• Journal of Wetlands Research
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• v.13 no.2
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• pp.171-179
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• 2011

The main objective of this study is to estimate of the vegetation response induced by climate change to soil moisture. We investigated a relationship between vegetation activity and climate variables using Moderate Resolution Imaging Spectroradiometer (MODIS)-retrieved Normalized Difference Vegetation Index (NDVI) and soil moisture. NDVI which extracted from MODIS 13 Vegetation Indices Product was considered as an useful parameter to figure out a relationship with two types of soil moisture, which were observed at Rural Development Administration sites and estimated from Advanced Microwave Scanning Radiometer E (AMSR-E) satellite imagery. The correlation of MODIS-NDVI and ground measured soil moisture were observed, became much stronger when compared to soil moisture values with time lag (5days, 10days, 15days). The correlation patterns between NDVI and soil moisture with different time lag were related to soil texture. The results from this study will be useful to understand the role of vegetation in water balance control in various scales from regional to global climate change.

• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.171-182
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• 2014

The objective of this study is to evaluate the utilization of bivariate joint drought index in South Korea. In order to develop the bivariate joint drought index, in this study, Clayton copula was used to estimate the joint distribution function and the calibration method was employed for parameter estimation. Precipitation and soil moisture data were selected as input data of bivariate joint drought index for period of 1977~2012. The time series analysis, ROC (Receiver Operating Characteristic) analysis, spatial analysis were used to evaluate the bivariate joint drought index with SPI (Standardized Precipitation Index) and SSI (Standardized Soil moisture Index). As a result, SPI performed better for drought onset and SSI for drought demise. On the other hand the bivariate joint drought index captured both drought onset and demise very well. The ROC score of bivariate joint drought index was higher than that of SPI and SSI, and it also reflected the local drought situations. The bivariate joint drought index overcomes the limitations of existing drought indices and is useful for drought analysis.

• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.161-170
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• 2014

It is important to estimate an appropriate quantile for design of hydraulic structure. For this purpose, it is necessary to find the appropriate probability distribution which can represent the sample data well. Probability plot correlation coefficient test as one of goodness-of-fit test, is recently developed and has been known as a simple and powerful method. In this study, probability plot correlation coefficient test statistics using the plotting position considering the coefficients of skewness for the GEV distribution is derived, and represented by the regression equation. Monte-Carlo method is also performed to compare the rejection power between each method. As the results, the probability plot correlation coefficient test which is derived in this study is better than the others. In particular, when sample size is small and distribution has the shape parameter, rejection power of probability plot correlation coefficient test considering the coefficients of skewness is bigger than the others.

• Journal of Korea Water Resources Association
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• v.49 no.8
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• pp.645-656
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• 2016

The study performed a regional flood frequency analysis and proposed a regression equation to estimate design floods corresponding to return periods for ungauged basins in Geum-river basin. Five preliminary tests were employed to investigate hydrological independence and homogeneity of streamflow data, i.e. the lag-one autocorrelation test, time homogeneity test, Grubbs-Beck outlier test, discordancy measure test ($D_i$), and regional homogeneity measure (H). The test results showed that streamflow data were time-independent, discordant and homogeneous within the basin. Using five probability distributions (generalized extreme value (GEV), three-parameter log-normal (LN-III), Pearson type 3 (P-III), generalized logistic (GLO), generalized Pareto (GPA)), comparative regional flood frequency analyses were carried out for the region. Based on the L-moment ratio diagram, average weighted distance (AWD) and goodness-of-fit statistics ($Z^{DIST}$), the GLO distribution was selected as the best fit model for Geum-river basin. Using the GLO, a regression equation was developed for estimating regional design floods, and validated by comparing the estimated and observed streamflows at the Ganggyeong station.

• Journal of Biosystems Engineering
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• v.28 no.4
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• pp.343-350
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• 2003

This study was conducted to find out the coefficient relationships between intensity values of image processing and biological/physical parameters of soil in greenhouses. Soil images were obtained by an image processing system consisting of a personal computer and a CCD earners. A software written in Visual C$\^$++/ systematically integrated the functions of image capture, image processing, and image analysis. Image processing data of the soil samples were analyzed by the method of regression analysis. The results are as follows. For detecting soil density of unbroken soil samples, the highest correlation coefficients of 0.82 and 0.84, respectively were obtained fur R-value and S-value among image processing data while it was 0.97 for G-value. Considering the relationship between biological characteristics and image processing data of soil in greenhouse, the correlation was found generally low. For pH of unbroken soil sample, the correlation coefficients were found 0.87, 0.85, and 0.94, respectively with G, I, and H values of image processing data. In the case of bacteria, any correlation was not found with the image processing data For Actinomyctes, they were 0.86 and 0.85, respectively with G-value and B-value of image processing data showing high correlation coefficient compared to the other variables. The correlation coefficient between Fungi and H-value was shown 0.88, the highest among the variables higher than 0.8 while the other variables showed low correlation. For broken soil samples from greenhouse, the relation between biological parameter and image processing data were rarely shown in this study. The results of this study indicated that most of correlation coefficient between the variables were usually lower than 0.01. Accordingly, it was assumed that the soil should be used without broken to fairly estimate biological characteristics using CCD camera.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.4
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• pp.313-319
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• 2007

Long term wave climate of both extreme and operational wave height is essential for planning and designing coastal structures. Since the availability of the field wave data for the waters around Korean peninsula is limited to provide a reliable wave statistics, the wave climate information has been generated by means of long-term wave hindcasting using available meteorological data. In this paper, a set of deep water wave data obtained from KORDI(2003) were analyzed for extreme wave heights. These wave data at 67 stations off the Korean coast from 1979 to 1998 were arranged in the 16 directions. The probability distributions considered in this research were the FT-I and Weibull distribution. For each of these distributions, the method proposed by Goda(2004) was applied to estimate the parameters. For judgment of best fitting, MIR criterion proposed by Goda and Gobune(1990) was used. FT-I distribution which best fits to the 886 data, while Weibull(k=0.75) 81 data, Weibull(k=1.00) 105 data.

