• 한국습지학회지
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• 제19권1호
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• pp.52-62
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• 2017

본 연구에서는 지표수문해석모형을 이용하여 과거 30년에 대한 남한과 북한의 토양수분을 모의하고 그 거동 차이를 분석하였다. 아울러 VIC 모형의 모의결과를 평가하기 위해 Soil Moisture CCI에서 제공하는 위성관측 토양수분 자료를 분석하였다. 모의결과와 관측자료 사이의 비교에는 CSEOF 분석을 적용하여 단순한 토양수분 값의 비교가 아닌 VIC 모형의 성능을 간접적으로 평가하는 방법을 이용하였다. 본 연구의 결과를 정리하면 다음과 같다. 첫 째, 토양수분의 경년변동은 남한과 북한 모두 전체적으로 유사한 경향을 보였으나, 남한의 토양수분이 북한의 토양수분보다 작게는 1%에서 크게는 7%까지 높은 것으로 확인되었다. 둘 째, 월 단위 토양수분의 경우, 봄철에 해당하는 4 - 6월의 토양수분 상태는 남한과 북한에서 유사하게 나타났다. 반면, 장마철 이후 토양수분은 남한의 경우 최대 40%까지 증가하지만, 북한에서는 최대 32% 정도에 머무르는 것으로 확인되었다. 셋 째, 전체적으로 모의된 토양수분이 인공위성에서 관측된 토양수분보다 약 4% 정도 작지만, 과거 30년 동안 나타난 증가 정도는 위성관측 토양수분과 유사한 것으로 확인되었다. 마지막으로, 위성관측 토양수분과 VIC 모형으로 유도된 토양수분 자료에 대한 CSEOF를 비교해본 결과, 4월부터 6월까지의 토양수분은 공간적으로 서로 상당히 다른 패턴을 보이는 것으로 나타났다. 그러나 7월과 10월의 경우에는 약한 유사성을 보이고 있으며, 8월과 9월은 상당히 유사한 패턴을 가지고 있음을 확인하였다.

• 한국수자원학회논문집
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• 제55권2호
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• pp.111-120
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• 2022

물의 흐름을 제어하는 토양의 기능을 정량적으로 계산하기 위한 방법인 토양수분 메모리(soil moisture memory)는 토양에 도달한 강수가 저장되고 배출되기까지 평균적으로 체류하는 시간을 평가한다. 본 연구에서는 2019, 2020년 한반도 지역에서 강수와 토양수분 위성 기반 모델 산출물을 활용하여 표층(0~5 cm)토양에서의 토양수분 메모리를 산출하고 이를 활용하여 연구지역 내 토양수분 메모리의 시공간적인 분포를 지표면의 경사 및 토양의 특성과 함께 평가하였다. 토양수분 메모리를 특성분석을 위해 강수 사건에 따라 토양수분의 증가를 추적하여 저장 강수율(F_p(f))이라는 새로운 측정 지표를 활용하였다. 강수 발생 초기(3시간 후)에는 산맥을 기준으로 토양 내 저장 강수율이 우선적으로 감소하여 토양수분 메모리의 공간적인 편차가 컸으며 24시간 이후 전반적으로 편차가 감소하였다. 토양 내 저장 강수율은 경사가 증가할수록 감소하는 형태가 뚜렷하게 나타났으며 토양 입자 크기의 구성 비율에 따른 토양 내 수분의 배수 활동에 의한 영향을 확인할 수 있었다. 또한 수리전도도 증감에 기여하는 평균토양수분이 저장 강수율에 미치는 영향을 확인하였다. 본 연구 결과는 강수가 지면에 체류하는 시간에 대한 척도인 토양수분 메모리가 지표의 경사와 토양 특성과 갖는 관계를 규명하고 토양수분의 시공간적 변동성을 이해하는 데 기여할 것으로 기대된다.

