基于标准化降水蒸散指数的甘肃省干旱时空特征分析
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摘要
为明确气候变化条件下甘肃省不同时间尺度的干旱特征,选用1951-2015年甘肃省33个气象站点逐日气象数据,计算了不同时间尺度的标准化降水蒸散指数SPEI,同时结合Mann-Kendall突变检验、复小波分析、经验正交函数分解、旋转经验正交函数分解等方法,对甘肃省65 a来干旱时空格局特征进行了分析。结果表明:在年际变化趋势方面,甘肃省干旱情势为由干变湿再变干,近年干旱趋势逐渐加重;四季均呈现由干变湿然后变干的趋势,近年春季变干趋势显著;干旱强度在全省范围内主要为轻旱和中旱等级,并表现为局域性轻旱和全域性中旱。在周期性变化方面,甘肃省的干旱时间周期性强弱依次为39、13、7、22 a尺度,但不同时间尺度表现出了不同的干湿震荡规律。在空间格局方面,甘肃省整体上呈西北部干旱缓解、东南部干旱加剧的趋势;春季干旱加剧最明显,冬季次之,夏季和秋季干湿状况基本相似。按照干旱区域敏感性强弱可将甘肃省分为东南地区东部(Ⅰ区)、西北地区(Ⅱ区)、中部地区(Ⅲ区)和东南地区西部(Ⅳ区),其中Ⅲ区呈干旱缓解趋势,其他地区基本呈干旱加剧的趋势。
To better understand the spatio-temporal distribution of drought characteristics under climate change in different time scales in Gansu Province, daily data from 33 meteorological stations for the period of 1951-2015 were used in this study. The standardized precipitation evapotranspiration index(SPEI) was established combining with Mann-Kendall mutation test, complex wavelet analysis, empirical orthogonal function(EOF) and rotated empirical orthogonal function(REOF) method to analyse the spatial and temporal patterns of drought in the past 65 a in Gasnu Province. The results showed that in terms of the inter-annual SPEI changes, it showed a trend to become humid and then dry, and in recent years the drought trend has gradually increased. On the other hand, it was getting wet from dry firstly and then being dry in all of seasons, especially spring(P<0.05) from the seasonal perspective. The drought coverage and the intensity of drought appeared as the features of the local slight drought and domain moderate drought mainly at the annual scale in Gansu. In the time cycle, the time periods in Gansu were 39, 13, 7 a and 22 a in turn decrease on periodicity, but it appeared different oscillation of dry and wet in different time scales. Spatially, the northwestern regions had a humid trend, but it was drier in the southeastern part of Gansu on the contrary. Most regions were getting dry in spring(P<0.05) and winter, and it was similar of dry and wet zones in summer as well as autumn in terms of spatial distribution. According to the strength of arid sensitivity in Gansu, it can be divided into 4 sub-regions: Eastern district of southeastern region(I sub-region), northwestern region(Ⅱ sub-region), central region(Ⅲ sub-region) and western district of southeastern region(Ⅳ sub-region). Drought in Ⅲ sub-region was gradually alleviated, and others showed a trend of being drier.
To better understand the spatio-temporal distribution of drought characteristics under climate change in different time scales in Gansu Province, daily data from 33 meteorological stations for the period of 1951-2015 were used in this study. The standardized precipitation evapotranspiration index(SPEI) was established combining with Mann-Kendall mutation test, complex wavelet analysis, empirical orthogonal function(EOF) and rotated empirical orthogonal function(REOF) method to analyse the spatial and temporal patterns of drought in the past 65 a in Gasnu Province. The results showed that in terms of the inter-annual SPEI changes, it showed a trend to become humid and then dry, and in recent years the drought trend has gradually increased. On the other hand, it was getting wet from dry firstly and then being dry in all of seasons, especially spring(P<0.05) from the seasonal perspective. The drought coverage and the intensity of drought appeared as the features of the local slight drought and domain moderate drought mainly at the annual scale in Gansu. In the time cycle, the time periods in Gansu were 39, 13, 7 a and 22 a in turn decrease on periodicity, but it appeared different oscillation of dry and wet in different time scales. Spatially, the northwestern regions had a humid trend, but it was drier in the southeastern part of Gansu on the contrary. Most regions were getting dry in spring(P<0.05) and winter, and it was similar of dry and wet zones in summer as well as autumn in terms of spatial distribution. According to the strength of arid sensitivity in Gansu, it can be divided into 4 sub-regions: Eastern district of southeastern region(I sub-region), northwestern region(Ⅱ sub-region), central region(Ⅲ sub-region) and western district of southeastern region(Ⅳ sub-region). Drought in Ⅲ sub-region was gradually alleviated, and others showed a trend of being drier.
