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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #328772
Title: The impact of vertical measurement depth on the information content of soil moisture for latent heat flux estimation

Author
item QIU, J. - Collaborator
item Crow, Wade
item NEARING, G.S. - National Aeronautics And Space Administration (NASA)

Submitted to: Journal of Hydrometeorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/15/2016
Publication Date: 9/1/2017
Citation: Qiu, J., Crow, W.T., Nearing, G. 2017. The impact of vertical measurement depth on the information content of soil moisture for latent heat flux estimation. Journal of Hydrometeorology. 17:2419–2430.

Interpretive Summary: Satellite-derived surface soil moisture retrievals have the potential to improve our ability to monitor crop water usage over large geographic areas. However, it is commonly assumed that this potential is limited by the shallow measurement depth (5 cm) of these retrievals. For the first time, this paper systematically examines how the value of vertically-integrated soil moisture observations for evapotranspiration monitoring is impacted by variations in their measurement depth. Surprising, results demonstrate that shallow surface observations are equally as valuable as observations obtained by vertically-integrating over deeper observing depths. This result strongly suggests that, for agricultural monitoring applications, the limited measurement depth of satellite-based surface soil moisture retrievals does not pose as large a problem as commonly-perceived. This result can be used by agricultural drought monitors to improve their ability to predict the large-scale impact of drought on crop health and agricultural productivity.

Technical Abstract: Using ground-based soil moisture and latent/sensible heat fluxes observations acquired from the Ameriflux Network, we calculate the mutual information (MI) content between multiple soil moisture variables and evaporative fraction (EF) to examine the existence of information in vertically-integrated soil moisture observations ('V) not present in either superficial soil moisture observations ('S) or a simple low-pass transformation of 'S (i.e., SWI). Results suggest that, contrary to expectations, 2-day averages of 'S and 'V have comparable mutual information with regards to EF. That is, there is no clear evidence that the information content for flux estimation is enhanced via improving the vertical support of superficial soil moisture observations. In addition, the SWI is a significantly-worse diagnostic EF monitor than 'V, and slightly worse than 'V as an EF forecaster. Similar results are obtained when analyses are conducted at the monthly time scale, only with larger error bars. The contrast between the results of this paper and past work focusing on utilizing soil moisture to predict vegetation condition demonstrates that the particular application should be considered when characterizing the information content of soil moisture time series measurements.