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Using InSAR to study aquifer properties in the Los Angeles Basin

Using InSAR to study aquifer properties in the Los Angeles Basin. Piyush Agram Mark Simons. Synthetic Aperture Radar (SAR). Satellite or airplane based active imaging system. Typical satellite system. 100 km x 100 km at a resolution of 25m. O rbit repeat time of 1 month.

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Using InSAR to study aquifer properties in the Los Angeles Basin

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  1. Using InSAR to study aquifer properties in the Los Angeles Basin PiyushAgram Mark Simons

  2. Synthetic Aperture Radar (SAR) • Satellite or airplane based active imaging system. • Typical satellite system. • 100 km x 100 km at a resolution of 25m. • Orbit repeat time of 1 month. • Can image through clouds and without sunlight.

  3. SAR Image characteristics • SAR Image • Monochromatic • Amplitude and phase information • Optical Image • Multi-chromatic • Amplitude information only

  4. Interferometric SAR Phase change can be related to deformation

  5. Large deformation events Fialko et al. (2001), Hector Mine EQ • Deformation typically much larger than noise sources • Atmospheric contributions - few mm to few cm • Orbital errors introduce long wavelength features

  6. For sensitive measurements • Time-series InSAR • Combine multiple observations • Atmospheric signal is uncorrelated over time • Orbital errors are random in time IFG span T0 T1 T2 T3 … Tn

  7. Example: ALOS stacks over SAF

  8. Data set over Los Angeles • 18 years of SAR data • European Remote-Sensing Satellite (ERS) • 105 SAR images combined into 523 interferograms • Aug 1992 to Mar 2007 • Environmental satellite (Envisat) • 60 SAR images combined into 358 interferograms • Sep 2003 to Sep 2010 • Almost monthly observations

  9. Average LOS velocity Pomona, CA Ground water pumping Santa Fe Springs, CA Oil wells San Jacinto Fault, Tectonic signal

  10. Decoupling the seasonal signal Long term deformation Observed deformation time-series Seasonal signal • 18 years of data allows us to decouple the seasonal signal • Monthly data increases the reliability of our seasonal estimates • We estimate the average seasonal cycle over 18 years

  11. Seasonal Amplitude Watson et al., (2002) InSAR time-series SOPAC GPS

  12. Seasonal phase Reference Sharp phase boundaries • Barriers are clearly identified. • Lines up with known faults.

  13. Phase delay in detail Phase in days and * marks maximum seasonal amplitude location • Time lag in days with greater detail • Within aquifer, phase can vary by as much as 15-20 days

  14. Relating to hydraulic head • Use equations from Jess’ thesis • Derive seasonal amplitude bounds she did in her thesis? • How can we better use the time-delay/ phase information? • What other properties would audience be interested in ?

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