• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.4
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• pp.103-112
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• 1989

A numerical model for Steady state groundwater flow has been established to understand the groundwater flow phenomena near a radioactive waste repository. The integrated finite difference method based on a network composed of nodes and members was applied to investigate groundwater flow in homogeneous, heterogeneous and layered media. Its numerical solution was in good agreement with analytic solution. Physical phenomena associated in the groundwater flow depending on both hydraulic characteristics and effects of fractured zone were also investigated. A method by which feasible groundwater flow paths can be identified was developed. This method used the composite network for the geologic media near a repository and the direction of computed groudwater velocity. Groundwater velocity and travel time were predicted for the possible pathway form a repository to a biosphere.

• Journal of Korea Water Resources Association
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• v.34 no.3
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• pp.275-285
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• 2001

Since the majority of streamflow during dry periods is provided by groundwater storage, the streamflow depends on a basin moisture state recharged from rainfall during wet periods. This hydrologic characteristics dives good condition to predict long-term streamflow if the basin state like groundwater recharge is known in advance. The objective of this study is to examine groundwater recharge effect to monthly streamflow, and to attempt monthly streamflow prediction using estimated groundwater recharge. The ground water recharge is used as an independent variable with streamflow and precipitation to construct multiple regression models for the prediction. Correlation analysis was performed to assess the effect of groundwater carry-over to streamflow and to establish the associations among independent variables. The predicted streamflow shows that the multiple regression model involved groundwater recharge gives improved results comparing to the model only using streamflow and precipitation as independent variables. In addition, this paper shows that the prediction model with the effect of groundwater carry-over taken into account can be developed using only precipitation.

• Journal of Korean Society on Water Environment
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• v.30 no.5
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• pp.549-558
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• 2014

Occurrence frequency of flood and drought tends to increase in last a few decades, leading to social and economic damage since the abnormality of climate changes is one of the causes for hydrologic facilities by exceedance its designed tolerance. Soil and Water Assessment Tool (SWAT) model was used in the study to estimate temporal variance of groundwater recharge and baseflow. It was limited to consider recession curve coefficients in SWAT model calibration process, thus the recession curve coefficient was estimated by the Baseflow Filter Program (BFLOW) before SWAT model calibration. Precipitation data were estimated for 2014 to 2100 using three models which are GFDL-ESM2G, IPSL-CM5A-LR, and MIROC-ESM with Representative Concentration Pathways (RCP) scenario. SWAT model was calibrated for the Soyang watershed with NSE of 0.83, and $R^2$ of 0.89. The percentage to precipitation of groundwater recharge and baseflow were 27.6% and 17.1% respectively in 2009. Streamflow, groundwater recharge, and baseflow were estimated to be increased with the estimated precipitation data. GFDL-ESM2g model provided the most large precipitation data in the 2025s, and IPSL-CM5A-LR provided the most large precipitation data in the 2055s and 2085s. Overall, groundwater recharge and baseflow displayed similar trend to the estimated precipitation data.

• The Journal of Engineering Geology
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• v.27 no.3
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• pp.313-322
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• 2017

The purpose of this study is to estimate the surface and subsurface flows through the modelling of the model area and facility agricultural complex, and to calculate the groundwater recharge rate through water budget analysis. From results of surface flow modeling, the surface water is flowed to a depth of about 1 to 5 meters from the upper region (northeast) to the lower region (southeast) of the Miryang River. At the M01 point (upper), the observed surface water flux and the model surface water flux are consistent. At the M02 points (lower), the observed surface water flux and the model surface water flux are a difference of 1%. From results of subsurface flow modeling, the depth of groundwater is similar to elevation in the river and higher to the forest area. Ground water depth considering groundwater pumping is that the model values appears higher than the observed values to be within 1.5 m. From results of surface-subsurface integrated modeling, the groundwater recharge area is estimated about 90% of the model area, and the groundwater recharge rate is estimated $1.92{\times}10^5m^3/day$. From results of annual water budget analysis, the groundwater recharge rate per unit area is estimated to be 503.9 mm/year, and average annual rainfall is estimated at around 39%.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.09a
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• pp.99-101
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• 2003

Unsaturated hydraulic conductivity models have been widely used for the numerical modeling of water flow and contaminant transport in soils. In this study, a simple hydraulic conductivity model is developed by using information of particle-size distribution from the lognormal distribution model and its results are compared with those from the Kosugi-Mualem (KM) model. The accuracy of the proposed model is verified for observed data chosen from the international UNSODA database. Results showed that the proposed model produces adequate predictions of hydraulic conductivities. Performance of this model is generally better than the KM function.

