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Gaussian process simulation of soil Zn micronutrient spatial heterogeneity and uncertainty – A performance appraisal of three semivariogram models

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dc.contributor.author Eze, Peter N.
dc.contributor.author Kumahor, Samuel K.
dc.date.accessioned 2021-12-01T09:47:19Z
dc.date.available 2021-12-01T09:47:19Z
dc.date.issued 2019-09
dc.identifier.citation Eze, P.N. and Kumahor, S.K. (2019) Gaussian process simulation of soil Zn micronutrient spatial heterogeneity and uncertainty–A performance appraisal of three semivariogram models. Scientific African, 5, https://doi.org/10.1016/j.sciaf.2019.e00110 en_US
dc.identifier.issn 2468-2276
dc.identifier.uri http://repository.biust.ac.bw/handle/123456789/382
dc.description.abstract Geostatistical modelling has proven to be a good tool for decision making in soil nutrient management because it has the ability to map spatial heterogeneity and uncertainty. This study outlines a comparative approach to quantify the uncertainties and correlations in spatial process models as illustrated for the distribution of Zn in top soils of a semi-arid environment. The spatial correlation of Zn uncertainties is investigated by calculating the semi-variance of normalized Zn concentration residuals, for a sufficiently large dataset, as a function of distance between pairs of locations within the Zn field. Three semi-variogram models, namely: Exponential, Gaussian, and Spherical models were tested on the spatial correlation structure of the normalized residuals and further used as default input model for Sequential Gaussian Simulation. The Sequential Gaussian Simulation led to an improved description of spatial heterogeneity and uncertainty. The choice of semivariogram model is therefore critical for robust Sequential Gaussian Simulation and uncertainty analysis. A new criterion is proposed to inform the choice of default input model for sequential Gaus- sian simulation given by ratio of partial sill to square of major range. With this criterion, Exponential model performed better than both Gaussian and Spherical models. The results indicate spatial correlation in Zn field and it is suggested that the spatial correlation of Zn uncertainties should be considered to exclude inaccurate estimation for spatially dis- tributed systems when performing nutrient distribution studies. en_US
dc.language.iso en en_US
dc.publisher Elsevier B.V. en_US
dc.subject Botswana en_US
dc.subject Semi-arid soil en_US
dc.subject Semivariogram en_US
dc.subject Sequential Gaussian Simulation en_US
dc.subject Zn micronutrients en_US
dc.title Gaussian process simulation of soil Zn micronutrient spatial heterogeneity and uncertainty – A performance appraisal of three semivariogram models en_US
dc.description.level phd en_US
dc.description.accessibility unrestricted en_US
dc.description.department ees en_US


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