The effects of heavy rain on the fate of urban and agricultural pollutants in the riverside area around weirs using multi-isotope, microbial data and numerical simulation.

The increase in extreme heavy rain due to climate change is a critical factor in the fate of urban and agricultural pollutants in aquatic system. Nutrients, including NO3- and PO43-, are transported with surface and seepage waters into rivers, lakes and aquifers and can eventually lead to algal blooms. δ15N-NO3-, δ18O-NO3-, and δ11B combined with hydrogeochemical and microbial data for groundwater and surface water samples were interpreted to evaluate the fate of nutrients in a riverside area around weirs in Daegu, South Korea. Most of the ions showed similar concentrations in the groundwater samples before and after heavy rain while concentrations of major ions in surface water samples were diluted after heavy rain. However, Si, PO43-, Zn, Ce, La, Pb, Cu and a number of waterborne pathogens increased in surface water after heavy rain. The interpretation of δ11B, δ15N-NO3-, and δ18O-NO3- values using a Bayesian mixing model revealed that sewage and synthetic fertilizers were the main sources of contaminants in the groundwater and surface water samples. δ18O and SiO2 interpreted using the Bayesian mixing model indicated that the groundwater component in the surface water increased from 4.4 % to 17.9 % during the wet season. This is consistent with numerical simulation results indicating that the direct surface runoff and the groundwater baseflow contributions to the river system had also increased 6.4 times during the wet season. The increase in proteobacteria and decrease of actinobacteria in the surface water samples after heavy rain were also consistent with an increase of surface runoff and an increased groundwater component in the surface water. This study suggests that source apportionment based on chemical and multi-isotope data combined with numerical modeling approaches can be useful for identifying main hydrological and geochemical processes in riverside areas around weirs and can inform suggestions of effective methods for water quality management.

Nitrate prediction in groundwater of data scarce regions: The futuristic fresh-water management outlook.

Nitrate contamination in groundwater poses a significant threat to water quality and public health, especially in regions with limited data availability. This study addresses this challenge by employing machine learning (ML) techniques to predict nitrate (NO3--N) concentrations in Mexico's groundwater. Four ML algorithms-Extreme Gradient Boosting (XGB), Boosted Regression Trees (BRT), Random Forest (RF), and Support Vector Machines (SVM)-were executed to model NO3--N concentrations across the country. Despite data limitations, the ML models achieved robust predictive performances. XGB and BRT algorithms demonstrated superior accuracy (0.80 and 0.78, respectively). Notably, this was achieved using ∼10 times less information than previous large-scale assessments. The novelty lies in the first-ever implementation of the 'Support Points-based Split Approach' during data pre-processing. The models considered initially 68 covariates and identified 13-19 significant predictors of NO3--N concentration spanning from climate, geomorphology, soil, hydrogeology, and human factors. Rainfall, elevation, and slope emerged as key predictors. A validation incorporated nationwide waste disposal sites, yielding an encouraging correlation. Spatial risk mapping unveiled significant pollution hotspots across Mexico. Regions with elevated NO3--N concentrations (>10 mg/L) were identified, particularly in the north-central and northeast parts of the country, associated with agricultural and industrial activities. Approximately 21 million people, accounting for 10 % of Mexico's population, are potentially exposed to elevated NO3--N levels in groundwater. Moreover, the NO3--N hotspots align with reported NO3--N health implications such as gastric and colorectal cancer. This study not only demonstrates the potential of ML in data-scarce regions but also offers actionable insights for policy and management strategies. Our research underscores the urgency of implementing sustainable agricultural practices and comprehensive domestic waste management measures to mitigate NO3--N contamination. Moreover, it advocates for the establishment of effective policies based on real-time monitoring and collaboration among stakeholders.

Identifying the origin and fate of dissolved U in the Boeun aquifer based on microbial signatures and C, O, Fe, S, and U isotopes.

