Organisation

PhD Defence Mr Yijian Zeng

Dept. of Water Resources

Title of defence

Coupled Dynamics in Soil: understanding the transport mechanisms of liquid water, water vapor, air pressure and heat by field experiments and numerical simulation

Summary

One of the earliest results was to show the diurnal variation pattern of water fluxes in soil, which can be divided into four components including thermal liquid flux, thermal vapor flux, isothermal liquid flux and isothermal vapor flux. According to the spatial-temporal distribution of water fluxes, a schematic map of the diurnal pattern of coupled processes was introduced. It provides a detailed understanding of the Philip and de Vries’ theory (1957) (PdV theory) on soil water and heat dynamics. The investigation demonstrated how the thermal-driven or isothermal-driven water fluxes can alternatively dominate in soil on a daily scale.

Following the insightful investigation of coupled processes in soil, the diurnal soil moisture and heat dynamics was applied in the Badain Jaran Desert to determine the diurnal variation of the drying front after a rainfall event. The drying front dynamics were then applied to determine the effective infiltration or rainfall in the desert, enabling an assessment of how much precipitation evaporated and how much was conserved in the sand. The effective infiltration or rainfall could be used to evaluate the water sources for desert plants.

Although the traditional coupled moisture and heat transport model is able to explain the field experiment quite well, the single-phase transport mechanism limits its capability of describing the two-phase flow phenomenon. Especially concerning vapor transport in soil, the traditional model uses only an enhancement factor to describe the vapor flux that cannot be explained by Fick’s law. Although the vapor transport is actually involved in the gas phase transport in soil, the traditional coupled model is trying to use a single-phase mechanism with certain semi-empirical equations to explain a two-phase mechanism. In order to discuss the uncertainty caused by such a simplification, a two-phase mass and heat transport model is proposed fully taking diffusion, convection and dispersion mechanisms into consideration. The numerical analysis of air-water-heat flow is implemented using published data. The results show that the traditional coupled model needs the inclusion of the air-phase transport mechanism to describe the vapor transport in soil.

The proposed two-phase heat and mass transport model was then applied to analyze how the vapor transport in soil affects evaporation on the soil surface. Although the thermal effect on evaporation has been studied in detail, no special attention was paid to the airflow effect on evaporation. The assessment of the latter effect needs to consider the vapor transport as part of the bulk flow of dry air in the soil, as has been implemented in the proposed two-phase model. Investigating this effect, it was found that there was a surprising underestimation error of evaporation when soil airflow was ignored. The underestimation error was even amplified the first day after a rainfall event. To understand the mechanism of the underestimation error, a simulation analysis of the advective effect on evaporation was implemented. The underestimation error was mainly caused by underestimating the isothermal hydraulic conductivity in the top soil due to neglecting the downward advective flux.

In land-atmosphere interaction studies, when implementing operational schemes to assimilate remotely sensed observations or when focusing on a specific purpose (e.g. retrieval of a soil moisture profile), the data assimilation system typically simplifies or avoids a number of key complexities in land surface models (LSMs). In terms of the assimilation of soil moisture and soil temperature, the most common simplification is the decoupling of concurrent flow of water and heat in soil. However, such simplification may cause errors in calculating evaporation fluxes as stated above. The proposed two-phase model is implemented in a data assimilation system to check the impact of different model physics complexities on retrieving soil state variables by using an ensemble Kalman filter. The result explains that an optimal combination may exist between the model physics chosen and the data typically available for assimilation, for gaining the best retrieval of soil state variables.

In-situ Station

Biography

Since January 2007, Yijian Zeng became a PhD candidate in ITC Faculty, University of Twente, under a joint-cooperation project supported by ITC, CUGB (China University of Geosciences (Beijing)) and CAREERI (Cold and Arid Regions Environmental and Engineering Research Institute, China Academy of Sciences). His study focuses on understanding coupled mechanism in soil, using field observations and numerical simulations. In 2007, with a control sand bunker experiment, he indicated how the thermal or isothermal soil moisture fluxes can alternatively dominate in soil on a daily scale.  After that (2008), he designed and conducted a field experiment in the Badain Jaran Desert, located in the Northwestern China. With the detailed observation of micrometeorological and soil physical parameters, he assessed how much precipitation evaporated and how much was conserved in the sand, which could be used to evaluate the water sources for desert plants.

With the analysis of the experiments mentioned above, he realized that single-phase transport mechanism of the classic theory cannot explain the discrepancy between model estimates and field observations of the vapor fluxes in soil. To overcome this, he developed a two-phase heat and mass transport model to consider vapor transport with diffusion, advection and dispersion mechanisms (2009). The results show that the newly developed model outperforms the traditional theory in calculating surface evaporation with regard to the comparison with the field observations (2010). To further explain why the newly developed model is better than the traditional model, he conducted an insightful investigation on the driving forces in the two models and explained the difference between the two models mechanically (2010). Furthermore, in order to understand how a changing climate can affect patterns of evaporation at a regional scale, he combined the newly developed model with data assimilation technique to retrieve soil moisture and temperature profiles (2011).

He earned his MSc degree in hydrology and water resources engineering from China University of Geosciences (Beijing) in China, and a B.Sc. degree in hydrogeology and engineering geology from Shijiazhuang University of Economics in China.

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