• Proceedings of the Korean Geotechical Society Conference
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• 2002.03a
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• pp.245-252
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• 2002

The Rock mass in which constructed a tunnel consist of the geological formations or the engineering rock type. Each layers are distinguished by the mineral, weathering and distributions of faults and Joints. Therefore, a tunneling design in rock mass starts from understanding and analyzing of the various geological engineering factors and then the engineering characteristics and distributions for each layers are determined to analysis and collection of the efficient informations. For this working, next two problems have to be solved. First, the layers in rock mass have to be classified and their distributions have to be defined. Second, the rock mass classifications and distributions based on the standard engineering classification have to be determined. Efficiently to approaching this two problems, the best solution is all geotechnical data are embodied to 3-D.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.291-291
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• 2021

모형이 갖는 불확실성의 정량화나 매개변수의 최적화는 계산시간의 기하급수적인 증가를 가져온다. 계산시간의 효율성을 극대화할 수 있는 기법으로 최근 대체모형이 개발되었으며, 다양한 분야에서 적용되고 있다. 그러나 대체모형은 훈련된 데이터 공간에서 크게 벗어난 극한 사상를 정확하게 모의하기는 어려운 단점이 있다. 본 연구는 이와 같은 대체모형의 단점을 개선할 수 있는 새로운 PCK(polynomial chaos-krigging) 기법을 제시한다. PCK는 PCE(polynomial chaos expansion) 기법과 OK(ordinary krigging) 기법을 결합한 것이며, PCK의 효과는 기존의 PCE 및 OK 모형의 결과와 비교하여 입증하였다. 본 연구의 분석 결과는 다음과 같다. (1) PCK는 더 적은 수의 훈련 샘플만으로도 원래 모형을 더 정확하게 대체할 수 있다. (2) 원래 훈련 샘플보다 약 3배 더 큰 극한사상을 모의했을 때, PCE와 OK는 예측이 실패하였지만, PCK의 예측은 정확하였다. (3) 민감도 분석 결과 PCK의 매개변수 특성과 거동이 PCE 및 OK보다 원래 모형의 특성과 거동에 더 일치한다. 본 연구에서는 3개의 대체모형의 결과를 원래모형의 결과와 비교하였으며 그 적용성을 극한강우에 대해 검토하였다. 일반적으로 훈련 샘플의 범위와 비슷한 강우사상에 대해서는 모든 대체모형의 결과가 우수하였으나, 훈련 샘플의 범위에서 벗어난 극한 사상의 모의는 PCK만 적용이 가능하였다. 제안된 대체모형은 극한사상의 예측에 있어 기존 대체모형보다 매우 향상된 정확도를 제공함을 확인할 수 있었다.

• Journal of Wetlands Research
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• v.4 no.2
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• pp.43-56
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• 2002

About 12 rain gauge stations of Korea, annual maximum rainfall series of before and after 1980 whose durations are 1, 2, 3, 6, 12, 24, 48, 72 hours respectively were composed and statistical characteristics of those time series were calculated and probability rainfall were estimated by L-moment frequency analysis method and compared each other in order to investigate the recent quantitative rainfall variations. And also, distribution curves of each statistical variations for each duration were constructed by using Kigging method to look into spacial rainfall variation aspects. As a result, We could confirm recent rainfall increase in the South Korea. And spatial increase pattern of standard deviation and frequency rainfall appeared analogously each other. 1n the cases of comparatively short rainfall duration, we could see relatively low increase or decrease tendency in Chungchong Province, Cholla-bukdo, Cholla-namdo eastern part, Kyongsang-namdo western part area. While, variations happened great1y in seaside district of east coast, southwest seashore, Inchon area etc. In the cases of longer durations relatively low increase was showed in southern seashore such as Yeosoo area and as distance recedes from this area, showed gradually augmented tendency. The aspect of mean looks similar tendency of above except that the variation rate of almost seaside district are big in the case of shorter durations. In addition, rainfall increases of short durations which became the center of hydrologist and meteorologist are unconfirmed in this study.

• Journal of KIBIM
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• v.12 no.4
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• pp.104-115
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• 2022

Fine Dust in Korea has been classified as a social disaster since 2019 due to continuous increase in concentration of Particulate Matter 10(PM 10) and PM 2.5. The fine dust issue has negative physical and mental impacts, especially on vulnerable population including children and the elderly. Seoul metropolitan government have installed fine dust shelters since 2019. However, there is a lack of research that evaluates spatiotemporal distribution of these facilities. Therefore, the first aim of this study is to find the relationship between PM levels and dust scattering construction sites, or air pollutant emission sites through in depth spatial analyses. The second purpose is to analyze the spatial distribution of PM shelters in Seoul, and to evaluate the location efficiency of them. Kernel density, krigging, and network analyses were conducted, and floating population was considered instead of census data for this research. The reults of network analysis based on the road system showed that Yangcheon-gu, Songpa-gu, Seongbuk-gu, and Dobong-gu were found to need additional fine dust shelters. Also, the results from analyzing the floating population that includes children and the elderly showed that Songpa-gu, Seodaemun-gu, Gangdong-gu, Seocho-gu, and Dongdaemun-gu need more placements of find dust shelters. The results of this study are expected to provide implications for urban planners to enhance find dust shelter placement in urban areas, and vulnerable population issues would be considered in many ways.