The uranium inventory in the Boeun aquifer is situated near an artificial reservoir (40-70 m apart) intended to supply water to nearby cities. However, toxic radionuclides can enter the reservoir. To determine the U mobility in the system, we analyzed groundwater and fracture-filling materials (FFMs) for environmental tracers, including microbial signatures, redox-sensitive elements and isotopes. In the site, U mass flux ranged from only 9.59 × 10-7 µg/L/y to 1.70 × 10-4 µg/L/y. The δ18O-H2O and 14C signatures showed that groundwater originated mainly from upland recharges and was not influenced by oxic surface water. We observed U accumulations (∼157 mg/kg) in shallow FFMs and Fe enrichments (∼226798 mg/kg) and anomalies in the 230Th/238U activity ratio (AR), 230Th/234U AR, δ56Fe and δ57Fe isotopes, suggesting that low U mobility in shallow depths is associated with a Fe-rich environment. At shallow depths, anaerobic Fe-oxidizers, Gallionella was prevalent in the groundwater, while Acidovorax was abundant near the U ore deposit depth. The Fe-rich environment at shallow depths was formed by sulfide dissolution, as demonstrated by δ34S-SO4 and δ18O-SO4 distribution. Overall, the Fe-rich aquifer including abundant sulfide minerals immobilizes dissolved U through biotic and abiotic processes, without significant leaching into nearby reservoirs.

Nitrate sources, timing, and pathways of a permeable volcanic aquifer system with mixed land use in Jeju Island, South Korea.

The occurrence of various N-related human activities increases the difficulty in distinguishing the major sources of NO3- contamination in groundwater, especially in areas with mixed land uses. In addition, the estimation of the timing and pathways of NO3- is necessary to better understand the processes of NO3- contamination in the subsurface aquifer system. This study applied environmental tracers, such as stable isotopes and age tracers (δ15N and δ18O of NO3-, δ11B, chlorofluorocarbons, and 3H), to elucidate the sources, timing, and pathways of NO3- contamination in the groundwaters of the Hanrim area, which has suffered from illegal disposal of livestock wastes since the 1980s, and also characterizes them based on mixed N-contaminant sources such as chemical fertilizers and sewage. The combined use of δ15N and δ11B overcame the limitation of using only NO3- isotopes for the identification of overlapping sources of N and successfully identified the major source of N as livestock wastes. The lumped parameter model (LPM) estimated the binary mixing of the young (age: 23-40 years, NO3-N: 2.55-15.10 mg/L) and old (age: >60 years, NO3-N: <3 mg/L) groundwaters, and explained their age mixing behaviors. The young groundwater was highly affected by livestock-derived N loading during 1987-1998, which coincides with the period of improper dumping of livestock wastes. Furthermore, the young groundwater with elevated NO3-N followed the historical NO3-N curves with younger ages (6 and 16 years) than those derived from the LPM, suggesting the possibility of faster inflows of livestock wastes through the permeable volcanic structures. This study demonstrated that a comprehensive understanding of NO3- contamination processes can be achieved using environmental tracer methods, which enables the efficient management of groundwater resources in areas with multiple N sources.

Estimation of nutrient sources and fate in groundwater near a large weir-regulated river using multiple isotopes and microbial signatures.

The excessive input of nutrients into groundwater can accelerate eutrophication in associated surface water systems. This study combined hydrogeochemistry, multi isotope tracers, and microbiological data to estimate nutrient sources and the effects of groundwater-surface water interactions on the spatiotemporal variation of nutrients in groundwater connected to a large weir-regulated river in South Korea. δ11B and δ15N-NO3- values, in combination with a Bayesian mixing model, revealed that manure and sewage contributed 40 % and 25 % respectively to groundwater nitrate, and 42 % and 27 % to nitrate in surface water during the wet season. In the dry season, the source apportionment was similar for groundwater while the sewage contribution increased to 52 % of nitrate in river water. River water displayed a high correlation between NO3- concentration and cyanobacteria (Microcystis and Prochlorococcus) in the wet season. The mixing model using multiple isotopes indicated that manure-derived nutrients delivered with increased contributions of groundwater to the river during the wet season governed the occurrence of cyanobacterial blooms in the river. We postulate that the integrated approach using multi-isotopic and microbiological data is highly effective for evaluating nutrient sources and for delineating hydrological interactions between groundwater and surface water, as well as for investigating surface water quality including eutrophication in riverine and other surface water systems.

