H13D-1138:
Integrated Cropland and Grassland Flux Tower Observation Sites over Grazinglands for Quantifying Surface-Atmosphere Exchange

Monday, 15 December 2014
Hayden Ray Mahan1, Pradeep Wagle1, Rajen Bajgain1, Yuting Zhou1, Jeffrey B Basara1, Xiangming Xiao2, Jonah m Duckles1, Jean Steiner3, Patrick j Starks3 and Brian K Northup3, (1)University of Oklahoma Norman Campus, Norman, OK, United States, (2)University of Oklahoma, Norman, OK, United States, (3)USDA-ARS, El Reno, OK, United States
Abstract:
Quantifying methane (CH4), carbon dioxide (CO2), and water vapor fluxes between land surface and boundary layer using the eddy covariance method have many applicable uses across several disciplines. Three eddy flux towers have been established over no-till winter wheat (Triticum aestivum L.), and native and improved pastures at the USDA ARS Grazinglands Research Laboratory, El Reno, OK. An additional tower will be established in fall 2014 over till winter wheat. Each flux site is equipped with an eddy covariance system, PhenoCam, COSMOS, and in-situ observations of soil and atmospheric state variables. The objective of this research is to measure, compare, and model the land-atmosphere exchange of CO2, water vapor, and CH4 in different land cover types and management practices (till vs no-till, grazing vs no-grazing, native vs improved pasture). Models that focus on net ecosystem CO2 exchange (NEE), gross primary production (GPP), evapotranspiration (ET), and CH4 fluxes can be improved by the cross verification of these measurements. Another application will be to link the in-situ measurements with satellite remote sensing in order to scale-up flux measurements from small spatial scales to local and regional scales. Preliminary data analysis from the native grassland site revealed that CH4 concentration was negligible (~ 0), and it increased significantly when cattle were introduced into the site. In summer 2014, daily ET magnitude was about 4-5 mm day-1 and the NEE magnitude was 4-5 g C day-1 at the native grassland site. Further analysis of data for all the sites for longer temporal periods will enhance understanding of biotic and abiotic factors that govern carbon, water, and energy exchanges between the land surface and atmosphere under different land cover and management systems. The research findings will help predict the responses of these ecosystems to management practices and global environmental change in the future.