An Evaluation of Coupled Water and Heat Transport Models in the Vadose Zone with Different Assumptions and Processes

Thursday, 18 December 2014
Zhenlei Yang, Texas A & M University, College Station, TX, United States and Binayak Mohanty, Texas A&M University, College Station, TX, United States
Understanding and simulating coupled water and heat transfer appropriately in the shallow subsurface is of vital significance for accurate prediction of soil evaporation that would improve the coupling between land surface and atmosphere, which consequently could enhance the reliability of weather and climate forecast. The theory of Philip and de Vries (1957), accounting for coupling between liquid water flow, vapor diffusion and heat transport, was considered physically incomplete and consequently extended by several researchers via taking into account more processes such as vapor convection, dispersion, air flow and dynamic phase change between liquid and vapor. Furthermore, the film flow process induced by adsorptive forces, which was also ignored in Philip and de Vries model for characterizing soil hydraulic parameters, was shown to be non-negligible for soil moisture and evaporation flux calculation in dry soils based on a recent synthetic analysis (Mohanty and Yang, 2013). In fact, the importance of these additional processes in arid and semiarid regions should be critically evaluated. Therefore, a general nonisothermal two-phase flow numerical model is developed to investigate the different conceptual model concepts, assumptions and processes regarding coupled water and heat transport in soils using two field data sets including Riverside, California and Audubon, Arizona. It is found that for the Riverside, California data sets, where the soil is relatively moist, the film flow effect is not very significant. However, for drier soils at the Audubon site in Arizona, the liquid film flow effect was significantly important. The airflow effect is important in both the Riverside site, California and Audubon, Arizona site data set and needs to be accounted for. In addition, the model taking into account non-equilibrium phase change effect is most complicated, however most accurate for both the sites in the study