共查询到18条相似文献，搜索用时 312 毫秒
1.
利用西江下游马口水文站1959 2009年月径流量数据计算径流干旱指数,经游程理论提取了水文干旱特征值.应用Copula函数分析水文干旱强度和历时之间的联合概率分布.对构建的干旱历时和强度联合分布模式进行分析,结果表明:(1)径流干旱历时和强度之间具有高关联性,秩相关系数达0.617;(2)三参数Weibull分布较好地描述了干旱历时和强度的边缘分布特征;(3)经拟合优度检验结果优选的干旱历时和强度之间的较优连接函数为Archimedean类的Gumbel-Hougaard Copula函数;(4)5～10年重现期和20年重现期的水文干旱分别达到了重旱级别和特旱级别;(5)干旱历时和强度之间的遭遇概率可为特定干旱历时与水文干旱级别或特定干旱强度与干旱历时之间的对应关系提供概率意义上的干旱特征诊断与预测. 相似文献
2.
基于二次重现期的多变量洪水风险评估 总被引：4，自引：2，他引：2
由于洪水是一种具有多个特征属性的随机事件,频率分析成为洪水风险评估的一种有效手段,多变量重现期与设计值的定义与计算则是洪水频率分析中的重点和难点.本文通过构造洪水历时、洪峰与洪量的联合分布,介绍了一种新的多变量重现期定义——二次重现期,并探讨了"或"重现期、"且"重现期和二次重现期对安全与危险域识别的差异性,以及在洪水风险管理与工程设计中的合理性与可靠性.传统的"或"和"且"多变量重现期对安全与危险域的识别存在局限性,利用Kendall函数定义的二次重现期则提供了更加合理的安全与风险域识别,避免了对安全事件与危险事件的错误判定,更有利于指导洪水风险的管理.在给定的二次重现期条件下,依据出现概率最大原则推算的历时、洪峰与洪量设计值组合可以满足工程设计以较低成本承受较大风险的追求,相比于单变量设计值,考虑了洪水多个属性联合特征的多变量设计值提供了更加全面和可靠的参考信息. 相似文献
3.
鄱阳湖流域5大水系来水变化与湖区水文极值事件有密切关系，研究径流变化特征与丰枯遭遇规律对区域防洪抗旱有重要意义.本文运用Copula函数构建了鄱阳湖水系多维径流联合分布模型，采用特枯、偏枯、平水、偏丰和特丰的径流丰枯分类，定量研究了鄱阳湖5大水系丰枯遭遇的问题，探讨了多维丰枯遭遇同步联合概率的变化特征.结果表明：鄱阳湖水系河流之间的径流具有较高的相关性，Gaussian Copula函数能较好地模拟二维至五维的径流联合分布.多条河流的丰枯遭遇随着维数的增加，丰枯组合增加，丰枯同步的联合概率明显下降，且丰枯同步的最大联合概率趋向于丰枯两端.对于相同的概率区间，非汛期径流的丰枯同步联合概率明显大于年径流和汛期径流，而年径流和汛期径流之间的丰枯同步联合概率差别较小.同处于流域北部或南部或相邻的河流之间的组合，其同步联合概率相较其他组合大，而南、北河流组合的同步联合概率相对较小.该研究可为流域水资源管理及水旱灾害预防提供科学依据. 相似文献
4.
洞庭湖是长江中游重要的通江湖泊,水系格局复杂.近年来在气候变化和人类活动的双重影响下,江湖关系发生变化,湖泊水文干旱事件频发.基于洞庭湖、流域和长江干流水文站点的实测数据,通过标准化水位指数和标准化径流指数识别了水文干旱事件,并运用Copula函数分析了洞庭湖-流域-长江系统水文干旱的联合概率分布特征.结果表明:在年尺度上,1964—2016年间洞庭湖共发生了9次水文干旱事件,水文干旱的发生概率为14.01%,洞庭湖-流域系统、洞庭湖-长江系统的水文干旱联合概率分别为9.65%和8.58%,表明年尺度上流域来水对洞庭湖水文干旱的影响更大.在季节尺度上,洞庭湖-流域系统春季水文干旱联合概率最高,且两者同时发生水文干旱事件的次数最多,表明洞庭湖春季水文干旱与流域入湖补给减少有密切关系;而洞庭湖-长江系统,其秋季水文干旱联合概率最大,尤其自2003年以后更加极端和频发,这一方面受秋季降水减少和流域内人类活动的影响,另一方面三峡水库秋季蓄水使长江中下游干流水位降低,长江对湖泊顶托作用减弱也是重要原因之一. 相似文献
5.