引文
[1] Wang W,Zhu Y,Xu R,et al.Drought severity change in China during 1961-2012 indicated by SPI and SPEI[J].2015,75(3):2437-2451.
[2] 符淙斌,马柱国.全球变化与区域干旱化[J].大气科学,2008,32(4):752-760.
[3] 钱正安,吴统文,宋敏红,等.干旱灾害和我国西北干旱气候的研究进展及问题[J].地球科学进展,2001,16(1):28-38.
[4] 陈丽丽,刘普幸,姚玉龙,等.1960-2010年甘肃省不同气候区SPI与Z指数的年及春季变化特征[J].生态学杂志,2013,32(03):704-711.
[5] 沈国强,郑海峰,雷振锋.基于SPEI指数的1961-2014年东北地区气象干旱时空特征研究[J].生态学报,2017,37(17):5882-5893.
[6] Miah M G,Abdullah H M,Jeong C.Exploring standardized precipitation evapotranspiration index for drought assessment in Bangladesh [J].Environmental Monitoring and Assessment,2017,189(11):547.
[7] 张运福,房一禾,龚强.基于SPEI指数的辽宁省生长季干旱时空特征[J].生态学杂志,2017,36(1):190-197.
[8] 陈少丹,张利平,汤柔馨,等.基于SPEI和TVDI的河南省干旱时空变化分析[J].农业工程学报,2017,33(24):126-132.
[9] 轩俊伟,郑江华,刘志辉.基于SPEI的新疆干旱时空变化特征[J].干旱区研究,2016,33(2):338-344.
[10] Beguería S,Vicente-Serrano S M,Reig F,et al.Standardized precipitation evapotranspiration index (SPEI) revisited:parameter fitting,evapotranspiration models,tools,datasets and drought monitoring[J],2014,34(10):3001-3023.
[11] 任培贵,张勃,张调风,等.基于SPEI的中国西北地区气象干旱变化趋势分析[J].水土保持通报,2014,34(1):182-187.
[12] 闫研,李忠贤.基于SPEI指数分析华中地区近40a干旱时空分布特征[J].气象科学,2015,35(5):646-652.
[13] 赵林,于家烁,薄岩,等.基于SPEI的湖北省近52年干旱时空格局变化[J].长江流域资源与环境,2015,24(7):1230-1237.
[14] Thornthwaite C W.An approach toward a rational classification of climate[J].Geographical Review,1948,38(1):55-94.
[15] Allen R G,Pereira L S,Raes D,et al.Crop evapotranspiration:guidelines for computing crop water requirements[M].Rome:FAO Irrigation and Drainage Paper 56,1998:300.
[16] 刘珂,姜大膀.基于两种潜在蒸散发算法的SPEI对中国干湿变化的分析[J].大气科学,2015,39(1):23-36.
[17] 李栋梁,刘德祥.甘肃气候.第1版.[M].北京:气象出版社,2000:1-3.
[18] 张煦庭,潘学标,徐琳,等.基于降水蒸发指数的1960-2015年内蒙古干旱时空特征[J].农业工程学报,2017,33(15):190-199.
[19] 余威.气象相似性网络构建及缺失气象要素数据的插补[D].重庆:西南大学,2015.
[20] 司鹏,郝立生,罗传军,等.河北保定气象站长序列气温资料缺测记录插补和非均一性订正[J].气候变化研究进展,2017,13(1):41-51.
[21] 庞新生.缺失数据插补处理方法的比较研究[J].统计与决策,2012,(24):18-22.
[22] 彭思岭.气象要素时空插值方法研究[D].长沙:中南大学,2010.
[23] Hernandez E A,Uddameri V.Standardized precipitation evaporation index (SPEI)-based drought assessment in semi-arid south Texas [J].Environmental Earth Sciences,2014,71(6):2491-2501.
[24] 国家质量监督检验检疫总局,国家标准化管理委员会.GBT20481-2017 气象干旱等级[S].北京:中国标准出版社,2018.
[25] 田甜,黄强,郭爱军,等.基于标准化降水蒸散指数的渭河流域干旱演变特征分析[J].水力发电学报,2016,35(2):16-27.
