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Title: Retrieval of an available water-based soil moisture proxy from thermal infrared remote sensing. Part I: Methodology and validation

Author
item HAIN, C - UNIVERSITY OF ALABAMA
item MECIKALSKI, J - UNIVERSITY OF ALABAMA
item Anderson, Martha

Submitted to: Journal of Hydrometeorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/10/2009
Publication Date: 6/15/2009
Citation: Hain, C.R., Mecikalski, J.R., Anderson, M.C. 2009. Retrieval of an available water-based soil moisture proxy from thermal infrared remote sensing. Part I: Methodology and validation. Journal of Hydrometeorology. 10:665-683.

Interpretive Summary: The ability to routinely map soil moisture conditions from space will be of great benefit to agriculture, in managing irrigation, detecting drought or root-zone saturation, and in predicting yield. To date, most of the emphasis in spaceborne soil moisture retrievals has been placed on techniques using passive microwave emission from the land-surface. Microwave techniques have proven quite effective at accurately reproducing in situ measurements of soil moisture and can operate under both clear and cloudy conditions, but there are limitations to these approaches. They tend to have limited sensitivity in areas of high vegetation cover, and the spatial resolution of microwave soil moisture products tends to be very coarse (10s of kilometers) – unable to resolve soil moisture from individual agricultural fields. In this paper, we present a technique for mapping soil moisture using thermal infrared (TIR) band imagery. TIR retrievals are very complementary to the standard microwave products, providing sensitivity under dense vegetation and much higher spatial resolution (down to 10s of meters). TIR retrievals are, however, cannot be applied to areas under cloud cover. Here, a TIR-based soil moisture retrieval technique is validated in comparison with observations collected with the Oklahoma Mesonet over a sequence of several dates spanning the growing season. Retrieval accuracy is comparable to that obtained with microwave techniques. Ultimately development of a technique integrating microwave and TIR-based moisture information will be beneficial for creating a robust soil moisture product with both high temporal and high spatial resolution.

Technical Abstract: A retrieval of soil moisture is proposed using surface flux estimates from satellite-based thermal infrared (TIR) imagery and the Atmosphere-Land-Exchange-Inversion (ALEXI) model. The ability of ALEXI to provide valuable information about the partitioning of the surface energy budget, which can be largely dictated by soil moisture conditions, accommodates the retrieval of an average soil moisture value from the surface to the rooting depth of the active vegetation. For this method, the fraction of actual to potential evapotranspiration (fPET) is computed from an ALEXI estimate of latent heat flux (LE) and potential evapotranspiration (PET). The ALEXI-estimated fPET can be related to a fraction of available water (fAW) in the soil profile. Four unique fPET to fAW relationships are proposed and validated against Oklahoma Mesonet soil moisture observations within a series of composite periods during the warm seasons of 2002-2004. Based on the validation results, the most representative of the four relationships is chosen and is shown to produce reasonable (mean absolute errors values less than 20% with respect to fAW) soil moisture estimates when compared to OK Mesonet observations. Quantitative comparisons between ALEXI and modeled soil moisture estimates from the Eta Data Assimilation System (EDAS) are also performed to assess the possible advantages of using ALEXI soil moisture estimates within numerical weather predication (NWP) simulations. This TIR retrieval technique is advantageous over microwave techniques because of the ability to sense soil moisture which extends into the root-zone layer. Soil moisture conditions can also be retrieved over dense vegetation cover and is available on spatial resolutions on the order of the native TIR imagery. A notable disadvantage is the inability to retrieve soil moisture conditions through cloud cover.