American Society of Civil Engineers

Incorporating Both Physical and Kinetic Limitations in Quantifying Dissolved Oxygen Flux to Aquatic Sediments

by Ben L. O’Connor, (corresponding author), (NRC Postdoctoral Associate, U.S. Geological Survey, Mail Stop 430 National Center, Reston, VA 20192; currently, Environmental Science Division, Argonne National Laboratory, EVS/240 9700 S. Cass Ave., Argonne, IL 60439 E-mail:, Miki Hondzo, (Professor, Dept. of Civil Engineering, St. Anthony Falls Laboratory, Univ. of Minnesota-Twin Cities, 2 Third Ave. SE, Minneapolis, MN 55414. E-mail:, and Judson W. Harvey, (Hydrologist, U.S. Geological Survey, Mail Stop 430 National Center, Reston, VA 20192. E-mail:

Journal of Environmental Engineering, Vol. 135, No. 12, December 2009, pp. 1304-1314, (doi:

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Document type: Journal Paper
Abstract: Traditionally, dissolved oxygen (DO) fluxes have been calculated using the thin-film theory with DO microstructure data in systems characterized by fine sediments and low velocities. However, recent experimental evidence of fluctuating DO concentrations near the sediment-water interface suggests that turbulence and coherent motions control the mass transfer, and the surface renewal theory gives a more mechanistic model for quantifying fluxes. Both models involve quantifying the mass transfer coefficient (k) and the relevant concentration difference (ΔC). This study compared several empirical models for quantifying k based on both thin-film and surface renewal theories, as well as presents a new method for quantifying ΔC (dynamic approach) that is consistent with the observed DO concentration fluctuations near the interface. Data were used from a series of flume experiments that includes both physical and kinetic uptake limitations of the flux. Results indicated that methods for quantifying k and ΔC using the surface renewal theory better estimated the DO flux across a range of fluid-flow conditions.

ASCE Subject Headings:
Surface water
Dissolved oxygen
Oxygen demand
Mass transport
Boundary layer flow