干旱指标和Copula函数在干旱事件多变量频率分析中的应用
发布时间：2022-05-05 21:00
干旱在从古至今一直影响和制约着经济与社会的发展。由于中国特殊的地理、气候、水文特征情况,更是深受其害。因此,正确理解多年尺度干旱特征和重现期对干旱风险评估至关重要。本文以中国大陆区域和七个子区域为研究对象,选取全国552个气象站1961-2013年的日气象数据,计算其气象干旱特征变量,研究区域干旱变量联合概率时空分布和重现期,并进行深度的干旱分析,以期为区域和全国的旱灾防控、用水量合理调配、水资源可持续发展提供一定的理论支撑。本文计算了多时间尺度的标准化降水指数（SPI）、标准化降水蒸发蒸腾指数（SPEI）、综合指数（CI）和有效干旱指数（EDI）,分别用Classical、Spearman和Kendall方法对各指标的相关性进行了分析,来研究干旱演变规律。基于全国日降水数据,提取一维干旱历时（Dd）、干旱烈度（Ds）、烈度峰值（Dp）和干旱间隔（Di）的单变量指标,分析其在各个分区和全国的特征。这些干旱变量指标之间有显著的相关性并遵循不同的分布,可用Copulas函数用来构建变量之间的联合分布。用Archimedean copulas函数从19种干旱变量组中选出3种,分别是干旱历时和...
【文章页数】：150 页
【学位级别】：博士
【文章目录】：
ABSTRACT 摘要 Chapter 1. Introduction
1.1 Background to the study
1.2 Drought characteristics
1.3 Classification of drought
1.4 Drought index and drought identification
1.5 Probabilistic Characterization of Drought
1.6 Copula and Drought Frequency Analysis
1.7 Research Gap
1.8 General Aims and Objectives Chapter 2. Study Area and Data
2.1 Study Area
2.2 Study sites and data
2.3 Drought Coverage Area
2.4 Structure of the research Chapter 3. Drought Indices and Univariate Analysis
3.1 Drought Index and Univariate Analysis
3.2 Methodology
3.2.1 Descriptive statistics
3.2.2 Potential evapotranspiration
3.2.3 Computation of Drought Indices
3.2.3.1 Standardized Precipitation Index
3.2.3.2 Standardized Precipitation Evapotranspiration Index
3.2.3.3 Composite Index
3.2.3.4 Effective Drought Index
3.2.4 Drought event identification and characterization
3.2.5 Selection of appropriate marginal distributions
3.2.6 Evaluation criteria
3.2.7 Estimation of Univariate Drought Return Period
3.2.8 Spatial interpolation
3.3 Results and Discussion
3.3.1 Spatiotemporal variations of climatic variables
3.3.2 Drought indices and their frequency distribution
3.3.3 Drought Characteristics
3.3.4 The Spatial and Temporal extent of Drought Characteristics
3.3.4.1 Spatial extent of Drought Characteristics
3.3.4.2 Temporal extent of Severe Drought events
3.3.5 Correlation of Drought Characteristics
3.3.6 Estimation of Effective drought index
3.3.7 Marginal distribution fit of drought variables
3.3.8 Univariate Return Period Analyses
3.3.9 Relative performance of drought indices
3.4 Brief summary Chapter 4. Frequency analysis using Two-Variate Archimedean Copula
4.1 Background of two-variate joint copula
4.2 Methodology
4.2.1 Theoretical aspects of copula functions
4.2.2 Bivariate Archimedean copulas
4.2.3 Copulas Parameter Estimation
4.2.4 Selecting the Best Copula Family
4.2.5 Probabilities of Drought Events
4.2.5.1 Bivariate joint occurrence probability
4.2.5.2 Bivariate joint Conditional probability
4.2.6 Return Periods of Drought Events
4.2.6.1 Bivariate joint return period
4.2.6.2 Conditional joint return period
4.3 Results and Discussion
4.3.1 Analysis of drought climatology
4.3.2 Drought Event Characterization
4.3.3 Analyzing trivariate dependence between drought variables
4.3.4 Estimation of bivariate joint distributions
4.3.5 Regional Characteristics of drought events
4.3.5.1 Regional joint probability of drought events
4.3.5.2 Regional bivariate return period of drought events
4.3.6 Spatial Characteristics of drought events
4.3.6.1 Spatial distribution of drought probabilities
4.3.6.2 Spatial pattern of bivariate drought return period
4.4 Brief Conclusion Chapter 5. Frequency analysis using Three-Variate Archimedean Copula
5.1 Background of Three-Variate Copula
5.2 Methodology
5.2.1 Empirical trivariate distribution of drought variables
5.2.2 Trivariate cumulative probability distribution of drought variables
5.2.3 Trivariate dependence modeling of droughts using Archimedean copula
5.2.4 Selection of appropriate Trivariate copula family
5.2.5 Trivariate frequency analysis of droughts
5.2.5.1 Trivariate joint occurrence probability of drought events
5.2.5.2 Trivariate return period of drought events
5.3 Results and Discussions
5.3.1 Copula-based joint dependence modeling of drought variables
5.3.2 Comparison of multivariate probability of drought events
5.3.2.1 Regional trivariate joint probability of drought events
