珠江流域多尺度极端降水时空特征及影响因子研究

doi:10.13249/j.cnki.sgs.2017.02.015

地理科学 ›› 2017, Vol. 37 ›› Issue (2): 283-291.doi: 10.13249/j.cnki.sgs.2017.02.015

珠江流域多尺度极端降水时空特征及影响因子研究

郑江禹¹(), 张强^2,^3,⁴(), 史培军^2,^3,⁴, 顾西辉¹, 郑泳杰¹

1. 中山大学水资源与环境系,广东广州 510275
2. 北京师范大学环境演变与自然灾害教育部重点实验室,北京 100875
3. 北京师范大学地理科学学部,北京 100875
4. 北京师范大学减灾与应急管理研究院,北京 100875

收稿日期:2016-03-03 修回日期:2016-06-11 出版日期:2017-02-25 发布日期:2017-02-25
作者简介:
作者简介：郑江禹（1993-）,男,江西宜春人,硕士研究生,主要从事气象水文学研究。E-mail：zhengjy37@mail2.sysu.edu.cn
基金资助:
国家自然基金委创新群体项目（41621061）,国家杰出青年科学基金（51425903）资助

Spatiotemporal Characteristics of Extreme Precipitation Regimes and Related Driving Factors in the Pearl River Basin

Jiangyu Zheng¹(), Qiang Zhang^2,^3,⁴(), Peijun Shi^2,^3,⁴, Xihu Gu¹, Yongjie Zheng¹

1.Department of Water Resources and Environment, Sun Yat-sen University, Guangzhou 510275, Guangdong, China
2.Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China
3.Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
4.Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing 100875, China

Received:2016-03-03 Revised:2016-06-11 Online:2017-02-25 Published:2017-02-25
Supported by:
Fund for Creative Research Groups of National Natural Science Foundation of China (41621061);National Science Foundation for Distinguished Young Scholars of China (51425903)

摘要/Abstract

摘要：

基于珠江流域74个气象站点1952~2013年逐日降水和气温数据,采用POT抽样、Mann-Kendall（MK）趋势检验、泊松回归等方法,从降水量级、降水频率及发生时间等方面系统分析了珠江流域年、雨季及旱季3个时间尺度上的极端降水特征,并从降水对温度变化响应及ENSO影响等角度,探讨了极端降水变化特征的机理。研究表明：① 珠江流域极端降水年内分布不均,多发于4~9月,其中6月份发生频率最高;② 珠江流域极端降水频率在雨季及年际间分布较为均匀。但在旱季,珠三角地区极端降水在不同年份差异性较大;③ 在雨季及年际尺度上,极端降水年序列趋势性并不显著;而相对干旱季节,极端降雨量级、发生频次均随年份增加呈显著上升趋势,且发生时间提前。珠江流域农业以水稻(Oryzasativa)种植为主,旱季极端降水增加易导致冬汛及其引起的作物倒伏与农田渍涝等灾害,同时对秋冬防洪提出新的挑战,需要引起人们的关注;④ 温度升高和ENSO事件对珠江流域极端降水过程有显著影响。从ENSO影响的角度讲,在厄尔尼诺年,珠江流域西部极端降水量级和频率增加,而流域东部沿海区域极端降水量级减少,时间延后。

关键词: 极端降水, 集聚性, 泊松过程, ENSO, 珠江流域

Abstract:

Daily precipitation and temperature data of 74 weather stations of the Pearl River Basin in 1952-2013 were analyzed to characterize spatiotemporal characteristics of extreme precipitation in terms magnitude, frequency and occurrence time by using the peaks-over-threshold approach (POT), Mann-Kendall test(MK) and Poisson Regression Model for the whole year, wet season(April-September) and dry season(October-March). In addition, causes behind extreme precipitation changes were investigated by relating spatiotemporal patterns of extreme precipitation to ENSO and large-scale moisture circulation. The results indicate that:1) Extreme precipitation over the Pearl River Basin is in uneven. Precipitation extreme mainly occurs from April to September and highest extreme precipitation regimes can be found in June; 2) The frequency of extreme precipitation across the Pearl River Basin during wet season and whole year is even. However, occurrence rates of extreme precipitation within the Pearl River Delta during dry season tends to be uneven with significant difference in annual frequency of extreme precipitation;3) Magnification of extreme precipitation can be observed during dry season with respect to precipitation magnitude and occurrence rates. Besides, occurrence timing of extreme precipitation regimes tends to be earlier. However, no significant trend can be identified in extreme precipitation during wet season and during the entire year. Winter flood has the potential to causeagriculturalloss. Therefore, wetting tendency of dry season can pose new challenges for regional water resources management; 4) Warming climate across the Pearl River Basin and variations of warm and cold episodes of ENSO have significant effects on extreme precipitation processes. From the perspective of the ENSO’s influence, magnitude and frequency of extreme precipitation over the west of the Pearl River Basin increases in El Ni?o years with decreased magnitude of extreme precipitation in the lower Pearl River Basin.

Key words: extreme precipitation, clustering, poisson process, ENSO, the Pearl River Basin

中图分类号:

P333.2

郑江禹, 张强, 史培军, 顾西辉, 郑泳杰. 珠江流域多尺度极端降水时空特征及影响因子研究[J]. 地理科学, 2017, 37(2): 283-291.

Jiangyu Zheng, Qiang Zhang, Peijun Shi, Xihu Gu, Yongjie Zheng. Spatiotemporal Characteristics of Extreme Precipitation Regimes and Related Driving Factors in the Pearl River Basin[J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(2): 283-291.

