The Soil Moisture Active Passive Marena, Oklahoma, In Situ Sensor Testbed (SMAP-MOISST): Testbed Design and Evaluation of In Situ Sensors
|Authors:||Cosh, M. H.|
|Resource type:||Composite Resource|
|Storage:||The size of this resource is 0 bytes|
|Created:||Mar 31, 2018 at 8:28 p.m.|
|Last updated:||Apr 09, 2018 at 8:35 p.m. by CTEMPs OSU-UNR|
|Citation:||See how to cite this resource|
In situ soil moisture monitoring networks are critical to the development of soil moisture remote sensing missions as well as agricultural and environmental management, weather forecasting, and many other endeavors. These in situ networks utilize a variety of sensors and installation practices, which confounds the development of a unified reference database for satellite calibration and validation programs. As part of the Soil Moisture Active Passive Mission, the Marena, Oklahoma, In Situ Sensor Testbed (SMAP-MOISST) was initiated to perform inter-comparisons and study sensor limitations. Soil moisture sensors that are deployed in major monitoring networks were included in the study, along with new and emerging technologies, such as the Cosmic Ray Soil Moisture Observing System (COSMOS), passive/active distributed temperature sensing (DTS), and global positioning system reflectometers (GPSR). Four profile stations were installed in May of 2010, and soil moisture was monitored to a depth of 1 m on an hourly basis. The four stations were distributed within a circular domain of approximately 600 m diameter, adequate to encompass the sensing range of COSMOS. The sensors included in the base station configuration included the Stevens Water Hydra Probe, Campbell Scientific 616 and 229, Decagon EC-TM, Delta-T Theta Probe, Acclima, and Sentek EnviroSMART capacitance system. In addition, the Pico TRIME system and additional time-domain reflectometry (TDR) systems were deployed when available. It was necessary to apply site-specific calibration to most sensors to reach an RMSE below 0.04 m3 m−3. For most sensor types, a single near surface sensor could be scaled to represent the areal-average of a field domain by simple linear regression, resulting in RMSE values around 0.03 m3 m−3.
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