, applicability, and usability of various models including artificial neural networks (ANN), support vector machines (SVM), k-nearest neighbors (KNN), decision tree (DT), random forest (RF), and deep learning (DL) (including deep neural networks [DNN] architectures) approaches. It offers a thorough synopsis and conclusion that neural networks have traditionally been the most widely used ML model in GWQ modelling. India, China, and the United States are global leaders in groundwater modelling, benefiting from extensive historical data. The most widely modelled elements are nitrate and heavy metal pollution, which are present in about half of the studies. Despite significant progress, several research gaps remain, particularly in the modelling of lesser-explored water quality parameters and in the integration of advanced ML techniques. Emerging approaches such as physics-informed machine learning (PIML), graph neural networks (GNNs), transformer-based architectures, and large language models (LLMs) show considerable potential for improving prediction accuracy and handling complex environmental datasets. These advancements may enable more robust and integrated GWQ management frameworks in future studies.
Pollution of groundwater by heavy metals poses a serious health hazard to human beings. This study evaluates the noncarcinogenic and carcinogenic risks of the following five metals: lead (Pb), chromium (Cr (VI)), cadmium (Cd), copper (Cu), and iron (Fe) in groundwater at 30 stations in the Bellandur industrial area of Bengaluru, India. The concentrations of groundwater metals were determined at these 30 stations, and the hazard quotient (HQ), hazard index (HI), and lifetime cancer risk (LTCR) were calculated according to USEPA standards. Probabilistic risk was measured using Monte Carlo simulation. Reductions of 20% and 50% were assessed by scenario modeling. The metal analysis shows that the exceedance percentages with respect to Pb, Cr (VI), Cd, and Fe are 33.33 53.33, 53.33, and 63.33, both with respect to Bureau of Indian Standards (BIS) and World Health Organization (WHO) as they both use the same permissible limits, while Cu exceeds the BIS Limits by 36.67%. However, WHO has not placed any minimum limits for Cu and only an upper limit of 2 mg/L, as per which none of the stations exceed the limits. Results show widespread exceedances, especially among children, where Pb is the dominant contributor to noncarcinogenic risk, while Cr (VI) is the sole driver of carcinogenic risk. HI exceeded 1 at 20 stations for adults and 21 stations for children. LTCR exceeded 1 × 10-4 at 19 adult stations and 16 child stations. The marginal stations that showed compliance only under 50% reduction were illustrated in the scenario model. Pb, Cr (VI), and Cd are identified as the chief drivers of health risks in the region. Targeted remediation and policy interventions are urgently needed. Probabilistic modeling and scenario analysis offer robust tools for groundwater risk governance.
In karst landscapes, trough valleys are key negative topographic units that act as both natural groundwater catchments and preferential pathways for contaminant transport. Their well-developed vertical karst features, such as sinkholes and fissures, facilitate the rapid entry of surface contaminants into groundwater systems, exerting significant control over flow paths, hydrochemical evolution, and pollutant fate. However, a systematic understanding of how this unique "catchment-conduit" functionality governs the spatial differentiation of groundwater chemistry, and how anthropogenic pollutants quantitatively interact with and evolve within this natural karst background, remains elusive. This study investigates an underground river system in a typical karst trough valley of northern Guizhou. Using hydrogeological surveys, tracer tests, and hydrochemical sampling, we employed integrated approaches including Piper diagrams, Gibbs diagrams, ion ratios, correlation analysis, and principal component analysis (PCA) to systematically characterize groundwater chemistry, spatial evolution patterns, and controlling factors. A mineral dissolution equilibrium model was further applied to quantify the contribution of anthropogenic nitric and sulfuric acids to carbonate dissolution. The results indicate that: (1) Groundwater is predominantly of the HCO3-Ca·Mg type, primarily controlled by carbonate dissolution, which constitutes the regional hydrochemical background. However, a distinct spatial pattern of "significant pollution input-self-purification recovery-localized recontamination" is observed along the subsurface flow path, a variability driven largely by anthropogenic activities. (2) PCA quantitatively identified three principal controlling factors. The anthropogenic pollution factor (PC1), represented by Na+, NH4 +, K+, and Cl-, exhibits a contribution rate of 44.718%, surpassing that of the natural dissolution factor (PC2, 17.578%). This confirms that anthropogenic activities have become the primary driver of spatial hydrochemical variations. (3) The mineral dissolution equilibrium model estimated that anthropogenic nitric and sulfuric acids contribute an average of 21.0% to carbonate dissolution, demonstrating that human activities significantly accelerate karst dissolution through the input of acidic substances. This study quantifies anthropogenic acid contribution (~21%, upper limit) to carbonate dissolution and reveals a spatial pattern of pollution input, self-purification, and recontamination driven by the valley's "catchment conduit" functionality, providing a scientific basis for groundwater protection in similar karst settings. These findings provide a mechanism-based scientific basis for groundwater protection and pollution control in similar geomorphic settings.
