Improving the visualization of rainfall trends using various innovative trend methodologies with time–frequency-based methodsShow others and affiliations
2022 (English)In: Applied water science, ISSN 2190-5487, E-ISSN 2190-5495, Vol. 12, no 9, article id 207
Article in journal (Refereed) Published
Abstract [en]
In this paper, the Innovative Trend Methodology (ITM) and their inspired approaches, i.e., Double (D-ITM) and Triple (T-ITM), were combined with Hilbert Huang transform (HHT) time frequency-based method. The new hybrid methods (i.e., ITM-HHT, D-ITM-HHT, and T-ITM-HHT) were proposed and compared to the DWT-based methods in order to recommend the best method. Three total annual rainfall time series from 1920 to 2011 were selected from three hydrological basins in Northern Algeria. The new combined models (ITM-HHT, D-ITM-HHT, and T-ITM-HHT) revealed that the 1950â1975 period has significant wet episodes followed by a long-term drought observed in the western region of Northern Algeria, while Northeastern Algeria presented a wet period since 2001. The proposed approaches successfully detected, in a visible manner, hidden trends presented in the signals, which proves that the removal of some modes of variability from the original rainfall signals can increase the accuracy of the used approaches. © 2022, The Author(s).
Place, publisher, year, edition, pages
Springer Nature, 2022. Vol. 12, no 9, article id 207
Keywords [en]
Innovative trend methodology, Hybrid methods, Hilbert Huang transform, Wet, Dry, Algeria
National Category
Ecology Environmental Sciences
Research subject
Soil Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-92550DOI: 10.1007/s13201-022-01722-3ISI: 000836260700007Scopus ID: 2-s2.0-85135269098OAI: oai:DiVA.org:ltu-92550DiVA, id: diva2:1688296
Note
Validerad;2022;Nivå 2;2022-08-18 (hanlid)
2022-08-182022-08-182023-09-05Bibliographically approved