• 한국농공학회논문집
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• 제62권6호
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• pp.11-20
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• 2020

We estimated the spatio-temporally distributed soil moisture using Sentinel-1A/B SAR (Synthetic Aperture Radar) sensor images and soil moisture data assimilation technique in South Korea. Soil moisture data assimilation technique can extract the hydraulic parameters of soils using observed soil moisture and GA (Genetic Algorithm). The SWAP (Soil Water Atmosphere Plant) model associated with a soil moisture assimilation technique simulates the soil moisture using the soil hydraulic parameters and meteorological data as input data. The soil moisture based on Sentinel-1A/B was validated and evaluated using the pearson correlation and RMSE (Root Mean Square Error) analysis between estimated soil moisture and TDR soil moisture. The soil moisture data assimilation technique derived the soil hydraulic parameters using Sentinel-1A/B based soil moisture images, ASOS (Automated Synoptic Observing System) weather data and TRMM (Tropical Rainfall Measuring Mission)/GPM (Global Precipitation Measurement) rainfall data. The derived soil hydrological parameters as the input data to SWAP were used to simulate the daily soil moisture values at the spatial domain from 2001 to 2018 using the TRMM/GPM satellite rainfall data. Overall, the simulated soil moisture estimates matched well with the TDR measurements and Sentinel-1A/B based soil moisture under various land surface conditions (bare soil, crop, forest, and urban).

• 한국농공학회논문집
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• 제59권1호
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• pp.71-79
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• 2017

Climate change phenomenon is posing a serious threat to sustainable corn production in Ghana. This study investigated the impacts of climate change on the rain-fed corn yield in the Dangme East district, Ghana by using Aquacrop model with a daily weather data set of 22-year from 1992 to 2013. Analysis of the weather data showed that the area is facing a warming trend as the numbers of years hotter and drier than the normal seemed to be increasing. Aquacrop model was assessed using the limited observed data to verify model's sufficiency, and showed credible results of $R^2$ and Nash-Sutcliffe efficiency (NSE). In order to simulate the corn yield response to climate variability four climate change scenarios were designed by varying long-term average temperature in the range of ${\pm}1^{\circ}C{\sim}{\pm}3^{\circ}C$ and average annual rainfall to ${\pm}5%{\sim}{\pm}30%$, respectively. Generally, the corn yield was negatively correlated to temperature rise and rainfall reduction. Rainfall variations showed more prominent impacts on the corn yield than that of temperature variations. The reduction in average rainfall would instantly limit the crop growth rate and the corn yield irrespective of the temperature variations.

• 한국농공학회논문집
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• 제64권1호
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• pp.79-89
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• 2022

Soil moisture is significantly related to crop growth and plays an important role in irrigation management. To predict soil moisture, various process-based model has been developed and used in the world. Various models (Land surface model) may have different performance depending on the model parameters and structures that causes the different model output for the same modeling condition. In this study, the three land surface models (Noah Land Surface Model, Soil Water Atmosphere Plant, Community Land Model) were used to compare the model performance (soil moisture prediction) and develop the multi-model simulation. At first, the genetic algorithm was used to estimate the optimal soil parameters for each model, and the parameters were used to predict soil moisture in the study area. Then, we used the multi-model approach based on Bayesian model averaging (BMA). The results derived from this approach showed a better match to the measurements than the results from the original single land surface model. In addition, identifying the strengths and weaknesses of the single model and utilizing multi-model methods can help to increase the accuracy of soil moisture prediction.

• Coupled systems mechanics
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• 제12권1호
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• pp.1-20
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• 2023

On the basis of the explicit time-domain method, an investigation is performed on the influence of the rotational stiffness and rotational damping of the vehicle body and front-rear bogies on the dynamic responses of the vehicle-bridge coupled systems. The equation of motion for the vehicle subsystem is derived employing rigid dynamical theories without considering the rotational stiffness and rotational damping of the vehicle body, as well as the front-rear bogies. The explicit expressions for the dynamic responses of the vehicle and bridge subsystems to contact forces are generated utilizing the explicit time-domain method. Due to the compact wheel-rail model, which reflects the compatibility requirement of the two subsystems, the explicit expression of the evolutionary statistical moment for the contact forces may be performed with relative ease. Then, the evolutionary statistical moments for the respective responses of the two subsystems can be determined. The numerical results indicate that the simplification of vehicle model has little effect on the responses of the bridge subsystem and the vehicle body, except for the responses of the rotational degrees of freedom for the vehicle subsystem, regardless of whether deterministic or random analyses are performed.

