• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.170-170
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• 2018

In some case studies, the heavy precipitation events and rapid cyclogenesis in the extratropics can be caused by moist and warm tropical air masses. Tropical Moisture Exports (TME) correspond to the meridional transport of moist air masses, primarily born in tropical oceanic areas, to higher latitudes; and are closely related to flood events, especially in the mid-latitudes. The TME for the region of interest is mostly estimated by the back tracking approach using Lagrangian Analysis Tools (LAGRANTO) from ECMWF Re-Analysis (ERA) data. In this study, we aim to estimate the TME that are related to rainfall in Korea. The major moisture sources of the TME that contribute to heavy rainfall and extreme floods in Korea are identified. The TME is found to have significant connection with extreme events in Korea such as heavy rainfall and extreme flood events. The results show the most of the moisture sources comes from the west Pacific during the warm half of the year and it contributes significantly to the annual TME and is linked to the East Asian monsoon.

• Journal of Biosystems Engineering
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• v.26 no.1
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• pp.39-46
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• 2001

This research conducted to investigate the variation of the moisture content, crack ratio, and hardness of the whole and cracked brown rice after conditioning at the initial moisture content of 13, 14, and 15% with time lapse. The conditioning was conducted by increasing the moisture content of the sample to 0.4 and 0.8%. For basic information and conditioning characteristics for the development of a conditioning machine for the brown rice, predicted models of above three properties were developed using a nonlinear regression analysis of SAS with Gauss-Newton, Gradient, and DUD methods. Results of this research could be summarized as follows. 1. No moisture variation occurred after 0.5 hour conditioning. 2. The increasement of the crack ratio was 7.6 and 17.5% with the sample increased the moisture content of 0.4 and 0.8%, respectively, after 8 hours conditioning. 3. The hardness of the conditioned whole grain of the brown rice decreased 0.82 and 1,000kg$\_$f/ with the sample increased moisture content 0.4 and 0.8%, respectively, after 8 hours conditioning with respect to the non-conditioned sample. 4. The hardness of the conditioned cracked grain of the brown rice decreased 0.54 and 0.81kg$\_$f/ with the sample increased moisture content 0.4 and 0.8%, respectively, after 8 hours conditioning with respect to the non-conditioned sample. The hardness of the broken grain was about 0.81∼1.88kg$\_$f/ lower than whole grain. 5. The moisture content variation, increasing rate of the crack ratio, and hardness of the cracked and whole grain was predicted as a negative exponential function. 6. Each predicted model with the nonlinear regression analysis, which was very accurate and had a very small amount of sum of square of error between experimental value and predicted value, which could be used for predicting the physical variation after conditioning.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.5
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• pp.81-90
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• 2016

Due to droughts and water shortages causing severe damage to crops and other vegetations, much attention has been given to efficient irrigation for upland farming. However, little information has been known to measure soil moisture levels in a field scale and apply their spatial variability for proper irrigation scheduling. This study aimed to characterize the spatial variability and temporal stability of soil water contents at depths of 10 cm, 20 cm and 30 cm on flat (loamy soil) and hill-slope fields (silt-loamy soil). Field monitoring of soil moisture contents was used for variogram analysis using GS+ software. Kriging produced from the structural parameters of variogram was applied for the means of spatial prediction. The overall results showed that the surface soil moisture presented a strong spatial dependence at the sampling time and space in the field scale. The coefficient variation (CV) of soil moisture was within 7.0~31.3 % in a flat field and 8.3~39.4 % in a hill-slope field, which was noticeable in the dry season rather than the rainy season. The drought assessment analysis showed that only one day (Dec. 21st) was determined as dry (20.4 % and 24.5 % for flat and hill-slope fields, respectively). In contrary to a hill-slope field where the full irrigation was necessary, the centralized irrigation scheme was appeared to be more effective for a flat field based on the spatial variability of soil moisture contents. The findings of this study clearly showed that the geostatistical analysis of soil moisture contents greatly contributes to proper irrigation scheduling for water-efficient irrigation with maximal crop productivity and environmental benefits.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1935-1943
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• 2022

