• Asian Journal of Turfgrass Science
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• v.22 no.2
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• pp.133-140
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• 2008

The growth of root and shoot normally decline dramatically in mid-summer of Korea, moreover the cool-season turfgrassgrass eventually wither to death over $30^{\circ}C$. The increase of air temperature also drives the heat of soil, that makes stress on root system. The heat stress affects physiological mechanisms of hormonal unbalance that stimulates shoot growth, photosynthesis, and transpiration. To solve those problems, many studies have been carried out to control soil moisture and OM content to decrease soil temperature for dissolving the growth retardant by heat stress. This study initiated to analyze the change of soil temperature with soil moisture, and the effect of soil depth and moisture content on heat transmit and thermal changes on turfgrass growth(productivity, green color, and damage by dryness and high temperature). Kentucky bluegrass plots prepared with 25%, 33%, 40% soil moisture treatments. Soil temperature was measured every five min. with four thermo-sensors at 12 and 2 cm soil depth. The most acceptable growth showed at 33% soil moisture, but the worst result showed at 40%. The soil moisture seriously affected on the growth of Kentucky bluegrass, however the quality of turfgrass may acceptable if we can control soil moisture down to 33% when the flooding season of monsoon.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.159-159
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• 2016

북한 지역에서 시작되어 한반도의 금문댐까지 연결되는 임진강은 북한지역의 유출량 미계측으로 인해 유출량 산출에 많은 어려움이 있어왔다. 본 연구에서는 위성 데이터를 활용하여 미계측 유역의 유출량을 추정 할 수 있는 기법을 제시하였다. Satellite-derived Flow Signal (SDF)는 위성 기반 특정 지역의 유출 정보를 제공하며, JAXA의 GCOM-W1 위성에 탑재된 Advanced Microwave Scanning Radiometer 2(AMSR2) 센서에서 산출된다. 본 연구에서는 SDS 뿐 아니라 유출에 크게 관련이 있는 지표 토양수분 데이터와 식생인자를 임진강 유출 값을 예측하기 위한 입력 값으로 활용하였다. 토양수분 데이터는 Metop-A 위성에 탑재된 Advanced Scatterometer(ASCAT) 센서에서 산출되는 데이터를 활용하였으며, 식생데이터는 Aqua 위성에 탑재된 Moderate Resolution Imaging Spectroradiometer(MODIS) 센서에서 측정되는 Normalized Difference Vegetation Index(NDVI) 데이터를 활용하였다. 추가적으로 SDS, 토양수분, NDVI 데이터는 다양한 lag time으로 약 150여개의 입력데이터로 세분화되었다. 150개의 방대한 입력인자는 Partial Mutual Information(PMI) 방법을 통해 소수 중요 인자들로 간추려져 기계 학습 입력인자로 활용되었다. 기계학습에 있어서는 Support Vector Machine(SVM), Artificial Neural Network (ANN) 기법을 활용하였다. SVM, ANN을 통해 모델화된 유출데이터는 금문댐 유출데이터와 비교/분석되었다. SVM 기법 기반의 유출량은 실제 유출량과 0.73의 상관계수를 보여주었고, ANN 기법 기반의 유출량은 0.66의 상관계수를 결과를 나타내었다. 하지만 SVM 기반 유출데이터는 과소 산정 되는 경향을 보였으며, ANN 기법 기반의 유출량은 과대산정되는 결과가 산출되는 한계점이 있음을 파악할 수 있었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.341-343
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• 2018

Agriculture has the longest history in many industries and is directly or indirectly linked to human development. However, recently agriculture in Korea has difficulties in farm management due to the decrease of rural population, aging of society, increase of material costs, and climate change on the Korean peninsula. Smart farms using ICT are proposed as an alternative to solve these problems. Smart farms manage the temperature and water supply facilities of farms through various sensors, but there is a limit to the delicate management of crops. Therefore, in this paper, unlike the conventional moisture sensor, the water supply is varied according to the depth of the soil, thereby realizing an optimized environment for plant growth.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.127-127
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• 2011

본 연구에서는 RHESSys (Regional Hydro-Ecologic Simulation System) 모형을 이용하여 산림 유역의 생태수문학적 거동을 평가하고자 한다. 설마천 유역($8.48\;km^2$)을 대상으로 2007~2009년의 관측 일유출량을 이용하여 유출량을 검 보정하였고, 증발산량 및 토양수분은 신뢰할 만한 실측자료를 바탕으로 모형의 보정(2007-2008)및 검증(2009)을 실시하였다. 또한 지구의 탄소순환을 규명할 수 있는 식생의 순광합성량과 총일차생산량에 대한 모형의 검 보정은 Terra 위성의 MODIS (Moderate Resolution Imaging Spectroradiometer) 센서를 이용한 산출물인 순광합성량과 총일차생산량 자료를 바탕으로 모형의 보정(2007)및 검증(2008)을 실시하였다. 모형의 최적의 수문, 생리생태학, 토양의 매개변수를 선정하여 검증한 결과, 유출량에 대한 Nash-Sutcliffe 모형효율은 0.84, 증발산, 토양수분, 총일차생산량, 순광합성량의 결정계수는 0.49, 0.18, 0.38, 0.93 이었다.

