Groundwater is the major source of fresh water,and it performs a crucial role in maintaining ecosystems and adapting humans to climate variation.Due to excessive reliance on groundwater in some regions,the amount of g...Groundwater is the major source of fresh water,and it performs a crucial role in maintaining ecosystems and adapting humans to climate variation.Due to excessive reliance on groundwater in some regions,the amount of groundwater being consumed is higher than the recharge,which leads to a durative decline of groundwater level.This study analyzed the spatiotemporal variability in groundwater storage(GWS)in China.And the possible drivers of observed GWS changes were also identified.GWS level displayed large regional disparities with higher reserves in the Yangtze River Basin and Songhua River Basin.Temporally,GWS level showed decreasing trends in the North China Plain region,Yellow River Basin,Inner Mongolia Plateau and Junggar Basin.And,GWS showed a significant increase in the Tibetan Plateau and Songhua River Basin.Without considering the impact of human activities,groundwater reserves are also showing a decreasing trend in future climate scenarios in most of the 15 zones.Contribution analysis of driving forces on the basis of the percentages of standardized coefficient(r)suggested that the variations of GWS were largely controlled by anthropogenic activities with the contribution proportions of 35.43%-73.37%.And the contribution proportions of natural drivers accounted for 26.63%-64.62%,with the key factors of precipitation,temperature and vegetation cover.The results would help to formulate sustainable strategies for managing groundwater resource.展开更多
Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base ...Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base in China with significant strategic importance,has undergone intensive coal mining activities that have substantially disrupted regional groundwater circulation.This study integrated data from the Gravity Recovery and Climate Experiment Satellite(GRACE)and Famine Early Warning Systems Network(FEWS NET)Land Data Assimilation System(FLDAS)models,combined with weighted downscaling methodology and water balance principles,to reconstruct high-resolution(0.01°)terrestrial water storage(TWS)and GWS changes in the Ordos Mining Region,China from April 2002 to December 2021.The accuracy of GWS variations were validated through pumping test measurements.Subsequently,Geodetector analysis was implemented to quantify the contributions of natural and anthropogenic factors to groundwater storage dynamics.Key findings include:1)TWS in the study area showed a fluctuating but overall decreasing trend,with a total reduction of 8901.11 mm during study period.The most significant annual decrease occurred in 2021,reaching 1696.77 mm.2)GWS exhibited an accelerated decline,with an average annual change rate of 44.35 mm/yr,totaling a decrease of 887.05 mm.The lowest annual groundwater storage level was recorded in 2020,reaching 185.69 mm.3)Precipitation(PRE)contributed the most to GWS variation(q=0.52),followed by coal mining water consumption(MWS)(q=0.41).The interaction between PRE and MWS exhibited a nonlinear enhancement effect on GWS changes(0.54).The synergistic effect of natural hydrological factors has a great influence on the change of GWS,but coal mining water consumption will continue to reduce GWS.These findings provide critical references for the management and regulation of groundwater resource in mining regions.展开更多
Water scarcity in Khuzestan Province,Iran,has attracted growing concerns despite the region's abundant water resources.The province predominantly relies on surface water,prompting an assessment of groundwater'...Water scarcity in Khuzestan Province,Iran,has attracted growing concerns despite the region's abundant water resources.The province predominantly relies on surface water,prompting an assessment of groundwater's potential to supplement water supplies during surface water shortages.This study assesses the province's groundwater availability and quality under increased exploitation conditions.Between 2008 and 2018,data on groundwater quantity and quality were collected from 204 exploration wells and 70 piezometric wells across 19 aquifers.The analysis revealed that 53%of aquifers in the eastern and northeastern regions experienced declining groundwater levels.Hydrochemical assessments indicated low concentrations of major ions in the northeastern,while high levels were observed from the central region towards the southeast.These variations were attributed to agricultural and industrial activities,seawater intrusion,and the influences of evaporation and geological factors.The dominant hydrochemical facies identified were of the Ca-Cl type.Water quality classification showed that 48%of groundwater samples fell within the C4S4-C4S1 category,primarily in the western,central,and southern regions,while 27%were classified as C3S2,C3S1,and 25%as C2S1,mainly in the northern and eastern regions.The Irrigation WWater Quality(IWQ)index indicated that many samples were suitable for irrigation.Additionally,the analysis potable groundwater was primarily found in the northern,northeastern,and eastern aquifers,with quality declining toward the south.The study highlights that certain aquifers in the northern and eastern regions offer greater potential for sustainable groundwater exploitation during water shortages.These findings provide valuable insights for on how to implement effective land and water management strategies to mitigate future water crises.展开更多
This study advances the DRASTIC groundwater vulnerability assessment framework by integrating a multi-hazard groundwater index(MHGI)to account for the dynamic impacts of diverse anthropogenic activities and natural fa...This study advances the DRASTIC groundwater vulnerability assessment framework by integrating a multi-hazard groundwater index(MHGI)to account for the dynamic impacts of diverse anthropogenic activities and natural factors on both groundwater quality and quantity.Incorporating factors such as population growth,agricultural practices,and groundwater extraction enhances the framework’s ability to capture multi-dimensional,spatiotemporal changes in groundwater vulnerability.Additional improvements include refined weighting and rating scales for thematic layers based on available observational data,and the inclusion of distributed recharge.We demonstrate the practical utility of this dynamic DRASTIC-based framework through its application to the agro-urban regions of the Irrigated Indus Basin,a major groundwater-dependent agricultural area in South Asia.Results indicate that between 2005 and 2020,54%of the study area became highly vulnerable to pollution.The MHGI revealed a 13%decline in potential groundwater storage and a 25%increase in groundwater-stressed zones,driven primarily by population growth and intensive agriculture.Groundwater vulnerability based on both groundwater quality and quantity dimensions showed a 19%decline in areas of low to very low vulnerability and a 6%reduction in medium vulnerability zones by 2020.Sensitivity analyses indicated that groundwater vulnerability in the region is most influenced by groundwater recharge(42%)and renewable groundwater stress(38%).Validation with in-situ data yielded area under the curve values of 0.71 for groundwater quality vulnerability and 0.63 for MHGI.The framework provides valuable insights to guide sustainable groundwater management,safeguarding both environmental integrity and human well-being.展开更多
The diversity and discontinuity of plant communities in the oasis–desert ecotone are largely shaped by variations in groundwater depth,yet the relationships between spatial distribution patterns and ecological niches...The diversity and discontinuity of plant communities in the oasis–desert ecotone are largely shaped by variations in groundwater depth,yet the relationships between spatial distribution patterns and ecological niches at a regional scale remain insufficiently understood.This study examined the oasis–desert ecotone in Qira County located in the Tarim Basin of China to investigate the spatial distribution of plant communities and groundwater depth as well as their relationships using an integrated approach that combined remote sensing techniques,field monitoring,and numerical modeling.The results showed that vegetation distribution exhibits marked spatial heterogeneity,with coverage ranked as follows:Tamarix ramosissima>Phragmites australis>Populus euphratica>Alhagi sparsifolia.Numerical simulations indicated that groundwater depths range from 2.00 to 65.00 m below the surface,with the system currently in equilibrium,sustaining an average annual recharge of 1.06×10^(8) m^(3) and an average annual discharge of 1.01×10^(8) m^(3).Groundwater depth strongly influences vegetation composition and structure:Phragmites australis dominates at average groundwater depth of 5.83 m,followed by Populus euphratica at average groundwater depth of 7.05 m.As groundwater depth increases,the community is initially predominated by Tamarix ramosissima(average groundwater depth of 8.35 m),then becomes a mixture of Tamarix ramosissima,Populus euphratica,and Karelinia caspia(average groundwater depth of 10.50 m),and finally transitions to Alhagi sparsifolia(average groundwater depth of 14.30 m).These findings highlight groundwater-dependent ecological thresholds that govern plant community composition and provide a scientific basis for biodiversity conservation,ecosystem stability,and vegetation restoration in the arid oasis–desert ecotone.展开更多
Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in th...Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.展开更多
Groundwater and surface water contamination by PTE(Potentially Toxic Elements)was assessed in Ruashi and Annexe municipalities of Lubumbashi city.Analyses of seventy water samples collected from six drilled wells,eigh...Groundwater and surface water contamination by PTE(Potentially Toxic Elements)was assessed in Ruashi and Annexe municipalities of Lubumbashi city.Analyses of seventy water samples collected from six drilled wells,eight spade-sunk wells,one river and one spring in both municipalities in 2017 and 2018 were carried out by ICP-SF-MS(Inductively Coupled Plasma-Sector Field Mass Spectrometry).Twenty PTEs including aluminum,arsenic,barium,bismuth,cadmium,cesium,chromium,cobalt,copper,iron,lead,manganese,molybdenum,nickel,strontium,thallium,tungsten,uranium,vanadium and zinc were detected at various concentrations in each one of the samples.Many samples had concentrations and mean concentrations of PTEs,such as aluminum,cadmium,copper,iron,lead,manganese,nickel and zinc,higher than the respective acceptable limits set for drinking water by the EU(European Union),the USEPA(United States Environmental Protection Agency),and the WHO(World Health Organization)standards.Most PTEs being deleterious to human health even at very low concentrations,people who use the groundwater and surface water to meet their water needs in both Ruashi and Annexe municipalities are at risk.展开更多
Located in northern China,the Hetao Plain is an important agro-economic zone and population centre.The deterioration of local groundwater quality has had a serious impact on human health and economic development.Nowad...Located in northern China,the Hetao Plain is an important agro-economic zone and population centre.The deterioration of local groundwater quality has had a serious impact on human health and economic development.Nowadays,the groundwater vulnerability assessment(GVA)has become an essential task to identify the current status and development trend of groundwater quality.In this study,the Convolutional Neural Network(CNN)and Long Short-Term Memory(LSTM)models are integrated to realize the spatio-temporal prediction of regional groundwater vulnerability by introducing the Self-attention mechanism.The study firstly builds the CNN-LSTM modelwith self-attention(SA)mechanism and evaluates the prediction accuracy of the model for groundwater vulnerability compared to other common machine learning models such as Support Vector Machine(SVM),Random Forest(RF),and Extreme Gradient Boosting(XGBoost).The results indicate that the CNNLSTM model outperforms thesemodels,demonstrating its significance in groundwater vulnerability assessment.It can be posited that the predictions indicate an increased risk of groundwater vulnerability in the study area over the coming years.This increase can be attributed to the synergistic impact of global climate anomalies and intensified local human activities.Moreover,the overall groundwater vulnerability risk in the entire region has increased,evident fromboth the notably high value and standard deviation.This suggests that the spatial variability of groundwater vulnerability in the area is expected to expand in the future due to the sustained progression of climate change and human activities.The model can be optimized for diverse applications across regional environmental assessment,pollution prediction,and risk statistics.This study holds particular significance for ecological protection and groundwater resource management.展开更多
Addressing the global challenge of uranium(U)-contaminated groundwater requires innovative bioremediation strategies.This study investigates Desulfovibrio desulfuricans,a neutrophilic and mesophilic sulfate-reducing b...Addressing the global challenge of uranium(U)-contaminated groundwater requires innovative bioremediation strategies.This study investigates Desulfovibrio desulfuricans,a neutrophilic and mesophilic sulfate-reducing bacteria(SRB)strain optimized for lowtemperature(15℃)and acidic(initial pH 4)conditions,to validate its bioaugmentation potential for uranium decontamination in groundwater.Our research aimed to assess its efficacy in treating U-contaminated groundwater and elucidate the optimal growth conditions for this strain in acidic and sulfate-enriched environments.We found that D.desulfuricans was phylogenetically distinct from the native microbial community in acidic Ucontaminated groundwater,while it maintained appreciable activity in sulfate reduction under contaminated groundwater conditions after accumulation.Acid-tolerant D.desulfuricans removed 75.87%of uranium and 30.64%of sulfate from acidic U-contaminated groundwater(pH 4.0)at 15℃ within 14 days.Furthermore,we explored the optimal sulfate concentration for bacterial growth,which was found to be 2000 mg/L,and an elevated Fe^(2+) concentration from 100 to 1000 mg/L increasingly stimulated sulfate-reducing activity.These findings provide a novel insight into the application of neutrophilic and mesophilic SRB in bioremediation of acidic and low-temperature groundwater after accumulation and underscore the feasibility of bioremediation by using exogenously pure SRB.展开更多
Coking industry is a potential source of heavy metals(HMs)pollution.However,its impacts to the groundwater of surrounding residential areas have not been well understood.This study investigated the pollution character...Coking industry is a potential source of heavy metals(HMs)pollution.However,its impacts to the groundwater of surrounding residential areas have not been well understood.This study investigated the pollution characteristics and health risks of HMs in groundwater nearby a typical coking plant.Nine HMs including Fe,Zn,Mo,As,Cu,Ni,Cr,Pb and Cd were analyzed.The average concentration of total HMswas higher in the nearby area(244.27μg/L)than that of remote area away the coking plant(89.15μg/L).The spatial distribution of pollution indices including heavy metal pollution index(HPI),Nemerow index(NI)and contamination degree(CD),all demonstrated higher values at the nearby residential areas,suggesting coking activity could significantly impact the HMs distribution characteristics.Four sources of HMs were identified by Positive Matrix Factorization(PMF)model,which indicated coal washing and coking emission were the dominant sources,accounted for 40.4%,and 31.0%,respectively.Oral ingestionwas found to be the dominant exposure pathway with higher exposure dose to children than adults.Hazard quotient(HQ)values were below 1.0,suggesting negligible non-carcinogenic health risks,while potential carcinogenic risks were from Pb and Ni with cancer risk(CR)values>10−6.Monte Carlo simulation matched well with the calculated results with HMs concentrations to be the most sensitive parameters.This study provides insights into understanding how the industrial coking activities can impact the HMs pollution characteristics in groundwater,thus facilitating the implement of HMs regulation in coking industries.展开更多
Rapid screening of inorganic arsenic(iAs)in groundwater used for drinking by hundreds of millions of mostly rural residents worldwide is crucial for health protection.Most commercial field test kits are based on the G...Rapid screening of inorganic arsenic(iAs)in groundwater used for drinking by hundreds of millions of mostly rural residents worldwide is crucial for health protection.Most commercial field test kits are based on the Gutzeit reaction that uses mercury-based reagents for color development,an environmental concern that increasingly limits its utilization.This study further improves the Molybdenum Blue(MB)colorimetric method to allow for faster screening with more stable reagents.More importantly,a portable three-channel colorimeter is developed for screening iAs relative to the WHO drinking water guideline value(10μg/L).Adding the reducing reagents in sequence not only prolongs the storage time to>7 days,but also accelerates the color development time to 6 min in conjunction with lowering the H_(2)SO_(4) concentration in chromogenic reagents.The optimal pH ranges from 1.2 to 1.3 and is achieved by acidifying groundwater to 1%(V/V)HCl.With detection limits of 3.7μg/L for inorganic arsenate(iAs(V))and 3.8μg/L for inorganic arsenite(iAs(Ⅲ)),testing groundwater with-10μg/L of As has a precision<20%.The method works well for a range of phosphate concentrations of 48-950μg/L(0.5-10μmol/L).Concentrations of total_iAs(6-300μg/L),iAs(V)(6-230μg/L)and iAs(Ⅲ)(0-170μg/L)for 14 groundwater samples from Yinchuan Plain,Pearl River Delta,and Jianghan Plain,are in excellent agreements(linear regression slope:0.969-1.029)with the benchmark methods.The improved chemistry here lays the foundation for the MB colorimetric method to become a commercially viable screening tool,with further engineering and design improvement of the colorimeter.展开更多
