• Journal of Biosystems Engineering
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• v.24 no.2
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• pp.89-98
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• 1999

In this paper, to estimate the effectiveness of the tractive performance prediction model(TPPMTV98) which was developed to predict the tractive performance of flexible tracked vehicles in previous paper, the experimental substantiation of the TPPMTV98 were conducted with the reconstructed tracked vehicle on the loam soil with the moisture content of 18.92%, and bevameter was constructed in order to measure soil properties in situ. The drawbar pulls measure were compared with predicted ones. As a result, the predicted drawbar pulls by the TPPMTV98 were well matched to the measured ones. Such results implied that the TPPMTV98 could well estimate the drawbar pulls at given soil conditions, and would be very useful as a simulation tool for designing a flexible tracked vehicle and predicting its tractive performance.

• Journal of Korean Society on Water Environment
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• v.36 no.5
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• pp.353-363
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• 2020

Hydrologic models can be classified into two types: those for understanding physical processes and those for predicting hydrologic quantities. This study deals with how to use the model to predict today's stream flow based on the system's knowledge of yesterday's state and the model parameters. In this regard, for the model to generate accurate predictions, the uncertainty of the parameters and appropriate estimates of the state variables are required. In this study, a relatively simple hydrologic partitioning model is proposed that can explicitly implement the hydrologic partitioning process, and the posterior distribution of the parameters of the proposed model is estimated using the Markov chain Monte Carlo approach. Further, the application method of the ensemble Kalman filter is proposed for updating the normalized soil moisture, which is the state variable of the model, by linking the information on the posterior distribution of the parameters and by assimilating the observed steam flow data. The stochastically and recursively estimated stream flows using the data assimilation technique revealed better representation of the observed data than the stream flows predicted using the deterministic model. Therefore, the ensemble Kalman filter in conjunction with the Markov chain Monte Carlo approach could be a reliable and effective method for forecasting daily stream flow, and it could also be a suitable method for routinely updating and monitoring the watershed-averaged soil moisture.

• Geomechanics and Engineering
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• v.33 no.6
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• pp.625-633
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• 2023

The volume changes associated with moisture or suction variation in expansive soils are of geotechnical and geoenvironmental design concern. These changes can impact the performance of infrastructure projects and lightweight structures. Assessment of unsaturated function for these materials leads to better interpretation and understanding, as well as providing accurate and economic design. In this study, expansive soils from different regions of Saudi Arabia were studied for their basic properties including gradation, plasticity and shrinkage, swelling, and consolidation characteristics. The unsaturated soil functions of saturated water content, air-entry values, and residual states were determined by conducting the tests for the entire soil water characteristic curves (SWCC) using different techniques. An attempt has been made to provide a prediction model for unsaturated properties based on the basic properties of these soils. Once the profile of SWCC has been predicted the time and cost for many tests can be saved. These predictions can be utilized in practice for the application of unsaturated soil mechanics on geotechnical and geoenvironmental projects.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.97-104
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• 2009

GIS (Geographic Information System) is very useful in describing basin wide geographic characteristics and hydrologic analysis. This study estimated long term hydrologic variations in the Geum river basin using the SSARR rainfall runoff simulation model to provide reliable hydrologic information associated with rainfall runoff management module. Calibrated various hydrologic information such as soil moisture index, water use, direct and base flow are generated using GIS tools to display spatial hydrologic information in the unit of subbasin of target watershed. In addition, the graphic user interface toolkit designed for data compilation is expected to support efficient basin wide rainfall runoff analysis.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.58-58
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• 2022

With the development of advanced technology, automation of agricultural work is spreading. In association with the 4th industrial revolution-based technology, research on field smart farm technology is being actively conducted. A state-of-the-art unmanned automated agricultural production demonstration complex was established in Naju-si, Jeollanam-do. For the operation of the demonstration area platform, it is necessary to build a sophisticated, advanced, and intelligent field smart farming model. For the operation of the unmanned automated agricultural production demonstration area platform, we are building data on the growth of soybean for smart cultivated crops and conducting research to determine the optimal time for agricultural work. In order to operate an unmanned automation platform, data is collected to discover digital factors for water management immediately after planting, water management during the growing season, and determination of harvest time. A subsurface drip irrigation system was established for smart water management. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. Vegetation indices were collected using drones to find key factors in soybean production prediction. In addition, major growth characteristics such as stem length, number of branches, number of nodes on the main stem, leaf area index, and dry weight were investigated. By discovering digital factors for effective decision-making through data construction, it is expected to greatly enhance the efficiency of the operation of the unmanned automated agricultural production demonstration area.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.83-100
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• 2020

This study evaluated the accuracy of soil moisture and evapotranspiration by calculating the hydrological parameters in Korean peninsula using Land Information System(LIS) developed by US NASA. We used Noah-MP surface model to calculate hydrological parameters, and used MERRA2(Modern-Era Retrospective analysis for Research and Applications, Version 2) for hydrological forcing data. And, International Geosphere-Biosphere Program(IGBP) and University of Maryland(UMD) land cover maps were applied to compare the output accuracy, and Automated Synoptic Observing System(ASOS) of KMA was used as ground observation data. In order to evaluate the accuracy of the output data, the correlation coefficient(CC), BIAS, and efficiency factor (NSE, Nash-Sutcliffe Efficiency) were analyzed with soil moisture and evapotranspiration by ASOS ground observation data. As a result, the correlation coefficient of soil moisture using IGBP was 0.56 on average, and evapotranspiration was about 0.71. On the other hand, soil moisture using UMD was 0.68 on average and evapotranspiration was about 0.72, and the correlation coefficient by UMD was evaluated as high accuracy compared to the results by using IGBP. The correlation coefficient of soil moisture was an average of 0.68 and evapotranspiration was an average of 0.72 when MERRA2 was used as hydrological forcing data. On the other hand, the soil moisture applied with ASOS was an average of 0.66, and evapotranspiration was an average of 0.72. It is judged that the ASOS point data was reanalyzed as 0.65°× 0.5°grids, which is the same spatial resolution with MERRA2, resulting in differences in accuracy depending on the region.

