• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.327-339
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• 2020

Transpiration is the movement of water into the atmosphere through leaf stomata of plant, and it accounts for more than half of evapotranspiration from the land surface. The measurements of transpiration could be conducted in various ways including eddy covariance and water balance method etc. However, the transpiration measurements of individual trees are necessary to quantify and compare the water use of each species and individual component within stands. For the measurement of the transpiration by individual tree, the thermometric methods such as heat dissipation and heat pulse methods are widely used. However, it is difficult and labor consuming to maintain the transpiration measurements of individual trees in a wide range area and especially for long-term experiment. Therefore, the sharing of sapflow data through database should be useful to promote the studies on transpiration and water balance for large spatial scale. In this paper, we present sap flow database, which have Granier type sap flux data from 18 Korean pine (Pinus koraiensis) since 2011 and 16 (Quercus aliena) since 2013 in Mt.Taehwa Seoul National University forest and 18 needle fir (Abies holophylla), seven (Quercus serrata), three (Carpinus laxiflora and C. cordata each since 2013 in Gwangneung. In addition, the database includes the sapling transpiration of nine species (Prunus sargentii, Larix kaempferii, Quercus accutisima, Pinus densiflora, Fraxinus rhynchophylla, Chamecypans obtuse, P. koraiensis, Betulla platyphylla, A. holophylla, Pinus thunbergii), which were measured using heat pulse method since 2018. We believe this is the first database to share the sapflux data in Rep. of Korea, and we wish our database to be used by other researchers and contribute a variety of researches in this field.

• Economic and Environmental Geology
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• v.44 no.1
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• pp.71-82
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• 2011

The unsaturated soil column tests were carried out for weathered gneiss soil and weathered granite soil in order to obtain the relationship between rainfall intensity and infiltration velocity of rainfall on the basis of different unit weight conditions of soil. In this study, volumetric water content and pore water pressure were measured using TDR sensors and tensiometers at constant time interval. For the column test, three different unit weights were used as in-situ condition, loose condition and dense condition, and rainfall intensities were selected as 20 mm/h and 50 mm/h. In 20 mm/h rainfall intensity condition, average rainfall infiltration velocities for both gneiss and weathered granite soils were obtained as $2.854{\times}10^{-3}$ cm/s ~ $1.297{\times}10^{-3}$ cm/s for different unit weight values and $2.734{\times}10^{-3}$ cm/s ~ $1.707{\times}10^{-3}$ cm/s, respectively. In 50 mm/h rainfall intensity condition, rainfall infiltration velocities were obtained as $4.509{\times}10^{-3}$ cm/s ~ $2.016{\times}10^{-3}$ cm/s and $4.265{\times}10^{-3}$ cm/s ~ $3.764{\times}10^{-3}$ cm/s respectively. The test results showed that the higher rainfall intensity and the lower unit weight of soil, the faster average infiltration velocity. In addition, the weathered granite soils had faster rainfall infiltration velocities than those of the weathered gneiss soils except for the looser unit weight conditions. This is due to the fact that the weathered granite soil had more homogeneous particle size, smaller unit weight condition and larger porosity.

• Journal of the Korean earth science society
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• v.31 no.6
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• pp.600-607
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• 2010

In 2008, multiple episodes of large-scale transport of natural airborne particles and anthropogenically affected particles from different sources in the East Asian continent were identified in the National Oceanic and Atmospheric Administration (NOAA) satellite RGB-composite images and the mass concentrations of ground level particulate matters. To analyze the aerosol size distribution during the large-scale transport of atmospheric aerosols, both aerosol optical depth (AOD; proportional to the aerosol total loading in the vertical column) and fine aerosol weighting (FW; fractional contribution of fine aerosol to the total AOD) of Moderate resolution Imaging Spectroradiometer (MODIS) aerosol products were used over the East Asian region. The six episodes of massive natural airborne particles were observed at Cheongwon, originating from sandstorms in northern China, Mongolia and the loess plateau of China. The $PM_{10}$ and $PM_{2.5}$ stood at 70% and 16% of the total mass concentration of TSP, respectively. However, the mass concentration of $PM_{2.5}$ among TSP increased as high as 23% in the episode in which they were flowing in by way f the industrial area in east China. In the other five episodes of anthropogenically affected particles that flowed into the Korean Peninsula from east China, the mass concentrations of $PM_{10}$ and $PM_{2.5}$ among TSP reached 82% and 65%, respectively. The average AOD for the large-scale transport of anthropogenically affected particle episodes in the East Asian region was measured at $0.42{\pm}0.17$ compared with AOD ($0.36{\pm}0.13$) for the natural airborne particle episodes. Particularly, the regions covering east China, the Yellow Sea, the Korean Peninsula, and the east Korean sea were characterized by high levels of AOD. The average FW values observed during the event of anthropogenically affected aerosols ($0.63{\pm}0.16$) were moderately higher than those of natural airborne particles ($0.52{\pm}0.13$). This observation suggests that anthropogenically affected particles contribute greatly to the atmospheric aerosols in East Asia.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.525-536
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• 2014

