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http://dx.doi.org/10.5389/KSAE.2021.63.5.083

Quality Control on Water-level Data in Agricultural Reservoirs Considering Filtering Methods  

Kim, Kyung-hwan (Jeonnam Regional Headquarter, Korea Rural Community Corporation (KRC))
Choi, Gyu-hoon (WeDB company)
Jung, Hyoung-mo (Agricultural Infrastructure Project Office, Korea Rural Community Corporation (KRC))
Joo, Donghyuk (Department of Rural and Bio-Systems Engineering & BK21 Education and Research Unit for Climate-Smart Reclaimed-Tideland Agriculture, Chonnam National University)
Na, Ra (Department of Rural and Bio-Systems Engineering & BK21 Education and Research Unit for Climate-Smart Reclaimed-Tideland Agriculture, Chonnam National University)
Choi, Eun-hyuk (Rural Research Institute, Korea Rural Community Corporation (KRC))
Kwon, Jae-Hwan (Agricultural Infrastructure Project Office, Korea Rural Community Corporation (KRC))
Yoo, Seung-Hwan (Department of Rural and Bio-Systems Engineering & BK21 Education and Research Unit for Climate-Smart Reclaimed-Tideland Agriculture, Chonnam National University)
Publication Information
Journal of The Korean Society of Agricultural Engineers / v.63, no.5, 2021 , pp. 83-93 More about this Journal
Abstract
Agricultural reservoirs are important facilities for storing or managing water for the purpose of securing agricultural water, creating and expanding agricultural production bases, and using them to increase agricultural production. In particular, the Korea Rural Community Corporation (KRC) manages agricultural reservoirs scattered across the country, and officially recognizes and distributes hydrological data to increase their public utilization and aims to improve the value of water resources. Data on the water level of agricultural reservoirs are important. However, errors such as missing values and outliners limit utilization of the data in various fields of research and industry. Therefore, water quality data measures should be devised to increase reliability. 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 the quality 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 the hydrological data.
Keywords
Statistical analysis; hampel filter; quality control; agricultural reservoirs;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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