324 resultados para geostatistics
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O presente trabalho tem por objetivo avaliar a distribuição espacial, por geoestatística, da produção de água gerada pelo modelo hidrológico matemático SWAT 2009 (Soil and Water Assessment Tool, versão 2009), da parte inicial da bacia hidrográfica do Rio Pardo – SP. Foi utilizado um Sistema de Informação Geográfica (SIG) associado a uma interface com o modelo SWAT para a confecção do banco de dados. Para isto, as informações de entrada necessárias para avaliar a produção de lâmina de água (mm), que infiltrou e armazenou em cada sub-bacia gerada pelo SWAT, referem-se a dados tabulares climáticos e de parâmetros físicos e químicos de solo e a planos de informações como: o Modelo Numérico do Terreno (MNT), Mapa de Uso do Solo e Mapa de Solos. A amostragem geoestatística foi representada por uma malha irregular georreferenciada com 43 pontos localizados na parte central de cada sub-bacia representando a quantidade de água produzida. A análise geoestatística foi realizada pela construção dos variogramas e posteriormente a confecção dos mapas interpolados por krigagem. Do resultado obtido observou-se que a produção de água apresentou dependência espacial e que esta ocorreu de forma homogênea, tanto para os maiores como para os menores valores de produção de água encontrados na bacia.
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No presente estudo foi avaliada a distribuição espacial do percentil 75 da precipitação decendial para o Estado de São Paulo, utilizando-se um total de 136 postos pluviométricos com séries acima de 27 anos de registros. Em um estágio preliminar os valores dos percentis 75 da precipitação decendial foram georeferenciados, permitindo a utilização de técnicas da geoestatística para proceder à interpolação dos dados. Modelos experimentais de semivariogramas padronizados foram obtidos, utilizando-se a variância amostral como fator de escalonamento, permitindo a verificação de proporcionalidade entre os modelos e agrupando-os sob a mesma tendência. O modelo teórico exponencial foi o que melhor se ajustou aos semivariogramas experimentais, seguido pelo modelo esférico. Os parâmetros estimados para os modelos, efeito pepita, patamar e alcance foram utilizados para a realização da krigagem e confecção dos mapas de isolinhas. A distribuição espacial dos percentis 75 da precipitação decendial reflete o comportamento da circulação atmosférica no Estado, apresentando alta variabilidade. As regiões oeste , sudoeste e noroeste apresentaram as menores intensidades de precipitação e foram variáveis de acordo com os níveis temporais na primavera. A região litorânea apresentou as maiores intensidades de precipitação para quase todos os níveis temporais estudados, diferenciando-se das demais regiões do Estado. A exceção foi à região nordeste no final da primavera que apresentou valores de intensidades maiores do que os registrados no litoral. A faixa litorânea apresentou comportamento homogêneo, detectado pelo forte agrupamento das isolinhas em quase todos os decêndios analisados.
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The sampling scheme is essential in the investigation of the spatial variability of soil properties in Soil Science studies. The high costs of sampling schemes optimized with additional sampling points for each physical and chemical soil property, prevent their use in precision agriculture. The purpose of this study was to obtain an optimal sampling scheme for physical and chemical property sets and investigate its effect on the quality of soil sampling. Soil was sampled on a 42-ha area, with 206 geo-referenced points arranged in a regular grid spaced 50 m from each other, in a depth range of 0.00-0.20 m. In order to obtain an optimal sampling scheme for every physical and chemical property, a sample grid, a medium-scale variogram and the extended Spatial Simulated Annealing (SSA) method were used to minimize kriging variance. The optimization procedure was validated by constructing maps of relative improvement comparing the sample configuration before and after the process. A greater concentration of recommended points in specific areas (NW-SE direction) was observed, which also reflects a greater estimate variance at these locations. The addition of optimal samples, for specific regions, increased the accuracy up to 2 % for chemical and 1 % for physical properties. The use of a sample grid and medium-scale variogram, as previous information for the conception of additional sampling schemes, was very promising to determine the locations of these additional points for all physical and chemical soil properties, enhancing the accuracy of kriging estimates of the physical-chemical properties.
