• Geophysics and Geophysical Exploration
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• v.11 no.2
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• pp.85-92
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• 2008

Magnetotelluric (MT) methods are widely applied as an effective exploration technique to geothermal surveys. Two-dimensional (2-D) analysis is frequently used to investigate a complicated subsurface structure in a geothermal region. A 2-D finite-element method (FEM) is usually applied to the MT analysis, but we must pay attention to the accuracy of so-called auxiliary fields. Rodi (1976) proposed an algorithm of improving the accuracy of auxiliary fields, and named it as the MOM method. Because it introduces zeros into the diagonal elements of coefficient matrix of the FEM total equation, a pivoting procedure applied to the symmetrical band matrix makes the numerical solution far less efficient. The MOM method was devised mainly for the inversion analysis, in which partial derivatives of both electric and magnetic fields with respect to model parameters are required. In the case of forward modeling, however, we do not have to resort to the MOM method; there is no need of modifying the coefficient matrix, and the auxiliary fields can be elicited from the regular FEM solution. The computational efficiency of the MOM method, however, can be greatly improved through a sophisticated rearrangement of the total equation.

• Journal of the Korean GEO-environmental Society
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• v.19 no.11
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• pp.23-30
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• 2018

According to recent ground collapse occurrence, ground subsidence is increasing every year in downtown area, which is a social problem. The purpose of this study is to investigate the relationship between ground water level lowering and ground collapse through laboratory model experiments. After mixing 1:1 granite weathered soil with sand, sandy soil was formed as a relative density of 30%, 50%, and 80%. And then the changes of soil discharge with change of groundwater level were compared. The physical property of material of which particle distribution were well graded with maximu dry unit weight of $1.94kg/cm^3$ and internal friction angle of 37degrees. Ground water levels were measured at 10 cm, 20 cm, and 30 cm from the bottom. As a result, the experiment shows that the higher the groundwater level works the higher the discharge velocity and the magnitude of underground cavity also increases with elapsed time. Finally, the cumulative quantity of soil discharge occurred up to 30 kg at the elapsed time, 35 minutes. It was also confirmed that the range of ground collapse increased due to soil discharge with ground water level lowering.

• Journal of Soil and Groundwater Environment
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• v.6 no.3
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• pp.3-12
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• 2001

This study conducted to Investigate the movement of fertilized nutrients in a volcanic ash soil in Jeju using by the pressure-vacuum soil water sampler. The percolated water to measure the ion concentration of leachates was taken from a lysimeter at depths of 20, 40, 60, 80, 100 and 120 cm in the soil in where a corn and potato were cultivated as a preceding and succeeding crop, respectively. Fertilizers of N-$P_2$O$_{5}$-$K_2$O were applied at the rate of 36-30-30 kg $10a^{-1}$ for the corn and 28-22-24 kg $10a^{-1}$ for the potato prior to planting of both crops. The highest concentrations of Cl , $NO_3$-N, $Ca^{+2}$ and $K^+$ in percolates were showed at 20cm and 40cm in soil depth at one month after fertilizing, and then gradually moved and reduced into below soil depths. At 5.5 months after fertilization, the concentrations in all soil depths were similar with the value of before fertilization. At depth of 120cm, the concentration of NO$_3$-N and the other cations in leachate was highest 1 to 1.5 months after fertilization. pH in percolated water was negatively correlated with NO$_3$-N concentration while the concentration of $NO_3$-N showed positive correlation between Cl, $Ca^{+2}$ and $Mg^{+2}$ concentrations. This result indicated that those cations can be leached out by accompanied with $NO_3$-N.

• Journal of Soil and Groundwater Environment
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• v.14 no.5
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• pp.18-28
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• 2009

