• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.29-29
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• 2011

SWAT (Soil and Water Assessment Tool) 모형은 물리적 기반의 준분포형 강우-유출 모형으로서, 대규모의 복잡한 유역에서 장기간에 걸친 다양한 종류의 토양과 토지이용 및 토지관리 상태에 따른 유출과 유사 및 오염물질의 거동에 대한 토지관리 방법의 영향을 예측이 가능하여, 수자원 관리 계획 및 유역관리를 위한 의사결정 지원 등 그 적용 범위가 매우 광범위하다. 이러한 모형의 적용성 검증을 위해서는 매개변수 민감도 분석 및 검 보정, 예측 불확실성 분석을 필요로 한다. 최근 수문 모델의 불확실성을 분석하기 위한 다양한 기법들이 개발 되었는데, 본 연구는 충주댐 유역(6,581.1 m)을 대상으로 유역출구점의 실측 일 유출량 자료(1998~2003)를 바탕으로 SWAT 모형의 유출관련 매개변수(총 18개)에 대한 불확실성 분석을 실시하였다. 이때 사용된 분석 기법으로는 SUFI2 (Sequential Uncertainty FItting algorithm 2), GLUE (Generalized Likelihood Uncertainty Estimation), ParaSol (Parameter Solution)등을 적용 하였다. 이러한 기법은 모두 SWAT-CUP (SWAT-Calibration Uncertainty Program, Abbaspour, 2007) 모형에 탑재되어있으며, 모형의 결과로써 검 보정, 매개변수의 민감도 분석, 각종 목적 함수 및 불확실성의 범위 등이 자동으로 산출 되므로 모형의 사용자가 불확실성 평가 기법의 분석 및 비교를 손쉽게 할 수 있다. 그 결과 대표적인 목적 함수인 결정 계수( $^2$)와 NSE (Nash-Sutcliffe Model Efficiency)는 모두 0.65에서 0.92사이의 값을 나타내어 대체적으로 모의가 잘 이루어졌음을 알 수 있었다. 그러나 불확실성의 범위를 나타내는 지표인 p-factor 및 r-factor에서는 평가 기법 별로 그 차이가 확연하게 드러났다. 여기서 p-factor는 불확실성 범위에 실측치가 포함되는 비율이며, r-factor는 불확실성의 상대적인 범위로 각각 1과 0에 가까울수록 모의 기법의 성능이 우수함을 의미한다. 세 가지 알고리듬 중에서 SUFI2의 p-factor가 약 0.51로 가장 높게 나타났으며, ParaSol의 r-factor가 0.00으로 가장 작게 나타났다. 여기서 p-factor는 불확실성 범위에 실측치가 포함되는 비율이며, r-factor는 불확실성의 상대적인 범위를 의미한다. 본 연구의 결과는 SWAT 모형을 이용한 수문모델링에서 수문분석에 따른 예측결과의 불확실성을 정량적으로 평가함으로서, 모형의 적용성 평가 및 모의결과의 신뢰성 확보에 근거자료로 활용이 가능할 것으로 판단된다.

• Journal of the Korean Wood Science and Technology
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• v.27 no.2
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• pp.70-77
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• 1999

Objective of this research is to obtain fundamental data of carbonized wood wastes for soil condition, de-ordorization, absorption of water, carrier for microbial activity, and purifying agent for water quality of river. The carbonization technique and the properties of carbonized wood wastes(thinned trees) are analyzed. Proximate analysis shows the thinned wood contains 0.22-0.73% ash, 77-80% volatile matter, and 10-14% fixed carbon. The charcoal yield decreases and the shrinkage rate increases as the carbonization temperature and time increase. The charcoal yields of Larix leptolepis, Pinus rigida and Pinus densiflora are high, whereas those of Pinus koraiensis and Quercus variabilis are low. The shrinkage rate by carbonization has same trend as water removal of wood. The specific gravity after the carbonization decreases about 50% comparing to green wood. The charcoal has 0.89-4.08% ash, 6.31-13.79% volatile matter, and 73.9-83.5% fixed carbon. As the carbonization temperature and time increase, pH of charcoal increases. When the carbonization temperature is $400^{\circ}C$, pH is about 7.5. When the temperature is between 600 to $800^{\circ}C$, pH is about 10 with small difference. The water-retention capacity is not affected by the carbonization temperature and time. The water-retention capacity within 24hr is about 2.5 - 3times of sample weight, and the equivalent moisture content becomes 2-10% after 24 hr.

