Statistical modeling of monthly rainfall variability in Soummam watershed of Algeria, between 1967 and 2018. (11th October 2020)

• Record Type: Journal Article
• Authors: Aieb, Amir; Lefsih, Khalef; Scarpa, Marco; Bonaccorso, Brunella; Cicero, Nicola; Mimeche, Omar; Madani, Khodir
• Is Part Of: Natural resource modelling. Volume 33:Number 4(2020:Nov.)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-10-11
• Subjects: aridity index -- bioclimatic floor -- fitting test -- monthly rainfall -- statistical modeling -- watershed; Conservation of natural resources -- Mathematical models -- Periodicals; Ecology -- Mathematical models -- Periodicals; 371.397
• DOI: 10.1111/nrm.12288
• Languages: English
• ISSNs: 0890-8575

Abstract

Abstract: The monthly precipitations obtained during 51 years of measurement in 24 stations of Soummam watershed in Algeria were analyzed to describe rainfall trends and aridity state of the area using statistical modeling. The choice of distribution laws was justified by comparing fitting results of different distributions laws used in literature reviews. Hence, the p values proved that Generalized Extreme Value, Weibull (3) and Logistic the distribution law are more adequate to analyze rainfall frequencies in different part of the watershed. The diagnostic given by Q‐Q plot, P‐P plot and survival regression curve showed the period of wetness and dryness in the northeastern and the southwestern part of the watershed, respectively. Moreover, the study given by the De Martonne index explains the consequences of climate change by a new form of aridity in the watershed between 1994 and 2018. Recommendations for Resource Managers The annual rainfall of Soummam watershed has a moderate and irregular rainfall distribution between 1967 and 2018. Using distribution function on monthly rainfall in each bioclimatic floor to analyze the trend of rainfall frequency gives a spatio‐temporal description of climate in the area. Fitting by Kolmogorov‐Smirnov test allows us to choose generalized extreme value, Weibull (3) and Logistic for modeling monthly rainfall variability in each part of the watershed. The diagnostic obtained by P‐P plot, Q‐Q plot and survival regression curve proved a change of aridity in the northeastern and southwestern part of the watershed between 1994 and 2018.