Masmoudi et al. (2026) Modelling and Mapping of Soil Salinity Related to Soil Characteristics and Irrigation in a Semi-Arid Context

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Identification

• Journal: Acta Biologica Slovenica
• Year: 2026
• Date: 2026-02-24
• Authors: Yassine Al Masmoudi, Sanae Bel-Lahbib, Khalid Ibno Namr, Adil Jouamaa, Meryem Moustakim, Malika Laghrour, Badr Rerhou
• DOI: 10.14720/abs.69.2.23520

Research Groups

Not explicitly stated in the provided text.

Short Summary

This study aimed to model and map soil salinity in semi-arid regions by correlating the Normalised Differential Salinity Index (NDSI) with various physicochemical parameters. The developed model accurately estimated soil salinity (R²=0.90), revealing that a significant portion of the studied area exhibits moderate to extreme salinity levels.

Objective

• To develop models and maps of soil salinity in semi-arid environments.
• To systematically examine correlations between the Normalised Differential Salinity Index (NDSI) and physicochemical parameters (Soil Organic Matter, Electrical Conductivity, pH, Texture, total limestone, and Evapotranspiration) to determine the parameters controlling salinity.

Study Configuration

• Spatial Scale: Regional scale, focusing on agricultural operations in semi-arid environments.
• Temporal Scale: Not explicitly specified for the overall study period, though evapotranspiration rates are given on a daily basis.

Methodology and Data

• Models used: Normalised Differential Salinity Index (NDSI) for salinity mapping; a developed model (likely a regression or machine learning model) for estimating soil salinity.
• Data sources: Remote sensing data (for NDSI); measurements of physicochemical parameters including Soil Organic Matter (SOM), Electrical Conductivity (EC), pH, Texture, total limestone (CaCO3), and Evapotranspiration (ET0), likely from field observations or laboratory analyses.

Main Results

• The predominant soil texture fraction was sand, accounting for 57.5%.
• Electrical Conductivity (EC) ranged from 0.09 to 0.132 S⋅m⁻¹, indicating varying salinity levels.
• Evapotranspiration (ET0) rates in the region ranged between 0.004 and 0.009 m⋅day⁻¹.
• The developed model demonstrated adequate performance in estimating soil salinity, with a coefficient of determination (R²) of 0.90.
• The generated salinity map showed that 36% of the total area had no salinity impact, 23% had mild salinity, 24% indicated moderate soil salinity, and 17% displayed extreme levels of soil salinity.

Contributions

• Provides a proactive cartography of soil salinity in dry and semi-dry areas.
• Introduces an advanced modeling technique for soil salinity estimation utilizing remote sensing data.
• Offers an integral methodology for informed decision-making processes regarding agricultural management in salinity-affected regions.

Funding

Not explicitly stated in the provided text.

Citation

@article{Masmoudi2026Modelling,
  author = {Masmoudi, Yassine Al and Bel-Lahbib, Sanae and Namr, Khalid Ibno and Jouamaa, Adil and Moustakim, Meryem and Laghrour, Malika and Rerhou, Badr},
  title = {Modelling and Mapping of Soil Salinity Related to Soil Characteristics and Irrigation in a Semi-Arid Context},
  journal = {Acta Biologica Slovenica},
  year = {2026},
  doi = {10.14720/abs.69.2.23520},
  url = {https://doi.org/10.14720/abs.69.2.23520}
}