• Ecology and Resilient Infrastructure
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• v.7 no.2
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• pp.114-125
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• 2020

Despite the various artificial neural networks that have been developed, most of the discharge models in previous studies have been developed using deep neural networks. This study aimed to develop a discharge model using a convolution neural network (CNN), which was used to solve classification problems. Furthermore, the applicability of CNN was evaluated. The photographs (pictures or images) for input data to CNN could not clearly show the characteristics of the study area as well as precipitation. Hence, the model employed in this study had to use numerical images. To solve the problem, the CN of NRCS was used to generate images as input data for the model. The generated images showed a good possibility of applicability as input data. Moreover, a new application of CN, which had been used only for discharge prediction, was proposed in this study. As a result of CNN training, the model was trained and generalized stably. Comparison between the actual and predicted values had an R² of 0.79, which was relatively high. The model showed good performance in terms of the Pearson correlation coefficient (0.84), the Nash-Sutcliffe efficiency (NSE) (0.63), and the root mean square error (24.54 ㎥/s).

• Bulletin of the Korean Space Science Society
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• 2007.10a
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• pp.139-143
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• 2007

Electric propulsion has become a cost effective and sound engineering solution for many space applications. The success of SMART-1 and MUSES-C developed by European Space Agency (ESA) and Japan Aerospace Exploration Agency (JAXA) each proved that even small spacecraft could accomplish planetary mission with electric propulsion systems. A small electric propulsion system which is Hall effect thruster like SMART-1 is under development by SaTReC and GDPL (Glow Discharge Plasma Lab.) in KAIST for the next microsatellite, STSAT-3. To achieve optimized propulsion system, it is very necessary to understand plasma motions of Hall effect thruster. In this paper, we try to approach comprehensive plasma model with the particle simulation complementary to Particle In Cell (PIC) simulation. We think these two different approaches will help experimenters to optimize Hall effect thruster performances.

• Journal of the Korean Recycled Construction Resources Institute
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• v.4 no.4
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• pp.431-438
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• 2016

Recently, Both rapid economic growth and high-quality native finishing materials demand in buildings such as local infrastructure facilities and cultural facilities have increased along with local quarries. So, increasing local quarries and environmental pollution occurred in quarries get the eyes to damaged area of the surroundings. As an example, carcinogen such as solid formed to fixing asbestos and dust have damaged to local resident. Especially, Radon gas released from asbestos can exist everywhere on earth, released soil and rock as radioactive substances, can be caused lung cancer followed by a smoking. When pollution source to indoor air quality that lacking ventilation rate of the residential building moved in a cycle, human responses such as headache, dizziness, etc. get appear, so on it threatened resident's physical condition. Thus, we need to urgent attention to reduction harmful substance. In the case of radon gas of the pollution source to indoor air quality in housing, it has characteristic that keep on going through half-life released from source, we need to control radon gas source than source removal. We set on vermiculite addition ratio to 10% which has harmful substances adsorption performance, proceed experiment to basalt waste rock addition ratio 50, 60, 70, 80(%). The result of an experiment, based on 'KS F 4035, precast terrazzo', we can be obtainable in the best terrazzo at basalt waste rock addition ratio 70%.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.359-365
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• 2019

This paper is a basic study for the performance evaluation, durability improvement and optimal design of tractor transmission. The engine torque of the 78 kW agricultural tractor during rotary tillage was measured using CAN communication. It was calculated with equivalent torque and then analyzed. In order to develop a reliable tractor, it is important to convert measured torque in various agricultural operations into equivalent torque and analyze it. The equivalent torque was calculated using Palmgren-Miner's rule, which is a representative cumulative damage law. The equivalent torque of rotary tillage period and steering period are 229.2 and 136.7 Nm, respectively. The maximum and average torque during rotary tillage period are 336.0 and 234.4 Nm, respectively. The maximum and average torque of the steering period are 288.0 and 134.6 Nm, respectively. The engine torque in rotary tillage period is higher than in the steering period because of cultivation of soil through PTO. The maximum and rated torque of engine are 387.0 and 323.0 Nm, respectively, which are 183% and 136% higher than the equivalent torque during rotary tillage and of steering section. Because transmission of agricultural tractor in Korea companies is generally designed by the rated torque of engine, there is a difference from measured torque during agricultural operations. Therefore, it is necessary to consider it for optimal design.

