Growing C4 perennial grass for bioenergy using a new Agro-BGC ecosystem model
Abstract
Accurate, spatially gridded estimates of bioenergy crop yields require 1) biophysically accurate crop growth models and 2) careful parameterization of unavailable inputs to these models. To meet the first requirement we have added the capacity to simulate C4 perennial grass as a bioenergy crop to the Biome-BGC ecosystem model. This new model, hereafter referred to as Agro-BGC, includes enzyme driven C4 photosynthesis, individual live and dead leaf, stem, and root carbon/nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that effectively simulates fertilization, harvest, fire, and incremental irrigation. There are four Agro-BGC vegetation parameters that are unavailable for Panicum virgatum (switchgrass), and to meet the second requirement we have optimized the model across multiple calibration sites to obtain representative values for these parameters. We have verified simulated switchgrass yields against observations at three non-calibration sites in IL. Agro-BGC simulates switchgrass growth and yield at harvest very well at a single site. Our results suggest that a multi-site optimization scheme would be adequate for producing regional-scale estimates of bioenergy crop yields on high spatial resolution grids.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2009
- Bibcode:
- 2009AGUFM.B43B0381D
- Keywords:
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- 0402 BIOGEOSCIENCES / Agricultural systems;
- 0414 BIOGEOSCIENCES / Biogeochemical cycles;
- processes;
- and modeling