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Field Evaluation of Portable Soil Water Content Sensors in a Sandy LoamGround observations are critical in the validation of soil water content (SWC) estimates from both satellites and land surface models. Portable SWC sensors provide useful information to determine the amount of SWC in the topsoil layer for various applications; however, these probes are not accurate without site‐specific correction. In the present study, we examined and compared six different types of portable electromagnetic (EM) SWC sensors, including multiple sensors made by the same manufacturers, for a total of 16 EM‐based SWC probes equipped with portable data loggers. All SWC probes met the target accuracy after onsite correction—the RMSD was <0.025 m(exp 3) m(exp -3). Using the two‐sample t-tests, we observed that SWC data obtained from similar electrode lengths and from different manufacturers showed similar distributions over time with the same mean. Furthermore, using the maximize R method to combine SWC data from two different types of sensors increased the accuracy of the results. When datasets from two different types of sensors were combined, the Pearson's correlation coefficient (R value) and RMSD values were improved. The average R value improved from .930 to .945, and the RMSD decreased from 0.036 m(exp 3) m(exp -3) to 0.018 m(exp 3) m(exp −3). These results indicate that, along with site‐specific correction, synergetic use of multiple manufacturers’ EM‐based SWC probes can improve the R value and reduce systematic bias.
Document ID
20205001480
Acquisition Source
Goddard Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Hyunglok Kim ORCID
(University of Virginia Charlottesville, Virginia, United States)
Michael Harold Cosh ORCID
(United States Department of Agriculture Washington D.C., District of Columbia, United States)
Rajat Bindlish ORCID
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Venkataraman Lakshmi ORCID
(University of Virginia)
Date Acquired
April 28, 2020
Publication Date
May 19, 2020
Publication Information
Publication: Vadose Zone Journal
Publisher: Wiley
Volume: 19
Issue: 1
Issue Publication Date: January 1, 2020
e-ISSN: 1539-1663
Subject Category
Earth Resources And Remote Sensing
Funding Number(s)
WBS: 372217.04.10.01.16
CONTRACT_GRANT: NNX12AP75G
CONTRACT_GRANT: 80NSSC19K1337
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Technical Review
External Peer Committee
Keywords
soil moisture data
portable electromagnetic
root mean square difference
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