• Journal of Environmental Science International
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• v.28 no.8
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• pp.701-707
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• 2019

Highland farming is agriculture that takes place 400 m above sea level and typically involves both low temperatures and long sunshine hours. Most highland Chinese cabbages are harvested in the Gangwon province. The Ubiquitous Sensor Network (USN) has been deployed to observe Chinese cabbages growth because of the lack of installed weather stations in the highlands. Five representative Chinese cabbage cultivation spots were selected for USN and meteorological data collection between 2015 and 2017. The purpose of this study is to develop a weight prediction model for Chinese cabbages using the meteorological and growth data that were collected one week prior. Both a regression and random forest model were considered for this study, with the regression assumptions being satisfied. The Root Mean Square Error (RMSE) was used to evaluate the predictive performance of the models. The variables influencing the weight of cabbage were the number of cabbage leaves, wind speed, precipitation and soil electrical conductivity in the regression model. In the random forest model, cabbage width, the number of cabbage leaves, soil temperature, precipitation, temperature, soil moisture at a depth of 30 cm, cabbage leaf width, soil electrical conductivity, humidity, and cabbage leaf length were screened. The RMSE of the random forest model was 265.478, a value that was relatively lower than that of the regression model (404.493); this is because the random forest model could explain nonlinearity.

• Spatial Information Research
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• v.7 no.1
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• pp.39-48
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• 1999

A GRId-based Soil MOsture Routing Model(GRISMORM) which predicts temporal variation and spatial distribution of water balance on a daily time step for each grid element of the watershed was developed. The model was programmed by C-language which aims for high flexibility to any kind of GIS softwares. The model uses ASCII-formatted map data supported by the irregular gridded map of the GRASS(Geographic Resources Analysis Support System)-GIS and generates daily or monthly spatial distribution map of water balance components within the watershed. The model was applied to Ipyunggyo watershed(75.6$km^2$) ; the part of Bocheongchun watershed. Predicted streamflows resulting from two years(95 and 96) daily data were compared with those observed at the watershed outlet. The results of temporal variation and spatial distribution of soil moisture are also presented by using GRASS.

• Proceedings of the Korean Geotechical Society Conference
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• 1999.10a
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• pp.3-44
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• 1999

This paper discusses the lateral behavior of single and group piles in homogeneous and non-homogeneous(two layered) soil. In the single pile, the model tests were conducted to investigate the effects on ratio of lower layer height to embedded pile length, ratio of soil modules of upper layer to lower layer, boundary rendition of pile head and tip, embedded pile length, pile construction condition, ground condition with saturate and moisture state in Nak-Dong river sand. Also, in the group pile, the model tests were to investigate the effects on spacing-to-diameter ratio of pile, pile array, ratio of pile spacing, boundary condition of pile head and tip, eccentric load and ground condition. The maximum bending moment and deflection induced in active piles were found to be highly dependent on the relative density, pile construction condition, boundary condition of pile head and tip. Based on the results obtained, it was found that the decrease of lateral bearing capacity in saturated sand was in the range of 31% - 53% as compared with the case of dry sand. Also, in the group pile, a spacing-to-diameter of 6.0 seems to be large enough to eliminate the group effect for the case of relative density of 61.8%, and 32.8%, and then each pile in such a case behaves essentially the same as a single pile. In this study, the program is developed by using the modified Chang method which used p - y method and the exact solution of governing equation of pile and it can be used to calculate the deflection, bending moment and soil reaction with FDM in non-homogeneous soil. In comparing the modified Chang method with field test results, the predict results shows better agreement with measured results in field tests.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.3
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• pp.19-29
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• 2014

This study was to evaluate the potential climate change impact on watershed hydrological components of evapotranspiration, surface runoff, lateral flow, return flow, and streamflow using Soil and Water Assessment Tool (SWAT). For Yongdam dam watershed (930 $km^2$), the SWAT model was calibrated for five years (2002-2006) and validated for three years (2004-2006) using daily streamflow data at three locations and daily soil moisture data at five locations. The Nash-Sutcliffe model efficiency (NSE) and coefficient of determination ($R^2$) were 0.43-0.67 and 0.48-0.70 for streamflow, and 0.16-0.65 and 0.27-0.76 for soil moisture, respectively. For future evaluation, the HadGEM3-RA climate data by Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios were adopted. The biased future data were corrected using 30 years (1982-2011, baseline period) of ground weather data. The HadGEM3-RA 2080s (2060-2099) temperature and precipitation showed increase of $+4.7^{\circ}C$ and +22.5 %, respectively based on the baseline data. The impacts of future climate change on the evapotranspiration, surface runoff, baseflow, and streamflow showed changes of +11.8 %, +36.8 %, +20.5 %, and +29.2 %, respectively. Overall, the future hydrologic results by RCP emission scenarios showed increase patterns due to the overall increase of future temperature and precipitation.