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Determination of Preferential Flow Model Parameters
Author(s) -
Logsdon S. D.
Publication year - 2002
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/sssaj2002.1095
Subject(s) - macropore , loam , mathematics , flow (mathematics) , soil water , soil science , hydrology (agriculture) , geometry , materials science , chemistry , geology , geotechnical engineering , mesoporous material , biochemistry , catalysis
Solute transport models that include a preferential flow component require many input parameters. There are well established procedures to determine micropore parameters, but procedures to determine macropore parameters are not well established. The objective of this paper was to evaluate methods to independently measure macropore parameters. The test model used was MACRO, a transient‐state, two‐flow domain model. The key macropore parameters in the model are saturated and boundary hydraulic conductivities ( K s and K b ), the absolute value of the boundary head between macropore and micropore domains ( h b ), the exponent ( n *) of the relation between K (variables are defined in the appendix) and water content (θ), the macropore fraction (θ sma ), and the half spacing ( d ) between equivalent parallel fractures. As an example this study used soils in the Des Moines lobe (Mollisols with textures ranging from sandy loam to silty clay). Data used to calculate model parameters included wet‐end K ‐θ‐ h and K ( h ), and results from image analysis. For the MACRO model, the parameters fit the equations best when h b was assumed to be 30 mm. For the measured data with assumed h b = 30 mm, n * had a median of 2.1 and a range from 0 to 5.2, median K b was 15 mm h −1 with a range from 1 to 100 mm h −1 , and the median K s was 122 mm h −1 with a range from 7 to 741 mm h −1 . The calculated d ranged from 1 to 847 mm, and θ sma ranged from 0.001 to 0.053 m 3 m −3 . Depending on the data available, the various techniques can be used to determine input parameters for preferential flow models.