• Journal of Korea Water Resources Association
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• v.54 no.9
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• pp.681-692
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• 2021

Vegetation processes have a significant impact on rainfall runoff processes through evapotranspiration control, but are rarely considered in the conceptual lumped hydrological model. This study evaluated the model performance of the Hapcheon Dam watershed by integrating the ecological module expressing the leaf area index data sensed remotely from the satellite into the hydrological partition module. The proposed eco-hydrological model has three main features to better represent the eco-hydrological process in humid regions. 1) The growth rate of vegetation is constrained by water shortage stress in the watershed. 2) The maximum growth of vegetation is limited by the energy of the watershed climate. 3) The interaction of vegetation and aquifers is reflected. The proposed model simultaneously simulates hydrologic components and vegetation dynamics of watershed scale. The following findings were found from the validation results using the model parameters estimated by the SCEM algorithm. 1) Estimating the parameters of the eco-hydrological model using the leaf area index and streamflow data can predict the streamflow with similar accuracy and robustness to the hydrological model without the ecological module. 2) Using the remotely sensed leaf area index without filtering as input data is not helpful in estimating streamflow. 3) The integrated eco-hydrological model can provide an excellent estimate of the seasonal variability of the leaf area index.

• Journal of Wetlands Research
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• v.24 no.2
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• pp.115-122
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• 2022

As the impermeable area of soil increases due to urbanization, the water circulation system of the city is deteriorating. The existing guidelines for low impact development (LID) facilities installed to solve these water problems or in previous studies, engineering aspects are more prominent than landscaping aspects. This study attempted to present an engineering and landscaping model for reducing pollutants by identifying the effects of vegetation on rainfall outflows and pollutant reduction in bioretention and the economic aspects of planting. Based on the results of artificial rainfall monitoring at Jeonju Seogok Park and the literature on vegetation rainfall runoff and pollutant reduction performance, the best vegetation for reducing pollution compared to cost was Lythrum salicaria L and Salix gracilistyla Miq. was the best vegetation for carbon storage. If you insist to design plants with only these two plantation, there is no choice but to take risks such as biodiversity. Herbaceous plants such as Lythrum salicaria L can be replaced by death of the plants or pests if considered planting various plants. The initial planting cost could expensive, but it is also necessary to mix and plant Salix gracilistyla Miq, which are woody plants that are advantageous in terms of maintenance, according to the surrounding environment and conditions. Based on the conclusions drawn in this study, it can be a reference material when considering the reduction of pollution by species and carbon storage of vegetation in LID facilities.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

• The Journal of Engineering Geology
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• v.22 no.1
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• pp.67-81
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• 2012

The physical, chemical, and biological properties of clogging materials formed within groundwater wells in the Mt. Geumjeong area, Busan, Korea, were characterized. The particle size distribution (PSD) of clogging materials was measured by a laser analyzer. XRD, SEM, and TEM analyses were performed to obtain mineralogical information on the clogging materials, with an emphasis on identifying and characterizing the mineral species. In most cases, PSD data exhibited an near log-normal distribution; however, variations in frequency distribution were found in some intervals (bi-or trimodal distributions), raising the possibility that particles originated from several sources or were formed at different times. XRD data revealed that the clogging materials were mainly amorphous ironhydroxides such as goethite, ferrihydrite, and lapidocrocite, with lesser amounts of Fe, Mn, and Zn metals and silicates such as quartz, feldspar, micas, and smectite. Reddish brown material was amorphous hydrous ferriciron (HFO), and dark red and dark black materials were Fe, Mn-hydroxides. Greyish white and pale brown materials consisted of silicates. SEM observations indicated that the clogging materials were mainly HFO associated with iron bacteria such as Gallionella and Leptothrix, with small amounts of rock fragments. In TEM analysis, disseminated iron particles were commonly observed in the cell and sheath of iron bacteria, indicating that iron was precipitated in close association with the metabolism of bacterial activity. Rock-forming minerals such as quartz, feldspar, and micas were primarily derived from soils or granite aquifers, which are widely distributed in the study area. The results indicate the importance of elucidating the formation mechanisms of clogging materials to ensure sustainable well capacity.