The development and application of a high-resolution soil moisture mapping method using satellite imagery has been considered one of the major research themes in remote sensing. In this study, soil moisture mapping in the test area of Jeju Island was performed. The soil moisture was calculated with optical images using linearly adjusted Synthetic Aperture Radar (SAR) polarization images and incident angle. SAR Backscatter data, Analysis Ready Data (ARD) provided by Google Earth Engine (GEE), was used. In the soil moisture processing process, the optical image was applied to normalized difference vegetation index (NDVI) by surface reflectance of KOMPSAT-3 satellite images and the land cover map of Environmental Systems Research Institute (ESRI). When the SAR image and the optical images are fused, the reliability of the soil moisture product can be improved. To validate the soil moisture mapping product, a comparative analysis was conducted with normalized difference water index (NDWI) products by the KOMPSAT-3 image and those of the Landsat-8 satellite. As a result, it was shown that the soil moisture map and NDWI of the study area were slightly negative correlated, whereas NDWI using the KOMPSAT-3 images and the Landsat-8 satellite showed a highly correlated trend. Finally, it will be possible to produce precise soil moisture using KOMPSAT optical images and KOMPSAT SAR images without other external remotely sensed images, if the soil moisture calculation algorithm used in this study is further developed for the KOMPSAT-5 image.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.6
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• pp.11-20
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• 2020

We estimated the spatio-temporally distributed soil moisture using Sentinel-1A/B SAR (Synthetic Aperture Radar) sensor images and soil moisture data assimilation technique in South Korea. Soil moisture data assimilation technique can extract the hydraulic parameters of soils using observed soil moisture and GA (Genetic Algorithm). The SWAP (Soil Water Atmosphere Plant) model associated with a soil moisture assimilation technique simulates the soil moisture using the soil hydraulic parameters and meteorological data as input data. The soil moisture based on Sentinel-1A/B was validated and evaluated using the pearson correlation and RMSE (Root Mean Square Error) analysis between estimated soil moisture and TDR soil moisture. The soil moisture data assimilation technique derived the soil hydraulic parameters using Sentinel-1A/B based soil moisture images, ASOS (Automated Synoptic Observing System) weather data and TRMM (Tropical Rainfall Measuring Mission)/GPM (Global Precipitation Measurement) rainfall data. The derived soil hydrological parameters as the input data to SWAP were used to simulate the daily soil moisture values at the spatial domain from 2001 to 2018 using the TRMM/GPM satellite rainfall data. Overall, the simulated soil moisture estimates matched well with the TDR measurements and Sentinel-1A/B based soil moisture under various land surface conditions (bare soil, crop, forest, and urban).

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.152-152
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• 2018

Soil moisture is a important factor in hydrologic analysis. So, if we have spatially distributed soil moisture data, it can help to study much research in a various field. Recently, there are a lot of satellite derived soil moisture data, and it can be served through web freely. Especially, NASA (National Aeronautics and Space Administration) launched the Soil Moisture Aperture Passive (SMAP) satellite for mapping global soil moisture on 31 January 2015. SMAP data have many advantages for study, for example, SMAP data has higher spatial resolution than other satellited derived data. However, becuase many satellited derived soil moisture data have a limitation to data accuracy, if we have ancillary materials for improving data accuracy, it can be used. So, in this study, after applying the alogorithm, which is data assimilation methods, applicability of satellite derived soil moisture data was analyzed. Among the various data assimilation methods, in this study, Model Output Statistics (MOS) technique was used for improving satellite derived soil moisture data. Model Output Statistics (MOS) is a type of statistical post-processing, a class of techniques used to improve numerical weather models' ability to forecast by relating model outputs to observational or additional model data.