Constraining the effectiveness of inherent tracers of captured CO2 for tracing CO2 leakage: Demonstration in a controlled release site.

Geological storage of carbon dioxide (CO2) is an integral component of cost-effective greenhouse gas emissions reduction scenarios. However, a robust monitoring regime is necessary for public and regulatory assurance that any leakage from a storage site can be detected. Here, we present the results from a controlled CO2 release experiment undertaken at the K-COSEM test site (South Korea) with the aim of demonstrating the effectiveness of the inherent tracer fingerprints (noble gases, δ13C) in monitoring CO2 leakage. Following injection of 396 kg CO2(g) into a shallow aquifer, gas release was monitored for 2 months in gas/water phases in and above the injection zone. The injection event resulted in negative concentration changes of the dissolved gases, attributed to the stripping action of the depleted CO2. Measured fingerprints from inherent noble gases successfully identified solubility-trapping of the injected CO2 within the shallow aquifer. The δ13C within the shallow aquifer could not resolve the level of gas trapping, due to the interaction with heterogeneous carbonate sources in the shallow aquifer. The time-series monitoring of δ13CDIC and dissolved gases detected the stripping action of injected CO2(g), which can provide an early warning of CO2 arrival. This study highlights that inherent noble gases can effectively trace the upwardly migrating and fate of CO2 within a shallow aquifer.

Abnormal groundwater levels and microbial communities in the Pohang Enhanced Geothermal System site wells pre- and post-Mw 5.5 earthquake in Korea.

In this study, two geothermal wells (PX-1 and PX-2) exhibiting abnormal groundwater levels and microbial communities were examined at the Enhanced Geothermal System site before and after the Pohang earthquake (November 2017). Furthermore, the EXP-1 well level, water temperature, microbial communities and their association with earthquakes, as well as the possibility of future earthquakes were explored. The primary objectives of this research were to: (1) perform correlation and cluster analyses of hydrophysical parameters for earthquakes using next-generation sequencing; (2) analyze pre-, co-, and post-seismic changes in groundwater levels, temperatures, and microbial communities; and (3) further assess the analyzed results of the post-earthquake changes in the groundwater levels and temperatures to interpret their implications. Although the pre-earthquake water levels in the three wells were unknown, their depth-to-water levels post-earthquake ranged from 50.33-98.20 m, 570.91-735.00 m, and 47.70-56.04 m for wells PX-1 (depth 4362 m), PX-2 (4348 m), and EXP-1 (180 m), respectively. In particular, the water levels of PX-2 were abnormally low compared with the surrounding area. Moreover, the geothermal wells demonstrated unstable microbial communities prior to the earthquake. However, while the microbial communities of PX-1 recovered relatively quickly post-earthquake, those of PX-2 failed to stabilize even within two years after the earthquake. Thus, it was inferred here that the PX-2 well is more closely related to seismic activity, the effects of which can still be seen. Accordingly, it is important that PX-2 is continuously monitored until June 2024, the minimum period predicted for the water levels to reach stability.

Earthquakes and very deep groundwater perturbation mutually induced.

