Abstract

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. The Energy Exascale Earth System Model (E3SM) Land Model (ELM) does not represent perennial bioenergy crops, however. In this study, we expand ELM’s crop model to include perennial bioenergy crops whose production increases in modeled socioeconomic pathways owing to their 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 eight parameters associated with phenology, carbon/nitrogen allocation, and photosynthetic capacity as the most sensitive parameters for carbon and energy fluxes. We calibrated the model against observations collected at the University of Illinois Energy Farm for carbon and energy fluxes, and found that the model closely captures the observed seasonality and the magnitude of carbon fluxes. The model accurately represents the seasonality of energy fluxes, but their magnitude is not well captured. This work provides a foundation for future analyses of the interactions between perennial bioenergy crops and carbon, water, and energy dynamics in the larger earth system and can also be used for studying the impact of future biofuel expansion on climate and terrestrial systems.

Highlights

  • Introduction inISAM model and used it to study the spatial and temporal patterns in biomass yield in the eastern United States

  • A total of twenty perennial crop parameters related to crop phenology, CN allocation, and photosynthetic capacity were selected for the surrogate construction, global sensitivity analysis and model calibration (Table 1)

  • The modified ELM model captures this longer growing season. Leaf onset for both perennial bioenergy cropping systems starts at approximately the same time but switchgrass gross primary productivity (GPP) increases and declines earlier than miscanthus

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Summary

Introduction

The model is calibrated to simulate carbon and energy fluxes by developing ELM surrogates, conducting a GSA, and performing Bayesian calibration using observational data. A total of twenty perennial crop parameters related to crop phenology, CN allocation, and photosynthetic capacity were selected for the surrogate construction, global sensitivity analysis and model calibration (Table 1).

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