• Journal of the Korean Society of Clothing and Textiles
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• v.23 no.6
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• pp.820-828
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• 1999

The purpose of this study was to investigate the changes of pore area and water vapour transport by the changes of moisture regain and fabric structure of wool fabrics, As specimens 4 worsted wool fabrics were used. The pore area were measured by image analysis method and dinamic vapour transport and water reisitance was determined by clothing-environment-body modelling system. The pore area was changed by the moisture regain of wool fabrics. The change of pore area was influenced by the yarn twist thread count and cover factor and the weave type. The water vapour transport was changed by the moisture regain. The change of water vapour transport was influenced by the change of pore aree which was determined by image analysis.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.3
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• pp.161-170
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• 2013

Spatio-temporal distribution of soil moisture was studied to improve understanding of hydrological processes at hillslope scale. Using field measurements for three designated periods during the spring, summer and autumn seasons in 2010 obtained from Beomryunsa hillslope located at the Sulmachun watershed, correlation analysis was performed between soil moisture measurements and 18 different terrain attributes (e.g., curvatures and topographic index). The results of correlation analysis demonstrated distinct seasonal variation features of soil moisture in different depths with different terrain attributes and rainfall amount. The relationship between predicted flow lines and distribution of the soil moisture provided appropriate model structures and terrain indices.

• Journal of Biosystems Engineering
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• v.41 no.3
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• pp.273-280
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• 2016

Purpose: This experiment was conducted to detect water stress in terms of the moisture content of cucumber seedlings under water stress condition using a hyperspectral image acquisition system, linear regression analysis, and partial least square regression (PLSR) to achieve a non-destructive measurement procedure. Methods: Changes in the reflectance spectrum of cucumber seedlings under water stress were measured using hyperspectral imaging techniques. A model for estimating moisture content of cucumber seedlings was constructed through a linear regression analysis that used the moisture content of cucumber seedlings and a normalized difference vegetation index (NDVI). A model using PLSR that used the moisture content of cucumber seedlings and reflectance spectrum was also created. Results: In the early stages of water stress, cucumber seedlings recovered completely when sub-irrigation was applied. However, the seedlings suffering from initial wilting did not recover when more than 42 h passed without irrigation. The reflectance spectrum of seedlings under water stress decreased gradually, but increased when irrigation was provided, except for the seedlings that had permanently wilted. From the results of the linear regression analysis using the NDVI, the model excluding wilted seedlings with less than 20% (n=97) moisture content showed a precision ($R^2$ and $R^2_{\alpha}$) of 0.573 and 0.568, respectively, and accuracy (RE) of 4.138% and 4.138%, which was higher than that for models including all seedlings (n=100). For PLS regression analysis using the reflectance spectrum, both models were found to have strong precision ($R^2$) with a rating of 0.822, but accuracy (RMSE and RE) was higher in the model excluding wilted seedlings as 5.544% and 13.65% respectively. Conclusions: The estimation model of the moisture content of cucumber seedlings showed better results in the PLSR analysis using reflectance spectrum than the linear regression analysis using NDVI.

• Journal of the Korean Society of Combustion
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• v.14 no.3
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• pp.16-23
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• 2009

It is strongly desired for coal-fired power plants to utilize not only low-rank coals with high moisture contents, but also lowering cost with diversifying fuel sources. In this study, combustion characteristics of low rank coal with high moisture, and standard pulverized coals are experimentally investigated using TGA (Thermogravimetric Analysis) and DTF (drop tube furnace). The coals tested are three kinds of coal with moisture content ranging from 8.32 to 26.82%. The results show that under the air combustion condition, the burn-out time at TGA rises as moisture content increases, and standard pulverized coal with 8.32% moisture content showed the lowest activation energy of 55.73 kJ/mol. In case of the high amount of moisture, the combustion efficiency decreases due to evaporation heat loss, and unburned carbon in ash produced at combustion process in DTF increased. Aslo, initial deformation temperature of slag attached in alumina tube of DTF decreased with lowering the crytallinity of anorthite and augite. To improve the combustion reactivity and efficiency, it is effective to upgrade through drying the high moisture coal to moisture level (less than 10%) of standard pulverized coal.