We report unique observations from drilling and hydraulic stimulation at a depth of approximately 4.3 km in two Enhanced Geothermal System (EGS) wells at the Pohang EGS site, South Korea. We surveyed drilling logs and hydraulic stimulation data, simulated pore pressure diffusion around the fault delineated by seismic and drilling log analyses, conducted acoustic image logging through the EGS wells, observed significant water level drops (740 m) in one of the two EGS wells, and obtained hydrochemical and isotopic variation data in conjunction with the microbial community characteristics of the two EGS wells. We discuss the hydraulic and hydrochemical responses of formation pore water to a few key seismic events near the hypocenter. We focused on how the geochemistry of water that flowed back from the geothermal wells changed in association with key seismic events. These were (1) a swarm of small earthquakes that occurred when a significant circulation mud loss occurred during well drilling, (2) the MW 3.2 earthquake during hydraulic stimulation, and (3) the MW 5.5 main shock two months after the end of hydraulic stimulation. This study highlights the value of real-time monitoring and water chemistry analysis, in addition to seismic monitoring during EGS operation.

Determining nitrate and sulfate pollution sources and transformations in a coastal aquifer impacted by seawater intrusion-A multi-isotopic approach combined with self-organizing maps and a Bayesian mixing model.

Over the past few decades, the La Paz aquifer system in Baja California Sur, Mexico, has been under severe pressure due to overexploitation for urban water supply and agriculture; this has caused seawater intrusion and deterioration in groundwater quality. Previous studies on the La Paz aquifer have focused mainly on seawater intrusion, resulting in limited information on nitrate and sulfate pollution. Therefore, pollution sources have not yet been identified sufficiently. In this study, an approach combining hydrochemical tools, multi-isotopes (δ2HH2O, δ18OH2O, δ15NNO3, δ18ONO3, δ34SSO4, δ18OSO4), and a Bayesian isotope mixing model was used to estimate the contribution of different nitrate and sulfate sources to groundwater. Results from the MixSIAR model revealed that seawater intrusion and soil-derived sulfates were the predominant sources of groundwater sulfate, with contributions of ~43.0% (UI90 = 0.29) and ~42.0% (UI90 = 0.38), respectively. Similarly, soil organic nitrogen (~81.5%, UI90 = 0.41) and urban sewage (~12.1%, UI90 = 0.25) were the primary contributors of nitrate pollution in groundwater. The dominant biogeochemical transformation for NO3- was nitrification. Denitrification and sulfate reduction were discarded due to the aerobic conditions in the study area. These results indicate that dual-isotope sulfate analysis combined with MixSIAR models is a powerful tool for estimating the contributions of sulfate sources (including seawater-derived sulfate) in the groundwater of coastal aquifer systems affected by seawater intrusion.

Delineation of groundwater quality locations suitable for target end-use purposes through deep neural network models.

Groundwater is the main source of water for beverages, and its quality varies depending on extraction location; this is particularly the case in regions with complex geology, topography, and multiple forms of land use. Thus, it is important to determine a suitable groundwater extraction location based on intended water use and the related water quality standards. In this study, deep neural network (DNN) models and GIS data relating to groundwater quality were applied to estimate potential maps of Gangwon Province in South Korea, where groundwater is frequently extracted for drinking purposes. These maps specify areas where the groundwater quality is conducive for being used as mineral water and water for brewing coffee (hereafter referred as "coffee water"). Sensitivity analysis identified how inputs were sensitive to model estimation and showed that land-use variables were the most sensitive. The importance of each variable quantified how good or bad its region is for the desired groundwater. The overall features of importance were similar between mineral water and coffee water. However, with differences in hydrogeological units, carbonate rock was a variable of high positive importance for mineral water; metamorphic rock was its equivalent for coffee water. Our results offer a potential map of desired groundwater quality in the absence of a detailed understanding of the underlying hydrochemical processes governing groundwater quality. Additionally, the development of such a potential mapping model can help to determine the appropriate development area of groundwater for their respective purposes.

Differentiation of natural and anthropogenic contaminant sources using isotopic and microbial signatures in a heavily cultivated coastal area.

