Document Type : Research Paper

Authors

• HAMEL IMANE ¹
• MOHAMED BENSLAMA ²
• FOUZI BENBRAHIM ³
• MOHAMED KRAIMAT ⁴
• FAREDJ CHIKHI ⁵
• SABRINA DAREM ⁶

¹ Department of Biology‎,Faculty of Natural and Life Sciences and Earth Sciences‎,University of Ghardaia‎,Ghardaia, Algeria.

² Department of Biology, Faculty of Natural and Life Sciences, University of Badji Mokhtar, Annaba, Algeria)

³ École Normale Supérieure de Ouargla, BP 398, Hai Ennasr, Ouargla 30000, Algérie

⁴ Department of Agronomy, Faculty of Natural Sciences and Life,University of Kasdi Merbah , Ouargla, Algeria

⁵ Department of Biology, Faculty of Natural and Life Sciences and Earth Sciences, University of Ghardaia, Ghardaïa, Algeria

⁶ Department of Biology, Faculty of Natural and Life Sciences, university of badji mokhtar, Annaba, Algeria

Abstract

Monitoring soil quality in irrigated areas is essential for assessing the sustainability of production systems. In this respect, the spatial variability of the properties of irrigated soils is a mean to know the evolution of the latter. This study aims to determine the spatial variability of soil organic matter, salinity, pH and active limestone using a geostatistical approach. The present study was carried out in the region of Zelfana located in the Algerian central Sahara, the samples were collected from a depth of 0 to 30 cm and analysed for organic matter, salinity, pH and active limestone. The analytical results show that the soil is very poor in organic matter, very salty, alkaline to very alkaline and moderately calcareous. The geostatistical analysis revealed various patterns and levels of spatial distribution of the studied properties. The results showed a weak spatial dependence for organic matter, moderate for pH and salinity and strong for active limestone. The variographic analysis showed that the nugget effect is weak for organic matter and pH, moderate for salinity, while active limestone does not show a nugget effect. The range varies from 75 meters for salinity to 299 meters for organic matter, confirming the validity of the adopted sampling and allowing the optimization of future sampling plans. The Arcgis autoKriging function was used to select the best theoretical variogram model from those most commonly used in geostatistics (Gaussian, spherical, exponential and circular). This model was used to produce the spatial variability maps using ordinary kriging. Spatial variability of soil properties is influenced by agricultural intensification, something that must be taken into consideration for integrated and sustainable land management in similar regions.

Keywords

• Geostatistics
• spatial variability
• organic matter
• salinity
• pH
• active limestone

Main Subjects

• Soil and water quality