共查询到20条相似文献，搜索用时 31 毫秒
1.
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
2.
J. T. Shiau 《Stochastic Environmental Research and Risk Assessment (SERRA)》2003,17(1-2):42-57
Extreme hydrological events are inevitable and stochastic in nature. Characterized by multiple properties, the multivariate
distribution is a better approach to represent this complex phenomenon than the univariate frequency analysis. However, it
requires considerably more data and more sophisticated mathematical analysis. Therefore, a bivariate distribution is the most
common method for modeling these extreme events. The return periods for a bivariate distribution can be defined using either
separate single random variables or two joint random variables. In the latter case, the return periods can be defined using
one random variable equaling or exceeding a certain magnitude and/or another random variable equaling or exceeding another
magnitude or the conditional return periods of one random variable given another random variable equaling or exceeding a certain
magnitude. In this study, the bivariate extreme value distribution with the Gumbel marginal distributions is used to model
extreme flood events characterized by flood volume and flood peak. The proposed methodology is applied to the recorded daily
streamflow from Ichu of the Pachang River located in Southern Taiwan. The results show a good agreement between the theoretical
models and observed flood data.
The author wishes to thank the two anonymous reviewers for their constructive comments that improving the quality of this
work. 相似文献
3.
水文干旱多变量联合设计及水库影响评估 总被引：2，自引：1，他引：1
基于东江流域博罗站月径流数据,采用游程理论提取水文干旱事件.选用Meta-Gaussian Copula函数,统计模拟水文干旱指标的多变量联合分布.采用Kendall联合重现期和最大可能权函数,设计给定联合超越重现期的水文干旱指标组合值,并定量评估水库径流调节作用对水文干旱多变量联合特征的影响.结果表明:东江流域水文干旱历时、强度和峰值的统计优选分布均为韦布尔分布.干旱指标之间具有较高的正相关性,Meta-Gaussian Copula能够很好地模拟水文干旱指标两变量和三变量联合分布.基于任意两个变量联合设计和三变量联合设计,干旱指标设计组合值位于同频位置附近,且同一个干旱指标设计值在不同变量组合之间差别较小.水库径流调节作用对于缓解东江流域水文干旱效果明显,同一组干旱指标的多变量联合超越重现期在水库影响下明显变大.联合超越重现期越小,水库对联合设计值的影响程度越大.根据目前水库运行模式,若要满足河道内最小管理流量目标,联合超越重现期10 a一遇的干旱历时、强度和峰值依然达到了约3.89~4.04月、7.20~7.97亿m3和2.99~3.12亿m3. 相似文献
4.
5.
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
6.
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
7.
ABSTRACTSeries of observed flood intervals, defined as the time intervals between successive flood peaks over a threshold, were extracted directly from 11 approximately 100-year streamflow datasets from Queensland, Australia. A range of discharge thresholds were analysed that correspond to return periods of approximately 3.7 months to 6.3 years. Flood interval histograms at South East Queensland gauges were consistently unimodal whereas those of the North and Central Queensland sites were often multimodal. The exponential probability distribution (pd) is often used to describe interval exceedence probabilities, but fitting utilizing the Anderson-Darling statistic found little evidence that it is the most suitable. The fatigue life pd dominated sub-year return periods (<1 year), often transitioning to a log Pearson 3 pd at above-year return periods. Fatigue life pd is used in analysis of the lifetime to structural failure when a threshold is exceeded, and this paper demonstrates its relevance also to the elapsed time between above-threshold floods. At most sites, the interval medians were substantially less than the means for sub-year return periods. Statistically the median is a better measure of the central tendency of skewed distributions but the mean is generally used in practice to describe the classical concept of flood return period.
Editor Z.W. Kundzewicz; Associate editor I. Nalbantis 相似文献
8.
