Abstract

AbstractModeling convective air movement in unsaturated porous media requires appropriate characterization of the relative air permeability (RAP). Adopting Assouline et al. (1998, https://doi.org/10.1029/97WR03039) water retention function that is based on the Weibull pore size distribution, this study was conducted to derive seven new predictive RAP models. These 7 new models, together with another 3 models developed by Assouline et al. (2016, https://doi.org/10.1002/2015WR018286), were then compared with data from 30 disturbed soil samples to investigate their predictive RAP performances. The model and data comparison results showed that the modified Burdine, modified Mualem, and modified Alexander and Skaggs relative permeability models proposed by Yang and Mohanty (2015, https://doi.org/10.1002/2014WR016190) had the highest accuracy for the RAP prediction among the 10 investigated models, which indicated that the tortuosity and connectivity exponent of water phase should be smaller than that of air phase for the disturbed soil samples. The modified Burdine, modified Mualem, and modified Alexander and Skaggs models were then the suggested RAP parameterizations for the subsurface multiphase flow numerical simulation.

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