• Korean Journal of Soil Science and Fertilizer
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• v.36 no.4
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• pp.181-192
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• 2003

We developed a mathematical simulation model to portray the vertical distribution of soil water from the measured weather data and the known soil hydraulic properties, and then compared simulation results with the periodically measured soil water profiles obtained on Jungdong sandy loam to verify the model, In this model, we solved potential-based Richards' equation by the implicit finite difference method superimposed on the predictor-corrector scheme. We presumed that: soil hydraulic properties are homogeneous; soil water flows isothermally; hysteresis is not considered; no vapor flows; no heat transfers into the soil profiles; and water added to soil surface is distributed along the soil profile following partial displacement principle. The input data were broadly classified into two groups: (1) daily weather data such as rainfall, maximum and minimum air temperatures, relative humidity and solar radiation and (2) soil hydraulic data to approximate unsaturated hydraulic conductivity and water retention. Each hydraulic polynomial function approximated using the Chebyshev polynomial and least square difference technique in tandem showed a fairly good fit of the given set of data. Vertical distribution of soil water as approximations to the Richards' equation subject to changing surface and phreatic boundaries was solved numerically during 53 days with a comparatively large time increment, and this pattern agreed well with field neutron scattering data, except for the surface 0.1 m slab.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.748-754
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• 2010

The contents of soil organic matter (SOM) and $Al_o+1/2Fe_o$ in soils are important criteria for the classification of new Andisols in Soil Taxonomy system. There are many soil types in Jeju Island with various soil forming environments. This paper was conducted to estimate the contents of soil organic matter and the content of ammonium oxalate extracted Al and Fe ($Al_o+1/2Fe_o$) using various environmental variables and to make soil property maps using a statistical analyses. The soil samples were collected from 321 locations and analyzed to measure the contents of SOM and $Al_o+1/2Fe_o$. It was analyzed the relationships among them and various environmental variables such as temperature, precipitation, net primary product, radiation, evapotranspiration, altitude, soil forming energy, topographic wetness index, elevation, difference surrounded area, and distances from the shore and the peak. We can exclude multi-collinearity among environmental variables with principal component analysis and reduce all the variables to 3 principal components. The contents of SOM and $Al_o+1/2Fe_o$ were estimated by multiple regression models and maps of them were made using the models.

• Journal of Bio-Environment Control
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• v.6 no.3
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• pp.205-215
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• 1997

An accurate transpiration model for greenhouse tomato crop, which is liable to transpiration depression and yield loss because of low solar radiation and high humidity, could be an efficient tool for the optimum control of greenhouse climate and for the optimization of Irrigation scheduling. The purpose of this study was to develop transpiration model of greenhouse tomato and to carry out the experimental verification. The formulas to calculate the canopy transpiration and temperature simultaneously were derived from the energy balance of canopy. Transpiration and microclimate variables such as net radiation, solar radiation, humidity, canopy and air temperature, etc. were simultaneously measured to estimate parameters of model equations and to verify the suggested model. Leaf boundary layer resistance was calculated as a function of Nusselt number and stomatal diffusive resistance was parameterized by solar radiation and leaf-air vapor pressure deficit. The equation for stomatal diffusive resistance could explain more than 80％ of its variation and the calculated stomatal diffusive resistance showed good agreements with the measured values in situations independent of which the constants of the equation were estimated. The canopy net radiation calculated by Stanghellini's model with slight modification agreed well with the measured values. The present transpiration model, into which afore-mentioned component equations were assembled, was found to predict the canopy temperature, instantaneous and daily transpiration with considerable accuracy in greenhouse climates.

