Preprints
https://doi.org/10.5194/nhess-2021-212
https://doi.org/10.5194/nhess-2021-212

  24 Aug 2021

24 Aug 2021

Review status: this preprint is currently under review for the journal NHESS.

Evaluation of filtering methods for use on high frequency measurements of landslide displacements

Sohrab Sharifi1, Michael Hendry1, Renato Macciotta1, and Trevor Evans2 Sohrab Sharifi et al.
  • 1Department of Civil and Environmental Engineering, University of Alberta, Edmonton, AB, Canada
  • 2Canadian National Railway, Kamloops, British Columbia, Canada

Abstract. Displacement monitoring is a critical control for risks associated with potentially sudden slope failures. Instrument measurements are, however, obscured by the presence of scatter. Data filtering methods aim to reduce the scatter and therefore enhance the performance of early warning systems (EWSs). The effectiveness of EWSs depends on the lag time between the onset of acceleration and its detection by the monitoring system, such that a timely warning is issued for implementation of consequence mitigation strategies. This paper evaluates the performance of three filtering methods (simple moving average, Gaussian-weighted moving average, and Savitzky-Golay), and considers their comparative advantages and disadvantages. The evaluation utilized six levels of randomly generated scatter on synthetic data as well as high-frequency global navigation satellite system (GNSS) displacement measurements at the Ten-mile landslide in British Columbia, Canada. The simple moving average method exhibited significant disadvantages compared to the Gaussian-weighted moving average and Savitzky-Golay approaches. A framework is presented that can be followed to evaluate the adequacy of different algorithms for minimizing monitoring data scatter.

Sohrab Sharifi et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-212', Ugur Öztürk, 11 Oct 2021
  • RC2: 'Comment on nhess-2021-212', Anonymous Referee #2, 02 Dec 2021

Sohrab Sharifi et al.

Sohrab Sharifi et al.

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Short summary
This study is devoted to comparing the effectiveness of three different filters for noise reduction of instruments. It was observed that the Savitzky-Golay and Gaussian-weighted moving average filters outperform the simple moving average. Application of these two filters in real-time landslide monitoring leads to timely detection of acceleration moment and better preservation of information regarding displacement and velocity.
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