Title

Copula-based flood frequency (COFF) analysis at the confluences of river systems

Authors

Authors

C. Wang; N. B. Chang;G. T. Yeh

Comments

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Abbreviated Journal Title

Hydrol. Process.

Keywords

confluence point; copula; flood frequency analysis; hydrological; process; joint probability; Monte Carlo simulation; BIVARIATE DISTRIBUTIONS; ARCHIMEDEAN COPULAS; GAMMA-DISTRIBUTION; MODEL; DURATION; INFERENCE; MARGINALS; RAINFALL; VOLUME; Water Resources

Abstract

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 flood, 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 (C) 2009 John Wiley & Sons, Ltd.

Journal Title

Hydrological Processes

Volume

23

Issue/Number

10

Publication Date

1-1-2009

Document Type

Article

Language

English

First Page

1471

Last Page

1486

WOS Identifier

WOS:000266193200008

ISSN

0885-6087

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