• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.153-153
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• 2019

Evapotranspiration (ET) is an important component of hydrological processes. Accurate estimates of ET variation are of vital importance for natural hazard adaptation and water resource management. This study first developed a soil water index (SWI)-based Priestley-Taylor algorithm (SWI-PT) based on the enhanced vegetation index (EVI), SWI, net radiation, and temperature. The algorithm was then compared with a modified satellite-based Priestley-Taylor ET model (MS-PT). After examining the performance of the two models at 10 flux tower sites in different land cover types over East Asia and Australia, the daily estimates from the SWI-PT model were closer to observations than those of the MS-PT model in each land cover type. The average correlation coefficient of the SWI-PT model was 0.81, compared with 0.66 in the original MS-PT model. The average value of the root mean square error decreased from $36.46W/m^2$ to $23.37W/m^2$ in the SWI-PT model, which used different variables of soil moisture and vegetation indices to capture soil evaporation and vegetative transpiration, respectively. By using the EVI and SWI, uncertainties involved in optimizing vegetation and water constraints were reduced. The estimated ET from the MS-PT model was most sensitive (to the normalized difference vegetation index (NDVI) in forests) to net radiation ($R_n$) in grassland and cropland. The estimated ET from the SWI-PT model was most sensitive to $R_n$, followed by SWI, air temperature ($T_a$), and the EVI in each land cover type. Overall, the results showed that the MS-PT model estimates of ET in forest and cropland were weak. By replacing the fraction of soil moisture ($f_{sm}$) with the SWI and the NDVI with the EVI, the newly developed SWI-PT model captured soil evaporation and vegetation transpiration more accurately than the MS-PT model.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.1
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• pp.1-12
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• 2020

As one of the essential resources in the agricultural process, soil moisture has been carefully managed by predicting future changes and deficits. In recent years, statistics and machine learning based approach to predict soil moisture has been preferred in academia for its generalizability and ease of use in the field. However, little is known that machine learning based soil moisture prediction is applicable in the situation of South Korea. In this sense, this paper aims to examine 1) whether publicly available weather data generated in South Korea has sufficient quality to predict soil moisture, 2) which machine learning algorithm would perform best in the situation of South Korea, and 3) whether a single machine learning model could be generally applicable in various regions. We used various machine learning methods such as Support Vector Machines (SVM), Random Forest (RF), Extremely Randomized Trees (ET), Gradient Boosting Machines (GBM), and Deep Feedforward Network (DFN) to predict future soil moisture in Andong, Boseong, Cheolwon, Suncheon region with open source weather data. As a result, GBM model showed the lowest prediction error in every data set we used (R squared: 0.96, RMSE: 1.8). Furthermore, GBM showed the lowest variance of prediction error between regions which indicates it has the highest generalizability.

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.423-429
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• 2016

This study aims at assessing the quality of the Advanced Microwave Scanning Radiometer 2 (AMSR2) soil moisture products onboard GCOM-W1 satellite based on Land Parameter Retrieval Model (LPRM) soil moisture retrieval algorithm with field measurements in South Korea from March to September, 2014. Results of mean bias and root mean square error between AMSR2 LPRM soil moisture products (X-band) and ground measurements showed reasonable value of 0.03 and 0.16. Also, the maximum of the Pearson correlation coefficients was 0.67, which showed good agreement in terms of temporal variability with ground measurements. By comparing AMSR2 soil moisture with in-situ measurement according to the overpass time and band frequency, X-band products on the ascending time outperformed than those of C1-band and C2-band. Furthermore, this study offers an insight into the applicability of the AMSR2 soil moisture products for monitoring various natural disasters at a large scale such as drought and flood.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.26-67
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• 2020

Synthetic Aperture Radar(SAR) is able to photograph the earth's surface regardless of weather conditions, day and night. Because of its possibility to search for hydrological factors such as soil moisture and groundwater, and its importance is gradually increasing in the field of water resources. SAR began to be mounted on satellites in the 1970s, and about 15 or more satellites were launched as of 2020, which around 10 satellites will be launched within the next 5 years. Recently, various types of SAR technologies such as enhancement of observation width and resolution, multiple polarization and multiple frequencies, and diversification of observation angles were being developed and utilized. In this paper, a brief history of the SAR system, as well as studies for estimating soil moisture and hydrological components were investigated. Up to now hydrological components that can be estimated using SAR satellites include soil moisture, subsurface groundwater discharge, precipitation, snow cover area, leaf area index(LAI), and normalized difference vegetation index(NDVI) and among them, soil moisture is being studied in 17 countries in South Korea, North America, Europe, and India by using the physical model, the IEM(Integral Equation Model) and the artificial intelligence-based ANN(Artificial Neural Network). RADARSAT-1, ENVISAT, ASAR, and ERS-1/2 were the most widely used satellite, but the operation has ended, and utilization of RADARSAT-2, Sentinel-1, and SMAP, which are currently in operation, is gradually increasing. Since Korea is developing a medium-sized satellite for water resources and water disasters equipped with C-band SAR with the goal of launching in 2025, various hydrological components estimation researches using SAR are expected to be active.

