Integrated Quality Control Process for Hydrological Database: A Case Study of Daecheong Dam Basin in South Korea
1
Department of Civil Engineering, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin 17104, Korea
2
Department of Civil Engineering, The University of Suwon, Hwaseong 18323, Korea
3
Department of Civil and Environmental Engineering, Hanyang University, Ansan 15588, Korea
4
Rural Research Institute, Korea Rural Community Corporation (KRC), Sejong 30130, Korea
5
K-Water Research Institute, K-Water (Korea Water Resources Corporation), Daejeon 34045, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Aizhong Ye
Water 2021, 13(20), 2820; https://doi.org/10.3390/w13202820
Received: 19 August 2021
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Revised: 3 October 2021
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Accepted: 5 October 2021
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Published: 11 October 2021
(This article belongs to the Special Issue Assessing and Managing Risk of Flood and Drought in a Changing World)
In our intelligent society, water resources are being managed using vast amounts of hydrological data collected through telemetric devices. Recently, advanced data quality control technologies for data refinement based on hydrological observation history, such as big data and artificial intelligence, have been studied. However, these are impractical due to insufficient verification and implementation periods. In this study, a process to accurately identify missing and false-reading data was developed to efficiently validate hydrological data by combining various conventional validation methods. Here, false-reading data were reclassified into suspected and confirmed groups by combining the results of individual validation methods. Furthermore, an integrated quality control process that links data validation and reconstruction was developed. In particular, an iterative quality control feedback process was proposed to achieve highly reliable data quality, which was applied to precipitation and water level stations in the Daecheong Dam Basin, South Korea. The case study revealed that the proposed approach can improve the quality control procedure of hydrological database and possibly be implemented in practice.
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Keywords:
data reconstruction; data validation; hydrological data; quality control; smart water management
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MDPI and ACS Style
Jeong, G.; Yoo, D.-G.; Kim, T.-W.; Lee, J.-Y.; Noh, J.-W.; Kang, D. Integrated Quality Control Process for Hydrological Database: A Case Study of Daecheong Dam Basin in South Korea. Water 2021, 13, 2820. https://doi.org/10.3390/w13202820
AMA Style
Jeong G, Yoo D-G, Kim T-W, Lee J-Y, Noh J-W, Kang D. Integrated Quality Control Process for Hydrological Database: A Case Study of Daecheong Dam Basin in South Korea. Water. 2021; 13(20):2820. https://doi.org/10.3390/w13202820
Chicago/Turabian StyleJeong, Gimoon, Do-Guen Yoo, Tae-Woong Kim, Jin-Young Lee, Joon-Woo Noh, and Doosun Kang. 2021. "Integrated Quality Control Process for Hydrological Database: A Case Study of Daecheong Dam Basin in South Korea" Water 13, no. 20: 2820. https://doi.org/10.3390/w13202820
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