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参考文献 19

[1]	Allan R P, Soden B J.Atmospheric warming and the amplification of precipitation extremes[J]. Science, 2008, 321(5895): 1481-1484.
[2]	Easterling D R, Meehl G A, Parmesan C et al. Climate extremes: Observations modelingand impacts[J]. Science, 2000, 289(5487): 2068-2074. doi: 10.1126/science.289.5487.2068 pmid: 11000103
[3]	Chou C. Tu J Y, Tan P H.Asymmetry of tropical precipitation change under global warming[J]. Geophysical Research Letters, 2007, 34(17): 421-425. doi: 10.1029/2007GL030327
[4]	Zhang Qiang, Li Jianfeng, Singh V P et al. Influence of ENSO on precipitation in the East River basin, South China[J]. Journal of Geophysical Research:Atmospheres, 2013, 118(5): 2207-2219. doi: 10.1002/jgrd.50279
[5]	Zhang Q. Xu C Y, Gemmer Metal.Changing properties of precipitation concentration in the pearl river basin,China[J]. Stochastic Environmental Research and Risk Assessment, 2009, 23(3): 377-385. doi: 10.1007/s00477-008-0225-7
[6]	彭俊台, 张强, 刘春玲. 珠江流域降雨特征研究[J]. 人民珠江, 2012, 33(5): 13-17. doi: 10.3969/j.issn.1001-9235.2012.05.003
	[Peng Juntai, Zhang Qiang, Liu Chunling.Changing properties of precipitation regimes over the Pearl River Basin. Pearl River, 2012, 33(5): 13-17.] doi: 10.3969/j.issn.1001-9235.2012.05.003
[7]	陆文秀, 刘丙军, 陈俊凡, 等. 近50a来珠江流域降水变化趋势分析[J]. 自然资源学报, 2014, (1): 80-90. doi: 10.11849/zrzyxb.2014.01.008
	[Lu Wenxiu, Liu Bingjun, Chen Junfan et al. Variation trend of precipitation in the Pearl River Basin in recent 50 years. Journal of Natural Resources, 2014(1): 80-90.] doi: 10.11849/zrzyxb.2014.01.008
[8]	Wang W, Chen X, Shi P et al. Detecting changes in extreme precipitation and extreme streamflow in the Dongjiang River Basin in southern China[J]. Hydrology and Earth System Sciences, 2008, 12(1): 207-221. doi: 10.5194/hess-12-207-2008
[9]	顾西辉, 张强, 孙鹏, 等. 新疆塔河流域洪水量级、频率及峰现时间变化特征、成因及影响[J]. 地理学报, 2015, 70(9): 1390-1401. doi: 10.11821/dlxb201509003
	[Gu Xihui, Zhang Qiang, Sun Peng et al. Magnitude, frequency and timing of floods in the Tarim River,Xinjiang:Characteristics, causes and impacts. Acta Geographica Sinica, 2015, 70(9): 1390-1401.] doi: 10.11821/dlxb201509003
[10]	Qiang Zhang, Jian Fengli, Vijay P S et al. Influence of ENSO on precipitation in the East River basin, SouthChina[J]. Journal of Geophysical Research, 2013, 118(5): 2207-2219. doi: 10.1002/jgrd.50279
[11]	Zhang Q, Xu C Y, Zhang Z.Observed changes of drought/wetness episodes in the Pearl River basin, China, using the standardized precipitation index and aridity index[J]. Theoretical&Applied Climatology, 2009, 98(1/2): 89-99. doi: 10.1007/s00704-008-0095-4
[12]	Zhang Qiang, Qi Tianyao, Singh V P et al. Regional frequency analysis of droughts in China: a multivariate perspective[J]. Water Resources Management, 2015, 29(6): 1767-1787. doi: 10.1007/s11269-014-0910-x
[13]	苏怀智, 王锋, 刘红萍. 基于POT模型建立大坝服役性态预警指标[J].水利学报, 2012, 43(8).
	[Su Huaizhi, Wang Feng, Liu Hongping.Early-warning index for dam service behavior based on POT model. ShuiLi XueBao,2012,43(8):974-986.]
[14]	Hamed K H, Rao A R.A modified Mann-Kendall trend test for autocorrelated data[J]. Journal of Hydrology, 1998, 204(1/4): 182-196. doi: 10.1016/S0022-1694(97)00125-X
[15]	Mitchell J M, Dzerdzeevskii B, Flohn H.Climate change[M].WHO Technical Note 79,World Meteorological Organization: Geneva,1966:79.
[16]	陈小龙. 泊松回归模型[A].科技资讯,2012,17.
	[Chen Xiaolong.Poisson regression model. Science& Technology Information, 2012,17.]
[17]	Villarini G, Smith J A, Vecchi G A.Changing frequency of heavy rainfall over the central United States[J]. Journal of Climate, 2013, 26(1): 351-357. doi: 10.1175/JCLI-D-12-00043.1
[18]	Zhang Qiang, Xiao Mingzhong, Singh V P et al. Regionalization and spatial changing properties of droughts across the Pearl River basin ,China [J]. Journal of Hydrology, 2012, 472-473(24): 355-366. doi: 10.1016/j.jhydrol.2012.09.054
[19]	Zhang Qiang, Xu Chongyu, Chen Xiaohong et al. Statistical behaviors of precipitation regimes in China and their links with atmospheric circulation 1960-2005[J]. International Journal of Climatology, 2011, 31(11): 1665-1678. doi: 10.1002/joc.2193

珠江流域多尺度极端降水时空特征及影响因子研究

Spatiotemporal Characteristics of Extreme Precipitation Regimes and Related Driving Factors in the Pearl River Basin

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