Applied Sciences (Mar 2023)

Wavelet Analysis for Studying Rainfall Variability and Regionalizing Data: An Applied Study of the Moulouya Watershed in Morocco

  • Rachid Addou,
  • Mohamed Hanchane,
  • Nir Y. Krakauer,
  • Ridouane Kessabi,
  • Khalid Obda,
  • Majda Souab,
  • Imad Eddine Achir

DOI
https://doi.org/10.3390/app13063841
Journal volume & issue
Vol. 13, no. 6
p. 3841

Abstract

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This study analyzes the spatiotemporal variability of precipitation at the scale of the Moulouya watershed in eastern Morocco, which is very vulnerable to the increasing water shortage. For this purpose, we opted for wavelet transformation, a method based on the spectral analysis of data which allows for periodic components of a rainfall time series to change with time. The results obtained from this work show spectral power across five frequency ranges of variability: 1 to 2 years, 2 to 4 years, 4 to 8 years, 8 to 16 years, and 16 to 32 years. The duration of significant power at these frequencies is generally not homogeneous and varies from station to station. The most widespread frequency over the entire study area was found in the 4- to 8-year range. This mode of variability can last up to 27 consecutive years. In most of the basin, this mode of variability was observed around the period between 1990 and 2010. Oscillations at 8 to 16 years in frequency appear in only five series and over different time periods. The 16- to 32-year mode of variability appears in 15 stations and extends over the period from 1983 to 2008. At this level, signal strength is very weak compared to other higher-frequency modes of variability. On the other hand, the mode of variability at the 1- to 2-year frequency range appeared to be continuous in some stations and intermittent in others. This allowed us to regionalize our study basin into two homogeneous clusters that only differ in variability and rainfall regime.

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