• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.1
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• pp.10-19
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• 2011

In order to predict the risk of anthracnose on hot pepper in the future, the projected climate data from SRES A1B scenario in South Korea were used with the modified anthracnose model to calculate Infection Risk (IR), which was to estimate the number of fungicide sprays. Based on daily temperature and precipitation, the anthracnose model resulted in an empirical relationship that IR = (Daily temperature - $16^{\circ}C$) ${\times}$ 0.07 + (Daily precipitation ${\times}$ 0.11). For 135 locations in South Korea, the total number of fungicide sprays needed from 2011 to 2100 was 12,150, indicating a complicated change with an overall increase in anthracnose development in all locations until 2100. In particular, radical changes in anthracnose development were predicted at Yeongdeok, Yeongyang, and Uiseong, whereas gradual changes were predicted at Heongsung, Hamyang and Taean. The eastern counties of Gyeongbuk Province, which ar the major plantation area in these days, would be the place with the highest disease pressure in the future. In addition, the years of 2058, 61, 78 and 2096 will be most severe, requiring 8-11 times of fungicide spraying. The GIS maps show that the mountain areas of Jeonbuk and Chungbuk Province would have the least disease pressure of anthracnose in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5964-5970
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• 2013

The recent budget planning for highway infrastructure implied that the investments for Operation & Maintenance(O&M) became greater than that for new construction. This circumstance made many stakeholders pay attention to the O&M of road infrastructure and adopt other countries' policies and system for effective management. In other countries, most O&M for road infrastructure have been done by private entities using long-term contract and Korea is about to shift from one year contract to long-term contract. The most important parts for the expansion of the long-term O&M contract for road infrastructure are valuation of the O&M contract based on accurate prediction of O&M costs and instrument for proper risk sharing between contracting parties. Thus, this study provides a methodology to estimate a reasonable O&M contract price and a framework to share contract risk between contracting parties using real option. The analysis results showed that the contract price and ceiling and floor conditions for the 20 year-contract of 20 km-highway project were 45.7, 60 and 42.3 billion won, respectively.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.999-1009
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• 2019

The importance of high-resolution sea ice maps of the Arctic Ocean is increasing due to the possibility of pioneering North Pole Routes and the necessity of precise climate prediction models. In this study,sea ice classification algorithms for two deep learning models were examined using Sentinel-1 A/B SAR data to generate high-resolution sea ice classification maps. Based on current ice charts, three classes (Open Water, First Year Ice, Multi Year Ice) of training data sets were generated by Arctic sea ice and remote sensing experts. Ten sea ice classification algorithms were generated by combing two deep learning models (i.e. Simple CNN and Resnet50) and five cases of input bands including incident angles and thermal noise corrected HV bands. For the ten algorithms, analyses were performed by comparing classification results with ground truth points. A confusion matrix and Cohen's kappa coefficient were produced for the case that showed best result. Furthermore, the classification result with the Maximum Likelihood Classifier that has been traditionally employed to classify sea ice. In conclusion, the Convolutional Neural Network case, which has two convolution layers and two max pooling layers, with HV and incident angle input bands shows classification accuracy of 96.66%, and Cohen's kappa coefficient of 0.9499. All deep learning cases shows better classification accuracy than the classification result of the Maximum Likelihood Classifier.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.483-497
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• 2016

Unmanned Aerial Vehicle (UAV) imagery are being assessed for analyzing within field spatial variability for agricultural precision management, because UAV imagery may be acquired quickly during critical periods of rapid crop growth. This study refers to the derivation of barley and wheat growth prediction equation by using UAV derived vegetation index. UAV imagery was taken on the test plots six times from late February to late June during the barley and wheat growing season. The field spectral reflectance during growing period for the 5 variety (Keunal-bori, Huinchalssal-bori, Saechalssal-bori, Keumkang and Jopum) were measured using ground spectroradiometer and three growth parameters, including plant height, shoot dry weight and number of tiller were investigated for each ground survey. Among the 6 Vegetation Indices (VI), the RVI, NDVI, NGRDI and GLI between measured and image derived showed high relationship with the coefficient of determination respectively. Using the field investigation data, the vegetation indices regression curves were derived, and the growth parameters were tried to compare with the VIs value.

