基于联合干旱指数的黄河流域干旱时空特征
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摘要
依据黄河流域100个气象站1961—2013年的降水数据,采用高斯Copula函数并联合5个时间尺度的标准降水指数(SPI),构建了联合干旱指数(JDI),进而剖析流域干旱时空演变特性和评估历史时期干旱特征(历时、烈度)及联合特征分布规律。结果表明:JDI具备短时间尺度SPI对干旱事件开始时刻的快速捕捉能力,同时考虑到长时间尺度SPI的时间滞后性,在捕捉干旱传播及演变过程方面体现出较大优势;从时空分布特征来看,黄河流域中南部地区在20世纪90年代存在明显的干旱高频区,渭河、泾河、洛河流域存在以年代为周期的旱涝交替现象;黄河流域西北部地区、北部河套平原和大黑河子流域及中南部少数地区比其他地区更易发生长历时、大烈度干旱事件;变动阈值水平能引起历时和烈度较大的变化幅度,而联合特征对阈值水平变化的响应不敏感。
According to daily precipitation data of 100 meteorological stations in the Yellow River basin from 1961 to 2013, using Gaussian Copula function and combining standard precipitation indexes(SPI) on 5 time scales, this paper constructed the Joint Drought Index(JDI), further analyzed the spatial-temporal drought evolution characteristics and evaluated the distribution laws of historical period drought characters(duration and intensity) and the joint drought characters. The results show that JDI has the ability to quickly capture the onset of drought events on the short time scale SPI and can take into consideration the time lag of the long time scale SPI, which shows a good advantage in capturing the propagation and evolution of drought; from the perspective of spatial-temporal distribution characteristics, the central and southern regions of the basin have significant high drought frequency areas in the 1990 s, the Weihe River basin and Jinghe River basin and Luohe River basin have the drought and flood alternation with the period; the northwestern region of the basin, the northern Hetao plain and Dahei River basin and a few areas in the south-central region are more vulnerable to prolonged and severe drought events than that of other regions; the variation of threshold level can lead to large variation range of drought features, while the joint features are insensitive to their responses.
According to daily precipitation data of 100 meteorological stations in the Yellow River basin from 1961 to 2013, using Gaussian Copula function and combining standard precipitation indexes(SPI) on 5 time scales, this paper constructed the Joint Drought Index(JDI), further analyzed the spatial-temporal drought evolution characteristics and evaluated the distribution laws of historical period drought characters(duration and intensity) and the joint drought characters. The results show that JDI has the ability to quickly capture the onset of drought events on the short time scale SPI and can take into consideration the time lag of the long time scale SPI, which shows a good advantage in capturing the propagation and evolution of drought; from the perspective of spatial-temporal distribution characteristics, the central and southern regions of the basin have significant high drought frequency areas in the 1990 s, the Weihe River basin and Jinghe River basin and Luohe River basin have the drought and flood alternation with the period; the northwestern region of the basin, the northern Hetao plain and Dahei River basin and a few areas in the south-central region are more vulnerable to prolonged and severe drought events than that of other regions; the variation of threshold level can lead to large variation range of drought features, while the joint features are insensitive to their responses.
引文
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[17] 程亮,金菊良,郦建强,等.干旱频率分析研究进展[J].水科学进展,2013,24(2):296-302.
[18] SHIAU J T.Fitting Drought Duration and Severity with Two-Dimensional Copulas[J].Water Resources Management,2006,20(5):795-815.
[2] REINMAN S L.Intergovernmental Panel on Climate Change (IPCC)[J].Encyclopedia of Energy Natural Resource & Environmental Economics,2013,26(2):48-56.
[3] 黄荣辉,杜振彩.全球变暖背景下中国旱涝气候灾害的演变特征及趋势[J].自然杂志,2010,32(4):187-195.
[4] 杨肖丽,郑巍斐,林长清,等.基于统计降尺度和SPI的黄河流域干旱预测[J].河海大学学报(自然科学版),2017,45(5):377-383.
[5] 魏甡生.中国历史上的干旱[J].知识就是力量,2009(4):16-18.
[6] 陆桂华,闫桂霞,吴志勇,等.基于Copula函数的区域干旱分析方法[J].水科学进展,2010,21(2):188-193.
[7] HAYES M J,SVOBODA M D,WILHITE D A,et al.Monitoring the 1996 Drought Using the Standardized Precipitation Index[J].Bulletin of the American Meteorological Society,1999,80(3):429-438.
[8] MO K C,LETTENMAIER D P.Objective Drought Classification Using Multiple Land Surface Model[J].Journal of Hydrometeorology,2014,15(3):990-1010.
[9] HAO Z,AGHAKOUCHAK A.Multivariate Standardized Drought Index:A Parametric Multi-Index Model[J].Advances in Water Resources,2013,57(9):12-18.
[10] JOE H.Multivariate Models and Dependence Concepts[J].Technometrics,1998,40(4):353.
[11] KAO S C,GOVINDARAJU R S.A Copula-Based Joint Deficit Index for Droughts[J].Journal of Hydrology,2010,380(1):121-134.
[12] NELSEN R B.An Introduction to Copulas[J].Technometrics,2000,42(3):317-317.
[13] YEVJEVICH V.An Objective Approach to Definitions and Investigations of Continental Hydrologic Droughts[J].Journal of Hydrology,1967,7(3):491-494.
[14] LIU X F,WANG S X,ZHOU Y,et al.Spatial Analysis of Meteorological Drought Return Periods in China Using Copulas[J].Natural Hazards,2016,80(1):367-388.
[15] CHEN X,FAN Y.Estimation of Copula-Based Semiparametric Time Series Models[J].Journal of Econometrics,2006,130(2):307-335.
[16] MASSEYJR F.The Kolmogorov-Smirnov Test for Goodness of Fit[J].Publications of the American Statistical Association,1951,46(3):68-78.
[17] 程亮,金菊良,郦建强,等.干旱频率分析研究进展[J].水科学进展,2013,24(2):296-302.
[18] SHIAU J T.Fitting Drought Duration and Severity with Two-Dimensional Copulas[J].Water Resources Management,2006,20(5):795-815.
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