• Korean Journal of Soil Science and Fertilizer
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• v.35 no.3
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• pp.162-168
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• 2002

The silica uptake of rice plant(Oryza sativa L.) and a potential capacity of paddy soil as a source of silica supply for rice plant was studied under field experimental condition. Amount of Si from irrigation water, rainfall, which was a source of silica supply, and percolating rate of water through paddy soil profile as a source of silica loss from paddy soil, was investigated. Rice plants were grown in three different conditions, which included Control as non-fertilized, RDA's recommandation(NPK, Urea-Fused phophate-Potassium chloride=$110-45-57kg\;ha^{-1}$) and RDA's recommandation with supplement of silicate fertilizer(NPK+Si, Urea-Fused phosphate-Potassium chloride+Si=$110\;N-45\;P_2O_5-57\;K_2O+267.2\;Si\;kg\;ha^{-1}$). An amount of silica supply from rainfall was $0.5kg\;ha^{-1}$ and average amount of silica supplied from irrigation water $42.5kg\;ha^{-1}$, ranging from $28.1kg\;ha^{-1}$ to $58.8kg\;ha^{-1}$. Silica amount percolated through the soil profile have uniform trend comparatively showing $62.9kg\;ha^{-1}$ in Control, $64.8kg\;ha^{-1}$ in NPK treatment and $62.9kg\;ha^{-1}$ in NPK+Si treatment. Silica uptaked by Rice plant was $335.6kg\;ha^{-1}$ in Control, $406.6kg\;ha^{-1}$ in NPK+Si treatment and $471.1kg\;ha^{-1}$ in NPK+Si treatment. The difference between an amount of Si input(from rainfall, irrigation water and silicate fertilizer) and an amount of Si output(percolated Si in soil, uptaked Si by rice plant) was $357.4kg\;ha^{-1}$ in control, $412.1kg\;ha^{-1}$ in NPK treatment and $238.2kg\;ha^{-1}$ in NPK+Si treatment. Results of our study imply that paddy soil is a potential pool as a source of Si supply during growing periods of rice plant.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.107-119
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• 2020

This study analyzed past drought characteristics based on the observed rainfall data and performed a long-term outlook for future extreme droughts using Representative Concentration Pathways 8.5 (RCP 8.5) climate change scenarios. Standardized Precipitation Index (SPI) used duration of 1, 3, 6, 9 and 12 months, a meteorological drought index, was applied for quantitative drought analysis. A single long-term time series was constructed by combining daily rainfall observation data and RCP scenario. The constructed data was used as SPI input factors for each different duration. For the analysis of meteorological drought observed relatively long-term since 1954 in Korea, 12 rainfall stations were selected and applied 10 general circulation models (GCM) at the same point. In order to analyze drought characteristics according to climate change, trend analysis and clustering were performed. For non-stationary frequency analysis using sampling technique, we adopted the technique DEMC that combines Bayesian-based differential evolution ("DE") and Markov chain Monte Carlo ("MCMC"). A non-stationary drought frequency analysis was used to derive Severity-Duration-Frequency (SDF) curves for the 12 locations. A quantitative outlook for future droughts was carried out by deriving SDF curves with long-term hydrologic data assuming non-stationarity, and by quantitatively identifying potential drought risks. As a result of performing cluster analysis to identify the spatial characteristics, it was analyzed that there is a high risk of drought in the future in Jeonju, Gwangju, Yeosun, Mokpo, and Chupyeongryeong except Jeju corresponding to Zone 1-2, 2, and 3-2. They could be efficiently utilized in future drought management policies.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.919-928
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• 2023