5.3.2.2 Spatial pattern of multivariate drought probabilities
5.3.3 Comparison of multivariate return periods of drought events
5.3.3.1 Regional trivariate return period of drought events
5.3.3.2 Spatial pattern of multivariate drought return period
5.4 Brief Conclusion Chapter 6. Frequency analysis using Four-Variate Archimedean Copula
6.1 Background of Four-variate dimensional Copula
6.2 Methodology
6.2.1Empirical four-variate distribution of drought variables
6.2.2 Joint cumulative probability distribution of drought variables
6.2.3 Modeling four-variate drought variables using copulas
6.2.4 Selection of appropriate copula function
6.2.5 Four-variate joint drought frequency analysis
6.3 Results and Discussions
6.3.1 Drought variable and four-variate dependence
6.3.2 Marginal Distribution for Inter-arrival time
6.3.3 Copula-based four-variate joint distributions
6.3.4 Four-variate joint drought frequency analysis
6.3.4.1 Regional four-variate probabilities of drought events
6.3.4.2 Regional four-variate return period of drought events
6.3.4.3 Spatial distribution of four-variate probability and return periods
6.4 Brief Summary Chapter 7. Conclusions and suggestions
7.1 General Conclusions
7.2 Future work References Acknowledgements Author’s Introduction
【参考文献】：
期刊论文
[1]Characteristics of Clustering Extreme Drought Events in China During 1961-2010[J]. 杨萍,肖子牛,杨杰,刘华. Acta Meteorologica Sinica. 2013(02)
[2]基于综合气象干旱指数的石羊河流域近50年气象干旱特征分析[J]. 张调风,张勃,王有恒,刘秀丽,安美玲,张建香. 生态学报. 2013(03)
[3]基于多变量概率分析的珠江流域干旱特征研究[J]. 肖名忠,张强,陈晓宏. 地理学报. 2012(01)
[4]The influence of the Madden-Julian Oscillation activity anomalies on Yunnan’s extreme drought of 2009-2010[J]. Lü JunMei 1 , JU JianHua 2* , REN JuZhang 3 & GAN WeiWei 4 1 Chinese Academy of Meteorological Sciences, Beijing 100081, China; 2 Yunnan Provincial Meteorological Service, Kunming 650034, China; 3 Yunnan Institute of Meteorology, Kunming 650034, China; 4 Department of Atmospheric Sciences, Yunnan University, Kunming 650091, China. Science China（Earth Sciences）. 2012(01)
[5]2009年秋至2010年春我国西南地区干旱及与历史场次干旱对比分析[J]. 刘建刚,万金红,谭徐明,马建明,张念强. 防灾减灾工程学报. 2011(02)
[6]近半个世纪我国干旱变化的初步研究[J]. 邹旭恺,张强. 应用气象学报. 2008(06)
[7]我国单站旱涝指标确定和区域旱涝级别划分的研究[J]. 鞠笑生,杨贤为,陈丽娟,王有民. 应用气象学报. 1997(01)
[8]中国综合自然地理区划的一个新方案[J]. 赵松乔. 地理学报. 1983(01)
本文编号：3651005
【文章页数】：150 页
【学位级别】：博士
【文章目录】：
ABSTRACT 摘要 Chapter 1. Introduction
1.1 Background to the study
1.2 Drought characteristics
1.3 Classification of drought
1.4 Drought index and drought identification
1.5 Probabilistic Characterization of Drought
1.6 Copula and Drought Frequency Analysis
1.7 Research Gap
1.8 General Aims and Objectives Chapter 2. Study Area and Data
2.1 Study Area
2.2 Study sites and data
2.3 Drought Coverage Area
2.4 Structure of the research Chapter 3. Drought Indices and Univariate Analysis
3.1 Drought Index and Univariate Analysis
3.2 Methodology
3.2.1 Descriptive statistics
3.2.2 Potential evapotranspiration
3.2.3 Computation of Drought Indices
3.2.3.1 Standardized Precipitation Index
3.2.3.2 Standardized Precipitation Evapotranspiration Index
3.2.3.3 Composite Index
3.2.3.4 Effective Drought Index
3.2.4 Drought event identification and characterization
3.2.5 Selection of appropriate marginal distributions
3.2.6 Evaluation criteria
3.2.7 Estimation of Univariate Drought Return Period
3.2.8 Spatial interpolation
3.3 Results and Discussion
3.3.1 Spatiotemporal variations of climatic variables
3.3.2 Drought indices and their frequency distribution
3.3.3 Drought Characteristics
3.3.4 The Spatial and Temporal extent of Drought Characteristics
3.3.4.1 Spatial extent of Drought Characteristics
3.3.4.2 Temporal extent of Severe Drought events
3.3.5 Correlation of Drought Characteristics
3.3.6 Estimation of Effective drought index
3.3.7 Marginal distribution fit of drought variables
3.3.8 Univariate Return Period Analyses
3.3.9 Relative performance of drought indices
3.4 Brief summary Chapter 4. Frequency analysis using Two-Variate Archimedean Copula
4.1 Background of two-variate joint copula
4.2 Methodology
4.2.1 Theoretical aspects of copula functions
