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Internal inconsistencies in dispersion‐dominated models that incorporate chemical and microbial kinetics
Author(s) -
Molz Fred J.,
Widdowson Mark A.
Publication year - 1988
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr024i004p00615
Subject(s) - extrapolation , aquifer , dispersion (optics) , soil science , environmental science , calibration , mathematical model , chemical species , mechanics , biological system , groundwater , chemistry , geology , physics , geotechnical engineering , mathematics , statistics , optics , organic chemistry , biology
Current understanding of transport processes in aquifers is limited by lack of precise point chemical concentration measurements. Recently, however, some careful measurements of vertical chemical concentration profiles have been made at several locations around the world that appear to support a consistent picture concerning the persistence of large vertical concentration gradients in aquifers and, by implication, the existence of very small vertical transverse dispersivities. These data were obtained in aquifers supporting microbial activity. Data analysis using a mathematical model which considers microbial degradation coupled to nutrient and oxygen transport indicates that a vertical transverse dispersivity on the order of 0.1 cm or less is consistent with the concentration gradients that were measured. The existence of such large gradients and low dispersivities is not consistent with the use of two‐dimensional vertically averaged (areal) models as currently applied, especially if one is interested in the development of transport models with predictive capability beyond that associated with standard calibration and extrapolation. Even three‐dimensional models with large vertical transverse dispersivities compared to those measured will produce results inconsistent with measurements. Microbial‐chemical activity is very sensitive to concentration distributions. Smearing of the oxygen profile can result in the prediction of aerobic activity where, in fact, none exists.