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2016 | OriginalPaper | Chapter

3. Predicting Cyclone Induced Flood: A Comprehensive Case Study

Authors : Isuri Wijesundera, Malka N. Halgamuge, Thrishantha Nanayakkara, Thas Nirmalathas

Published in: Natural Disasters, When Will They Reach Me?

Publisher: Springer Singapore

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Abstract

The prediction of \({\textit{MFPT}}\) in the propagation of cyclone induced flood is comprehensively discussed in this chapter as a special case study to gain an entrance to a more generic study in the proceeding chapters. The inhomogeneity in terrain is addressed using a novel concept of dividing the terrain into geographic primitives (GPs) identified through flood propagation vector fields. A modularised approach including a Bayesian framework is followed allowing easy and flexible assimilation of data and integration of outputs from other models when they become available. Simultaneous events distributed in the environment leading to biased propagation are encapsulated into transition probability matrices (TPM) allowing efficient real time predictions via computation through a Markov chain. Comparative studies using real datasets show the models ability of predicting up to 3 h ahead of official forecasts with a 33 % improvement of accuracy when compared to other models currently used.

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previous chapter Background Guide to Random Walk Analysis
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Appendix
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Metadata
Title
Predicting Cyclone Induced Flood: A Comprehensive Case Study
Authors
Isuri Wijesundera
Malka N. Halgamuge
Thrishantha Nanayakkara
Thas Nirmalathas
Copyright Year
2016
Publisher
Springer Singapore
Book
Natural Disasters, When Will They Reach Me?

Print ISBN: 978-981-10-1111-5

Electronic ISBN: 978-981-10-1113-9

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-981-10-1113-9_3

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