Parameterizing Perennial Bioenergy Crops in Version 5 of the Community Land Model Based on Site‐Level Observations in the Central Midwestern United States
Abstract
Abstract With projected expansion of biofuel production at a global scale, there is a pressing need to develop adequate representation of bioenergy crops in land surface models to help effectively quantify the biogeophysical and biogeochemical effects of its associated land use changes. This study implements two new perennial bioenergy crops, Miscanthus and switchgrass, into the Community Land Model Version 5 based on site‐level observations from the midwestern United States by modifying parameters associated with photosynthesis, phenology, allocation, decomposition, and carbon cost of nitrogen uptake and integrating concomitantly land management practices. Sensitivity analyses indicate that carbon and energy fluxes of the perennial crops are most sensitive to photosynthesis and phenology parameters. Validation of simulated fluxes against site‐level measurements demonstrates that the model is capable of capturing the overall patterns of energy and carbon fluxes, as well as physiological transitions from leaf emergence to senescence. Compared to annual crops, perennial crops feature longer growing season, greater leaf areas, and higher productivity, leading to increased transpiration, lower annual runoff, and larger carbon uptake. The model simulations suggest that with higher CO 2 assimilation rates and lower demands for nutrients and water, high‐yielding perennial crops are promising alternatives of bioenergy feedstocks compared to traditionalmore »
- Authors:
-
- Atmospheric Sciences and Global Change Division Pacific Northwest National Laboratory Richland WA USA
- Joint Global Change Research Institute Pacific Northwest National Laboratory College Park MD USA
- Department of Natural Resources and Environmental Sciences University of Illinois at Urbana‐Champaign Urbana IL USA, National Center for Supercomputing Applications University of Illinois at Urbana‐Champaign Urbana IL USA
- Agricultural Research Service, Global Change and Photosynthesis Research Unit U.S. Department of Agriculture Urbana IL USA, Department of Plant Biology University of Illinois at Urbana‐Champaign Urbana IL USA, Carl R. Woese Institute for Genomic Biology University of Illinois at Urbana‐Champaign Urbana IL USA
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1581191
- Alternate Identifier(s):
- OSTI ID: 1581192
- Grant/Contract Number:
- 59534
- Resource Type:
- Published Article
- Journal Name:
- Journal of Advances in Modeling Earth Systems
- Additional Journal Information:
- Journal Name: Journal of Advances in Modeling Earth Systems Journal Volume: 12 Journal Issue: 1; Journal ID: ISSN 1942-2466
- Publisher:
- American Geophysical Union (AGU)
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Cheng, Yanyan, Huang, Maoyi, Chen, Min, Guan, Kaiyu, Bernacchi, Carl, Peng, Bin, and Tan, Zeli. Parameterizing Perennial Bioenergy Crops in Version 5 of the Community Land Model Based on Site‐Level Observations in the Central Midwestern United States. United States: N. p., 2020.
Web. doi:10.1029/2019MS001719.
Cheng, Yanyan, Huang, Maoyi, Chen, Min, Guan, Kaiyu, Bernacchi, Carl, Peng, Bin, & Tan, Zeli. Parameterizing Perennial Bioenergy Crops in Version 5 of the Community Land Model Based on Site‐Level Observations in the Central Midwestern United States. United States. https://doi.org/10.1029/2019MS001719
Cheng, Yanyan, Huang, Maoyi, Chen, Min, Guan, Kaiyu, Bernacchi, Carl, Peng, Bin, and Tan, Zeli. Sat .
"Parameterizing Perennial Bioenergy Crops in Version 5 of the Community Land Model Based on Site‐Level Observations in the Central Midwestern United States". United States. https://doi.org/10.1029/2019MS001719.
@article{osti_1581191,
title = {Parameterizing Perennial Bioenergy Crops in Version 5 of the Community Land Model Based on Site‐Level Observations in the Central Midwestern United States},
author = {Cheng, Yanyan and Huang, Maoyi and Chen, Min and Guan, Kaiyu and Bernacchi, Carl and Peng, Bin and Tan, Zeli},
abstractNote = {Abstract With projected expansion of biofuel production at a global scale, there is a pressing need to develop adequate representation of bioenergy crops in land surface models to help effectively quantify the biogeophysical and biogeochemical effects of its associated land use changes. This study implements two new perennial bioenergy crops, Miscanthus and switchgrass, into the Community Land Model Version 5 based on site‐level observations from the midwestern United States by modifying parameters associated with photosynthesis, phenology, allocation, decomposition, and carbon cost of nitrogen uptake and integrating concomitantly land management practices. Sensitivity analyses indicate that carbon and energy fluxes of the perennial crops are most sensitive to photosynthesis and phenology parameters. Validation of simulated fluxes against site‐level measurements demonstrates that the model is capable of capturing the overall patterns of energy and carbon fluxes, as well as physiological transitions from leaf emergence to senescence. Compared to annual crops, perennial crops feature longer growing season, greater leaf areas, and higher productivity, leading to increased transpiration, lower annual runoff, and larger carbon uptake. The model simulations suggest that with higher CO 2 assimilation rates and lower demands for nutrients and water, high‐yielding perennial crops are promising alternatives of bioenergy feedstocks compared to traditional annual crops not only for mitigating climate change but also for environmental conservation purposes by reducing fertilizer application and therefore alleviating surface‐ and ground‐water contaminations. Although the local‐scale simulations shed light on potential benefits of using perennial grasses as bioenergy feedstocks, quantifying consequences of their plantations at larger scales warrants additional investigation.},
doi = {10.1029/2019MS001719},
journal = {Journal of Advances in Modeling Earth Systems},
number = 1,
volume = 12,
place = {United States},
year = {Sat Jan 04 00:00:00 EST 2020},
month = {Sat Jan 04 00:00:00 EST 2020}
}
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