中文摘要：

干旱已成为西南农业区的具有一定破坏力的自然灾害,研究干旱的时空变化对该区干旱的评估、预测具有重要的现实意义。根据西南农业区1962~2012年月气象资料,利用Penman-Monteith公式计算蒸散发和标准化降水蒸散指数（SPEI）值;采用线性回归、Mann-Kendall方法、小波分析和旋转经验正交函数（REOF）等方法分析了西南农业区干旱时空变化。研究结果表明：（1）西南农业区整体呈干旱化趋势;2000年以来年、四季变干趋势更加明显;秋季变干趋势显著;年均SPEI指数不存在显著突变点;年和四季干湿变化均存在2~8 a左右的振荡周期。（2）根据REOF分解的前6个空间模态,将西南农业区划分成6个干湿特征区域：云南高原东部区、汉中盆地区、东部山地区、云南高原西部区、四川盆地区、贵州高原区;其中云南高原东部区变干趋势显著,汉中盆地区和东部山地区有变湿润趋势,但并不明显;6个分区干湿变化普遍存在2~6 a左右的振荡周期。研究结果可为西南农业区防旱、抗旱提供科学参考。

英文摘要：

Drought, one of the most devastating natural hazards, has caused tremendous damage in Southeast China. It is of great importance to evaluate and investigate the spatial and temporal evolution of drought in Southeast China. Based on the monthly precipitation and temperature data in Southeast China during 1962-2012, this study applied the standard precipitation and evaporation index（SPEI）, linear analysis, Mann-Kendall test, wavelet analysis as well as rotated empirical orthogonal function（REOF） methods to analyze drought dynamics in Southeast China. The results showed that：（1） A significant rising trend of drought frequency has been detected in Southeast both at annual and seasonal scales, especially since 2000; autumn and winter presented frequent occurrence of drought in Southeast while the trend of drought in autumn has become more significant; there was no obvious mutation point in the annual SPEI; 2 to 8 years period of oscillation has been found in the area when researching the annual and seasonal variation of drought.（2） According to the front six spatial modes disassembled from REOF, we divided Southwest China into six different areas with totally different aridity and wetness features： the eastern Yunnan Plateau, Hanzhong Basin, the eastern mountainous area, the western Yunnan Plateau,Sichuan Basin and the Guizhou Plateau. Among the six different areas, the eastern Yunnan plateau has an obvious dry trend, while Hanzhong basin and eastern mountain area have a wet trend（but not obvious）; also, the variation of the six areas generally exists 2-6 years period of oscillation. The study will contribute to exploring the spatial-temporal variability of dryness conditions in Southeast China while allowing a prediction of possible future drought distribution and trends under global climate change.