Both feasibility and accuracy of lumped approach to group 12 organic compounds in mixtures into a fewer number of pseudocompounds in sorption processes were evaluated using mixtures containing organic compounds with various physicochemical properties and low-surface-area mineral sorbents. The lumped approach for sorption to simulated mineral sorbents was developed by cluster analysis from statistics. Using the lumped approach, the sorption estimated from both reduced number of pseudocompounds and their sorption parameters (i.e., $K_f$, n) can approximate sorption behavior of complex organic mixtures. Additionally, the pseudocompounds for various mixtures to different types of low-surface-area mineral sorbents can be estimated a priori from the physicochemical properties of organic compound (i.e., ${\gamma_w}^{sat}$). Therefore, the lumped approach may help to simplify the complex fate and transport model of organic contaminant mixtures, reduce experimental efforts, and yet provide results that are statistically identical for practical purposes. Further research is warranted to enhance the accuracy of lumped approach using the multiple regression analysis considering the H-bonding capacity, site concentrations, functional groups for mineral sorbents.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.581-593
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• 2006

Various geological thematic maps have been generated by interpolating sparsely sampled ground survey data and geostatistical kriging that can consider spatial correlation between neighboring data has widely been used. This paper applies multi-variate geostatistical algorithms to integrate secondary information with sparsely sampled ground survey data for geological thematic mapping. Simple kriging with local means and kriging with an external drift are applied among several multi-variate geostatistical algorithms. Two case studies for spatial mapping of groundwater level and grain size have been carried out to illustrate the effectiveness of multi-variate geostatistical algorithms. A digital elevation model and IKONOS remote sensing imagery were used as secondary information in two case studies. Two multi-variate geostatistical algorithms, which can account for both spatial correlation of neighboring data and secondary data, showed smaller prediction errors and more local variations than those of ordinary kriging and linear regression. The benefit of applying the multi-variate geostatistical algorithms, however, depends on sampling density, magnitudes of correlation between primary and secondary data, and spatial correlation of primary data. As a result, the experiment for spatial mapping of grain size in which the effects of those factors were dominant showed that the effect of using the secondary data was relatively small than the experiment for spatial mapping of groundwater level.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.164-175
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• 2019

The Tor Tong Daeng Irrigation Project with the irrigation area of 61,400 hectares is located in the Ping Basin of the Upper Central Plain of Thailand where farmers depended on both surface water and groundwater. In the drought year, water storage in the Bhumipol Dam is inadequate to allocate water for agriculture, and caused water deficit in many irrigation projects. Farmers need to find extra sources of water such as water from farm pond or groundwater as a supplement. The operation of Bhumipol Dam and irrigation demand estimation are vital for irrigation water allocation to help solve water shortage issue in the irrigation project. The study aims to determine the smart dam operation system to mitigate water shortage in this irrigation project via introduction of machine learning to improve dam operation and irrigation demand estimation via soil moisture estimation from satellite images. Via ANN technique application, the inflows to the dam are generated from the upstream rain gauge stations using past 10 years daily rainfall data. The input vectors for ANN model are identified base on regression and principal component analysis. The structure of ANN (length of training data, the type of activation functions, the number of hidden nodes and training methods) is determined from the statistics performance between measurements and ANN outputs. On the other hands, the irrigation demand will be estimated by using satellite images, LANDSAT. The Enhanced Vegetation Index (EVI) and Temperature Vegetation Dryness Index (TVDI) values are estimated from the plant growth stage and soil moisture. The values are calibrated and verified with the field plant growth stages and soil moisture data in the year 2017-2018. The irrigation demand in the irrigation project is then estimated from the plant growth stage and soil moisture in the area. With the estimated dam inflow and irrigation demand, the dam operation will manage the water release in the better manner compared with the past operational data. The results show how smart system concept was applied and improve dam operation by using inflow estimation from ANN technique combining with irrigation demand estimation from satellite images when compared with the past operation data which is an initial step to develop the smart dam operation system in Thailand.

• Korean Journal of Environmental Agriculture
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• v.40 no.4
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• pp.248-259
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• 2021

