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  • Samel, Arthur N.  (2)
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  • 1
    In: Agronomy Journal, Wiley, Vol. 104, No. 3 ( 2012-05), p. 675-683
    Abstract: Climate variability and changes affect crop yields by causing climatic stresses during various stages of the plant life cycle. A crop growth model must be able to capture the observed relationships between crop yields and climate stresses before its credible use as a prediction tool. This study evaluated the ability of the geographically distributed cotton growth model redeveloped from GOSSYM in simulating U.S. cotton ( Gossypium hirsutum L.) yields and their responses to climate stresses during 1979 to 2005. Driven by realistic climate conditions, the model reproduced long‐term mean cotton yields within ± 10% of observations at the 30‐km model resolution across virtually the entire U.S. Cotton Belt and correctly captured the critical dependence of their geographic distributions on regional climate characteristics. Significant correlations between simulated and observed interannual variations were found across 87% of the total harvest grids. The model also faithfully represented the predictive role of July to August air temperature and August to September soil temperature anomalies on interannual cotton yield changes on unirrigated lands, with a similar but weaker predictive signal for irrigated lands as observed. The modeled cotton yields exhibited large, positive correlations with July to August leaf area index. These results indicate the model's ability to depict the regional impact of climate stresses on cotton yields and suggest the potential predictive value of satellite retrievals. They also provide a baseline reference for further model improvements and applications in the future study of climate–cotton interactions.
    Type of Medium: Online Resource
    ISSN: 0002-1962 , 1435-0645
    Language: English
    Publisher: Wiley
    Publication Date: 2012
    detail.hit.zdb_id: 1471598-3
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  • 2
    In: Agronomy Journal, Wiley, Vol. 104, No. 3 ( 2012-05), p. 661-674
    Abstract: Prediction of cotton ( Gossypium hirsutum L.) production under a changing climate requires a coupled modeling system that represents climate–cotton interactions. The existing cotton growth model GOSSYM has drawbacks that prohibit its effective coupling with climate models. We developed a geographically distributed cotton growth model from the original GOSSYM and optimized it for coupling with the regional Climate–Weather Research Forecasting model (CWRF). This included software redesign, physics improvement, and parameter specification for consistent coupling of CWRF and GOSSYM. Through incorporation of the best available physical representations and observational estimates, the long list of inputs in the original GOSSYM was reduced to two parameters, the initial NO 3 amount in the top 2 m of soil and the ratio of irrigated water amount to potential evapotranspiration. The geographic distributions of these two parameters are determined by optimization that minimizes model errors in simulating cotton yields. The result shows that the redeveloped GOSSYM realistically reproduces the geographic distribution of mean cotton yields in 30‐km grids, within ± 10% of observations across most of the U.S. Cotton Belt, whereas the original GOSSYM overestimated yields by 27 to 135% at the state level and 92% overall. Both models produced interannual yield variability with comparable magnitude; however, the temporal correspondence between modeled and observed interannual anomalies was much more realistic in the redeveloped than the original GOSSYM because significant ( P = 0.05) correlations were identified in 87 and 40% of harvest grids, respectively. The redeveloped GOSSYM provides a starting point for additional improvements and applications of the coupled CWRF–GOSSYM system to study climate–cotton interactions.
    Type of Medium: Online Resource
    ISSN: 0002-1962 , 1435-0645
    Language: English
    Publisher: Wiley
    Publication Date: 2012
    detail.hit.zdb_id: 1471598-3
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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