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Title: Conclusions from the SMAP Marena Oklahoma in situ soil moisture testbed (SMAP-MOISST)

item Cosh, Michael
item OCHSNER, TYSON - Oklahoma State University
item BASARA - University Of Oklahoma
item Evett, Steven - Steve
item SMALL, ERIC - University Of Colorado
item SELKER, J. - Oregon State University
item STEELE-DUNNE, SUSAN - Delft University
item ZREDA, MAREK - University Of Arizona

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 4/1/2014
Publication Date: 6/9/2014
Citation: Cosh, M.H., Ochsner, T., Basara, Evett, S.R., Small, E., Selker, J., Steele-Dunne, S., Zreda, M. 2014. Conclusions from the SMAP Marena Oklahoma in situ soil moisture testbed (SMAP-MOISST)[abstract]. 21st Conference on Applied Climatology, J2.1, Available:

Interpretive Summary:

Technical Abstract: The scientific data record for soil moisture is just developing. The earliest methods of record are physical collection of gravimetric samples. Soon thereafter, in situ networks of automated measurements allowed the data record to increase exponentially. However, the diversity of in situ soil moisture network protocols and instrumentation created a dilemma for integrated these networks into a single unified data record. This led to the development of a testbed for comparing in situ soil moisture sensors. Initiated by NASA and its Soil Moisture Active Passive mission, a testbed was developed in Marena, Oklahoma on the Oklahoma State University Range Research Station. The testbed consists of four base stations. Each station contains different soil moisture sensors installed in profiles to compare their performance. Multiple stations enabled replication of the measurements, while also support the investigation of larger spatial distributions of soil moisture. These stations have been operating since their installation in 2010, providing data with one hour resolution. These include stations from the COSMOS network, GPS Reflectometry Network, Climate Reference Network, and active and passive Distributed Temperature Systems. Early results of this testbed include calibration and scaling analysis as well as performance of the sensors during freeze-thaw cycles. Most sensors are able to perform with an error less than 0.04 m3/m3, when compared to a gravimetric sample, but site specific calibration is necessary for most of the sensors. In addition, analysis of time series of soil moisture revealed that the temporal characteristics of sensors are not always linear. When compiling a unified dataset, some standard must be established versus ground truth, and a baseline sensor methodology will likely be required to establish continuity within the data record.