A methodology for the analysis of continuous time-series of automatic inclinometers for slow-moving landslides monitoring in Piemonte region, northern Italy

Massimiliano Bordoni (), Valerio Vivaldi, Roberta Bonì, Simone Spanò, Mauro Tararbra, Luca Lanteri, Matteo Parnigoni, Alessandra Grossi, Silvia Figini and Claudia Meisina
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Massimiliano Bordoni: University of Pavia
Valerio Vivaldi: University of Pavia
Roberta Bonì: University of Urbino “Carlo Bo”
Simone Spanò: University of Pavia
Mauro Tararbra: ARPA Piemonte - Agenzia Regionale Per La Protezione Ambientale
Luca Lanteri: ARPA Piemonte - Agenzia Regionale Per La Protezione Ambientale
Matteo Parnigoni: RIDS - RES Institute for Data Science
Alessandra Grossi: RIDS - RES Institute for Data Science
Silvia Figini: University of Pavia
Claudia Meisina: University of Pavia

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 115, issue 2, No 6, 1115-1142

Abstract: Abstract In-place automatic inclinometers are typical devices used to monitor displacements of extremely slow to slow-moving landslides. The significance of these measurements requires methodologies able to distinguish real measures from anomalous ones, to quantify significant moments of acceleration in deformation trends and to determine the main factors that influence the kinematic behavior measured by an automatic inclinometer. This work aimed at developing a novel method, which allows to cover all the steps of analysis of data acquired by automatic inclinometers. The methodology is composed by five steps: (I) evaluation of the reliability of the instruments; (II) identification and elimination of anomalous measures from displacement time-series; (III) recognition of significant moments of acceleration in the rate of displacement, through thresholds based on the mean rate of displacement and on the cumulated amount of the deformation; (IV) clustering of the events of significant acceleration, to characterize different typologies of events according to different landslides kinematic behaviors; (V) identification of the main meteorological and groundwater parameters influencing the deformation pattern measured by an automatic inclinometer. The methodology was developed and tested using displacement time-series of 89 automatic inclinometers, belonging to the regional monitoring network of Piemonte region (northern Italy), managed by Arpa Piemonte. Two representative inclinometric time-series were selected to validate all the steps of the methodology for different types of monitored slow-moving landslides. The developed method is reliable in the estimation of anomalous measures and in the identification of significant accelerations, helping in the comprehension of the response of displacement trends during activity phases. Moreover, it is able to identify the factors which influence more the deformation pattern measured in correspondence of an automatic inclinometer.

Keywords: Slow-moving landslides; In-place automatic inclinometers; Displacement time-series; Acceleration; Thresholds (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-022-05586-3

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