Prediction of the peak break‐up water level, which is the maximum instantaneous stage during ice break‐up, is desirable to allow effective ice flood mitigation, but traditional hydrologic flood routing techniques are not efficient in addressing the large uncertainties caused by numerous factors driving the peak break‐up water level. This research provides a probability prediction framework based on vine copulas. The predictor variables of the peak break‐up water level are first chosen, the pair copula structure is then constructed by using vine copulas, the conditional density distribution function is derived to perform a probability prediction, and the peak break‐up water level value can then be estimated from the conditional density distribution function given the conditional probability and fixed values of the predictor variables. This approach is exemplified using data from 1957 to 2005 for the Toudaoguai and Sanhuhekou stations, which are located in the Inner Mongolia Reach of the Yellow River, and the calibration and validation periods are divided at 1986. The mean curve of the peak break‐up water level estimated from the conditional distribution function can capture the tendency of the observed series at both the Toudaoguai and Sanhuhekou stations, and more than 90% of the observed values fall within the 90% prediction uncertainty bands, which are approximately twice the standard deviation of the observed series. The probability prediction results for the validation period are consistent with those for the calibration period when the nonstationarity of the marginal distributions for the Sanhuhekou station are considered. Compared with multiple linear regression results, the uncertainty bands from the conditional distribution function are much narrower; moreover, the conditional distribution function is more capable of addressing the nonstationarity of predictor variables, and the conclusions are confirmed by jackknife analysis. Scenario predictions for cases in which the peak break‐up water level is likely to be higher than the bankfull water level can also be conducted based on the conditional distribution function, with good performance for the two stations. 相似文献
9.
工程结构抗震设计中小震、中震和大震的确定方法 总被引：3，自引：1，他引：2
基于Ｐｏｉｓｓｏｎ分布,导出了地震危险性分析中的几个重要关系式。研究了烈度的平均重现周期曲线的特征。根据此特征将此分为缓慢变化型、中等变化型和急剧变化型。提出了小震、中震和大震的确定方法,对于具有不同类型的重现周期曲线的地震区,分别导出了小震、中震和大震的取值公式。最后,给出了该方法的应用实例。 相似文献
10.
Complex hydrological events such as floods always appear to be multivariate events that are characterized by a few correlated variables. A complete understanding of these events needs to investigate joint probabilistic behaviours of these correlated variables. The lognormal distribution is one of frequently selected candidates for flood‐frequency analysis. The multivariate lognormal distribution will serve as an important tool for analysing a multivariate flood episode. This article presents a procedure for using the bivariate lognormal distribution to describe the joint distributions of correlated flood peaks and volumes, and correlated flood volumes and durations. Joint distributions, conditional distributions, and the associated return periods of these random variables can be readily derived from their marginal distributions. The approach is verified using observed streamflow data from the Nord river basin, located in the Province of Quebec, Canada. The theoretical distributions show a good fit to observed ones. Copyright © 2000 John Wiley & Sons, Ltd. 相似文献
11.
《水文科学杂志》2013,58(4)
Abstract Because droughts cover extensive areas, it is important to consider multisite droughts in a region. Probability distribution of joint droughts at a number of sites is derived assuming that flows are cross-correlated first-order Markov processes. A geometric distribution is found with a parameter that depends on the threshold probability, lag-one autocorrelation coefficients, and the multivariate probability of remaining below the threshold. Computation of the parameter of the geometric distribution is discussed. An expression is obtained for the return period of multisite droughts. Application of the derived expression is shown in an example. 相似文献
12.
Abstract A procedure is presented for using the bivariate normal distribution to describe the joint distribution of storm peaks (maximum rainfall intensities) and amounts which are mutually correlated. The Box-Cox transformation method is used to normalize original marginal distributions of storm peaks and amounts regardless of the original forms of these distributions. The transformation parameter is estimated using the maximum likelihood method. The joint cumulative distribution function, the conditional cumulative distribution function, and the associated return periods can be readily obtained based on the bivariate normal distribution. The method is tested and validated using two rainfall data sets from two meteorological stations that are located in different climatic regions of Japan. The theoretical distributions show a good fit to observed ones. 相似文献
13.
The index flood procedure coupled with the L‐moments method is applied to the annual flood peaks data taken at all stream‐gauging stations in Turkey having at least 15‐year‐long records. First, screening of the data is done based on the discordancy measure (Di) in terms of the L‐moments. Homogeneity of the total geographical area of Turkey is tested using the L‐moments based heterogeneity measure, H, computed on 500 simulations generated using the four parameter Kappa distribution. The L‐moments analysis of the recorded annual flood peaks data at 543 gauged sites indicates that Turkey as a whole is hydrologically heterogeneous, and 45 of 543 gauged sites are discordant which are discarded from further analyses. The catchment areas of these 543 sites vary from 9·9 to 75121 km2 and their mean annual peak floods vary from 1·72 to 3739·5 m3 s?1. The probability distributions used in the analyses, whose parameters are computed by the L‐moments method are the general extreme values (GEV), generalized logistic (GLO), generalized normal (GNO), Pearson type III (PE3), generalized Pareto (GPA), and five‐parameter Wakeby (WAK). Based on the L‐moment ratio diagrams and the |Zdist|‐statistic criteria, the GEV distribution is identified as the robust distribution for the study area (498 gauged sites). Hence, for estimation of flood magnitudes of various return periods in Turkey, a regional flood frequency relationship is developed using the GEV distribution. Next, the quantiles computed at all of 543 gauged sites by the GEV and the Wakeby distributions are compared with the observed values of the same probability based on two criteria, mean absolute relative error and determination coefficient. Results of these comparisons indicate that both distributions of GEV and Wakeby, whose parameters are computed by the L‐moments method, are adequate in predicting quantile estimates. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
14.
