DSSAT模式在预測水稻産量及氣候變遷衝擊評估之通用性探討

The Applicability of DSSAT Model to Predict the Production of Rice and to Evaluate the Impact of Climate Change

姚銘輝(Ming-Hwi Yao) ； 盧虎生(Huu-Shen Lur) ； 朱鈞(Chun Chu) ； 蔡金川(Jin-Chuan Tsai)

《中華農業研究》 49卷4期 (2000/12) Pp. 16-28

https://doi.org/10.29951/JARC.200012.0002

摘要

對農業生産而言，氣候具有二種意義，若能有效管理則為一種資源，相反的，則是一種危害。大氣二氧化碳濃度在過去200年來，由280ppm增加到350ppm，最近35年和其他溫室氣體快速增加，由315ppm迅速增加到350ppm，增加的二氧化碳濃度經由直接刺激光合作用進行而影響作物生長，這種生理反應一般稱為“二氧化碳肥料效應”，在其他條件配合下可使作物生育更好及更有活力，進而提高乾物重産量。此外，提高二氧化碳也可透過對氣候因子（例如溫度及降水）的影響，間接影響作物生長。水稻是台灣地區最主要農作物，探討未來氣候變遷對水稻生産相當重要。本研究利用DSSAT生長模式並和大氣環流模式相結合，同時由氣象因子的敏感度分析瞭解對産量的影響，結果顯示提高二氧化碳濃度有助於水稻增産，但提高溫度則相反。而由DSSAT模式預測台中地區水稻産量，在二倍現行二氧化碳濃度下，GISS模式預測為增産2.5%，GFDL為4.2%，UKMO為4.0%。

關鍵字

氣候變遷 ； 溫室效應 ； 二氧化碳肥料效應 ； 大氣環流模式

並列摘要

For agriculture production, climate must be managed both, as a resource to be used wisely on the one hand, and a hazard to be dealt with on the other. Concentration of atmospheric CO2 has increased from about 280 to 350 ppm in the last 200 year and has increased rapidly from 315 to 350 ppm during the past 35 year along with other ”greenhouse” trace gases. Increased CO2 concentration can affect plant growth due to directly stimulation of photosynthesis. These physiological responses known as ”CO2-fertilization effects” can produce larger and more vigorous plant as well as higher yield of total dry matter. In addition, elevated CO2 can also affect plant growth indirectly through alteration of climatic factors such as temperature and precipitation. For this reason, it is very important to understand the impact of climate change on agriculture. Because rice is one of the most important grain crops in Taiwan, it is important to understand the impact of weather and climate change on rice production. In this study DSSAT (Decision support system for agrotechnology transfer) rice model and GCM (General circulation model) were combined to predict the production of rice and to evaluate of climate change. In addition, the sensitivity analysis simulation was used to demonstrate the effect of change in each weather variable alone on rice yield performance. The result showed an increase in CO2 level could increase yields while an increase in temperature would reduced yields. Rice production in Taichung region was predicted by the DSSAT model to change by +2.5, +4.2 and +4.0% under the GFDL, GISS and UKMO 2(superscript *)CO2 scenarios, respectively.

並列關鍵字

Climate change ； Greenhouse effect ； CO2 fertilization effect ； General circulation model