Water distribution in the top 1 m of the earth's surface soil layer often controls the success of agricultural crops. In this near-surface zone, large spatial and temporal variations in soil water content are associated with soil heterogeneities, topography, land cover, evapotranspiration, and precipitation. Conventional techniques of measuring soil water content for agricultural purposes—e.g., time domain reflectometry (TDR), neutron probe, or gravimetric techniques, are intrusive and provide information at a point scale only, which is often inadequate for capturing the variations in soil water content with sufficient resolution. Both passive and active remote sensing methods have also been investigated as a tool to provide soil water content in the top 0–5 cm of the subsurface over large spatial areas and in a rapid manner. However, it is still a challenge to obtain information about soil water content from remote sensing data in the presence of a mature crop cover. At the spatial and temporal scales necessary to describe dynamic shallow soil environments, reliance on only sparse, high-resolution point measurements or on remote sensing proxy information could generate large uncertainties regarding near-surface soil water content distribution and flux.
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Hubbard et al. (2002) studied this question.
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