Analysis of meteorological drought indices in the Wadi Righ area (southern Algeria)


Bettahar A., ŞENER Ş.

Sustainable Water Resources Management, vol.8, no.5, 2022 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 8 Issue: 5
  • Publication Date: 2022
  • Doi Number: 10.1007/s40899-022-00740-y
  • Journal Name: Sustainable Water Resources Management
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus
  • Keywords: Droughts, Meteorological indices, Statistical methods, Principal component analysis (PCA), Hierarchical ascending classification (HAC), WATER-QUALITY, RIVER-BASIN, GROUNDWATER QUALITY, TEMPORAL VARIATIONS, TERMINAL COMPLEX, TRACE-ELEMENTS, SEVERITY INDEX, EVOLUTION, SYSTEM, CHEMISTRY
  • Süleyman Demirel University Affiliated: Yes

Abstract

© 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.Drought is a natural phenomenon represented by atmospheric changes in an area for a period. These changes cause an imbalance in the hydrological system. Our study aims to explain the meteorological droughts observed in the Wadi Righ area during the period of historical dryness from 1975 to 2018. It compares the performance of five indices for drought monitoring in the study area, such as the standardized precipitation index (SPI), rainfall anomaly index (RAI), deciles index (DI), Z-score, and percent of normal (PN). We compared the indices and examined the connection between them to come to a common conclusion that the Wadi Righ has suffered from dry conditions to varying degrees according to the indices. The years 1995, 1997, 2000, 2005, 2012, and 2014 experienced an extremely dry climate according to the classification of SPI (e.g., the drought of 2012 was extremely dry with an SPI value of − 1.67, PN = 26.4, RAI = − 2.38, and Z-score = − 1.25), RAI, DI, PN, and Z-score, while the climate of years 1999, 2001, 2004, 2009, and 2015 ranged from wet to extremely wet. The statistical methods of hierarchical ascending classification (HAC) and principal component analysis (PCA) were selected in the present research to prove and emphasize if there was a correlation between the indices. The use of HAC indicated that the data extracted from the calculated indices were grouped into two main groups; the first represented by rainfall which is the years characterized by low average precipitation (less than the average 68.84 mm/year), while the second is represented by the indices (the years which have a very high precipitation average). In general, this analysis confirmed the existence of a positive correlation between the studied indices and precipitation, which made it the main variable in measuring the indices.