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농업용저수지의 실시간 수위 보정을 위한 Hampel Filter의 최적 Window Size 분석
주동혁,나라,김하영,최규훈,권재환,유승환 한국농공학회 2022 한국농공학회논문집 Vol.64 No.3
Currently, a vast amount of hydrologic data is accumulated in real-time through automatic water level measuring instruments in agricultural reservoirs. At the same time, false and missing data points are also increasing. The applicability and reliability of quality control of hydrological data must besecured for efficient agricultural water management through calculation of water supply and disaster management. Considering the characteristics ofirregularities in hydrological data caused by irrigation water usage and rainfall pattern, the Korea Rural Community Corporation is currently applyingthe Hampel filter as a water level data quality management method. This method uses window size as a key parameter, and if window size is large,distortion of data may occur and if window size is small, many outliers are not removed which reduces the reliability of the corrected data. Thus,selection of the optimal window size for individual reservoir is required. To ensure reliability, we compared and analyzed the RMSE (Root Mean SquareError) and NSE (Nash–Sutcliffe model efficiency coefficient) of the corrected data and the daily water level of the RIMS (Rural InfrastructureManagement System) data, and the automatic outlier detection standards used by the Ministry of Environment. To select the optimal window size, weused the classification performance evaluation index of the error matrix and the rainfall data of the irrigation period, showing the optimal values at3 h. The efficient reservoir automatic calibration technique can reduce manpower and time required for manual calibration, and is expected to improvethe reliability of water level data and the value of water resources.
농업용 수로부의 수위 보정을 위한 필터기법별 적용성 분석
주동혁,유승환,나라,김하영,최규훈,윤형찬,박상빈 한국농공학회 2023 한국농공학회논문집 Vol.65 No.5
Due to the recent integrated water management policy, it is important to identify a reliable supply amount for establishing an agricultural water supplyplan. In order to identify the amount of agricultural water supply, it is essential to calculate the discharge by measuring the water level and flow velocityof reservoirs and canal agricultural water, and quality control to ensure reliability must be preceded. Unlike agricultural reservoirs, canal agriculturalwater are more sensitive to the surrounding environment and reservoir irrigation methods (continuous, intermittent irrigation, etc.), making it difficultto estimate general water level patterns and at the same time a lot of erroneous data. The Korea Rural Community Corporation is applying a filtertechnique as a quality control method capable of processing large quantities and real-time processing of canal agricultural water level data, andapplicability evaluation is needed. In this study, the types of errors generated by the automatic water level measurement system were first determined. In addition, by using the manual quality control data, a technique with high applicability is derived by comparing and analyzing data calibrated withGaussian, Savitzky-Golay, Hampel, and Median filter techniques, RMSE, and NSE, and the optimal parameters of the technique range was derived. Asa result, the applicability of the Median filter was evaluated the highest, and the optimal parameters were derived in the range of 120min to 240min. Through the results of this study, it is judged that it can be used for quantitative evaluation to establish an agricultural water supply plan.
딥러닝 기법을 이용한 농업용저수지 CCTV 영상 기반의 수위계측 방법 개발
주동혁,이상현,최규훈,유승환,나라,김하영,오창조,윤광식 한국농공학회 2023 한국농공학회논문집 Vol.65 No.1
This study aimed to evaluate the performance of water level classification from CCTV images in agricultural facilities such as reservoirs. Recently, theCCTV system, widely used for facility monitor or disaster detection, can automatically detect and identify people and objects from the images bydeveloping new technologies such as a deep learning system. Accordingly, we applied the ResNet-50 deep learning system based on ConvolutionalNeural Network and analyzed the water level of the agricultural reservoir from CCTV images obtained from TOMS (Total Operation ManagementSystem) of the Korea Rural Community Corporation. As a result, the accuracy of water level detection was improved by excluding night and rainfallCCTV images and applying measures. For example, the error rate significantly decreased from 24.39 % to 1.43 % in the Bakseok reservoir. We believethat the utilization of CCTVs should be further improved when calculating the amount of water supply and establishing a supply plan according tothe integrated water management policy.