Skip to main content
ARS Home » Midwest Area » Ames, Iowa » National Laboratory for Agriculture and The Environment » Soil, Water & Air Resources Research » Research » Publications at this Location » Publication #315225

Title: Variable atmospheric, canopy, and soil effects on energy and carbon fluxes over crops

item Hatfield, Jerry
item Prueger, John

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 3/15/2016
Publication Date: 10/14/2016
Citation: Hatfield, J.L., Prueger, J.H. 2016. Variable atmospheric, canopy, and soil effects on energy and carbon fluxes over crops. In: Hatfield, J.L., Fleisher, D.H. editors. Advances in Agricultural Systems Modeling. Vol. 7. Madison, WI: ASA, CSSA, and SSSA. p. 195-216.

Interpretive Summary:

Technical Abstract: The fluxes of energy and carbon fluxes for canopies represent the dynamics of several exchange processes which couple the soil, plant, and atmosphere components. Energy exchanges are driven by net radiation, windspeed, canopy dynamics and soil water availability. The largest factor affected the energy balance is net radiation driven by the variation in solar radiation and subject to changes in cloud cover and season. Sensible and latent heat fluxes are driven by the available energy, the aerodynamic and canopy conductance, and soil water availability. All of the energy balance components exhibit spatial and temporal variation in response to the variation in the driving variables. One of the major coupling factors between a canopy and the atmosphere is canopy conductance which is affected by vapor pressure deficit, solar radiation, and available soil water and development of dynamic conductance models have proven to quantify the energy exchanges within a day, over a growing season, and among growing seasons. Energy and carbon fluxes can be quantified for their spatial and temporal variation and developing these approaches will allow for more robust models to quantify the energy exchanges across landscapes and to provide the ability to compare differences among years. Incorporating spatial and temporal variation into energy and carbon models will increase our ability to develop a more complete model of the impacts of land use changes and management practices on the energy and carbon exchanges of agricultural landscapes.