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Seoul, South Korea

Jo Y.-J.,Kangwon National University | Lee J.-Y.,Kangwon National University | Yi M.-J.,GeoGreen21 Co. | Kim H.-S.,Jungwon University | Lee K.-K.,Seoul National University
Geosciences Journal | Year: 2010

We examined levels of soil contamination by trichloroethylene (TCE) at an industrial complex in Wonju, Korea. The examination was focused on the surrounding area of an asphalt laboratory where TCE had been used as a solvent for testing the asphalt quality. TCE contamination in soil was found at depths of 1~5 m and ranged between 0.13 and 14,702.82 mg/kg. However, the soil contamination was restricted in immediate proximity of the laboratory. Batch isotherm experiments showed that there was a linear relationship between the sorbed concentration and the aqueous TCE concentration, which is typical for non-polar organic chemicals such as TCE. The distribution coefficient (Kd) ranged between 0.375 and 0.639 L/kg and increased with depth. Considering TCE concentration in deep soil, Kd and higher groundwater level, TCE concentration in groundwater can reach up to 19.36 mg/L. In addition, highly weathered and fractured rocks, where groundwater level formed, underlain by the contaminated soil zone can facilitate vertical TCE movement and form an extensive groundwater plume in the downgradient area. As a source removal measure, the contaminated soil at the presumably hot source zone had been remediated in 2004. © 2010 The Association of Korean Geoscience Societies and Springer. Source


Yoon H.,Seoul National University | Jun S.-C.,GeoGreen21 Co. | Hyun Y.,Seoul National University | Bae G.-O.,Seoul National University | Lee K.-K.,Seoul National University
Journal of Hydrology | Year: 2011

We have developed two nonlinear time-series models for predicting groundwater level (GWL) fluctuations using artificial neural networks (ANNs) and support vector machines (SVMs). The models were applied to GWL prediction of two wells at a coastal aquifer in Korea. Among the possible variables (past GWL, precipitation, and tide level) for an input structure, the past GWL was the most effective input variable for this study site. Tide level was more frequently selected as an input variable than precipitation. The results of the model performance show that root mean squared error (RMSE) values of ANN models are lower than those of SVM in model training and testing stages. However, the overall model performance criteria of the SVM are similar to or even better than those of the ANN in model prediction stage. The generalization ability of a SVM model is superior to an ANN model for input structures and lead times. The uncertainty analysis for model parameters detects an equifinality of model parameter sets and higher uncertainty for ANN model than SVM in this case. These results imply that the model-building process should be carefully conducted, especially when using ANN models for GWL forecasting in a coastal aquifer. © 2010 Elsevier B.V. Source


Dynamic variation in the saltwater-freshwater transition zone below a seafront beach in South Korea was investigated with long-term monitoring of the groundwater in relation to the precipitation, wave height, and tide. Correlation, spectral analysis, and regression analysis of monitoring data were performed to deduce the relationships between these factors. The general shape of the transition zone was affected by the seasonal groundwater levels, but temporary fluctuations were predominantly affected by local rising-groundwater-level events. The distinct increases in the groundwater level were closely related to the wave height. Different patterns of electrical conductivity (EC) change were detected in the shallow and deep zones, and these differences indicated that the transition zone was highly dynamic. The EC values at shallow depths were temporarily increased by the wave setup and tidal fluctuations during the rising-groundwater events, but the EC at greater depths was reduced by the seaward or downward movement of the relative freshwater. In exceptional cases, during extreme increases in the groundwater level resulting from seawater flooding, the rapid downward flow of the flooding saltwater through the well bore caused synchronous EC fluctuations at all depths. © 2013 Springer-Verlag Berlin Heidelberg. Source


Lee S.,Korea Institute of Geoscience and Mineral Resources | Song K.-Y.,Korea Institute of Geoscience and Mineral Resources | Kim Y.,GeoGreen21 Co. | Park I.,University of Seoul
Hydrogeology Journal | Year: 2012

An artificial neural network model (ANN) and a geographic information system (GIS) are applied to the mapping of regional groundwater productivity potential (GPP) for the area around Pohang City, Republic of Korea. The model is based on the relationship between groundwater productivity data, including specific capacity (SPC) and its related hydrogeological factors. The related factors, including topography, lineaments, geology, and forest and soil data, are collected and input into a spatial database. In addition, SPC data are collected from 44 well locations. The SPC data are randomly divided into a training set, to analyse the GPP using the ANN, and a test set, to validate the predicted potential map. Each factor's relative importance and weight are determined by the back-propagation training algorithms and applied to the input factor. The GPP value is then calculated using the weights, and GPP maps are created. The map is validated using area under the curve analysis with the SPC data that have not been used for training the model. The validation shows prediction accuracies between 73.54 and 80.09 %. Such information and the maps generated from it could serve as a scientific basis for groundwater management and exploration. © 2012 Springer-Verlag. Source


Yang J.-H.,Seoul National University | Jun S.-C.,GeoGreen21 Co. | Kwon H.-P.,GeoGreen21 Co. | Lee K.-K.,Seoul National University
Environmental Earth Sciences | Year: 2014

Depth-discrete tracing of residual dense non-aqueous phase liquid (DNAPL) sources in the subsurface is of great importance in making decisions related to contaminated groundwater remediation. Temporal variations in the natural tracer 222Rn and contaminant concentrations in groundwater contaminated with multiple chlorinated contaminants, such as trichloroethene, carbon tetrachloride, and chloroform, were examined to trace residual multiple DNAPL contaminants at an industrial complex in Wonju, Korea. The 222Rn activities and multiple DNAPL concentrations in the groundwater fluctuated irregularly according to the groundwater recharge. The natural tracer 222Rn in groundwater present in the soil layer, originating from the underlying crystalline biotite granite, had a wide range from 29,000 to 179,000 Bq/m3, and total concentrations of chlorinated solvents ranged from 0.06 to 17.77 mg/l, indicating the ambiguous results of 222Rn for tracing the residual DNAPL sources. In this paper, a method is presented to locate zones with a high probability of containing depth-discrete residual multiple DNAPL sources using 222Rn and considering relative contaminant concentrations. The results demonstrate that the combination of the 222Rn activities as a natural tracer and the relative contaminant concentrations is able to be used as a useful tool for tracing residual DNAPLs. © 2013 Springer-Verlag Berlin Heidelberg. Source

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