4.6 Article

Modeling Perennial Bioenergy Crops in the E3SM Land Model (ELMv2)

Journal

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2022MS003171

Keywords

crop modeling; perennial crops; ELM

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In this study, the Energy Exascale Earth System Land Model was expanded to include perennial bioenergy crops, and various parameters associated with their growth stages were estimated and optimized through global sensitivity analysis. The model was calibrated and validated against observations, capturing the seasonality and magnitude of carbon fluxes, but showing some limitations in capturing sensible heat flux for miscanthus. This work lays the foundation for future analysis of the interactions between perennial bioenergy crops and carbon, water, and energy dynamics, and for studying the impact of biofuel expansion on climate and terrestrial systems.
Perennial bioenergy crops are increasingly important for the production of ethanol and other renewable fuels, and as part of an agricultural system that alters the climate through its impact on biogeophysical and biogeochemical properties of the terrestrial ecosystem. Few Earth System Models (ESMs) represent such crops, however. In this study, we expand the Energy Exascale Earth System Land Model to include perennial bioenergy crops with a high potential for mitigating climate change. We focus on high-productivity miscanthus and switchgrass, estimating various parameters associated with their different growth stages and performing a global sensitivity analysis to identify and optimize these parameters. The sensitivity analysis identifies five parameters associated with phenology, carbon/nitrogen allocation, stomatal conductance, and maintenance respiration as the most sensitive parameters for carbon and energy fluxes. We calibrated and validated the model against observations and found that the model closely captures the observed seasonality and the magnitude of carbon fluxes. The validated model represents the latent heat flux fairly well, but sensible heat flux for miscanthus is not well captured. Finally, we validated the model against observed leaf area index (LAI) and harvest amount and found modeled LAI captured observed seasonality, although the model underestimates LAI and harvest amount. This work provides a foundation for future ESM analyses of the interactions between perennial bioenergy crops and carbon, water, and energy dynamics in the larger Earth system, and sets the stage for studying the impact of future biofuel expansion on climate and terrestrial systems.

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