Location: Soil and Water Management ResearchTitle: COSMOS soil water sensing affected by crop biomass and water status
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 3/3/2014
Publication Date: 3/12/2014
Citation: Evett, S.R., Schwartz, R.C., Bell, J. 2014. COSMOS soil water sensing affected by crop biomass and water status.[abstract]. In Proceedings of the Third In-Situ and Remote Soil Moisture Sensing Technology Conference, March 12-14, 2014, Houston, TX. p.30.
Technical Abstract: Soil water sensing methods are widely used to characterize water content in the root zone and below, but only a few are capable of sensing soil volumes larger than a few hundred liters. Scientists with the USDA-ARS Conservation & Production Research Laboratory, Bushland, Texas, evaluated: a) the Cosmic Ray Soil Moisture Observing System (COSMOS), which responds to surface soil water content changes in a circular area of radius up to several hundred meters; b) electromagnetic (EM) soil water sensors that each sense only a few hundred cubic centimeters, used in a wireless sensor network to interrogate larger volumes of soil; and c) the neutron probe (NP), used in a network of eight access tubes. These were inter-compared and compared as well with a large precision weighing lysimeter that measured soil water storage changes to within 0.04 mm (<0.01 inch). COSMOS was well correlated with 0-30 cm water content and storage as measured by the field-calibrated EM sensors. COSMOS responded to rainfall better than to subsurface drip irrigation at 30-cm depth. COSMOS water content data were biased upward by green, living vegetation. The COSMOS "effective depth" algorithm did not work well in this study; but assuming that the effective depth was constant at 30 cm depth resulted in good correlation with EM measured soil water storage. The wireless EM sensors system worked very well, providing timely information that correlated well with weighing lysimeter soil water storage data. The wireless EM sensor system would be very useful for irrigation scheduling since the tall corn crop did not result in signal and data loss and the data accurately represented soil water content as it changed over time due to irrigation and precipitation.