[26] 刘盈曦,彭贵芬,陈先刚,等.香格里拉未来50a主要气候环境要素变化预估——基于小波分析和多元VAR回归预估模型[J].资源科学,2016,38(9):1754-1767.
[27] 胡永宁,王林和,张国盛,等.毛乌素沙地1969-2009年主要气候因子时间序列小波分析[J].中国沙漠,2013,33(2):390-395.
[28] 黄晚华,杨晓光,李茂松,等.基于标准化降水指数的中国南方季节性干旱近58a演变特征[J].农业工程学报,2010,26(7):50-59.
[29] Norh G R,Bell T L,Cahalan R F,et al.Sampling errors in the estimation of empirical orthogonal functions [J].Monthly Weather Review,1982,110(7):699-706.
[30] Denbo D W,Allen J S.Rotary empirical orthogonal function analysis of currents near the Oregon Coast[J].American Meteorological Society,1984,14(1):35-46.
[31] 魏凤英.现代气候统计诊断与预测技术.第1版.[M].北京:气象出版社,1999:280.
[32] 屠其璞,邓自旺,周晓兰.中国近117年年平均气温变化的区域特征研究[J].应用气象学报,1999,10(S1):35-43.
[33] 杨素英,孙凤华,陈岩.近45a东北地区春季降水异常的气候特征[J].南京气象学院学报,2005,28(2):197-204.
[34] 施雅风,沈永平,李栋梁,等.中国西北气候由暖干向暖湿转型的特征和趋势探讨[J].第四纪研究,2003,23(2):152-164.
[35] 任余龙,石彦军,王劲松,等.1961-2009年西北地区基于SPI指数的干旱时空变化特征[J].冰川冻土,2013,35(4):938-948.
[36] 庄少伟,左洪超,任鹏程,等.标准化降水蒸发指数在中国区域的应用[J].气候与环境研究,2013,18(5):617-625.
[37] 李伟光,侯美亭,陈汇林,等.基于标准化降水蒸散指数的华南干旱趋势研究[J].自然灾害学报,2012,21(4):84-90.
[38] 张玉静,王春乙,张继权.基于SPEI指数的华北冬麦区干旱时空分布特征分析[J].生态学报,2015,35(21):7097-7107.
[39] 杨义,舒和平,马金珠,等.基于Mann-Kendall法和小波分析中小尺度多年气候变化特征研究——以甘肃省白银市近50年气候变化为例[J].干旱区资源与环境,2017,31(5):126-131.
[2] 符淙斌,马柱国.全球变化与区域干旱化[J].大气科学,2008,32(4):752-760.
[3] 钱正安,吴统文,宋敏红,等.干旱灾害和我国西北干旱气候的研究进展及问题[J].地球科学进展,2001,16(1):28-38.
[4] 陈丽丽,刘普幸,姚玉龙,等.1960-2010年甘肃省不同气候区SPI与Z指数的年及春季变化特征[J].生态学杂志,2013,32(03):704-711.
[5] 沈国强,郑海峰,雷振锋.基于SPEI指数的1961-2014年东北地区气象干旱时空特征研究[J].生态学报,2017,37(17):5882-5893.
[6] Miah M G,Abdullah H M,Jeong C.Exploring standardized precipitation evapotranspiration index for drought assessment in Bangladesh [J].Environmental Monitoring and Assessment,2017,189(11):547.
[7] 张运福,房一禾,龚强.基于SPEI指数的辽宁省生长季干旱时空特征[J].生态学杂志,2017,36(1):190-197.
[8] 陈少丹,张利平,汤柔馨,等.基于SPEI和TVDI的河南省干旱时空变化分析[J].农业工程学报,2017,33(24):126-132.
[9] 轩俊伟,郑江华,刘志辉.基于SPEI的新疆干旱时空变化特征[J].干旱区研究,2016,33(2):338-344.
[10] Beguería S,Vicente-Serrano S M,Reig F,et al.Standardized precipitation evapotranspiration index (SPEI) revisited:parameter fitting,evapotranspiration models,tools,datasets and drought monitoring[J],2014,34(10):3001-3023.
[11] 任培贵,张勃,张调风,等.基于SPEI的中国西北地区气象干旱变化趋势分析[J].水土保持通报,2014,34(1):182-187.
[12] 闫研,李忠贤.基于SPEI指数分析华中地区近40a干旱时空分布特征[J].气象科学,2015,35(5):646-652.