Hydrogeochemical and multiple isotope data for groundwater samples were obtained and interpreted to discriminate anthropogenic and natural contaminant sources in a coastal aquifer underlying a heavily cultivated watershed in Hwaseong, South Korea. The local aquifers are vulnerable to contamination, due to high anthropogenic N inputs and the location close to the ocean facilitating seawater intrusion. Thus, to effectively control the groundwater quality in the study area, it is necessary to differentiate between anthropogenic and natural contaminant sources. The concentrations of NO3-N in the groundwater ranged between 0.14 and 45.6 mg/L in August 2015 and 0.2-39.6 mg/L in March 2016. High concentrations of Cl- (388-1107 mg/L) and a high electrical conductivity (1027-2715 µS/cm) were observed in the study area, suggesting that the groundwater was affected by seawater intrusion. Furthermore, δ15N-NO3-, δ34S-SO42- values and 87Sr/86Sr of groundwater were determined to reveal the origins of the natural and anthropogenic contaminants and the groundwater mean residence times (MRT) and 87Sr/86Sr ratios were used to assess the hydrogeochemical processes along the flow path in the study area. Young groundwater was affected by an anthropogenic contamination source with contributions of 26-46% adding nitrate to the aquifer, whereas old groundwater was impacted by mixing with seawater with contributions of 10-20% with low concentrations of NO3-N, but elevated concentrations of chloride and sulfate. Recently recharged uncontaminated groundwater showed oxic conditions with a diverse microbial community structure, whereas young groundwater contaminated by anthropogenic sources showed a less diverse microbial community structure. The results of this study suggest that multiple isotopes combined with groundwater MRT and microbial data can be applied to distinguish natural and anthropogenic contaminant sources in a groundwater system.

Complexity of groundwater age mixing near a seawater intrusion zone based on multiple tracers and Bayesian inference.

Aquifer flow systems near seawater interfaces can be complicated by density-driven flows and the formation of stagnation zones, which inevitably introduces uncertainty into groundwater age-dating. While age-dating has proved effective to understand the seawater intrusion and aquifer salinization process in coastal aquifers, further efforts are needed to propagate model and data uncertainty to the uncertainty associated with the inferred age distributions. This study was performed in a coastal aquifer located close to the Yellow Sea, South Korea, where there is a decreasing trend of groundwater levels due to recent heavy exploitation, raising a warning of induced seawater intrusion. We inferred the groundwater age distributions in wells around the intrusion zone and estimated the uncertainty associated with the inference based on multiple age tracers including 3H, tritiogenic 3He, radiogenic 4He, CFC-11, CFC-12 and CFC-113 using Bayesian inference. We examined various models representing the age distributions including traditional parametric Lumped Parameter Models (LPMs) and two non-parametric "shape-free" models. The results showed that the mean ages at the study site ranged from 10.9 to 522.5 y. Complex, multimodal distributions of ages occurred near a seawater intrusion area and upland recharge zones, implying converging paths of a wide range of different ages in those regions. In particular, the age distributions estimated near the seawater intrusion interface were characterized by heavy-tailed mixing structures with elevated concentrations of 4He. This likely indicates density-driven upward flow at the seawater intrusion interface, forcing old groundwater rich in 4He into the shallow aquifer. The Bayesian inference estimated large uncertainties particularly for the old age distributions, which was attributed partly to the gradual accumulation of 4He in groundwater. The Bayesian inference improved understanding of flow dynamics at a complex seawater interface and identified opportunities to further reduce uncertainty of old water age estimates that characterize upwelling groundwater near the interface.

Characterization of a NAPL-contaminated site using the partitioning behavior of noble gases.

Noble gases have been used for oil field exploration due to their partitioning behavior in oil-water systems. However, their application to study sites contaminated with non-aqueous phase liquids (NAPL) has been limited, except for 222Rn, which has been traditionally used as a partitioning tracer for contaminated sites. This study applied natural noble gas components such as 222Rn, He, Ne, Ar, Kr, and Xe to the characterization of a field site contaminated with trichloroethylene (TCE) located in Wonju, Korea. Groundwater at the site showed a maximum level of TCE that exceeded 1000 µg/L, with an approximate average of 400 µg/L, indicating the presence of residual TCE in the subsurface system even after remediation. The traditional tracer (i.e., 222Rn) was first used to characterize residual TCE. However, its heterogeneous distribution throughout the fractured bedrock aquifer negated its usefulness as a TCE indicator. The use of radiogenic 4He was also limited by the wide distribution of radiogenic sources on the site. By contrast, changes in the TCE level had clear effects on the conditions of other noble gases, such as Ne, Ar, and Xe, making them useful for characterization of the TCE-contaminated site. Furthermore, calculation of the TCE/water ratio including residual TCE was achieved, but identification of the TCE originating from the vadose zone was relatively hard. The results of this study indicate that based on their partitioning behavior, naturally-occurring noble gases can be used to delineate and quantify residual TCE.

