• 한국농공학회논문집
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• 제65권5호
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• pp.1-11
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• 2023

Due to climate change and aging of reservoirs, damage to embankment slopes is increasing. However, the safety diagnosis of the reservoir slope is mainly conducted by visual observation, and the time and economic cost are formidable to apply soil mechanical tests and slope stability analysis. Accordingly, this study presented a predicting method for the compaction and strength characteristics of the reservoir embankment soil using a portable static cone penetration test. The predicted items consisted of dry density, cohesion, and internal friction angle, which are the main factors of slope stability analysis. Portable static cone penetration tests were performed at 19 reservoir sites, and prediction equations were constructed from the correlation between penetration resistance data and test results of soil samples. The predicted dry density and strength parameters showed a correlation with test results between R² 0.40 and 0.93, and it was found to replace the test results well when used as input data for slope stability analysis (R² 0.8134 or more, RMSE 0.0320 or less). In addition, the prediction equations for the minimum safety factor of the slope were presented using the penetration resistance and gradient. As a result of comparing the predicted safety factor with the analysis results, R² 0.5125, RMSE 0.0382 in coarse-grained soil, R² 0.4182 and RMSE 0.0628 in fine-grained soil. The results of this study can be used as a way to improve the existing slope safety diagnosis method, and are expected to be used to predict the characteristics of various soils and inspect slopes.

• 대한원격탐사학회지
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• 제37권5_2호
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• pp.1317-1328
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• 2021

본 연구는 천리안 해양위성 2호(GOCI-II)를 활용하여 개발된 해무 탐지 알고리즘의 초기 결과에 대한 분석을 수행하였다. GOCI-II 해무 탐지 성능을 확인하기 위해 1호와 2호가 중복으로 관측한 2020년 10월-2021년 3월 사이에 발생한 해무 사례에 대해 광학적 특성 분석을 실시하였다. 해무 탐지 알고리즘에 입력자료로 사용되는 412 nm 밴드 레일리 산란 보정 반사도(Rayleigh-corrected reflectance; R_rc)와 정규화된 국소 표준 편차(Normalized Local Standard Deviation; NLSD)를 GOCI, GOCI-II 자료를 시공간 일치시킨 뒤 분석한 결과 412 nm 밴드 레일리 R_rc의 경우 0.01의 평균 제곱근 오차 (Root Mean Squared Error; RMSE)와 0.998의 상관계수(correlation coefficient)을 나타내고, NLSD의 경우 0.007의 RMSE, 0.798의 correlation을 나타낸다. 해무와 구름이 갖는 광학적 특성을 분석하기 위해 천리안 해양위성 2호의 밴드 별 R_rc 값을 확인하였다. 구름의 경우 넓은 영역에서 높은 반사도를 보인 반면, 해무의 경우 모든 밴드에서 구름에 비해 상대적으로 반사도가 낮고 좁은 영역에 분포한다. 실제 해무 사례에 대해 GOCI와 GOCI-II 해무 탐지 알고리즘을 비교한 결과 전반적인 해무 탐지 성능은 크게 차이가 없으나 높아진 공간 해상도의 영향으로 해무 경계면에서 공간적으로 더 세밀한 탐지가 가능했다. 종관기상관측소 시정계 자료와 비교 분석하여 초기 자료에 대한 신뢰도를 조사하였다. 추후 충분한 샘플 확보로 인한 안정적인 성능 검증, 실시간 구름 정보 교체를 통한 후처리 과정 개선, 에어로졸 자료 추가로 해무 오탐지 감소를 통해 해무 탐지 알고리즘의 성능 향상이 기대된다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2005년도 학술발표회 논문집
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• pp.644-648
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• 2005

본 연구의 목적은 새만금 유역의 복잡한 용$\cdot$배수체계와 다양한 하천의 유출체계를 반영할 수 있는 유역 물수지모형을 구축하여 합리적인 유출량 추정을 위하여 새만금 상류유역의 신태인수위표 소유역을 대상으로 유역물수지모형의 적용성을 검토하고 일별 유출량을 모의하였다. 유역물수지모형을 이용하여 대상유역에서 모형의 보정기간인 1998년의 유출량을 모의한 결과, RMSE는 2.64mm/day, RMAE는 0.24mm/day, 그리고 결정계수($R^2$)는 0.91로 모의되었으며, 모형의 검정기간인 2003년의 유출량을 모의한 결과, RMSE는 3.53mm/day, RMAE는 0.35mm/day, 그리고 결정계수($R^2$)는 0.83로 모의되었다.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2003년도 학술발표논문집
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• pp.535-538
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• 2003

