• Water Engineering Research
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• v.6 no.2
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• pp.39-48
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• 2005

The Brazos River is one of the longest rivers contained entirely in the state of Texas, flowing over 700 miles from northwest Texas to the Gulf of Mexico. Today, the Brazos River Authority and Texas Commission on Environmental Quality interest in drought protection plan, waterpower project, and allowing the appropriation of water system-wide and water right within the Brazos River Basin to meet water needs of customers like farmers and local civilians in the future. Especially, this purpose of this paper primarily intended to provide the data for the engineering guidelines and make easily geological mapping tool. In the Brazos River basin, many stream-flow gage station sites are not working, and they can not provide stream-flow data sets enough for development of the Probable Maximum Flood (PMF) for use in the evaluation of proposed and existing dams and other impounding structures. Integrated GIS-Spatial Interpolation (GIS-SI) tool are composed of two parts; (1) extended GIS technique (new making interface for hydrological regionalization parameters plus classical GIS mapping skills), (2) Spatial Interpolation technique using weighting factors from kriging method. They are obtained from the relationship among location and elevation of geological watershed and existing stream-flow datasets. GIS-SI technique is easily used to compute parameters which get drainage areas, mean daily/monthly/annual precipitation, and weighted values. Also, they are independent variables of multiple linear regressions for simulation at un gaged stream-flow sites. In this study, GIS-SI technique is applied to the Brazos river basin in Texas. By assuming the ungaged flow at the sites of Palo Pinto, Bryan and Needville, the simulated daily/monthly/annual time series are compared with observed time series. The simulated daily/monthly/annual time series are highly correlated with and well fitted to the observed times series.

• The Journal of Engineering Geology
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• v.21 no.4
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• pp.393-402
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• 2011

Asbestos is a toxic material that can lead to lung cancer and other diseases. There is no information regarding areas in Korea that contain asbestos in nature; consequently we need to manage such areas with care. The purpose of this study was to construct a local graded map of asbestos exposure risk based on the natural occurrence of asbestos in rocks. We first developed a means of evaluating the asbestos exposure risk and produced thematic maps based on a field survey. In addition, we constructed a knowledge base for asbestos through analysis, representation and processes about asbestos data and prepare for the development of an evaluation model for asbestos exposure risk. The spatial analysis of asbestos exposure risk is based on a weighted-overlay analysis using expert opinion and the literature, and a fuzzy-overlay analysis using the uncertainty in the data. The map of asbestos exposure risk, compiled according to the weighted and fuzzy operations, is expected to be used to ensure safety and to reduce the risk of exposure to asbestos.

• Economic and Environmental Geology
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• v.29 no.3
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• pp.345-355
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• 1996

The effectiveness of various electrode configurations in horizontal mappings and 1-D inversions of vertical sounding data for delineating 2-D structures was studied. Apparent resistivity values of three point, dipole-dipole, Wenner, and Schlumberger mappings were simulated for such structures as vertical dyke, tabular prism, buried vertical fault, ramp and complex structure by finite difference method (FDM) and they were compared with each other. Also 2-D cross sections for three structures obtained by interpolation of 1-D inverted sounding data in terms of three layers were compared for Schlumberger and Wenner arrays. On these cross sections, horizontal and vertical resistivity interfaces of the 2-D structures are revealed relatively clearly. Apparent resistivity curves of Schlumberger mapping show vertical resistivity discontinuities very well. On the whole, Schlumberger array is superior to the other arrays in electric sounding as well as mapping. This study clearly indicates that interpretations of 2-D structures based on 1-D inversion are possible.

• Economic and Environmental Geology
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• v.25 no.3
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• pp.283-296
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• 1992

The Keumryeong deposits is a low grade copper deposits in which copper minerals form disseminated grains and thin veinlets in felsic volcanics seem to be dacite. Alteration of the volcanics consists mainly pervasive propylitization and silicification. Potassic alteration characterized by biotite developed locally adjacent to southwestern contact of granodiorite body. Principal sulfide minerals in altered zone are mainly pyrite and lesser chalcopyrite. Chalcopyrite content in potassic zone is relatively higher than that of surrounding propylitized zone. Pyrite and chalcopyrite accompanies magnetite, molybdenite, sphalerite, pyrrhotite, arsenopyrite, pentlandite, marcasite, hematite, ilmenite, rutile, bismuthinite and native Bi as disseminations, veinlets and knots. Granodiorite body is propylitized and contains veinlets of pyrite, chalcopyrite and molybdenite. Fluid inclusions in sulfide-bearing quartz veinlets and quartz grains of felsic volcanics and granodiorite in altered zone consist of liquid-rich, vapor-rich, $CO_2-bearing$ and halite-bearing inclusions. These four types of inclusion intimately associated on a microscopic scale and indicate condensing or boiling of ore fluid during mineralization. Homogenization temperature of coexisting fluid inclusions are mostly in the range of 350 to $450^{\circ}C$. High salinity fluid contains 28.6 to 48.4 weight percent NaCI equivalent and moderate salinity fluid cotains 0.5 to 12.5 weight percent NaCl equivalent. Pressure estimated from $CO_2$ mole fraction of $CO_2-bearing$ inclusion range 160 to 375 bars. The Kigu copper deposits is a fissure filling copper vein developed 500 m south from the Keumryong deposits. Mineralogy and fluid inclusion data of the Kigu deposits are similar to that of the Keumryeong deposits. Homogenization temperature of fluid inclusions from the Kigu deposits are reasonable agreement with temperature estimated from sulfidation curve of cubanite-chalcopyrite-pyrite-pyrrhotite and pyrite-pyrrhotite mineral assemblages. Not only mineral occurrence and wall rock alteration in the Keumryeong deposits but also fluid inclusion data such as temperature, salinity, pressure and boiling evidences are similar to those of porphyry copper deposits.