• Journal of Korean Society of Steel Construction
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• v.26 no.4
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• pp.323-334
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• 2014

In this paper, experimental program and associated numerical study were carried out to evaluate the fire resistance of unprotected concrete-filled rectangular steel tubular (CFT) columns subjected to the standard fire. The key testing parameters included the length effect, the load ratio, and the sectional dimensions of the CFT columns. Temperature distribution and axial deformation of the CFT column specimens were measured and analyzed. Rather early local buckling of steel tubes was observed in all the specimens. This caused subsequent load transfer from steel tube to concrete, and eventually triggered concrete crushing, or complete loss of the load bearing capacity of the column. This implies that the limit state of local buckling as well as overall flexural buckling should be incorporated in fire design procedure. As expected, the fire resistance time of specimen with higher load ratio consistently lessened. The prediction of fire resistance time of unprotected CFT columns based on the limiting steel temperature in current design codes or the formula proposed by previous studies is slightly conservative compared to the fire test results available. To establish the finite element analysis model that can be used to predict the thermal and structural behaviour of unprotected CFT columns in fire, the fully coupled thermal-stress analysis was also tried by using the commercial code ABAQUS. The numerical results showed a reasonable global correlation with the experimental results.

• Korean Journal of Soil Science and Fertilizer
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• v.41 no.3
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• pp.228-234
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• 2008

The purpose of this study was to predict environmental distribution of anthracene, benzene, benzo[a]pyrene, 1-methylphenanthrene and phenanthrene in a four phase biopile system - air, water, soil and non aqueous phase liquid (NAPL) phase using level I fugacity model. Soil samples used for this study were collected from three sites in the United Kingdom which were historically contaminated with petroleum hydrocarbons. The level I fugacities (f) for the five contaminants were markedly different, however, the fugacities of each contaminant in three soil samples did not show significant difference. NAPL and soil were the dominant phases for all five contaminants. Results of this study indicated that difference in percentage of organic carbon strongly influenced the partitioning behavior of the cntaminants. The presence of benzene calls for an urgent need for risk-based management of air and water phase. Whereas insignificant amount of chemicals leached in the water phase for other organic contaminants showing greatly reduced potential of groundwater contamination. Furthermore, this study helped us to confirm the association of risk critical contaminants with the residual saturation in treated soils. They also can be used to emphasize the importance of accounting for the partitioning behavior of both NAPL and soil phases in the process of the risk assessment of the sites contaminated with petroleum hydrocarbons.

• Journal of Korean Society on Water Environment
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• v.28 no.3
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• pp.347-358
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• 2012

The SWAT (Soil and Water Assessment Tool) should be calibrated and validated with observed data to secure accuracy of model prediction. Recently, the SWAT-CUP (Calibration and Uncertainty Program for SWAT) software, which can calibrate SWAT using various algorithms, were developed to help SWAT users calibrate model efficiently. In this study, three algorithms (GLUE: Generalized Likelihood Uncertainty Estimation, PARASOL: Parameter solution, SUFI-2: Sequential Uncertainty Fitting ver. 2) in the SWAT-CUP were applied for the Soyang-gang dam watershed to evaluate these algorithms. Simulated total streamflow and 0~75% percentile streamflow were compared with observed data, respectively. The NSE (Nash-Sutcliffe Efficiency) and $R^2$ (Coefficient of Determination) values were the same from three algorithms but the P-factor for confidence of calibration ranged from 0.27 to 0.81 . the PARASOL shows the lowest p-factor (0.27), SUFI-2 gives the greatest P-factor (0.81) among these three algorithms. Based on calibration results, the SUFI-2 was found to be suitable for calibration in Soyang-gang dam watershed. Although the NSE and $R^2$ values were satisfactory for total streamflow estimation, the SWAT simulated values for low flow regime were not satisfactory (negative NSE values) in this study. This is because of limitations in semi-distributed SWAT modeling structure, which cannot simulated effects of spatial locations of HRUs (Hydrologic Response Unit) within subwatersheds in SWAT. To solve this problem, a module capable of simulating groundwater/baseflow should be developed and added to the SWAT system. With this enhancement in SWAT/SWAT-CUP, the SWAT estimated streamflow values could be used in determining standard flow rate in TMDLs (Total Maximum Daily Load) application at a watershed.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.823-832
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• 2006

