Wavelet analysis of land subsidence time-series: Madrid Tertiary aquifer case study
Roberto Tomás, José Luis Pastor, Marta Béjar‐Pizarro, Roberta Bonì, Pablo Ezquerro, J. A. Fernández Merodo, Carolina Guardiola‐Albert, Gerardo Herrera, Claudia Meisina, Pietro Teatini, Francesco Zucca, Claudia Zoccarato, Andrea Franceschini
Abstract
Abstract. Interpretation of land subsidence time-series to understand the evolution of the phenomenon and the existing relationships between triggers and measured displacements is a great challenge. Continuous wavelet transform (CWT) is a powerful signal processing method mainly suitable for the analysis of individual nonstationary time-series. CWT expands time-series into the time-frequency space allowing identification of localized nonstationary periodicities. Complementarily, Cross Wavelet Transform (XWT) and Wavelet Coherence (WTC) methods allow the comparison of two time-series that may be expected to be related in order to identify regions in the time-frequency domain that exhibit large common cross-power and wavelet coherence, respectively, and therefore are evocative of causality. In this work we use CWT, XWT and WTC to analyze piezometric and InSAR (interferometric synthetic aperture radar) time-series from the Tertiary aquifer of Madrid (Spain) to illustrate their capabilities for interpreting land subsidence and piezometric time-series information.