• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.337-345
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• 2022

For data such as rainfall and soil moisture, it is important to obtain the values of all points required as geostatistical data. Spatial interpolation is generally performed in this process, and commercial software such as ArcGIS is often used. However, commercial software has fatal drawbacks due to its high expertise and cost. In this study, R, an open source-based environment with ArcGIS, a commercial software, was used to compare the differences according to the processing environment when performing spatial interpolation. The data for spatial interpolation was weather forecast data calculated through Land-Atmosphere Modeling Package (LAMP)-WRF model, and soil moisture data calculated for each cumulative rainfall scenario. There was no difference in the output value in the two environments, but there was a difference in user interface and calculation time. The results of spatial interpolation work in the test bed showed that the average time required for R was 5 hours and 1 minute, and for ArcGIS, the average time required was 4 hours and 40 minutes, respectively, showing a difference of 7.5%. The results of this study are meaningful in that researchers can derive the same results in a commercial software environment and an open source-based environment, and can choose according to the researcher's environment and level.

• Water for future
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• v.26 no.2
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• pp.99-105
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• 1993

A practical flood forecasting model(FFM) is suggested. The output of the model is the results which the initial condition of meteorological parameters and soil moisture are projected on the future. The physically based station model for rainfall forecasting(RF) and the storage function model for runoff prediction(RP) are adopted respectively. Input variables for FFM are air temperature, pressure, and dew-point temperature at the ground level and the flow at the rising limb(FRL). The constant parameters for FFM are average of optimum values which the past storm events have. Also loss rate of rainfall can predicted by FRL.

• Journal of Korea Water Resources Association
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• v.33 no.S1
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• pp.20-27
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• 2000

The grid-based KIneMatic wave STOrm Runoff Model(Kim, 1998; Kim, et al., 1998) which predicts temporal variation and spatial distribution of saturated overland flow, subsurface flow and stream flow was evaluated at two watersheds. this model adopts the single overland flowpath algorithm and simulates surface and/or subsurface water depth at each cell by using water balance of hydrologic components. the model programmed by C-language uses ASCII-formatted map data supported by the irregular gridded map of the GRASS (Geographic Resources Analysis Support System) GIS and generates the spatial distribution maps of discharge, flow depth and soil moisture of the watershed.

• Water Engineering Research
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• v.1 no.4
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• pp.321-330
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• 2000

The grid-based KIneMatic wave STOrm Runoff Model(Kim, 1998; Kim, et al., 1998) which predicts temporal variation and spatial distribution of overland flow, subsurface flow and stream flow was evaluated at two watersheds. This model adopts the single overland flowpath algorithm and simulates surface and/or subsurface water depth at each cell by using water balance of hydrologic components. The model programmed by C-language uses ASCII-formatted map data supported by the irregular gridded map of the GRASS(Geographic Resources Analysis Support System) GIS and generates the spatial distribution maps of discharge, flow depth and soil moisture of the watershed.

• Journal of Soil and Groundwater Environment
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• v.20 no.3
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• pp.34-40
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• 2015

Studies using stable water vapor isotopes have been recently conducted over the past two decades because of difficulties in analysis and sample collection in the past. Stable water vapor isotope data provide information of the moisture transport from ocean to continent, which are also used to validate an isotope enabled general circulation model for paleoclimate reconstructions. The isotopic compositions of groundwater and water vapor also provide a clue to how moisture moves from soil to atmosphere by evapotranspiration. International Atomic Energy Agency designates the stations over the world to observe the water vapor isotopes. To analyze the water vapor isotopes, a cryogenic sampling method has been used over the past two decades. Recently, two types of laser-based spectroscopy have been developed and remotely sensed data from satellites have the global coverage. In this review, measurements of isotopic compositions of water vapor will be introduced and some studies using the water vapor isotopes will also be introduced. Finally, we will suggest the future study in Korea.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.1
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• pp.91-97
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• 2013

The input parameters of scattering models for computing the backscattering coefficients of earth terrains are mainly soil moisture and surface roughness. The backscattering coefficients of soil surfaces are more sensitive to surface roughness than soil moisture. In this study, we propose a precise measurement method for roughness parameters and analyze measurement errors. We measured surface roughness using a pin-board profiler(1 m, 0.5 cm interval) and a laser profiler(1 m, 0.25 cm interval). The measurement differences between two profilers in an average sense are 0.097 cm for root-mean-square (RMS) height and 1.828 cm for correlation length. The analysis of the correlation functions and relative errors shows that the laser measurements are more stable than the pin-board measurements. The differences of the calculated backscattering coefficients using a surface scattering model between pin-board and laser profiler measurements are less than 1 dB.

