The Experts below are selected from a list of 309 Experts worldwide ranked by ideXlab platform
Bernard Bobée - One of the best experts on this subject based on the ideXlab platform.
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multivariate hydrological Frequency Analysis using copulas
Water Resources Research, 2004Co-Authors: Annecatherine Favre, Salaheddine El Adlouni, Luc Perreault, Nathalie Thiemonge, Bernard BobéeAbstract:[1] This article presents the modeling of multivariate extreme values using copulas. Our approach allows us to model the dependence structure independently of the marginal distributions, which is not possible with standard classical methods. The methodology has been applied on two different problems in hydrology. The first application is concerned with the combined risk in the framework of Frequency Analysis. Four copulas have been tested on peak flows from the watershed of Peribonka in Quebec, Canada. The second application relates to the joint modeling of peak flows and volumes. Three copulas have been applied to the watershed of the Rimouski River in Quebec, Canada. This approach using copulas is promising since it allows us to take into account a wide range of correlation which can happen in hydrology.
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Recent advances in flood Frequency Analysis
Reviews of Geophysics, 1995Co-Authors: Bernard Bobée, Peter F. RasmussenAbstract:Research on flood Frequency Analysis has taken place with varying intensity over the last couple of decades. The eighties proved to be important years with many significant contributions, reviewed for instance by Greis [1983], Potter [1987], Kirby and Moss [1987], Cunnane [1987], NRC [1988], WMO [1989], and Bobee and Ashkar [1991]. Due to its large economical and environmental impact, flood Frequency Analysis remains a subject of great importance and interest, and the research on improved methods for obtaining reliable flood estimates has continued into the nineties, although with different emphasis. In the seventies and eighties much effort was spent on developing efficient at-site flood Frequency procedures. New distributions and estimation methods were introduced in the hydrologic journals, some of them developed specifically for flood Frequency Analysis. It seems that this tendency has decelerated somewhat in the beginning of the nineties. Researchers are increasingly realizing that the lack of sufficiently long data series imposes an upper limit on the degree of sophistication that can reasonably be justified in at-site flood Frequency Analysis. It has been emphasized by many that instead of developing new methodologies for flood Frequency Analysis, effort should be spent on comparing existing ones and on looking for other sources of information [Potter, 1987; Bobee et al, 1993a]. Regionalization is probably the most viable avenue for improving flood estimates, and fortunately this seems to be the direction that the research in flood Frequency Analysis has taken in the nineties.
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Robust Estimators in Hydrologic Frequency Analysis
Engineering Hydrology, 1993Co-Authors: Fahim Ashkar, Taha B. M. J. Ouarda, Bernard BobéeAbstract:This paper applies a specific robust estimation procedure known as 'trimming' in flood Frequency Analysis. The trimming technique consists in censoring the series of recorded floods by excluding the most extreme values. Using Monte Carlo simulation, the effect of various proportions of symmetric trimming on the estimation of moments, distribution parameters, and quantiles, is examined. The influence of the sample size and the parent distribution parameters on the estimation performance is also investigated for the log-Pearson Type 3 distribution (LP3D). The classical method of moments, the 'sundry averages method' (SAM) and the method of mixed moments are selected for the fitting of the LP3D. The utility of robust techniques in hydrologic Frequency Analysis is demonstrated, and recommendations are made based on the root mean square error of parameter and quantile estimates.
James R Wallis - One of the best experts on this subject based on the ideXlab platform.
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regional Frequency Analysis an approach based on l moments
Journal of the American Statistical Association, 1997Co-Authors: J R M Hosking, James R WallisAbstract:Preface 1. Regional Frequency Analysis 2. L-moments 3. Screening the data 4. Identification of homogeneous regions 5. Choice of a Frequency distribution 6. Estimation of the Frequency distribution 7. Performance of the regional L-moment algorithm 8. Other topics 9. Examples Appendix References Index of notation.
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some statistics useful in regional Frequency Analysis
Water Resources Research, 1993Co-Authors: J R M Hosking, James R WallisAbstract:Regional Frequency Analysis uses data from a number of measuring sites. A “region” is a group of sites each of which is assumed to have data drawn from the same Frequency distribution. The Analysis involves the assignment of sites to regions, testing whether the proposed regions are indeed homogeneous, and choice of suitable distributions to fit to each region's data. This paper describes three statistics useful in regional Frequency Analysis: a discordancy measure, for identifying unusual sites in a region; a heterogeneity measure, for assessing whether a proposed region is homogeneous; and a goodness-of-fit measure, for assessing whether a candidate distribution provides an adequate fit to the data. Tests based on the statistics provide objective backing for the decisions involved in regional Frequency Analysis. The statistics are based on the L moments [Hosking, 1990] of the at-site data.
