필터링 기법을 이용한 농업용저수지 수위자료의 품질관리 방안
Quality Control on Water-level Data in Agricultural Reservoirs Considering Filtering Methods
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초록
Agricultural reservoirs are important facilities for storing or managing water for the purpose of securing agricultural water, creating and expandingagricultural production bases, and using them to increase agricultural production. In particular, the Korea Rural Community Corporation (KRC) managesagricultural reservoirs scattered across the country, and officially recognizes and distributes hydrological data to increase their public utilization and aimsto improve the value of water resources. Data on the water level of agricultural reservoirs are important. However, errors such as missing values andoutliners limit utilization of the data in various fields of research and industry. Therefore, water quality data measures should be devised to increasereliability. this study categorized different error types and looked at automatic correction methods to enhance the reliability of the vast hydrological data. In addition, the water level data corrected from errors were compared to the reference hydrologic data through expert judgment in accordance with thequality control procedure, and the most appropriate measures were verified. As KRC manages more agricultural reservoirs than any other institution,the proposed method of efficient and automatic water level data correction in this study is expected to increase the availability and reliability of thehydrological data.
Abstract
The Doam Lake Watershed is one of Gangwon-do’s non-point source management areas. This area has a lot of snowfall in winter, and it is expectedthat there will be a lot of soil erosion in early spring due to snow melting. In this study, snow melting was monitored in the Doam Lake watershedfrom February to 3, 2020. It was conducted to analyze the water quality changes by calculating the concentration of non-point source pollution causedby snowmelt, and to compare the concentration of water quality during snowmelt event with rainfall and non-rainfall event. As a result of water qualityanalysis, Event Mean Concentration (EMC) at the first monitoring was SS 33.9 mg/L, TP 0.13 mg/L, TN 4.33 mg/L, BOD 1.35 mg/L, TOC 1.84 mg/L. At the second monitoring, EMC were SS 81.3 mg/L, TP 0.15 mg/L, TN 3.12 mg/L, BOD 1.32 mg/L, TOC 3.46 mg/L. In parameter except SS, itshowed good water quality. It is necessary to establish management measures through continuous monitoring.
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