Integrated Quality Control Process for Hydrological Database: A Case Study of Daecheong Dam Basin in South Korea

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...

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Bibliographic Details
Published in:Water (Basel) 2021-10, Vol.13 (20), p.2820
Main Authors: Jeong, Gimoon, Yoo, Do-Guen, Kim, Tae-Woong, Lee, Jin-Young, Noh, Joon-Woo, Kang, Doosun
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Automation
Case studies
Dams
Data processing
Decision making
Hydrologic data
Hydrology
Linear programming
Machine learning
Methods
Precipitation
Quality control
Reading
Water levels
Water resources
Water resources management
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Summary: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.
ISSN:2073-4441
2073-4441
DOI:10.3390/w13202820