Rainfall characteristics in Korea are concentrated during the summer flood season. In particular, when a large amount of turbid water flows into the dam due to the increasing trend of concentrated rainfall due to abnormal rainfall and abnormal weather conditions, prolonged turbid water phenomenon occurs due to the overturning phenomenon. Much research is being conducted on turbid water prediction to solve these problems. To predict turbid water, turbid water data from the upstream inflow is required, but spatial and temporal data resolution is currently insufficient. To improve temporal resolution, the development of the Turbidity-SS conversion equation is necessary, and to improve spatial resolution, multi-item water quality measurement instrument (YSI), Laser In-Situ Scattering and Transmissometry (LISST), and hyperspectral sensors are needed. Sensor-based measurement can improve the spatial resolution of turbid water by measuring line and surface unit data. In addition, in the case of LISST-200X, it is possible to collect data on particle size, etc., so it can be used in the Turbidity-SS conversion equation for fraction (Clay: Silt: Sand). In addition, among recent remote sensing methods, the spatial distribution of turbid water can be presented when using UAVs with higher spatial and temporal resolutions than other payloads and hyperspectral sensors with high spectral and radiometric resolutions. Therefore, in this study, the Turbidity-SS conversion equation was calculated according to the fraction through laboratory analysis using LISST-200X and YSI-EXO, and sensor-based field measurements including UAV (Matrice 600) and hyperspectral sensor (microHSI 410 SHARK) were used. Through this, the spatial distribution of turbidity and suspended sediment concentration, and the turbidity calculated using the Turbidity-SS conversion equation based on the measured suspended sediment concentration, was presented. Through this, we attempted to review the applicability of the Turbidity-SS conversion equation and understand the current status of turbid water occurrence.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.21 no.1
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• pp.24-35
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• 2016

To assess the relationship between environmental factors and seasonal phytoplankton community structure, we investigated abiotic and biotic factors in Ulsan Bay, Korea. We divided the bay into two areas based on geographical characteristics and compared the difference in each factor between inner and outer bay with t-test statistics. As a result, temperature in the outer bay was higher than that of the inner bay during winter (t = -5.833, p < 0.01) and autumn (p > 0.05). However, opposite trend was observed during spring (t = 4.247, p < 0.01) and summer (t = 2.876, p < 0.05). Salinity was significantly lower in the inner bay than in the outer bay in winter, spring, and summer (p < 0.01). However, the salinity was not significantly different between the inner and the outer bay in the autumn (p > 0.05). In particular, high nutrient concentration was observed in most stations during winter season due to vertical well mixing. The nutrient concentration was significantly higher in surface layers of inner bay after rainfall, particularly in the summer. The relative contribution (approximately 70%) of < $20{\mu}m$ (nano and pico) size phytoplankton was increased in all seasons with continuously low nutrients from the offshore water due to their adaption to low nutrient without other large competitors. Interestingly, high population of Eutreptiella gymnastica was kept in the inner bay during the spring and summer associated with high DIN (nitrate+nitrite, ammonium) after river discharge following rainfall, suggesting that DIN supply might have triggered the increase of Eutreptiella gymnastica population. In addition, high density of freshwater species Oscillatoria sp. and Microcystis sp. were found in several stations of the inner bay that were provided with large amounts of freshwater from the Tae-wha River. Diatom and cryptophyta species were found to be dominant species in the autumn and winter. Of these, centric diatom Chaetoceros genus was occupied in the outer bay in the autumn. Cryptophyta species known as opportunistic micro-algae were found to have high biomass without competitors in the inner bay. Our results demonstrated that Ulsan Bay was strongly affected by freshwater from Tae-wha River during the rainy season and by the surface warm water current from the offshore of the bay during dry season. These two external factors might play important roles in regulating the seasonal phytoplankton community structures.

