High-precision GPS receivers can be used to estimate fluctuations in near surface soil moisture and vegetation water content.  This approach, referred to as GPS-Interferometric Reflectometry (GPS-IR), relates precise changes in the geometry of reflected GPS signals to observe soil moisture while simultaneously using signal attenuation and diffuse scattering to infer changes in vegetative state.  Standard GPS antenna configurations, for example that used in NSF's Plate Boundary Observatory network, yield sensing footprints of ~1000 m².  Previous remote sensing research has shown that microwave signals (e.g., L-band) are optimal for measuring hydrologic variables, such as soil moisture.  GPS satellites transmit similar signals and therefore are useful for sensing water in the environment.  Given this sensitivity, hundreds of GPS receivers that exist in the U.S. could be used to provide near-real time estimates of soil moisture and vegetation water content for satellite validation, drought monitoring and related studies.  

A significant obstacle to using L-band (or similar) signals for remote sensing of soil moisture is removing the effects of vegetation.  This same challenge exists when using GPS-IR data.  We have established nine research sites with identical GPS and hydrologic infrastructure to study this problem.  These sites span a wide range of soil, vegetation, and climate types.  In addition to daily GPS and hourly soil moisture data, we have collected weekly vegetation water content samples at all sites.  Our data demonstrate that soil moisture fluctuations can be estimated from GPS-IR records when vegetation water content is < 2 kg m^-2.  We outline different approaches for separating the soil moisture and vegetation signals and quantifying errors in our retrieval algorithm.