• Journal of Animal Science and Technology
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• v.53 no.4
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• pp.289-296
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• 2011

Swine industry in Korea plays an important role in providing the meat for domestic consumption, and the number of pigs in Korea was about 9.72 million heads as of June, 2010. Meat quality is used to describe any traits which impact the consumer acceptability of fresh meat products. Meat color, firmness, water holding capacity, ultimate muscle $pH_{24h}$ (measured 24 hours post-mortem), shear force, and intramuscular fat percentage (IMF) are generally accepted as important indicators of meat quality and ultimately, consumer acceptance of fresh pork. The objective of this study was to estimate genetic parameters for meat quality traits in Berkshire pigs. The heritability estimates for muscle $pH_{24h}$, lightness (CIE $L^*$), NPPC marbling were 0.61, 0.56 and 0.57, respectively, The heritability estimates for drip loss, cooking loss, shear force were 0.51, 0.66 and 0.56, respectively. The phenotypic correlations between $pH_{24h}$ and lightness (CIE $L^*$), drip loss, cooking loss were negative, ranging from -.45 ~ -.13. The genetic correlations between muscle $pH_{24h}$ and lightness (CIE $L^*$), drip loss were negative, ranging from -.35 ~ -.32. Genetic parameters obtained herein indicate that genetic improvement of muscle $pH_{24h}$ is not related to the NPPC marbling of meat, but rather to improved lightness(CIE $L^*$) and drip loss. Genetic trends of meat quality traits showed increased muscle $pH_{24h}$ and decreased cooking loss and drip loss.

• The Journal of Engineering Geology
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• v.17 no.3
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• pp.471-481
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• 2007

The Landslide in natural slope is occurred mostly by a heavy rain of the summer. This landslide is influenced in soil property of the surface than the rock mass. Soils in natural slope are created by weathering phenomena of the bedrock. These soils differed to the geological conditions such as sedimentary rock, metamorphic rock and volcanic rock. Therefore, estimation of landslide in natural slope is the most important analysis of the bedrock distributions and soil characteristics. This study analyzed the soil property to the natural slopes of Busan area where is distributed to volcanic rock, granite and sedimentary rock. Soil sample conducted various soil tests for estimate the soil physical property and soil engineering characteristics, and analysis of the correlation of geological conditions. In the experiment result, soils were mainly classified by a clayey sand. It is also established that $1.07{\sim}1.99kg/cm^3$ for wet density, $28.2{\sim}39.6^{\circ}$ for angle of shearing resistance, and $8.10{\times}10^{-5}{\sim}8.38{\times}10^{-2}cm/sec$ for coefficient of permeability. From the physical parameter, the soils are estimated to the permeable ground with good shear strength, and soil properties are showed a differential tendency for each geological condition.

• Korean Journal of Environmental Agriculture
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• v.20 no.3
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• pp.192-200
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• 2001

The event-based agricultural non-point source(AGNPS) pollution model was applied to estimate the loads of nitrogen and phosphorus in a stream draining small agricultural watersheds. Calibration and verification of the model were performed using observed data collected from rainfall events in the Imgo watersheds during 1997-1998. Parameter calibrations were made for the runoff curve number. The peak flow volumes in the watersheds were well reproduced by the modified model. Average deviation between observed and simulated values was 10%, and this match was confirmed by the coefficient of efficiency value of 0.97. The deviations tended to increase as the peak flows increased. The simulated total N concentrations in the stream water were fairly close to the measured values, and the coefficient of efficiency in the estimation was 0.93. However, there were relatively large variations between calculated and observed values of total P concentration, and the coefficient of efficiency in the estimation was 0.74. Any inaccuracies that arise in estimating runoff flow and nutrient loading can not be explained exactly and further adjustment and refinements may be needed for application of AGNPS in agricultural watersheds. With this restrictions in mind, it can be concluded that AGNPS can provide realistic estimates of nonpoint source nutrient yields.

• Journal of the Korean Geotechnical Society
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• v.20 no.2
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• pp.131-141
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• 2004

For geotechnical applications, engineers use data obtained from a site investigation to interpret the structure and potential behavior of the subsurface. In most cases, these data consist of samples that represent 1/100,000 or less of the total volume of soil. These samples and associated field and lab testing provide the information used to estimate soil parameter values. The resulting values are estimated ones and there exists some likelihood that actual soil conditions are significantly different from the estimates. This may be the case even if the sampling and interpretation procedures are performed in accordance with standard practice. Although these efforts have been made to characterize the uncertainty associated with geotechnical parameters, there is no commonly accepted method to evaluate quantitatively the quality of an investigation plan as a whole or the relative significance of individual sampling points or potential sampling points.