Streamflow data analysis using persistent homology

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Understanding streamflow data can be important climatic indicators for environmental risk problems such as flooding. Recently, topological data analysis (TDA) gave a new insight in data analysis. The main idea in TDA is to used results based on topology to develop tools for studying qualitative features or shape-like structure of data. Persistent homology (PH) is one of the tools in TDA that focuses on aspects of topological features in data that persists across multiple scales. So the question here is, can PH detect flood based on streamflow data. Therefore, the first attempt of streamflow analysis using PH was conducted at Guillemard Bridge Station, Kelantan River, Malaysia. Analysis for streamflow data during dry period, wet period and flood events were perform using TDA approach. The analysis result shows that PH can detect the pattern of topological features in streamflow data. The analysis suggests that the presence of short-lived topological features indicates dry period while long-lived topological features for wet period. Based on the streamflow data of flood events, PH consistently captured long-lived topological features of the data.

Original languageEnglish
Title of host publication2018 UKM FST Postgraduate Colloquium
Subtitle of host publicationProceedings of the Universiti Kebangsaan Malaysia, Faculty of Science and Technology 2018 Postgraduate Colloquium
EditorsNoor Hayati Ahmad Rasol, Kamarulzaman Ibrahim, Siti Aishah Hasbullah, Mohammad Hafizuddin Hj. Jumali, Nazlina Ibrahim, Marlia Mohd Hanafiah, Mohd Talib Latif
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735418431
DOIs
Publication statusPublished - 27 Jun 2019
Event2018 UKM FST Postgraduate Colloquium - Selangor, Malaysia
Duration: 4 Apr 20186 Apr 2018

Publication series

NameAIP Conference Proceedings
Volume2111
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference2018 UKM FST Postgraduate Colloquium
CountryMalaysia
CitySelangor
Period4/4/186/4/18

Fingerprint

homology
stream flow
streamflow
data analysis
Malaysia
environmental indicators
rivers
topology
stations
environmental risk
flooding
analysis
river

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Plant Science
  • Physics and Astronomy(all)
  • Nature and Landscape Conservation

Cite this

Musa, S. M. S., Md. Noorani, M. S., Abdul Razak, F., Ismail, M., & Alias, M. A. (2019). Streamflow data analysis using persistent homology. In N. H. A. Rasol, K. Ibrahim, S. A. Hasbullah, M. H. H. Jumali, N. Ibrahim, M. M. Hanafiah, & M. T. Latif (Eds.), 2018 UKM FST Postgraduate Colloquium: Proceedings of the Universiti Kebangsaan Malaysia, Faculty of Science and Technology 2018 Postgraduate Colloquium [020021] (AIP Conference Proceedings; Vol. 2111). American Institute of Physics Inc.. https://doi.org/10.1063/1.5111228

Streamflow data analysis using persistent homology. / Musa, S. M.S.; Md. Noorani, Mohd. Salmi; Abdul Razak, Fatimah; Ismail, Munira; Alias, M. A.

2018 UKM FST Postgraduate Colloquium: Proceedings of the Universiti Kebangsaan Malaysia, Faculty of Science and Technology 2018 Postgraduate Colloquium. ed. / Noor Hayati Ahmad Rasol; Kamarulzaman Ibrahim; Siti Aishah Hasbullah; Mohammad Hafizuddin Hj. Jumali; Nazlina Ibrahim; Marlia Mohd Hanafiah; Mohd Talib Latif. American Institute of Physics Inc., 2019. 020021 (AIP Conference Proceedings; Vol. 2111).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Musa, SMS, Md. Noorani, MS, Abdul Razak, F, Ismail, M & Alias, MA 2019, Streamflow data analysis using persistent homology. in NHA Rasol, K Ibrahim, SA Hasbullah, MHH Jumali, N Ibrahim, MM Hanafiah & MT Latif (eds), 2018 UKM FST Postgraduate Colloquium: Proceedings of the Universiti Kebangsaan Malaysia, Faculty of Science and Technology 2018 Postgraduate Colloquium., 020021, AIP Conference Proceedings, vol. 2111, American Institute of Physics Inc., 2018 UKM FST Postgraduate Colloquium, Selangor, Malaysia, 4/4/18. https://doi.org/10.1063/1.5111228
Musa SMS, Md. Noorani MS, Abdul Razak F, Ismail M, Alias MA. Streamflow data analysis using persistent homology. In Rasol NHA, Ibrahim K, Hasbullah SA, Jumali MHH, Ibrahim N, Hanafiah MM, Latif MT, editors, 2018 UKM FST Postgraduate Colloquium: Proceedings of the Universiti Kebangsaan Malaysia, Faculty of Science and Technology 2018 Postgraduate Colloquium. American Institute of Physics Inc. 2019. 020021. (AIP Conference Proceedings). https://doi.org/10.1063/1.5111228
Musa, S. M.S. ; Md. Noorani, Mohd. Salmi ; Abdul Razak, Fatimah ; Ismail, Munira ; Alias, M. A. / Streamflow data analysis using persistent homology. 2018 UKM FST Postgraduate Colloquium: Proceedings of the Universiti Kebangsaan Malaysia, Faculty of Science and Technology 2018 Postgraduate Colloquium. editor / Noor Hayati Ahmad Rasol ; Kamarulzaman Ibrahim ; Siti Aishah Hasbullah ; Mohammad Hafizuddin Hj. Jumali ; Nazlina Ibrahim ; Marlia Mohd Hanafiah ; Mohd Talib Latif. American Institute of Physics Inc., 2019. (AIP Conference Proceedings).
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