Extreme rain trend analysis in Macta watershed North West Algeria

• Published in: Arabian journal of geosciences Vol. 14; no. 4
• Main Authors: Benzater, Benali, Elouissi, Abdelkader, Dabanli, Ismail, Benaricha, Boumediene, Hamimed, Abderrahmane
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.02.2021; Springer Nature B.V
• Subjects: Autumn; Climate change; Confidence intervals; Earth and Environmental Science; Earth science; Earth Sciences; Extreme weather; Floods; Original Paper; Rain; Rainfall; Stations; Trend analysis; Trends; Watersheds; Algeria; Trend; Climate change; Mann-Kendall; North West Algeria; Extreme rain; Macta
• ISSN: 1866-7511; 1866-7538
• DOI: 10.1007/s12517-021-06636-z

The north of Algeria is subject to floods generated directly by extreme rains. Detecting their trends, at different spatial and temporal scales, is a crucial step in the context of climate change. In this article, the Mann-Kendall method was used to detect the trends of maximum daily rains in 41 rainfall stations in the Macta watershed (North West Algeria) for a period of 41 years (1970–2010). The results show contrasting monthly trends; a significant increase, at the 5% (10%) confidence level, was detected in March, May, June, November, and December months, with 29% (7%), 24% (32%), 17% (24%), 12% (0%), and 10% (20%) of stations respectively. In terms of rain intensity, an increase was detected in April, July, August, September, October, and November. It is obvious that the months of August and September, representing the beginning of the autumn season, are marked by the greatest increases in the intensity of the rains justifying the catastrophic floods that hit our basin each year. The same significant upward trends are detected for autumn and winter, accompanied by an increase in quantities in the first season (autumn). Annually, a trend towards a significant increase trend, at 5% (10%) confidence level, in extreme rains with 20% (15%) of stations, was detected. Furthermore, a slight decrease in quantities was observed.