• Korean Journal of Environmental Agriculture
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• v.13 no.2
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• pp.160-167
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• 1994

Meteorological elements such as air temperature, relative humidity, rainfall, sunshine duration, and so on observed by Korea Meteorological Administration, were analyzed to estimate the climatic change and to establish countermeasures in agriculture. Climatic differences were compared between two periods, early($1931{\sim}1960$) and late($1961{\sim}1990$), by calculating climatic resource indices, coldness index and warmth index of the two periods. Annual mean air temperatures of Seoul, Taegu, and Pusan in 1910's were 10.7, 12.3, and $13.4^{\circ}C$, respectively, having increased by $1.3^{\circ}C$ in Seoul and Taegu and by $0.9^{\circ}C$ in Pusan in 1990's. Mean air temperature in the spring($March{\sim}May$) increased by $0.69^{\circ}C$, which is a higher increasing rate than in the other seasons ($0.26{\sim}0.33^{\circ}C$). Regional differences exist in annual mean air temperature between the early and late part of the 20th century with little increase in this experiment did not germinate at pH 1.0. At pH 2.0, the flowering cabbage and geranium in the middle northern area, while in the southern part about $1^{\circ}C$increase was recorded during the last period. In the late period the annual rainfall increased by 100mm, except for the western coast area and the middle northern area. The P/E ratio showed a trend of an annual increase in the late period, being higher in the summer and lower in the winter. Relative humidity showed slight differences in seasons and regions but annual values did not. Duration of sunshine decreased by about an hour in the spring. Coldness index and warmth index of the late period were higher by 3.7 and 1.0 than those of the early period, respectively.

• The Journal of Engineering Geology
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• v.26 no.1
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• pp.63-70
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• 2016

The aim of this study is the safety and an accident prevention in limestone terrain by the underground tunneling. The geology of the study area consists of a Paleozoic sedimentary sequence dominated by limestone, sandstone, shale, and carbonaceous shale. The sequence gently dips to the northeast but the joint contains steep with variable trend. A significant fracture zone is developed in the limestone and shale beds, sub-parallel to bedding, and follows in part the limestone-sandstone contact. Monitoring of groundwater levels in the area shows marked fluctuations in the water table, which repeatedly rose to a level of -4 m before sinking to -15 m. These cycles occurred in mid-May, 2007 and in early and middle June. The data indicate that these fluctuations were unrelated to rainfall that occurred during the study period. We infer that the fluctuations were associated with the development of underground karstic networks along the deep fracture zone, and overlying ground subsidence is likely related to the rapid sinking of groundwater and the associated strong downward suction force.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.69-79
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• 2013

This paper presents a two-stage geostatistical integration approach that aims at downscaling of coarse scale remote sensing data. First, downscaling of the coarse scale sedoncary data is implemented using area-to-point kriging, and this result will be used as trend components on the next integration stage. Then simple kriging with local varying means that integrates sparse precise observation data with the downscaled data is applied to generate thematic information at a finer scale. The presented approach can not only account for the statistical relationships between precise observation and secondary data acquired at the different scales, but also to calibrate the errors in the secondary data through the integration with precise observation data. An experiment for precipitation mapping with weather station data and TRMM (Tropical Rainfall Measuring Mission) data acquired at a coarse scale is carried out to illustrate the applicability of the presented approach. From the experiment, the geostatistical downscaling approach applied in this paper could generate detailed thematic information at various finer target scales that reproduced the original TRMM precipitation values when upscaled. And the integration of the downscaled secondary information with precise observation data showed better prediction capability than that of a conventional univariate kriging algorithm. Thus, it is expected that the presented approach would be effectively used for downscaling of coarse scale data with various data acquired at different scales.

• Magazine of the Korean Society of Agricultural Engineers
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• v.8 no.2
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• pp.1193-1199
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• 1966

