• Journal of Environmental Science International
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• v.22 no.4
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• pp.415-424
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• 2013

In this paper, time series of soil moisture were measured for a steep forest hillslope to model and understand distinct hydrological behaviours along two different transects. The transfer function analysis was presented to characterize temporal response patterns of soil moisture for rainfall events. The rainfall is a main driver of soil moisture variation, and its stochastic characteristic was properly treated prior to the transfer function delineation between rainfall and soil moisture measurements. Using field measurements for two transects during the rainy season in 2007 obtained from the Bumrunsa hillslope located in the Sulmachun watershed, a systematic transfer functional modeling was performed to configure the relationships between rainfall and soil moisture responses. The analysis indicated the spatial variation pattern of hillslope hydrological processes, which can be explained by the relative contribution of vertical, lateral and return flows and the impact of transect topography.

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.401-408
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• 2013

Soil moisture is a very important variable in various area of hydrological processes. We predict the soil moisture using a support vector regression. The model is trained and tested using the soil moisture data observed in five sites in the Yongdam dam basin. With respect to soil moisture data of of four sites-Jucheon, Bugui, Sangieon and Ahncheon which are used to train the model, the correlation coefficient between the esimtates and the observed values is about 0.976. As the result of the application to Cheoncheon2 for validating the model, the correlation coefficient between the estimates and the observed values of soil moisture is about 0.835. We compare those results with those of artificial neural network models.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.6
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• pp.674-683
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• 2017

The frequency and intensity of soil moisture stress associated with climate change has increasing, and the stability of field crop cultivation has decreasing. This experiment was conducted to investigate the effect of soil moisture management method on growth and yield of corn. Soil moisture was managed at the grade of WSM (wet soil moisture, 34.0~42.9%), OSM (optimum soil moisture, 27.8~34.0%), DSM (dry soil moisture, 20.3~27.8%), and ESM (extreme dry moisture, 16.6~20.3%) during V8 (8th leaf stage)-VT (tasseling stage). After VT, irrigation was limited. The treated amount of irrigation was 54.1, 47.7, 44.0 and 34.5% of total water requirement, respectively. The potential evapotranspiration during the growing period was $3.29mm\;day^{-1}$, and upward movement of soil water was estimated by the AFKAE 0.5 model in the order of ESM, DSM, OSM, and WSM. We could confirm this phenomenon from actual observations. There was no significant difference in leaf characteristics, dry matter, and primary productivity depending on the level of soil moisture, but leaf development was delayed and dry weight decreased in DSM. However, dry weight and individual productivity of DSM increased after irrigation withdrawal compared to that of OSM. In DSM, ear yield and number of kernels per ear decreased, but water use efficiency and harvest index were higher than other treatments. Therefore, it is considered that the soil moisture is concentratedly managed before the V8 period, the V8-VT period is controlled within the range of 100 to 500 kPa (20.3~27.8%), and no additional irrigation is required after the VT.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.737-740
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• 2005

Soil moisture, through its dominance in the exchange of energy and moisture between the land and atmosphere, plays a crucial role in influencing atmospheric circulation. To identify the crucial role, it is a common agreement that knowledge of land surface processes and development of remote sensing techniques are of great important scientific issues. This research uses TRMM satellite C band (10.65 GHz) data to retrieve soil moisture on the Tibetan Plateau in Mainland China. Two retrieval schemes that are implemented include the t-(J) model and the R model. The latter one is developed based on a land surface process and radiobrightness (R) model for bare soil and vegetated terrain. Compared with the in situ ground measurements, the soil moisture retrieved from the R model and the t-(J) model with vegetation information obviously appear more accurate than that derived from bare soil model. Retrieved soil moisture contents from the two inversion models, R model and t-(J) model, have a similar trend, but the former appears to be superior in terms of correlation coefficient and bias compared with in situ data. In the future, we will apply the R model with the TRMM 10.65 GHz brightness temperature to monitor long-term soil moisture variation over Tibet Plateau.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.1
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• pp.50-56
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• 2015

This research was performed to test the hypothesis that the optimal fertilization rate for lettuce is various with soil moisture conditions. The experiment was conducted under a rainfall-intercepted facility in Suwon, South Korea from 2002 to 2003. Soil was irrigated at 30, 50, or 80 kPa of soil moisture tension at 15 cm soil depth in 2002 spring and fall and 20, 30, 50, or 80 kPa in 2003 spring. Fertilization was performed with four levels in spring for both years: none, 0.5, 1.0, and 1.5 times of the recommended N, P, and K fertilization rate. The irrigation amount increased with decreased irrigation starting point as soil moisture tension. The maximum yield was found at the lowest soil moisture tension in spring while irrigation at 50 kPa resulted in the greatest yield in fall. The yield responses of lettuce to fertilization rates were various with soil moisture condition. In spring, maximum yield was found at 1.0 or 1.5 times of the recommended fertilization rate at 20, 30, and 50 kPa irrigation while 0.5 or 1.0 times of fertilization rate resulted in the maximum yield in fall. Especially for 80 kPa irrigation in 2003 spring, yield was decreased by fertilization. It suggested that the optimum fertilization rate for lettuce is affected by soil moisture condition and that lower fertilization rate should be suggested when soil is managed in drier condition.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.6
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• pp.29-37
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• 2017

