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Title: MODELING THE SPATIAL AND TEMPORAL DISTRIBUTION OF SOIL WATER CONTENT AT WATERSHED SCALES USING REMOTE SENSING AND GIS

Author
item Starks, Patrick
item Ross, John
item Heathman, Gary

Submitted to: American Society for Testing and Materials
Publication Type: Abstract Only
Publication Acceptance Date: 1/25/2001
Publication Date: 1/25/2001
Citation: N/A

Interpretive Summary:

Technical Abstract: Recentremotesensingexperimentshavedemonstratedthatpassivemicrowave radiometers can provide reasonable estimates of surface (0-5 cm) soil water content over large areas. However, these point-in-time, remotely sensed, surface soil water content estimates need to be linked to the root zone to be generally useful to water resource managers and researchers in the agricultural, hydrological, and meteorological sciences. The objective of this study is to examine the feasibility of estimating root zone soil water content at watershed scales, and it's spatial and temporal variability, by combining in-situ field data, remotely sensed data, GIS and modeling techniques. A one-dimensional, two-layer soil water budget model was selected for this study. At the point scale surface estimate of soil water content compared well to measured data. The two-layer model was then modified to accommodate spatial data obtained with remote sensing instrumentation and soils, vegetation, and meteorological data for the Little Washita River Experimental Watershed (LWREW). Estimates of surface soil water content from the spatial model were within about 0.05 cubic meter/cubic meter of measurements at the ground-truthing sites. Surface soil moisture estimates were averaged over the LWREW and were within about 0.06 cubic meter/cubic meter of that estimated directly from the remotely sensed data. At the point scale, modeled root zone estimates of soil water contentwerewithinabout0.02cubicmeter/cubicmeterofmeasuredvalues. Correlationcoefficientswere>0.76at3ofthe4studysiteswhenroot zone soil water content estimates from the point and spatial models were compared. However, the spatial model generally underestimated the soil moisture estimates from the point model.