This study presents a systematic and reproducible methodology for developing synthetic wastewater that mimics the bulk physicochemical characteristics of palm oil mill final effluent (SWM-POMEFE) at laboratory scale. The framework was established through four sequential phases: (1) physicochemical characterization of real POMEFE (R-POMEFE), (2) dose-response analysis of selected media, (3) iterative formulation of SWM-POMEFE, and (4) stability and statistical validation. R-POMEFE was characterized across 10 sampling events to establish baseline conditions for key parameters. Dose-response analyses of glucose, lignin, surfactant, unrefined red palm oil, and NH4Cl were conducted to reproduce COD, BOD5, color, O&G, and NH3-N contributions. Three progressively refined formulations were developed through iterative adjustments, demonstrating strong agreement between experimental results (Exp-R) and calibrated predictions (Cal-P), with deviations ranging from 0.3% to 6.3%. Statistical similarity analysis of the final SWM-POMEFE formulation showed that NH3-N, O&G, color, and turbidity closely matched the distribution of the R-POMEFE dataset, with mean values falling within the 95% confidence interval, interquartile range, and ±10% tolerance band. These parameters also exhibited very small standardized deviations (|z| ≤ 0.2), indicating negligible differences relative to the natural variability of the field measurements. TSS met all criteria except the interquartile range (z = 0.76). In contrast, COD and BOD5 fell outside the central distribution metrics but remained within the observed field range (z = 1.03 and 1.52, respectively). Although formal equivalence testing using the two one-sided tests procedure did not demonstrate strict equivalence, this was attributed to the large natural variability of the field measurements. Stability assessments further confirmed the robustness of the formulation, with < 5% variation during the 5-day short-term test and only minor reductions after 3-month storage, indicating that SWM-POMEFE provides a stable physicochemical surrogate for controlled laboratory studies.
Groundwater is the primary freshwater source in semiarid regions, yet intensive overextraction and water quality deterioration increasingly threaten agricultural production and ecological sustainability. The Angulinao Endorheic Basin (AEB) in northern China has experienced rapid irrigation expansion, wetland degradation, and severe lake desiccation over recent decades. In this study, we integrated long-term climate and hydrology records, land-use dynamics, hydrochemical data, and regional groundwater resource balance calculations to quantify groundwater availability, quality evolution, and supply-demand relationships. Results indicate that mean annual groundwater recharge is approximately 1.04 × 108 m3, whereas sustainable groundwater exploitation is limited to 4.16 × 107 m3 year-1. Projections suggest that by 2030, groundwater demand will exceed sustainable supply by 2.86 × 106 m3 year-1 in normal hydrological years and up to 9.83 × 106 m3 year-1 in dry years. Groundwater quality exhibits pronounced spatial heterogeneity: 55% of irrigated areas exceed nitrate (NO3 -) standards and 17% exceed fluoride (F-) thresholds. Discharge zones are characterized by elevated total dissolved solids (TDS), NO3 -, Fe, and Mn, reflecting combined geological controls and anthropogenic inputs, whereas elevated F- concentrations are primarily associated with strong evaporation processes. These findings reveal critical risks associated with continued groundwater overextraction and quality degradation and emphasize the urgent need for integrated groundwater management strategies to ensure long-term water security and ecosystem resilience in semiarid endorheic basins.