A Grey model was developed to forecast short-term runoff from the Naju watershed in Korea. In calibration, the root mean square error(RMSE) of the simulated runoff of six hours ahead using Grey model ranged from 6.3 to $290.52m^3/s,\;R^2$ ranged from 0.91 to 0.99, compared to the observed data. In verification, the RMSE ranged from 75.7 to $218.9m^3/s,\;R^2$ ranged from 0.87 to 0.96, compared to the observed data. The results in this study demonstrate that the proposed model can reasonably forecast runoff one to six hours ahead.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2005년도 학술발표논문집
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• pp.673-678
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• 2005

The objective of this paper is to develop the microorganism concentration simulation model for the health related effect analysis while farmers and water managers reuse the wastewater for agricultural irrigation. This model consists of the CE-QUAL-R1 model and the CREAMS-PADDY model. The CE-QUAL-R1 model is the 1-D numerical model to analyze the water quality of the reservoir and the CREAMS-PADDY model is modified from CREAMS model for considering the hydrologic cycles in paddy field. This model was applied to examine the application by the observed data from 2003 in Byoungjum study area. From this research, the average root mean square error (RMSE) for the simulated concentration during the calibration period was 0.51 MPN/100ml and correlation coefficient $(R^2)$ was 0.71. And the RMSE for the simulated concentration during the verification period was 0.46 MPN/100ml and $R^2$ was 0.73. This simulation results show that the coliform inflow concentrations by the wastewater irrigation wield great influence upon the temporal coliform concentrations in paddy field.

• 풍력에너지저널
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• 제14권3호
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• pp.25-33
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• 2023

In order to secure the safety of increasing offshore activities such as offshore wind farm maintenance and fishing, IMPACT, a mid-term marine weather forecasting system, was established by predicting marine weather up to 7 days in advance. Forecast data from the Korea Hydrographic and Oceanographic Agency (KHOA), which provides the most reliable marine meteorological service in Korea, was used, but wind speed and wave height forecast errors increased as the leading forecast period increased, so improvement of the accuracy of the model results was needed. The Model Output Statistics (MOS) method, a post-correction method using statistical machine learning, was applied to improve the prediction accuracy of wave height, which is an important factor in forecasting the risk of marine activities. Compared with the observed data, the wave height prediction results by the model before correction for 6 to 7 days ahead showed an RMSE of 0.692 m and R of 0.591, and there was a tendency to underestimate high waves. After correction with the MOS technique, RMSE was 0.554 m and R was 0.732, confirming that accuracy was significantly improved.

• Journal of Biosystems Engineering
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• 제36권2호
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• pp.96-108
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• 2011

Several methods of in-field measurements of Nitrogen and other soil properties using cores extracted by a hydraulic soil sampler were evaluated. A prototype core scanner was built to accommodate Veris Technologies commercial Vis-NIRS equipment. The testing result for pH, P and Mg were close to RPD (Ratio of Prediction to Deviation = Standard deviation/RMSE) of 2, however the scanner could not achieve the goal of RPD of 2 on some other properties, especially on nitrate nitrogen ($NO_3$) and potassium (K). In situ NIRS/EC probe showed similar results to the core scanner; pH, P and Mg were close to RPD of 2, while $NO_3$ and K were RPD of 1.5 and 1.2, respectively. Correlations between estimations using the probe and the core scanner were strong, with $r^2$ > 0.7 for P, Mg, Total N, Total C and CEC. Preliminary results for mid-IR spectroscopy showed an $r^2$ of 0.068 and an RMSE for nitrate (N) of 18 ppm, even after the removal of calcareous samples and possible N outlier. After removal of calcareous samples on a larger sample set, results improved considerably with an $r^2$ of 0.64 and RMSE of 6 ppm. However, this was only possible after carbonate samples were detected and eliminated, which would not be feasible under in-field measurements. Testing of $NO_3$ and K ion-selective electrodes (ISEs) revealed promising results, with acceptable errors measuring soil solutions containing nitrate and potassium levels that are typical of production agriculture fields.

