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Rainfall Spatial Interpolation in the State of the Espirito Santo, Brazil

ABSTRACT

The knowledge of spatial variability of rainfall is important in many agricultural and environmental sciences applications, such as crop production, water resources management, environmental management, and soil erosion studies. The purpose of this study was to evaluated two spatial interpolation methods applied to monthly rainfall in the State Espirito Santo, Brazil. Thirty years of monthly rainfall data (1997-2006) from 110 rain gauge stations, 94 stations in the State of Esprito Santo and 16 stations in the neighboring states, were used. The spatial interpolation methods ‘Inverse Distance to a Power’ (IPD), considering power from 2 to 6, and ‘Kriging’ (KR), exponential, spherical and linear models, were evaluated through the use of cross validation. The evaluation and selection of the best spatial interpolation methods was done by analyzing the statistical indexes (trusty index, adjusted efficiency coefficient and mean percent error). Results showed that KR method had better performance than IPD method concerning spatial interpolation of monthly rainfall in the State of Espirito Santo, presenting mean percent errors varying from 7.9 to 14.6%.

Keywords:
geostatistics; time series; spatial dependence.

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