This 2-year pilot-scale study aimed to remediate chlorinated volatile organic compounds (cVOCs) in a low-permeability aquifer, with trichloroethylene (TCE) and 1,2-dichloroethane (1,2-DCA) as the target contaminants. To overcome the limitations of conventional amendment delivery methods, a high-pressure waterjet injection technique was applied to create fine circular slots within the aquifer, enabling the directional delivery of electron donor substrates and improving their distribution in low-permeability zones. The efficiency of substrate transport and reaction was evaluated using time-lapse cross-hole electrical resistivity tomography (TL-CHERT) and groundwater monitoring data, including total organic carbon (TOC), chloride, and metabolic by-products such as ethene and methane. Prior to injection, the aquifer at the site was under aerobic conditions with low organic carbon content, indicating insufficient electron donor availability and unfavorable conditions for reductive dechlorination. After waterjet injection, geochemical results indicated that reducing conditions were rapidly established, accompanied by the gradual depletion of dissolved electron acceptors. As anaerobic conditions developed, concentrations of TCE and 1,2-DCA decreased to below Taiwan's Groundwater Pollution Control Standards (0.05 mg/L) within 1 month, with no rebound observed during the subsequent monitoring period. In addition, the formation and subsequent transformation of intermediate dechlorination products, along with the detection of ethene and methane, further confirmed the ongoing reductive dechlorination process. Overall, these results demonstrate that waterjet injection is a robust and practical approach for delivering amendments in heterogeneous, low-permeability formations.
Graphene-supported titania (TiO2) nanopowder is widely studied for photocatalytic contaminant degradation; however, the effect of graphene on tuning the internal mesoporous network of TiO2 remains underexplored. This study provides a deeper understanding of the enhanced photocatalytic performance of graphene-supported titania by uncovering the architectural modifications in the mesoporous structure of the original nanopowder. Specifically, exfoliated-reduced graphene oxide (Ex-rGO) was synthesized using a physicochemical method. The Ex-rGO nanosheets, in varying concentrations (0.1%, 0.2%, and 0.4%), were added to the titania precursor as hard templates for the growth of TiO2 nanoparticles. The resulting graphene-supported titania nanocomposites, TiO2/Ex-rGO (0.1%-0.4%), were characterized to evaluate their physical, chemical, crystallographic, and optical properties. The photocatalytic performance of the reference TiO2, TiO2/Ex-rGO (0.1%), TiO2/Ex-rGO (0.2%), and TiO2/Ex-rGO (0.4%), measured by determining degradation of methylene blue (MB) dye, was found to be 72.62%, 79.58%, 94.63%, and 82%, respectively, in 2 h of UV exposure. Although TiO2/Ex-rGO (0.4%) exhibited the lowest electron-hole recombination among all synthesized titania nanopowders, the highest photocatalytic degradation rate was achieved with an optimal Ex-rGO concentration of 0.2% in the TiO2 nanoparticles. This unexpected response was attributed to the rapid diffusion of dye molecules into the internal porous networks, facilitated by the relatively large average pore diameter of 13.78 nm and the widely open porous structure observed in TiO2/Ex-rGO (0.2%). This study, for the first time, revealed that incorporating graphene nanosheets within the titania matrix can favorably tailor the mesoporous architecture of the parent nanopowder, enhancing pore accessibility and thereby boosting photocatalytic performance.
