The Impact of Crop Rotation and Spatially Varying Crop Parameters in the E3SM Land Model (ELMv2)

Authors

Eva Sinha, Pacific Northwest National Laboratory
Ben Bond-Lamberty, Pacific Northwest National Laboratory
Katherine V. Calvin, Pacific Northwest National Laboratory
Beth A. Drewniak, Argonne National Laboratory
Gautam Bisht, Pacific Northwest National Laboratory
Carl Bernacchi, USDA Agricultural Research Service
Bethany J. Blakely, University of Illinois Urbana-Champaign
Caitlin E. Moore, University of Illinois Urbana-Champaign

Document Type

Article

Date of this Version

3-1-2023

Citation

Sinha, E., Bond-Lamberty, B., Calvin, K. V., Drewniak, B. A., Bisht, G., Bernacchi, C., et al. (2023). The impact of crop rotation and spatially varying crop parameters in the E3SM land model (ELMv2). Journal of Geophysical Research: Biogeosciences, 128, e2022JG007187. https://doi. org/10.1029/2022JG007187

Comments

U.S. government work

Abstract

Earth System Models (ESMs) are increasingly representing agriculture due to its impact on biogeochemical cycles, local and regional climate, and fundamental importance for human society. Realistic large scale simulations may require spatially varying crop parameters that capture crop growth at various scales and among different cultivars, as well as common crop management practices, but their importance is uncertain, and they are often not represented in ESMs. In this study, we examine the impact of using constant versus spatially varying crop parameters using a novel, realistic crop rotation scenario in the Energy Exascale Earth System Model (E3SM) Land Model version 2 (ELMv2). We implemented crop rotation by using ELMv2's dynamic land unit capability, and then calibrated and validated the model against observations collected at three AmeriFlux sites in the US Midwest with corn soybean rotation. The calibrated model closely captured the magnitude and observed seasonality of carbon and energy fluxes across crops and sites. We performed regional simulations for the US Midwest using the calibrated model and found that spatially varying only a few crop parameters across the region, as opposed to using constant parameters, had a large impact, with the carbon fluxes and energy fluxes both varying by up to 40%. These results imply that large scale ESM simulations using spatially invariant crop parameters may result in biased energy and carbon fluxes estimation from agricultural land, and underline the importance of improving human-earth systems interactions in ESMs.