• 한국농공학회논문집
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• 제62권2호
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• pp.31-38
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• 2020

Controlled Low Strength Material (CLSM) has high fluidity and self-compaction characteristics. CLSM is mainly used for backfilling the excavated road. Early-age properties of CLSM should be characterized for fast restoration of the road. In this study, shear wave monitoring and Vicat needle test are performed to investigate the early-age properties of CLSM depending on the setting time. CLSM consists of CSA cement, fly ash, silt and sand, accelerator, and water. Five fly ashes with different chemical properties are used for CLSM samples. The penetration of CLSM along setting time is obtained through the Vicat needle test. A pair of bender elements are placed in a mold for shear wave measurement, and the change in shear waves with the setting time is monitored. The experimental results show that, regardless of the type of fly ash, the penetration depth decreases and the shear wave velocity increases with the setting time. Depending on the type of fly ash, initial and final times and shear wave velocity change. After testing, the correlation between penetration and shear wave velocity is obtained with high coefficient of determination. The shear wave measurement technique using the bender element can be used to identify early-age properties.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.196-196
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• 2020

토양은 육상생태계에 있어 가장 많은 탄소를 저장하고 있으며, 대기 중 CO₂를 토양탄소로 전환하여 쉽게 방출되지 않고 토양 내에 저장하는 역할을 한다. 이렇듯 토양 유기탄소 배출관리는 기후변화에 있어 중요한 문제로 대두되고 있다. 하지만 토지이용의 변화와 무분별한 관리로 인하여 토양내에 저장되어 있는 토양 탄소배출이 지속적으로 증가 하고 있다. 따라서 토양탄소 배출로 인한 경제적 피해를 수치적으로 표현하는 가치평가가 필요하다. 현재 토양에 저장된 토양유기탄소 함량을 토양통별로 토양정보시스템에서 제공하고 있지만 국내 토양 토양탄소 저장량의 산정에 관한 연구는 미비한 실정이다. 따라서 본 연구에서는 토양 특성을 이용하여 토양 유기탄소 저장량을 산정하고, 산정된 토양 유기탄소 저장량과 정밀토양도를 이용하여 남한의 토양 유기탄소 가치평가를 실시하였다. 토양의 특성은 물리적 특성인 모래(Sand), 이토(Silt), 점토(Clay), 자갈(Gravel)함량과 화학적 특성인 유기물함량(Organic Matter)를 사용하였다. 토양 유기탄소저장량 산정의 검증을 위하여 전라남도 진도군의 토양유기탄소 저장량을 산정한 결과 486,696t으로, 선행연구와 유사한 결과를 나타내었다. 이러한 검증 결과를 바탕으로 남한의 토양 유기탄소 저장량을 산정한 결과 305.54Mt의 유기탄소가 저장된 것으로 나타났으며, 단위 면적당 유기탄소 저장량의 경우 3.11kg/㎡으로 나타났다. 또한 2019년 상반기 기준 평균 탄소거래권 가격(27,500원/톤)을 이용하여 우리나라 국토의 토양탄소 저장량 가치평가를 실시한 결과, 약 8조 4천억원의 경제적 가치가 있는 것으로 나타났다. 본 연구는 토양의 물리적·화학적 특성을 이용하여 토양의 유기탄소 저장량을 산정하였으며, 토양에 저장되어 있는 유기탄소의 가치평가를 수행하였다. 본 연구결과는 농업, 수문, 기후변화 등 다양한 분야에서 필요로 하는 기초자료로 활용될 수 있을 것으로 판단된다.

