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| 基于Copula函数的暴雨要素三维联合分布——以宽甸县为例 | |
| 引用本文： | 张野,王康,刘欣铭,张苏辰,周嘉,王菜林.基于Copula函数的暴雨要素三维联合分布——以宽甸县为例[J].地理科学,2017,37(4):603-610. |
| 作者姓名： | 张野 王康 刘欣铭 张苏辰 周嘉 王菜林 |
| 作者单位： | 1. 东北师范大学地理科学学院,吉林 长春 130024 2. 齐齐哈尔大学理学院,黑龙江 齐齐哈尔 161006 3. 哈尔滨师范大学地理科学学院,黑龙江 哈尔滨 150025 4.北京师范大学/民政部/教育部减灾与应急管理研究院,北京 100875 |
| 基金项目： | 哈尔滨科技局科技创新人才研究专项基金（2016RAXXJ037）,齐齐哈尔软科学项目（RKX-201409）,齐齐哈尔大学青年教师科研启动支持计划项目（2014K-M13）资助 |
| 摘 要： | 以辽宁省宽甸县为例,利用1955~2012年逐日降水数据,提取年暴雨日数（D50）、年暴雨量（P50）、年均暴雨强度（I）和暴雨比（R）共4个暴雨要素,运用K-S法确定各单要素最优概率分布函数;针对暴雨要素多面性,通过引入Copula函数,构建三维联合分布并进行AIC和RMSE优度检验,确定适合暴雨要素的最优Copula函数,分析多要素联合后暴雨的概率和重现期特征。研究表明： ① 单变量拟合仅反映暴雨单个要素本身的信息,无法涉及要素间的联系;三维Copula联合可从3方面呈现暴雨要素间的内在信息,更贴近实际;暴雨本身的多要素性,为Copula函数在暴雨分析上提供了广阔前景; ② 年暴雨日数、年暴雨量和年均暴雨强度的联合适合反映宽甸县暴雨重现期;宽甸县暴雨联合重现期短,多为0~2 a,同现重现期较长,集中于200 a左右;2种重现期变化趋势一致,存在同步效应,反映了暴雨要素的不可分割性。 |
| 关 键 词： | Copula函数 三维联合 暴雨要素 重现期 |
| 收稿时间： | 2016-09-22 |
| 修稿时间： | 2017-01-09 |
The Three-dimensional Joint Distributions of Rainstorm Factors Based on Copula Function: A Case in Kuandian County,Liaoning Province |
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| Ye Zhang,Kang Wang,Xinming Liu,Suchen Zhang,Jia Zhou,Cailin Wang.The Three-dimensional Joint Distributions of Rainstorm Factors Based on Copula Function: A Case in Kuandian County,Liaoning Province[J].Scientia Geographica Sinica,2017,37(4):603-610. | |
| Authors: | Ye Zhang Kang Wang Xinming Liu Suchen Zhang Jia Zhou Cailin Wang |
| Institution: | 1. College of Geographical Sciences, Northeast Normal University, Changchun 130024, Jilin, China 2. School of Science, QiqiharUniversity, Qiqihar 161006, Heilongjiang, China 3. College of Geographical Sciences, Harbin Normal University, Harbin 150025, Heilongjiang, China 4.Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs & Ministry of Education, Beijing Normal University, Beijing 100875,China |
| Abstract: | Taking Kuandian County in Liaoning Province as an example, the author extract four rainstorm factors: the annual rainstorm days, annual of rainstorm depth, annual average rainstorm intensity and rainstorm contribution, through the daily precipitation data from 1955 to 2012 and use the Kolmogorov-Smimov method to determine optimal probability distribution for each single factor. For the multifaceted rainstorm factor, we use AIC and RMSE test to confirm the best fitted copulas connect function suitable for rainstorm factor by introducing the copula function and building three-dimensional joint distribution, and analyze the probability of rainstorm and characteristics of return period with many combined factors. Research shows that: 1) The joint of annual rainstorm days, annual of rainstorm depth and annual average rainstorm intensity is suitable for reaction joint return period of rainstorm factor in Kuandian County; In Kuandian County, joint return period is short and distribute on 0-2 years, co-occurrence return period is longer, concentrated in around 200 years; the change trend of two kinds of return period is consistent, it has synchronization effect, this reflect inseparable of rainstorm factor. 2) The univariate reflect just one factor of information in rainstorm and doesn’t involved in the relationship between factors; Three-dimensional copulas joint can present the internal information between heavy elements from three aspects and closer to the actual; Multiple factors of rainstorm, as copulas function on the rainstorm analysis provides a broad prospects. |
| Keywords: | Copula function three-dimensional joint rainstorm factors return period |
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