The shallow sediments in the southwestern Ulleung Basin consist of mass flow deposits such as slide/slump and debris flow deposits (DFD), caused by slope failure. These sediments are proven to be important in studying geological disaster and stability of the seafloor. In this paper, we analysised the flow accumulation and slope failure susceptibility of the Ulleung Basin on the basis of multi-beam data, collected in this area. We also studied the distribution pattern and the seismic characteristics of the DFD in the uppermost layer of the Ulleung Basin on the basis of seismic data. The slope susceptibility was calculated as the frequency ratio of each factors including slope, aspect, curvature and stream power index (SPI), which causes the slope failure. These results indicate that the slope failure is frequently to occur in the southern and western continental slope of the Ulleung Basin. The sediment flow (mass flow) caused by the slope failure converges to the north and northwest of the Ulleung Basin. According to the seismic characteristics, the uppermost layer in study area can be divided into four sedimentary unit. These sedimentary units develop from the south and southwest to the north and northwest in association with slope susceptibility and flow accumulation.
The stability of the designed rock slope is analysed based on two kinds of shear strength model. Besides the deterministic analysis, a probabilistic approach on Monte Carlo simulation is proposed to deal with the uncertain characteristics of the discontinuity and the results obtained from two models are compared to each other. To carry out the research of characteristics of the discontinuity, BIPS, DOM Scanline survey data and direct shear test data are used, and chi-square test is used for determining the probability distribution function. The rock slope is evaluated to be stable in the deterministic analysis, but in the probabilistic analysis, the probability of failure is more than 5%, so, it is considered that the rock slope is unstable. In the shear strength models, the probability of the failure based on the Mohr-Coulomb model(linear model) is higher than that of the Barton model. It is supported by the fact that the Mohr-Coulomb model is more sensitive to block size than the Barton model. In fact, there is no reliable way to estimate the unit cohesion of the Mohr-Coulomb model except f3r back analysis and in the case of small block failure in the slope, Mohr-Coulomb model may excessively evaluate the factor of the safety. So, the Barton model of which parameters are easily acquired using the geological survey is more reasonable for the stability of the studied slope. Also, the selection of the proper shear strength model is an important factor for slope failure analysis.
We have performed multiple geophysical surveys comprised of gravity, magnetic and resistivity methods at the Yangsan fault zone which runs through the Eonyang area, the eastern part of Kyeongsang in southeast Korea. The gravity and magnetic data provide information about geological structures. Furthermore, sections of electrical resistivity show the sharp contrast of electrical resistivity distribution across the fault zone. Since the fractured zone tends to be more conductive than fresh host rocks, the electrical resistivity survey is effective in determining the detailed structure of the fault zone. We have made gravity measurements at a total of 71 points alongside two profiles across the fault zone, and carried out an electrical resistivity survey with a dipole-dipole array at the same location using 40m dipole length. In addition, we have analyzed the aeromagnetic data on the corresponding area. The multiple geophysical properties appear to be abruptly changed in electrical resistivity, gravity and aeromagneticclearly show the different appearance across the fault zone. The fault is identified by its sub vertical attitude which is well known in the Yangsan fault zone. We have also confirmed that the magnitude of the response of the fault is much larger in the southern part of the survey area than the northern area. These results most likely to provide basic information for the further studies about the physical properties and the structures at the Yangsan fault.
Seismic reflection profile analysis, potential field analysis, and potential field modeling using deep seismic reflection, gravity, magnetic, and geological data were performed to better understand the location and nature of the Grenville Front in Ohio, USA. The seismic reflection profile reveals a broad zone of east dipping basement reflectors associated with the Grenville Front in western Ohio and a broad region of west dipping reflectors cutting through the entire crust in eastern Ohio. Potential field analysis indicates that the Grenville Front is characterized by a gravity low, an associated gravity positive and a magnetic high. The results of the gravity and magnetic modeling using seismic data suggest that the lower crust is thickened at the interpreted position of the Grenville Front and high grade metamorphic rocks make up the Grenville Front Tectonic Zone (GFTZ). The gravity low at the Grenville Front is due to the thickened crust, while the magnetic high is due to high grade metamorphic rocks. The gravity high immediately east of the GFTZ in central Ohio is caused by thrusting of high density lower and middle crustal rocks into the upper crust. There is no compelling evidence that this gravity high is related to a Precambrian rift zone as has been suggested in previous studies.
Volcanic eruptions alone may lead to serious natural disasters, but the associated release of water from a caldera lake may be equally damaging. There is both historical and geological evidence of the past eruptions of Mt. Baekdusan, and the volcano, which has not erupted for over 100 years, has recently shown signs of reawakening. Action is required if we are to limit the social, political, cultural, and economic damage of any future eruption. This study aims to identify the area that would be inundated following a volcanic flood from the Cheon-Ji caldera lake that lies within Mt. Baekdusan. A scenario-based numerical analysis was performed to generate a flood hydrograph, and the parameters required were selected following a consideration of historical records from other volcanoes. The amount of water at the outer rim as a function of time was used as an upper boundary condition for the downstream routing process for a period of 10 days. Data from the USGS were used to generate a DEM with a resolution of 100 m, and remotely sensed satellite data from the moderate-resolution imaging spectroradiometer (MODIS) were used to show land cover and use. The simulation was generated using the software FLO-2D and was superposed on the remotely sensed map. The results show that the inundation area would cover about 80% of the urban area near Erdaobaihezhen assuming a 10 m/hr collapse rate, and 98% of the area would be flooded assuming a 100 m/hr collapse rate.
