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

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, in...

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Bibliographic Details
Published in:Hydrological processes 2002-03, Vol.16 (5), p.1065-1084
Main Authors: Alila, Younes, Mtiraoui, Ahmed
Format: Article
Language:English
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Summary: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. Copyright © 2002 John Wiley & Sons, Ltd.
ISSN:0885-6087
1099-1085
DOI:10.1002/hyp.346