• Geomechanics and Engineering
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• v.17 no.2
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• pp.181-194
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• 2019

Due to the seepage of groundwater, the resisting force of slopes decreases and the sliding force increases, resulting in significantly reduced slope stability. The instability of most natural slopes is closely related to the influence of groundwater. Therefore, it is important to study slope stability under groundwater seepage conditions. Thus, using a simplified seepage model of groundwater combined with the analysis of stresses on the slip surface, the limit equilibrium (LE) analytical solutions for two- and three-dimensional slope stability under groundwater seepage are deduced in this work. Meanwhile, the general nonlinear Mohr-Coulomb (M-C) strength criterion is adopted to describe the shear failure of a slope. By comparing the results with the traditional LE methods on slope examples, the feasibility of the proposed method is verified. In contrast to traditional LE methods, the proposed method is more suitable for analyzing slope stability under complex conditions. In addition, to facilitate the optimization of drainage design in the slope, stability charts are drawn for slopes with different groundwater tables. Furthermore, the study concluded that: (1) when the hydraulic gradient of groundwater is small, the effect on slope stability is also small for a change in the groundwater table; and (2) compared with a slope without a groundwater table, a slope with a groundwater table has a larger failure range under groundwater seepage.

• Journal of Korea Water Resources Association
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• v.53 no.4
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• pp.273-283
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• 2020

Quantitative forecasting of groundwater levels for the assessment of groundwater variation and vulnerability is very important. To achieve this purpose, various time series analysis and machine learning techniques have been used. In this study, we developed a prediction model based on LSTM (Long short term memory), one of the artificial neural network (ANN) algorithms, for predicting the daily groundwater level of 11 groundwater wells in Hankyung-myeon, Jeju Island. In general, the groundwater level in Jeju Island is highly autocorrelated with tides and reflected the effects of precipitation. In order to construct an input and output variables based on the characteristics of addressing data, the precipitation data of the corresponding period was added to the groundwater level data. The LSTM neural network was trained using the initial 365-day data showing the four seasons and the remaining data were used for verification to evaluate the fitness of the predictive model. The model was developed using Keras, a Python-based deep learning framework, and the NVIDIA CUDA architecture was implemented to enhance the learning speed. As a result of learning and verifying the groundwater level variation using the LSTM neural network, the coefficient of determination (R²) was 0.98 on average, indicating that the predictive model developed was very accurate.

• Environmental Engineering Research
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• v.15 no.2
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• pp.117-121
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• 2010

The continual extraction and indiscriminante use of groundwater for residential sectors could cause a decrease in the groundwater level in Para$\tilde{n}$aque river and Las Para$\tilde{n}$aque City; and allows saltwater to penetrate into the aquifer due to the proximity of Manila Bay. This study models the present condition and extent of saltwater intrusion in the aquifer bounded by Para$\tilde{n}$aque river River and Manila Bay. The model is simulated using a 3D finite element modeling software (FEMWATER) that is capable of modeling the groundwater flow condition in the aquifer. Moreover, the model can also be used to predict the future condition of the aquifer for better groundwater management. This study aims to raise public awareness of the extent of the problem and the possible side effects incurred. The model will serve as a basis for further studies on remediation techniques and saltwater intrusion control in the coastal aquifer of Para$\tilde{n}$aque river City.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05b
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• pp.1034-1040
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• 2002

A rainwater recharge model, which is combined with the quasi-three dimensional unconfined groundwater flow, is proposed in the present paper. The water budget in the catchments of the planned new campus of Kyushu University is evaluated by the present method that calculates both the surface runoff and groundwater flow simultaneously. The results obtained in the present study reveal that the calculated monthly and annual runoff discharges agree reasonably well with the observed discharge. Combining the rainwater recharge model, the two-phase groundwater flow equation is numerically solved f3r the entire area including the low land where the salt water intrusion is observed. The calculated depth of the salt-fresh interface agrees reasonably well with the observed ones at several cross sections. On the other hand, however, it is found that the calculated water budget remains uncertain because of lack of information on the accurate potential evapotranspiration including rainfall interception. In conclusion, however, it is found that the proposed method is applicable for the areas where the horizontal flow is dominant and the interface is assumed to be sharp.

• Geomechanics and Engineering
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• v.35 no.5
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• pp.499-509
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• 2023

The objective of this study is to perform outlier analysis to obtain the distribution of groundwater levels through the best model. The groundwater levels are measured in 10, 25 and 30 piezometers in Seoul, Daejeon and Suncheon in South Korea. Fifty-eight empirical distribution functions were applied to determine a suitable fit for the measured groundwater levels. The best fitted models based on the measured values are determined as the Generalized Pareto distribution, the Johnson SB distribution and the Normal distribution for Seoul, Daejeon and Suncheon, respectively; the reliability is estimated through the Anderson-Darling method. In this study, to choose the appropriate confidence interval, the relationship between the amount of outlier data and the confidence level is demonstrated, and then the 95% is selected at a reasonable confidence level. The best model shows a smaller error ratio than the GEV while the Mahalanobis distance and outlier labelling methods results are compared and validated. The outlier labelling and Mahalanobis distance based on median shown higher validated error ratios compared to their mean equivalent suggesting, the methods sensitivity to data structure.