Information concerning a total number of 13700 instrumentally recorded earthquakes is used to study the geographical and the vertical distribution of the Earth's seismicity. From these earthquakes, which form four complete samples of data (M 7.0, 1894–1992; M 6.5, 1930–1992; M 6.0, 1953–1992; M 5.5, 1966–1992), 11511 are shallow (h 60 km), 2085 are of intermediate focal depth (61 h 300 km) and 564 are deep focus earthquakes (301 h 720 km). The parameters a and b of the frequency-magnitude relationship were calculated in a grid of equally spaced points at 1° by using the data of earthquakes located inside circles centered at each point. The radius of the circles increased from 30 km with a step of 10 km until the information for the earthquakes located inside the circle fulfil three criteria which concern the size of the sample used to compute these parameters at each point of the grid. The results are given in a qualitative way (epicenter maps) as well as in a quantitative way (mean return periods). 相似文献
15.
Regional frequency analysis based on L-moments was applied to assess the spatial extent of meteorological droughts in tandem with their return periods in Zambia. Weather station monthly rainfall data were screened to form homogeneous sub-regions-, validated by a homogeneity criterion and fitted by a generalized extreme value distribution using goodness-of-fit test statistics. Predictor equations at regional scale for L-moment ratios and mean annual precipitation were developed to generate spatial maps of meteorological drought recurrences. The 80% of normal rainfall level and two thresholds of 60% and 70% were synonymous with moderate and severe droughts, respectively. Droughts were more severe in the south than in the north of Zambia. The return periods for severe and moderate droughts showed an overlapping pattern in their occurrence at many locations, indicating that in certain years droughts can affect the entire country. The extreme south of Zambia is the most prone to drought. 相似文献
16.
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
17.
18.
Many civil infrastructures are located near the confluence of two streams, where they may be subject to inundation by high flows from either stream or both. These infrastructures, such as highway bridges, are designed to meet specified performance objectives for floods of a specified return period (e.g. the 100 year flood). Because the flooding of structures on one stream can be affected by high flows on the other stream, it is important to know the relationship between the coincident exceedence probabilities on the confluent stream pair in many hydrological engineering practices. Currently, the National Flood Frequency Program (NFF), which was developed by the US Geological Survey (USGS) and based on regional analysis, is probably the most popular model for ungauged site flood estimation and could be employed to estimate flood probabilities at the confluence points. The need for improved infrastructure design at such sites has motivated a renewed interest in the development of more rigorous joint probability distributions of the coincident flows. To accomplish this, a practical procedure is needed to determine the crucial bivariate distributions of design flows at stream confluences. In the past, the copula method provided a way to construct multivariate distribution functions. This paper aims to develop the Copula‐based Flood Frequency (COFF) method at the confluence points with any type of marginal distributions via the use of Archimedean copulas and dependent parameters. The practical implementation was assessed and tested against the standard NFF approach by a case study in Iowa's Des Moines River. Monte Carlo simulations proved the success of the generalized copula‐based joint distribution algorithm. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
19.
ABSTRACTThe aim of this study is to reveal statistical characteristics and exceedance probability of discharge under the combined effect of climate change and human activities. The study is conducted in the Xiaoqing River in Jinan, China, based on data of discharge, land-use types and precipitation from the period 1970–2016. A multivariate joint probability distribution of the data is established to test the univariable, bivariable and trivariable change points. These are then used to calculate and analyse the risk probability of discharge exceeding the specific values under different conditions of precipitation and land-use type. The results show that the change point calculated by trivariate joint distribution can reduce the disturbance of the change point obtained with the univariable or bivariable approach and reflect the changes of various factors in the hydrological processes more objectively. When the land-use type is taken into consideration, the trivariate distribution can reflect the variation of hydrological processes more reasonably. 相似文献