Estimating root zone soil moisture using near-surface observations from SMOS

Satellite-derived soil moisture provides more spatially and temporally extensive data than in situ observations. However, satellites can only measure water in the top few centimeters of the soil. Therefore estimates of root zone soil moisture must be inferred from near-surface soil moisture retrievals. The accuracy of this inference is contingent on the relationship between soil moisture in the near-surface and at greater depths. This study uses cross correlation analysis to quantify the association between near-surface and root zone soil moisture using in situ data from the United States Great Plains. Our analysis demonstrates that there is generally a strong relationship between near-surface (5 to 10 cm) and root zone (25 to 60 cm) soil moisture. An exponential decay filter is applied to estimate root zone soil moisture from near-surface observations. Reasonably skillful predictions of root zone soil moisture can be made using near-surface observations. The same method is then applied to evaluate whether soil moisture derived from the Soil Moisture and Ocean Salinity (SMOS) satellite can be used to accurately estimate root zone soil moisture. We conclude that the exponential filter method is a useful approach for accurately predicting root zone soil moisture from SMOS surface retrievals.