Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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v.29
no.4
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pp.69-76
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2015
This paper presents the results of an investigation into the frequency-dependent electrical parameters for different types of soil as a function of moisture content. The frequency dependence of soil electrical parameters is very important in the design of grounding systems. In fact, the performance of grounding systems is greatly dependent upon various factors such as soil type, particle size, water content, temperature, frequency, and the like. The resistivity and relative permittivity for four different soils were measured and analyzed in the frequency range of 1kHz - 1MHz. Soil resistivity declined as moisture content and frequency increased. In particular, the frequency dependence of soil resistivity was significant as the moisture content was low. In contrast, the relative permittivity of soil dramatically declined at the frequency of 10kHz or below as the moisture content increased, showing the opposite pattern in terms of variation patterns, compared to resistivity.
Background: For understanding and evaluating a more realistic and accurate assessment of ecosystem carbon balance related with environmental change or difference, it is necessary to analyze the various interrelationships between soil respiration and environmental factors. However, the soil temperature is mainly used for gap filling and estimation of soil respiration (Rs) under environmental change. Under the fact that changes in precipitation patterns due to climate change are expected, the effects of soil moisture content (SMC) on soil respiration have not been well studied relative to soil temperature. In this study, we attempt to analyze relationship between precipitation and soil respiration in temperate deciduous broad-leaved forest for 2 years in Gwangneung. Results: The average soil temperature (Ts) measured at a depth of 5 cm during the full study period was $12.0^{\circ}C$. The minimum value for monthly Ts was $-0.4^{\circ}C$ in February 2015 and $2.0^{\circ}C$ in January 2016. The maximum monthly Ts was $23.6^{\circ}C$ in August in both years. In 2015, annual precipitation was 823.4 mm and it was 1003.8 mm in 2016. The amount of precipitation increased by 21.9% in 2016 compared to 2015, but in 2015, it rained for 8 days more than in 2016. In 2015, the pattern of low precipitation was continuously shown, and there was a long dry period as well as a period of concentrated precipitation in 2016. 473.7 mm of precipitation, which accounted for about 51.8% of the precipitation during study period, was concentrated during summer (June to August) in 2016. The maximum values of daily Rs in both years were observed on the day when precipitation of 20 mm or more. From this, the maximum Rs value in 2015 was $784.3mg\;CO_2\;m^{-2}\;h^{-1}$ in July when 26.8 mm of daily precipitation was measured. The maximum was $913.6mg\;CO_2\;m^{-2}\;h^{-1}$ in August in 2016, when 23.8 mm of daily precipitation was measured. Rs on a rainy day was 1.5~1.6 times higher than it without precipitation. Consequently, the annual Rs in 2016 was about 12% higher than it was in 2015. It was shown a result of a 14% increase in summer precipitation from 2015. Conclusions: In this study, it was concluded that the precipitation pattern has a great effect on soil respiration. We confirmed that short-term but intense precipitation suppressed soil respiration due to a rapid increase in soil moisture, while sustained and adequate precipitation activated Rs. In especially, it is very important role on Rs in potential activating period such as summer high temperature season. Therefore, the accuracy of the calculated values by functional equation can be improved by considering the precipitation in addition to the soil temperature applied as the main factor for long-term prediction of soil respiration. In addition to this, we believe that the accuracy can be further improved by introducing an estimation equation based on seasonal temperature and soil moisture.
Emission of methyl bromide(MeBr) of soil fumigant was implicated in stratospheric ozone depletion. To determine the environmental fate for 1,3-dichloropene(1,3-D) of alternatives fumigants for MeBr, this paper researched the transformation for 1,3-D in water and soil. Half lives of cis-1,3-D in water with first-order kinetics are 9.9day and 1.7day at $25^{\circ}C\;and\;40^{\circ}C$, half lives of trans-1,3-D are 8.6day and 1.5day at $25^{\circ}C\;and\;40^{\circ}C$, respectively. Transformation for 1,3-D in water at high temperature faster then at low temperature. Hydrolysis for 1,3-D in water are unaffected at $pH\;2.5{\sim}pH\;10.0$, but hydrolysis for 1,3-D at pH 11.5 higher then at $pH\;2.5{\sim}pH\;10.0$. Half lives of cis-1,3-D in soil are 11.5day and 7.7day at 3% and 10% of soil moisture, half lives of trans-1,3-D are 9.9day and 6.9day at 3% and 10% of soil moisture, respectively. Transformation for 1,3-D in water increased with increasing soil moisture. Transformation for trans-1,3-D isomer are more rapid then cis-1,3-D isomer in water and soil. This research has identified that transformation for 1,3-dichloropropene are affected by temperature, pH, soil moisture, and isomer of cis and trans in water and soil.