• The Journal of Engineering Geology
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• v.24 no.1
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• pp.123-135
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• 2014

Earthquakes can cause serious loss of life and significant property damage. Thus, the study of active faults is important in evaluating future fault activity and hazards caused by future earthquake events. Structural mapping and the tracing of active faults are the primary steps in studies of active faults. Until now, active faults in South Korea have been mapped using aerial photography, satellite images, and low-quality DEMs. Lineament analysis as a means of identifying active faults is relatively difficult in Korea due to geological characteristics (weak tectonic activity) and dense vegetation cover. In this paper, we introduce the basic concept of the LiDAR technique (a new prospective remote sensing method) and a data analysis method that can overcome these problems. This paper will contribute to a better understanding of the airborne LiDAR technique and its application to South Korea. Some preliminary results from Korean and USA LiDAR data show the usefulness of this technique for tracing lineaments, active faults, and terraces in South Korea.

• Korean Journal of Remote Sensing
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• v.17 no.2
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• pp.165-181
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• 2001

Using a field spectrometer having a spectral range of 0.4$\mu\textrm{m}$~2.5$\mu\textrm{m}$ with a spectral resolution of 1nm, the researchers measured the reflectance of granite, andesitic rocks, sedimentary rocks, and pyrophyllite ore in the Ungsang area, Kyungsang Basin, South Korea. Spectral characteristics of the geological media were investigated from the analysis. The in-situ measured sites were selected in well exposed rock outcrops. In case of unfavorable weather conditions, rocks were sampled and remeasured under natural solar condition. The reflectance of field data was measurd at three sistes for granite, six sites for andesitic rock three sites for sedimentary rocks, and two sites for pyrophyllite ore. The vibrational absorption bands for pyrophyllite are detected in the spectral range of 2.0$\mu\textrm{m}$~2.5$\mu\textrm{m}$. The absorption band for granites in study area is not distinctive. The reflectance measured under normal field conditions showed strong absorption at wavelengths of 1.4$\mu\textrm{m}$ and 1.9$\mu\textrm{m}$ due to the effect of moisture in the atmosphere. After the bands of 1.4$\mu\textrm{m}$ and 1.9$\mu\textrm{m}$ were removed, Hull Quotient method was applied to characterize absorption bands. The reflectances of field data were calculated to estimate the band ratio corresponding to the Landsat TM and EOS Terra ASTER. The researchers suggest here that the TM band2, band3, band4, and band7 or ASTER band2, band3, band4, and band9 are the best combination for discriminating outcrops. The researchers tested and demonstrated using a Landsat TM image in the study area. For geologic applications, decorrelation stretch is also an effective tool to enhance the exposed rock mass in images.

• Geomechanics and Engineering
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• v.25 no.1
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• pp.1-16
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• 2021

Machine learning models have been widely used for landslide susceptibility assessment (LSA) in recent years. The large number of inputs or conditioning factors for these models, however, can reduce the computation efficiency and increase the difficulty in collecting data. Feature selection is a good tool to address this problem by selecting the most important features among all factors to reduce the size of the input variables. However, two important questions need to be solved: (1) how do feature selection methods affect the performance of machine learning models? and (2) which feature selection method is the most suitable for a given machine learning model? This paper aims to address these two questions by comparing the predictive performance of 13 feature selection-based machine learning (FS-ML) models and 5 ordinary machine learning models on LSA. First, five commonly used machine learning models (i.e., logistic regression, support vector machine, artificial neural network, Gaussian process and random forest) and six typical feature selection methods in the literature are adopted to constitute the proposed models. Then, fifteen conditioning factors are chosen as input variables and 1,017 landslides are used as recorded data. Next, feature selection methods are used to obtain the importance of the conditioning factors to create feature subsets, based on which 13 FS-ML models are constructed. For each of the machine learning models, a best optimized FS-ML model is selected according to the area under curve value. Finally, five optimal FS-ML models are obtained and applied to the LSA of the studied area. The predictive abilities of the FS-ML models on LSA are verified and compared through the receive operating characteristic curve and statistical indicators such as sensitivity, specificity and accuracy. The results showed that different feature selection methods have different effects on the performance of LSA machine learning models. FS-ML models generally outperform the ordinary machine learning models. The best FS-ML model is the recursive feature elimination (RFE) optimized RF, and RFE is an optimal method for feature selection.

