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Located in western Inner Mongolia, the Badain Jaran Desert is the second largest desert in China and consists of a regular series of stable megadunes, among which over 70 permanent lakes exist. The unexpected lakes in desert attracted research interests in exploring the hydrological process in this particular landscape. However, only a little literature exists on the diurnal and spatial variation of the drying front in this area, which is the main issue in the desert hydrological process to characterize the movement of water in soil. In order to understand the drying front in the Badain Jaran Desert, a field campaign was conducted by the observations of soil physical parameters and micrometeorological parameters. With the field data, the performance of a vadose zone soil water balance model, the HYDRUS1D, was calibrated. Then, the HYDRUS1D was used to produce the spatial and temporal information of coupled water, water vapor and heat transport in sand to characterize the variation pattern of the drying front before, during and after the rainfall. The deepest drying front was applied to determine the effective infiltration, which is defined as the amount of soil water captured by the sand beneath the deepest drying front by infiltrated water of an incident rainfall event.

A brief history of the coupled moisture and heat transport theory is presented, accompanied by the discussion on the doubt about the enhanced vapor transport mechanism put forward by Philip and de Vries [62] (PdV model). The discussion points out that apart from a diffusion mechanism, vapor transport in the soil may also include advection and dispersion mechanisms. To check this, a two-phase mass and heat transport model has been developed based on the PdV model. The difference between the proposed model and the PdV model is discussed. Furthermore, the specific items added to the PdV model to take the airflow into consideration, are explained. The constitutive equations are introduced to link the independent variables (unknowns) and the dependent variables. The finite element formulation for the model is briefly described. The accuracy of the proposed model is assessed through comparison with analytical work for coupled mass and heat transfer and experimental work for isothermal two-phase flow (moisture/air transfer). The influence adding airflow has on the coupled moisture and heat transfer is further investigated, clearly identifying the importance of including airflow in the coupled mass and heat transfer. How the isothermal two-phase flow is affected by considering heat flow is also investigated, showing the influence of heat flow only to be significant if the air phase plays a significant role in solving the equations of the water phase.

Soil airflow is crucial in determining surface evaporation, which subsequently affects the atmospheric modeling. However, most land surface models (LSMs) usually ignore the airflow and only employ the diffusion-based soil water and heat transport model. In order to check how different model complexities can affect the model performance in retrieving soil moisture and soil temperature profiles, this chapter introduces three models with gradually-decreased complexities. The results show that the most complex model (i.e. coupled soil water–vapor-air-heat transport model developed in Chap.4) can perform better than other models in retrieving soil moisture when only soil moisture observation is available. For retrieving soil temperature, the medium complex model (i.e. coupled soil water–vapor-heat transport model) stands out from the three models. The simplest model (i.e. diffusion-based soil water and heat transport model) can produce assimilation estimates of soil temperature as satisfactory as the most complex model does; and, its assimilation estimate of soil moisture closely follows its simulation (e.g. open loop), which is not a proper representative of the observed truth. Nevertheless, the RMSE between its soil moisture assimilation estimates and the observation is the lowest among the three models, which may be responsible for the popular use of the diffusion-based model in the LSMs.

The concept of enhanced vapor transfer in unsaturated soils has been questioned for its reliance on soil temperature gradient, which leads to consideration of other mechanisms of vapor transfer, e.g. advective vapor transfer due to soil air pressure gradient. Although the advective flux is an important portion of evaporation, there is a lack of knowledge in its effect on evaporation. In order to assess the dependence of evaporation on the soil air pressure gradient, the vertical one-dimensional two-phase heat and mass flow model developed in Chap. 4 is used to investigate the advective effect in both low- and high-permeability soils. The advective effect is reflected by underestimating evaporation when the airflow is neglected and is more evident in the low-permeability soil. Neglecting airflow causes the underestimation error of 53.3 % on the day right after rainfall event in the low-permeability soil (7.9 × 10−4 cm s−1), and 33.3 % in the high-permeability soil (2 × 10−3 cm s−1). The comparisons of driving forces and conductivities show that the isothermal liquid flux, driven by the soil matric potential gradient, is the main reason for the underestimation error.

Due to the relatively low soil moisture in arid or semi-arid regions, vapor movement often predominates in the vadose zone and affects the partitioning of energy among various land surface fluxes. In an experiment, the soil water content at 10 and 30 cm depth were measured at hourly intervals for 2.5 days during October 2004. It was found that the soil moisture reached the daily maximum value (5.9–6.1 % at 10 cm and 11.9–13.1 % at 30 cm) at midday (12:00–13:00 for 10 cm and 14:00–15:00 for 30 cm) and minimum value (4.4–4.5 % at 10 cm and 10.4–10.8 % at 30 cm) before dawn (02:00–03:00 for 10 cm and 04:00–05:00 for 30 cm). The modified HYDRUS1D-1D code, which refers to the coupled water, vapor and heat transport in soil, was used to develop a deeper understanding of the physical processes of soil water dynamics in this experiment. The numerical analyses provided insight into the diurnal movement of liquid water and water vapor driven by both pressure heads and temperature gradients in the subsurface zone. The simulated temperature and water content were in good agreement with the measured values. The spatial-temporal distribution of liquid water flux, water vapor flux and soil temperature showed a detailed diurnal pattern of soil water dynamics in relatively coarse sand.