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Open AccessArticle

Outlier Detection and Smoothing Process for Water Level Data Measured by Ultrasonic Sensor in Stream Flows

by Inhyeok Bae 1 and Un Ji 1,2,*
1
Smart City and Construction Engineering, Korea University of Science and Technology, Goyang-Si 10223, Korea
2
Department of Land, Water and Environment Research, Korea Institute of Civil Engineering and Building Technology, Goyang-Si 10223, Korea
*
Author to whom correspondence should be addressed.
Water 2019, 11(5), 951; https://doi.org/10.3390/w11050951
Received: 8 March 2019 / Revised: 3 May 2019 / Accepted: 3 May 2019 / Published: 7 May 2019
(This article belongs to the Section Hydraulics)
Water level data sets acquired by ultrasonic sensors in stream-scale channels exhibit relatively large numbers of outliers that are off the measurement range between the ultrasonic sensor and water surface, as well as data dispersion of approximately 2 cm due to random errors such as water waves. Therefore, this study develops a data processing algorithm for outlier removal and smoothing for water level data measured by ultrasonic sensors to consider these characteristics. The outlier removal process includes an initial cutoff process to remove outliers out of the measurement range and an outlier detection process using modified Z-scores based on the median absolute deviation (MAD) of a robust estimator. In addition, an exponentially weighted moving average (EWMA) method is applied to smooth the processed data. Sensitivity analyses are performed for factors that are subjectively set by the user, including the window size for the MAD outlier detection stage, the rejection criterion for the modified Z-score outlier removal stage, and the smoothing constant for the EWMA smoothing stage, based on four different water level data sets acquired by ultrasonic sensors in stream-scale experiments. View Full-Text
Keywords: data smoothing; exponentially weighted moving average; median absolute deviation; modified Z-scores; outlier detection; ultrasonic sensor; water level monitoring data smoothing; exponentially weighted moving average; median absolute deviation; modified Z-scores; outlier detection; ultrasonic sensor; water level monitoring
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Bae, I.; Ji, U. Outlier Detection and Smoothing Process for Water Level Data Measured by Ultrasonic Sensor in Stream Flows. Water 2019, 11, 951.

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