Contribution of rainfall variability to salts’ dynamics in the region of Mahdia (Tunisian Sahel)

Abstract

The wide use of irrigation areas in the region of Mahdia is considered to be one of the main factors of soil salinity increase. The present study aims to evaluate the impact of extreme rainfall events on soil salinity. To fill the missing values in our rainfall dataset, we applied the artificial neural network algorithm. In addition, we used the RClimDex software to gain further insights on the number of rainy days’ variability over the period between 1960 and 2017. Moreover, to study the presence/absence of a trend in the rainfall time series, we used the modified Mann-Kendall (MM-K) test. Furthermore, to establish the current saline profiles, a drilling operation was carried out at four agricultural plots. These profiles were compared to previous ones observed in 2011. The statistical analysis of the precipitations’ time series reveals that the highest probability of extreme rainfall events is associated with the MS El Djem. The indices generated by the RClimDex software shows a slight increasing trend of days with rainfall ranging between 1 and 25 mm and a slight decreasing trend of days with rainfall ranging between 26 and 50 mm. However, the MM-K test shows an absence of any significant trend for all studied parameters. In addition, results show that the exceptional precipitations, which occurred in autumn 2016 have, indeed, leached the salts that were being retained at the soil surface layers. For instance, in the Ouled Chamekh Center plot, salinity has decreased by around 32%, between 2011 and 2017.

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Acknowledgments

This research was realized jointly between the research unit: Sustainable Management of Water and Soil Resources (UR17AGR03) and the research laboratory: Management and control of animal and environmental resources in semi-arid regions. A part of this research study was accomplished during the master thesis of Mr. Farhat at ESIM. The authors would like to thank the Tunisian General Directorate of Water Resources (DGRE) for providing the conventional data for the study area. Finally, the authors would like to express their gratitude for the anonymous reviewers of this paper.

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Correspondence to Lokmen Farhat.

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Editorial handling: Maurizio Barbieri

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Farhat, L., El Amri, A., Khlifi, S. et al. Contribution of rainfall variability to salts’ dynamics in the region of Mahdia (Tunisian Sahel). Arab J Geosci 12, 123 (2019). https://doi.org/10.1007/s12517-019-4291-6

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Keywords

  • Artificial neural network
  • RClimDex indices
  • Mann-Kendall test
  • Extreme rainfall events
  • Soil salinity
  • Mahdia