Métodos geoestatísticos na modelagem espacial do diâmetro médio do cristal da goethita

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.

Modelagem geoestatística das incertezas da distribuição espacial do fósforo disponível no solo, em área de cana-de-açúcar

Phosphorus is one of the limiting nutrients for sugarcane development in Brazilian soils. The spatial variability of this nutrient is great, defined by the properties that control its adsorption and desorption reactions. Spatial estimates to characterize this variability are based on geostatistical interpolation. However, inherent uncertainties in the procedure of these estimates are related to the variability structure of the property under study and the sample configuration of the area. Thus, the assessment of the uncertainty of estimates associated with the spatial distribution of available P (Plabile) is decisive to optimize the use of phosphate fertilizers. The purpose of this study was to evaluate the performance of sequential Gaussian simulation (sGs) and ordinary kriging (OK) in the modeling of uncertainty in available P estimates. A sampling grid with 626 points was established in a 200-ha experimental sugarcane field in Tabapuã, São Paulo State. The sGs algorithm generated 200 realizations. The sGs realizations reproduced the statistics and the distribution of the sample data. The G statistic (0.81) indicated good agreement between the values of simulated and observed fractions. The sGs realizations preserved the spatial variability of Plabile without the smoothing effect of the OK map. The accuracy in the reproduction of the variogram of the sample data obtained by the sGs realizations was on average 240 times higher than that obtained by OK. The uncertainty map, obtained by OK, showed less variation in the study area than that obtained by sGs. Thus, the evaluation of uncertainties by sGs was more informative and can be used to define and delimit specific management areas more precisely.

Spatial Distribution of the Risk of Dengue and the Entomological Indicators in Sumare, State of Sao Paulo, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modelagem e quantificação da incerteza espacial do potássio disponível no solo por simulações estocásticas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mapeamento geoestatístico da vulnerabilidade do Aquífero Guarani no município de Ribeirão Bonito - SP

The Guaraní aquifer has relevant importance both as a source of water for several urban centres and the development of agriculture and livestock. In recharge areas the aquifer is free and, therefore, subject to contamination of effluents and tailings deposited on soils that cover it. Thus, it becomes crucial not only its protection at all levels, as the knowledge of its degree of natural vulnerability. The present work used geostatistics modeling techniques to study the natural vulnerability of the Guaraní aquifer in the city of Rio Bonito, State of São Paulo, southeastern Brazil, where the Guarani aquifer is exposed. These techniques, extensively used in evaluation studies of mineral deposits and oil tanks, can be adapted to produce a spatial classification or a regionalisation of probabilistic indices of vulnerability. By ordinary kriging method maps of vulnerability classification were obtained. To determine the vulnerability of the aquifer was employed the Aquifer Vulnerability Index (AVI), which requires knowledge of unsaturated zone thickness and permeability. The final product was a map with probabilistic index of vulnerability of the Guaraní aquifer, which presented values between 0 to 0.33 years, framing the area studied in AVI class extremely high vulnerability

Simulação geoestatística e classificação numérica para o delineamento de unidade de mapeamento de atributos e erosão do solo

Pós-graduação em Agronomia (Ciência do Solo) - FCAV

Mapeamento de cianobactérias por meio da fluorescência da ficocianina e de análise geoestatística

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise geoestatística para geração de superfícies a partir de dados de clorofila-a adquiridos em transectos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Spatial distribution of runoff depth from a watershed located in a cuesta relief area of São Paulo State, Brazil

This study was undertaken in a 1566 ha drainage basin situated in an area with cuesta relief in the state of São Paulo, Brazil. The objectives were: 1) to map the maximum potential soil water retention capacity, and 2) to simulate the depth of surface runoff in each geographical position of the area based on a typical rainfall event. The database required for the development of this research was generated in the environment of the geographical information system ArcInfo v.10.1. Undeformed soil samples were collected at 69 points. The ordinary kriging method was used in the interpolation of the values of soil density and maximum potential soil water retention capacity. The spherical model allowed for better adjustment of the semivariograms corresponding to the two soil attributes for the depth of 0 to 20 cm, while the Gaussian model enabled a better fit of the spatial behavior of the two variables for the depth of 20 to 40 cm. The simulation of the spatial distribution revealed a gradual increase in the depth of surface runoff for the rainfall event taken as example (25 mm) from the reverse to the peripheral depression of the cuesta (from west to east). There is a positive aspect observed in the gradient, since the sites of highest declivity, especially those at the front of the cuesta, are closer to the western boundary of the watershed where the lowest depths of runoff occur. This behavior, in conjunction with certain values of erodibility and depending on the land use and cover, can help mitigate the soil erosion processes in these areas.

Espacialização dos sedimentos produzidos na parte inicial da bacia hidrográfica do Rio Pardo, Botucatu/SP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Eficiência da cokrigagem na estimativa da produtividade do café conilon

The objective of this research was to estimate the productivity (PRODUT) in sc/ha of coffee conilon through the technique of cokriging, using as covariate the production of humid coffee (PROD) in kg and compare the results with estimates obtained by kriging ordinary. The study was conducted in a commercial area of conilon coffee, Coffea canephora Pierre var. conilon, located in São Mateus Municipality, Espirito Santo State. For the field work was sampled the humid coffee production in a sampling grid irregular of 18.5 ha, 87 sampling points in the total. We also determined the production of dry coffee beans and coffee benefited 12% moisture, to obtain the PRODUT variable. After exploratory data analysis, which showed the correlation between variables in the order of 0.899, was performed variogram analysis. Were adjusted theoretical variograms to PROD and PRODUT and cross variogram between two variables. Finally we estimated the value of productivity, both by ordinary kriging as per cokriging. The validation of the estimation by cokriging not shows, however, significant gains in relation to validation by ordinary kriging.