• Journal of Biosystems Engineering
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• 제2권1호
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• pp.25-32
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• 1977

This experiment was conducted in order to find out the drawing performance of a two-wheel tractor under different levels of the soil moisture and hardness, so as to obtain some basic data for improving their drawing performance. With fairly homogeneous soil, 5 levels of soil moisture contents (8, 13, 17, 20 and 23%) and 3 levels of soil hardness (0 , 2 and 4kg/$cm^2$) were selected for this experiment.The summerized results are as follows ;1. The draft force, on the hard soil (hardness ; 4kg/$cm^2$), had a distinct tendency to decrease with the increasing soil moisture. On the medium soil (hardness ; 2 kg/$cm^2$), and the soft soil (hardness ; 0kg$cm^2$), the draft force showed the highest when the moisture contents were within the range of 16-19%.But the maximum draft force, on the soft soil, was higher than that on the medium soil by 10 %. 2. The driving axle torque increased with increasing soil by 10 %. 3.The values of horizontal distance between the soil reaction point and axle shaft were within the range of 0~10cm , and it had the tendency to increase with the increasing soil moisture. Also, it s value was the largest on the hard soil and the smallest on the soft soil. 4.The tractive efficiency decreased with the increasing soil moisture. On the hard soil, the average value of tractive efficiency was higher than that on the medium soil by 19.0% and that on the soft soil was lower than that on the medium soil. 5.The traction ratio were within the range of 30 ~45%, and their changing tendency with respect to the soil moisture was similar to that in the case of the draft force. 6. The travel resistance ratio tended to increased with increasing soil moisture, and the highest value was found on the soft soil, and the lowest on the hard soil.

• 대한원격탐사학회지
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• 제30권3호
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• pp.375-381
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• 2014

Soil moisture is an essential satellite-driven variable for understanding hydrologic, pedologic and geomorphic processes. The European Space Agency (ESA) has endorsed soil moisture as one of Climate Change Initiates (CCI) and had merged multi-satellites over 30 years. The $0.25^{\circ}$ coarse resolution soil moisture satellite data showed correlations with variables of a water stress index, Temperature-Vegetation Dryness Index (TVDI), from a stepwise regression analysis. The ancillary data from TVDI, Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) from MODIS were inputted to a multi-regression analysis for estimating the surface soil moisture. The estimated soil moisture was validated with in-situ soil moisture data from April, 2012 to March, 2013 at Andong observation sites in South Korea. The soil moisture estimated using satellite-based LST and NDVI showed a good agreement with the observed ground data that this approach is plausible to define spatial distribution of surface soil moisture.

• Journal of Korean Society for Atmospheric Environment
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• 제14권E호
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• pp.9-17
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• 1998

Oxides of nitrogen play important roles in atmospheric chemistry. Soil has been recognized as a major natural source of NO, and its emission depends on soil parameters such as soil nitrogen availability, soil moisture and temperature. It is necessary to understand effects of these controlling parameters on soil NO emission. In order to understand soil moisture effects on NO emission, variations of NO concentration and existence of its equilibrium concentration were observed from ammonium fertilized Japanese upland soil prepared for different soil moisture conditions. The closed chamber technique was employed for this study. The significant increases in NO with soil moisture were found. Maximum was occurred at sample ID4 (55% of water-filled pore space (WFPS)), but it decreased as soil moisture increased. No significant NO concentration was emitted from soil sample without fertilizer, but there was significant NO in fertilized soil samples. The magnitudes of NO from soil increased with time and reached at steady state within ten minutes approximately. These results suggest that nitrogen input from fertilizer takes charge in the first step of sharp increase in NO emission, and then soil moisture becomes important factor to control NO emission from the soils. NO concentrations from soil were compared to those one-day after the experiment. Results from the comparison analysis suggest that the soil NO flux might have been stimulated by soil disturbances like mixing, and this is much more effective in dry soils rather than in wet soils. It was found that much less NO came out from soils after a day; suggesting that most of NO was released from the soils within a day after fertilizer application during our experiment. The length of NO releasing time span may depend on the amounts of fertilizer applied, soil moisture condition, and other soil physical parameters.

• 한국자원식물학회지
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• 제34권6호
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• pp.608-615
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• 2021

Soil moisture control system including soil sensing and automatic water supply chain was constructed on open farmland and pot conditions. Soil moisture was controlled by the system showing over the soil moisture contents except 40% treatment. EC was gradually decreased by increasing cultivation days. On applying this system to control soil moisture, the growth and development characters of the bellflower were improved compared with control, cultivation without the automatic irrigation. Of the growth and development characters, plant height with water treatments was higher than that of control in 1st-year plants. Moreover, numbers of branch were increased by the increased soil moisture on farmland and pot condition. Capsule numbers for seed were best at 20%, 30% soil moisture treatment in 1st-year plants, and 20% to 50% treatment in 2nd-year plants. The construction of automatic soil moisture control system provide fundamental data for plant growth and development on open farmland soil condition.

