• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.279-289
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• 2022

Since the frequency of heavy rainfall is increasing due to climate change, water levels in the river exceed past historical records. The rating-curve is to convert water level into flow dicscharge from the regression analysis of the water level and corresponding flow discharges. However, the rating-curve involves many uncertainties because of the limited data especially when observed water level exceed past historical water levels. In order to compensate for insufficient data and increase the accuracy of flow discharge data, this study estimates the flow discharge in the river computed mathematically using Monte Carlo simulation based on a 1D hydrodynamic numerical model. Based on the existing rating curve, a random combination of coefficients constituting the rating-curve creates a number of virtual rating curve. From the computed results of the hydrodynamic model, it is possible to estimate flow discharge which reproduces best fit to the observed water level. Based on the statistical evaluation of these samples, a method for mathematically estimating the water level and flow discharge of all cross sections is porposed. The proposed methodology is applied to the junction of Yochoen Stream in the Seomjin River. As a result, it is confirmed that the water level reproducibility was greatly improved. Also, the water level and flow discharge can be calculated mathematically when the proposed method is applied.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.5
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• pp.139-152
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• 2015

Along with climate change, it is reported that the scale and frequency of extreme climate events show unstable tendency of increase. Thus, to comprehend the change characteristics of precipitation data, it is needed to consider non-stationary. The main objectives of this study were to estimate future design floods for Wonpyeongcheon watershed based on RCP (Representative Concentration Pathways) scenario. Wonpyeongcheon located in the Keum River watershed was selected as the study area. Historical precipitation data of the past 35 years (1976~2010) were collected from the Jeonju meteorological station. Future precipitation data based on RCP4.5 were also obtained for the period of 2011~2100. Systematic bias between observed and simulated data were corrected using the quantile mapping (QM) method. The parameters for the bias-correction were estimated by non-parametric method. A non-stationary frequency analysis was conducted with moving average method which derives change characteristics of generalized extreme value (GEV) distribution parameters. Design floods for different durations and frequencies were estimated using rational formula. As the result, the GEV parameters (location and scale) showed an upward tendency indicating the increase of quantity and fluctuation of an extreme precipitation in the future. The probable rainfall and design flood based on non-stationarity showed higher values than those of stationarity assumption by 1.2%~54.9% and 3.6%~54.9%, respectively, thus empathizing the necessity of non-stationary frequency analysis. The study findings are expected to be used as a basis to analyze the impacts of climate change and to reconsider the future design criteria of Wonpyeongcheon watershed.

• Journal of Korean Library and Information Science Society
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• v.52 no.1
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• pp.55-77
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• 2021

Based on the analysis of historical backgrounds and terms of Taekwondo, this study was conducted to analyze the characteristics of cataloging records related to Taekwondo in 53 national libraries of each country. The results are as follows. To begin with, while most of the Taekwondo-related records are concentrated in some specific national libraries such as the United States, Germany, Republic of China, United Kingdom, and Spain, there are four libraries that do not have one. Second, the title keyword of Taekwondo-related records was 93.5% for the term that directly meant Taekwondo and 6.5% for Korean martial art, Korean art of self-defense, and Korean karate etc. The frequency of materials by language is 38.7% for English and 8~9% for German, Spanish, Chinese, and Korean, respectively. The Roman translation for Taekwondo is 50.3% for 'Taekwondo', and 18.5% for 'Tae kwon do'. Third, the subject heading of Taekwondo-related records was 86.9% for 'Tae kwon do' or 'Taekwondo' etc. 7.6% for 'karate', 5.7% for general subject heading, and 12.0% for blank. This means that some national libraries misunderstand Taekwondo as karate.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.1
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• pp.41-49
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• 2023

To utilize the hydraulic and hydrological models when simulating floods in agricultural watersheds, it is necessary to consider agricultural reservoirs, farmland, and farmland drainage system, which are characteristics of agricultural watersheds. However, most of them are developed individually by different researchers, also, each model has a different simulation scope, so it is hard to use them integrally. As a result, there is a need to link each hydraulic and hydrological model. Therefore, this study established an integrated flood simulation system for the comprehensive flood simulation of agricultural reservoir watersheds. The system can be applied easily to various watersheds because historical weather data and the SSP (Shared Socio-economic Pathways) climate change scenario database of ninety weather stations were built-in. Individual hydraulic and hydrological models were coded and coupled through Python. The system consists of multiplicative random cascade model, Clark unit hydrograph model, frequency analysis model, HEC-5 (Hydrologic Engineering Center-5), HEC-RAS (Hydrologic Engineering Center-River Analysis System), and farmland drainage simulation model. In the case of external models with limitations in conceptualization, such as HEC-5 and HEC-RAS, the python interpreter approaches the operating system and gives commands to run the models. All models except two are built based on the logical concept.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.128-134
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• 2016

