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Inverse estimation of parameters for multidomain flow models in soil columns with different macropore densities
Bhavna Arora1, Binayak P Mohanty1, Jennifer T McGuire2
1Department of Biological and Agricultural Engineering, Texas A&M University, College Station, Texas, USA.
Abstract:
Soil and crop management practices have been found to modify soil structure and alter macropore densities. An ability to accurately determine soil hydraulic parameters and their variation with changes in macropore density is crucial for assessing potential contamination from agricultural chemicals. This study investigates the consequences of using consistent matrix and macropore parameters in simulating preferential flow and bromide transport in soil columns with different macropore densities (no macropore, single macropore, and multiple macropores). As used herein, the term"macropore density" is intended to refer to the number of macropores per unit area. A comparison between continuum-scale models including single-porosity model (SPM), mobile-immobile model (MIM), and dual-permeability model (DPM) that employed these parameters is also conducted. Domain-specific parameters are obtained from inverse modeling of homogeneous (no macropore) and central macropore columns in a deterministic framework and are validated using forward modeling of both low-density (3 macropores) and high-density (19 macropores) multiple-macropore columns. Results indicate that these inversely modeled parameters are successful in describing preferential flow but not tracer transport in both multiple-macropore columns. We believe that lateral exchange between matrix and macropore domains needs better accounting to efficiently simulate preferential transport in the case of dense, closely spaced macropores. Increasing model complexity from SPM to MIM to DPM also improved predictions of preferential flow in the multiple-macropore columns but not in the single-macropore column. This suggests that the use of a more complex model with resolved domain-specific parameters is recommended with an increase in macropore density to generate forecasts with higher accuracy.
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