More stable and higher yields in rice paddy depend mainly upon an adequately balanced supply of water for higher yield. Rice paddy is supplied naturally by rainfall but inevitably requires artificial supplenental irrigation for higher yields. Even though it may be true that the water requirement of rice plants is generally higher than those of other crops, the submerged condition is not necessarily required for rice. The moisture requirements of rice vary according to its growing stages and it is possible to increse the irrigation efficiency by means of lessening the loss due to percolation and evapolation in the field. This experiment was conducted on the effect of the various amount of water supply and different irrigation periods for yield and yield components, and was carried out to find out the most suitable irrigation method and to increase the irrigation efficiency for higher yields in rice paddy. Randomized block design with 3 replications was employed where the 3 levels of the amount of irrigation water; (120% moisture contents), unirrigated (90~100%) and more un irrigated candition (80~90% moisture content), and levels of the various irrigation periods; usual, initial, intermediate and final periods, being treated. The results obtained in this experiment are as follows: 1. As for the physical and chemical and soil properfies, and other characteristics, there are no differences among the treatments enough to be effective for the growth of rice plants. 2. Culm length was measured after harvest as shown in table 2. 3. Difference of the amount of irrigation water did not change the culm length and ear length, however it also indicated more apparent increase in final treatment plots thatn that of usual. 3. No difference in the number of ears and number of ears pers per hill was founded treatments both in the difference of water supply and in the various irrigation periods. 4. There is no difference in the maturing rate and 1000 grains weight. 5. The number of panicles and grains and more increased in 80~100% moisture contents soil than those of 120%. and it shows in un irrigated plots, more irrigated plots and control plots in turn. Other wise according to the period\ulcorner of irrigation the trend is appeared in turn initial, usual, final and intermediate treatments.6. Yield as shown in table 7. 8 was more increased in unirrigated plots(90~IOO% moisture content) than the control plots (120% moisture content) by up to 8.2% and also 3. 2% in more unirrigated plots than that of control by periods is shown: usual plots final, initial, inter mediate treatment plots in turn. 7. The above resutts lead to the conclusion that no remarkable, differences in yields and soil properties are made by the unirrigation. However, it is apparent that this treatment has .some advantages in the points that one could spare the amount of water supply for irrigation with more increase in yield. In addition, a higher temperature and a brisk oxygen supply would be possible throug h this treatments. Accordingly, these treatment would be a more reasonable and economical cultivation method of rice for the better harvest.

• Journal of Korea Water Resources Association
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• v.38 no.12 s.161
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• pp.985-994
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• 2005

We examined problems of the principal component analysis(PCA), which is able to analyze at the low dimensionality as a methodologv to assess hydrologic time series, and introduced the theory and characteristics of independent component analysis(ICA) that can supplement problems of principal component analysis. We also applied the global sea surface temperature(SST) of the Nino region and assessed the correlation between El $\tilde{n}ino$-Southern Oscillation(ENSO) and SST. The results of examining separation-ability of principal components using mixed signals indicate that the independent component analysis is statistically superior compared to that of the principal component analysis. Finally, we assessed correlation between ENSO and global anomaly SST. The independent component analysis was applied to the $5^{\circ}{\times}5^{\circ}$(latitude and longitude) global anomaly SST in the Nino+3.4 region that is the El $\tilde{n}ino$ observation section. We assessed the correlation with the ENSO years. These results of the analysis show that only one independent component($86\%$) was able to represent the entire behavior and was consistent with the main ENSO years. Finally, we carried out independent component analysis for summer seasonal rainfalls at nine stations and could extract ICs to reflect geographical characteristics. The increasing trend has been shown at IC-1 and IC-2 since 1970s.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.3
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• pp.252-261
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• 2018

This study was conducted to develop a method to generate daily maximum and minimum temperatures using monthly data. We analyzed 30-year daily weather data of the 23 meteorological stations in South Korea and elucidated the parameters for predicting annual trend (center value ($\hat{U}$), amplitude (C), deviation (T)) and daily fluctuation (A, B) of daily maximum and minimum temperature. We use national average values for C, T, A and B parameters, but the center value is derived from the annual average data on each stations. First, daily weather data were generated according to the occurrence of rainfall, then calibrated using monthly data, and finally, daily maximum and minimum daily temperatures were generated. With this method, we could generate daily weather data with more than 95% similar distribution to recorded data for all 23 stations. In addition, this method was able to generate Growing Degree Day(GDD) similar to the past data, and it could be applied to areas not subject to survey. This method is useful for generating daily data in case of having monthly data such as climate change scenarios.