Precipitation is the most important component to the study of water and energy cycle in hydrology. In this study we investigate rainfall retrieval uncertainty from different sources of remotely sensed precipitation field and then probable error propagation in the simulation of hydrologic variables especially, runoff on different vegetation cover. Two remotely sensed rainfall retrievals (space-borne IR-only and ground radar rainfall) are explored and compared visually and statistically. Then, an offline Community Land Model (CLM) is forced with in situ meteorological data to simulate the amount of runoff and determine their impact on model predictions. A fundamental assumption made in this study is that CLM can adequately represent the physical land surface processes. Results show there are big differences between different sources of precipitation fields in terms of the magnitude and temporal variability. The study provides some intuitions on the uncertainty of hydrologic prediction via the interaction between the land surface and near atmosphere fluxes in the modelling approach. Eventually it will contribute to the understanding of water resources redistribution to the climate change in Korean Peninsula.

• Journal of Korea Water Resources Association
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• v.50 no.2
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• pp.89-97
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• 2017

Turbulent flow structure in the high amplitude meandering channel is complex due to secondary recirculation with helicoidal motions and shear layers formed by flow separation from the curved sidewall. In this work, the secondary flow and the superelevation of the water surface produced in the high-amplitude Kinoshita channel are reproduced by the unsteady Reynolds-averaged Navier-Stokes (RANS) computations using the VOF technique for resolving the variation of water surface elevation and three statistical turbulence models ($k-{\varepsilon}$, RNG $k-{\varepsilon}$, $k-{\omega}$ SST). The numerical results computed by a second-order accurate finite volume method are compared with an existing experimental measurement. Among applied turbulence models, $k-{\omega}$ SST model relatively well predicts overall distribution of the secondary recirculation in the Kinoshita channel, while all three models yield similar prediction of water superelevation transverse slope. The secondary recirculation driven by the radial acceleration in the upstream bend affects the flow structure in the downstream bend, which yields a pair of counter-rotating vortices at the bend apex. This complex flow pattern is reasonably well reproduced by the $k-{\omega}$ SST model. Both $k-{\varepsilon}$ based models fail to predict the clockwise-rotating vortex between a pair of counter-rotating vortices which was observed in the experiment. Regardless of applied turbulence models, the present computations using the VOF method appear to well reproduce the superelevation of water surface through the meandering channel.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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• pp.148-155
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• 2005

An accurate prediction of blooming date is crucial for many authorities to schedule and organize successful spring flower festivals in Korea. The Korea Meteorological Administration (KMA) has been using regression models combined with a subjective correction by forecasters to issue blooming date forecasts for major cities. Using mean monthly temperature data for February (observed) and March (predicted), they issue blooming date forecasts in late February to early March each year. The method has been proved accurate enough for the purpose of scheduling spring festivals in the relevant cities, but cannot be used in areas where no official climate and phenology data are available. We suggest a thermal time-based two-step phenological model for predicting the blooming dates of spring flowers, which can be applied to any geographic location regardless of data availability. The model consists of two sequential periods: the rest period described by chilling requirement and the forcing period described by heating requirement. It requires daily maximum and minimum temperature as an input and calculates daily chill units until a pre-determined chilling requirement for rest release. After the projected rest release date, it accumulates daily heat units (growing degree days) until a pre- determined heating requirement for flowering. Model parameters were derived from the observed bud-burst and flowering dates of cherry tree (Prunus serrulata var. spontanea) at KMA Seoul station along with daily temperature data for 1923-1950. The model was applied to the 1955-2004 daily temperature data to estimate the cherry blooming dates and the deviations from the observed dates were compared with those predicted by the KMA method. Our model performed better than the KMA method in predicting the cherry blooming dates during the last 50 years (MAE = 2.31 vs. 1.58, RMSE = 2.96 vs. 2.09), showing a strong feasibility of operational application.