• Journal of Biosystems Engineering
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• 제43권4호
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• pp.420-425
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• 2018

Purpose: Chemical fertilizers contribute to agricultural productivity. Annually, 450,000 tons of chemical fertilizers are used in Korea, which is 268 kg per hectare (MAFRA, 2016). However, excessive use causes problems such as environmental pollution and soil acidification. This study proposes use conditions for a fertilizer distributor that can reduce excessive fertilization by analyzing distribution patterns. Methods: This study analyzed fertilizer application uniformity according to the number of blades on a centrifugal fertilizer distributor (three or four blades), orifice gate open ratio (50 or 100%), and blade rotation speed (400, 500, or 600 rpm). Results: When using four blades, the coefficient of variation (CV) was lower than when using three by 11-13% points, and the CV using the 50% open ratio was 10-30% points lower than using the 100% open ratio. The CV at 500 rpm blade rotating speed was 9-12% points lower than that for 400 and 600 rpm. Conclusions: The CV with four blades, 50% orifice gate open ratio, and 500 rpm of blade rotating speed was 18.4%, which provided the most uniform fertilization.

• 한국농공학회논문집
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• 제64권1호
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• pp.39-50
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• 2022

In this study, we suggested the optimal training period for predicting the streamflow using the LSTM (Long Short-Term Memory) model based on the deep learning and CMIP5 (The fifth phase of the Couple Model Intercomparison Project) future climate scenarios. To validate the model performance of LSTM, the Jinan-gun (Seongsan-ri) site was selected in this study. We comfirmed that the LSTM-based streamflow was highly comparable to the measurements during the calibration (2000 to 2002/2014 to 2015) and validation (2003 to 2005/2016 to 2017) periods. Additionally, we compared the LSTM-based streamflow to the SWAT-based output during the calibration (2000~2015) and validation (2016~2019) periods. The results supported that the LSTM model also performed well in simulating streamflow during the long-term period, although small uncertainties exist. Then the SWAT-based daily streamflow was forecasted using the CMIP5 climate scenario forcing data in 2011~2100. We tested and determined the optimal training period for the LSTM model by comparing the LSTM-/SWAT-based streamflow with various scenarios. Note that the SWAT-based streamflow values were assumed as the observation because of no measurements in future (2011~2100). Our results showed that the LSTM-based streamflow was similar to the SWAT-based streamflow when the training data over the 30 years were used. These findings indicated that training periods more than 30 years were required to obtain LSTM-based reliable streamflow forecasts using climate change scenarios.

• 한국농공학회논문집
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• 제58권5호
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• pp.19-28
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• 2016

This study was to design the optimal locations of the water level monitoring to quantify the agricultural water use in irrigation area supplied from an agricultural reservoir. In most of agricultural areas without TM/TC (Tele-Monitoring and Tele-Control) or monitoring network, irrigation water have been supplied on conventional experience and agricultural reservoir have been operated based on the operating simulation results by HOMWRS (Hydrological Operation Model for Water Resources System). Therefore, this study quantified the amount of agricultural water use in an irrigation area (Musu Reservoir, Jincheon-gun) by establishing water level monitoring network and analyzed the agricultural water saving effect. According to the evaluation of the economic values for water saving effect, the saving agricultural water of 1.7 million ton was analyzed to have economic values of 0.85 million won as water for living, and 1.78 million won as water for industrial use. It is identified to secure economic feasibility of the new water monitoring network by establishing one monitoring point in the entrance, irrigation area and endpoint through the economic analysis.

• 한국농공학회논문집
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• 제62권1호
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• pp.51-60
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• 2020

The purpose of this study is to determine the spatial and temporal resolutions that can represent land surface characteristics comprised of various land use using Landsat/AMSR2-based soil moisture data. We estimated the Landsat (30 m×30 m)-based soil moisture values using the soil moisture regression model. Then, the Landsat (30 m×30 m)-based soil moisture (reference values) were resampled to the relatively coarse resolutions from 1 km to 4 km, respectively. Comparing the reference values to the resampled soil moisture values, we confirmed that uncertainties were increased with the spatial resolutions of 2 km~4 km indicating that the spatial resolution of 1 km×1 km is required to represent the complicated land surface. Also, the AMSR2 soil moisture values have less uncertainties compared to SMAP data with the temporal resolution of 1~2 days. Thus, our findings can be useful for various areas such as agriculture, hydrology, forest, etc.