Polybromodiphenyl ethers(PBDEs),the widely used flame retardants,are common contaminants in surface soils at e-waste recycling sites.The association of PBDEs with soil colloids has been observed,indicating the potenti...Polybromodiphenyl ethers(PBDEs),the widely used flame retardants,are common contaminants in surface soils at e-waste recycling sites.The association of PBDEs with soil colloids has been observed,indicating the potential risk to groundwater due to colloid-facilitated transport.However,the extent to which soil colloidsmay enhance the spreading of PBDEs in groundwater is largely unknown.Herein,we report the co-transport of decabromodiphenyl ester(BDE-209)and soil colloids in saturated porous media.The colloids released froma soil sample collected at an e-waste recycling site in Tianjin,China,contain high concentration of PBDEs,with BDE-209 being the most abundant conger(320±30 mg/kg).The colloids exhibit relatively high mobility in saturated sand columns,under conditions commonly observed in groundwater environments.Notably,under all the tested conditions(i.e.,varying flow velocity,pH,ionic species and ionic strength),the mass of eluted BDE-209 correlates linearly with that of eluted soil colloids,even though the mobility of the colloids varies markedly depending on the specific hydrodynamic and solution chemistry conditions involved.Additionally,the mass of BDE-209 retained in the columns also correlates strongly with themass of retained colloids.Apparently,the PBDEs remain bound to soil colloids during transport in porous media.Findings in this study indicate that soil colloidsmay significantly promote the transport of PBDEs in groundwater by serving as an effective carrier.This might be the reason why the highly insoluble and adsorptive PBDEs are found in groundwater at some PBDE-contaminated sites.展开更多
Arsenic-contaminated groundwater is widely used in agriculture.To meet the increasing demand for safe water in agriculture,an efficient and cost-effective method for As removal from groundwater is urgently needed.We h...Arsenic-contaminated groundwater is widely used in agriculture.To meet the increasing demand for safe water in agriculture,an efficient and cost-effective method for As removal from groundwater is urgently needed.We hypothesized that Fe(oxyhydr)oxide(FeOOH)minerals precipitated in situ from indigenous Fe in groundwater may immobilize As,providing a solution for safely using As-contaminated groundwater in irrigation.To confirm this hypothesis and identify the controlling mechanisms,we comprehensively evaluated the transport,speciation changes,and immobilization of As and Fe in agricultural canals irrigated using As-contaminated groundwater.The efficiently removed As and Fe in the canals accumulated in shallow sediment rather than subsurface sediment.Linear combination fitting(LCF)analysis of X-ray absorption near edge spectroscopy(XANES)indicated that As(Ⅴ)was the dominant As species,followed by As(Ⅲ),and therewas no FeAsO_(4) precipitate.Sequential extraction revealed higher contents of amorphous FeOOH and associated As in shallower sediment than in the subsurface layer.Stoichiometric molar ratio calculations,SEM-EDS,FTIR,and fluorescence spectroscopy collectively demonstrated that the microbial reductive dissolution of amorphous FeOOH proceeded via reactive dissolved organic matter(DOM)consumption in subsurface anoxic porewater environment facilitating high labile As,whereas in surface sediment,the in situ-generated amorphous FeOOH was stable and strongly inhibited As release via adsorption.In summary,groundwater Fe^(2+)can efficiently precipitate in benthic surface sediment as abundant amorphous FeOOH,which immobilizes most of the dissolved As,protecting agricultural soil from contamination.This field research supports the critical roles of the phase and reactivity of in situ-generated FeOOH in As immobilization and provides new insight into the sustainable use of contaminated water.展开更多
Groundwater,surface water and tap water contamination by PTEs(Potentially Toxic Elements)was assessed in Kipushi town and Lupoto locality of Kipushi administrative territory in the Upper-Katanga province,Democratic Re...Groundwater,surface water and tap water contamination by PTEs(Potentially Toxic Elements)was assessed in Kipushi town and Lupoto locality of Kipushi administrative territory in the Upper-Katanga province,Democratic Republic of Congo.A total of fifty four water samples including thirty two samples from drilled water wells,ten samples from spade-sunk water wells,six samples from supplied tap water,four samples from a mine effluent and two samples from a river were collected from both localities in November and December 2017 and in January,February and March 2018.Then the samples were analyzed for their PTE contents by ICP-SF-MS(Inductively Coupled Plasma-Sector Field Mass Spectrometry).Twenty PTEs including aluminum,arsenic,barium,bismuth,cadmium,cesium,chromium,cobalt,copper,iron,lead,manganese,molybdenum,nickel,strontium,thallium,tungsten,uranium,vanadium and zinc were detected at various concentrations in each one of the samples.Many samples had concentrations and mean concentrations of PTE,such as arsenic,aluminum,cadmium,iron,lead,manganese and zinc,higher than the respective acceptable limits set for drinking water by the EU(European Union),the USEPA(United States Environmental Protection Agency),and the WHO(World Health Organization)standards.Most PTEs being deleterious to human health even at very low concentrations,people who use the groundwater,surface water and tap water to meet their water needs in both localities are at risk.展开更多
Groundwater,the world’s largest freshwater supply,is facing increasing strain due to various uses such as agriculture,industry,livestock,and household.This study aims to investigate groundwater prospective zonation i...Groundwater,the world’s largest freshwater supply,is facing increasing strain due to various uses such as agriculture,industry,livestock,and household.This study aims to investigate groundwater prospective zonation in the Bandu Sub-watershed in Purulia,West Bengal,using the AHP model and RS&GIS methodologies.To achieve Goal 6 of the UN-initiated 17 SDGs,it is crucial to determine the spatial distribution of groundwater prospective zones village-by-village,with 1/3 of the regions falling under red alert zones for sustainable development.The 16 most crucial elements affecting groundwater prospective zones(GWPZs)were mapped using AHP,and the final prospective map was obtained through Weighted Overlay analysis.The study identified five different classes within the Sub-watershed as excellent,good,moderate,poor,and very poor.The validation results showed that the approach used to derive GWPZ is reliable,and the results can be applied to future sustainable developments to reduce water shortages through suitable management methods.The research aims to increase the effectiveness of sustainable groundwater zone management,ensuring long-term water management and access.展开更多
Quantifying the spatial and temporal distribution of natural groundwater recharge is essential for effective groundwater modeling and sustainable resource management.This paper presents M-RechargeCal,a user-friendly s...Quantifying the spatial and temporal distribution of natural groundwater recharge is essential for effective groundwater modeling and sustainable resource management.This paper presents M-RechargeCal,a user-friendly software tool developed to estimate natural groundwater recharge using two widely adopted approaches:the Water Balance(WB)method and Water Table Fluctuation(WTF)method.In the WB approach,the catchment area is divided into seven land-use categories,each representing distinct recharge characteristics.The tool includes eighteen different reference Evapotranspiration(ET0)estimation methods,accommodating varying levels of climatic input data availability.Additional required inputs include crop coefficients for major crops and Curve Numbers(CN)for specific land-use types.The WTF approach considers up to three aquifer layers with different specific yields(for unconfined aquifer)or storage coeffi-cient(for confined aquifer).It also takes into account groundwater withdrawal(draft)and lateral water movement within or outside the aquifer system.M-RechargeCal is process-based and does not require cali-bration.Its performance was evaluated using six datasets from humid-subtropical environments,demon-2 strating reliable results(R=0.867,r=0.93,RE=10.6%,PMARE=9.8,ENS=0.93).The model can be applied to defined hydrological or hydrogeological units such as watersheds,aquifers,or catchments,and can be used to assess the impacts of land-use/land-cover changes on hydrological components.However,it has not yet been tested in arid regions.M-RechargeCal provides modelers and planners with a practical,accessible tool for recharge estimation to support groundwater modeling and water resource planning.The software is available free of charge and can be downloaded from the author's institutional website or obtained by contacting the author via email.展开更多