基于气象和水文干旱的二维变量干旱状态基础上,通过一阶马尔科夫链模型对二维变量干旱状态进行频率、重现期和历时分析,建立水文气象干旱指数,从干旱灾害形成、演变和持续3方面对干旱灾害进行研究,同时预测未来6个月非水文干旱到水文干旱的概率.结果表明:(1)修河流域在干旱形成中危害大,抚河流域和修河流域在干旱演变中危害大,赣江流域和饶河流域在干旱持续中危害大;(2)鄱阳湖流域状态4(气象、水文干旱)发生的频率最高,为0.30,连续湿润或者干旱的概率最大,湿润状态(状态2)与水文干旱(状态4、状态5(气象湿润、水文干旱))的相互转移概率最低;(3)在长期干旱预测中,鄱阳湖流域从状态2转到状态4和状态5的平均概率为0.11,属最低,而状态1(气象、水文无旱)和状态3(气象干旱、水文湿润)到达状态4的概率为0.23,发生概率最大.修河流域在非水文干旱状态下未来发生气象、水文干旱状态的平均概率为0.28,是"五河"中最高的,而赣江流域在正常或者湿润状态下未来发生气象、水文干旱的概率最低,为0.18,该研究对于鄱阳湖流域水文气象干旱的抗旱减灾具有重要理论与现实意义. 相似文献
6.
基于卫星遥感的太湖蓝藻水华时空分布规律认识 总被引：14，自引：6，他引：8
由于大尺度水文模型和无资料区水文研究是当前国际水文研究的重点和难点,通过参数区域化方法来估计大尺度区域和无资料区的模型参数值成为了研究的热点之一将HBV模型应用于东江流域及其子流域,采用代理流域法和全局乎均法来估计该区域内无资料流域的模型参数研究表明：HBV模型能较好得用于东江流域径流模拟;交叉检验中,较小的序和ME值对应的参数,其转移效果不一定比较大的R^2和ME值对应的参数转移效果差;全局平均法中,面积权重平均值和泰森多边形插值后平均并不能明显改进子流域算术平均值估计无资料流域的模型参数的模拟结果;两者都能有效用于东江流域无资料流域的参数估计,且效果相差不大。 相似文献
7.
变化环境下珠江流域洪水频率变化特征、成因及影响(1951-2010年) 总被引：4，自引：0，他引：4
气候变化和人类活动导致珠江流域水文变化,变化前后洪水频率分布显著不同.运用滑动秩和(Mann-Whitney U test)结合Brown-Forsythe、滑动T、有序聚类和Mann-Kendall检验法,并用累积距平曲线法获取年最大流量序列详细信息,综合确定样本最佳变化节点,并对水文变化成因做了系统分析.在此基础上,对整体序列、变化前后序列用线性矩法推求广义极值分布参数以及不同重现期设计流量.结果表明:(1)西江大部以及北江流域最佳变化节点在1991年左右;东江流域最佳变化节点与该流域内3大控制性水库建成时间基本吻合;(2)变化后,西江、北江年最大流量持续增加,洪峰强度增大,尤其是西江干流年最大流量显著增加;东江流域年最大流量显著减小,洪峰强度降低;(3)变化后,西江与北江洪水风险增加,尤其是下游珠三角地区本身受人类活动显著影响,加之西江与北江持续增加的洪水强度,珠三角地区发生洪水的强度及频次加剧,而东江洪水风险减小.此研究对于珠江流域在变化环境下的洪水风险评估与防洪抗灾具有重要意义. 相似文献
8.
湖泊作为一种蓄水单元,尤其是大型过水性湖泊,是一种典型的平原型水库,在功能上与山谷型水库具有许多相似之处,但由于其特殊的地理地形构造,使得入湖洪水过程与入库洪水过程存在着较大的差异.在防洪安全设计研究中,山谷型水库关注的多是坝址洪水,即总的入库洪水过程,而对于湖泊来说,还需要关注各个分区的入湖洪水过程对湖区洪水演进的影响.针对大型过水性湖泊入湖洪水特征,本文采用Copula函数构造了多个联合分布函数,提出了一套基于总的入湖洪水过程推导各个分区入湖洪水过程置信区间的方法.以洪泽湖为应用实例,结果表明:1)在联合重现期已知的情况下,该方法能够确定总入湖洪量与洪峰的95%置信区间;2)该方法通过径流相关性分析对入湖河道合并聚类,形成分区入湖过程,既考虑了河道间天然的水文、水力联系,又避免了联合分布函数维度过高的问题;3)在总入湖洪量已知的情况下,该方法能够确定各分区入湖洪量分配95%置信区域.该方法具有较强的统计理论基础,拓展了多变量洪水频率分析技术在水利工程实际中的应用范围. 相似文献
9.
10.
