• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2002.09a
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• pp.32-35
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• 2002

In order to characterize the migration of DNAPL in rock fractures, the dynamic macromodified invasion percolation (DMMIP) model, that is able to reflect the viscous force of groundwater in a fracture network, is suggested. DMMIP simulations are verified against the laboratory expenments, which shows a good qualitative and quantitative agreement.

• Economic and Environmental Geology
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• v.44 no.5
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• pp.433-442
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• 2011

In Korea, groundwater management has been conducted based on the estimation of annual average of groundwater recharge. Since groundwater recharge and surface water-groundwater interactions show spatiotemporal variation, continuous monitoring and dynamic analysis must be carried out to evaluate the sustainability of groundwater resources. In this study, SWAT-MODFLOW, an integrated surface water-groundwater model was used to analyze surface-groundwater interactions for various groundwater pumping scenarios in Musimcheon watershed. When current usage is applied, the baseflow reduction is about 16%, and annual averaged storage reduction is about 27 mm for whole watershed. As a holistic approach to groundwater sustainability considers the hydrological, ecological, socioeconomic, technological aspects of groundwater utilization, the exploitable groundwater should be determined by physical analysis as well as social compromise in a community.

• Journal of Soil and Groundwater Environment
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• v.12 no.4
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• pp.54-59
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• 2007

In this study, a semi-analytical model to address groundwater level fluctuations in response to precipitations and its infiltration is developed through mathematical modeling based on water balance equation. The developed model is applied to a prediction of groundwater level fluctuations in Hongcheon area. The developed model is calibrated through a nonlinear parameter estimator by using daily precipitation rates and groundwater fluctuations data of a same year 2003. The calibrated input parameters are directly applied to the prediction of groundwater fluctuations of year 2004 and the simulated curve successfully mimics the observed. The developed model is also applied to practical problems such as a prediction of a effect of reduced recharge due to surface coverage change and a induced water level reduction. Through this study, we found that recharge to precipitation ratio is not a constant and may be a function of a precipitation pattern.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.583-592
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• 2018

Recently, concern has arisen regarding the lowering of groundwater levels in the hinterland caused by the development of high-capacity radial collector wells in riverbank filtration areas. In this study, groundwater levels are estimated using Modflow software in relation to the water volume pumped by the radial collector well in Anseongcheon Stream. Using the water volume data, an artificial neural network (ANN) model is developed to determine the amount of water that can be withdrawn while minimizing the reduction of groundwater level. We estimate that increasing the pumping rate of the horizontal well HW-6, which is drilled parallel to the stream direction, is necessary to minimize the reduction of groundwater levels in wells OW-7 and OB-11. We also note that the number of input data and the classification of training and test data affect the results of the ANN model. This type of approach, which supplements ANN modeling with observed data, should contribute to the future groundwater management of hinterland areas.

• Journal of the Korean Society of Groundwater Environment
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• v.2 no.1
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• pp.9-13
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• 1995

In the stream-aquifer setting, this study evaluated the effects of spatial variability in nonpoint sources and hydraulic conductivity on groundwater outflow concentration history. Monte Carlo experiments based on the advection-dispersion equation were used to determine the statistical moments of groundwater outflow concentration history. The comparison between a spatially distributed model and spatially integrated model (SID) was made in order to examine the possibility of applying SID to the problems of nonpoint source groundwater pollution.

• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.6
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• pp.88-98
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• 1997

In this study, pumping capacity in the area of natural river estuary is estimated by the quantitative analysis using finite element method. The study area is Iga-ri pumping station in the estuary of Seojung-chun which runs to the East coast. First of aH, hydraulic properties and effects of different seawater levels are analyzed in this area. Variations of groundwater level caused by pumping and properties of seawater intrusion are analyzed, then compared the case of reinforcing the existing intake weir with the case of setting up an weir at the upper stream. The observed data of groundwater drawdown caused by pumping during drought period and seawater intrusion are compared with results of the analysis done by groundwater model using finite element method, and it is found that both are similar. Accordingly, groundwater model used in this study reflects well the variation of groundwater level caused by pumping.

• Journal of Environmental Science International
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• v.23 no.4
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• pp.625-635
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• 2014

Temporal variation of groundwater levels in Jeju Island reveals time-delaying and dispersive process of recharge, mainly caused by the hydrogeological feature that thickness of the unsaturated zone is highly variable. Most groundwater flow models have limitations on delineating temporal variation of recharge, although it is a major component of the groundwater flow system. A new mathematical model was developed to generate time series of recharge from precipitation data. The model uses a convolution technique to simulate the time-delaying and dispersive process of recharge. The vertical velocity and the dispersivity are two parameters determining the time series of recharge for a given thickness of the unsaturated zone. The model determines two parameters by correlating the generated recharge time series with measured groundwater levels. The model was applied to observation wells of Jeju Island, and revealed distinctive variations of recharge depending on location of wells. The suggested model demonstrated capability of the convolution method in dealing with recharge undergoing the time-delaying and dispersive process. Therefore, it can be used in many groundwater flow models for generating a time series of recharge.

• 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.

• Economic and Environmental Geology
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• v.53 no.3
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• pp.245-258
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• 2020

In this study, a data-driven response surface method using the results acquired from the numerical simulation is developed to evaluate the potential storage capacity of groundwater due to the construction of a groundwater dam. The hydraulic conductivities of alluvium and basement rock, depth and slope of the channel are considered as the natural conditions of the location for groundwater dam construction. In particular, the probability models of the hydraulic conductivities and the various types of geometry of the channel are considered to ensure the reliability of the numerical simulation and the generality of the developed estimation model. As the results of multiple simulations, it can be seen that the hydraulic conductivity of basement rock and the depth of the channel greatly influence to the groundwater storage capacity. In contrast, the slope of the channel along the groundwater flow direction shows a relatively lower impact on the storage capacity. Based on the considered natural conditions and the corresponding numerical simulation results, the storage capacity estimation model is developed applying an artificial neural network as the nonlinear regression model for training. The developed estimation model shows a high correlation coefficient (>0.9) between the simulated and the estimated storage amount. This result indicates the superiority of the developed model in evaluating the storage capacity of the potential location for groundwater dam construction without the numerical simulation. Therefore, a more objective and efficient comparison for the storage capacity between the different potential locations can be possibly made based on the developed estimation model. In line with this, the proposed method can be an effective tool to assess the optimal location of groundwater dam construction across Korea.

• The Journal of Engineering Geology
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• v.21 no.4
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• pp.305-312
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• 2011

Because groundwater recharge shows spatial-temporal variability due to climatic conditions, it is necessary to investigate land use and hydrogeological heterogeneity, and estimate the spatial variability in the daily recharge rate based on an integrated surface-groundwater model. The integrated SWAT-MODFLOW model was applied to compute physically based daily groundwater recharge in the Jincheon region. The temporal variations in estimated recharge were calibrated using the observed groundwater head at several National Groundwater Monitoring Stations and at automatic groundwater-monitoring sites constructed during the Basic Groundwater Investigation Project (2009-2010). For the whole Mihocheon watershed, including the Jincheon region, the average groundwater recharge rate is estimated to be 20.8% of the total rainfall amount, which is in good agreement with the analytically estimated recharge rate. The proposed methodology will be a useful tool in the management of groundwater in Korea.