Examining Flood Frequency Distributions in the Midwest U.S.

Authors

  • Gabriele Villarini,

    1. Respectively, Research Associate (Villarini), Professor (Smith), and Research Staff (Baeck), Department of Civil and Environmental Engineering, Princeton University, Engineering Quadrangle, Princeton, New Jersey 08540
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  • James A. Smith,

    1. Respectively, Research Associate (Villarini), Professor (Smith), and Research Staff (Baeck), Department of Civil and Environmental Engineering, Princeton University, Engineering Quadrangle, Princeton, New Jersey 08540
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  • Mary Lynn Baeck,

    1. Respectively, Research Associate (Villarini), Professor (Smith), and Research Staff (Baeck), Department of Civil and Environmental Engineering, Princeton University, Engineering Quadrangle, Princeton, New Jersey 08540
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  • Witold F. Krajewski

    1. Professor (Krajewski), IIHR-Hydroscience and Engineering, The University of Iowa, 100 C. Maxwell Stanley Hydraulics Laboratory, Iowa City, Iowa 52242
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  • Paper No. JAWRA-10-0046-P of the Journal of the American Water Resources Association (JAWRA). Discussions are open until six months from print publication.

(E-Mail/Villarini: gvillari@princeton.edu).

Abstract

Villarini, Gabriele, James A. Smith, Mary Lynn Baeck, and Witold F. Krajewski, 2011. Examining Flood Frequency Distributions in the Midwest U.S. Journal of the American Water Resources Association (JAWRA) 47(3):447-463. DOI: 10.1111/j.1752-1688.2011.00540.x

Abstract:  Annual maximum peak discharge time series from 196 stream gage stations with a record of at least 75 years from the Midwest United States is examined to study flood peak distributions from a regional point of view. The focus of this study is to evaluate: (1) “mixtures” of flood peak distributions, (2) upper tail and scaling properties of the flood peak distributions, and (3) presence of temporal nonstationarities in the flood peak records. Warm season convective systems are responsible for some of the largest floods in the area, in particular in Nebraska, Kansas, and Iowa. Spring events associated with snowmelt and rain-on-snow are common in the northern part of the study domain. Nonparametric tests are used to investigate the presence of abrupt and slowly varying changes. Change-points rather than monotonic trends are responsible for most violations of the stationarity assumption. The abrupt changes in flood peaks can be associated with anthropogenic changes, such as changes in land use/land cover, agricultural practice, and construction of dams. The trend analyses do not suggest an increase in the flood peak distribution due to anthropogenic climate change. Examination of the upper tail and scaling properties of the flood peak distributions are examined by means of the location, scale, and shape parameters of the Generalized Extreme Value distribution.

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