Random and systematic errors in mixed sensor networks
Abstract
In the development of a National Soil Moisture Network, it will become necessary to consider the aggregation of soil moisture data which derives from different soil moisture network designs and instrumentation. The methodology for installing and monitoring with a variety of sensors introduces new systematic errors into the time series and these errors must be understood moving forward with integrated network designs. Therefore, long time series of data from a variety of in situ soil moisture sensors were analyzed to quantify the increased variability of data from an integrated network based on the composition of that network. Data from the Marena Oklahoma In Situ Sensor Testbed (MOISST) is used to determine the long term record impacts of mixed sensor networks with regards to random and systematic errors related to sensor choice. Triple collocation analysis is employed to measure the additional random error in estimating a soil moisture average from the inclusion of a variety of common commercial sensors. This study will impact the future development of sensor networks.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.H53J1720C
- Keywords:
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- 1843 Land/atmosphere interactions;
- HYDROLOGYDE: 1865 Soils;
- HYDROLOGYDE: 1866 Soil moisture;
- HYDROLOGYDE: 1895 Instruments and techniques: monitoring;
- HYDROLOGY