Nationwide groundwater monitoring around infectious-disease-caused livestock mortality burials in Korea: Superimposed influence of animal leachate on pre-existing anthropogenic pollution.

A foot-and-mouth disease (FMD) outbreak during 2010 affected the entire country of South Korea and approximately 3.4 million swine and bovine mortalities were disposed of at approximately 4800 on-farm burial sites for a few months following the first outbreak. Furthermore, outbreaks of avian influenza (AI) have struck Korea consistently since 2014. Public concern regarding the deterioration of the surrounding environment has been raised aiming at the enormous infected animal carcass burials. On behalf of the Ministry of Environment (ME) of the Korean government, we conducted groundwater monitoring at approximately 3000 wells around the burial sites for 7 years from 2011 to 2017. The baseline groundwater already had enriched levels of nitrogen and chloride compounds masking the influence of leachate with the pre-existing anthropogenic contamination. Based on the trend analysis, most monitoring wells had no significant trends in NO3-N and Cl implying that an abrupt degradation in water quality was not expected across the country. Increasing proportions of total coliform detection in the groundwater of the majority of provinces will cause potential damage to human health around the carcass burial sites. Wells showing frequent upward and downward trends near the carcass burial pits were targeted for principal component analysis (PCA) and the results showed that NH4-N, TOC, Cl, and K could be indicators distinguishing the sole impacts of animal leachate on the groundwater. Analyses of the nationwide monitoring data indicated possibly delayed and prolonged impacts of the widespread burials of livestock mortalities on the groundwater environment. The finding provides realistic insight regarding how to manage the mass burial of livestock mortalities to protect groundwater resources.

Combining pyrosequencing and isotopic approaches to assess denitrification in a hyporheic zone.

Hyporheic zones are considered hot spots for numerically vast and phylogenetically diverse microbial communities. However, biogeochemical effects of hyporheic zones have rarely been investigated in detail because of the difficulty in accurately measuring denitrification in these zones. To date, little is known about the hydroecology of hyporheic zones. The effect of changes in hydraulic conditions on the community variations of indigenous microorganisms and water quality was examined based on the depth of the hyporheic zone. In particular, we report on the use of the pyrosequencing technique to elucidate denitrifying bacteria (DNB) community profiles combined with the stable isotope composition of nitrate and hydrological patterns in the hyporheic zones to reveal whether denitrification occurs. δ15N-NO3 and δ18O-NO3 values of nitrate were analyzed to evaluate the transformation processes of nitrate in upwelling and downwelling areas and mixed zones. The isotope values indicated different origins of water in upwelling and downwelling zones and that denitrification occurred predominantly in the upwelling areas. Analyses of microbial communities in the hyporheic zone showed that the new genera, species, and isotope data were associated with the hydrological uniqueness of the hyporheic zones. The 16S rRNA sequences were determined and phylogenetic analysis revealed that the DNB communities distributed and gathered the genus Comamonas denitrificans within the mixing patterns of the hyporheic zones and that the relative scarcity of these microbes in these zones was caused by the lack of appropriate substrates. The delineation of the surface water-groundwater mixing zone was quantitatively determined by systematically combining the hydrological and heat transfer analyses and by comparing denitrifying bacteria communities and N isotope data. This study showed that pyrosequencing and isotopic approaches are useful for evaluating the transformation processes of nitrate at the upwelling and downwelling points of a hyporheic zone.