In this study, a method to assess and monitor hydrological drought using remote sensing was investigated for use in regions with limited observation data, and was applied to the Upper Namhangang basin in South Korea, which was seriously affected by the 2008-2009 drought. Drought information may be obtained more easily from meteorological data based on water balance than hydrological data that are hard to estimate. Air temperature data at 2 m above ground level (AGL) were estimated using remotely sensed data, evapotranspiration was estimated from the air temperature, and the correlations between precipitation minus evapotranspiration (P-PET) and streamflow percentiles were examined. Land Surface Temperature data with $1{\times}1km$ spatial resolution as well as Atmospheric Profile data with $5{\times}5km$ spatial resolution from MODIS sensor on board Aqua satellite were used to estimate monthly maximum and minimum air temperature in South Korea. Evapotranspiration was estimated from the maximum and minimum air temperature using the Hargreaves method and the estimates were compared to existing data of the University of Montana based on Penman-Monteith method showing smaller coefficient of determination values but smaller error values. Precipitation was obtained from TRMM monthly rainfall data, and the correlations of 1-, 3-, 6-, and 12-month P-PET percentiles with streamflow percentiles were analyzed for the Upper Namhan-gang basin in South Korea. The 1-month P-PET percentile during JJA (r = 0.89, tau = 0.71) and SON (r = 0.63, tau = 0.47) in the Upper Namhan-gang basin are highly correlated with the streamflow percentile with 95% confidence level. Since the effect of precipitation in the basin is especially high, the correlation between evapotranspiration percentile and streamflow percentile is positive. These results indicate that remote sensing-based P-PET estimates can be used for the assessment and monitoring of hydrological drought. The high spatial resolution estimates can be used in the decision-making process to minimize the adverse impacts of hydrological drought and to establish differentiated measures coping with drought.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.6
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• pp.1203-1210
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• 2012

As the area of upland crops increase, it is become more important for farmers to understand status of soil water at their own fields due to key role of proper irrigation. In order to estimate daily water balance and soil water content with simple weather data and irrigation records, we have developed the model for estimating water balance and soil water content, called AFKAE0.5, and verified its simulated results comparing with daily change of soil water content observed by soil profile moisture sensors. AFKAE0.5 has two hypothesis before establishing its system. The first is the soil in the model has 300 mm in depth with soil texture. And the second is to simplify water movement between the subjected soil and beneath soil dividing 3 categories which is defined by soil water potential. AFKAE0.5 characterized with determining the amount of upward and downward water between the subjected soil and beneath soil. As a result of simulation of AFKAE0.5 at Gongju region with red pepper cultivation in 2005, the water balance with input minus output is recorded as - 88 mm. the amount of input water as precipitation, irrigation, and upward water is annually 1,043, 0, and 207 mm, on the other, output as evapotranspiration, run-off, and percolation is 831, 309, and 161 mm, respectively.

• Journal of Bio-Environment Control
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• v.15 no.4
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• pp.296-305
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• 2006

The heterogeneity of crop transpiration is important to clearly understand the microclimate mechanisms and to efficiently handle the water resource in greenhouses. A computational fluid dynamic program (Fluent CFD version 6.2) was developed to study the internal climate and crop transpiration distributions of greenhouses. Additionally, the global solar radiation model and a crop heat exchange model were programmed together. Those models programmed using $C^{++}$ software were connected to the CFD main module using the user define function (UDF) technology. For the developed CFD validity, a field experiment was conducted at a $17{\times}6 m^2$ plastic-covered mechanically ventilated single-span greenhouse located at Pusan in Korea. The CFD internal distributions of air temperature, relative humidity, and air velocity at 1m height were validated against the experimental results. The CFD computed results were in close agreement with the measured distributions of the air temperature, relative humidity, and air velocity along the greenhouse. The averaged errors of their CFD computed results were 2.2%,2.1%, and 7.7%, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.259-267
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• 2020

This study measured the Particulate Matter (PM) concentration according to altitude (30 m, 60 m, 90 m, 120 m, and 150 m) in three different environments: a construction site, natural environment (arboretum), and residential area. PM_2.5 and PM₁₀ values at 30 m above the construction site were 18.63 ㎍/㎥ and 24.23 ㎍/㎥ while values at 150 m were 10.89 ㎍/㎥ and 10.61 ㎍/㎥, respectively, indicating the average concentration decreased as altitude increased. PM_2.5 and PM₁₀ values at 30 m above the natural environment were 9.03 ㎍/㎥ and 11.21 ㎍/㎥ while those at 150 m were 3.42 ㎍/㎥ and 3.57 ㎍/㎥, respectively, showing lower average concentrations as altitude increased. PM_2.5 and PM₁₀ values at 30 m above the residential area were 10.65 ㎍/㎥ and 12.06 ㎍/㎥ while those at 150 m were 4.24 ㎍/㎥ and 5.17 ㎍/㎥, also demonstrating lower PM concentrations as altitude increased. The PM concentrations decreased as altitude increased at all tested sites and also decreased between environments in the following order: construction site, residential area, and natural environment. The results of this study are significant because PM concentrations were measured at various altitudes at different land-use sites. The results are expected to serve as basic data for decision-making in both regional and urban planning.

