Time‐dependent volcano source monitoring using interferometric synthetic aperture radar time series: A combined genetic algorithm and Kalman filter approach

Abstract

Modern geodetic methods allow continuous monitoring of deformation fields of volcanoes. The acquired data contribute significantly to the study of the dynamics of magmatic sources prior to, during and after eruptions and intrusions. In addition to advancing the monitoring techniques, it is important to develop suitable approaches to deal with deformation time series. Here, we present, test and apply a new approach for time‐dependent, nonlinear inversion using a combination of a genetic algorithm (GA) and a Kalman filter (KF). The GA is used in the form presented by Shirzaei and Walter (2009), and the KF implementation now allows for the treatment of monitoring data as a full time series rather than as single time steps. This approach provides a flexible tool for assessing unevenly sampled and heterogeneous time series data and explains the deformation field using time‐consistent dislocation sources. Following synthetic tests, we demonstrate the merits of time‐consistent source modeling for interferometric synthetic aperture radar (InSAR) data available between 1992 and 2008 from the Campi Flegrei volcano in Italy. We obtained multiple episodes of linear velocity for the reservoir pressure change associated with a parabolic surface deformation on the volcano. These data may be interpreted via differential equations as a linear flux to the shallow reservoir that provides new insight into how both the shallow and deep reservoirs communicate beneath Campi Flegrei. The synthetic test and case study demonstrate the robustness of our approach and the ability to track and monitor the source of systems with complex dynamics. It is applicable to time‐dependent optimization problems in volcanic and tectonic environments in other tectonic environments in other areas and allows understanding of the spatiotemporal extent of a physical process in quantitative manner.