Evaluation of the fate and transport of chlorinated ethenes in a complex groundwater system discharging to a stream in Wonju, Korea.

Chlorinated ethenes such as trichloroethylene (TCE) are common and persistent groundwater contaminants. If contaminated groundwater discharges to a stream, then stream water pollution near the contamination site also becomes a problem. In this respect, the fate and transport of chlorinated ethenes around a stream in an industrial complex were evaluated using the concentration of each component, and hydrogeochemical, microbial, and compound-specific carbon isotope data. Temporal and spatial monitoring reveal that a TCE plume originating from main and local source zones continues to be discharged to a stream. Groundwater geochemical data indicate that aerobic conditions prevail in the upgradient area of the studied aquifer, whereas conditions become anaerobic in the downgradient. The TCE molar fraction is high at the main and local source zones, ranging from 87.4 to 99.2% of the total volatile organic compounds (VOCs). An increasing trend in the molar fraction of cis-1, 2-Dichloroethene (cis-DCE) and vinyl chloride (VC) was observed in the downgradient zone of the study area. The enriched δ(13)C values of TCE and depleted values of cis-DCE in the stream zone, compared to those of the source zone, also suggest biodegradation of VOCs. Microbial community structures in monitoring wells adjacent to the stream zone in the downgradient area were analyzed using 16S rRNA gene-based pyrosequencing to identify the microorganisms responsible for biodegradation. This was attributed to the high relative abundance of dechlorinating bacteria in monitoring wells under anaerobic conditions farthest from the stream in the downgradient area. The multilateral approaches adopted in this study, combining hydrogeochemical and biomolecular methods with compound-specific analyses, indicate that contaminants around the stream were naturally attenuated by active anaerobic biotransformation processes.

Identifying the sources of nitrate contamination of groundwater in an agricultural area (Haean basin, Korea) using isotope and microbial community analyses.

An integrated study based on hydrogeochemical, microbiological and dual isotopic approaches for nitrate and sulfate was conducted to elucidate sources and biogeochemical reactions governing groundwater contaminants in different seasons and under different land use in a basin of Korea. The land use in the study area is comprised of forests (58.0%), vegetable fields (27.6%), rice paddy fields (11.4%) and others (3.0%). The concentrations of NO3-N and SO4(2-) in groundwater in vegetable fields were highest with 4.2-15.2 mg L(-1) and 1.6-19.7 mg L(-1) respectively, whereas under paddy fields NO3-N concentrations ranged from 0 to 10.7 mg L(-1) and sulfate concentrations were ~15 mg L(-1). Groundwater with high NO3-N concentrations of >10mgL(-1) had δ(15)N-NO3(-) values ranging from 5.2 to 5.9‰ and δ(18)O values of nitrate between 2.7 and 4.6‰ suggesting that the nitrate was mineralized from soil organic matter that was amended by fertilizer additions. Elevated concentrations of SO4(2-) with δ(34)S-SO4(2-) values between 1 and 6‰ in aquifers in vegetable fields indicated that a mixture of sulfate from atmospheric deposition, mineralization of soil organic matter and from synthetic fertilizers is the source of groundwater sulfate. Elevated δ(18)O-NO3(-) and δ(18)O-SO4(2-) values in samples collected from the paddy fields indicated that denitrification and bacterial sulfate reduction are actively occurring removing sulfate and nitrate from the groundwater. This was supported by high occurrences of denitrifying and sulfate reducing bacteria in groundwater of the paddy fields as evidenced by 16S rRNA pyrosequencing analysis. This study shows that dual isotope techniques combined with microbial data can be a powerful tool for identification of sources and microbial processes affecting NO3(-) and SO4(2-) in groundwater in areas with intensive agricultural land use.

Identification of multiple sources of groundwater contamination by dual isotopes.

