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Publication Date
1 March 2023

Modeling Agriculture Matters for Carbon Cycling

Researchers investigated the impact of using constant versus spatially varying crop parameters on carbon and energy fluxes in a realistic crop rotation scenario.
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Field with corn and clouds

Global land models increasingly include representations of crops, which can affect the local and regional climate. However, there is a limited understanding of how crop rotation and different crop cultivars affect carbon and energy fluxes from the land surface. A new study implements crop rotation and spatially varying crop parameters in the Energy Exascale Earth System Model Land Model (E3SM) to more realistically represent agricultural practices. It shows that varying crop parameters improve carbon and energy flux estimation from cropland areas, producing simulations that are significantly closer to observed values.


These findings emphasize the importance of accurately representing agricultural management practices and differences in crop growth characteristics in global land models. Accurately capturing these will improve the feedbacks between crops and climate. The feedbacks are especially important for next-generation earth system models (ESMs) that focus on improving the human–earth system interactions. This work is an initial step toward more realistic crop representations in ESMs and demonstrates a practical approach to modeling crop rotation. This work also highlights the importance of capturing spatial differences in crop growth characteristics.


The study examines the impact of using constant versus spatially varying crop parameters using a novel, realistic crop rotation scenario in the E3SM Land Model version 2 (ELMv2). Researchers implemented crop rotation using ELMv2's dynamic land unit capability. They then calibrated and validated the model against observations collected at three AmeriFlux sites in the U.S. Midwest with corn–soybean rotation. The calibrated model closely captured the magnitude and observed seasonality of carbon and energy fluxes across crops and sites. Regional simulations of the Midwest with the calibrated model showed that spatially varying only a few crop parameters across the region, as opposed to using constant parameters, had a large impact on the carbon and energy fluxes, both varying by up to 40%. These results imply that large-scale ESM simulations using spatially invariant crop parameters that do not represent agricultural realities may result in biased energy and carbon flux estimations from agricultural land. They underline the importance of improving human–earth system interactions in ESMs.

Point of Contact
L. Ruby Leung
Pacific Northwest National Laboratory
Funding Program Area(s)