958 resultados para hydrometeorology, Penman-Monteith-FAO, kriging


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There are many methods used to estimate values in places no sampled for construction of contours maps. The aim of this study was to use the methods of interpolation kriging, inverse of the square of the distance and polynomial in the representation of the spatial variability of the pH of the soil in the organic and conventional management in the culture of the coffee plantation. For that, irregular meshes were built for soil sampling in the depth of 0-0,10 meters, totaling 40 points sampling in each area. For gauging of the interpolation methods they were solitary 10% of the total of points, for each area. Initially, the data were appraised through the classic statistics (descriptive and exploratory) and spatial analysis. The method inverse square of the distance and kriging has low error in estimating dados. The method of kriging presented low variation around the average in different managements.

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The aim of this study is to define the basement map of the Taubaté Basin applying geostatistics to seismic, gravimetric and deep wells data. The study consisted of the interpretation of eleven seismic sections obtained in the central and northeastern portions of the basin. The altitude of the basement and the distribution of faults was determined based on these sections. New information was obtained from 79 wells located mainly in the regions of São José dos Campos and Jacareí. The method of kriging with an external drift was applied, using seismic and well data as the main variables and the gravimetric map as the secondary variable. The basement contour map obtained has a strong correlation with the main faults. It was possible to obtain a better resolution in the region of São José dos Campos and in the northeast area, where the vast majority of wells are located.

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The spatial variability of several soil attributes (bulk density, penetration resistance, water content, organic matter content and pH) as well as soybean yield have been assessed during the 2007/08 growing season, in Selviria (MS) in a Hapludox (Typic Acrustox), under no tillage. The objectives were to assess the spatial variability of soil and plant parameters at the small plot scale and to select the best soil attribute explaining most the variability of agricultural productivity. Soil and plant were sampled on a grid with 121 points within a plot of 25,600 m 2 in area and slope of 0.025 mm -1 slope. Medium and low coefficients of variation were obtained for most of the studied soil attributes as expected, due to the homogenizing effect of the no-till system on the soil physical environment. From the standpoint of linear regression and spatial pattern of variability, productivity of soybeans could be explained according to the hydrogen potential (pH). Results are discussed taken into account that the soybean crop in no-tillage is widely used in crop-livestock integration on the national scene.

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