BACKGROUND: Contaminated water was a major source of food-borne pathogens in various recent fresh produce-related outbreaks. This study was conducted to investigate the microbial contamination level and correlations between the level of sanitary indicator bacteria and the detection ratio of pathogens in agricultural water by logistic regression analysis. METHODS AND RESULTS: Agricultural water was collected from 457 sites including surface water (n=300 sites) and groundwater (n=157 sites) in South Korea from 2018 to 2020. Sanitary indicator bacteria (total coliform, fecal coliform, and Escherichia coli) and food-borne pathogens (pathogenic E. coli, E. coli O157:H7, Salmonella spp., and Listeria monocytogenes) were analyzed. In surface water, the coliform, fecal coliform, and E. coli were 3.27±0.89 log CFU/100 mL, 1.90±1.19 log CFU/100 mL, and 1.39±1.26 log CFU/100 mL, respectively. For groundwater, three kinds of sanitary indicators ranged in the level from 0.09 - 0.57 log CFU/100 mL. Pathogenic E. coli, Salmonella and Listeria monocytogenes were detected from 3%-site, 1.5%- site, and 0.6%-site water samples, respectively. According to the results of correlations between the level of sanitary indicator bacteria and the detection ratio of pathogens by logistic regression analysis, the probability of pathogen detection increased individually by 1.45 and 1.34 times as each total coliform and E. coli concentration increased by 1 log CFU/100mL. The accuracy of the model was 70.4%, and sensitivity and specificity were 81.5% and 51.7%, respectively. CONCLUSION(S): The results indicate the need to manage the microbial risk of agricultural water to enhance the safety of fresh produce. In addition, logistic regression analysis is useful to analyze the correlation between the level of sanitary indicator bacteria and the detection ratio of pathogens in agricultural water.

• Tunnel and Underground Space
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• v.33 no.5
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• pp.388-398
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• 2023

The changes in groundwater flow due to mining development act as a contributing factor to major issues such as ground subsidence, strength reduction and collapse. For the sustainable mining development, measures for dealing with fluctuations in seasonal underground water inflow, power losses, pump damage, and unexpected increases in inflow must be put in place. In this study, the aim is to identify the causes of underground seepage through the examination of hydrological connectivity between the study area and nearby limestone mine. A tracer tes for assessing subsurface connectivity has been planned. A variety of tracers, such as dyes and ions, were applied in lab test to select the optimal tracer material, and a hydrological model of the study area was implemented through field test. Finally, the hydrological connectivity between the external stream and underground water in the mine was analyzed.

• Journal of the Korean Chemical Society
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• v.40 no.2
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• pp.101-108
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• 1996

The chemical characteristics and age dating of the thermal springwater developed recently in Chullabukdo were investigated. The temperature range of the thermal springwater was found 27∼29$^{\circ}C$, indicating a low temperature thermal springwater. The concentration of $F^-$ ion in the springwater was found relatively high in the range of 2∼3 ppm, but $NO_3^-$ ion was nearly not detected. The concentration range of $SO_4^{2-}$ ion was 0.02∼23 ppm, among which $SO_4^{2-}$ content of $Y_3$ was found very high compared to that of other springwater, since this site is known as a sulfur spring. $HCO_3^-$ ion content was found 2∼5 times higher than that of groundwater. $Y_1,\;Y_3,\;Y_5,\;Y_2,\;Y_4,\;and\;Y_8$, were classified as $HCO_3^-$ type, $Y_6$ as $CI^-$type, and $Y_7$, as no domonant type by classification diagram for anion and cation facies. From the results of age dating on the basis of the mean tritium level of precipitation and thermal springs, $Y_1$ was identified as the oldest thermal spring (-89 years) and $Y_7$ was identified as -89 years and $Y_7$ was -1 year using dispersive model. The results calculated by two models agreed well each other.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.507-519
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• 2013

This study is to evaluate agricultural water supply capacity in Geum river basin (9,865 $km^2$), one of the 5 big river basin of South Korea using MODSIM-DSS (MODified SIMyld-Decision Support System) model. The model is a generalized river basin decision support system and network flow model developed at Colorado State University designed specifically to meet the growing demands and pressures on river basin management. The model was established by dividing the basin into 14 subbasins and the irrigation facilities viz. agricultural reservoirs, pumping stations, diversions, culverts and groundwater wells were grouped and networked within each subbasin and networked between subbasins including municipal and industrial water supplies. To prepare the inflows to agricultural reservoirs and multipurpose dams, the Soil and Water Assessment Tool (SWAT) was calibrated using 6 years (2005-2010) observed dam inflow and storage data. By MODSIM run for 8 years from 2004 to 2011, the agricultural water shortage had occurred during the drought years of 2006, 2008, and 2009. The agricultural water shortage could be calculated as 282 $10^6m^3$, 286 $10^6m^3$, and 329 $10^6m^3$ respectively.