Geoelectrical mapping of contamination in the cemeteries: the case study in Piracicaba, Sao Paulo/Brazil

This paper presents the results of electrical resistivity methods in the area delineation that was potentially contaminated by liquefaction products, which are also called putrefactive liquids in Vila Rezende municipal cemetery, Piracicaba, So Paulo, Brazil. The results indicate a depth of water table between 3.1 and 5.1 m, with two groundwater direction flows, one to the SW and another to the SE. Due to the contamination plumes, which have the same groundwater direction flow, as well the conductive anomalies observed in the geoelectric sections, the contamination suspicions in the area were confirmed. The probable plume to the SE extends beyond the limits of the cemetery. The location of the conductive anomalies and the probable contamination plumes showed that the contamination is linked with the depth of the water table and the burial time. Mapping using the geostatistical method of ordinary kriging applied to the work drew structural characteristics of the regional phenomenon and spatial behavior of the electrical resistivity data, resulting in continued surfaces. Thus, this method has proved to be an important tool for mapping contamination plumes in cemeteries.

SPATIAL VARIABILITY OF THE RAINFALL EROSIVE POTENTIAL IN THE STATE OF MATO GROSSO DO SUL, BRAZIL

Information about rainfall erosivity is important during soil and water conservation planning. Thus, the spatial variability of rainfall erosivity of the state Mato Grosso do Sul was analyzed using ordinary kriging interpolation. For this, three pluviograph stations were used to obtain the regression equations between the erosivity index and the rainfall coefficient EI30. The equations obtained were applied to 109 pluviometric stations, resulting in EI30 values. These values were analyzed from geostatistical technique, which can be divided into: descriptive statistics, adjust to semivariogram, cross-validation process and implementation of ordinary kriging to generate the erosivity map. Highest erosivity values were found in central and northeast regions of the State, while the lowest values were observed in the southern region. In addition, high annual precipitation values not necessarily produce higher erosivity values.

Estimativa de densidade amostral para elaboração de mapas de produtividade

Yield mapping represents the spatial variability concerning the features of a productive area and allows intervening on the next year production, for example, on a site-specific input application. The trial aimed at verifying the influence of a sampling density and the type of interpolator on yield mapping precision to be produced by a manual sampling of grains. This solution is usually adopted when a combine with yield monitor can not be used. An yield map was developed using data obtained from a combine equipped with yield monitor during corn harvesting. From this map, 84 sample grids were established and through three interpolators: inverse of square distance, inverse of distance and ordinary kriging, 252 yield maps were created. Then they were compared with the original one using the coefficient of relative deviation (CRD) and the kappa index. The loss regarding yield mapping information increased as the sampling density decreased. Besides, it was also dependent on the interpolation method used. A multiple regression model was adjusted to the variable CRD, according to the following variables: spatial variability index and sampling density. This model aimed at aiding the farmer to define the sampling density, thus, allowing to obtain the manual yield mapping, during eventual problems in the yield monitor.

Whale sightings, group sizes and krill biomass in West Greenland in 2005

This study combined data on fin whale Balaenoptera physalus, humpback whale Megaptera novaeangliae, minke whale B. acutorostrata, and sei whale B. borealis sightings from large-scale visual aerial and ship-based surveys (248 and 157 sightings, respectively) with synoptic acoustic sampling of krill Meganyctiphanes norvegica and Thysanoessa sp. abundance in September 2005 in West Greenland to examine the relationships between whales and their prey. Krill densities were obtained by converting relationships of volume backscattering strengths at multiple frequencies to a numerical density using an estimate of krill target strength. Krill data were vertically integrated in 25 m depth bins between 0 and 300 m to obtain water column biomass (g/m**2) and translated to density surfaces using ordinary kriging. Standard regression models (Generalized Additive Modeling, GAM, and Generalized Linear Modeling, GLM) were developed to identify important explanatory variables relating the presence, absence, and density of large whales to the physical and biological environment and different survey platforms. Large baleen whales were concentrated in 3 focal areas: (1) the northern edge of Lille Hellefiske bank between 65 and 67°N, (2) north of Paamiut at 63°N, and (3) in South Greenland between 60 and 61° N. There was a bimodal pattern of mean krill density between depths, with one peak between 50 and 75 m (mean 0.75 g/m**2, SD 2.74) and another between 225 and 275 m (mean 1.2 to 1.3 g/m**2, SD 23 to 19). Water column krill biomass was 3 times higher in South Greenland than at any other site along the coast. Total depth-integrated krill biomass was 1.3 x 10**9 (CV 0.11). Models indicated the most important parameter in predicting large baleen whale presence was integrated krill abundance, although this relationship was only significant for sightings obtained on the ship survey. This suggests that a high degree of spatio-temporal synchrony in observations is necessary for quantifying predator-prey relationships. Krill biomass was most predictive of whale presence at depths >150 m, suggesting a threshold depth below which it is energetically optimal for baleen whales to forage on krill in West Greenland.