Date of Award:
12-2025
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Civil and Environmental Engineering
Committee Chair(s)
Jeffery S. Horsburgh
Committee
Jeffery S. Horsburgh
Committee
Belize Lane
Committee
Hamid Karimi
Abstract
Advances in water monitoring technologies have led to a large increase in the amount of data collected from rivers, lakes, and other water systems. However, ensuring that these data are accurate and reliable remains a major challenge. Traditional data quality checks are done manually by a technician, which can be slow, inconsistent, and not practical for real-time monitoring. This research addresses these challenges by developing standardized datasets for testing computer-based methods that automatically detect and correct errors in water data. Using information from the Logan River Observatory in northern Utah, we created a step-by-step process to identify, categorize, and label errors in sensor data. This process uses computer programming to make the work faster, more consistent, and easy to repeat. The standardized datasets developed through this work will help scientists compare different automated quality control methods under a variety of water conditions. Ultimately, this will improve the accuracy and reliability of water data, leading to better water management decisions and greater public confidence in water information systems.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Kahrizi, Ehsan, "Developing Standardized Testing Datasets for Benchmarking Automated Quality Control Algorithm Performance With Aquatic Sensor Data" (2025). All Graduate Theses and Dissertations, Fall 2023 to Present. 674.
https://digitalcommons.usu.edu/etd2023/674
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