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

    Authors

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

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    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

    Share

    COinS