In this study, we analyzed the impacts of land surface characteristics on spatially and temporally distributed soil moisture values at the Yongdam and Soyang-river dam watersheds in 2014 and 2015. The soil moisture, NDVI (Normalized Difference Vegetation Index) and temperature values at the spatio-temporal scales were estimated using satellite-based MODIS (MODerate Resolution Imaging Spectroradiometer) products. Then the Pearson correlations between soil moisture and land surface characteristics (NDVI, temperature and DEM-digital elevation model) were estimated and analyzed, respectively. Overall, the monthly soil moisture values at the time step were highly influenced by the precipitation amounts. Also, the results showed that the soil moisture has the strong correlation with DEM while the temperature was inversely correlated with the soil moisture. However the monthly correlations between NDVI and soil moisture were highly varied along the time step. These findings indicated that water loss near the land surface are highly occurred by soil and plant activities as evapotranspiration and infiltration during the no/less precipitation period. But the high precipitation amounts reduce the impacts of land surface characteristics because of saturated condition of land surface. Thus these results demonstrated that soil moisture values are highly correlated with land surface characteristics. Our findings can be useful for water resources/environmental management, agricultural drought, etc.

• The Korean Journal of Ecology
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• v.6 no.3
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• pp.227-235
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• 1983

This research was made over drought resistance and optimum soil moisture needed with Plantago asiatica L. as the material by means of making out the process of its growth under different soil moisture contents. The soil used for the experiment was a mixture of vermiculite and c-layer soil, and the process of growth was compared with each other controlling its soil mositure as: 7%, 15%, 30%, 45%, and 60%. In 7% range of soil moisture which was of low content, the increase of growth was neither significantly indicated nor any permanent seeding done. In view of this phenomenon, Plantago asiatica L. appeared to be highly drought-resistant. It was found rising at 30% range and reaching the optimum state at 45% range and falling down at 60% range range. In viw of this fluctuation indicated above, the optimum soil moisture content needed for the growth of Plantago asiatica L. is thought to be between 30% and 60%. It is thought the number of seed per capsule is not affected by the soil moisture content. It is expected an ecotypic variation by the soil moisture content will bring forth upon Plantago asiatica L.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.2
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• pp.35-46
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• 2008

Soil moisture is one of the important components in hydrological processes and also controls the subsurface flow mechanism at a hillslope scale. In this study, time series of soil moisture were measured at a hillslope located in Gwangneung National Arboretum, Korea using a multiplex Time Domain Reflectometry(TDR) system measuring soil moisture with bi-hour interval. The Box-Jenkins transfer function and noise model was used to estimate spatial distributions of soil moisture histories between May and September, 2007. Rainfall was used as an input parameter and soil moisture at 10 cm depth was used as an output parameter in the model. The modeling process consisted of a series of procedures(e.g., data pretreatment, model identification, parameter estimation, and diagnostic checking of selected models), and the relationship between soil moisture and rainfall was assessed. The results indicated that the patterns of soil moisture at different locations and slopes along the hillslope were similar with those of rainfall during the measurment period. However, the spatial distribution of soil moisture was not associated with the slope of the monitored location. This implies that the variability of the soil moisture was determined more by rainfall than by the slope of the site. Due to the influence of vegetation activity on soil moisture flow in spring, the soil moisture prediction in spring showed higher variability and complexity than that in early autumn did. This indicates that vegetation activity is an important factor explaining the patterns of soil moisture for an upland forested hillslope.

• Journal of Korea Water Resources Association
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• v.54 no.2
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• pp.81-91
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• 2021

Synthetic Apreture Radar (SAR) is attracting attentions with its possibility of producing high resolution data that can be used for soil moisture estimation. High resolution soil moisture data enables more specific observation of soil moisture than existing soil moisture products from other satellites. It can also be used for studies of wildfire, landslide, and flood. The SAR based soil moisture estimation should be conducted considering vegetation, which affects backscattering signals from the SAR sensor. In this study, a SAR based soil moisture estimation at regions covered with various vegetation types on the middle area of Korea (Cropland, Grassland, Forest) is conducted. The representative backscattering model, Water Cloud Model (WCM) is used for soil moisture estimation over vegetated areas. Radar Vegetation Index (RVI) and in-situ soil moisture data are used as input factors for the model. Total 6 study areas are selected for 3 vegetation types according to land cover classification with 2 sites per each vegetation type. Soil moisture evaluation result shows that the accuracy of each site stands out in the order of grassland, forest, and cropland. Forested area shows correlation coefficient value higher than 0.5 even with the most dense vegetation, while cropland shows correlation coefficient value lower than 0.3. The proper vegetation and soil moisture conditions for SAR based soil moisture estimation are suggested through the results of the study. Future study, which utilizes additional ancillary vegetation data (vegetation height, vegetation type) is thought to be necessary.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1185-1193
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• 2023

The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.