Agrosystems, Geosciences & Environment (Dec 2023)

Soil pH mapping as a function of land use, elevation, and rainfall in the lake tana basin, northwestern of ethiopia

  • Addisu Mengist Belay,
  • Yihenew G. Selassie,
  • Enyew Adgo Tsegaye,
  • Derege Tsegaye Meshesha,
  • Hailu Kendie Addis

DOI
https://doi.org/10.1002/agg2.20420
Journal volume & issue
Vol. 6, no. 4
pp. n/a – n/a

Abstract

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Abstract Soil acidity has become a serious problem in the northern highlands of Ethiopia, limiting land productivity mainly that of crop yield. Research had been done to try to come up with results showing the area was affected by severe acidity, but based on few watersheds and districts in a haphazard way. The objective of this research was therefore to develop a comprehensive soil pH map that covers a broader area of 27 districts covering 2,810,055 ha of land to assess the degree of soil acidity in the Tana Sub‐basin, northwestern highlands of Ethiopia. Using GPS (3‐m precision), 2652 soil point data were collected. Precipitation, elevation, and land use cover were taken into account when creating an interpolated soil pH map. Using adjacent probed pH values, ordinary kriging interpolation (R2 = 0.65; root‐mean‐square error = 0.37125) technique was used to estimate the unmeasured locations, while the spatial pH variability was mapped using the geostatistical (GS+10) software. All Food and Agriculture Organization of the United Nations soil pH categories, with 11.22%, 19.97%, 18.77%, 14.59%, 9.64%, and 6.29% of the soil samples being extremely acidic, strongly acidic, moderately acidic, slightly acidic, neutral, moderately alkaline and strongly alkaline, respectively, were observed. The interpolation result showed a moderate coefficient of variation (10.52%) indicating that the research area had medium variability. In addition, the nugget‐to‐total semivariance ratio ranged from 25% to 75%, indicating moderate geographic dependence. The pH semivariograms best fitted the exponential model, which means the one with maximum (R2 = 0.834) and with minimum residual sum of squares (1.819E‐06) value for mapping of pH. Our result showed that soil pH was inversely dependent on precipitation and altitude, while it varies with land use type. The research result/map could give useful tools for effective integrated land management to minimize soil acidification by policymakers, agriculturalists, and other stakeholder groups. We also recommended future routine updates on the size and distribution of surface soil acidity in the study area.