The primary objective of this study is to measure fluoride levels in groundwater samples using machine learning approaches alongside traditional and fuzzy logic models based health risk assessment in the hard rock Arj...The primary objective of this study is to measure fluoride levels in groundwater samples using machine learning approaches alongside traditional and fuzzy logic models based health risk assessment in the hard rock Arjunanadi River basin,South India.Fluoride levels in the study area vary between 0.1 and 3.10 mg/L,with 32 samples exceeding the World Health Organization(WHO)standard of 1.5 mg/L.Hydrogeochemical analyses(Durov and Gibbs)clearly show that the overall water chemistry is primarily influenced by simple dissolution,mixing,and rock-water interactions,indicating that geogenic sources are the predominant contributors to fluoride in the study area.Around 446.5 km^(2)is considered at risk.In predictive analysis,five Machine Learning(ML)models were used,with the AdaBoost model performing better than the other models,achieving 96%accuracy and 4%error rate.The Traditional Health Risk Assessment(THRA)results indicate that 65%of samples pose highly susceptible for dental fluorosis,while 12%of samples pose highly susceptible for skeletal fluorosis in young age groups.The Fuzzy Inference System(FIS)model effectively manages ambiguity and linguistic factors,which are crucial when addressing health risks linked to groundwater fluoride contamination.In this model,input variables include fluoride concentration,individual age,and ingestion rate,while output variables consist of dental caries risk,dental fluorosis,and skeletal fluorosis.The overall results indicate that increased ingestion rates and prolonged exposure to contaminated water make adults and the elderly people vulnerable to dental and skeletal fluorosis,along with very young and young age groups.This study is an essential resource for local authorities,healthcare officials,and communities,aiding in the mitigation of health risks associated with groundwater contamination and enhancing quality of life through improved water management and health risk assessment,aligning with Sustainable Development Goals(SDGs)3 and 6,thereby contributing to a cleaner and healthier society.展开更多
This study systematically investigates natural radioactivity in groundwater from the densely populated eastern Gonghe Basin in Qinghai Province,aiming to reveal its spatial distribution,origins,and potential health ri...This study systematically investigates natural radioactivity in groundwater from the densely populated eastern Gonghe Basin in Qinghai Province,aiming to reveal its spatial distribution,origins,and potential health risks.The characteristics of gross-αand gross-βactivities,as well as the concentrations of nuclide including^(238)U,^(232)Th,and^(226)Ra,have been investigated in groundwater samples from 12 groups encompassing various types such as hot springs and artesian wells across different aquifer systems.Correlation analysis and dose estimation models were applied to preliminary estimate the radiation exposure to local residents and to explore the genesis and hazards of natural radioactivity in groundwater.Results indicate that overall groundwater radioactivity in the Gonghe Basin remains within acceptable limits,with mean gross-αand gross-βactivity concentrations of 0.32 Bq/L and 0.27 Bq/L,respectively.Approximately 83.33%of samples comply with relevant national standards.However,two fault-controlled high-temperature spring samples exhibited gross-αactivity exceeding regulatory limits,with one also showing elevated gross-βactivity surpassing China's Class III groundwater quality standards for radioactivity.Furthermore,single-radionuclideαradioactivity from^(230)Th,^(226)Ra,^(210)Po,and^(232)Th exceeded regulatory thresholds in some samples,suggesting potential long-term health risks.While most samples complied with effective dose limits,four showed^(210)Poαradioactivity exceedances within controllable risk ranges.The findings suggest that groundwater radioactivity in the region is primarily controlled by geological structures,lithology,and hydrothermal conditions,with fault zones and high-temperature environments serving as key factors in radionuclide enrichment.This research provides scientific foundation for the sustainable development of geothermal resources and the prevention of radioactive water contamination.Continuous monitoring of high-radioactivity hot springs and prudent resource utilization are recommended.展开更多
This review critically examines strategies for sustainable groundwater and surface water management,emphasizing their integration to achieve environmental sustainability.The study synthesizes findings from a wide rang...This review critically examines strategies for sustainable groundwater and surface water management,emphasizing their integration to achieve environmental sustainability.The study synthesizes findings from a wide range of research articles,identifying key trends,gaps,and controversies within the field.It highlights the importance of cohesive management approaches that take into account climate change,policy impacts,and methodological advancements.The review aims to provide a structured,analytical discussion that aligns with the thematic focus of integrated water management.By offering original insights and practical recommendations,this review seeks to contribute to the development of more effective and sustainable water management practices.The analysis underscores the necessity of interdisciplinary approaches that integrate hydrological,ecological,and socio-economic factors.Furthermore,the review discusses the role of adaptive management and technological innovations in enhancing the resilience and efficiency of water management systems.The findings suggest that a comprehensive understanding of the interactions between groundwater and surface water is crucial for developing strategies that ensure long-term environmental sustainability.This review concludes with recommendations for future research and policy development,emphasizing the need for adaptive,resilient,and integrated water management strategies that can address the challenges posed by climate change and other environmental pressures.展开更多
Agriculture is a major contributor to the global economy,accounting for approximately 70%of the freshwater use,which cause significant stress on aquifers in intensively irrigated regions.This stress often leads to the...Agriculture is a major contributor to the global economy,accounting for approximately 70%of the freshwater use,which cause significant stress on aquifers in intensively irrigated regions.This stress often leads to the decline in both the quantity and quality of groundwater resources.This study is focused on an intensively irrigated region of Northern India to investigate the sources and mechanism of groundwater recharge using a novel integrated approach combining isotope hydrology,Artificial Neural Network(ANN),and hydrogeochemical models.The study identifies several key sources of groundwater recharge,including natural precipitation,river infiltration,Irrigation Return Flow(IRF),and recharge from canals.Some groundwater samples exhibit mixing from various sources.Groundwater recharge from IRF is found to be isotopically enriched due to evaporation and characterized by high Cl−.Stable isotope modeling of evaporative enrichment in irrigated water helped to differentiate the IRF during various cultivation periods(Kharif and Rabi)and deduce the climatic conditions prevailed during the time of recharge.The model quantified that 29%of the irrigated water is lost due to evaporation during the Kharif period and 20%during the Rabi period,reflecting the seasonal variations in IRF contribution to the groundwater.The ANN model,trained with isotope hydrogeochemical data,effectively captures the complex interrelationships between various recharge sources,providing a robust framework for understanding the groundwater dynamics in the study area.A conceptual model was developed to visualize the spatial and temporal distribution of recharge sources,highlighting how seasonal irrigation practices influence the groundwater.The integration of isotope hydrology with ANN methodologies proved to be effective in elucidating the multiple sources and processes of groundwater recharge,offering insights into the sustainability of aquifer systems in intensively irrigated regions.These findings are critical for developing data-driven groundwater management strategies that can adapt to future challenges,including climate change,shifting land use patterns,and evolving agricultural demands.The results have significant implications for policymakers and water resource managers seeking to ensure sustainable groundwater use in water-scarce regions.展开更多
基金funded by the China Geological Survey Program(No.DD20230075)the key project supported by the National Natural Science Foundation of China(No.U21A20155)。
文摘Groundwater is the major source of fresh water,and it performs a crucial role in maintaining ecosystems and adapting humans to climate variation.Due to excessive reliance on groundwater in some regions,the amount of groundwater being consumed is higher than the recharge,which leads to a durative decline of groundwater level.This study analyzed the spatiotemporal variability in groundwater storage(GWS)in China.And the possible drivers of observed GWS changes were also identified.GWS level displayed large regional disparities with higher reserves in the Yangtze River Basin and Songhua River Basin.Temporally,GWS level showed decreasing trends in the North China Plain region,Yellow River Basin,Inner Mongolia Plateau and Junggar Basin.And,GWS showed a significant increase in the Tibetan Plateau and Songhua River Basin.Without considering the impact of human activities,groundwater reserves are also showing a decreasing trend in future climate scenarios in most of the 15 zones.Contribution analysis of driving forces on the basis of the percentages of standardized coefficient(r)suggested that the variations of GWS were largely controlled by anthropogenic activities with the contribution proportions of 35.43%-73.37%.And the contribution proportions of natural drivers accounted for 26.63%-64.62%,with the key factors of precipitation,temperature and vegetation cover.The results would help to formulate sustainable strategies for managing groundwater resource.