A nanocomposite of MWCNTs (40%) and polyaniline macromolecule (60%) was prepared and characterized. The doxycycline antibiotic was removed from the water using this nanocomposite. At 60 mg/L of doxycycline, 1.0 g/L of the antibiotic, 60 min of contact time, and 298 K temperature, the adsorbent had an adsorption capacity of 45 mg/g. The Henry, Langmuir, Freundlich, D-R, and Temkin models were used. The best fitting model was the Langmuir model based on statistical data. According to the thermodynamic data, the adsorption occurred spontaneously and thermodynamically. A combination of external mass transfer processes and intraparticle diffusion, along with external mass transfer, led to the adsorption. The supramolecular mechanism demonstrated the adsorption of the antibiotic doxycycline through π-π interactions, hydrophobic interactions, and hydrogen bonding. The adsorbent showed good removal at natural pH 8 and is cost-effective. This method is useful in removing doxycycline from water.
In this study, a total of 103 groundwater samples were collected from four subareas in the Xingtai Se-enriched area, central North China to explore controlling factors of hydrochemical components and suitability for drinking and irrigation purposes. The results indicate that the groundwater exhibits neutral to slightly alkaline properties. Piper diagram classifies the major groundwater types as SO4-Ca and Cl-Ca·Mg. Integrated hydrochemical analyses (Gibbs and Gaillardet diagrams, ionic ratios, Chloro-Alkali Index, and Saturation Index) together with statistical approaches (Pearson's correlation analysis and principal component analysis) reveal that hydrogeochemical evolution is governed by water-rock interactions (dissolution of calcite, dolomite, fluorite, gypsum, pyrite, and halite), cation exchange, and anthropogenic influences. Nonpoint sources (fertilizers, manure, and sewage) contribute to the elevations of NO3 - and Cl- concentrations. Water Quality Index (WQI) assessments indicate 80.58% of samples are suitable for drinking. SO4 2- and NO3 -are identified as key triggers of water quality deterioration, which are linked to carbonate rock dissolution, cation exchange, sulfur-containing minerals dissolution (gypsum and pyrite), and anthropogenic pollution (fertilizers and sewage). USSL classifications indicate 44.67% of samples are suitable for irrigation, contrasting with 1.94% deemed unsuitable, whereas Wilcox diagram categorizations show 43.68% as excellent-to-good and 2.91% as unsuitable. The findings can provide scientific guidance for rationally utilizing the valuable local Se-enriched groundwater resource on the premise of balancing exploitation with protection against hydrogeochemical and anthropogenic contamination.
Temperature is widely recognized as a critical limiting factor for the stable operation of anaerobic ammonium oxidation (Anammox) systems, with low-temperature environments typically imposing severe inhibition on the metabolic activity of functional anaerobic ammonium oxidation bacteria (AnAOB) and the overall nitrogen removal performance. While Anammox has emerged as a promising low-carbon nitrogen removal technology for wastewater treatment, its full-scale application in temperate and cold regions is largely constrained by low-temperature suppression, and the mitigation potential of biogas coupling in this context remains poorly elucidated. To address this knowledge gap, this study systematically investigated the alleviation effect of intermittent biogas injection on low-temperature inhibition of Anammox systems under a gradient of temperature conditions (30°C, 25°C, and 20°C) using upflow anaerobic sludge blanket (UASB) reactors. Results demonstrated that the experimental reactor with intermittent biogas injection exhibited significantly superior nitrogen removal efficiency and long-term operational stability compared with the non-biogas control group at each tested temperature. Specifically, the total nitrogen removal efficiency of the biogas-amended reactor remained as high as 74.83% at 20°C, which was markedly higher than that of the control group. Mechanistic investigations revealed that intermittent biogas injection optimized the physicochemical characteristics of Anammox granular sludge, slowed the attenuation of specific Anammox activity (SAA), and enriched the dominant AnAOB genus Candidatus_Kuenenia via three synergistic pathways: continuous inorganic carbon supply from CO2 dissolution, pH buffering capacity, and shear force regulation. Collectively, these effects significantly enhanced the low-temperature resistance and operational resilience of the Anammox system. This work provides critical mechanistic insights and technical support for the stable operation of Anammox-based processes in low-temperature regions, advancing the practical application of low-carbon nitrogen removal technologies.
