| 引用本文: | 张向明,粟晓玲,张更喜.基于SRI与Copula函数的黑河流域水文干旱等级划分及特征分析[J].灌溉排水学报,2019,38(5):107-113. |
| ZHANG Xiangming,SU Xiaoling,ZHANG Gengxi.基于SRI与Copula函数的黑河流域水文干旱等级划分及特征分析[J].灌溉排水学报,2019,38(5):107-113. |
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| 摘要: |
| 【目的】基于SRI对黑河流域水文干旱进行等级划分及特征分析。【方法】利用2种不同的径流丰枯等级分类方法，对黑河流域莺落峡水文站的径流资料进行概率统计分析，提出基于SRI的水文干旱等级划分标准（标准1），分别采用标准1和基于标准化降水指数（SPI）的干旱等级划分标准（标准2），识别水文干旱历时、烈度、烈度峰值3个干旱特征变量，利用Copula函数进行水文干旱多变量联合分布研究，选取RMSE、AIC、BIC准则作为联合分布拟合优度检验的判别依据优选Copula函数类型，计算了不同干旱事件的重现期。【结果】基于标准1的水文干旱等级划分结果比标准2更符合实际干旱情况；单变量重现期介于联合重现期与同现重现期之间，可以进行干旱事件重现期估计；黑河流域发生持续2.68个月的重旱事件的重现期为3 a。【结论】基于SRI的干旱等级划分在多变量水文干旱研究中使联合分布函数拟合更优，分析得到的干旱特征更接近实际情况。 |
| 关键词: SRI； 干旱； 等级划分； Copula函数； 重现期； 黑河流域 |
| DOI：10.13522/j.cnki.ggps.20180327 |
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| Classifying Drought in Heihe Basin Using SRI Index and Copula Function |
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ZHANG Xiangming, SU Xiaoling*, ZHANG Gengxi
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College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China
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| Abstract: |
| 【Objective】 The purpose of this paper is to present a method to classify drought based on the measured data in Heihe basin.【Method】Two methods based on runoff-frequency classification were used to realize probabilistic statistical analysis of the runoff data at the Yingluoxia hydrological station in the Heihe River Basin. The SRI-based hydrological drought classification standard (Standard 1) was proposed. The Standard 1 and drought standardization criteria (Standard 2) based on the standardized precipitation index (SPI) were used to identify three drought characteristic variables of hydrological drought, including duration, intensity, and peak intensity. The Copula function was used to study the multivariate joint distribution of hydrological drought, the RMSE, AIC, and BIC criteria was selected as the discriminant basis for the joint distribution goodness of fit test to optimize the Copula function type and then calculated the return period for different drought events.【Result】The classification of hydrological drought grade based on Standard 1 is more consistent with the real drought situation than Standard 2. The univariate return period is between the joint return period and the cooccurrence return period, it therefore is possible to estimate the return period of the drought events. A severe drought lasing for 2.68 months occurs about every three years in the basin.【Conclusion】The SRI-based classification of drought in the multivariable hydrological drought study improves the joint distribution function, and the calculated drought characteristics marched historical data. |
| Key words: SRI; drought; grade division; Copula function; return period |