降雨径流过程驱动因子的室内模拟实验研究 总被引：9，自引：1，他引：9
降雨径流过程的驱动作用可以归结为两个方面: 第一是降雨过程的影响, 第二是下垫面变化的影响. 通过179场室内降雨径流模拟实验发现, 无论是降雨历时还是降雨强度都会影响汇流的滞时, 这与传统的假设有明显的矛盾. 尤其是在降雨历时小于全面汇流时间和较小的降雨强度下这种非线性关系的影响十分明显. 由此可以推定, 单位线用于南方湿润地区的降雨径流过程模拟更为合理, 而在北方的干旱、半干旱地区, 由于降雨强度变化快, 降雨历时短, 所以使用时要特别注意降水条件. 这也说明了过去的水文模型在北方地区的产汇流效果不好的原因. 降水历时较小时, 流域的汇流特性有较为剧烈的变化, 因为此时流域未达到全流域汇流, 这反映了实际北方降雨径流情况, 因此单位线使用时必须进行适当的非线性校正. 当降雨历时大于流域的全面汇流时间以后整个流域达到蓄泄平衡, 适用于南方长时间降雨径流关系和产汇流的基础理论研究. 在充分降雨条件下, 洪峰流量、降雨强度呈线性关系, 而与下垫面无关, 降雨强度与峰现时间成负线性关系. 流域的调蓄量与降雨强度和洪峰流量呈线性关系, 受下垫面影响和作物截留作用十分明显, 而与作物截留的位置关系不大. 相似文献
11.
A bivariate pareto model for drought 总被引：2，自引：2，他引：0
Saralees Nadarajah 《Stochastic Environmental Research and Risk Assessment (SERRA)》2009,23(6):811-822
Univariate Pareto distributions have been so widely used in hydrology. It seems however that bivariate or multivariate Pareto
distributions have not yet found applications in hydrology, especially with respect to drought. In this note, a drought application
is described by assuming a bivariate Pareto model for the joint distribution drought durations and drought severity in the
State of Nebraska. Based on this model, exact distributions are derived for the inter arrival time, magnitude and the proportion
of droughts. Estimates of 2, 5, 10, 20, 50 and 100 year return periods are derived for the three variables, drought duration,
drought severity and the pairwise combinations: (drought duration, drought severity), (inter arrival time of drought, proportion
of drought) and (drought duration, drought magnitude). These return period estimates could have an important role in hydrology,
for example, with respect to measures of vegetation water stress for plants in water-controlled ecosystems. 相似文献
12.
Multivariate drought characteristics using trivariate Gaussian and Student t copulas 总被引：4，自引：0，他引：4
This study aims to investigate the changing properties of drought events in Weihe River basin, China, by modeling the multivariate joint distribution of drought duration, severity and peak using trivariate Gaussian and Student t copulas. Monthly precipitations of Xi'an gauge are used to illustrate the meta‐elliptical copula‐based methodology for a single‐station application. Gaussian and Student t copulas are found to produce a better fit comparing with other six symmetrical and asymmetrical Archimedean copulas, and, checked by the goodness‐of‐fit tests based on a modified bootstrap version of Rosenblatt's transformation, both of them are acceptable to model the multivariate joint distribution of drought variables. Gaussian copula, the best fitting, is employed to construct the dependence structures of positively associated drought variables so as to obtain the multivariate joint and conditional probabilities of droughts. A Kendall's return period (KRP) introduced by Salvadori and De Michele (2010) is then adopted to assess the multivariate recurrent properties of drought events, and its spatial distributions indicate that prolonged droughts are likely to break out with rather short recurrence intervals in the whole region, while drought status in the southeast seems to be severer than the northwest. The study is of some merits in terms of multivariate drought modeling using a preferable copula‐based method, the results of which could serve as a reference for regional drought defense and water resources management. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
13.
Basic concepts such as conditional probability distributions, conditional return periods, and joint return periods are important to understand and to interpret multivariate hydrological events such as floods and storms. However, these concepts are not well documented in the open literature. This paper assembles and clarifies these concepts, and illustrates their practical utility. Relationships between joint return periods and univariate return periods are also derived. These concepts and relationships are demonstrated by applying a bivariate extreme value distribution to represent the joint distribution of flood peak and volume from an actual basin. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
14.
Frequency analysis of droughts using the Plackett copula and parameter estimation by genetic algorithm 总被引：11，自引：8，他引：3
Songbai Song Vijay P. Singh 《Stochastic Environmental Research and Risk Assessment (SERRA)》2010,24(5):783-805
This study aims to model the joint probability distribution of drought duration, severity and inter-arrival time using a trivariate
Plackett copula. The drought duration and inter-arrival time each follow the Weibull distribution and the drought severity
follows the gamma distribution. Parameters of these univariate distributions are estimated using the method of moments (MOM),
maximum likelihood method (MLM), probability weighted moments (PWM), and a genetic algorithm (GA); whereas parameters of the
bivariate and trivariate Plackett copulas are estimated using the log-pseudolikelihood function method (LPLF) and GA. Streamflow
data from three gaging stations, Zhuangtou, Taian and Tianyang, located in the Wei River basin, China, are employed to test
the trivariate Plackett copula. The results show that the Plackett copula is capable of yielding bivariate and trivariate
probability distributions of correlated drought variables. 相似文献
15.