Seo, Eunkyo;Lee, Myong-In;Jeong, Jee-Hoon;Kang, Hyun-Suk;Won, Duk-Jin
Atmosphere
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v.26
no.1
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pp.35-45
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2016
Initialization of the global seasonal forecast system is as much important as the quality of the embedded climate model for the climate prediction in sub-seasonal time scale. Recent studies have emphasized the important role of soil moisture initialization, suggesting a significant increase in the prediction skill particularly in the mid-latitude land area where the influence of sea surface temperature in the tropics is less crucial and the potential predictability is supplemented by land-atmosphere interaction. This study developed a new soil moisture initialization method applicable to the KMA operational seasonal forecasting system. The method includes first the long-term integration of the offline land surface model driven by observed atmospheric forcing and precipitation. This soil moisture reanalysis is given for the initial state in the ensemble seasonal forecasts through a simple anomaly initialization technique to avoid the simulation drift caused by the systematic model bias. To evaluate the impact of the soil moisture initialization, two sets of long-term, 10-member ensemble experiment runs have been conducted for 1996~2009. As a result, the soil moisture initialization improves the prediction skill of surface air temperature significantly at the zero to one month forecast lead (up to ~60 days forecast lead), although the skill increase in precipitation is less significant. This study suggests that improvements of the prediction in the sub-seasonal timescale require the improvement in the quality of initial data as well as the adequate treatment of the model systematic bias.
This study aimed to determine a method for restoring grasslands to forests in mountainous areas. The study was conducted in an area damaged by trampling due to construction activity and herding. Additionally, there were concerns of hindered tree growth due to the alpine region climate, characterized by the low temperatures, drying, and strong winds. Therefore, forest restoration treatments such as tillage, furrow, and shading were performed to improve growth conditions. From July 2021 to April 2023, soil temperature and moisture were monitored for each treatment plot, and changes in the initial growth and survival rate of Abies holophylla were investigated. Both soil temperature and soil moisture showed significantly higher values during the four seasons in the grassland-furrow treatment plot (p < 0.05). Compared to the grassland-control plot, the average soil temperature in winter was as high as 1.1℃, and the soil moisture in summer was as high as 20.3%. Additionally, the survival rate and relative growth rate were the largest in the grassland-furrow treatment plot. The survival rate was 87.5%, the relative growth rate in terms of height was 0.013, and the relative growth rate in terms of diameter at root collar was 0.023, indicating that furrow treatment had a positive effect on the initial survival and growth of seedlings. These results suggest that furrow treatment may be an appropriate restoration method when implementing forest restoration projects in areas where tree growth is challenged.
Journal of Korean Society for Atmospheric Environment
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v.19
no.5
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pp.529-540
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2003
A closed chamber system was used for measuring $N_2$0 fluxes from an agriculturally managed upland soil in Kunsan during the growing season from May to July 2002. It is known that soil is one dominant source of atmospheric $N_2$O, contributing to about 57% (9 Tg y $^{-1}$ ) of the total annual global emission. Hence, its increasing emissions and concentrations are largely associated with agricultural activities. In order to elucidate characteristics of soil nitrogen emissions from intensively managed agricultural soils and to understand the roles of soil parameters (soil moisture, soil pH, soil temperature, and soil nitrogen) in the gas emission, $N_2$O soil emissions were measured at every hour during the experimental period (21 days). Soil $N_2$O fluxes were calculated based on changes of $N_2$O concentrations measured inside a closed chamber at every hour. The analysis of $N_2$O was made by using a Gas Chromatography (equipped with Electron Capture Detector). Soil parameters at sampling plots were also analyzed. Monthly averaged $N_2$O fluxes during May, June, and July were 0.14, 0.05, and 0.13 mg-$N_2$O m$^{-2}$ h$^{-1}$ , respectively. Soil temperature and soil pH did not significantly vary over the experimental period; soil temperatures ranged from 12∼$25^{\circ}C$, and soil pH ranged 4.56∼4.75. However, soil moisture varied significantly from 32% to 56% in WFPS. Relationships between soil parameters and $N_2$O fluxes exhibited positive linear relationships. Strong positive correlation ($R^2$ = 0.57, P< 0.0001) was found between $N_2$O flux and sil moisture. It suggests that soil moisture has affected strongly soil $N_2$O emissions during the experimental periods, while other parameters have remained relatively at constant levels. $N_2$O flux from agricultural soils was significant and should be taken account for the national emission inventory.
