An Observational and Modeling Study of the Energy, Water, and Carbon Cycle at Calhoun Critical Zone - Yao Tang

Where: 
Mason Building, Room 2119
When: 
Tuesday, December 4, 2018 - 09:00

 

Abstract:

This study investigates the evolution of the energy, water, and carbon cycle due to land-use change at Calhoun critical zone (CCZ) using field observations and modeling results of eco-hydro-meteorological variables. Land-use change such as deforestation, cultivation, and reforestation alters the energy, water, and carbon cycle by changing the land surface temperature, heat fluxes, evapotranspiration, and carbon storage. CCZ is an ideal platform for investigating this issue as Calhoun has experienced a huge land-use change including severe deforestation in the 18th century, intensive cultivation before the Great Depression in the 1920s, and tremendous reforestation in the 20th century. Three field observational sites were constructed at CCZ from August 2016 to May 2017. The observational system measures more than 300 eco-hydro-meteorological variables from 7 m below ground to 9 m above ground, and records more than 500 GB raw data. The field observations are used to test three models of land surface processes, the maximum entropy production model of heat fluxes, the model of friction velocity, and the half-order derivative model of gas fluxes. With the field observations and modeling results, the evolution of the energy, water, and carbon cycle due to land-use change at CCZ is quantitatively investigated. This study draws three conclusions. Firstly, land surface fluxes are more significantly influenced by land-use change than the corresponding meteorological state variables. Secondly, land-use change alters soil conditions more significantly than air conditions. Thirdly, when CO2 concentration at pre- and post-agricultural ecosystems are almost identical, CO2 fluxes and water use efficiency at the post-agricultural ecosystem are almost twice of those at the pre-agricultural ecosystem. Therefore, microclimate change would be significantly underestimated using the most concerned and commonly used variables such as air temperature, relative humidity, and CO2 concentration.

Advisor:

Dr. Jingfeng Wang

Committee:

Dr. Aris P. Georgakakos
Dr. Jian Luo
Dr. Satish Bastola
Dr. Yi Deng (EAS)