Droughts are one of the normal and recurrent climatic phenomena on Earth. However, recurring prolonged droughts have caused far‐reaching and diverse impacts because of water deficits. This study aims to investigate the hydrological droughts of the Yellow River in northern China. Since drought duration and drought severity exhibit significant correlation, a bivariate distribution is used to model the drought duration and severity jointly. However, drought duration and drought severity are often modelled by different distributions; the commonly used bivariate distributions cannot be applied. In this study, a copula is employed to construct the bivariate drought distribution. The copula is a function that links the univariate marginal distributions to form the bivariate distribution. The bivariate return periods are also established to explore the drought characteristics of the historically noticeable droughts. The results show that the return period of the drought that occurred in late 1920s to early 1930s is 105 years. The significant 1997 dry‐up phenomenon that occurred in the downstream Yellow River (resulting from the 1997–1998 drought) only has a return period of 4·4 years and is probably induced by two successive droughts and deteriorated by other factors, such as human activities. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
16.
A gamma distribution is one of the most frequently selected distribution types for hydrological frequency analysis. The bivariate gamma distribution with gamma marginals may be useful for analysing multivariate hydrological events. This study investigates the applicability of a bivariate gamma model with five parameters for describing the joint probability behavior of multivariate flood events. The parameters are proposed to be estimated from the marginal distributions by the method of moments. The joint distribution, the conditional distribution, and the associated return periods are derived from marginals. The usefulness of the model is demonstrated by representing the joint probabilistic behaviour between correlated flood peak and flood volume and between correlated flood volume and flood duration in the Madawask River basin in the province of Quebec, Canada. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
17.
Chang Hwan Lee Tae-Woong Kim Gunhui Chung Minha Choi Chulsang Yoo 《Stochastic Environmental Research and Risk Assessment (SERRA)》2010,24(3):389-397
Bivariate distributions have been recently employed in hydrologic frequency analysis to analyze the joint probabilistic characteristics
of multivariate storm events. This study aims to derive practical solutions of application for the bivariate distribution
to estimate design rainfalls corresponding to the desired return periods. Using the Gumbel mixed model, this study constructed
rainfall–frequency curves at sample stations in Korea which provide joint relationships between amount, duration, and frequency
of storm events. Based on comparisons and analyses of the rainfall–frequency curves derived from univariate and bivariate
storm frequency analyses, this study found that conditional frequency analysis provides more appropriate estimates of design
rainfalls as it more accurately represents the natural relationship between storm properties than the conventional univariate
storm frequency analysis. 相似文献
18.
Xinjun Tu Xiaohong Chen Mingwei Ma Qiang Zhang Yong Zhao 《Stochastic Environmental Research and Risk Assessment (SERRA)》2016,30(5):1317-1334
There are two kinds of uncertainty factors in modeling the bivariate distribution of hydrological droughts: the alteration of predefined critical ratios for pooling droughts and excluding minor droughts and the temporal variability of univariate and/or bivariate characteristics of droughts due to the impact of human activities. Daily flow data covering a period of 56 hydrological years from two gauging stations from a humid region in South China are used. The influences of alterations of threshold values of flow and critical ratios of pooling droughts and excluding minor droughts on drought properties are analyzed. Six conventional univariate models and three Archimedean copulas are employed to fit the marginal and joint distributions of drought properties, the Kolmogorov–Smirnov and Anderson–Darling methods are used for testing the goodness-of-fit of the univariate model, and the Cramer-von Mises method based on Rosenblatt’s transform is applied for the test of the bivariate model. The change point analysis of the copula parameter of bivariate distribution of droughts is first made. Results demonstrate that both the statistical characteristics of each drought property and their bivariate joint distributions are sensitive to the critical ratio of excluding minor droughts. A model can be selected to fit the marginal distribution for drought deficit volume or maximum deficit, but it is not determined for drought duration with the lower ratios of the pooling and excluding droughts. The statistical uncertainty of drought duration makes the modeling of bivariate joint distribution of drought duration and deficit volume or of drought duration and maximum deficit undermined. Change points significantly occurred in the period from the late 1970s to the middle 1980s for a single drought property and the copula parameter of their joint distribution due to the impact of human activities. The difference between two subseries separated by the change point is remarkable in the magnitudes of drought properties and the joint return periods. A copula function can be selected to optimally fit the bivariate distribution, provided that the critical ratios of pooling and excluding droughts are great enough such as the optimal value of 0.4 in the case study. It is valuable that the modeling and designing of the bivariate joint correlation and distribution of drought properties can be performed on the subseries separated by the change point of the copula parameter. 相似文献