Establishment of Soil Management Zones Using Multivariate Analysis and GIS

ABSTRACT

Delineation of soil management zones (MZ) that can define subfields with homogenous soil properties provides a basis for successful site-specific management. This study was conducted in order to create MZ for a field of 460 ha in Egypt using multivariate analysis and geographic information system (GIS). Soil samples were collected in a grid pattern from 104 topsoil (0–30 cm) locations within the field. Substantial variation was observed in shale depth (known locally as Tafla), electrical conductivity (EC), pH, CaCO₃, available phosphorus (P), potassium, iron (Fe), manganese, zinc, and copper. Principal component analysis was performed to aggregate and summarize the variability of the dataset. The analysis showed that shale depth, EC, pH, available P, and Fe are the parameters representing the overall variability. Accordingly, k-means clustering analysis was performed on the standardized data of these parameters, and three clusters were formed. These clusters were used for creating MZ with heterogeneity in overall soil properties. Zone #3 had favorable parameters led by deep shale depth (112.5 cm ±3.7) and EC (11.99 dS m⁻¹ ± 0.47), whereas zone #1 was the worst with shale depth of 60.7 cm ±7.98 and EC of 29.76 dS m⁻¹ ± 2.66. Zone #2 had intermediate conditions with shale depth of 100 cm ±10 and EC of 14.25 dS m⁻¹ ± 0.32. These subfields should be helpful for making successful agronomic decisions such as selecting crops, irrigation, and fertilization.

KEYWORDS:

• Soil management zones
• principal component analysis
• k-means clustering
• GIS

Disclosure statement

The authors declare that they have no conflict of interest.