Soil moisture monitoring with long term in situ sensors: Lessons from MOISST.
Abstract
In situ networks to monitor soil moisture regularly select a sensor based upon economics, soil characteristics, and landscape features. But as networks endure years of deployment, sensors fail and new sensors are sought. Therefore it is necessary to determine the impact of replacing existing sensors with new and alternate sensors. In 2010, a long term soil moisture sensor testbed was installed near Stillwater, OK. The Marena Oklahoma In Situ Sensor Testbed (MOISST) is an ideal location for long term sensor inter-comparison between soil moisture sensors. Spatial averages of soil moisture may be influenced by sensor selection as there are different distributions present in the long term data record between sensors technologies, such as TDR vs. impedance, TDR vs. TDT, etc. In addition, analysis is performed to determine the impact of sensor variation on random errors.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.H51E1310C
- Keywords:
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- 1805 Computational hydrology;
- HYDROLOGY;
- 1847 Modeling;
- HYDROLOGY;
- 1855 Remote sensing;
- HYDROLOGY;
- 1910 Data assimilation;
- integration and fusion;
- INFORMATICS