Effects of Near-Surface Soil Moisture on GPS SNR Data: Development of a Retrieval Algorithm for Soil Moisture

Global Positioning System (GPS) multipath signals can be used to infer volumetric soil moisture around a GPS antenna. While most GPS users concentrate on the signal that travels directly from the satellite to the antenna, the signal that is reflected by nearby surfaces contains information about the environment surrounding the antenna. The interference between the direct and reflected signals produces a modulation that can be observed in temporal variations of the signal-to-noise ratio (SNR) data recorded by the GPS receiver. Changes in the dielectric constant of the soil, which are associated with fluctuations in soil moisture, affect the effective reflector height, amplitude, and phase of the multipath modulation. Empirical studies have shown that these changes in SNR data are correlated with near-surface volumetric soil moisture. This study uses an electrodynamic single-scattering forward model to test the empirical relationships observed in field data. All three GPS interferogram metrics (effective reflector height, phase, and amplitude) are affected by soil moisture in the top 5 cm of the soil; surface soil moisture (
$< 1\hbox{-}\hbox{cm}$
depth) exerts the strongest control. Soil type exerts a negligible impact on the relationships between GPS interferogram metrics and soil moisture. Phase is linearly correlated with surface soil moisture. The slope of the relationship is similar to that observed in field data. Amplitude and effective reflector height are also affected by soil moisture, although the relationship is nonlinear. Phase is the best metric derived from GPS data to use as a proxy for soil moisture variations.