基金Under the National Key R&D Program Key Project(No.2021YFC3201201)National Natural Science Foundation of China(No.52360032)+2 种基金Basic Scientific Research Business Fee Project of Colleges And Universities Directly Under the Inner Mongolia Autonomous Region(No.JBYYWF2022001)Development Plan of Innovation Team of Colleges And Universities in Inner Mongolia Autonomous Region(No.NMGIRT2313)the Innovation Team of‘Grassland Talents’。
文摘Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base in China with significant strategic importance,has undergone intensive coal mining activities that have substantially disrupted regional groundwater circulation.This study integrated data from the Gravity Recovery and Climate Experiment Satellite(GRACE)and Famine Early Warning Systems Network(FEWS NET)Land Data Assimilation System(FLDAS)models,combined with weighted downscaling methodology and water balance principles,to reconstruct high-resolution(0.01°)terrestrial water storage(TWS)and GWS changes in the Ordos Mining Region,China from April 2002 to December 2021.The accuracy of GWS variations were validated through pumping test measurements.Subsequently,Geodetector analysis was implemented to quantify the contributions of natural and anthropogenic factors to groundwater storage dynamics.Key findings include:1)TWS in the study area showed a fluctuating but overall decreasing trend,with a total reduction of 8901.11 mm during study period.The most significant annual decrease occurred in 2021,reaching 1696.77 mm.2)GWS exhibited an accelerated decline,with an average annual change rate of 44.35 mm/yr,totaling a decrease of 887.05 mm.The lowest annual groundwater storage level was recorded in 2020,reaching 185.69 mm.3)Precipitation(PRE)contributed the most to GWS variation(q=0.52),followed by coal mining water consumption(MWS)(q=0.41).The interaction between PRE and MWS exhibited a nonlinear enhancement effect on GWS changes(0.54).The synergistic effect of natural hydrological factors has a great influence on the change of GWS,but coal mining water consumption will continue to reduce GWS.These findings provide critical references for the management and regulation of groundwater resource in mining regions.
文摘Water scarcity in Khuzestan Province,Iran,has attracted growing concerns despite the region's abundant water resources.The province predominantly relies on surface water,prompting an assessment of groundwater's potential to supplement water supplies during surface water shortages.This study assesses the province's groundwater availability and quality under increased exploitation conditions.Between 2008 and 2018,data on groundwater quantity and quality were collected from 204 exploration wells and 70 piezometric wells across 19 aquifers.The analysis revealed that 53%of aquifers in the eastern and northeastern regions experienced declining groundwater levels.Hydrochemical assessments indicated low concentrations of major ions in the northeastern,while high levels were observed from the central region towards the southeast.These variations were attributed to agricultural and industrial activities,seawater intrusion,and the influences of evaporation and geological factors.The dominant hydrochemical facies identified were of the Ca-Cl type.Water quality classification showed that 48%of groundwater samples fell within the C4S4-C4S1 category,primarily in the western,central,and southern regions,while 27%were classified as C3S2,C3S1,and 25%as C2S1,mainly in the northern and eastern regions.The Irrigation WWater Quality(IWQ)index indicated that many samples were suitable for irrigation.Additionally,the analysis potable groundwater was primarily found in the northern,northeastern,and eastern aquifers,with quality declining toward the south.The study highlights that certain aquifers in the northern and eastern regions offer greater potential for sustainable groundwater exploitation during water shortages.These findings provide valuable insights for on how to implement effective land and water management strategies to mitigate future water crises.
基金funding from the National Science Foundation(NSF Award 2114701)of the United States.
文摘This study advances the DRASTIC groundwater vulnerability assessment framework by integrating a multi-hazard groundwater index(MHGI)to account for the dynamic impacts of diverse anthropogenic activities and natural factors on both groundwater quality and quantity.Incorporating factors such as population growth,agricultural practices,and groundwater extraction enhances the framework’s ability to capture multi-dimensional,spatiotemporal changes in groundwater vulnerability.Additional improvements include refined weighting and rating scales for thematic layers based on available observational data,and the inclusion of distributed recharge.We demonstrate the practical utility of this dynamic DRASTIC-based framework through its application to the agro-urban regions of the Irrigated Indus Basin,a major groundwater-dependent agricultural area in South Asia.Results indicate that between 2005 and 2020,54%of the study area became highly vulnerable to pollution.The MHGI revealed a 13%decline in potential groundwater storage and a 25%increase in groundwater-stressed zones,driven primarily by population growth and intensive agriculture.Groundwater vulnerability based on both groundwater quality and quantity dimensions showed a 19%decline in areas of low to very low vulnerability and a 6%reduction in medium vulnerability zones by 2020.Sensitivity analyses indicated that groundwater vulnerability in the region is most influenced by groundwater recharge(42%)and renewable groundwater stress(38%).Validation with in-situ data yielded area under the curve values of 0.71 for groundwater quality vulnerability and 0.63 for MHGI.The framework provides valuable insights to guide sustainable groundwater management,safeguarding both environmental integrity and human well-being.
基金financially supported by the Tianchi Talents Program of Xinjiang Uygur Autonomous Region(E5358525,2025–2026)the Major Science and Technology Special Project of Xinjiang Uygur Autonomous Region(2024A03009-4)+4 种基金the Third Xinjiang Scientific Expedition Program(2022xjkk010402)the National Key Research and Development Program of China(2022FY202305-06)the Tianshan Talents Program of Xinjiang Uygur Autonomous Region(2022TSYCJU0002)the Outstanding Member of the Youth Innovation Promotion Association of the Chinese Academy of Sciences(20192024–2026).
文摘The diversity and discontinuity of plant communities in the oasis–desert ecotone are largely shaped by variations in groundwater depth,yet the relationships between spatial distribution patterns and ecological niches at a regional scale remain insufficiently understood.This study examined the oasis–desert ecotone in Qira County located in the Tarim Basin of China to investigate the spatial distribution of plant communities and groundwater depth as well as their relationships using an integrated approach that combined remote sensing techniques,field monitoring,and numerical modeling.The results showed that vegetation distribution exhibits marked spatial heterogeneity,with coverage ranked as follows:Tamarix ramosissima>Phragmites australis>Populus euphratica>Alhagi sparsifolia.Numerical simulations indicated that groundwater depths range from 2.00 to 65.00 m below the surface,with the system currently in equilibrium,sustaining an average annual recharge of 1.06×10^(8) m^(3) and an average annual discharge of 1.01×10^(8) m^(3).Groundwater depth strongly influences vegetation composition and structure:Phragmites australis dominates at average groundwater depth of 5.83 m,followed by Populus euphratica at average groundwater depth of 7.05 m.As groundwater depth increases,the community is initially predominated by Tamarix ramosissima(average groundwater depth of 8.35 m),then becomes a mixture of Tamarix ramosissima,Populus euphratica,and Karelinia caspia(average groundwater depth of 10.50 m),and finally transitions to Alhagi sparsifolia(average groundwater depth of 14.30 m).These findings highlight groundwater-dependent ecological thresholds that govern plant community composition and provide a scientific basis for biodiversity conservation,ecosystem stability,and vegetation restoration in the arid oasis–desert ecotone.