• Journal of Bio-Environment Control
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• v.8 no.1
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• pp.49-55
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• 1999

This study aims at analyzing environment factors of two tier cropping systems and suggesting effective structures of two tier cropping systems. The environment factors in two tier cropping systems are temperature, relative humidity, solar radiation, temperature of nutrient solution, and wind velocity. Especially, The most important factors are the solar radiation and the solar incident area between the two tiers. During the experiment, observations were made of the two levels in the plastic greenhouse. The highest temperatures were 38.3$^{\circ}C$ in the top level and, 35.5$^{\circ}C$ in the bottom level, respectively. The temperature of the nutrient solution between the two levels showed little difference. The relative humidity in the top level was 60~7o% and that in the bottom 65~80%, exhibiting that the bottom is approximately 10% higher. Change of photosynthetic photon flux density and solar radiation both have a tendency to be similar. The wind velocities for both levels were recorded at 0.1m.s$^{-1}$ in the afternoon and 0.05m.s$^{-1}$ in the evening. The solar incident areas in the bottom level increased by approximately 25% at an East-West position and 17.7% at a South-North position, respectively.

• Journal of Bio-Environment Control
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• v.27 no.1
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• pp.20-26
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• 2018

This study was conducted to develop a device for measuring the air flow by space variation through monitoring program, which acquires data by each point from each environmental sensor located in the greenhouse. The distribution of environmental factors(air temperature, humidity, wind speed, etc.) in the greenhouse is arranged at 12 points according to the spatial variation and a large number of measurement points (36 points in total) on the X, Y and Z axes were selected. Considering data loss and various greenhouse conditions, a bit rate was at 125kbit/s at low speed, so that the number of sensors can be expanded to 90 within greenhouse with dimensions of 100m by 100m. Those system programmed using MATLAB and LabVIEW was conducted to measure distributions of the air flow along the greenhouse in real time. It was also visualized interpolated the spatial distribution in the greenhouse. In order to verify the accuracy of CFD modeling and to improve the accuracy, it will compare the environmental variation such as air temperature, humidity, wind speed and $CO_2$ concentration in the greenhouse.

• Journal of Korea Soil Environment Society
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• v.5 no.1
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• pp.75-83
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• 2000

Recently, many landfills are constructed by using geosynthetics with earth materials. Geotextiles in geosynthetics are applied for the various purposes such as filters of the leachate collection and removal system and protectors of geomembrane liner. However geotextiles can be exposed to direct sunlight during the construction of landfill for several months. As you know the exposure of polymers to sunlight can be a major source of degradation of them. This study is to suggest a criteria on the installation of heavy weight geotextiles at the landfill. For this purpose, several different geotextiles were evaluated by outdoor exposure at two different locations and under the different seasons for one and half years. As the results of outdoor exposure, polypropylene geotextiles with 500g/$m^2$ and 700g/$\textrm{m}^2$were maintained around 40% of the initial strength during for one and half years. However, the polypropylene geotextile of 1000g/$\textrm{m}^2$showed 65% of the retained strength for the same duration of exposure. The retained strength of all polypropylene geotextile reduced dramatically with the cumulative sunshine radiation on a horizontal surface of around 1500MJ/$\textrm{m}^2$.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.2
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• pp.242-251
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• 2010

In comparison with other terrestrial ecosystems, rice paddies are unique because they provide the primary food source for over 50% of the world's population, and act as major sources of global methane. The present paper summerizes a long-term field study that combine carbon isotopes, and canopy-scale flux measurements in an irrigated rice paddy, in conjugation with continuous monitoring of environmental, and vegetational factors. Both $CO_2$, and methane fluxes were largely influenced by soil temperature, and moisture conditions, especially across drainage events. Soil-entrapped $CO_2$, and methane showed a gradually increasing trend throughout growing season, but rapidly decreased upon flood water drainage. These variations in flux were well correlated with changes in concentration, and isotope ratio of soil $CO_2$, and methane, and of atmospheric $CO_2$, and methane within, and above the canopy. The isotopic signature of the gas exchange process varied markedly in response to change in contribution of soil respiration, belowground storage, fraction of $CO_2$ recycled, magnitude, and direction of $CO_2$ exchange, transport mechanism, and fraction of methane oxidized. Our results clearly demonstrate that stable isotope analysis can be a useful tool to study underlying mechanisms of gas exchange processes under natural conditions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.4
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• pp.242-249
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• 2006

