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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #319558
Title: Scaling an in situ network for high resolution modeling during SMAPVEX15

Author
item Coopersmith, Evan
item Cosh, Michael
item JACOBS, J. - University Of New Hampshire
item Jackson, Thomas
item Crow, Wade
item Holifield Collins, Chandra
item Goodrich, David - Dave
item COLLIANDER, ANDREAS - Jet Propulsion Laboratory

Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: 8/5/2015
Publication Date: 10/1/2015
Citation: Coopersmith, E., Cosh, M.H., Jacobs, J., Jackson, T.J., Crow, W.T., Holifield-Collins, C., Goodrich, D.C., Colliander, A. 2016. Scaling an in situ network for high resolution modeling during SMAPVEX15. American Geophysical Union Fall Meeting, December 14-18, 2015, San Francisco, CA. Abstract # H51I-1506.

Interpretive Summary:

Technical Abstract: Among the greatest challenges within the field of soil moisture estimation is that of scaling sparse point measurements within a network to produce higher resolution map products. Large-scale field experiments present an ideal opportunity to develop methodologies for this scaling, by coupling in situ networks, temporary networks, and aerial mapping of soil moisture. During the Soil Moisture Active Passive Validation Experiments in 2015 (SMAPVEX15) in and around the USDA-ARS Walnut Gulch Experimental Watershed and LTAR site in southeastern Arizona, USA, a high density network of soil moisture stations was deployed across a sparse, permanent in situ network in coordination with intensive soil moisture sampling and an aircraft campaign. This watershed is also densely instrumented with precipitation gages (one gauge/0.57 km2) to monitor the North American Monsoon System, which dominates the hydrologic cycle during the summer months in this region. Using the precipitation and soil moisture time series values provided, a physically-based model is calibrated that will provide estimates at the 3km, 9km, and 36km scales. The results from this model will be compared with the point-scale gravimetric samples, aircraft-based sensor, and the satellite-based products retrieved from NASA’s Soil Moisture Active Passive mission.