Dryland soil quality modelling in Najran, Saudi Arabia, using a GIS-based geometric approach

Introduction Ensuring that natural resources are managed sustainably to achieve global food security is vital given changing climates and increasing demand for food due to population growth. In seeking to secure food security, assessing and safeguarding soil quality is an essential factor in ensuring that increasing demands for food can be met. Methods This study uses the Soil Quality Index (SQI) in Najran, Saudi Arabia to conduct spatial modelling of the geomorphological, physical, chemical, and fertility parameters of soil, using a Geometric Mean Algorithm (GMA) approach. A Digital Elevation Model (DEM) was used with Sentinel-2 satellite images and processed to generate digital soil and landform maps. Results and discussion The GMA results for Najran show a SQI range from 0.33 to 0.59, corresponding to “very low” to “very high” soil quality grades. Five categories of soil quality (SQ) – very low, low, moderate, high, and very high – were developed using the GMA model, and these cover 2.98, 45.69, 40.68, 8.98, and 1.65% of the land area, respectively. The small wadis in the area are nutrient-rich due to fluvial sediment deposition from the surrounding mountainous areas, and correlate to the higher SQ values. To validate the GMA model, a weighted additive (WA) model has been used; the coefficient of determination, R 2 , is 0.942. The proposed model achieves a high sensitivity index of 1.78, showing that the model performs well in assessing SQ in the selected area, and is therefore an effective tool for monitoring SQ. Conclusion This tool can support agricultural planning strategies in the Najran region and can also be used as an analogue for other dryland arid regions where there is a dearth of thorough soil research determining SQ. In addition, this integration improves the reliability of land suitability assessments and supports sustainable agricultural development.