• 한국농공학회지
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• 제38권1호
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• pp.98-106
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• 1996

An irrigation scheduling model, IRIS developed to evaluate irrigation demand and irrigation time for upland crops. For IRlS modeling the soil moisture simulation model, SWATRER was adopted and modified. The developed model, IRIS operated under 5 different soil moisture level that is 20%, 40%, 60%, 80% of available soil moisture and optimum soil moisture level, OSML, which is different about the growing stage and no rainfall condition during growing period. As a result for IRIS simulation, irrigation demand for 5 different soil moisture level was 332.3, 409.8, 569.3, 732.2, 539.3mm, irrigation number was 5, 8, 18, 54, 16 times and irrigation interval during peak time of consumptive use was 20, 13, 6, 2, 6 days respectively. It is appeared that the higher soil moisture level the more irrigation demand and irrigation number and the higher soil moisture level the less irrigation interval.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.26-28
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• 2008

Soil moisture plays an important role in the land-atmosphere energy balance because it governs the partitioning of energy through latent heat fluxes or evapotranspiration. From the numerous studies, it is evident that the L-band radiometer is a useful and effective tool to measure soil moisture. The objective of the study is to develop and to verify the soil moisture retrieval algorithms for the L-band radiometer system. Through the radiometer-observed brightness temperature, surface emissivity and reflectivity can be derived, and, hence, soil moisture. We collect field and L-band airborne radiometer data from washita92, SGP97 and SGP99 experiments to assist the development of the retrieval algorithms. Upon launching the satellite L-band radiometer such as ESA-sponsored SMOS (Soil Moisture and Ocean Salinity) mission, the developed algorithms may be used to study and monitor globe soil moisture change.

• 한국농공학회논문집
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• 제59권5호
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• pp.31-40
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• 2017

The aim of this study is to estimate net irrigation requirements for red pepper during growing period using soil moisture model. The soil moisture model based on water balance approach simulates soil moisture contents of 4 soil layers in crop root zone considering soil moisture extraction pattern. The LAMP (Land-Atmosphere Modeling Package) high resolution meteorological data provided from National Center for AgroMeteorology (NCAM) was used to simulate soil moisture as the input weather data. Study area for the LAMP data and soil moisture simulation covers $36.92^{\circ}{\sim}37.40^{\circ}$ in latitude and $127.36^{\circ}{\sim}127.94^{\circ}$ in longitude. Soil moisture was monitored using FDR (Frequency Domain Reflectometry) sensors and the data were used to validate the simulation model from May 24 to October 20 in 2016. The results showed spatially detailed soil moisture pattern under different weather conditions and soil texture. Net irrigation requirements were also different by location reflecting the spatially distributed weather condition. The average of the requirements was 470.7 mm and averages about soil texture were 466.8 mm, 482.4 mm, 456.0 mm, 481.7 mm, and 465.6 mm for clay loam, sandy loam, silty clay loam, clay, and sand respectively. This study showed spatial differences of soil moisture and the irrigation requirements of red pepper about spatially uneven weather condition and soil texture. From the results, it was demonstrated that high resolution meteorological data could provide an opportunity of spatially different crop water requirement estimation during the irrigation management.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.205-205
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• 2021

Surface soil moisture, which governs the partitioning of precipitation into infiltration and runoff, plays an important role in the hydrological cycle. The assimilation of satellite soil moisture retrievals into a land surface model or hydrological model has been shown to improve the predictive skill of hydrological variables. This study aims to improve streamflow prediction with Weather Research and Forecasting model-Hydrological modeling system (WRF-Hydro) by assimilating Soil Moisture Active and Passive (SMAP) data at 3 km and analyze its impacts on hydrological components. We applied Cumulative Distribution Function (CDF) technique to remove the bias of SMAP data and assimilate SMAP data (April to July 2015-2019) into WRF-Hydro by using an Ensemble Kalman Filter (EnKF) with a total 12 ensembles. Daily inflow and soil moisture estimates of major dams (Soyanggang, Chungju, Sumjin dam) of South Korea were evaluated. We investigated how hydrologic variables such as runoff, evaporation and soil moisture were better simulated with the data assimilation than without the data assimilation. The result shows that the correlation coefficient of topsoil moisture can be improved, however a change of dam inflow was not outstanding. It may attribute to the fact that soil moisture memory and the respective memory of runoff play on different time scales. These findings demonstrate that the assimilation of satellite soil moisture retrievals can improve the predictive skill of hydrological variables for a better understanding of the water cycle.