Spatial analysis of some soil chemical properties of the Amhara region in Ethiopia

Abstract

Soil chemical properties have a major impact on both agriculture and the environment, particularly with regard to soil fertility, soil quality, and crop production. However, little research has been done to address the spatial patterns of soil nutrients in the northwestern highlands of Amhara region of Ethiopia. The objective of this research was therefore to explore spatial variability of selected soil chemical properties that covers a broader area of 4 districts covering 560,085.2 ha of land to assess the spatial variability in the northwestern highlands of Amhara region in Ethiopia. Using Global Positioning System (GPS) (3 m precision), 363 (0–30 cm depth) soil point data were collected. Soil organic carbon (SOC), available P (AvP), electrical conductivity (EC), and soil acidity (pH) were taken into account when we explore the spatial variability. Inverse distance weighting (IDW), ordinary kriging (OK) methods, and geostatistical analysis (GS + 10) were used to analyze the spatial variability patterns of the SOC, EC, AvP, and pH concentrations. The results showed that the chemical properties vary considerably; the highest and lowest coefficients of variation (CV) were AvP (82.64%) and pH (9.12%), respectively. Moderate spatial dependencies (48.13–24.91%) were typically observed (SOC, EC, and pH), while AvP (17.84%) was strong. Cross-validation analysis showed that OK performed better (AvP, EC, and pH) than IDW (SOC). A semivariogram of log-transformed data for soil AvP, EC, and SOC was fitted with a spherical model whereas exponential model for pH. Spatial patterns of a pH map showed that the southeastern region is characterized by higher soil pH and high fertility potential for food crops. The research result/map could give useful tool for effective integrated land management to minimize soil acidification by policymakers, agriculturalists, and other stakeholder groups. We also recommended future routine update on the size and distribution of surface soil acidity, AvP, and SOC in the study area.