Magazine of the Korean Society of Agricultural Engineers
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v.22
no.3
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pp.37-45
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1980
This study was carried out to investigate the consumptive use of water for red peppers and soy beans. The correlation between the soil moisture contents and the selected meteorological factors during the growing season was analyzed. Characteristics of the drought at Jinju, Yeosu, Gwangju, and Mokpo area were figured out in view of frequency analysis. The results obtained from this study could be used as a reasonable criteria for the estimation of the duty of water in the design of upland irrigation systems. Obtained results are summarized as follows: 1. Red peppers were grown at the three levels of soil moisture contents; 75 percent, 50 percent, and 25 percent, respectively. The red pepper grown at the 75 percent of soil moisture content showed the highest yield. The total evapotranspiration during the growing season from red peppers was 471. lmm, which was 86.6mm less than the pan evaporation. 2. The soy bean grown at 75 percent soil moisture content showed the highest yield, although there was no signicant difference in yields among treatments. The total evapotranspiration during the growing season from the soy bean was 342.8 mm, which was 119.2mm less than the pan evaporation. 3. Coefficients of consumptive use(k) and meteorological data are shown on Table-9. 4. The significant correlations between the evapotranspiration and the humidity and daily temperature range were observed. Results are shown on Table-11.. Evaporanspiration can be easily estimated from the humidity and daily temperature range by using the equation...... (1) Ept=4.808-0.041H+0.207T.......(1) where, Ept; evapotranspiration(mm/day) H ; humidity(%) T ; daily temperature range ($^{\circ}C$) 5. The variations of soil moisture content during the growing season at the soil depth of 5cm, 15cm, and 45cm are shown on Fig. 4~9. The results of the correlation analysis between the evapotranspiration from the crops and the soil moisture content are shown on Table-12. The evapotranspiration can be estimated from soil moisture content at the different depth of the soil by using the equation....... (2). Ept = 3.433 - 0. 364M1 +0. 359M$_2$- 0. 055M$_3$....... (2) where, Ept; evapotranspiration (mm/day) M1 soil moisture meter reading at 5cm depth M$_2$; " 15cm " M$_2$; " 40cm " 6. The estimated probab]e successive dry days in selected areas are shown on Table 13. Gumbel-Chow method was used to calculate the probable successive dry days. Further investigation are required to obtain the more detailed and reliable results.
Climate models forecast more frequent and a longer period of drought events which may impact forest soil carbon dynamics, thereby altering the soil respiration (SR) rate. We examine the simulated drought effects on soil $CO_2$ effluxes from soil surface partitioning heterotrophic and autotrophic soil respiration sources. Three replicates of drought plots ($6{\times}6m$) were constructed with the same size of three control plots. We examined the relation between $CO_2$ and soil temperature and soil moisture, each being measured at a soil depth of 15 cm. We also compared which factor affected $CO_2$ efflux more under drought conditions. Total SR, autotrophic respiration (AR) and heterotrophic respiration (HR) were positively correlated with soil temperature (p < 0.05), and the relationships were stronger in roof plots than in control plots. Total SR, AR, and HR were negatively correlated only in roof plots, and the only HR showed a significant correlation (p < 0.05, r = -0.59). Soil respiration rates were more influenced by soil temperature than by soil moisture, and this relationship was more evident under drought conditions.
Magazine of the Korean Society of Agricultural Engineers
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v.14
no.4
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pp.2761-2769
/
1972
The following results were obtained by the compression test of 3, 7, 14 and 28 days cured lime soil mixtures. The soil used in this test was clayey soil(sand : 20% silt : 45%, clay : 35%) and the rates of hydrated lime mixture for the dry weight of soil were 4, 8, 12, 19 and 20 percents. 1. The optimum moisture content increases and the maximum dry density decreases with the increase of the lime content. 2. The compacted moisture for the maximum strength in lime soil mixture increases with the increase of the lime content and the increase of curing periods. 3. The compressive strength increase of curing periods and its increasing ratio is largest at the 8 percent lime content. 4. The line content for the maximum strength decreases with increase of curing period and the largest strength shows at the 8 percent lime content when the curing period is over two weeks. 5. It seems to depend on the temperature effect that the compressive strength of lime soil mixtures cured in soil shows the lowest value. Accordingly, the effect of curing moisture does not influence to the strength of lime soil mixtures as much as the variation of curing temperature.
Journal of The Korean Society of Agricultural Engineers
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v.61
no.6
/
pp.123-132
/
2019
This study is to estimate the spatial soil moisture using Terra MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data and machine learning technique. Using the 3 years (2015~2017) data of MODIS 16 days composite NDVI (Normalized Difference Vegetation Index) and daily Land Surface Temperature (LST), ground measured precipitation and sunshine hour of KMA (Korea Meteorological Administration), the RDA (Rural Development Administration) 10 cm~30 cm average TDR (Time Domain Reflectometry) measured soil moisture at 78 locations was tested. For daily analysis, the missing values of MODIS LST by clouds were interpolated by conditional merging method using KMA surface temperature observation data, and the 16 days NDVI was linearly interpolated to 1 day interval. By applying the RNN-LSTM (Recurrent Neural Network-Long Short Term Memory) artificial neural network model, 70% of the total period was trained and the rest 30% period was verified. The results showed that the coefficient of determination ($R^2$), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency were 0.78, 2.76%, and 0.75 respectively. In average, the clay soil moisture was estimated well comparing with the other soil types of silt, loam, and sand. This is because the clay has the intrinsic physical property for having narrow range of soil moisture variation between field capacity and wilting point.
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