• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.353-360
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• 2007

We practiced fresh water injection test to identify its applibility as a method of seawater intrusion mitigation technique, and monitored the change of borehole fluid conductivity and the behavior of injected fresh water using borehole multichannel electrical conductivity monitoring and well-logging, and DC resistivity and SP monitoring at the surface. Well-logging and multichannel EC monitoring showed the decrease of fluid conductivity due to fresh water injection. We note that such an injection effect lasts more than several month which means the applibility of fresh water injection as a seawater intrusion control technique. Although SP monitoring did not show meaningful results because of weather condition during monitoring and the defects of electrodes due to long operation time, DC resistivity monitoring showed its effectiveness and applicability as a monitoring and assessment techniques of injection test by means of imaging the behavior and the front of fresh water body in terms of the increase of resistivity with reasonable resolution. In conclusion, we note that geophysical techniques can be an effective method of monitoring and evaluation of fresh water injection test, and expect that fresh water injection may be an practical method for the mitigation of seawater intrusion when applied with optimal design of injection well distribution and injection rate based on geophysical evaluation.

• Journal of Soil and Groundwater Environment
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• v.21 no.6
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• pp.67-79
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• 2016

Gaussian process regression (GPR) is proposed as a tool of long-term groundwater quality predictions. The major advantage of GPR is that both prediction and the prediction related uncertainty are provided simultaneously. To demonstrate the applicability of the proposed tool, GPR and a conventional non-parametric trend analysis tool are comparatively applied to synthetic examples. From the application, it has been found that GPR shows better performance compared to the conventional method, especially when the groundwater quality data shows typical non-linear trend. The GPR model is further employed to the long-term groundwater quality predictions based on the data from two domestically operated groundwater monitoring stations. From the applications, it has been shown that the model can make reasonable predictions for the majority of the linear trend cases with a few exceptions of severely non-Gaussian data. Furthermore, for the data shows non-linear trend, GPR with mean of second order equation is successfully applied.

• Economic and Environmental Geology
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• v.39 no.5 s.180
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• pp.537-554
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• 2006

Water levels of thermal groundwater ($>30^{\circ}C$) were recorded from March 2002 to June 2006 at several monitoring wells within the Yuseong spa area. Using these data, we elucidated the long-term cyclic fluctuations of thermal groundwater levels with 1 year period. We also observed a noticeable water level variation with periods of 0.5, 1 and 7 days in most monitoring wells, which indicates relatively good hydraulic connectivity within the main hotspring area. By comparing water level variations among several wells, we found out that E-W and N-S trending geological structures should be an important control factor for emplacement and flow of thermal groundwater in the study area. It may be also inferred that geothermal source is highly associated with the hydraulic connectivity of aquifers at the Yuseong spa area.

• Journal of Soil and Groundwater Environment
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• v.15 no.6
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• pp.17-28
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• 2010

As a preliminary survey to improve efficiency of well-based permeable reactive barrier system for groundwater remediation, this site-scale study was carried to identify the flowpaths and controlling factors of plume at a remediation site in Suwon City, Korea. A total of 22 monitoring wells were installed as a grid system in the $4m{\times}4m$ square area by 1-m interval. For the groundwater characterization, various tests were performed including water-level monitoring, water sampling & analysis, pumping and slug tests, and tracer tests. The aquifer appeared to be unconfined with hydraulic conductivities (K) ranging from $2.6{\times}10^{-4}cm/s$ to $9.5{\times}10^{-3}cm/s$. The average linear velocity of groundwater was estimated to be $2.94{\times}10^{-6}m/s$, and the longitudinal dispersivity of a conservative tracer to be $5.94{\times}10^{-7}m^2/s$. Groundwater plume moves preferentially through the high-K zones, and the relatively high ion concentrations along the low-K zones implying deterred groundwater flow. Consequently, the spatial variation of hydraulic conductivity caused by aquifer heterogeneity and anisotropy appears to be the most important factor to maximize the effect of plume treatment system for application of in-situ groundwater remediation techniques.

• Journal of Soil and Groundwater Environment
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• v.28 no.3
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• pp.12-28
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• 2023

Each national groundwater monitoring well showed distinct change patterns in groundwater levels and electrical conductivity (EC) in the Nakdong River Estuary, implying different external forces (EFs) on each well. According to the annual average data in 1997-2020, seawater was invaded into Well C. The desalination rate of -1,062 µS/cm/year represents the adaptive capacity of the well to seawater intrusion. The water levels and EC in Well E responded to precipitation, indicating the low absorptive capacity to climate changes. Meanwhile, Well B showed constant increases in water levels, suggesting that problems by rising groundwater should be considered in the study area where confined aquifers are overlaid by clay aquitards. The other wells showed consistent water levels and EC, indicating resilience to EFs. Here, resilience is the capacity of a well to resist changes by EFs, including the absorptive and adaptive capacity. The resilience of Wells E and F to climate changes was quantitatively compared using a resilience cost (RC). The RC showed Well F was more resilient than Well E, and the bedrock aquifer was more resilient than the alluvium aquifer, supporting the usefulness of RC. The resilience assessment against EFs (e.g., changes in land use and climate) helps sustainable groundwater management.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2002.09a
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• pp.9-12
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• 2002

The purpose of this study is to understand the high saline water phenomenon of Handong-ri area in the eastern coast of Jeju Island, were investigate the tidal effect of groundwater level, variation of electric conductivity and temperature, geological logging on the monitoring wells, chemical water quality, and ratios of oxygen istope of groundwater and seawater Results in investigating variation of interface zone of freshwater and saline water represented that the hyaloclastites formed at below groundwater table is developing toward the coast; this area consisted of stratum of good permeability. Hyaloclastites is presumed the main path of the high salinity water There are a lot of movement by the tide at upper layer. Salinity of lower layer spreads to upper up step in proportion to tidal energy. Because of hydrogeological characteristics, Interface zone of freshwater and saline water is made, High salinity of groundwater occur in east coastal area of Jeju Island. Therefore, I think that high saline groundwater phenomenon is natural condition by simple mixing.

