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a Dep. of Soil Sciences, SLU, Box 7014, 750 07 Uppsala, Sweden
b Agrosphere Institute, ICG–IV, Forschungszentrum Jülich GmbH, D–52425 Jülich, Germany
c Currently, Soil Protection Group, Insitute of Terresterial Ecology, ETH Zurich, Grabenstrasse 11a, 8952 Schlieren, Switzerland
* Corresponding author (Mats.Larsbo{at}mv.slu.se)
Received 23 September 2004.
We introduce an improved, one-dimensional, non-steady-state dual-permeability model (MACRO 5.1). The model simulates water flow and solute transport in the vadose zone of structured soils by coupling a high-conductivity–low porosity macropore domain to a low-conductivity–high porosity domain representing the soil matrix. Mass exchange between the domains is approximated by first-order expressions. The numerical solutions are briefly described, focusing on the dual-permeability formulation. The solution method for water flow in macropores was verified by comparing simulation results with analytical solutions for a "kinematic wave". The model was tested against high time-resolution measurements of water flow and nonreactive (Cl–) solute transport in transient microlysimeter experiments. The objective was to test the identifiability of four key model parameters determining the degree of preferential flow using the generalized likelihood uncertainty estimation (GLUE) procedure. The parameters were chosen either because they are difficult or impossible to measure directly or because they were considered sensitive on the basis of earlier experience with the model. The measurements, indicating strong preferential flow, were adequately reproduced by the model simulations (overall model efficiency = 0.62). The GLUE procedure conditioned the saturated matrix hydraulic conductivity, the macroporosity, and the mass exchange coefficient (diffusion pathlength), indicating that these parameters would be identifiable in inverse modeling approaches based on microlysimeter experiments. The conditioning of the kinematic exponent was poor, which was attributed primarily to correlation with the macroporosity.
Abbreviations: GLUE, generalized likelihood uncertainty estimation
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