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Effects of Soil Physical Nonuniformity on Chamber‐Based Gas Flux Estimates
Author(s) -
Venterea Rodney T.,
Baker John M.
Publication year - 2008
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj2008.0019
Subject(s) - flux (metallurgy) , soil science , environmental science , soil water , trace gas , calibration , soil gas , observational error , mechanics , hydrology (agriculture) , mathematics , atmospheric sciences , chemistry , physics , statistics , geology , geotechnical engineering , organic chemistry
Chamber methods for measuring trace gas fluxes are prone to errors resulting in large part from the alteration of near‐surface concentration gradients. There is little information available, however, for quantifying these errors or determining how they vary with soil physical properties, chamber deployment methods, and flux calculation schemes. This study used numerical modeling to examine how these factors influence flux estimate errors in physically uniform and nonuniform soil profiles. Errors varied widely among profiles and flux calculation techniques. Soil profiles having identical predeployment fluxes but differing in water content and bulk density generated substantially different flux chamber data. A theoretical flux model that assumes physical uniformity performed relatively well in nonuniform soils but still generated substantial errors. For all flux models, errors were minimized with larger effective chamber heights ( h ) and shorter deployment times (DT). In light of these findings, recent studies that recommend minimizing h and extending DT to enhance nonlinearity of chamber data need to be reevaluated. It was also determined that random measurement error can result in skewed flux‐estimate errors. Selection of chamber and flux calculation methods should consider the physical characteristics of the soil profile as well as measurement error. The techniques presented here can be used to develop soil‐ and method‐specific error estimates.

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