• 수산해양기술연구
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• 제49권1호
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• pp.18-28
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• 2013

It was compared the estimated parameters by the surplus production from three different models, i.e., three types (Schaefer, Gulland, and Schnute) of the traditional surplus production models, a stock production model incorporating covariates (ASPIC) model and a maximum entropy (ME) model. We also evaluated the performance of models in the estimation of their parameters. The maximum sustainable yield (MSY) of small yellow croaker (Pseudosciaena polyactis) in Korean waters ranged from 35,061 metric tons (mt) by Gulland model to 44,844mt by ME model, and fishing effort at MSY ($f_{MSY}$) ranged from 262,188hauls by Schnute model to 355,200hauls by ME model. The lowest root mean square error (RMSE) for small yellow croaker was obtained from the Gulland surplus production model, while the highest RMSE was from Schnute model. However, the highest coefficient of determination ($R^2$) was from the ME model, but the ASPIC model yielded the lowest coefficient. On the other hand, the MSY of Kapenta (Limnothrissa miodon) ranged from 16,880 mt by ASPIC model to 25,373mt by ME model, and $f_{MSY}$, from 94,580hauls by ASPIC model to 225,490hauls by Schnute model. In this case, both the lowest root mean square error (RMSE) and the highest coefficient of determination ($R^2$) were obtained from the ME model, which showed relatively better fits of data to the model, indicating that the ME model is statistically more stable and robust than other models. Moreover, the ME model could provide additional ecologically useful parameters such as, biomass at MSY ($B_{MSY}$), carrying capacity of the population (K), catchability coefficient (q) and the intrinsic rate of population growth (r).

• Journal of Biosystems Engineering
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• 제42권3호
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• pp.190-198
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• 2017

Purpose: A thin-layer drying equation was developed to analyze the drying processes of soybeans (white and black beans) and investigate drying conditions by verifying the suitability of existing grain drying equations. Methods: The drying rates of domestic soybeans were measured in a drying experiment using air at a constant temperature and humidity. The drying rate of soybeans was measured at two temperatures, 50 and $60^{\circ}C$, and three relative humidities, 30, 40 and 50%. Experimental constants were determined for the selected thin layer drying models (Lewis, Page, Thompson, and moisture diffusion models), which are widely used for predicting the moisture contents of grains, and the suitability of these models was compared. The suitability of each of the four drying equations was verified using their predicted values for white beans as well as the determination coefficient ($R^2$) and the root mean square error (RMSE) of the experiment results. Results: It was found that the Thompson model was the most suitable for white beans with a $R^2$ of 0.97 or greater and RMSE of 0.0508 or less. The Thompson model was also found to be the most suitable for black beans, with a $R^2$ of 0.97 or greater and an RMSE of 0.0308 or less. Conclusions: The Thompson model was the most appropriate prediction drying model for white and black beans. Empirical constants for the Thompson model were developed in accordance with the conditions of drying temperature and relative humidity.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.222-223
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• 2017

기후변화로 인한 태풍 및 집중호우의 발생빈도가 증가함에 따라 매년 많은 홍수피해가 발생하고 있다. 특히 제주도는 지리적 특성상 태풍의 길목에 위치하고 있어 집중호우, 돌발홍수 등과 같은 자연재해에 연중 노출되어 있으며, 이상기후로 인한 일강우량의 경신이 빈번하게 발생함에 따라 홍수피해 위험이 증가하고 있다. 홍수피해를 저감시키기 위해서는 정확한 홍수량 산정을 통한 하천기본계획 및 치수계획 수립이 매우 중요하다. 실무에서는 홍수량 산정 시 대부분 HEC-HMS 모형을 활용하고 있으나 본 연구에서는 기존 방법이 아닌 분포형 모형인 Vflo를 활용하여 제주도심하천의 홍수유출을 해석하였다. 도심하천인 외도천을 연구대상유역으로 선정하였으며 Arc-GIS를 이용하여 DEM, 토지피복도, 토양도 등 지형인자들을 $30m{\times}30m$ 격자크기로 나누어 매개변수로 구축하였다. 제주도는 강우관측소가 조밀하고 고르게 분포되어 있어 강우자료의 경우는 레이더영상 자료로부터 추출하여 G/R 기법을 적용하여 보정하였다. 2012년 7월 태풍 카눈은 RMSE 2.6954와 0.9115, 8월 집중호우는 RMSE 2.5703, $R^2$ 0.9202, 9월 태풍 산바는 RMSE 2.1569, $R^2$ 0.9842로 높은 상관관계를 보였다. 본 연구의 홍수량 산정 방법 정확도 비교를 위해 현장관측자료(FSIV)를 분석한 유출량과 비교 분석하였다. Vflo를 활용한 홍수량 산정 방법은 미계측 유역이 많은 제주도에서 효율적으로 활용될 수 있을 것으로 판단되며, 다양한 홍수량 산정 방법을 통하여 하천기본계획 및 유역종합치수계획 등 치수계획 수립 시 많은 활용이 될 것으로 기대한다.