• Journal of Korean Association for Spatial Structures
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• v.18 no.3
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• pp.45-55
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• 2018

The arched stone bridge has been continuously deteriorated and damaged by the weathering and corrosion over time, and also natural disaster such as earthquake has added the damage. However, masonry stone bridge has the behavior characteristics as discontinuum structure and is very vulnerable to lateral load such as earthquake. So, it is necessary to analyze the dynamic behavior characteristics according to various design variables of arched stone bridge under seismic loads. To this end, the arched stone bridge can be classified according to arch types, and then the discrete element method is applied for the structural modelling and analysis. In addition, seismic loads according to return periods are generated and the dynamic analysis considering the discontinuity characteristics is carried out. Finally, the dynamic behavior characteristics are evaluated through the structural safety estimation for slip condition.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.47-59
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• 2007

Efficiency and limitations of HAZUS-MH, a GIS based systematic and informative system developed by FEMA and NIBS for natural hazard loss estimations, are discussed by means of a pilot study in the Korean Peninsula. Gyeongsang-do has been selected for the test after careful reviews of previous studies including historical and modern seismicity in the peninsula. A ShakeMap for the selected scenario earthquake with magnitude 6.7 in Gyeongju area is prepared. Then, any losses due to the scenario event have been estimated using HAZUS. Results of the pilot test show that the study area may experience significant physical, economic, and social damages. Detailed study in the future will provide efficient and crucial information to the decision makers and emergency agents to mitigate any disaster posed by natural hazards.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1145-1149
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• 2006

The typhoon Rusa passed through the Korean peninsula from the west-southern part to the east-northern part in the summer season of 2002. The flash flood due to the Rusa was occurred over the Korean peninsula and especially the damage was concentrated in Kangnung, Yangyang, Kosung, and Jeongsun areas of Kangwon-Do. Since the latter half of the 1990s the flash flood has became one of the frequently occurred natural disasters in Korea. Flash floods are a significant threat to lives and properties. The government has prepared against the flood disaster with the structural and nonstructural measures such as dams, levees, and flood forecasting systems. However, since the flood forecasting system requires the rainfall observations as the input data of a rainfall-runoff model, it is not a realistic system for the flash flood which is occurred in the small basins with the short travel time of flood flow. Therefore, the flash flood forecasting system should be constructed for providing the realistic alternative plan for the flash flood. To do so, firstly, Flash Flood Monitoring and Prediction (FFMP) Model must be developed suitable to Korea terrain. In this paper, We develop the FFMP model which is based on GIS, Radar techniques and hydro-geomorphologic approaches. We call it the F2MAP model. F2MAP model has three main components (1) radar rainfall estimation module for the Quantitative Precipitation Forecasts (QPF), (2) GIS Module for the Digital terrain analysis, called TOPAZ(Topographic PArametiZation), (3) hydrological module for the estimation of threshold runoff and Flash Flood Guidance(FFG). For the performance test of the model developed in this paper, F2MAP model applied to the Kangwon-Do, Korea, where had a severe damage by the Typhoon Rusa in August, 2002. The result shown that F2MAP model is suitable for the monitoring and the prediction of flash flood.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.1
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• pp.59-66
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• 2011

Lifeline Damages induced by earthquake loading brings not only a structure damage but the communication problems by the interruption of various energy utilities such as electric power, gas, and water resources. Earthquake loss estimation systems in USA and Japan, called as HAZUS (Hazard in US) and HERAS (Hazards Estimation and Restoration Aid System), respectively, have been established for the purpose of efficient responding to the earthquake hazard. Sufficient damage records are required to establish these systems. However, there are insufficient data set of damage records obtained from previous earthquakes in Korea. In this study, according to the construction specifications of the pipelines in both Korea and USA, the behavior of both ductile and brittle pipelines embedded in dense sand overlying various soils, such as clay, sand, and gravel were examined with respect to the pipeline characteristics under various earthquake loadings. The applicability of pipeline damage prediction used in HAZUS program to Korea has been investigated.

• Journal of Korean Society of Disaster and Security
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• v.13 no.4
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• pp.25-36
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• 2020

An increasing frequency and intensity of natural disasters have been observed due to climate change. To better prepare for these, the MOIS (ministry of the interior and safety) announced a comprehensive plan for minimizing damages associated with natural disasters, including drought and heavy snowfall. The spatial-temporal pattern of snowfall is greatly influenced by temperature and geographical features. Heavy snowfalls are often observed in Gangwon-do, surrounded by mountains, whereas less snowfall is dominant in the southern part of the country due to relatively high temperatures. Thus, snow depth data often contains zeros that can lead to difficulties in the selection of probability distribution and estimation of the parameters. A generalized mixture distribution approach to a maximum snow depth series over the southern part of Korea (i.e., Changwon, Tongyeoung, Jinju weather stations) are located is proposed to better estimate a threshold (𝛿) classifying discrete and continuous distribution parts. The model parameters, including the threshold in the mixture model, are effectively estimated within a Bayesian modeling framework, and the uncertainty associated with the parameters is also provided. Comparing to the Daegwallyeong weather station, It was found that the proposed model is more effective for the regions in which less snow depth is observed.

