Skip to main content
ARS Home » Pacific West Area » Maricopa, Arizona » U.S. Arid Land Agricultural Research Center » Plant Physiology and Genetics Research » Research » Publications at this Location » Publication #349177

Research Project: Strengthening the Analysis Framework of G x E x M under Climate Uncertainty

Location: Plant Physiology and Genetics Research

Title: Validation of spring wheat responses to elevated CO2, irrigation, and nitrogen fertilization in the Community Land Model 4.5

item LU, YAQIONG - National Center For Atmospheric Research (NCAR)
item Kimball, Bruce

Submitted to: Earth and Space Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/30/2020
Publication Date: 6/9/2020
Citation: Lu, Y., Kimball, B.A. 2020. Validation of spring wheat responses to elevated CO2, irrigation, and nitrogen fertilization in the Community Land Model 4.5. Earth and Space Science. 7(6).

Interpretive Summary: The CO2 concentration in the atmosphere is increasing, which can affect plant photosynthesis and also cause a partial closure of the stomata in plant leaves through which the plant exchanges CO2 and water vapor with the atmosphere. The magnitude of both effects and the extent to which they change growth, yield, and water requirements of crops is likely to be influenced by other environmental factors such as soil nitrogen supply. In order to predict what effect the elevated CO2 will have on future crop production, as well as Earth’s future global carbon balance and climate, land surface simulation models are being developed. This paper reports a successful test of one such model called the Community Land Model, comparing model predictions against the results of an experiment where open-field-grown wheat was exposed to elevated levels of CO2 using free-air CO2-enrichment (FACE) technology at ample and limited levels of soil water and nitrogen. Many model results were acceptably close to observed values, but several others were not, which identified areas for which the model needs improvement. This work will benefit both future growers and consumers of wheat and wheat products, as well as improving future climate predictions.

Technical Abstract: The Community Land Model (CLM) is a state-of-the-art land surface model that simulates biogeophysical and biogeochemical processes. CLM started to incorporate the crop growth models since version 4.0 in 2012, and since then the crop model in CLM has been evolved remarkably, but some of the key crop growth responses to environmental conditions (such as the elevated CO2) have not been well validated. The Maricopa spring wheat Free Air CO2 Enrichment (FACE) experiment is one of the most frequently used experiments for such validation because the experiment consisted of multi-year paired treatments to understand the growth response to elevated CO2, irrigation, nitrogen fertilization, and their interactions. We set up single point simulations with CLM (version 4.5) forcing with the observed hourly meteorology and applied the same amount of CO2, irrigation, and nitrogen fertilization as actually applied for each treatment. We focused on both spring wheat growth and energy flux responses to these land managements. Overall, CLM underestimated above ground biomass by 7% (117 g m-2) and overestimated grain yield by 13% (91 g m-2), and showed too positive growth response to elevated CO2, but insufficient growth response to irrigation. The overestimated growth response to elevated CO2 may be due to ignoring factors (e.g., leaf traits) that will limit crop growth under elevated CO2. The insufficient response to irrigation is due to CLM simulating lower latent heat flux during April and May, which resulted in higher soil moisture. Thus, spring wheat grows well even with lower amounts of irrigation in CLM. In response to nitrogen fertilization, CLM underestimated LAI increase but overestimated grain yield increase. In terms of energy fluxes, CLM showed decreased latent heat flux in response to elevated CO2 but increased latent heat flux in response to nitrogen fertilization, but the response magnitude was much smaller than the observations. The poor simulated energy fluxes was partly due to CLM underestimating vegetation controls on transpiration, and partly due the observed latent heat flux was not obtained by direct measurments where an abnormal high amount (97%) of energy partitioning into latent heat flux. Based on these validations, we summarized further model developments for CLM to better simulate crop growth process.