Estimating the repair and reinforcement (R&R) costs for each bridge member is essential for managing the life cycle of a bridge using a bridge management system (BMS). Representative members of a bridge were defined in this study, and detailed and representative R&R methods for each one were drawn in order to develop a systematic maintenance cost model that is applicable to the BMS. The unit cost for each detailed R&R method was established using the standard of estimate and historical cost data, and a systematic procedure is presented using an integration program to enable easy renewal of the R&R unit cost. Also, the average unit cost of the representative R&R methods was calculated in the form of a weighted average by considering the unit cost and application frequency of each detained R&R method. The appropriateness of the drawn average unit cost was reviewed by comparing and verifying it with the previous historical unit cost. The suggested average R&R unit cost can be used to review the validity of the required budget or the appropriateness of the R&R performance cost in the stage to establish the bridge maintenance plan. The results of this study are expected to improve the reliability of maintenance cost information and the rationality of decision making.

• Journal of Wetlands Research
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• v.18 no.1
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• pp.76-83
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• 2016

In recent, the series of extreme storm events were occurred by those continuous typhoons and the severe flood damages due to the loss of life and the destruction of property were involved. In this study, we call Mega flood for the Extreme flood occurred by these successive storm events and so we can have a hypothetical Mega flood by assuming that a extreme event can be successively occurred with a certain time interval. Inter Event Time Definition (IETD) method was used to determine the time interval between continuous events in order to simulate Mega flood. Therefore, the continuous extreme rainfall events are determined with IETD then Mega flood is simulated by the consecutive events : (1) consecutive occurrence of two historical extreme events, (2) consecutive occurrence of two design events obtained by the frequency analysis based on the historical data. We have shown that Mega floods by continuous extreme rainfall events were increased by 6-17% when we compared to typical flood by a single event. We can expect that flood damage caused by Mega flood leads to much greater than damage driven by a single rainfall event. The second increase in the flood caused by heavy rain is not much compared to the first flood caused by heavy rain. But Continuous heavy rain brings the two times of flood damage. Therefore, flood damage caused by the virtual Mega flood of is judged to be very large. Here we used the hypothetical rainfall events which can occur Mega floods and this could be used for preparing for unexpected flood disaster by simulating Mega floods defined in this study.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.29 no.4
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• pp.78-86
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• 2011

The recovering of historical mountain fortress needs the maintenance of forest scape for achieving visibility. In the study, the methods for the maintenance of the forest around the fortress were proposed. The Cumulative Visibility Analysis and Multiple Sight Surface Analysis were tested to verify the methods using GIS on the Myeong-hwal Fortress in Kyungju. The results of the study are as follows. First, the Cumulative Visibility Analysis was made on the Myeong-hwal Fortress from surrounding major viewpoints. The Cumulative Visibility Analysis enables the selection of excellent visibility sectors on the fortress. The 6 excellent visibility sectors were 1,937m(which occupied 41.2% of the area). Second, two cases of pine tree height were compared in the Cumulative Visibility Analysis. One used the average height of pines and the other used the maximum growth height. The comparative result demonstrated that the case of average height would be more effective for deciding the pine removal zone as well as achieving visibility to the mountain fortress. Third, to examine the feasibility of the management method, the tree removal plan and removal execution were compared on the A zone which showed high visibility frequency. Asa comparative result, there was insignificant difference(3.3%) in area between the tree removal plan($10,935m^2$) and removal execution($11,296m^2$). This study proved the Cumulative Visibility Analysis and Multiple Sight Surface Analysis to be effective for forest scape maintenance around a mountain fortress.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.821-831
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• 2019

The 9.12 earthquake (2016.9.12., M_L=5.8) and Pohang (2017.11.15., M_L=5.4) caused social and economic damage, resulting in a greater public interest in earthquakes than in the past. In the U.S., Japan and Chile, which have high frequency of earthquakes, infrastructure facilities are already managed based on probabilistic seismic hazard analysis (PSHA) and ground motion prediction equation (GMPE) to prepare for and respond to seismic disasters. In South Korea, the aforementioned PSHA and GMPE models have been developed independently through individual researchers. However, the limited disclosure of basic data, calculation methods, and final results created during the model development poses a problem of deploying new data without updating the earthquake that occurs every year. Therefore, this paper describes how to create flatfile, which is the basic data of GMPE, and how to process for seismic waves, and how to create intensity measures.