Abstract
The average precipitation spatialization in annual and seasonal scale provides important information for the management and maintenance of water resources. Located at the south region of Brazil the state of Santa Catarina has water as its main assets for agriculture and economic development. Therefore, the aim of this study was to spatialize the average annual and seasonal precipitation for the state of Santa Catarina, by means of a geostatistic approach based on models. Data from meteorological stations made available by the Mineral Resources Research Company (CPRM) were used. These stations have regular distribution and high density within the state. For the geostatistical modeling, some basic assumptions such as data normality and nonstationarity were verified. After accepting the assumptions it was verified through statistical tests regarding its likelihood, if the structure of spatial dependence of the geostatistical model increase its performance, justifying the use of this structure for the precipitation spatialization. To check the assumptions of good prediction, the residue dispersion of the spatial interpolations was evaluated through cross-validation. The results showed a better performance for the geostatiscal models with the spatial dependence structure, both for average annual and seasonal precipitation. Thus, these models were used to the spatial interpolation, observing a good prediction through the residual dispersion and, consequently, mapping of precipitation.
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