• Korean Journal of Agricultural Science
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• v.14 no.1
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• pp.68-80
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• 1987

This study was carried out to investigate the evapotranspiration and variations of soil moisture contents for soybeans. The relationship between actual evapotranspiration obtained by the water balance equation and estimated evapotranspiration obtained by the soil moisture model was analyzed. The results obtained were summarized as follows; 1. The total amount of actual evapotranspiration of soybeans during growing season was 405.7mm. The total amount of reference crop evapotranspiration of soybeans that was estimated by Pan evaporation and Hargreaves method were 547.8 mm and 586.8 mm, respectively. Crop coefficient during growing season were shown on Table 1. 2. Measured actual evapotranspiration of soybean during growing season was 405.7 mm and estimated actual evapotranspiration by pan evaporation and Hargreaves method were 424.7 mm, and 426.1mm, r3 respectively. 3. The variations of soil moisture content for soybeans were high at 10cm layer, as compared with those at 30cm and 50cm layers. Because discrepancy between the variations of soil moisture content predicted by model and observed by soil moisture meter was still great, it is required to study the consumptive types of soil moisture at each root depth.

• Korean Journal of Remote Sensing
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• v.10 no.2
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• pp.17-35
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• 1994

A semi-empirical model for microwave polarimetric radar backscattering from bare soil surfaces was developed using polarmetric radar measurements and the knowledge based on the theoretical and numerical solutions. The microwave polarimetric backscatter measurements were conducted for bare soil surfaces under a variety of roughness and moisture conditions at L-, C-, and X-band frequencies at incidence angles ranging from 10` to 70`. Since the accrate target parameters as well as the radar parameters are necessary for radar scattering modeling, a complete and accurate set of ground truth data were also collected using a laser profile meter and dielectric probes for each surface condition, from which accurate measurements were made of the rms height, correlation length, and dielectric constant. At first, the angular and spectral dependencies of the measured radar backscatter for a wide range of roughnesses and moisture conditions are examined. Then, the measured scattering behavior was tested using theoretical and numerical solutions. Based on the experimental observations and the theoretical and numerical solutions, a semi-empirical model was developed for backscattering coeffients in terms of the surface roughness parameters and the relative dielectric constant of the soil surface. The model was found to yield very good agreement with the backscattering measurements of this study as well as with independent measurements.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.187-192
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• 2000

The severity of drought could be evaluated by the accumulative rainfall method, soil moisture condition method, storage ratio method, and water supply restriction intensity method, etc. The pattern of drought could be forecast with the most similar pattern of accumulative rainfall out of the file of past rainfall history. The information that how much rainfall should be expected to overcome the present drought could be obtained from the reservoir storage ratio and soil moisture condition.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.8 no.1
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• pp.21-31
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• 2012

This paper reviewed and evaluated some of the commonly used prediction models for thermal conductivity of soils with the experimental data. Semi-theoretical models for two-component materials were found inappropriate to estimate the thermal conductivity of dry state soils. It came out that the model developed by Cote and Konrad gave the best overall prediction results for unsaturated soils available in the literature. However, it still needs to be improved to cover a wider range of soil types and degrees of saturation. In the present study, parametric analysis is also conducted to investigate the effect of soil type and moisture content on the horizontal ground heat exchanger design. The analysis shows that horizontal ground heat exchanger pipe length is reduced with the increase of soil thermal conductivity and water content. The calculation results also show that horizontal ground heat exchanger size can be reduced to a certain extent by using backfilling material with a higher thermal conductivity of solid particles.

• Journal of Biosystems Engineering
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• v.28 no.1
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• pp.1-10
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• 2003

A computer simulation was carried out to determinate the optimum capacity of bulk type trailer which is used as a tractor attachment. Soil physical properties. such as soil moisture content. bulk density, soil hardness and soil texture were measured in the 10 major rice production area for computer simulation. Mathematical model which include soil physical properties and vehicle factor was used for computer simulation. Most of the soil texture of the investigated area was silty loam. Soil moisture content ranged between 30 and 40% mostly. Soil bulk density was in the range of 1.500 to 1.700 kg/㎥. Soil hardness ranged between 1 to 18 kg/$\textrm{cm}^2$. Soil hardness incorporate the effects of many soil physical properties such as moisture content texture and bulk density, and so the range of soil hardness was greater than any other physical properties. The capacity of bulk type trailer was above 3000 kg$_{f}$ fer the most of the investigated area. and mostly in the range of 4000 to 6000 kg$_{f}$ depending upon the slip. But for the soft soil area such as Andong and Namyang. tractor itself had mobility problem and showed minus trailer capacity for some places. For this area. the capacity of bulk type trailer ranged between 1000 and 2000 kg$_{f}$ mostly so bulk type trailer should be designed as a small capacity compared to the other area.ared to the other area. area.

• Korean Journal of Soil Science and Fertilizer
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• v.47 no.1
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• pp.48-58
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• 2014

In order to evaluate water balance at upland according to RCP8.5 climate change scenario distributed by Korean Meteorological Administration (KMA), we simulated soil moisture using estimation model, called AFKAE0.5 for 66 sites from 2011 to 2020, and established the water balance maps. The amount of annual average precipitation by RCP8.5 scenario was highest in 2016 as recorded 2,062 mm and lowest in 2011 with 1,134 mm. As result of analysis for monthly precipitation and runoff, the amounts of precipitation and runoff have been especially intensive in July in 2014, 2016, 2019, and 2020. Overall, the area of Kyeongbuk and Gyeonggi was estimated more dried status of soil compared with precipitation. Except 2015 and 2020, soil water balance was recorded as negative value in other years which was calculated by subtracting output from input. The status of soil moisture was the most dry in 2020 among those in other years.