Bivariate flood frequency analysis: Part1. Determination of marginals by parametric and nonparametric techniques
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Title |
Bivariate flood frequency analysis: Part1. Determination of marginals by parametric and nonparametric techniques
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Creator |
KARMAKAR, S
SIMONOVIC, SP |
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Subject |
hydrological application
bandwidth selection probability density model series copula flood frequency analysis kernel density nonparametric orthonormal series parametric |
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Description |
In flood frequency analysis, a flood event is mainly characterized by peak flow, volume and duration. These three variables or characteristics of floods are random in nature and mutually correlated. In this article, an effort is made to find out appropriate marginal distribution of the flood characteristics considering a set of parametric and nonparametric distributions, and further mathematically model the correlated nature among them. A set of parametric distribution functions and nonparametric methods based on kernel density estimation and orthonormal series are used to determine the marginal distribution functions for peak flow, volume and duration. In conventional methods of flood frequency analysis, the marginal distribution functions of peak flow, volume and duration are assumed to follow some specific parametric distribution function. The present work performs a better selection of marginal distribution functions for flood characteristics as both parametric and nonparametric estimation procedures are extensively followed. The methodology is demonstrated with 70-year stream flow data of Red River at Grand Forks of North Dakota, USA.
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Publisher |
WILEY-BLACKWELL PUBLISHING, INC
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Date |
2011-09-01T11:20:19Z
2011-12-26T12:59:37Z 2011-12-27T05:52:09Z 2011-09-01T11:20:19Z 2011-12-26T12:59:37Z 2011-12-27T05:52:09Z 2008 |
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Type |
Article
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Identifier |
JOURNAL OF FLOOD RISK MANAGEMENT, 1(4), 190-200
1753-318X http://dx.doi.org/10.1111/j.1753-318X.2008.00022.x http://dspace.library.iitb.ac.in/xmlui/handle/10054/12764 http://hdl.handle.net/10054/12764 |
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Language |
en
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