MCA: Modeling Surface Aerodynamic Temperature over Agricultural Fields

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).

This project will study the heat transfer process, from agricultural fields into the atmosphere, to improve the estimation of crop water use rates (evapotranspiration, ET). The project will integrate three-dimensional (3D) crop height, crop density and orientation, weather data, wind angle of attack, and crop light reflectance and temperature images, from drones, in the heat flux modeling effort.

Modeling heat fluxes accurately will promote the adoption of a land surface energy balance (EB) model to map ET and improve irrigation management. The 3D crop characterization and its dynamic interaction with the wind have not been incorporated in heat flux models yet. Current EB models use one-dimensional crop characteristics, often resulting in ET estimation inaccuracies, which limits the general applicability of EB models.

Benefits from this study include the scientific characterization of Ag fields’ dynamic heat fluxes, enhancement of the research process, updating academic courses, training of students and dissemination of results through webinars, scientific papers, and conference presentations.

This project will integrate modern technology with knowledge from micro-meteorology, agronomy, remote sensing, and engineering to model a dynamic aerodynamic temperature. Two locations will be included, one in Colorado and another in Spain. The specific research objectives are to: a) characterize crop canopy directional (3D) structures and their effects on the zero-plane displacement height, roughness length for momentum transfer, friction velocity and surface aerodynamic resistance, as the wind (from a given angle of attack) interacts with the structure, under different surface and environmental conditions; b) develop a robust surface aerodynamic temperature model for agricultural applicability; and c) evaluate derived sensible and latent heat fluxes, to determine their accuracy, and advantages and improvements over existing one-dimensional models.

Intellectual Merit: The novelty of this study is the incorporation of 3D crop characteristics into aerodynamic and temperature terms to model the surface aerodynamic temperature and accurately determine agricultural sensible heat fluxes. Broader Impacts: crop ET will be well determined, which will promote a global adoption of the EB algorithm to improve water management decision making and foster agricultural sustainability.

Research results will be disseminated through scientific publications, conferences, webinars, and academic curricula.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.