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ARS Home » Midwest Area » West Lafayette, Indiana » National Soil Erosion Research » Research » Publications at this Location » Publication #251966

Title: Spatio-Temporal Analysis of Surface Soil Moisture in Evaluating Ground Truth Monitoring Sites for Remotely Sensed Observations

item Heathman, Gary
item Cosh, Michael
item HAN, EUNJIN - Purdue University
item Jackson, Thomas
item McKee, Lynn
item McAfee, Scott

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 3/27/2010
Publication Date: 10/11/2010
Citation: Heathman, G.C., Cosh, M.H., Han, E., Jackson, T.J., Mckee, L.G., Mcafee, S.J. 2010. Spatio-Temporal Analysis of Surface Soil Moisture in Evaluating Ground Truth Monitoring Sites for Remotely Sensed Observations [abstract]. Hydrology Conference, 2010. October 11-13, 2010, San Diego, CA. CD ROM.

Interpretive Summary:

Technical Abstract: Soil moisture is an intrinsic state variable that varies considerably in space and time. Although soil moisture is highly variable, repeated measurements of soil moisture at the field or small watershed scale can often reveal certain locations as being temporally stable and representative of the area average. Temporal stability can be used in describing the persistence of spatial patterns and characteristic behavior of soil moisture. This study is aimed at determining the adequacy of long term, point-scale surface soil moisture measurements in representing local field averages that serve as in situ locations for the calibration and validation of remotely sensed soil moisture. Experimental data were obtained by frequency-domain reflectometry (FDR) sensors permanently installed in two agricultural fields (2.23 and 2.71 ha) at depths of 5, 20, 45, and 60 cm. Twenty additional FDR sensors, on a 35 m grid, were installed at a depth of 5cm in each field with automated data collection transmitted every 30 min from July 15 through September 20, 2009. The FDR sensors revealed persistent patterns in surface soil moisture, as well as drainage, within each field and identified sites that were temporally stable. The locations that were optimal for estimating the area-average water contents were different from the permanent sensor locations in both fields. However, the permanent sensor locations showed approximately 10% mean relative difference for each field. Thus, minimum offset values can be applied to the permanent sensor data to obtain long term, in situ field average values of surface soil moisture. The in situ results are of relevance for interpreting and downscaling coarser resolution soil moisture data such as that retrieved from active and passive microwave platforms. Alternative protocols for large-scale in situ soil moisture campaigns involved with the calibration and validation of satellite based soil moisture observations are also discussed.