Using persistent homology as preprocessing of early warning signals for critical transition in flood

Abstract Flood early warning systems (FLEWSs) contribute remarkably to reducing economic and life losses during a flood. The theory of critical slowing down (CSD) has been successfully used as a generic indicator of early warning signals in various fields. A new tool called persistent homology (PH)...

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Autores principales:	Syed Mohamad Sadiq Syed Musa, Mohd Salmi Md Noorani, Fatimah Abdul Razak, Munira Ismail, Mohd Almie Alias, Saiful Izzuan Hussain
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/53335c58414f47e98b060c16ce1eb30f
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spelling	oai:doaj.org-article:53335c58414f47e98b060c16ce1eb30f2021-12-02T14:25:09ZUsing persistent homology as preprocessing of early warning signals for critical transition in flood10.1038/s41598-021-86739-52045-2322https://doaj.org/article/53335c58414f47e98b060c16ce1eb30f2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86739-5https://doaj.org/toc/2045-2322Abstract Flood early warning systems (FLEWSs) contribute remarkably to reducing economic and life losses during a flood. The theory of critical slowing down (CSD) has been successfully used as a generic indicator of early warning signals in various fields. A new tool called persistent homology (PH) was recently introduced for data analysis. PH employs a qualitative approach to assess a data set and provide new information on the topological features of the data set. In the present paper, we propose the use of PH as a preprocessing step to achieve a FLEWS through CSD. We test our proposal on water level data of the Kelantan River, which tends to flood nearly every year. The results suggest that the new information obtained by PH exhibits CSD and, therefore, can be used as a signal for a FLEWS. Further analysis of the signal, we manage to establish an early warning signal for ten of the twelve flood events recorded in the river; the two other events are detected on the first day of the flood. Finally, we compare our results with those of a FLEWS constructed directly from water level data and find that FLEWS via PH creates fewer false alarms than the conventional technique.Syed Mohamad Sadiq Syed MusaMohd Salmi Md NooraniFatimah Abdul RazakMunira IsmailMohd Almie AliasSaiful Izzuan HussainNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Syed Mohamad Sadiq Syed Musa Mohd Salmi Md Noorani Fatimah Abdul Razak Munira Ismail Mohd Almie Alias Saiful Izzuan Hussain Using persistent homology as preprocessing of early warning signals for critical transition in flood
description	Abstract Flood early warning systems (FLEWSs) contribute remarkably to reducing economic and life losses during a flood. The theory of critical slowing down (CSD) has been successfully used as a generic indicator of early warning signals in various fields. A new tool called persistent homology (PH) was recently introduced for data analysis. PH employs a qualitative approach to assess a data set and provide new information on the topological features of the data set. In the present paper, we propose the use of PH as a preprocessing step to achieve a FLEWS through CSD. We test our proposal on water level data of the Kelantan River, which tends to flood nearly every year. The results suggest that the new information obtained by PH exhibits CSD and, therefore, can be used as a signal for a FLEWS. Further analysis of the signal, we manage to establish an early warning signal for ten of the twelve flood events recorded in the river; the two other events are detected on the first day of the flood. Finally, we compare our results with those of a FLEWS constructed directly from water level data and find that FLEWS via PH creates fewer false alarms than the conventional technique.
format	article
author	Syed Mohamad Sadiq Syed Musa Mohd Salmi Md Noorani Fatimah Abdul Razak Munira Ismail Mohd Almie Alias Saiful Izzuan Hussain
author_facet	Syed Mohamad Sadiq Syed Musa Mohd Salmi Md Noorani Fatimah Abdul Razak Munira Ismail Mohd Almie Alias Saiful Izzuan Hussain
author_sort	Syed Mohamad Sadiq Syed Musa
title	Using persistent homology as preprocessing of early warning signals for critical transition in flood
title_short	Using persistent homology as preprocessing of early warning signals for critical transition in flood
title_full	Using persistent homology as preprocessing of early warning signals for critical transition in flood
title_fullStr	Using persistent homology as preprocessing of early warning signals for critical transition in flood
title_full_unstemmed	Using persistent homology as preprocessing of early warning signals for critical transition in flood
title_sort	using persistent homology as preprocessing of early warning signals for critical transition in flood
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/53335c58414f47e98b060c16ce1eb30f
work_keys_str_mv	AT syedmohamadsadiqsyedmusa usingpersistenthomologyaspreprocessingofearlywarningsignalsforcriticaltransitioninflood AT mohdsalmimdnoorani usingpersistenthomologyaspreprocessingofearlywarningsignalsforcriticaltransitioninflood AT fatimahabdulrazak usingpersistenthomologyaspreprocessingofearlywarningsignalsforcriticaltransitioninflood AT muniraismail usingpersistenthomologyaspreprocessingofearlywarningsignalsforcriticaltransitioninflood AT mohdalmiealias usingpersistenthomologyaspreprocessingofearlywarningsignalsforcriticaltransitioninflood AT saifulizzuanhussain usingpersistenthomologyaspreprocessingofearlywarningsignalsforcriticaltransitioninflood
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Using persistent homology as preprocessing of early warning signals for critical transition in flood

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