Dryland Soil Research (DLSR)

Dryland Soil Research (DLSR)

Spatial variability and delineation of soil fertility management zones using geostatistics and fuzzy c-means clustering in an irrigated wheat system in alborz province, Iran

Articles in Press

Document Type : Original Article

Authors
Hamed Rezaei
Leila Esmaeelnejad
Rasoul Mirkhani
Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
Abstract
Sustainable soil management and precision nutrient application in irrigated wheat systems require a detailed understanding of the spatial variability of soil properties and their implications for site-specific practices. This study aimed to quantify the spatial variability of some key soil fertility attributes and to delineate soil fertility management zones (MZs) for site-specific nutrient management in irrigated wheat fields of Alborz province, Iran. A total of 222 geo referenced surface soil samples (0–30 cm) were collected on a 1,650 × 1,650 m grid. Soil pH, electrical conductivity (EC), soil organic carbon (SOC), total neutralizing value (TNV), particle-size distribution, and available macro and micronutrients (P, K, Ca, Mg, Fe, Mn, Zn, Cu) were determined by the standard laboratory methods. Descriptive statistics and Pearson correlations were computed, and geostatistical analyses (semivariograms and ordinary kriging) were used to characterize and map spatial variability. Principal component analysis (PCA) followed by fuzzy c means clustering were applied to delineate soil fertility MZs.
Most soil properties exhibited moderate to high coefficients of variation, with only low variability for the pH, while clay and TNV fell into the moderate class and EC, SOC, and most available nutrients showed high variability. Semivariogram modelling indicated exponential and Gaussian models as the best fit for the majority of properties, with moderate to strong spatial dependence and ranges varying from 1.65 to 105.6 km. Kriged maps revealed that about 78% of the area was non saline (EC <4 dS m⁻¹), whereas roughly 22% was saline, and more than half of the fields had SOC <1%, highlighting significant constraints on yield and soil health. Micronutrient maps showed widespread Zn and Fe deficiencies in the western, more alkaline and lighter textured parts of the province. PCA identified four principal components explaining 66.6% of the total variance, capturing major gradients in overall fertility, lime–nutrient–texture status, salinity–pH conditions, and macronutrient availability.
Using the first four PCs as input, fuzzy c means clustering and cluster validity indices (fuzzy performance index and normalized classification entropy) indicated that four MZs provided the most appropriate partitioning of the fields. These MZs differed significantly in SOC, EC, pH, texture, and nutrient status. In zones with high K and P but adequate Fe and Zn, further K and P fertilization is unnecessary, whereas zones with low P, Fe, and Zn and low SOC require targeted P and micronutrient inputs and organic matter management. The delineated MZs and associated maps offer a practical framework for variable rate fertilization and more efficient soil sampling, supporting sustainable intensification of irrigated wheat production in Alborz province and similar semi arid regions.
Keywords
Aridisols
delineation of management zones
fertilizer application rate
nutrient management
precision agriculture
wheat production
Subjects
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Dryland Soil Research (DLSR)

Articles in Press, Accepted Manuscript
Available Online from 06 September 2026

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