Potential impacts of the future climate change on crop production can be inferred by crop simulations at a landscape scale, if the climate data may be provided at appropriate spatial scales. Northern Gyunggi Province is one of the few prospective regions in South Korea for growing quality soybeans. Any geographical shift of production areas under the changing climate may influence the current land planning policy in this region. A soybean growth simulation was performed at 342 land units in northern Gyunggi province to test the potential geographical shift of the current production areas for quality soybeans in the near future (form 2011 to 2100). The land units for soybean cultivation were selected by the land use, the soil characteristics, and the minimum arable land area. Daily maximum and minimum temperature, precipitation, the number of rain days and solar radiation were extracted for each land unit from the future digital climate models (DCM, 2011-2040, 2041-2070, 2071-2100). Daily weather data for 30 years were randomly generated for each land unit for each normal year by using a well-known statistical method. They were used to run CROPGRO-Soybean model to simulate the growth, phonology, and yields of 3 cultivars representing different maturity groups grown at 342 land units. According to the model calculations, the warming trend in this region will accelerate the flowering and physiological maturity of all cultivars, resulting in a 7 to 9 days reduction in overall growing season and a 1 to 15% reduction in grain yield of early to medium maturity cultivars. There was a slight increase in grain yield of the late maturing cultivar under the projected climate by 2070, but a decreasing tend was dominant by the year 2100.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.2
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• pp.102-107
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• 2015

This study was conducted to classify agro-climatic zones in Northeast district of China. For agro-climatic zoning, monthly mean temperature and precipitation data from Global Modeling and Assimilation Office (GMAO) of National Aeronautics and Space Administration (NASA, USA) between 1979 and 2010 (http://disc.sci.gsfc.nasa.gov/) were collected. Altitude and vegetation fraction of East Asia from Weather Research and Forecasting (WRF) were also used to classify them. The criteria of agro-climatic classification were altitude (200 m, between 200-800 m, 800 m), vegetation fraction (60%), annual mean temperature ($0^{\circ}C$), temperature in the hottest month ($22^{\circ}C$), and annual precipitation (700 mm). In Northeast district of China, mean annual temperature, annual precipitation, and solar radiation were $3.4^{\circ}C$, 613.2 mm, and $4,414.2MJ/m^2$ between 2009 and 2013, respectively. Twenty-two agro-climatic zones identified in Northeast district of China by metrics classification method, from which the map of agro-climatic zones for Northeast district of China was derived. The results could be useful as information for estimating agro-meteorological characteristics and predicting crop development and crop yield of Northeast district of China as well as those of North Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.3
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• pp.195-202
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• 2007

The normalized difference in incident solar energy between a target surface and a level surface (overheating index, OHI) is useful in eliminating estimation error of site-specific maximum temperature in complex terrain. Due to the complexity in its calculation, however, an empirical proxy variable called northern exposure index (NEI) which combines slope and aspect has been used to estimate OHI based on empirical relationships between the two. An experiment with real-world landscape and temperature data was carried out to evaluate performance of the NEI - derived OHI (N-OHI) in reduction of spatial interpolation error for daily maximum temperature compared with that by the original OHI. We collected daily maximum temperature data from 7 sites in a mountainous watershed with a $149 km^2$ area and a 795m elevation range ($651{\sim}1,445m$) in Pyongchang, Kangwon province. Northern exposure index was calculated for the entire 166,050 grid cells constituting the watershed based on a 30-m digital elevation model. Daily OHI was calculated for the same watershed ana regressed to the variation of NEI. The regression equations were used to estimate N-OHI for 15th of each month. Deviations in daily maximum temperature at 7 sites from those measured at the nearby synoptic station were calculated from June 2006 to February 2007 and regressed to the N-OHI. The same procedure was repeated with the original OHI values. The ratio sum of square errors contributable by the N-OHI were 0.46 (winter), 0.24 (fall), and 0.01 (summer), while those by the original OHI were 0.52, 0.37 and 0.15, respectively.