[13] 赵林,于家烁,薄岩,等.基于SPEI的湖北省近52年干旱时空格局变化[J].长江流域资源与环境,2015,24(7):1230-1237.
[14] Thornthwaite C W.An approach toward a rational classification of climate[J].Geographical Review,1948,38(1):55-94.
[15] Allen R G,Pereira L S,Raes D,et al.Crop evapotranspiration:guidelines for computing crop water requirements[M].Rome:FAO Irrigation and Drainage Paper 56,1998:300.
[16] 刘珂,姜大膀.基于两种潜在蒸散发算法的SPEI对中国干湿变化的分析[J].大气科学,2015,39(1):23-36.
[17] 李栋梁,刘德祥.甘肃气候.第1版.[M].北京:气象出版社,2000:1-3.
[18] 张煦庭,潘学标,徐琳,等.基于降水蒸发指数的1960-2015年内蒙古干旱时空特征[J].农业工程学报,2017,33(15):190-199.
[19] 余威.气象相似性网络构建及缺失气象要素数据的插补[D].重庆:西南大学,2015.
[20] 司鹏,郝立生,罗传军,等.河北保定气象站长序列气温资料缺测记录插补和非均一性订正[J].气候变化研究进展,2017,13(1):41-51.
[21] 庞新生.缺失数据插补处理方法的比较研究[J].统计与决策,2012,(24):18-22.
[22] 彭思岭.气象要素时空插值方法研究[D].长沙:中南大学,2010.
[23] Hernandez E A,Uddameri V.Standardized precipitation evaporation index (SPEI)-based drought assessment in semi-arid south Texas [J].Environmental Earth Sciences,2014,71(6):2491-2501.
[24] 国家质量监督检验检疫总局,国家标准化管理委员会.GBT20481-2017 气象干旱等级[S].北京:中国标准出版社,2018.
[25] 田甜,黄强,郭爱军,等.基于标准化降水蒸散指数的渭河流域干旱演变特征分析[J].水力发电学报,2016,35(2):16-27.
[26] 刘盈曦,彭贵芬,陈先刚,等.香格里拉未来50a主要气候环境要素变化预估——基于小波分析和多元VAR回归预估模型[J].资源科学,2016,38(9):1754-1767.
[27] 胡永宁,王林和,张国盛,等.毛乌素沙地1969-2009年主要气候因子时间序列小波分析[J].中国沙漠,2013,33(2):390-395.
[28] 黄晚华,杨晓光,李茂松,等.基于标准化降水指数的中国南方季节性干旱近58a演变特征[J].农业工程学报,2010,26(7):50-59.
[29] Norh G R,Bell T L,Cahalan R F,et al.Sampling errors in the estimation of empirical orthogonal functions [J].Monthly Weather Review,1982,110(7):699-706.
[30] Denbo D W,Allen J S.Rotary empirical orthogonal function analysis of currents near the Oregon Coast[J].American Meteorological Society,1984,14(1):35-46.
[31] 魏凤英.现代气候统计诊断与预测技术.第1版.[M].北京:气象出版社,1999:280.
[32] 屠其璞,邓自旺,周晓兰.中国近117年年平均气温变化的区域特征研究[J].应用气象学报,1999,10(S1):35-43.
[33] 杨素英,孙凤华,陈岩.近45a东北地区春季降水异常的气候特征[J].南京气象学院学报,2005,28(2):197-204.
[34] 施雅风,沈永平,李栋梁,等.中国西北气候由暖干向暖湿转型的特征和趋势探讨[J].第四纪研究,2003,23(2):152-164.
[35] 任余龙,石彦军,王劲松,等.1961-2009年西北地区基于SPI指数的干旱时空变化特征[J].冰川冻土,2013,35(4):938-948.
[36] 庄少伟,左洪超,任鹏程,等.标准化降水蒸发指数在中国区域的应用[J].气候与环境研究,2013,18(5):617-625.
[37] 李伟光,侯美亭,陈汇林,等.基于标准化降水蒸散指数的华南干旱趋势研究[J].自然灾害学报,2012,21(4):84-90.
[38] 张玉静,王春乙,张继权.基于SPEI指数的华北冬麦区干旱时空分布特征分析[J].生态学报,2015,35(21):7097-7107.
[39] 杨义,舒和平,马金珠,等.基于Mann-Kendall法和小波分析中小尺度多年气候变化特征研究——以甘肃省白银市近50年气候变化为例[J].干旱区资源与环境,2017,31(5):126-131.