Predictability of hydraulic head changes and characterization of aquifer-system and fault properties from InSAR-derived ground deformation

Chaussard, E., R. Burgmann, M. Shirzaei, E.J. Fielding, and B. Baker (2014), Predictability of hydraulic head changes and characterization of aquifer-system and fault properties from InSAR-derived ground deformation, J. Geophys. Res., 119, doi:10.1002/2014JB011266.
Abstract

We evaluate the benefits of space-derived ground deformation measurements for basin-wide characterization of aquifer-system properties and groundwater levels. We use Interferometric Synthetic Aperture Radar (InSAR) time series analysis of ERS, Envisat, and ALOS SAR data to resolve 1992–2011 ground deformation in the Santa Clara Valley, California. T-mode principal component analysis successfully isolates temporally variable deformation patterns embedded in the multidecadal time series. The data reveal uplift at 0.4 cm/yr between 1992 and 2000 and < 0.1 cm/yr during 2000–2011, illustrating the end of the aquifer-system’s poroelastic rebound following recovery of hydraulic heads after the 1960s low stand. In addition, seasonal elastic deformation with amplitude of up to 3 cm, in phase with head fluctuations, is observed over the confined aquifer sharply partitioned by the Quaternary Silver Creek Fault (SCF). Integration of this deformation with hydraulic head data enables characterization of the aquifer-system storativity and elastic skeletal specific storage. Modeling of the deformation partitioning across the SCF constrains the fault’s last tectonic activity, hydraulic conductivity, and material composition. The SCF likely cuts the shallow confining clays and was last active since ~140 ka, it has a horizontal hydraulic conductivity several orders of magnitude lower than the surrounding aquifer-system, and is likely composed of clays, making it an effective barrier to across-fault fluid flow. Finally, we show that after a period of calibration, InSAR can be used to characterize basin-wide water level changes without well measurements with an accuracy of 70%, which demonstrates that it provides useful data for groundwater management.

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