Uncertainty Analysis in Rainfall-Runoff Modelling - Application of Machine Learning Techniques: UNESCO-IHE PhD Thesis

Durga Lal Shrestha

ISBN 10: 0415565987 / ISBN 13: 9780415565981

Published by Taylor & Francis Ltd, 2009

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Bibliographic Details

• Title: Uncertainty Analysis in Rainfall-Runoff Modelling - Application of Machine Learning Techniques: UNESCO-IHE PhD Thesis
• Publisher: Taylor & Francis Ltd
• Publication Date: 2009
• Language: English
• ISBN 10: 0415565987
• ISBN 13: 9780415565981
• Binding: Paperback / softback
• Condition: New
• Weight: 422 grams

About this title

Synopsis

This book describes the use of machine learning techniques to build predictive models of uncertainty with application to hydrological models, focusing mainly on the development and testing of two different models. The first focuses on parameter uncertainty analysis by emulating the results of Monte Carlo simulation of hydrological models using efficient machine learning techniques. The second method aims at modelling uncertainty by building an ensemble of specialized machine learning models on the basis of past hydrological model’s performance. The book then demonstrates the capacity of machine learning techniques for building accurate and efficient predictive models of uncertainty.

About the Author

Durga Lal Shrestha is a researcher in the Hydroinformatics and Knowledge Management Department of the UNESCO-IHE Institute for Water Education, Netherlands. He received his Masters degree in hydroinformatics from the UNESCO-IHE Institute for Water Education in 2002. His research interests include hydrological modelling, uncertainty analysis, global and evolutionary optimisation, machine learning techniques and their applications in water based systems.