INFERRING SNOW WETNESS USING C-BAND DATA FROM SIR-CS POLARIMETRIC SYNTHETIC-APERTURE RADAR

In hydrological investigations, modeling and forecasting of snow melt runoff require timely information about spatial variability of snow pr operties, among them the liquid water content-snow wetness-in the top layer of a snow pack, Our polarimetric model shows that scattering mec hanisms control the relationship between snow wetness and the copolari zation signals in data from a multi-parameter synthetic aperture radar , Along with snow wetness, the surface roughness and local incidence a ngle also affect the copolarization signals, making them either larger or smaller depending on the snow parameters, surface roughness, and i ncidence angle, We base our algorithm for retrieving snow wetness from SIR-C/X-SAR on a first-order scattering model that includes both surf ace and volume scattering, It is applicable for incidence angles from 25 degrees-70 degrees and for surface roughness with rms height less t han or equal to 7 mm and correlation length less than or equal to 25 c m. Comparison with ground measurements showed that the absolute error in snow wetness inferred from the imagery was within 2.5% at 95% confi dence interval, Typically the free liquid water content of snow ranges from O% to 15% by volume, We conclude that a C-hand polarimetric SAR can provide useful estimates of the wetness of the top layers of seaso nal snow packs.