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Uma das necessidades da agricultura de precisão é avaliar a qualidade dos mapas dos atributos dos solos. Neste sentido, o presente trabalho objetivou avaliar o desempenho dos métodos geoestatísticos: krigagem ordinária e simulação sequencial gaussiana na predição espacial do diâmetro médio do cristal da goethita com 121 pontos amostrados em uma malha de 1 ha com espaçamentos regulares de 10 em 10 m. Após a análise textural e da concentração dos óxidos de ferro, calcularam-se os valores do diâmetro médio do cristal da goethita os quais foram analisados pela estatística descritiva e geoestatística; em seguida, foram utilizadas a krigagem ordinária e a simulação sequencial gaussiana. Com os resultados avaliou-se qual foi o método mais fiel para reproduzir as estatísticas, a função de densidade de probabilidade acumulada condicional e a estatística epsilon εy da amostra. As estimativas E-Type foram semelhantes à krigagem ordinária devido à minimização da variância. No entanto, a krigagem deixa de apresentar, em locais específicos, o grau de cristalinidade da goethita enquanto o mapa E-Type indicou que a simulação sequencial gaussiana deve ser utilizada ao invés de mapas de krigagem. Os mapas E-type devem ser preferíveis por apresentar melhor desempenho na modelagem.
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The knowledge on spatial distribution of soil properties by means of geostatistics is important as an indicator for a better soil use and management. This study aimed at evaluating the spatial distribution of soil chemical properties, in a forest and pasture area in Manicoré, Amazonas State, Brazil. Grids with 70.00 m x 70.00 m, with regular spacing of 10.00 m x 10.00 m, totaling 64 points, were established, and then soil samples were collected at the depths of 0.0-0.20 m and 0.40-0.60 m and had their chemical properties determined. Data were analyzed by using descriptive statistics and geostatistics, and the sampling density analysis was based on the coefficient of variation and semivariograms range. The mean and median values were adjusted to the closest values, indicating normal distribution, while the spherical, exponential and gaussian models were adjusted to the soil chemical properties. It was concluded that the geostatistics provided adequate information for understanding the spatial distribution. The forest area showed a higher spatial continuity and the pasture area a lower sampling density. The chemical properties showed differences in the spatial variability, while the range represented better the estimates for sampling density and spacing, in the forest and pasture area.
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The use of geostatistical techniques allows detection of the existence of dependence and the spatial distribution of soil properties, thus constituting an important tool in the analysis and detailed description of the behavior of soil physical properties. The aim of the present study was to use geostatistics in assessment of physical properties in a Latossolo (Oxisol) dystrophic under native forest and pasture in the Amazon region of Manicore. Grids with of 70 x 70 m were established in native forest and pasture, and points were marked in these grids spaced at every 10 m, for a total of 64 points. These points were then georeferenced and in each one, soil samples (128) were collected at the depths of 0.00-0.20 and 0.40-0.60 m for a survey of their physical properties. These grids are parallel at a distance of 100 m from one another. The following determinations were made: texture, bulk density and particle density, macroporosity, microporosity, total porosity and aggregate stability in water. After tabulating the data, descriptive statistical analysis and geostatistical analysis were performed. The pasture had a slight variation in its physical properties in relation to native forest, with a high coefficient of variation and weak spatial dependence. The scaled semivariograms were able to satisfactorily reproduce the spatial behavior of the properties in the same pattern as the individual semivariograms, and the use of the parameter range of the semivariogram was efficient for determining the optimal sampling density for the environments under study. The geostatistical results indicate that the removal of native forest for establishing pasture altered the natural variability of the physical properties.
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In agriculture, the search for higher crop yields based on sustainable soil management has led to a gradual pursuit of knowledge of the variables related to production systems. The identification of the causes of variability of these properties has become a part of strategic planning in the sugar and ethanol industry. This study investigated the spatial variability of iron oxides in the clay fraction and its relationship to soil physical and chemical properties in different sugarcane cultivation systems in the region of Ribeirão Preto, São Paulo State. Two 1-ha plots were outlined in areas with mechanical and manual harvesting systems. Soil samples were taken at 126 points from the 0.00-0.25 m layer in both areas. The mineralogical and chemical data were subjected to geostatistical analyses, to determine the spatial dependence, semivariograms and kriging maps of the properties. To analyze the correlation between the parameters cross-semivariograms were constructed. The spatial variability of chemical properties was greater in areas with mechanical harvesting than burnt harvesting (manual harvesting), whereas the range of the mineralogical properties was largest in the area of green-harvested sugarcane. The properties organic matter, mean crystal diameter goethite had a negatively spatial correlation, while clay was positive correlated with P sorption in the two sugarcane harvest systems.
