Field-scale moisture estimates using COSMOS sensors: A validation study with temporary networks and Leaf-Area-Indices
•Compares COSMOS SM field estimates with field averages produced by in situ networks.•COSMOS sensors respond to water stored in vegetation while in situ sensors do not.•Adding LAI helps resolve discrepancies between COSMOS and in situ network estimates. The COsmic-ray Soil Moisture Observing System...
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Published in: | Journal of hydrology (Amsterdam) Vol. 519; pp. 637 - 643 |
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Main Authors: | , , |
Format: | Journal Article |
Language: | English |
Published: |
Kidlington
Elsevier B.V
27-11-2014
Elsevier |
Subjects: | |
Online Access: | Get full text |
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Summary: | •Compares COSMOS SM field estimates with field averages produced by in situ networks.•COSMOS sensors respond to water stored in vegetation while in situ sensors do not.•Adding LAI helps resolve discrepancies between COSMOS and in situ network estimates.
The COsmic-ray Soil Moisture Observing System (COSMOS) is a new and innovative method for estimating surface and near-surface soil moisture at large (∼700m) scales. This system accounts for liquid water within its measurement volume. Many of the sites used in the early validation of the system had low and stable vegetation water content. It is necessary to perform validation of COSMOS in a landscape with a significant change in vegetation water content to estimate its impact on the COSMOS estimate, and potentially, correct the estimate to account for the dynamic vegetation cover. A COSMOS station was installed in Beltsville, MD in the spring of 2012, within the domain of a long-term experimental station on USDA property. This station has a large array of soil moisture sensors in profile across the field, which is approximately 700m in diameter. Frequent estimates of Leaf Area Index (LAI) were made throughout the 2012 and 2013 growing seasons (May through September). COSMOS readings, with a simple linear adjustment, were able to produce estimates of area-weighted averages of the existing in situ network with root-mean-squared-errors (RMSE) of soil-water content well below 0.04m3/m3 and with additional modeling to account for Leaf Area Index (LAI) values, RMSE values less than 0.03m3/m3 were achieved. |
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Bibliography: | http://handle.nal.usda.gov/10113/60398 http://dx.doi.org/10.1016/j.jhydrol.2014.07.060 |
ISSN: | 0022-1694 1879-2707 |
DOI: | 10.1016/j.jhydrol.2014.07.060 |