• Economic and Environmental Geology
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• v.55 no.6
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• pp.701-716
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• 2022

This study investigated the distribution behaviors of PM2.5 and PM10 at two air quality monitoring sites, Go-eup (GO) and Backseokeup (BS), located in Yangju City, South Korea. The amounts of emissions sources of pollutants were analyzed based on the Clean Air Policy Support System (CAPSS), and the contribution rates of neighboring cities were enumerated in Yangju. Yangju has a geological basin structure, and it is a city with mixed urban and rural characteristics. The emission concentration of particulate matter was affected by geological and seasonal factors for all sites observed in this study. Therefore, these factors should be considered when establishing policies related to particulate matter. Because the official GO and BS station sites in Yangju are both situated in the southern part of the city, the representativeness of both stations was checked using correlation analysis for the measurement of PM2.5 and PM10 by considering two more sites-those of Bongyang-dong (BY) and the Gumjun (GJ) industrial complex. The data included discharge amounts for business types 4 and 5, which were not sufficiently considered in the CAPSS estimates. Because the 4 and 5 types of businesses represent over 92.6% of businesses in this city, they are workplaces in Yangju that have a significant effect on the total air pollutant emission. These types of businesses should be re-inspected as the main discharge sources in industry, and basic data accumulation should be carried out. Moreover, to manage the emission of particulate matter, attainable countermeasures for the main sources of these emissions should be prepared in a prioritized fashion; such countermeasures include prohibition of backyard burning, supervision of charcoal kilns, and management of livestock excretions and fugitive dust in construction sites and on roads. The contribution rates by neighboring cities was enumerated between 6.3% and 10.9% for PM2.5. Cooperation policies are thought to be required with neighboring cites to reduce particulate matter.

• Economic and Environmental Geology
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• v.56 no.5
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• pp.565-580
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• 2023

In this study, we reviewed and summarized comprehensive roles and importance of natural analogue studies for demonstrating the safety and improving the reliability of the safety for the deep geological disposal of high-level radioactive waste. We also investigated domestic and foreign status of natural analogue studies in order to study and substantiate complex and various radionuclide behaviors in subsurface disposal environments. In addition, we investigated and uranium behaviors in groundwater and rock in uranium deposits including domestic uranium deposits in Ogcheon Metamorphic Belt and biogeochemical interactions in geological environments. Although there are many limitations and uncertainties in directly using the information and data for uranium behaviors obtained from uranium deposits in the disposal safety assessment, the information and data can be utilized in the disposal safety assessment and safety case construction both in qualitative and partly quantitative ways.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.643-646
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• 2005

The gas hydrate exploration using seismic reflection data, the detection of BSR(Bottom Simulating Reflector) on the seismic section is the most important work flow because the BSR have been interpreted as being formed at the base of a gas hydrate zone. Usually, BSR has some dominant qualitative characteristics on seismic section i.e. Wavelet phase reversal compare to sea bottom signal, Parallel layer with sea bottom, Strong amplitude, Masking phenomenon above the BSR, Cross bedding with other geological layer. Even though a BSR can be selected on seismic section with these guidance, it is not enough to conform as being true BSR. Some other available methods for verifying the BSR with reliable analysis quantitatively i.e. Interval velocity analysis, AVO(Amplitude Variation with Offset)analysis etc. Usually, AVO analysis can be divided by three main parts. The first part is AVO analysis, the second is AVO modeling and the last is AVO inversion. AVO analysis is unique method for detecting the free gas zone on seismic section directly. Therefore it can be a kind of useful analysis method for discriminating true BSR, which might arise from an Possion ratio contrast between high velocity layer, partially hydrated sediment and low velocity layer, water saturated gas sediment. During the AVO interpretation, as the AVO response can be changed depend upon the water saturation ratio, it is confused to discriminate the AVO response of gas layer from dry layer. In that case, the AVO modeling is necessary to generate synthetic seismogram comparing with real data. It can be available to make conclusions from correspondence or lack of correspondence between the two seismograms. AVO inversion process is the method for driving a geological model by iterative operation that the result ing synthetic seismogram matches to real data seismogram wi thin some tolerance level. AVO inversion is a topic of current research and for now there is no general consensus on how the process should be done or even whether is valid for standard seismic data. Unfortunately, there are no well log data acquired from gas hydrate exploration area in Korea. Instead of that data, well log data and seismic data acquired from gas sand area located nearby the gas hydrate exploration area is used to AVO analysis, As the results of AVO modeling, type III AVO anomaly confirmed on the gas sand layer. The Castagna's equation constant value for estimating the S-wave velocity are evaluated as A=0.86190, B=-3845.14431 respectively and water saturation ratio is $50\%$. To calculate the reflection coefficient of synthetic seismogram, the Zoeppritz equation is used. For AVO inversion process, the dataset provided by Hampson-Rushell CO. is used.