Salaheddine El Adlouni - One of the best experts on this subject based on the ideXlab platform.
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Encyclopedia of Environmetrics - Hydrological Frequency Analysis
Encyclopedia of Environmetrics, 2013Co-Authors: Salaheddine El AdlouniAbstract:This article presents a detailed review on developments related to hydrological Frequency Analysis (HFA). All the HFA steps for hypothesis testing, probability distribution tails, and parameter estimation are discussed. These developments on HFA concern nonstationary models in order to consider the effect of covariates on extreme quantile estimation. Such an approach allows one to reduce uncertainty when estimating return period events. Keywords: hydrological Frequency Analysis; hydrological extremes; heavy tailed distributions; generalized maximum likelihood; hypothesis testing; decision support systems
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multivariate hydrological Frequency Analysis using copulas
Water Resources Research, 2004Co-Authors: Annecatherine Favre, Salaheddine El Adlouni, Luc Perreault, Nathalie Thiemonge, Bernard BobéeAbstract:[1] This article presents the modeling of multivariate extreme values using copulas. Our approach allows us to model the dependence structure independently of the marginal distributions, which is not possible with standard classical methods. The methodology has been applied on two different problems in hydrology. The first application is concerned with the combined risk in the framework of Frequency Analysis. Four copulas have been tested on peak flows from the watershed of Peribonka in Quebec, Canada. The second application relates to the joint modeling of peak flows and volumes. Three copulas have been applied to the watershed of the Rimouski River in Quebec, Canada. This approach using copulas is promising since it allows us to take into account a wide range of correlation which can happen in hydrology.
J R M Hosking - One of the best experts on this subject based on the ideXlab platform.
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regional Frequency Analysis an approach based on l moments
Journal of the American Statistical Association, 1997Co-Authors: J R M Hosking, James R WallisAbstract:Preface 1. Regional Frequency Analysis 2. L-moments 3. Screening the data 4. Identification of homogeneous regions 5. Choice of a Frequency distribution 6. Estimation of the Frequency distribution 7. Performance of the regional L-moment algorithm 8. Other topics 9. Examples Appendix References Index of notation.
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some statistics useful in regional Frequency Analysis
Water Resources Research, 1993Co-Authors: J R M Hosking, James R WallisAbstract:Regional Frequency Analysis uses data from a number of measuring sites. A “region” is a group of sites each of which is assumed to have data drawn from the same Frequency distribution. The Analysis involves the assignment of sites to regions, testing whether the proposed regions are indeed homogeneous, and choice of suitable distributions to fit to each region's data. This paper describes three statistics useful in regional Frequency Analysis: a discordancy measure, for identifying unusual sites in a region; a heterogeneity measure, for assessing whether a proposed region is homogeneous; and a goodness-of-fit measure, for assessing whether a candidate distribution provides an adequate fit to the data. Tests based on the statistics provide objective backing for the decisions involved in regional Frequency Analysis. The statistics are based on the L moments [Hosking, 1990] of the at-site data.
Annecatherine Favre - One of the best experts on this subject based on the ideXlab platform.
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multivariate hydrological Frequency Analysis using copulas
Water Resources Research, 2004Co-Authors: Annecatherine Favre, Salaheddine El Adlouni, Luc Perreault, Nathalie Thiemonge, Bernard BobéeAbstract:[1] This article presents the modeling of multivariate extreme values using copulas. Our approach allows us to model the dependence structure independently of the marginal distributions, which is not possible with standard classical methods. The methodology has been applied on two different problems in hydrology. The first application is concerned with the combined risk in the framework of Frequency Analysis. Four copulas have been tested on peak flows from the watershed of Peribonka in Quebec, Canada. The second application relates to the joint modeling of peak flows and volumes. Three copulas have been applied to the watershed of the Rimouski River in Quebec, Canada. This approach using copulas is promising since it allows us to take into account a wide range of correlation which can happen in hydrology.