• International Journal of Advanced Culture Technology
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• v.8 no.1
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• pp.19-25
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• 2020

This article describes the automated incubator designs for white mushrooms growing. Mongolia has a very long and cold winter, so the process of growing mushrooms is short. Therefore, we aim to design an automated incubator system that has created a favorable artificial environment for mushroom growing by examining the necessary conditions for mushroom growing. This system was designed to be able to hold for some time the required levels of soil moisture, air humidity, soil temperature, air temperature, and CO2 levels. This article presents the results of a system-based experiment that allows you to grow mushrooms for 30 days without human interference.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.1
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• pp.22-32
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• 1997

This experiment was conducted to obtain information for the cultivation of Korean valerian(Valeriana lauriei var. dasycarpa Hara) which will be useful for medicinal and aromatic resources. The effect of different temperature conditions, light intensities and soil water conditions on growth, yield and component of essential oil of V. fauriei were measured at the Dankook University, Cheonan, and a study on the shading treatment was at Umsung, Chungchongbukdo, and Jinbu, Kangwondo, in 1995. V. laudei was planted at five different temperature conditions, 10, 15, 20, 25 and 3$0^{\circ}C$, eight light intensity conditions, 1, 000, 2, 500, 5, 000, 20, 000, 30, 000, 40, 000, 50, 000 and 60, 000lux, six soil water contents, 30, 45, 55, 70, 80 and 90％ of the saturated soil, during growth stage. Shading treatment was three conditions, 0, 25 and 50％, during the daytime in field conditions. Photosynthesis had a highly significant relationship with temperature conditions in a quadratic regression model, from which the temperature for the plant growth was estimated to be 17.7$^{\circ}C$. A highly significant quadratic regression was noted between temperature and leaf width or root weight of V. fauriei. It was estimated from the regression equation that the optimum temperature for root growth was 20.3$^{\circ}C$. The content of essential oil and extract rate of root was the highest in the 15~2$0^{\circ}C$. Photosynthesis also was significantly affected by light intensity in a quadratic regression model, from which the optimum light intensity for the growth was estimated to be 40, 000lux. Root yield was more produced in Jinbu than that of in Umsung. The root yield was increased by the shading treatment in Umsung, whereas it was decreased by the shading treatment in Jinbu. The content of essential oil was not affected by the shading treatment of plants during the cultivation, while the compositions of components of essential oil were related to the growing locations. As soil water content was higher, the growth and content of root extract were increased. The optimum soil moisture for the growth of V. fauriei was 80~90％ of the saturated soil. In summary, the results indicated that the growth, yield and component of essential oil in V. fauriei were affected by environmental factors as well as soil moisture.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.5
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• pp.395-404
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• 2017

Cultivating soybeans in rice paddy field reduces labor costs and increases the yield. Soybeans, however, are highly susceptible to excessive soil water in paddy field. Controlled drainage system can adjust groundwater level (GWL) and control soil moisture content, resulting in improvement soil environments for optimum crop growth. The objective of this study was to fit the soybean growth data (canopy height and stem diameter) using Gompertz model and Logistic model at different GWL and validate those models. The soybean, Daewon cultivar, was grown on the lysimeters controlled GWL (20cm and 40cm). The soil textures were silt loam and sandy loam. The canopy height and stem diameter were measured from the 20th days after seeding until harvest. The Gompertz and Logistic models were fitted with the growth data and each growth rate and maximum growth value was estimated. At the canopy height, the $R_2$ and RMSE were 0.99 and 1.58 in Gompertz model and 0.99 and 1.33 in Logistic model, respectively. The large discrepancy was shown in full maturity stage (R8), where plants have shed substantial amount of leaves. Regardless of soil texture, the maximum growth values at 40cm GWL were greater than the value at 20cm GWL. The growth rates were larger at silt loam. At the stem diameter, the $R_2$ and RMSE were 0.96 and 0.27 in Gompertz model and 0.96 and 0.26 in Logistic model, respectively. Unlike the canopy height, the stem diameter in R8 stage didn't decrease significantly. At both GWLs, the maximum growth values and the growth rates at silt loam were all larger than the values at sandy loam. In conclusion, Gompertz model and Logistic model both well fit the canopy heights and stem diameters of soybeans. These growth models can provide invaluable information for the development of precision water management system.

• Journal of Korean Society of Rural Planning
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• v.30 no.1
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• pp.57-66
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• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.