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Satellite-derived soil moisture provides more spatially and temporallyextensive data than in situ observations. However, satellites can only measurewater in the top few centimeters of the soil. Root zone soil moisture ismore important, particularly in vegetated regions. Therefore estimates ofroot zone soil moisture must be inferred from near-surface soil moistureretrievals. The accuracy of this inference is contingent on the relationshipbetween soil moisture in the near-surface and the soil moisture at greaterdepths. This study uses cross correlation analysis to quantify theassociation between near-surface and root zone soil moisture using in situ datafrom the United States Great Plains. Our analysis demonstrates that there isgenerally a strong relationship between near-surface (5–10 cm) and rootzone (25–60 cm) soil moisture. An exponential decay filter is used toestimate root zone soil moisture using near-surface soil moisture derivedfrom the Soil Moisture and Ocean Salinity (SMOS) satellite. Root zone soilmoisture derived from SMOS surface retrievals is compared to in situ soil moistureobservations in the United States Great Plains. The SMOS-based root zonesoil moisture had a mean R2 of 0.57 and a mean Nash–Sutcliffe score of0.61 based on 33 stations in Oklahoma. In Nebraska, the SMOS-based root zonesoil moisture had a mean R2 of 0.24 and a mean Nash–Sutcliffe score of0.22 based on 22 stations. Although the performance of the exponentialfilter method varies over space and time, we conclude that it is a usefulapproach for estimating root zone soil moisture from SMOS surfaceretrievals

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