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Modelling Uncertainty in Flood Forecasting Systems

Shreedhar Maskey

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English
A A Balkema Publishers
15 May 2004
Like all natural hazards, flooding is a complex and inherently uncertain phenomenon. Despite advances in developing flood forecasting models and techniques, the uncertainty in forecasts remains unavoidable. This uncertainty needs to be acknowledged, and uncertainty estimation in flood forecasting provides a rational basis for risk-based criteria. This book presents the development and applications of various methods based on probablity and fuzzy set theories for modelling uncertainty in flood forecasting systems. In particular, it presents a methodology for uncertainty assessment using disaggregation of time series inputs in the framework of both the Monte Carlo method and the Fuzzy Extention Principle. It reports an improvement in the First Order Second Moment method, using second degree reconstruction, and derives qualitative scales for the interpretation of qualitative uncertainty. Application is to flood forecasting models for the Klodzko catchment in POland and the Loire River in France. Prospects for the hybrid techniques of uncertainty modelling and probability-possibility transformations are also explored and reported.

By:  
Imprint:   A A Balkema Publishers
Dimensions:   Height: 246mm,  Width: 174mm, 
Weight:   317g
ISBN:   9789058096944
ISBN 10:   9058096947
Pages:   192
Publication Date:  
Audience:   College/higher education ,  Professional and scholarly ,  Further / Higher Education ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active
Chapter 1: Introduction, Chapter 2: Flood Forecasting Models and Uncertainy Representation, Chapter 3: Existing Mathematical Methods for Uncertainty Assessment, Chapter 4: Contribution of Present Research to Uncertainty Assessment Methods, Chapter 5: Application: Flood Forecasting Model for Klodzko Catchment (Poland), Chapter 6: Application: Flood Forecasting Model for Loire River (France), Chapter 7: Conclusions and Recommendations, Appendix I: Fuzzy Sets, Fuzzy Arithmetic and Defuzzification, Abbreviations, Notations, References, Samenvatting: Modellering Van Onzekerheid in Systemen Voor Hoogwatervoorspelling, Acknowledgements, About the Author

Shreedhar Maskey was born on 24 December 1966 in Charikot, in the district Dolkha, Nepal. In 1990, he graduated in Civil Engineering from Tribhuvan University in Nepal. Since 1991 he served in the same university as a lecturer until he joined UNESCO-IHE (then IRE-Delft) in 1997 to participate in the Master's Programme in Hydroinformatics. He received the Master of Science degree with distinction in hydro informatics in April 1 999. Since April 1999 he has been at UNESCO-IRE as a PhD research fellow. During this period he also worked for the COWl project (Apr. 1999 - Dec. 1999) and the OS1RIS2 project (Jan. 2000 - Mar. 2003) and assisted in various ways in the Hydroinformatics Master's Programme.

Reviews for Modelling Uncertainty in Flood Forecasting Systems

This book is an excellent one. It is directed to the skeptic engineers who still refuse to embrace concept of uncertainty and continue to use deterministic approaches. This is due to the fact that books dealing with uncertainty seldom include any practical application. Therefore, many engineers assume that uncertainty modeling, be it of probabilistic, fuzzy, or convex nature, are reserved for research only. This book is a welcome harbinger which paves the way to systematic uncertainty analysis as an extremely practical problem.... Dr. Issac Elishakoff, J. M. Rubin Distinguished Professorin Safety, Reliability and Security, Florida Atlantic University writing in Shock and Vibration 13 (2006) 63 IOS Press Shock and Vibration 13 (2006) 63 63 IOS Press Book Review Modeling Uncertainty in Flood Forecasting Systems, by ShreedharMaskey, Taylor and Francis Group plc, London, UK (ISBN 90-5809-6947) This book deals with uncertainty in flood forecasting systems. Author bases his approach by observing that like all natural hazards flooding is complex and inherently uncertain phenomenon. Author applies probability theory and fuzzy sets based theory; central point is the development of improved first-order second moment method using a second-order reconstruction of the model function. The temporal disaggregation method, presented in Chapter 4 (the previous one dealing with genuine randomness, fuzziness or their hybrid) is utilized in Chapter 5 to flood forecasting model of Klodzko catchment located on the river Nysa Klodzka in Poland; Chapter 6 utilizes the same model for Loire River in France. Author recommends risk based flood forecasting and warning systems. This book is an excellent one. It is directed to the skeptic engineers who still refuse to embrace concept of uncertainty and continue to use deterministic approaches. This is due to the fact that books dealing with uncertainty seldom include any practical application. Therefore, many engineers assume that uncertainty modeling, be it of probabilistic, fuzzy, or convex nature, are reserved for research only. This book is a welcome harbinger which paves the way to systematic uncertainty analysis as an extremely practical problem. Dr. Issac Elishakoff J. M. Rubin Distinguished Professor in Safety, Reliability and Security College of Engineering Florida Atlantic University Boca Raton, FL 33431-2825, USA E-mail: elishako@fau.edu ISSN 1070-9622/06/$17.00 (c) 2006 - IOS Press and the authors. All rights reserved


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