• The Journal of Engineering Geology
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• v.32 no.4
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• pp.697-723
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• 2022

Data-driven models to predict groundwater levels 30 days in advance were developed for 12 groundwater monitoring stations in the middle-Jeju watershed, Jeju Island. Stacked long short-term memory (stacked-LSTM), a deep learning technique suitable for time series forecasting, was used for model development. Daily time series data from 2001 to 2022 for precipitation, groundwater usage amount, and groundwater level were considered. Various models were proposed that used different combinations of the input data types and varying lengths of previous time series data for each input variable. A general procedure for deep-learning-based model development is suggested based on consideration of the comparative validation results of the tested models. A model using precipitation, groundwater usage amount, and previous groundwater level data as input variables outperformed any model neglecting one or more of these data categories. Using extended sequences of these past data improved the predictions, possibly owing to the long delay time between precipitation and groundwater recharge, which results from the deep groundwater level in Jeju Island. However, limiting the range of considered groundwater usage data that significantly affected the groundwater level fluctuation (rather than using all the groundwater usage data) improved the performance of the predictive model. The developed models can predict the future groundwater level based on the current amount of precipitation and groundwater use. Therefore, the models provide information on the soundness of the aquifer system, which will help to prepare management plans to maintain appropriate groundwater quantities.

• Journal of Soil and Groundwater Environment
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• v.19 no.5
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• pp.18-25
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• 2014

Traditional investigation procedures of soil and groundwater contamination are followed by soil gas sampling, soil sampling, groundwater sampling, establishment of monitoring wells, and groundwater monitoring. It often takes several weeks to obtain the analysis reports, and sometimes, it needs supplemental sampling and analysis to delineate the polluted area. Laser induced fluorescence (LIF) system is designed for the detection of free-phase petroleum pollutants, and it is suitable for on-site real-time site investigation when coupling with a direct push testing tool. Petroleum products always contain polycyclic aromatic hydrocarbon (PAH) compounds possessing fluorescence characteristics that make them detectable through LIF detection. In this study, LIF spectroscopy of 5 major fuel products was conducted to establish the databank of LIF fluorescence characteristic spectra, including gasoline, diesel, jet fuel, marine fuel and low-sulfur fuel. Multivariate statistical tools were also applied to distinguish LIF fluorescence characteristic spectra among the mixtures of selected fuel products. This study successfully demonstrated the feasibility of identifying fuel species based on LIF characteristic fluorescence spectra, also LIF seemed to be uncovered its powerful ability of tracing underground petroleum leakages.

• Journal of Soil and Groundwater Environment
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• v.26 no.6
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• pp.130-143
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• 2021

Wetlands are one of the most representative groundwater dependent ecosystems(GDEs) that require access to groundwater on a permanent or intermittent basis to maintain their biological communities and ecological processes. In this study, the seasonal characteristics of the GDEs in Baekseok Reservoir Wetland were evaluated through the monitoring of the temporal and spatial community of benthic macroinvertebrates in the wetland. The appearance of benthic macroinvertebrates appearance was changed seasonally depending on environmental factors such temperature, precipitation and water level for their habitat and it also showed the clear spatial difference in the wetland. The scores of Diversity index(H'), Richness Index (R1) and the Ecological score of benthic macroinvertebrates (TESB/AESB) were relatively high at St.3 and 4(i.e., north area) where groundwater inflows into wetland(i.e., high ²²²Rn conc.). The statistical analysis (ANOVA test and PCA) investigated the correlation among the benthic macroinvertebrates' community, groundwater level, wetland water level and water quality. The results showed that the community of benthic macroinvertebrates at St. 3 and 4 in Baekseok Reservoir Wetlands was spatially dependent on groundwater level and groundwater inflow. The characterization and assessment of GDEs requires understanding the hydrological, biogeochemical and biological process and this study will provide information for characterization and assessment of GDEs.

• The Journal of Engineering Geology
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• v.23 no.2
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• pp.137-147
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• 2013

For the effective management of groundwater resources, it is necessary to predict groundwater level fluctuations in response to rainfall events. In the present study, time series models using artificial neural networks (ANNs) and support vector machines (SVMs) have been developed and applied to groundwater level data from the Gasan, Shingwang, and Cheongseong stations of the National Groundwater Monitoring Network. We designed four types of model according to input structure and compared their performances. The results show that the rainfall input model is not effective, especially for the prediction of groundwater recession behavior; however, the rainfall-groundwater input model is effective for the entire prediction stage, yielding a high model accuracy. Recursive prediction models were also effective, yielding correlation coefficients of 0.75-0.95 with observed values. The prediction errors were highest for Shingwang station, where the cross-correlation coefficient is lowest among the stations. Overall, the model performance of SVM models was slightly higher than that of ANN models for all cases. Assessment of the model parameter uncertainty of the recursive prediction models, using the ratio of errors in the validation stage to that in the calibration stage, showed that the range of the ratio is much narrower for the SVM models than for the ANN models, which implies that the SVM models are more stable and effective for the present case studies.