• Korean Journal of Soil Science and Fertilizer
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• v.30 no.4
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• pp.314-327
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• 1997

A 2-dimensional soil water flow model was developed to describe the migration of soil moisture in drip-irrigated root zone employing cylindrical coordinate system. Several natural phenomena were incorporated into the model such as transpiration, various types of evaporation, and ponding due to the increase in irrigation rate. Model was solved numerically by finite difference method. The model was verified in several ways leading to the conclusion that it can describe the soil moisture migration in drip-irrigated root zone fairly well. From sensitivity analysis, vertical migration of soil moisture was found to move faster than the horizontal one, which indicates the vertical location just under the dripping point are adequate for measuring points of soil moisture. The pot shape of soil moisture in irrigated zone was proved to be caused by evaporation at the soil surface. Also, it was found that the hydraulic conductivity has greatly influential to the soil moisture migration, and that the soil moisture continues to migrate vertically after irrigation stops.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.3
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• pp.331-336
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• 2011

Capacitance soil moisture sensor is extensively used by soil research and irrigation management with its convenience and accuracy. This experiment was conducted to evaluate the acceptability of capacitance soil moisture sensor, named EnviroSCAN made by Sentek Ltd., in Jeju Island where volcanic ash soils are widely distributed, and to calibrate it to various soils with different amount of soil organic matter. For sensor calibration equation of volcanic ash soils, a logarithm function is better than a typical power function of non-volcanic ash soils. So there are possibilities of under evaluated in soil water contents in very wet and very dry conditions by using typical power function with volcanic ash soil areas. We suggested practical coefficients of typical calibration equation for using capacitance sensor in volcanic ash soils, also suggested equations for estimation of them with soil organic matter contents. The measurement of soil water content with a capacitance sensor can be affected by some soil characteristics such as porosity, soil organic matter content, EC, etc. So those factors should be controlled for improving the accuracy of measurement.

• Journal of the Geological Society of Korea
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• v.54 no.5
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• pp.545-556
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• 2018

This study was conducted to estimate the deep percolation using numerical modeling and field observation data based on rainfall in Haean basin. Soil moisture sensors were installed to monitoring at 30, 60 and 90 cm depths in four sites (YHS1-4) and automatic weather station was installed to around YHS3. Soil moisture and meteorological data was observed from March 25, 2017 to March 25, 2018 and May 06, 2016 to May 06, 2018, respectively. Numerical analysis was performed from June to August, 2017 using the HYDRUS-1D. Average soil moisture contents were high to generally in YHS3 for 0.300 to $0.334m^3/m^3$ and lowest in YHS1 for 0.129 to $0.265m^3/m^3$ during the soil moisture monitoring period. The results of soil moisture flow modeling showed that field observations and modeling values were similar but the peak values were larger in the modeling result. Correlation analysis between observation and modeling data showed that r, $r^2$ and RMSE were 0.88, 0.77, and 0.0096, respectively. This show high correlation and low error rate. The total deep percolation was 744.2 mm during the period of modelling at 500 cm depth. This showed that 61.3% of the precipitation amount (1,214 mm) was recharged in 2017. Deep percolation amount was high in the study area. This study is expected to provide basic data for the estimation of groundwater recharge through unsaturated zone.

• 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 Korea Water Resources Association
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• v.49 no.3
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• pp.263-273
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• 2016

This study applied conditional merging (CM) spatial interpolation technique to obtain the satellite and in-situ composite soil moisture data. For the analysis, 24 gages of hourly in-situ data sets from the Rural Development Administration (RDA) of Korea and the satellite soil moisture data retrieved from Advanced Microwave Scanning Radiometer-Earth observing system (AMSR-E) were used. In order to verify the performance of the CM method, leave-one-out cross validation was used. The cross validation result was spatially interpolated to figure out spatial correlation of the CM method. The results derived from this study are as follow: (1) The CM method produced better soil moisture map over Korean Peninsula than AMSR-E did for the over 100 days out of total 113 days considered for the analysis. (2) The method of CM showed high correlation with gage density and better performance on the western side of Korean peninsula due to high spatial gauge density. (3) The performance of CM is not affected by the non-rainy season unlike to AMSR-E data is. Overall, the result of this study indicates that the CM method can be applied for predicting soil moisture at ungaged locations.

• Journal of Wetlands Research
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• v.13 no.2
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• pp.171-179
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• 2011

The main objective of this study is to estimate of the vegetation response induced by climate change to soil moisture. We investigated a relationship between vegetation activity and climate variables using Moderate Resolution Imaging Spectroradiometer (MODIS)-retrieved Normalized Difference Vegetation Index (NDVI) and soil moisture. NDVI which extracted from MODIS 13 Vegetation Indices Product was considered as an useful parameter to figure out a relationship with two types of soil moisture, which were observed at Rural Development Administration sites and estimated from Advanced Microwave Scanning Radiometer E (AMSR-E) satellite imagery. The correlation of MODIS-NDVI and ground measured soil moisture were observed, became much stronger when compared to soil moisture values with time lag (5days, 10days, 15days). The correlation patterns between NDVI and soil moisture with different time lag were related to soil texture. The results from this study will be useful to understand the role of vegetation in water balance control in various scales from regional to global climate change.