Land surface subsidence due to excessive groundwater pumping is an increasing concern in California, USA. Interferometric Synthetic Aperture Radar (InSAR) is a remote sensing technique for measuring centimeter-to-millimeter surface deformation at 10-100 m spatial resolution. Here, a data-driven approach that attributes deformation to individual depth intervals within an aquifer system by integrating head data acquired from each of three screened intervals in a monitoring well with InSAR surface deformation measurements was developed. The study area was the Colusa Basin in northern Central Valley. To reconstruct the surface deformation history over the study area, 13 ALOS-PALSAR scenes acquired between 2006 and 2010 were processed. Up to ~3-cm year-1 long-term subsidence and up to ~6 cm seasonal subsidence were observed using the InSAR technique. The technique developed in this paper integrates the InSAR-observed seasonal deformation rate and the co-located head measurements in multiple depth intervals to estimate the elastic skeletal storage coefficient, the time delay between the head change and the observed deformation, and subsequently the deformation of each depth interval. This technique can be implemented when hydraulic head measurements within each depth interval are not correlated with each other. Using this approach, the depth interval that contributed the most to the total subsidence, as well as storage parameters for all intervals, are estimated. The technique can be used for identification of the depth interval within the aquifer system responsible for deformation.
R. G. Smith et al., "Apportioning Deformation among Depth Intervals in an Aquifer System using InSAR and Head Data," Hydrogeology Journal, vol. 29, no. 7, pp. 2475 - 2486, Springer, Nov 2021.
The definitive version is available at https://doi.org/10.1007/s10040-021-02386-0
Geosciences and Geological and Petroleum Engineering
Keywords and Phrases
Alluvial aquifers; Groundwater level; InSAR; Subsidence; USA
International Standard Serial Number (ISSN)
Article - Journal
© 2021 The Authors, All rights reserved.
01 Nov 2021