METHODS OF VARIOGRAM FITTING FOR THE RAINFALL ION SPATIAL MODELING IN CUIABÁ, BRAZIL
DOI:
https://doi.org/10.5902/2179460X12101Keywords:
Geostatistics. Rainfall. Spatial modeling. Nitrate. Sulfate.Abstract
http://dx.doi.org/10.5902/2179460X12101
The mapping of ion precipitation is of fundamental importance to knowledge and understanding of emission sources of air pollutants. Therefore, spatial interpolation methods should be assessed for support the mapping of these ions. In this context, the aim of this study was to assess the semivariogram modeling methods that best fit the variables pH, electrical conductivity, nitrate and sulfate precipitation in Cuiabá, Mato Grosso, Brazil. We assessed the methods ordinary least squares (OLS) and residual maximum likelihood (REML). The criteria for selecting the best method were the Akaike information criterion (AIC) and the standard deviation of the reduced errors (SER) generated by cross-validation. The restricted maximum likelihood method was the best for mapping ion precipitation in Cuiabá. Analysis of the structure of the semivariogram was important because it indicated local emission sources (urban) and regional (burning) of aerosol particles and gases.
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