Regionalization of Watersheds : An Approach Based on Cluster Analysis

Rao, A. R.; Srinivas, V. V.

ISBN 10: 9048177375 ISBN 13: 9789048177370
Edité par Springer, 2010
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Design of water control structures, reservoir management, economic evaluation of flood protection projects, land use planning and management, flood insurance assessment, and other projects rely on knowledge of magnitude and frequency of floods. Often, estimation of floods is not easy because of lack of flood records at the target sites. Regional flood frequency analysis (RFFA) alleviates this problem by utilizing flood records pooled from other watersheds, which are similar to the watershed of the target site in flood characteristics.

Clustering techniques are used to identify group(s) of watersheds which have similar flood characteristics. This book is a comprehensive reference on how to use these techniques for RFFA and is the first of its kind. It provides a detailed account of several recently developed clustering techniques, including those based on fuzzy set theory and artificial neural networks. It also documents research findings on application of clustering techniques to RFFA that remain scattered in various hydrology and water resources journals.

The optimal number of groups defined in an area is based on cluster validation measures and L-moment based homogeneity tests. These form the bases to check the regions for homogeneity.

The subjectivity involved and the effort needed to identify homogeneous groups of watersheds with conventional approaches are greatly reduced by using efficient clustering techniques discussed in this book. Furthermore, better flood estimates with smaller confidence intervals are obtained by analysis of data from homogeneous watersheds. Consequently, the problem of over- or under-designing by using these flood estimates is reduced. This leads to optimal economic design of structures. The advantages of better regionalization of watersheds and their utility are entering into hydrologic practice.

Audience:
This book will be of interest to researchers in stochastic hydrology, practitioners in hydrology and graduate students.

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Titre : Regionalization of Watersheds : An Approach ...
Éditeur : Springer
Date d'édition : 2010
Reliure : Couverture souple
Etat : New

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A.R. Rao|V. V. Srinivas
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The only book on this topicSummarizes and illustrates the research in this topicBrings out the benefits of regionalizationDelineates the problems which need to be addressed in this research topicClustering techniques are u. N° de réf. du vendeur 5821574

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Rao, A.R.; Srinivas, V. V.
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A.R. Rao
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Paperback. Etat : new. Paperback. Design of water control structures, reservoir management, economic evaluation of flood protection projects, land use planning and management, flood insurance assessment, and other projects rely on knowledge of magnitude and frequency of floods. Often, estimation of floods is not easy because of lack of flood records at the target sites. Regional flood frequency analysis (RFFA) alleviates this problem by utilizing flood records pooled from other watersheds, which are similar to the watershed of the target site in flood characteristics.Clustering techniques are used to identify group(s) of watersheds which have similar flood characteristics. This book is a comprehensive reference on how to use these techniques for RFFA and is the first of its kind. It provides a detailed account of several recently developed clustering techniques, including those based on fuzzy set theory and artificial neural networks. It also documents research findings on application of clustering techniques to RFFA that remain scattered in various hydrology and water resources journals.The optimal number of groups defined in an area is based on cluster validation measures and L-moment based homogeneity tests. These form the bases to check the regions for homogeneity. The subjectivity involved and the effort needed to identify homogeneous groups of watersheds with conventional approaches are greatly reduced by using efficient clustering techniques discussed in this book. Furthermore, better flood estimates with smaller confidence intervals are obtained by analysis of data from homogeneous watersheds. Consequently, the problem of over- or under-designing by using these flood estimates is reduced. This leads to optimal economic design of structures. The advantages of better regionalization of watersheds and their utility are entering into hydrologic practice. Audience:This book will be of interest to researchers in stochastic hydrology, practitioners in hydrology and graduate students. Design of water control structures, reservoir management, economic evaluation of flood protection projects, land use planning and management, flood insurance assessment, and other projects rely on knowledge of magnitude and frequency of floods. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9789048177370

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V. V. Srinivas
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Clustering techniques are used to identify groups of watersheds which have similar flood characteristics. This book, the first of its kind, is a comprehensive reference on how to use these techniques for regional flood frequency analysis. It provides a detailed account of several recently developed clustering techniques, including those based on fuzzy set theory. It also brings together formerly scattered research findings on the application of clustering techniques to RFFA. 260 pp. Englisch. N° de réf. du vendeur 9789048177370

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V. V. Srinivas
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Design of water control structures, reservoir management, economic evaluation of flood protection projects, land use planning and management, flood insurance assessment, and other projects rely on knowledge of magnitude and frequency of floods. Often, estimation of floods is not easy because of lack of flood records at the target sites. Regional flood frequency analysis (RFFA) alleviates this problem by utilizing flood records pooled from other watersheds, which are similar to the watershed of the target site in flood characteristics.Clustering techniques are used to identify group(s) of watersheds which have similar flood characteristics. This book is a comprehensive reference on how to use these techniques for RFFA and is the first of its kind. It provides a detailed account of several recently developed clustering techniques, including those based on fuzzy set theory and artificial neural networks. It also documents research findings on application of clustering techniques to RFFA that remain scattered in various hydrology and water resources journals.The optimal number of groups defined in an area is based on cluster validation measures and L-moment based homogeneity tests. These form the bases to check the regions for homogeneity.The subjectivity involved and the effort needed to identify homogeneous groups of watersheds with conventional approaches are greatly reduced by using efficient clustering techniques discussed in this book. Furthermore, better flood estimates with smaller confidence intervals are obtained by analysis of data from homogeneous watersheds. Consequently, the problem of over- or under-designing by using these flood estimates is reduced. This leads to optimal economic design of structures. The advantages of better regionalization of watersheds and their utility are entering into hydrologic practice.Audience:This book will be of interest to researchers in stochastic hydrology, practitioners in hydrology and graduate students.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 260 pp. Englisch. N° de réf. du vendeur 9789048177370

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V. V. Srinivas
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Design of water control structures, reservoir management, economic evaluation of flood protection projects, land use planning and management, flood insurance assessment, and other projects rely on knowledge of magnitude and frequency of floods. Often, estimation of floods is not easy because of lack of flood records at the target sites. Regional flood frequency analysis (RFFA) alleviates this problem by utilizing flood records pooled from other watersheds, which are similar to the watershed of the target site in flood characteristics.Clustering techniques are used to identify group(s) of watersheds which have similar flood characteristics. This book is a comprehensive reference on how to use these techniques for RFFA and is the first of its kind. It provides a detailed account of several recently developed clustering techniques, including those based on fuzzy set theory and artificial neural networks. It also documents research findings on application of clustering techniques to RFFA that remain scattered in various hydrology and water resources journals.The optimal number of groups defined in an area is based on cluster validation measures and L-moment based homogeneity tests. These form the bases to check the regions for homogeneity. The subjectivity involved and the effort needed to identify homogeneous groups of watersheds with conventional approaches are greatly reduced by using efficient clustering techniques discussed in this book. Furthermore, better flood estimates with smaller confidence intervals are obtained by analysis of data from homogeneous watersheds. Consequently, the problem of over- or under-designing by using these flood estimates is reduced. This leads to optimal economic design of structures. The advantages of better regionalization of watersheds and their utility are entering into hydrologic practice. Audience:This book will be of interest to researchers in stochastic hydrology, practitioners in hydrology and graduate students. N° de réf. du vendeur 9789048177370

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