• Spatial Information Research
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• v.21 no.5
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• pp.33-41
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• 2013

Recently, the number of disasters has been seriously increasing. The total damages by the natural or man-made disasters during the past years resulted in tremendous fatalities and recovery costs. It is necessary to have efficient emergency evacuation management which is concerned with identifying evacuation route, and the estimation of evacuation and clearance times. An emergency evacuation model is important in identifying critical locations, and developing various evacuation strategies. In that existing evacuation models have focused on route analysis for indoor evacuation, there are only a few models for areawide emergency evacuation analysis. Therefore, we developed a mesoscopic model by using Cube Avenue and performed evacuation simulation, targeting road network in City of Fargo, North Dakota. Consequently, a mesoscopic model developed in this study is used to carry out dynamic analysis using network and input variable of existing travel demand model. The results of this study show that the model is an appropriate tool for areawide emergency evacuation analysis to save time and cost. Henceforth, the results of this study can be applied to develop a disaster evacuation model which can be used for a variety of disaster simulation and evaluation based on scenarios in the local metropolitan area.

• Journal of Wetlands Research
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• v.17 no.4
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• pp.370-379
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• 2015

In recent, the natural disaster like localized heavy rainfall due to the climate change is increasing. Therefore, it is important issue that the precise observation of rainfall and accurate spatial distribution of the rainfall for fast recovery of damaged region. Thus, researches on the use of the radar rainfall data have been performed. But there is a limitation in the estimation of spatial distribution of rainfall using rain gauge. Accordingly, this study uses the Kriging method which is a spatial interpolation method, to measure the rainfall field in Namgang river dam basin. The purpose of this study is to apply KED(Kriging with External Drift) with OK(Ordinary Kriging) and CK(Co-Kriging), generally used in Korea, to estimate rainfall field and compare each method for evaluate the applicability of each method. As a result of the quantitative assessment, the OK method using the raingauge only has 0.978 of correlation coefficient, 0.915 of slope best-fit line, and 0.957 of $R^2$ and shows an excellent result that MAE, RMSE, MSSE, and MRE are the closest to zero. Then KED and CK are in order of their good results. But the quantitative assessment alone has limitations in the evaluation of the methods for the precise estimation of the spatial distribution of rainfall. Thus, it is considered that there is a need to application of more sophisticated methods which can quantify the spatial distribution and this can be used to compare the similarity of rainfall field.

• Journal of Korean Society of Forest Science
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• v.106 no.4
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• pp.424-430
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• 2017

With its rapid velocity and wide deposition, debris flow is a natural disaster that causes loss of human life and destruction of facility. To design effective debris barriers, impact force of debris flow should be first considered. Debris flow velocity is one of the key features to estimate the impact force of debris flow. In this study, we conducted small-scale flume experiments to analyze flow characteristics of debris flow, and determine flow resistance coefficients with different slope gradients and sediment mixtures. Flow velocity significantly varied with flume slope and mixture type. Debris flow depth decreased as slope increased, but difference in depth between sediment mixtures was not significant. Among flow resistance coefficients, Chezy coefficient ($C_1$) showed not only relatively highest goodness of fit, but also constant value ($20.19m^{-1/2}\;s^{-1}$) regardless the scale of debris flow events. The overall results suggested that $C_1$ can be most appropriately used to estimate flow velocity, the key factor of assessing impact force, in wide range of debris flow scale.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.89-98
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• 2018

Satellite data have attracted attention on research such as natural disaster and climate changes because satellite data is very advantageous for observing a wide range of variability. However, there are still limited spatial and temporal resolutions in satellite data. To overcome these limitations, fusion of various sensors and combination of primary products are used. In this study, surface temperature data of 500 m spatial resolution was produced by fusion of GOCI and MI data of COMS. Also these LST are used with NDVI for estimating TVDI. Soil moisture condition of the Korean peninsula was evaluated by these TVDI and it was compared with SSMI derived from ASCAT surface soil moisture data. As a result, COMS TVDI and ASCAT SSMI showed similar spatial distribution and suggested the possibility of observing the soil moisture using COMS. Therefore, the TVDI estimations can be used as a basis for estimating the high resolution soil moisture, and the application of the COMS can be expanded for various studies.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.208-208
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• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.