COUPLING OF NONPARAMETRIC FREQUENCY AND L‐MOMENT ANALYSES FOR MIXED DISTRIBUTION IDENTIFICATION <sup>1</sup>

Gingras, D.; Adamowski, Kaz

doi:10.1111/j.1752-1688.1992.tb03992.x

Cited by 27 publications

(15 citation statements)

References 17 publications

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“…Two recent investigations have suggested that the GEV distribution might be an improved alternative to the LP3 for flood-frequency analysis in the USA (Vogel et al, 1993a;Vogel and Wilson, 1996), particularly when using L-moments. Vogel and Wilson (1996) Continental USA LN3, GEV and LP3 1490 Onoz and Bayazit (1995) Different parts of the world GEV 19 Karim and Chowdhury (1995) Bangladesh GEV 31 IH (1999) UK GLO 1000 Vogel et al (1993b) Australia GEV, GP and LP3 61 Vogel et al (1993a) Southwestern USA LN3, LN2, GEV and LP3 383 Gingras and Adamowski (1992) New Brunswick, Canada GEV 53 Pilon and Adamowski (1992) Nova Scotia, Canada GEV 25 Pearson (1991) South Island, New Zealand EV1, EV2 and GEV 275 Nathan and Weinmann (1991) Central Victoria, Australia GEV 53 Wallis (1988) Eastern USA GEV 55…”

Section: Analysis Of Floods Using Homogeneous Frequency Distributionsmentioning

confidence: 99%

Implications of heterogeneous flood‐frequency distributions on traditional stream‐discharge prediction techniques

Alila

Mtiraoui

2002

Hydrological Processes

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Abstract:Traditional flood-frequency analysis involves the assumption of homogeneity of the flood distribution. However, floods are often generated by heterogeneous distributions composed of a mixture of two or more populations. Differences between the populations may be the result of a number of factors, including seasonal variations in the flood-producing mechanisms, changes in weather patterns resulting from low-frequency climate shifts and/or El Niño/La Nina oscillations, changes in channel routing owing to the dominance of within-channel or floodplain flow, and basin variability resulting from changes in antecedent soil moisture. Not recognizing these physical processes in conventional flood-frequency analysis probably is the main reason that many frequency distributions do not provide an acceptable fit to flood data. In this paper, we use long-term hydroclimatic records from the Gila River basin of south-east and central Arizona in the USA to explore the extent and significance of mixed populations. First, we discuss the probable causes of heterogeneity in the frequency distribution of annual flood and present evidence of its occurrence. Second, we investigate the implications of using various popular homogeneous distributions for predicting peak flows for basins that exhibit mixed population characteristics. Third, we demonstrate how alternative frequency models that explicitly account for floods generated by a mixture of two or more populations are both hydrologically and statistically more appropriate. We illustrate how the selection of the most plausible distribution for flood-frequency analysis also should be based on hydrological reasoning as opposed to the sole application of the traditional statistical goodness-of-fit tests.

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Section: Analysis Of Floods Using Homogeneous Frequency Distributionsmentioning

confidence: 99%

Implications of heterogeneous flood‐frequency distributions on traditional stream‐discharge prediction techniques

Alila

Mtiraoui

2002

Hydrological Processes

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“…A partitioning of annual maximum floods in New Brunswick by seasons indicated a strong, although imperfect, correlation between seasonal occurrence and flood mechanism (Gingras & Adamowski, 1992). Sample sizes of less than 20 years for many stations, along with poor coordination between meteorological and hydrometric stations, made some of the analysis uncertain.…”

Section: Fig 2 Climatic Regions Of New Brunswick (Taken From Inlandmentioning

confidence: 99%

“…The 53 stations were classified into three distinct groupings based on probability density function shape: a unimodal group, a bimodal group and a heavy-tailed group. It should be noted here that, for the bimodal and heavy-tailed group, parametric flood frequency would have fitted a unimodal, and therefore unsuitable, distribution to the data (Gingras & Adamowski, 1992).…”

