Geo-Statistical Characterization of Annual Maximum Daily Rainfall Variability in Semi-Arid Regions

In the Wadi Cheliff basin (Algeria), a 48-year (1971–2018) time series of annual maximum daily rainfall was studied to identify and quantify trends observed at 150 rain gauges. Initial trends in annual maximum daily rainfall were determined using the Mann–Kendall test, with a significance level of 95%. The slope or increase/decrease in the annual maximum daily precipitation was assessed using the Theil–Sen estimator. A running trend analysis was then performed to quantify the effects of different time windows on trend detection. Finally, to assess the different spatial distribution of annual maximum daily precipitation during the observation period, spatial analysis was performed using a geo-statistical approach for the whole observation period and at different decades. The results showed a predominant negative trend in annual maximum daily rainfall (about 11% of rain gauges at a 95% significance level), mainly affecting the north-eastern area of the catchment. The spatial distribution of annual maximum daily rainfall showed high rainfall variability in the period of 1970–1980, with a decrease in the decades of 1980–1990 and 2010–2017 when the maximum values were more evenly distributed across the region.

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Publication Details

Journal
Atmosphere
Published
2024-12-19
DOI
https://doi.org/10.3390/atmos15121519
Citations
1
Primary Topic
Hydrology and Drought Analysis
Type
article
Field-Weighted Citation Impact
0.28

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Geo-Statistical Characterization of Annual Maximum Daily Rainfall Variability in Semi-Arid Regions

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Geo-Statistical Characterization of Annual Maximum Daily Rainfall Variability in Semi-Arid Regions

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article en
1 citations

Abstract

In the Wadi Cheliff basin (Algeria), a 48-year (1971–2018) time series of annual maximum daily rainfall was studied to identify and quantify trends observed at 150 rain gauges. Initial trends in annual maximum daily rainfall were determined using the Mann–Kendall test, with a significance level of 95%. The slope or increase/decrease in the annual maximum daily precipitation was assessed using the Theil–Sen estimator. A running trend analysis was then performed to quantify the effects of different time windows on trend detection. Finally, to assess the different spatial distribution of annual maximum daily precipitation during the observation period, spatial analysis was performed using a geo-statistical approach for the whole observation period and at different decades. The results showed a predominant negative trend in annual maximum daily rainfall (about 11% of rain gauges at a 95% significance level), mainly affecting the north-eastern area of the catchment. The spatial distribution of annual maximum daily rainfall showed high rainfall variability in the period of 1970–1980, with a decrease in the decades of 1980–1990 and 2010–2017 when the maximum values were more evenly distributed across the region.

AtmosphereVol. 15(12)
University of Lisbon (PT), University of Agriculture in Krakow (PL), Research Institute for Geo-Hydrological Protection (IT), Qurtuba University of Science and Information Technology (PK), National Research Council (IT), Hassiba Benbouali University of Chlef (DZ), Hanyang University (KR)
Direction Générale de la Recherche Scientifique et du Développement Technologique
Climate action
Openalex Percentile: Top 39%
Hydrology and Drought Analysis
0.28
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