4.2.2 Bivariate Archimedean copulas
4.2.3 Copulas Parameter Estimation
4.2.4 Selecting the Best Copula Family
4.2.5 Probabilities of Drought Events
4.2.5.1 Bivariate joint occurrence probability
4.2.5.2 Bivariate joint Conditional probability
4.2.6 Return Periods of Drought Events
4.2.6.1 Bivariate joint return period
4.2.6.2 Conditional joint return period
4.3 Results and Discussion
4.3.1 Analysis of drought climatology
4.3.2 Drought Event Characterization
4.3.3 Analyzing trivariate dependence between drought variables
4.3.4 Estimation of bivariate joint distributions
4.3.5 Regional Characteristics of drought events
4.3.5.1 Regional joint probability of drought events
4.3.5.2 Regional bivariate return period of drought events
4.3.6 Spatial Characteristics of drought events
4.3.6.1 Spatial distribution of drought probabilities
4.3.6.2 Spatial pattern of bivariate drought return period
4.4 Brief Conclusion Chapter 5. Frequency analysis using Three-Variate Archimedean Copula
5.1 Background of Three-Variate Copula
5.2 Methodology
5.2.1 Empirical trivariate distribution of drought variables
5.2.2 Trivariate cumulative probability distribution of drought variables
5.2.3 Trivariate dependence modeling of droughts using Archimedean copula
5.2.4 Selection of appropriate Trivariate copula family
5.2.5 Trivariate frequency analysis of droughts
5.2.5.1 Trivariate joint occurrence probability of drought events
5.2.5.2 Trivariate return period of drought events
5.3 Results and Discussions
5.3.1 Copula-based joint dependence modeling of drought variables
5.3.2 Comparison of multivariate probability of drought events
5.3.2.1 Regional trivariate joint probability of drought events
5.3.2.2 Spatial pattern of multivariate drought probabilities
5.3.3 Comparison of multivariate return periods of drought events
5.3.3.1 Regional trivariate return period of drought events
5.3.3.2 Spatial pattern of multivariate drought return period
5.4 Brief Conclusion Chapter 6. Frequency analysis using Four-Variate Archimedean Copula
6.1 Background of Four-variate dimensional Copula
6.2 Methodology
6.2.1Empirical four-variate distribution of drought variables
6.2.2 Joint cumulative probability distribution of drought variables
6.2.3 Modeling four-variate drought variables using copulas
6.2.4 Selection of appropriate copula function
6.2.5 Four-variate joint drought frequency analysis
6.3 Results and Discussions
6.3.1 Drought variable and four-variate dependence
6.3.2 Marginal Distribution for Inter-arrival time
6.3.3 Copula-based four-variate joint distributions
6.3.4 Four-variate joint drought frequency analysis
6.3.4.1 Regional four-variate probabilities of drought events
6.3.4.2 Regional four-variate return period of drought events
6.3.4.3 Spatial distribution of four-variate probability and return periods
6.4 Brief Summary Chapter 7. Conclusions and suggestions
7.1 General Conclusions
7.2 Future work References Acknowledgements Author’s Introduction
【参考文献】：
期刊论文
[1]Characteristics of Clustering Extreme Drought Events in China During 1961-2010[J]. 杨萍,肖子牛,杨杰,刘华. Acta Meteorologica Sinica. 2013(02)
[2]基于综合气象干旱指数的石羊河流域近50年气象干旱特征分析[J]. 张调风,张勃,王有恒,刘秀丽,安美玲,张建香. 生态学报. 2013(03)
[3]基于多变量概率分析的珠江流域干旱特征研究[J]. 肖名忠,张强,陈晓宏. 地理学报. 2012(01)
[4]The influence of the Madden-Julian Oscillation activity anomalies on Yunnan’s extreme drought of 2009-2010[J]. Lü JunMei 1 , JU JianHua 2* , REN JuZhang 3 & GAN WeiWei 4 1 Chinese Academy of Meteorological Sciences, Beijing 100081, China; 2 Yunnan Provincial Meteorological Service, Kunming 650034, China; 3 Yunnan Institute of Meteorology, Kunming 650034, China; 4 Department of Atmospheric Sciences, Yunnan University, Kunming 650091, China. Science China（Earth Sciences）. 2012(01)
[5]2009年秋至2010年春我国西南地区干旱及与历史场次干旱对比分析[J]. 刘建刚,万金红,谭徐明,马建明,张念强. 防灾减灾工程学报. 2011(02)
[6]近半个世纪我国干旱变化的初步研究[J]. 邹旭恺,张强. 应用气象学报. 2008(06)
[7]我国单站旱涝指标确定和区域旱涝级别划分的研究[J]. 鞠笑生,杨贤为,陈丽娟,王有民. 应用气象学报. 1997(01)
[8]中国综合自然地理区划的一个新方案[J]. 赵松乔. 地理学报. 1983(01)
本文编号：3651005
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