基金supported by the National Natural Science Foundation of China [grant numbers 42088101 and 42375048]。
文摘Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.
基金funding received from UNESCO-SIDA Project as well as Professor Martine Leermakers and Professor Willy Baeyens for their financial help to analyze the water samples in their laboratory at VUB.Acknowledgements
文摘Groundwater and surface water contamination by PTE(Potentially Toxic Elements)was assessed in Ruashi and Annexe municipalities of Lubumbashi city.Analyses of seventy water samples collected from six drilled wells,eight spade-sunk wells,one river and one spring in both municipalities in 2017 and 2018 were carried out by ICP-SF-MS(Inductively Coupled Plasma-Sector Field Mass Spectrometry).Twenty PTEs including aluminum,arsenic,barium,bismuth,cadmium,cesium,chromium,cobalt,copper,iron,lead,manganese,molybdenum,nickel,strontium,thallium,tungsten,uranium,vanadium and zinc were detected at various concentrations in each one of the samples.Many samples had concentrations and mean concentrations of PTEs,such as aluminum,cadmium,copper,iron,lead,manganese,nickel and zinc,higher than the respective acceptable limits set for drinking water by the EU(European Union),the USEPA(United States Environmental Protection Agency),and the WHO(World Health Organization)standards.Most PTEs being deleterious to human health even at very low concentrations,people who use the groundwater and surface water to meet their water needs in both Ruashi and Annexe municipalities are at risk.
基金supported by the National Key Research and Development Program of China(No.2021YFA0715900).
文摘Located in northern China,the Hetao Plain is an important agro-economic zone and population centre.The deterioration of local groundwater quality has had a serious impact on human health and economic development.Nowadays,the groundwater vulnerability assessment(GVA)has become an essential task to identify the current status and development trend of groundwater quality.In this study,the Convolutional Neural Network(CNN)and Long Short-Term Memory(LSTM)models are integrated to realize the spatio-temporal prediction of regional groundwater vulnerability by introducing the Self-attention mechanism.The study firstly builds the CNN-LSTM modelwith self-attention(SA)mechanism and evaluates the prediction accuracy of the model for groundwater vulnerability compared to other common machine learning models such as Support Vector Machine(SVM),Random Forest(RF),and Extreme Gradient Boosting(XGBoost).The results indicate that the CNNLSTM model outperforms thesemodels,demonstrating its significance in groundwater vulnerability assessment.It can be posited that the predictions indicate an increased risk of groundwater vulnerability in the study area over the coming years.This increase can be attributed to the synergistic impact of global climate anomalies and intensified local human activities.Moreover,the overall groundwater vulnerability risk in the entire region has increased,evident fromboth the notably high value and standard deviation.This suggests that the spatial variability of groundwater vulnerability in the area is expected to expand in the future due to the sustained progression of climate change and human activities.The model can be optimized for diverse applications across regional environmental assessment,pollution prediction,and risk statistics.This study holds particular significance for ecological protection and groundwater resource management.
基金supported by the Centralized R&D Project of China National Nuclear Corporation(CNNC[2021]No.144)the Key Research and Development Program of Hunan Province(Nos.2022SK2076 and 2020WK2022)+2 种基金the Natural Science Foundation of Changsha(No.kq2202089)the Postdoctoral Fellowship Program of CPSF(No.BX20230437)the Natural Science Foundation of Hunan Province(No.2023JJ30658).
文摘Addressing the global challenge of uranium(U)-contaminated groundwater requires innovative bioremediation strategies.This study investigates Desulfovibrio desulfuricans,a neutrophilic and mesophilic sulfate-reducing bacteria(SRB)strain optimized for lowtemperature(15℃)and acidic(initial pH 4)conditions,to validate its bioaugmentation potential for uranium decontamination in groundwater.Our research aimed to assess its efficacy in treating U-contaminated groundwater and elucidate the optimal growth conditions for this strain in acidic and sulfate-enriched environments.We found that D.desulfuricans was phylogenetically distinct from the native microbial community in acidic Ucontaminated groundwater,while it maintained appreciable activity in sulfate reduction under contaminated groundwater conditions after accumulation.Acid-tolerant D.desulfuricans removed 75.87%of uranium and 30.64%of sulfate from acidic U-contaminated groundwater(pH 4.0)at 15℃ within 14 days.Furthermore,we explored the optimal sulfate concentration for bacterial growth,which was found to be 2000 mg/L,and an elevated Fe^(2+) concentration from 100 to 1000 mg/L increasingly stimulated sulfate-reducing activity.These findings provide a novel insight into the application of neutrophilic and mesophilic SRB in bioremediation of acidic and low-temperature groundwater after accumulation and underscore the feasibility of bioremediation by using exogenously pure SRB.
基金supported by the National Key Research and Development Program of China(No.2019YFC1804501)the National Natural Science Foundation of China(Nos.42122056 and U1901210)+2 种基金Guangdong Basic and Applied Basic Research Foundation(No.2021B1515020063)the Key Research and Development Program of Guangdong Province(No.2021B1111380003)the Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program(No.2017BT01Z032).
文摘Coking industry is a potential source of heavy metals(HMs)pollution.However,its impacts to the groundwater of surrounding residential areas have not been well understood.This study investigated the pollution characteristics and health risks of HMs in groundwater nearby a typical coking plant.Nine HMs including Fe,Zn,Mo,As,Cu,Ni,Cr,Pb and Cd were analyzed.The average concentration of total HMswas higher in the nearby area(244.27μg/L)than that of remote area away the coking plant(89.15μg/L).The spatial distribution of pollution indices including heavy metal pollution index(HPI),Nemerow index(NI)and contamination degree(CD),all demonstrated higher values at the nearby residential areas,suggesting coking activity could significantly impact the HMs distribution characteristics.Four sources of HMs were identified by Positive Matrix Factorization(PMF)model,which indicated coal washing and coking emission were the dominant sources,accounted for 40.4%,and 31.0%,respectively.Oral ingestionwas found to be the dominant exposure pathway with higher exposure dose to children than adults.Hazard quotient(HQ)values were below 1.0,suggesting negligible non-carcinogenic health risks,while potential carcinogenic risks were from Pb and Ni with cancer risk(CR)values>10−6.Monte Carlo simulation matched well with the calculated results with HMs concentrations to be the most sensitive parameters.This study provides insights into understanding how the industrial coking activities can impact the HMs pollution characteristics in groundwater,thus facilitating the implement of HMs regulation in coking industries.
基金the National Key R&D Program of China(No.2021YFA0715900)the National Natural Science Foundation of China(No.41831279)+2 种基金the Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks(No.ZDSYS20220606100604008)the Guangdong Province Bureau of Education(No.2020KCXTD006)the Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control(No.2023B1212060002).