Section: Fig 4 Cumulative Frequency Functions For Lepreau River At Lmentioning

confidence: 99%

“…The test was applied (Gingras & Adamowski, 1992) to the entire 53 stations resulting in three heterogeneity measures between 1 and 2, implying that the New Brunswick flood data set was possibly heterogeneous. The same test was then applied to the 44 stations from the delineated homogeneous bimodal region, resulting in three heterogeneity measures less than 1.…”

Section: Fig 8 Probability Density Function For Lepreaumentioning

confidence: 99%

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Homogeneous region delineation based on annual flood generation mechanisms

Gingras

Adamowski

1993

Hydrological Sciences Journal

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Flood distributions can have unimodal or multimodal densities due to different flood generation mechanisms such as snowmelt and rainfall in the annual flood series. When applying nonparametric frequency analysis to annual flood data from the province of New Brunswick in Canada, unimodal, bimodal and heavy-tailed distribution shapes were found. By grouping basins with similarly-shaped densities on a geographical basis, homogeneous regions were delineated. Regional equations derived for a homogeneous region gave lower integral square errors than those of province-wide equations. Délimitation de régions homogènes basée sur le mécanisme de la genèse de la crue annuelleRésumé Les distributions des crues peuvent avoir des densités unimodales ou multimodales par suite de différents mécanismes tels que la fonte des neiges et la pluie dans la série annuelle des crues. En applicant l'analyse de fréquence non-paramétrique aux crues de la province du Nouveau-Brunswick au Canada, des distributions unimodales, bimodales et avec grande queue ont été découvertes. En groupant des bassins avec des densités de même forme sur une base géographique, des régions homogènes ont été délimitées. Des équations régionales pour une région homogène ont donné des erreurs carrées intégrées plus petites que celles des équations pour la province entière.

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“…• Régions géographiquement contiguës : Ces régions peuvent être définies, par exemple, à partir de la similarité des densités non paramétriques des débits de crues GINGRAS et ADAMOWSKI, 1992;GINGRAS et al, 1994;HOSKING et WALLIS, 1993). La validation de cette méthode est réalisée avec l'application des L-moments.…”

Section: Approche Basée Sur Des Régions Fixesunclassified

Régionalisation des débits moyens mensuels en Algérie du nord

Touazi¹,

Bhiry

Laborde

et al. 2011

rseau

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L'identification des régions ayant des caractéristiques hydrologiques homogènes en Algérie du Nord représente l'objectif principal de cette étude. L'analyse en composantes principales (ACP) et la classification par les composantes principales dynamiques (CPD) ont été appliquées sur les débits moyens mensuels de 51 stations hydrométriques. Les résultats de l'ACP ont montré l'existence de trois groupes hydrologiquement homogènes. La mise en oeuvre de la méthode CPD a aussi mis en évidence les trois mêmes groupes. Les types de régimes mis en évidence avec les deux méthodes sont de types simple, mixte et complexe. Le type de climat qui caractérise ces groupes est méditerranéen pour le premier, transition entre méditerranéen et semi-aride pour le deuxième et semi-aride pour le troisième groupe.

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COUPLING OF NONPARAMETRIC FREQUENCY AND L‐MOMENT ANALYSES FOR MIXED DISTRIBUTION IDENTIFICATION ¹

Cited by 27 publications

References 17 publications

Implications of heterogeneous flood‐frequency distributions on traditional stream‐discharge prediction techniques

Implications of heterogeneous flood‐frequency distributions on traditional stream‐discharge prediction techniques

Homogeneous region delineation based on annual flood generation mechanisms

Régionalisation des débits moyens mensuels en Algérie du nord

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COUPLING OF NONPARAMETRIC FREQUENCY AND L‐MOMENT ANALYSES FOR MIXED DISTRIBUTION IDENTIFICATION 1

Cited by 27 publications

References 17 publications

Implications of heterogeneous flood‐frequency distributions on traditional stream‐discharge prediction techniques

Implications of heterogeneous flood‐frequency distributions on traditional stream‐discharge prediction techniques

Homogeneous region delineation based on annual flood generation mechanisms

Régionalisation des débits moyens mensuels en Algérie du nord

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COUPLING OF NONPARAMETRIC FREQUENCY AND L‐MOMENT ANALYSES FOR MIXED DISTRIBUTION IDENTIFICATION ¹