• Journal of Life Science
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• v.30 no.2
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• pp.137-146
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• 2020

Calcium is one of the important secondary signaling molecules in plant cells. Calcium-dependent protein kinases (CDPK)-the sensor proteins of Ca²⁺ and phosphorylating enzymes-are the most abundant serine/threonine kinases in plant cells. They convert and transmit signals in response to various stimuli, resulting in specific responses in plants. In rice, 31 CDPK gene families have been identified, which are mainly involved in plant growth and development and are known to play roles in response to various stress conditions. However, little is known about the biochemical characteristics of CDPK proteins. In this study, OsCPK11-a CDPK in rice-was partially purified, and its biochemical characteristics were found. Partially purified OsCPK11 from rice seedlings was obtained by three-step column chromatography that involved anion exchange chromatography consisting of DEAE, hydrophobic interaction chromatography consisting of phenyl-Sepharose, and gel filtration chromatography consisting of Sephacryl-200HR. An in vitro kinase assay using partially purified OsCPK11 was also performed. This partially purified OsCPK11 had a molecular weight of 54 kDa and showed a strong hydrophobic interaction with the hydrophobic resin. In vitro kinase assay showed that the OsCPK11 also had Ca²⁺-dependent autophosphorylation activity. The OsCPK11 phosphorylated histone III-S, and the optimum pH for its kinase activity was found to be 7.5~8.0. The native OsCPK11 shared several biochemical characteristics with recombinant OsCPK11 studied previously, and both had Ca²⁺-dependent autophosphorylation activity and favored histone III-S as a substrate for kinase activity, which also had a Ca²⁺-dependence.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.507-520
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• 2007

Satellite passive microwave(PM) sensors have been observing polar sea ice concentration(SIC), ice temperature, and snow depth since 1970s. Among them SIC is playing an important role in the various studies as it is considered the first factor for the monitoring of global climate and environment changes. Verification and correction of PM SIC is essential for this purpose. In this study, we calculated SIC from KOMPSAT-1 EOC images obtained from Arctic sea ice edges from July to August 2005 and compared with SSM/I SIC calculated from NASA Team(NT) algorithm. When we have no consideration of sea ice types, EOC and SSM/I NT SIC showed low correlation coefficient of 0.574. This is because there are differences in spatial resolution and observing time between two sensors, and the temporal and spatial variation of sea ice was high in summer Arctic ice edge. For the verification of SSM/I NT SIC according to sea ice types, we divided sea ice into land-fast ice, pack ice, and drift ice from EOC images, and compared them with SSM/I NT SIC corresponding to each ice type. The concentration of land-fast ice between EOC and SSM/I SIC were calculated very similarly to each other with the mean difference of 0.38%. This is because the temporal and spatial variation of land-fast ice is small, and the snow condition on the ice surface is relatively dry. In case of pack ice, there were lots of ice ridge and new ice that are known to be underestimated by NT algorithm. SSM/I NT SIC were lower than EOC SIC by 19.63% in average. In drift ice, SSM/I NT SIC showed 20.17% higher than EOC SIC in average. The sea ice with high concentration could be included inside the wide IFOV of SSM/I because the drift ice was located near the edge of pack ice. It is also suggested that SSM/I NT SIC overestimated the drift ice covered by wet snow.

• Journal of the Korean earth science society
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• v.40 no.5
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• pp.447-463
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• 2019

Sea surface wind is a fundamental element for understanding the oceanic phenomena and for analyzing changes of the Earth environment caused by global warming. Global research institutes have developed and operated scatterometers to accurately and continuously observe the sea surface wind, with the accuracy of approximately ${\pm}20^{\circ}$ for wind direction and ${\pm}2m\;s^{-1}$ for wind speed. Given that the spatial resolution of the scatterometer is 12.5-25.0 km, the applicability of the data to the coastal area is limited due to complicated coastal lines and many islands around the Korean Peninsula. In contrast, Synthetic Aperture Radar (SAR), one of microwave sensors, is an all-weather instrument, which enables us to retrieve sea surface wind with high resolution (<1 km) and compensate the sparse resolution of the scatterometer. In this study, we investigated the Geophysical Model Functions (GMF), which are the algorithms for retrieval of sea surface wind speed from the SAR data depending on each band such as C-, L-, or X-band radar. We reviewed in the simulation of the backscattering coefficients for relative wind direction, incidence angle, and wind speed by applying LMOD, CMOD, and XMOD model functions, and analyzed the characteristics of each GMF. We investigated previous studies about the validation of wind speed from the SAR data using these GMFs. The accuracy of sea surface wind from SAR data changed with respect to observation mode, GMF type, reference data for validation, preprocessing method, and the method for calculation of relative wind direction. It is expected that this study contributes to the potential users of SAR images who retrieve wind speeds from SAR data at the coastal region around the Korean Peninsula.