Geospatial Distribution of Soil Reaction in Central Southeastern Nigeria
1 Department of Soil Science and Technology, School of Agriculture and Agricultural Technology, Federal University of Technology, Owerri.
2 Department of Soil Science and Technology, Federal University of Technology, P.M.B 1526,Owerri, Imo State, Nigeria
3 Department of Soil Science and Technology, Federal University of Technology, Owerri
4 Department of Soil Science and Technology, Federal University of Technology, P.M.B. 1526, Owerri, Imo State, Nigeria.
* Corresponding author: onyechere.adaobi@gmail.com
2 Department of Soil Science and Technology, Federal University of Technology, P.M.B 1526,Owerri, Imo State, Nigeria
3 Department of Soil Science and Technology, Federal University of Technology, Owerri
4 Department of Soil Science and Technology, Federal University of Technology, P.M.B. 1526, Owerri, Imo State, Nigeria.
* Corresponding author: onyechere.adaobi@gmail.com
Abstract
The study applied Geographic Information System (GIS) in the Study of Soil Acidity Distribution in Soils of Central Southeastern Nigeria from six different parent materials, namely Imo Clay Shale, Ajali Sandstone, Asu River group, Afikpo Sandstone, Ogwashi-Asaba formation and Bende Ameki formation. Free soil survey method was used to site the eighteen profile pits investigated. The pits were geo-referenced with a hand held Global Positioning System (GPS) Receiver. Routine laboratory analyses were conducted on soil samples from the field study. Microsoft Excel was used to analyse the mean and percentage coefficient of variation of the results. Geostatistical Wizard of Arc GIS 10.2 software was used for the descriptive statistics, semivariogram and cross validation. Ordinary kriging method was also performed for interpolation and developed into attribute maps. The average pH in water was highest in soils formed on Asu river group (6.04-7.14) and lowest in soils formed on Ogwashi-Asaba formation and Bende-Ameki formation (5.47-6.48). The geostatistical analysis revealed that there was high spatial variability of soil properties analysed at different geographical scales however, the soil analysed showed moderate spatial dependency. The Gaussian model gave the best fitted model for the semivariogram presenting a semi variance with lowest nugget and highest spatial autocorrelation. The result of the cross validation showed that the models made a moderate prediction for pH. The map revealed that soil pH followed an observable pattern with soils of Anambra State being more acidic (lower pH level) when compared with the soils of Enugu and Ebonyi State.
Keywords
Geographical Information System Semivariogram Cross Validation Kriged Map Soil Acidity Geostatistical Analysis