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      Métodos de interpolação espacial para o mapeamento da precipitação pluvial Translated title: Spatial interpolation methods for mapping of rainfall

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          Abstract

          A espacialização de variáveis climáticas, notadamente a precipitação pluvial, necessita de estudos constantes, visando ao aperfeiçoamento de interpoladores e desenvolvimento de mapas sem tendência. Objetivou-se, neste contexto, avaliar o desempenho dos interpoladores krigagem (KG), a partir do melhor modelo de semivariograma, cokrigagem (CA), introduzindo a altitude como variável secundária, modelagem estatística (ME), na qual a precipitação média pode ser estimada a partir de coordenadas geográficas, e inverso do quadrado da distância (IQD), para espacialização da precipitação média mensal, precipitação média do período seco e precipitação média anual, em Minas Gerais; para isto se utilizaram informações de 232 postos pluviométricos para modelagem e de 70 para validação, com base no erro médio absoluto, além de um modelo digital de elevação com resolução de 270 m. Quanto à avaliação dos métodos de interpolação, constatou-se bom desempenho das metodologias abordadas, com erro absoluto médio variando de 12,84 a 19,96%, com destaque para a cokrigagem, que obteve menor erro em 50% das situações analisadas.

          Translated abstract

          The mapping of weather elements, especially rainfall, needs constant studies to improve the performance of interpolators, and to obtain unbiased maps. This work aimed to evaluate the performance of some spatial interpolators for mean monthly rainfall, mean rainfall during the dry season and mean annual rainfall in the Minas Gerais State. For that, the ordinary kriging was evaluated and compared, after the semi-variogram modeling, co-kriging (introducing the altitude above sea level as a secondary variable), statistical modeling in which the mean precipitation can be estimated from geographical coordinates, and inverse square distance. In this study, data sets were evaluated from 232 pluviometric stations, in the Minas Gerais area, to apply each one of the interpolators mentioned and 70 stations to evaluate the performance that was conducted on the basis of absolute mean error. In addition, a digital elevation model, with a resolution of 270 m, was applied. The interpolators have shown good performance, with mean errors varying from 12.84 to 19.96%, the co-kriging method presenting a smaller absolute mean error in 50% of the situations evaluated.

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          Most cited references26

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          Caracterização climática do Estado de Minas Gerais

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            Assessing the effect of integrating elevation data into the estimation of monthly precipitation in Great Britain

            C.D. Lloyd (2005)
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              Multivariate geostatistical analysis of evapotranspiration and precipitation in mountainous terrain

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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Journal
                rbeaa
                Revista Brasileira de Engenharia Agrícola e Ambiental
                Rev. bras. eng. agríc. ambient.
                Departamento de Engenharia Agrícola - UFCG (Campina Grande )
                1807-1929
                September 2010
                : 14
                : 9
                : 970-978
                Affiliations
                [1 ] Universidade Federal do Tocantins Brazil
                [2 ] Universidade Federal de Lavras Brazil
                [3 ] Universidade Federal de Lavras Brazil
                Article
                S1415-43662010000900009
                10.1590/S1415-43662010000900009
                86a273ae-c438-4a8a-9184-68358e50eaf7

                http://creativecommons.org/licenses/by/4.0/

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                Product

                SciELO Brazil

                Self URI (journal page): http://www.scielo.br/scielo.php?script=sci_serial&pid=1415-4366&lng=en
                Categories
                AGRICULTURAL ENGINEERING
                ENVIRONMENTAL SCIENCES

                Agricultural engineering,General environmental science
                spatial modeling,climatology,interpolators,modelagem espacial,climatologia,interpoladores

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