Chlorinated solvents are one of the most commonly detected groundwater contaminants in industrial areas. Identification of polluters and allocation of contaminant sources are important concerns in the evaluation of complex subsurface contamination with multiple sources. In recent years, compound-specific isotope analyses (CSIA) have been employed to discriminate among different contaminant sources and to better understand the fate of contaminants in field-site studies. In this study, the usefulness of dual isotopes (carbon and chlorine) was shown in assessments of groundwater contamination at an industrial complex in Wonju, Korea, where groundwater contamination with chlorinated solvents such as trichloroethene (TCE) and carbon tetrachloride (CT) was observed. In November 2009, the detected TCE concentrations at the study site ranged between nondetected and 10,066 µg/L, and the CT concentrations ranged between nondetected and 985 µg/L. In the upgradient area, TCE and CT metabolites were detected, whereas only TCE metabolites were detected in the downgradient area. The study revealed the presence of separate small but concentrated TCE pockets in the downgradient area, suggesting the possibility of multiple contaminant sources that created multiple comingling plumes. Furthermore, the variation of the isotopic (δ(13) C and δ(37) Cl) TCE values between the upgradient and downgradient areas lends support to the idea of multiple contamination sources even in the presence of detectable biodegradation. This case study found it useful to apply a spatial distribution of contaminants coupled with their dual isotopic values for evaluation of the contaminated sites and identification of the presence of multiple sources in the study area.

Hydrogeochemistry and isotopic tracing of nitrate contamination of two aquifer systems on Jeju Island, Korea.

The groundwater of Jeju Island (Republic of Korea) is vulnerable to contamination because its aquifers are mainly composed of highly permeable geological units and its agricultural fields are often exposed to excessive use of predominantly synthetic fertilizers. In the Gosan area of Jeju Island, we investigated nitrate contamination in both a perched aquifer above an impermeable clay bed and the regional groundwater beneath this aquitard. The δO and δD values indicate that the perched groundwater is recharged by local precipitation, whereas the regional groundwater is recharged mainly by regional flow from an adjacent mountainous region. The perched groundwater contained very high NO-N concentrations of up to 87 mg/L. The isotopic composition of nitrate in the perched groundwater showed that synthetic fertilizers applied in high excesses of crop N needs were the main cause of aquifer pollution. Elevated nitrate concentrations were also observed in the regional groundwater especially after precipitation events. Concentration and isotopic data revealed that the inflow of shallow perched groundwater along the poorly cemented or uncemented annulus of regional groundwater wells was one of the main reasons for the nitrate contamination observed in the regional groundwater. In both aquifers, δN and δO values showed that the sources of nitrate were derived from synthetic fertilizers that had been recycled in the soil zone by nitrification and in some portions of the perched aquifer (dissolved oxygen concentrations <2 mg/L) indicated that denitrification occurred locally.

Prediction of groundwater contamination with multivariate regression and probabilistic capture zones.

Probabilistic capture zones are combined with a regression model and used as buffer zones around wells for Tobit regression analysis to predict contaminant concentration of groundwater in an agricultural region. A backward transport equation, which is a mathematical model based on the physical processes of solute transport, is used to delineate probabilistic capture zones. The probabilistic capture zone defines the area where contaminant discharge can have a direct influence, with pertinent probability, on the quality of groundwater pumped from a well. Tobit regression analysis is used to find the relationship between independent regression variables and a dependent variable, which is contaminant concentration in this study. The capture zone and the regression are combined into a model, and its applicability for prediction of nitrate concentration is tested in a small agricultural basin in Chuncheon, Korea, which is occupied mainly by vegetation fields, orchards, and small barns. Three cases of Model 1, Model 2, and Model 3 are compared in which buffer zones are circles, capture zones with probability over 0.1, and capture zones divided into sections with different probabilities, respectively. The resulting regression model describes nitrate concentration in terms of selected independent variables. When the concentrations are calculated with the model, the best fit with the observed concentrations was in Model 3. This result supports the applicability of the method proposed in this study to prediction of contaminant concentration of groundwater.