文摘Rapid screening of inorganic arsenic(iAs)in groundwater used for drinking by hundreds of millions of mostly rural residents worldwide is crucial for health protection.Most commercial field test kits are based on the Gutzeit reaction that uses mercury-based reagents for color development,an environmental concern that increasingly limits its utilization.This study further improves the Molybdenum Blue(MB)colorimetric method to allow for faster screening with more stable reagents.More importantly,a portable three-channel colorimeter is developed for screening iAs relative to the WHO drinking water guideline value(10μg/L).Adding the reducing reagents in sequence not only prolongs the storage time to>7 days,but also accelerates the color development time to 6 min in conjunction with lowering the H_(2)SO_(4) concentration in chromogenic reagents.The optimal pH ranges from 1.2 to 1.3 and is achieved by acidifying groundwater to 1%(V/V)HCl.With detection limits of 3.7μg/L for inorganic arsenate(iAs(V))and 3.8μg/L for inorganic arsenite(iAs(Ⅲ)),testing groundwater with-10μg/L of As has a precision<20%.The method works well for a range of phosphate concentrations of 48-950μg/L(0.5-10μmol/L).Concentrations of total_iAs(6-300μg/L),iAs(V)(6-230μg/L)and iAs(Ⅲ)(0-170μg/L)for 14 groundwater samples from Yinchuan Plain,Pearl River Delta,and Jianghan Plain,are in excellent agreements(linear regression slope:0.969-1.029)with the benchmark methods.The improved chemistry here lays the foundation for the MB colorimetric method to become a commercially viable screening tool,with further engineering and design improvement of the colorimeter.
基金supported by the National Key Research and Development Program of China(No.2019YFC1804202)the National Natural Science Foundation of China(No.22020102004)+1 种基金the Tianjin Municipal Science and Technology Bureau(No.21JCZDJC00280)the Fundamental Research Funds for the Central Universities by the Ministry of Education of China(No.T2017002).
文摘Polybromodiphenyl ethers(PBDEs),the widely used flame retardants,are common contaminants in surface soils at e-waste recycling sites.The association of PBDEs with soil colloids has been observed,indicating the potential risk to groundwater due to colloid-facilitated transport.However,the extent to which soil colloidsmay enhance the spreading of PBDEs in groundwater is largely unknown.Herein,we report the co-transport of decabromodiphenyl ester(BDE-209)and soil colloids in saturated porous media.The colloids released froma soil sample collected at an e-waste recycling site in Tianjin,China,contain high concentration of PBDEs,with BDE-209 being the most abundant conger(320±30 mg/kg).The colloids exhibit relatively high mobility in saturated sand columns,under conditions commonly observed in groundwater environments.Notably,under all the tested conditions(i.e.,varying flow velocity,pH,ionic species and ionic strength),the mass of eluted BDE-209 correlates linearly with that of eluted soil colloids,even though the mobility of the colloids varies markedly depending on the specific hydrodynamic and solution chemistry conditions involved.Additionally,the mass of BDE-209 retained in the columns also correlates strongly with themass of retained colloids.Apparently,the PBDEs remain bound to soil colloids during transport in porous media.Findings in this study indicate that soil colloidsmay significantly promote the transport of PBDEs in groundwater by serving as an effective carrier.This might be the reason why the highly insoluble and adsorptive PBDEs are found in groundwater at some PBDE-contaminated sites.
基金supported by the National Natural Science Foundation of China(Nos.41830753,42277201,42377242,and 41977286)the Scientific Research Foundation of Guangzhou University(No.YJ2023027)the College Student Innovation and Entrepreneurship Training Program(No.S202311078057).
文摘Arsenic-contaminated groundwater is widely used in agriculture.To meet the increasing demand for safe water in agriculture,an efficient and cost-effective method for As removal from groundwater is urgently needed.We hypothesized that Fe(oxyhydr)oxide(FeOOH)minerals precipitated in situ from indigenous Fe in groundwater may immobilize As,providing a solution for safely using As-contaminated groundwater in irrigation.To confirm this hypothesis and identify the controlling mechanisms,we comprehensively evaluated the transport,speciation changes,and immobilization of As and Fe in agricultural canals irrigated using As-contaminated groundwater.The efficiently removed As and Fe in the canals accumulated in shallow sediment rather than subsurface sediment.Linear combination fitting(LCF)analysis of X-ray absorption near edge spectroscopy(XANES)indicated that As(Ⅴ)was the dominant As species,followed by As(Ⅲ),and therewas no FeAsO_(4) precipitate.Sequential extraction revealed higher contents of amorphous FeOOH and associated As in shallower sediment than in the subsurface layer.Stoichiometric molar ratio calculations,SEM-EDS,FTIR,and fluorescence spectroscopy collectively demonstrated that the microbial reductive dissolution of amorphous FeOOH proceeded via reactive dissolved organic matter(DOM)consumption in subsurface anoxic porewater environment facilitating high labile As,whereas in surface sediment,the in situ-generated amorphous FeOOH was stable and strongly inhibited As release via adsorption.In summary,groundwater Fe^(2+)can efficiently precipitate in benthic surface sediment as abundant amorphous FeOOH,which immobilizes most of the dissolved As,protecting agricultural soil from contamination.This field research supports the critical roles of the phase and reactivity of in situ-generated FeOOH in As immobilization and provides new insight into the sustainable use of contaminated water.
文摘Groundwater,surface water and tap water contamination by PTEs(Potentially Toxic Elements)was assessed in Kipushi town and Lupoto locality of Kipushi administrative territory in the Upper-Katanga province,Democratic Republic of Congo.A total of fifty four water samples including thirty two samples from drilled water wells,ten samples from spade-sunk water wells,six samples from supplied tap water,four samples from a mine effluent and two samples from a river were collected from both localities in November and December 2017 and in January,February and March 2018.Then the samples were analyzed for their PTE contents by ICP-SF-MS(Inductively Coupled Plasma-Sector Field Mass Spectrometry).Twenty PTEs including aluminum,arsenic,barium,bismuth,cadmium,cesium,chromium,cobalt,copper,iron,lead,manganese,molybdenum,nickel,strontium,thallium,tungsten,uranium,vanadium and zinc were detected at various concentrations in each one of the samples.Many samples had concentrations and mean concentrations of PTE,such as arsenic,aluminum,cadmium,iron,lead,manganese and zinc,higher than the respective acceptable limits set for drinking water by the EU(European Union),the USEPA(United States Environmental Protection Agency),and the WHO(World Health Organization)standards.Most PTEs being deleterious to human health even at very low concentrations,people who use the groundwater,surface water and tap water to meet their water needs in both localities are at risk.
文摘Groundwater,the world’s largest freshwater supply,is facing increasing strain due to various uses such as agriculture,industry,livestock,and household.This study aims to investigate groundwater prospective zonation in the Bandu Sub-watershed in Purulia,West Bengal,using the AHP model and RS&GIS methodologies.To achieve Goal 6 of the UN-initiated 17 SDGs,it is crucial to determine the spatial distribution of groundwater prospective zones village-by-village,with 1/3 of the regions falling under red alert zones for sustainable development.The 16 most crucial elements affecting groundwater prospective zones(GWPZs)were mapped using AHP,and the final prospective map was obtained through Weighted Overlay analysis.The study identified five different classes within the Sub-watershed as excellent,good,moderate,poor,and very poor.The validation results showed that the approach used to derive GWPZ is reliable,and the results can be applied to future sustainable developments to reduce water shortages through suitable management methods.The research aims to increase the effectiveness of sustainable groundwater zone management,ensuring long-term water management and access.
