Adapting SOYGRO V5.42 for prediction under climate change conditions
- Univ. of Florida, Gainesville, FL (United States)
In some studies of the impacts of climate change on global crop production, crop growth models were empirically adapted to improve their response to increased CO{sub 2} concentration and air temperature. This chapter evaluates the empirical adaptations of the photosynthesis and evapotranspiration (ET) algorithms used in the soybean [Glycine max (L.) Merr.] model, SOYGRO V5.42, by comparing it with a new model that includes mechanistic approaches for these two processes. The new evapotranspiration-photosynthesis sub-model (ETPHOT) uses a hedgerow light interception algorithm, a C{sub 3}-leaf biochemical photosynthesis submodel, and predicts canopy ET and temperatures using a three-zone energy balance. ETPHOT uses daily weather data, has an internal hourly time step, and sums hourly predictions to obtain daily gross photosynthesis and ET. The empirical ET and photosynthesis curves included in SOYGRO V5.42 for climate change prediction were similar to those predicted by the ETPHOT model. Under extreme conditions that promote high leaf temperatures, like in the humid tropics. SOYGRO V5.42 overestimated daily gross photosynthesis response to CO{sub 2} compared with the ETPHOT model. SOYGRO V5.42 also slightly overestimated daily gross photosynthesis at intermediate air temperatures and ambient CO{sub 2} concentrations. 80 refs., 12 figs.
- OSTI ID:
- 248048
- Report Number(s):
- CONF-9211217-; ISBN 0-89118-126-1; TRN: IM9628%%148
- Resource Relation:
- Conference: 1992 annual meeting of the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Minneapolis, MN (United States), 1-6 Nov 1992; Other Information: PBD: 1995; Related Information: Is Part Of Climate change and agriculture: Analysis of potential international impacts; PB: 399 p.; ASA special publication, Number 59
- Country of Publication:
- United States
- Language:
- English
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