Hwang, Youngtaek;Ko, Nak-Youl;Choi, Jong Won;Jo, Seong-Seock
Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
/
v.10
no.4
/
pp.295-303
/
2012
Based on the data observed and analyzed on a groundwater flow system in the KURT (KAERI Underground Research Tunnel) site, the transport of radionuclides, which were assumed to be released at the supposed position, was calculated on the time-domain. A groundwater pathway from the release position to the surface was identified by simulating the groundwater flow model with the hydrogeological characteristics measured from the field tests in the KURT site. The elapsed time when the radionuclides moved through the pathway is evaluated using TDRW (Time Domain Random Walk) method for simulating the transport on the time-domain. Some retention mechanisms, such as radioactive decay, equilibrium sorption, and matrix diffusion, as well as the advection-dispersion were selected as the factors to influence on the elapsed time. From the simulation results, the effects of the sorption and matrix diffusion, determined by the properties of the radionuclides and underground media, on the transport of the radionuclides were analyzed and a decay chain of the radionuclides was also examined. The radionuclide ratio of the mass discharge into the surface environment to the mass released from the supposed repository did not exceed $10^{-3}$, and it decreased when the matrix diffusion were considered. The method used in this study could be used in preparing the data on radionuclide transport for a safety assessment of a geological disposal facility because the method could evaluate the travel time of the radionuclides considering the transport retention mechanism.
Magazine of the Korean Society of Agricultural Engineers
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v.22
no.3
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pp.75-87
/
1980
Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.
Korean Journal of Agricultural and Forest Meteorology
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v.15
no.4
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pp.219-233
/
2013
We employed the ecological niche modeling framework using GARP (Genetic Algorithm for Ruleset Production) to model the current and future geographic distribution of Pinus densiflora based on environmental predictor variable datasets such as climate data including the RCP 8.5 emission climate change scenario, geographic and topographic characteristics, soil and geological properties, and MODIS enhanced vegetation index (EVI) at 4 $km^2$ resolution. National Forest Inventory (NFI) derived occurrence and abundance records from about 4,000 survey sites across the whole country were used for response variables. The current and future potential geographic distribution of Pinus densiflora, one of the tree species dominating the present Korean forest was modeled and mapped. Future models under RCP 8.5 scenarios for Pinus densiflora suggest large areas predicted under current climate conditions may be contracted by 2090 showing range shifts northward and to higher altitudes. Area Under Curve (AUC) values of the modeled result was 0.67. Overall, the results of this study were successful in showing the current distribution of major tree species and projecting their future changes. However, there are still many possible limitations and uncertainties arising from the select of the presence-absence data and the environmental predictor variables for model input. Nevertheless, ecological niche modeling can be a useful tool for exploring and mapping the potential response of the tree species to climate change. The final models in this study may be used to identify potential distribution of the tree species based on the future climate scenarios, which can help forest managers to decide where to allocate effort in the management of forest ecosystem under climate change in Korea.
Kim, Kyung-Su;Kim, Chun-Soo;Bae, Dae-Seok;Ji, Sung-Hoon;Yoon, Si-Tae
Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
/
v.6
no.4
/
pp.245-255
/
2008
Korea Hydro and Nuclear Power Company(KHNP) conducted site investigations for a low and intermediate-level nuclear waste repository in the Gyeong Ju site. The site characterization work constitutes a description of the site, its regional setting and the current state of the geosphere and biosphere. The main objectives of hydogeological investigation aimed to understand the hydrogeological setting and conditions of the site, and to provide the input parameters for safety evaluation. The hydogeological characterization of the site was performed from the results of surface based investigations, i.e geological mapping and analysis, drilling works and hydraulic testing, and geophysical survey and interpretation. The hydro-structural model based on the hydrogeological characterization consists of one-Hydraulic Soil Domain, three-Hydraulic Rock Domains and five-Hydraulic Conductor Domains. The hydrogeological framework and the hydraulic values provided for each hydraulic unit over a relevant scale were used as the baseline for the conceptualization and interpretation of flow modeling. The current hydrogeological characteristics based on the surface based investigation include some uncertainties resulted from the basic assumption of investigation methods and field data. Therefore, the reassessment of hydrostructure model and hydraulic properties based on the field data obtained during the construction is necessitated for a final hydrogeological characterization.
A fault is a geological structure that can be a migration path or a cap rock of hydrocarbon such as oil and gas, formed from source rock. The fault is one of the main targets of seismic exploration to find reservoirs in which hydrocarbon have accumulated. However, conventional fault detection methods using lateral discontinuity in seismic data such as semblance, coherence, variance, gradient magnitude and fault likelihood, have problem that professional interpreters have to invest lots of time and computational costs. Therefore, many researchers are conducting various studies to save computational costs and time for fault interpretation, and machine learning technologies attracted attention recently. Among various machine learning technologies, many researchers are conducting fault interpretation studies using the support vector machine, multi-layer perceptron, deep neural networks and convolutional neural networks algorithms. Especially, researchers use not only their own convolution networks but also proven networks in image processing to predict fault locations and fault information such as strike and dip. In this paper, by investigating and analyzing these studies, we found that the convolutional neural networks based on the U-Net from image processing is the most effective one for fault detection and interpretation. Further studies can expect better results from fault detection and interpretation using the convolutional neural networks along with transfer learning and data augmentation.
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