• Journal of Korea Water Resources Association
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• v.40 no.1 s.174
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• pp.1-10
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• 2007

Reallocation procedure of multipurpose reservoir storage capacity between flood control and conservation is presented as an alternative to secure more water resources. Storage reallocation is an adaptive management mechanism for converting existing normal pool level of reservoirs to more beneficial uses without requirement for physical alteration. This study is intended to develop a reservoir storage reallocation methodology that allows increased water supply storage without minimizing adverse impacts on flood control. The methodology consists of flood control reservoir simulation for inflows with various return periods, flow routing from reservoir to a potential damage site, analyzing river carrying capacity, and reservoir yields estimation for reallocated storages. For the flood control model, a simulation model called Rigid ROM(Reservoir Operation Method) and HEC-5 are used. The approach is illustrated by applying it to two reservoirs system in Geum River basin. Especially with and without new project conditions are considered to analyze trade-offs between competing objectives.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.4
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• pp.49-55
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• 2009

This paper is to induce design floods through L-moment with 3 and 4 parameter Kappa distributions including test of independence by Wald-Wolfowitz, homogeneity by Mann-Whitney and outlier by Grubbs-Beck on annual maximum flood flows at 9 water level gaging stations in Han, Nakdong and Geum Rivers of South Korea. After analyzing appropriateness of the data of annual maximum flood flows by Kolmogorov-Smirnov test, 3 and 4 Kappa distributions were applied and the appropriateness was judged. The parameters of 3 and 4 Kappa distributions were estimated by L-moment method and the design floods by water level gaging station was calculated. Through the comparative analysis using the relative root mean square errors (RRMSE) and relative absolute errors (RAE) calculated by 3 and 4 parameter Kappa distributions with 4 plotting position formulas, the result showed that the design floods by 4 parameter Kappa distribution with Weibull and Cunnane plotting position formulas are closer to the observed data than those obtained by 3 parameter Kappa distribution with 4 plotting position formulas and 4 parameter Kappa distribution with Hazen and Gringorten plotting position formulas.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.4
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• pp.123-132
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• 2008

Aseries of in-situ tests and ground water level measurements with stone and slug materials had been conducted to find out effect of ground settlement reduction and bearing capacity improvement by the Stone Column method. As the result of the tests, it was proved that the Stone Column method is effective for reduction of ground settlement and improvement of bearing capacity. In addition the ground water level went down without overburden load. These results show that the Stone Column method is effective for an increase in density and resistance to liquefaction. The results of estimation of ground settlement and bearing capacity by general theoretical equation, it show that the Stone Column method increases bearing capacity by 2.7~5.7 times and decreases ground settlement by 2~3.5 times.

• Journal of Wetlands Research
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• v.13 no.1
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• pp.13-23
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• 2011

In this study, Mike11 will be used as the numerical model where a data assimilation method will be applied to it. This paper aims to gain an insight and understanding of data assimilation in flood forecasting models. It will start with a general discussion of data assimilation, followed by a description of the methodology and discussion of the statistical error forecast model used, which in this case is the linear regression. This error forecast model is applied to the water level forecast simulated by MIKE11 to produced improved forecast and validated against real measurements. It is found that there exists a phase error in the improved forecasts. Hence, 2 general formula are used to account for this phase error and they have shown improvement to the accuracy of the forecasts, where one improved the immediate forecast of up to 5 hours while the other improved the estimation of the peak discharge.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.11a
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• pp.801-804
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• 2004

It should be noted that the critical chloride threshold level is not considered to be a unique value for all conditions. This value is dependent on concrete mixture proportions, cement type and constituents, presence of admixtures, environmental factors, steel reinforcement surface conditions, and other factors. In this study, the accelerated corrosion test for reinforcing steel was conducted by electrochemical and sea water-circulated method, respectively and during the test, corrosion monitoring by half cell potential method was carried out to estimate the critical chloride threshold value when corrosion for reinforcing steel in concrete was perceived. For this purpose, lollypop and beam test specimens were made for $31.4\%,\;41.5\%\;and\;49.7\%$ of w/c. respectively and then the accelerated corrosion test for reinforcing steel was executed. It was observed from the test that the time to initiation of corrosion was found to be different with water-cement ratio and the critical chloride threshold value was found to range from 0.91 to $1.27kg/m^3$.

• Nuclear Engineering and Technology
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• v.32 no.5
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• pp.485-494
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• 2000

In this work, a fuzzy neural network is used to estimate the relevant sensor signal using other sensor signals. Noise components in input signals into the fuzzy neural network are removed through the wavelet denoising technique . Principal component analysis (PCA) is used to reduce the dimension of an input space without losing a significant amount of information. A lower dimensional input space will also usually reduce the time necessary to train a fuzzy-neural network. Also, the principal component analysis makes easy the selection of the input signals into the fuzzy neural network. The fuzzy neural network parameters are optimized by two learning methods. A genetic algorithm is used to optimize the antecedent parameters of the fuzzy neural network and a least-squares algorithm is used to solve the consequent parameters. The proposed algorithm was verified through the application to the pressurizer water level and the hot-leg flowrate measurements in pressurized water reactors.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.27-30
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• 2007

The objective of this study is to improve an accuracy of PWV estimates using GPS in Korea. We determined a weighted mean temperature equation by a linear regression method based on 6 radiosonde meteorological observations, for a total 17,129 profiles, from 2003 to 2005. Weighted mean temperature, Tm, is a key parameter in the retrieval of atmospheric PWV from ground-based GPS measurements of zenith path delay. The accuracy of the GPS-derived PWV is proportional to the accuracy of Tm. And we applied the reduction of air Pressure to GPS station altitude. The reduction value of air pressure from mean sea level to GPS stations altitude is adopted a reverse sea level correction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.949-963
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• 2017

This study present an efficient way of operating drainage pump station as part of nonstructural measures for reducing urban flood damage. The water level in the drainage pump station was forecast using Neuro-Fuzzy and then operation rule of the drainage pump station was determined applying the genetic algorithm method based on the predicted inner water level. In order to reflect the topographical characteristics of the drainage area when constructing the Neuro-Fuzzy model, the model considering spatial parameters was developed. Also, the model was applied a penalty type of genetic algorithm so as to prevent repeated stops and operations while lowering my highest water level. The applicability of the development model for the five drainage pump stations in the Mapo drainage area was verified. It is considered to be able to effectively manage urban drainage facilities in the development of these operating rules.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1185-1193
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• 2023

The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.5
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• pp.103-109
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• 2008

Precipitation on slope is separated into infiltration and outflow according to physical properties of soil and slope. However, the slope analysis is assumed that all precipitation are percolated. So, groundwater level is excessive tend to be calculated. In this paper, NRCS model and Horton models that have a suitability were used for agro-type analysis of Seoul station after precipitation was separated into infiltration and outflow. Also, gradient of slope was analyzed about seepage behavior and underground water level aspect through numerical analysis. After inclination correction, the estimated infiltration was compose of slopes much applied by domestic design standard. The change of groundwater level is appeared greatly as agro-type goes from D type to A type in the analysis results.