文摘Quantifying the spatial and temporal distribution of natural groundwater recharge is essential for effective groundwater modeling and sustainable resource management.This paper presents M-RechargeCal,a user-friendly software tool developed to estimate natural groundwater recharge using two widely adopted approaches:the Water Balance(WB)method and Water Table Fluctuation(WTF)method.In the WB approach,the catchment area is divided into seven land-use categories,each representing distinct recharge characteristics.The tool includes eighteen different reference Evapotranspiration(ET0)estimation methods,accommodating varying levels of climatic input data availability.Additional required inputs include crop coefficients for major crops and Curve Numbers(CN)for specific land-use types.The WTF approach considers up to three aquifer layers with different specific yields(for unconfined aquifer)or storage coeffi-cient(for confined aquifer).It also takes into account groundwater withdrawal(draft)and lateral water movement within or outside the aquifer system.M-RechargeCal is process-based and does not require cali-bration.Its performance was evaluated using six datasets from humid-subtropical environments,demon-2 strating reliable results(R=0.867,r=0.93,RE=10.6%,PMARE=9.8,ENS=0.93).The model can be applied to defined hydrological or hydrogeological units such as watersheds,aquifers,or catchments,and can be used to assess the impacts of land-use/land-cover changes on hydrological components.However,it has not yet been tested in arid regions.M-RechargeCal provides modelers and planners with a practical,accessible tool for recharge estimation to support groundwater modeling and water resource planning.The software is available free of charge and can be downloaded from the author's institutional website or obtained by contacting the author via email.
基金the Anusandhan National Research Foundation(ANRF),New Delhi[Erstwhile,Science and Engineering Research Board(SERB)]Department of Science and Technology(DST)(Government of India)(File No.:CRG/2022/002618 Dated:22.08.2023)for providing the grant and support to carry out this work effectively.
文摘The primary objective of this study is to measure fluoride levels in groundwater samples using machine learning approaches alongside traditional and fuzzy logic models based health risk assessment in the hard rock Arjunanadi River basin,South India.Fluoride levels in the study area vary between 0.1 and 3.10 mg/L,with 32 samples exceeding the World Health Organization(WHO)standard of 1.5 mg/L.Hydrogeochemical analyses(Durov and Gibbs)clearly show that the overall water chemistry is primarily influenced by simple dissolution,mixing,and rock-water interactions,indicating that geogenic sources are the predominant contributors to fluoride in the study area.Around 446.5 km^(2)is considered at risk.In predictive analysis,five Machine Learning(ML)models were used,with the AdaBoost model performing better than the other models,achieving 96%accuracy and 4%error rate.The Traditional Health Risk Assessment(THRA)results indicate that 65%of samples pose highly susceptible for dental fluorosis,while 12%of samples pose highly susceptible for skeletal fluorosis in young age groups.The Fuzzy Inference System(FIS)model effectively manages ambiguity and linguistic factors,which are crucial when addressing health risks linked to groundwater fluoride contamination.In this model,input variables include fluoride concentration,individual age,and ingestion rate,while output variables consist of dental caries risk,dental fluorosis,and skeletal fluorosis.The overall results indicate that increased ingestion rates and prolonged exposure to contaminated water make adults and the elderly people vulnerable to dental and skeletal fluorosis,along with very young and young age groups.This study is an essential resource for local authorities,healthcare officials,and communities,aiding in the mitigation of health risks associated with groundwater contamination and enhancing quality of life through improved water management and health risk assessment,aligning with Sustainable Development Goals(SDGs)3 and 6,thereby contributing to a cleaner and healthier society.
文摘This study systematically investigates natural radioactivity in groundwater from the densely populated eastern Gonghe Basin in Qinghai Province,aiming to reveal its spatial distribution,origins,and potential health risks.The characteristics of gross-αand gross-βactivities,as well as the concentrations of nuclide including^(238)U,^(232)Th,and^(226)Ra,have been investigated in groundwater samples from 12 groups encompassing various types such as hot springs and artesian wells across different aquifer systems.Correlation analysis and dose estimation models were applied to preliminary estimate the radiation exposure to local residents and to explore the genesis and hazards of natural radioactivity in groundwater.Results indicate that overall groundwater radioactivity in the Gonghe Basin remains within acceptable limits,with mean gross-αand gross-βactivity concentrations of 0.32 Bq/L and 0.27 Bq/L,respectively.Approximately 83.33%of samples comply with relevant national standards.However,two fault-controlled high-temperature spring samples exhibited gross-αactivity exceeding regulatory limits,with one also showing elevated gross-βactivity surpassing China's Class III groundwater quality standards for radioactivity.Furthermore,single-radionuclideαradioactivity from^(230)Th,^(226)Ra,^(210)Po,and^(232)Th exceeded regulatory thresholds in some samples,suggesting potential long-term health risks.While most samples complied with effective dose limits,four showed^(210)Poαradioactivity exceedances within controllable risk ranges.The findings suggest that groundwater radioactivity in the region is primarily controlled by geological structures,lithology,and hydrothermal conditions,with fault zones and high-temperature environments serving as key factors in radionuclide enrichment.This research provides scientific foundation for the sustainable development of geothermal resources and the prevention of radioactive water contamination.Continuous monitoring of high-radioactivity hot springs and prudent resource utilization are recommended.
文摘This review critically examines strategies for sustainable groundwater and surface water management,emphasizing their integration to achieve environmental sustainability.The study synthesizes findings from a wide range of research articles,identifying key trends,gaps,and controversies within the field.It highlights the importance of cohesive management approaches that take into account climate change,policy impacts,and methodological advancements.The review aims to provide a structured,analytical discussion that aligns with the thematic focus of integrated water management.By offering original insights and practical recommendations,this review seeks to contribute to the development of more effective and sustainable water management practices.The analysis underscores the necessity of interdisciplinary approaches that integrate hydrological,ecological,and socio-economic factors.Furthermore,the review discusses the role of adaptive management and technological innovations in enhancing the resilience and efficiency of water management systems.The findings suggest that a comprehensive understanding of the interactions between groundwater and surface water is crucial for developing strategies that ensure long-term environmental sustainability.This review concludes with recommendations for future research and policy development,emphasizing the need for adaptive,resilient,and integrated water management strategies that can address the challenges posed by climate change and other environmental pressures.
基金This study was conducted as a part of the IAEA Co-ordinated Research Project(CRP)“Isotope techniques for the evaluation of water sources in irrigation systems(F-33025)”。
文摘Agriculture is a major contributor to the global economy,accounting for approximately 70%of the freshwater use,which cause significant stress on aquifers in intensively irrigated regions.This stress often leads to the decline in both the quantity and quality of groundwater resources.This study is focused on an intensively irrigated region of Northern India to investigate the sources and mechanism of groundwater recharge using a novel integrated approach combining isotope hydrology,Artificial Neural Network(ANN),and hydrogeochemical models.The study identifies several key sources of groundwater recharge,including natural precipitation,river infiltration,Irrigation Return Flow(IRF),and recharge from canals.Some groundwater samples exhibit mixing from various sources.Groundwater recharge from IRF is found to be isotopically enriched due to evaporation and characterized by high Cl−.Stable isotope modeling of evaporative enrichment in irrigated water helped to differentiate the IRF during various cultivation periods(Kharif and Rabi)and deduce the climatic conditions prevailed during the time of recharge.The model quantified that 29%of the irrigated water is lost due to evaporation during the Kharif period and 20%during the Rabi period,reflecting the seasonal variations in IRF contribution to the groundwater.The ANN model,trained with isotope hydrogeochemical data,effectively captures the complex interrelationships between various recharge sources,providing a robust framework for understanding the groundwater dynamics in the study area.A conceptual model was developed to visualize the spatial and temporal distribution of recharge sources,highlighting how seasonal irrigation practices influence the groundwater.The integration of isotope hydrology with ANN methodologies proved to be effective in elucidating the multiple sources and processes of groundwater recharge,offering insights into the sustainability of aquifer systems in intensively irrigated regions.These findings are critical for developing data-driven groundwater management strategies that can adapt to future challenges,including climate change,shifting land use patterns,and evolving agricultural demands.The results have significant implications for policymakers and water resource managers seeking to ensure sustainable groundwater use in water-scarce regions.