• The Journal of Engineering Geology
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• v.13 no.2
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• pp.239-256
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• 2003

The purpose of this study is to investigate the hydrochemical characteristics of emergency-use groundwater in the Daejeon area, and to elucidate the contamination source of $NO_3-N$ and the origin of sulfate in the groundwater. The groundwater shows weak acidic pH, the electrical conductivity ranging from 142 to $903{\;}\mu\textrm{S}/cm$, and the hydrochemical types of $Ca-HCo_3$ and $Ca-Cl(SO_4,{\;}NO_3)$. The Box-Whisker analysis and the Krigging analysis of chemical data of groundwater were made to demonstrate the concentration distribution of hydrochemical composition, and to compare the trend of hydrochemical data. The groundwater in the area of Dong-gu, Jung-gu and Daeduk-gu, where are old town, shows higher electrical conductivity, nitrate content, sulfate and $EpCO_2$ levels than groundwater in new town area of Seo-gu and Yusung-gu. ${\delta}^{15}N$ of groundwater in the area of Seo-gu and Yusung-gu ranges from +7.4 to $+9.6{\textperthousand}$, indicating that major contamination source of $NO_3-N$ is the leakage from municipal sewage pipe lines. ${\delta}^{15}N$ of groundwater in the old town area of Tong-gu, Jung-gu and Daeduk-gu shows the range between +10.2 and $+23.5{\textperthousand}$, meaning that major contamination source is leakage of septic tank. ${\delta}^{34}S$ of groundwater shows the range of $+3~13.4{\;}{\textperthousand}$. Sulfur isotope indicates the possibility of a sulfate reduction and the input of anthrophogenic source.

• Journal of Korea Water Resources Association
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• v.48 no.9
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• pp.719-728
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• 2015

In this study, urban runoff analyses were performed using high resolution Quantitative Precipitation Estimation (QPE), and variation of rainfall and runoff were analyzed to evaluate QPE data for urban runoff analysis. The five drainage districts (Seocho3, 4, 5, Yeoksam and Nonhyun) around Gangnam station were chosen as study area, the area is $7.4km^2$. Rainfall data from KMA AWS (34 stations), SKP AWS (156 stations) and Gwanduk radar were used for QPEs in Seoul area. Four types of QPE(QPE1: KMA AWS, QPE2: KMA+ SKP AWS, QPE3: Gwangduk radar, QPE4: QPE2+QPE3) of 6 events in July 2013 were generated by using Krigging and conditional merging. The temporal and spatial resolution of QPEs are 10 minutes and 250 m, respectively. The complex pipe network were treated as 773 manholes, 772 sub-drainage districts and 1,059 pipelines for urban runoff analysis as input data. QPE2 and QPE4 show spatial variation of rainfall by sub-drainage districts as 1.9 times bigger than QPE1. The peak runoff of QPE2 and QPE4 also show spatial variation as 6 times bigger than Gangnam and Seocho AWS. Thus, the spatial variation of rainfall and runoff could exist in small area such as this study area, and using high-resolution rainfall data is desirable for accurate urban runoff analysis.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Economic and Environmental Geology
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• v.41 no.2
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• pp.211-217
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• 2008

The gravity anomalies that observed by ground and shipborne survey and calculated from GRACE satellite are combined by using spherical cap harmonic analysis (SCHA). In this study, ground gravity data from Korea Institute of Geoscience and Mineral Resource(KIGAM) and shipborne gravity data from National Ocean Research Institute(NORI) and Korea Ocean Research and Development institute(KORDI) were used. L-2 level GRACE Gravity Model (GGM02C) was also used for satellite gravity anomaly. The ground and shipborne surveyed data were combined and gridded using Krigging method with 0.05 degree interval and GRACE data were also gridded using the same method with 0.05 degree to harmonize with the resolution of SCHA that has coefficient up to 80. Generalized Minimal Residual(GMRES) inversion method was implemented for calculating the coefficients of SCHA using the gridded ground and satellite gravity anomalies that had 0 km and 50 km altitude, respectively. The results of inversion method showed good correlation of 0.950 and 0.995 with original ground and satellite data. The gravity anomaly using SCHA satisfies Laplace's equation, therefore, using these SCHA coefficients, gravity anomaly can be calculated at any altitude. In this study, gravity anomaly was calculated from 10 km to 60 km altitude and each altitude, very stable results were shown. The ground and shipborne gravity data that have higher resolution and satellite data in long wavelength are harmonized well with SCHA coefficients and successfully applied in South Korea area. If more continuous survey and muti-altitude surveyed data like airborne data available, more precise gravity anomaly can be acquired using SCHA method.

• Journal of Korean Society of Forest Science
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• v.110 no.3
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• pp.322-340
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• 2021

Due to climate change and its consequential spring temperature rise, flowering time of Robinia pseudoacacia has advanced and a simultaneous blooming phenomenon occurred in different regions in South Korea. These changes in flowering time became a major crisis in the domestic beekeeping industry and the demand for accurate prediction of flowering time for R. pseudoacacia is increasing. In this study, we developed and compared performance of four different models predicting flowering time of R. pseudoacacia for the entire country: a Single Model for the country (SM), Modified Single Model (MSM) using correction factors derived from SM, Group Model (GM) estimating parameters for each region, and Local Model (LM) estimating parameters for each site. To achieve this goal, the bloom date data observed at 26 points across the country for the past 12 years (2006-2017) and daily temperature data were used. As a result, bloom dates for the north central region, where spring temperature increase was more than two-fold higher than southern regions, have advanced and the differences compared with the southwest region decreased by 0.7098 days per year (p-value=0.0417). Model comparisons showed MSM and LM performed better than the other models, as shown by 24% and 15% lower RMSE than SM, respectively. Furthermore, validation with 16 additional sites for 4 years revealed co-krigging of LM showed better performance than expansion of MSM for the entire nation (RMSE: p-value=0.0118, Bias: p-value=0.0471). This study improved predictions of bloom dates for R. pseudoacacia and proposed methods for reliable expansion to the entire nation.