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| Titel |
Modeling agriculture in the Community Land Model |
| VerfasserIn |
B. Drewniak, J. Song, J. Prell, V. R. Kotamarthi, R. Jacob |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 6, no. 2 ; Nr. 6, no. 2 (2013-04-19), S.495-515 |
| Datensatznummer |
250017805
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| Publikation (Nr.) |
 copernicus.org/gmd-6-495-2013.pdf |
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| Zusammenfassung |
| The potential impact of climate change on agriculture is uncertain. In
addition, agriculture could influence above- and below-ground carbon
storage. Development of models that represent agriculture is necessary to
address these impacts. We have developed an approach to integrate
agriculture representations for three crop types – maize, soybean, and
spring wheat – into the coupled carbon–nitrogen version of the Community
Land Model (CLM), to help address these questions. Here we present the new
model, CLM-Crop, validated against observations from two AmeriFlux sites in
the United States, planted with maize and soybean. Seasonal carbon fluxes
compared well with field measurements for soybean, but not as well for
maize. CLM-Crop yields were comparable with observations in countries such
as the United States, Argentina, and China, although the generality of the
crop model and its lack of technology and irrigation made direct comparison
difficult. CLM-Crop was compared against the standard CLM3.5, which
simulates crops as grass. The comparison showed improvement in gross primary
productivity in regions where crops are the dominant vegetation cover. Crop
yields and productivity were negatively correlated with temperature and
positively correlated with precipitation, in agreement with other modeling
studies. In case studies with the new crop model looking at impacts of
residue management and planting date on crop yield, we found that increased
residue returned to the litter pool increased crop yield, while reduced
residue returns resulted in yield decreases. Using climate controls to
signal planting date caused different responses in different crops. Maize
and soybean had opposite reactions: when low temperature threshold resulted
in early planting, maize responded with a loss of yield, but soybean yields
increased. Our improvements in CLM demonstrate a new capability in the model
– simulating agriculture in a realistic way, complete with fertilizer and
residue management practices. Results are encouraging, with improved
representation of human influences on the land surface and the potentially
resulting climate impacts. |
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