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100%: Rao, A. Ramachandra;Srinivas, V. V.: Regionalization of Watersheds (ISBN: 9781402068522) 2008, in Englisch, auch als eBook.Nur diese Ausgabe anzeigen…
42%: Rao, A. Ramachandra;Srinivas, V. V.: REGIONALIZATION OF WATERSHEDS: AN APPROACH BASED ON CLUSTER ANALYSIS (WATER SCIENCE AND TECHNOLOGY LIBRARY, VOLUME 58) (ISBN: 9781402068515) 2008, Springer Apr 2008, 2008. Ausgabe, in Englisch, Broschiert.Nur diese Ausgabe anzeigen…
Regionalization of Watersheds - 6 Angebote vergleichen
| Preise | 2013 | 2014 | 2018 | 2020 |
|---|---|---|---|---|
| Schnitt | € 53,49 | € 110,96 | € 117,86 | € 143,00 |
| Nachfrage |
1
Regionalization of Watersheds (2008)
~EN NW EBISBN: 9781402068522 bzw. 1402068522, vermutlich in Englisch, Springer, neu, E-Book.
Lieferung aus: Österreich, Sofort per Download lieferbar.
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. TOC:Preface. 1. Introduction. 2. Regionalization by hybrid cluster analysis. 3. Regionalization by fuzzy cluster analysis. 4. Regionalization by artificial neural networks. 5. Effect of regionalization on flood frequency analysis. 6. Concluding remarks. References. Index of notation. Abbreviations. Index. PDF, 18.04.2008.
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. TOC:Preface. 1. Introduction. 2. Regionalization by hybrid cluster analysis. 3. Regionalization by fuzzy cluster analysis. 4. Regionalization by artificial neural networks. 5. Effect of regionalization on flood frequency analysis. 6. Concluding remarks. References. Index of notation. Abbreviations. Index. PDF, 18.04.2008.
2
Regionalization of Watersheds - An Approach Based on Cluster Analysis
EN NW EB DLISBN: 9781402068522 bzw. 1402068522, in Englisch, Springer Netherlands, neu, E-Book, elektronischer Download.
Lieferung aus: Deutschland, E-Book zum Download.
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, practitioner.
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, practitioner.
3
Regionalization of Watersheds
EN NWISBN: 9781402068522 bzw. 1402068522, in Englisch, Springer Netherland, neu.
Lieferung aus: Deutschland, sofort lieferbar.
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.
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.
4
Regionalization of Watersheds als eBook von A.R. Rao, V. V. Srinivas, A. Ramachandra Rao, V. V. Srinivas (2008)
EN NW EB DLISBN: 9781402068522 bzw. 1402068522, in Englisch, Springer Netherlands, neu, E-Book, elektronischer Download.
Regionalization of Watersheds ab 111.49 EURO An Approach Based on Cluster Analysis. Auflage 2008.
5
Regionalization of Watersheds
EN NW EBISBN: 9781402068522 bzw. 1402068522, in Englisch, Springer Nature, neu, E-Book.
Lieferung aus: Vereinigte Staaten von Amerika, In Stock.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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