應用主成份 析評估氣候變遷對作物產量因子之影響; Application of factor analysis in climate change impact assessment of crop yields in northern Taiwan

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题名:	應用主成份析評估氣候變遷對作物產量因子之影響;Application of factor analysis in climate change impact assessment of crop yields in northern Taiwan
作者:	方紀棠;Fang,Chi-tang
贡献者:	土木工程學系
关键词:	氣候變遷;水稻;DSSAT作物模式;主成份分析
日期:	2013-07-25
上传时间:	2013-08-22 11:36:38 (UTC+8)
出版者:	國立中央大學
摘要:	氣候變遷為長期氣候特徵發生變化，而農業活動受氣候影響，當氣候發生改變時，溫度、降雨型態等各種氣候因子皆會發生變化，而進一步對農業活動造成影響，如作物品質、產量等。台灣最主要之糧食作物為水稻，其產量為農業生產及糧食安全之重要指標。本研究使用台灣氣候變遷推估與資訊平台建置(TCCIP)所提供之SRES(Special Report on Emissions Scenarios ,SRES)情境模擬之未來氣候分析預測情境，採用A1B之情境，並使用氣象合成模式(WGEN)模擬未來每日降雨量與日均溫，進一步推估日最高溫、日最低溫及日輻射量。本研究利用The Decision Support System for Agrotechnology Transfer (DSSAT)模式評估未來氣候變遷下稻作生長天數及產量之變化。 DSSAT模式所需之基本氣象資料下列四項：日輻射量、日最高溫、日最低溫及日降雨量。將影響產量之因子運用多變量統計分析中之主成份分析法，影響產量之因子有開花前之累積日輻射量、開花前之累積生育度數、開花前之累積作物生長需水量、開花前之生長天數、開花後之累積日輻射量、開花後之累積生育度數、開花後之作物生長需水量及開花後之生長天數，進行基期資料(1985~1990)與近未來(2020~2039)資料之主成份分析，分析結果可以得知在氣候變遷前影響產量的主要成因為稻作開花後之溫度。在氣候變遷情境中發現系集模式及CM3模式中影響產量的主要成因為稻作開花前之溫度，而MK3_0模式中影響產量的主要成因為稻作開花前之日輻射量。 Climate change affects all agriculture activities. When long-term climate pattern has changed, the weather factors, such as temperature or rainfall, affect the crop growth and quantity. Paddy rice is the most important crop in Taiwan. It takes about 70% of total agriculture water usage. Therefore, the quantity of crop is an very important analysis index for food security and agriculture management. This study utilizes the Decision Support System for Agrotechnology Transfer (DSSAT) model to analysis the future difference of rice crop growth days and quantity under climate change. The Weather Generator Model (WGEN) was used to generate the base climate input data of DSSAT model, which included daily future rainfall, mean temperature, maximum/minimum temperature and solar radiation factor. The Taiwan Climate Change Projection and Information Platform Project (TCCIP) provides future climate analyze estimation under A1B scenario of Special Report on Emissions Scenarios . To understand the factors impact extent of crop yields before and after climate change, the Principal Component Analysis based on multivariate statistics is applied to quantity effect factor analysis in the period of baseline data (1985~1990) and far future data (2020~2039). The analysis factors included accumulate of solar radiation, growing degree, crop water requirement and growing days in each period of before and after anthesis. Climate change models and CM3 model ensemble affecting rice production mainly because before flowering into the temperature, while MK3_0 modes affect rice production mainly due to the amount of radiation .
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