Groundwater salinization poses a critical challenge to water security in arid and semiarid regions worldwide. To elucidate the processes governing salinity evolution and support sustainable management, this study integrates hydrogeochemical, isotopic, and solute transport modeling analyses based on 50 groundwater samples collected from 34 wells in the Wadi Aday Basin, Oman. Total dissolved solids (TDS) range from 585 to 1926 mg/L, with chloride concentrations reaching up to 886 mg/L. The primary source of salinity is attributed to the dissolution of evaporitic sedimentary units, with secondary contributions from evaporation, soil salt leaching, and limited natural recharge. Stable isotope data differentiate deeper, isotopically depleted groundwater formed under past humid climatic conditions from shallower wells influenced by episodic surface recharge, leakage from water-supply networks, and evaporative enrichment. Most wells exceed Omani drinking water standards for TDS, Mg, and SO4, although minor element ratios and vertical EC profiles indicate no seawater intrusion. Groundwater flow and solute transport models developed using MODFLOW-USG and MT3DMS, respectively, were calibrated successfully. Simulations identify an area downstream of a proposed dam as an optimal site for future development owing to higher hydraulic conductivity and enhanced recharge potential, which would help dilute salinity and stabilize water quality. Modeling shows that under "no change" (Sc1), chloride concentrations increased by approximately 11 mg/L, whereas under "construction of a new dam with increased groundwater recharge" (Sc2) concentrations remained relatively stable and were approximately 10-11 mg/L lower than Sc1 by the end of the simulation. Recommended management options include implementing managed aquifer recharge via dam construction, optimizing well design to isolate high-salinity zones, adopting blending strategies, and deepening wells to access fresher groundwater.
Wastewater treatment plants (WWTPs) are facing dual pressures of increasing influent variability and the urgent need for decarbonization. Aeration processes, accounting for 50%-70% of total energy consumption, represent the most critical target for optimization. Specifically, transitioning from conventional empirical methods to AI-CFD integrated frameworks can quantitatively reduce aeration energy consumption from 0.30 to 0.70 kWh/m3 down to 0.15-0.25 kWh/m3. This review provides a comprehensive analysis of the evolution from classical hydrodynamic assessments to advanced computational fluid dynamics (CFD) and artificial intelligence (AI) integrated frameworks, identifying the multiphase Euler-Euler approach coupled with population balance models (PBM) as the most suitable framework for capturing complex WWTP hydrodynamics. Unlike conventional reviews, this study critically evaluates the numerical robustness of turbulence closures, highlighting how advanced formulations such as shear stress transport (SST) k-ω can enhance predictive reliability in shear-dominated and rotational flow regions when appropriately validated against experimental data (typically yielding R2 > 0.90 and RMSE < 10%). Furthermore, the role of population balance modeling (PBM) in capturing complex bubble dynamics-such as coalescence and breakup-is analyzed as a prerequisite for accurate oxygen transfer efficiency (OTE) estimations. A significant focus is placed on the "scale-up" challenge, identifying the mathematical discrepancies between pilot-scale validations and full-scale plant performance. To bridge these gaps, the review explores emerging approaches such as physics-informed neural networks (PINNs) and digital twins. Specifically, AI-driven surrogate models drastically reduce computational times to enable real-time control, whereas PINNs ensure predictions remain physically robust even with sparse operational data. These integrations offer substantial potential for reducing energy use and associated carbon emissions when integrated with renewable energy systems. By synthesizing validated physical models with AI-driven surrogates, this review demonstrates that actionable CFD strategies can yield absolute aeration energy reductions of 15%-30% while paving the way for carbon-conscious wastewater treatment.