A Distributed Cotton Growth Model Developed from GOSSYM and Its Parameter Determination
A Distributed Cotton Growth Model Developed from GOSSYM and Its Parameter Determination
复制标题
GOSSYM分布式棉花生长模型及其参数确定
DOI：
10.2134/agronj2011.0250
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发表时间：
2012
期刊：
影响因子：
2.1
通讯作者：
A. N. Samel
中科院分区：
文献类型：
--
作者：
Xin‐Zhong Liang;Wei Gao;K. R. Reddy;K. Kunkel;D. Schmoldt;A. N. Samel
棉花产量预测在不断变化的气候条件下的生产需要一个耦合的建模系统，代表气候-棉花的相互作用。现有的棉花生长模型GOSSYM存在着不能与气候模型有效耦合的缺陷。我们开发了一个地理分布的棉花生长模型，从原来的GOSSYM和优化耦合区域气候天气研究预测模型（CWRF）。包括软件的重新设计、物理的改进和CWRF与GOSSYM一致耦合的参数的确定。通过引入最佳物理表示和观测估计，将GOSSYM中的输入参数简化为2个参数，即土壤表层2 m的初始NO3含量和灌溉水量与潜在蒸散量的比值。这两个参数的地理分布是通过优化来确定的，该优化使模拟棉花产量的模型误差最小化。结果表明，重新开发的GOSSYM真实地再现了30 km网格内棉花平均产量的地理分布，在美国大部分棉花带的观测值的±10%以内，而原始GOSSYM在州一级高估了27 ~ 135%，总体高估了92%。这两个模型产生的年际产量变化具有可比性的幅度，但是，模拟和观察到的年际异常之间的时间对应关系是更现实的重新开发比原来的GOSSYM，因为显着（P = 0.05）的相关性被确定为艾德在87和40%的收获网格，分别。重新开发的GOSSYM为进一步改进和应用CWRF-GOSSYM耦合系统研究气候-棉花相互作用提供了一个起点。
Prediction of cotton (Gossypium hirsutum L.) production under a changing climate requires a coupled modeling system that represents climate–cotton interactions. Th e existing cotton growth model GOSSYM has drawbacks that prohibit its eff ective 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). Th is included soft ware redesign, physics improvement, and parameter specifi cation for consistent coupling of CWRF and GOSSYM. Th rough 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. Th e geographic distributions of these two parameters are determined by optimization that minimizes model errors in simulating cotton yields. Th e 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 signifi cant (P = 0.05) correlations were identifi ed in 87 and 40% of harvest grids, respectively. Th e redeveloped GOSSYM provides a starting point for additional improvements and applications of the coupled CWRF–GOSSYM system to study climate–cotton interactions.