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Pós-graduação em Geociências e Meio Ambiente - IGCE
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The State of Mato Grosso do Sul is in full growth of this sector, thus the concern about harvesting systems are being studied, and these systems may influence the weed community interference of weeds in the cane sugar. The integrated management tool attached to geostatistics is to avoid productivity losses due to weed interference. The objective of this work was to study the spatial variability of the seed bank of weeds depending on the system for collecting cane sugar (raw and burning). The experiment was conducted in the area of commercial cultivation of the plant ETH Bioenergy S/A Eldorado Unity. Soil samples were taken with auger layer from 0.00 to 0.40 m depth in both cropping systems. The experimental plot was composed by a mesh consisting of 50 points georeferenced with irregular distances. Soil samples were taken to the greenhouse for germination. The number of weed species was analyzed using descriptive statistics and geostatistical techniques. The seeds of B. pilosa, dicots, bitter grass, nutsedge, dayflower monocots and spatial dependence of the seed bank in the collection system with burning of cane sugar. For the system of harvest only the raw sedge species present spatial dependence of distribution in the seed bank. In the harvest green cane enable the mapping of these species through the kriging maps produced, spot applications of herbicides in integrated management of Cyperus rotundus.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Better knowledge of the anthropogenic soils can help create future scenarios for the Amazon region through information that supports the sustainable planning. The aim of this study was to evaluate the spatial variability of soil physical anthropogenic and not anthropogenic in the region of Manipur, AM. In the study area we selected two, one with no anthropogenic soils (native forest) and another with anthropogenic soils (black earth archaeological). In each area, we established a grid measuring 70 x 70 m and the soils were sampled at the points of intersection of the grid with regular spacing of 10 by 10 feet, making a total of 64 sampling points in each landscape. Soil samples were collected at a depth from 0.0 to 0.10 I did the analyzes physical (texture, bulk density, macroporosity, microporososidade, porosity and aggregate stability). Then, the data were subjected to descriptive statistics and geostatistics. It was found that the anthropogenic and non-anthropogenic soils showed different behaviors in relation ace their spatial structures. The spatial variability that prevailed in anthropogenic and non-anthropogenic soil was moderate and weak indicating that these soils are strongly linked to changes in the soil by extrinsic factors. The soil was observed anthropogenic best results for total porosity, microporosity and bulk density, showing superior characteristics compared for agronomic soil not anthropogenic. And the range of values found in the above two areas were used in the mesh, showing greater spatial continuity in these environments.
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The objective of this study was to analyze different intensities of soil sampling for accuracy in geostatistical analysis and interpolation maps for precision agriculture in the sugarcane area. Soil samples were collected at two regular grids at a depth of 0.00 to 0.20m for granulometric analysis (area 1) and soil fertility (area 2). We compared soil sampling intensities: 208, 105, 58 and 24 points in Area 1 and 206, 102 and 53 points in Area 2. The data were submitted to descriptive analysis and geostatistics. The variograms constructed with 105 points didn't differ from variograms with 208 points, which doesn't occur for 58 and 24 points. The increase of sampling interval and reducing the number of points promote greater error in kriging. Samples with more than 100 points per area did not result in significant improvements in the error of kriging, or differed in the amount of fertilizer applied to the field.
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Soil CO2 emission (F-CO2) is influenced by chemical, physical and biological factors that affect the production of CO2 in the soil and its transport to the atmosphere. F-CO2 varies in time and space depending on environmental conditions, including the management of the agricultural area. The aim of this study was to investigate the spatial variability structure of F-CO2 and soil attributes in a mechanically harvested sugarcane area (green harvest) using fractal dimension (D-F) derived from isotropic variograms at different scales (fractograms). F-CO2 showed an overall average of 1.51 mu mol CO2 m(-2) s(-1) and correlated significantly (P < 0.05) with soil physical attributes, such as soil bulk density, air-filled pore space, macroporosity and microporosity. Topologically significant DF values were obtained from the characterization of F-CO2 at medium and large scales (above 20 m), with values of 2.92 and 2.90, respectively. The variations in D-F with scales indicate that the spatial variability structure of F-CO2 was similar to that observed for soil temperature and total pore volume and was the inverse of that observed for other soil attributes, such as soil moisture, soil bulk density, microporosity, air-filled pore space, silt and clay content, pH, available phosphorus and the sum of bases. Thus, the spatial variability structure of F-CO2 presented a significant relationship with the spatial variability structure for most soil attributes, indicating the possibility of using fractograms as a tool to better describe the spatial dependence of variables along the scale. (C) 2014 Elsevier B.V. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)