Quantification of uncertainties associated with space-time estimates of short-term soil CO2 emissions in a sugar cane area

The characterization of soil CO2 emissions (FCO2) is important for the study of the global carbon cycle. This phenomenon presents great variability in space and time, a characteristic that makes attempts at modeling and forecasting FCO2 challenging. Although spatial estimates have been performed in several studies, the association of these estimates with the uncertainties inherent in the estimation procedures is not considered. This study aimed to evaluate the local, spatial, local-temporal and spatial-temporal uncertainties of short-term FCO2 after harvest period in a sugar cane area. The FCO2 was featured in a sampling grid of 60m×60m containing 127 points with minimum separation distances from 0.5 to 10m between points. The FCO2 was evaluated 7 times within a total period of 10 days. The variability of FCO2 was described by descriptive statistics and variogram modeling. To calculate the uncertainties, 300 realizations made by sequential Gaussian simulation were considered. Local uncertainties were evaluated using the probability values exceeding certain critical thresholds, while the spatial uncertainties considering the probability of regions with high probability values together exceed the adopted limits. Using the daily uncertainties, the local-spatial and spatial-temporal uncertainty (Ftemp) was obtained. The daily and mean emissions showed a variability structure that was described by spherical and Gaussian models. The differences between the daily maps were related to variations in the magnitude of FCO2, covering mean values ranging from 1.28±0.11μmolm-2s-1 (F197) to 1.82±0.07μmolm-2s-1 (F195). The Ftemp showed low spatial uncertainty coupled with high local uncertainty estimates. The average emission showed great spatial uncertainty of the simulated values. The evaluation of uncertainties associated with the knowledge of temporal and spatial variability is an important tool for understanding many phenomena over time, such as the quantification of greenhouse gases or the identification of areas with high crop productivity. © 2013 Elsevier B.V.

Variabilidade espacial da umidade do solo em irrigação por gotejamento sob cultivo protegido

Pós-graduação em Agronomia (Irrigação e Drenagem) - FCA

Estrutura de variabilidade espacial e temporal da emissão de CO2 e atributos do solo caracterizada por dimensão fractal em área de cana-de-açúcar

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Desenvolvimento de sensor elétrico de contato e correlações com atributos do solo visando à agricultura de precisão

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geoestatística, simulação estocástica e sensoriamento remoto na estimativa de produção do café conilon

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Utilização da geoestatística na construção de mapas de temperatura média mensal para o Estado do Paraná

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Mapeamento de atributos do solo para o planejamento da irrigação sob pivô central

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Variabilidade Espacial da Umidade do Solo em Irrigação por Gotejamento Sob Cultivo Protegido

Foi estudada a variabilidade espacial da umidade do solo num sistema de irrigação por gotejamento em uma estufa (5,0 x 20,0m) na Fazenda Experimental São Manuel, da Faculdade de Ciências Agronômicas, Universidade Estadual Paulista, Estado de São Paulo, Brasil. Foi estabelecida a malha de amostragem no espaçamento de 1,0 x 0,5m, acrescida de quatro adensamentos de 0,25m. Foram utilizados dados da umidade do solo em 178 pontos. A análise da dependência espacial foi obtida com o auxílio do Programa GS+. Foi construído o variograma experimental e definido o modelo de ajuste, de modo que a curva que melhor se ajustou aos pontos obtidos representasse a magnitude, alcance e intensidade da variabilidade espacial da variável estudada. A umidade do solo apresentou distribuição espacial anisotrópica. Para a direção 0°, pode-se notar uma dependência espacial caracterizada como alta, com o alcance de aproximadamente 3,30m, no sentido do comprimento da estufa. Entretanto, no sentido da largura da estufa, não foi possível ajustar modelos. Utilizando a representação gráfica da superfície, a área estudada apresentou um maior teor de água na parte inicial e menor na parte final das linhas de distribuição de água. A krigagem mostrou-se um bom interpolador para mapeamento da umidade do solo.

Optimization of the sampling scheme for maps of physical and chemical properties estimated by kriging

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.

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.

Análise de dados pedogeoquímicos de multielementos visando o refinamento de mapeamento geológico de detalhe em alvos de Pb-Zn nos municípios de Adrianópolis, Cerro Azul e Tunas do Paraná (Vale do Ribeira, PR)

In order to to research, the region of Perau, base metal mineralization, Grupo Votorantim Metals conducted a soil sampling on targets predetermined holding its chemical analysis. These reviews have been provided by the company for this work was to evaluate the potential use of these data pedogeochemical multi-element for refinement of the work of geological mapping. We selected six targets: Varginha, Salvador, Guararema Taquara Lisa and Coffin of Mendes, in the municipalities of Adrianople, Cerro Azul and Tunas do Paraná, located in Vale do Ribeira (PR). Both have about 10 km2 and situated in the geological context of the Fold Belt Terrane and the Massif de Joinville. The main rock types are present metasedimentary rocks of low to medium grade metamorphic, interspersed the amphibolites ortoderivados, both belonging to the Complex Perau, gneisses and migmatitic Complex. Applied to the geochemical data descriptive statistical techniques (variogram, kriging and histogram). From the correlation between the distributions of elements with the geological data, we could assess the potential of the proposed methodology.

Spatial intra-annual variability of precipitation based on geostatistics. a case study for the Paraiba do Sul Basin, southeastern Brazil

The emphasis in this research is to evaluate the spatial distribution of the precipitation using a geostatistics approach. Seasonal time scales records considering DJF, MAM, JJA e SON periods performed the analysis. Procedures to evaluate the variogram selection and to produce kriging maps were performed in a GIS environment (ArcGIS®). The results showed that kriging method was very suitable to detect both large changes in the whole area as those local small and subtle changes. Kriging demonstrated be a powerful statistical interpolation method that might be very useful in regions with great complexity in climatology and geomorphology.

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.

Longitudinal familial analysis of blood pressure involving parametric (co)variance functions

Abstract Background For analyzing longitudinal familial data we adopted a log-linear form to incorporate heterogeneity in genetic variance components over the time, and additionally a serial correlation term in the genetic effects at different levels of ages. Due to the availability of multiple measures on the same individual, we permitted environmental correlations that may change across time. Results Systolic blood pressure from family members from the first and second cohort was used in the current analysis. Measures of subjects receiving hypertension treatment were set as censored values and they were corrected. An initial check of the variance and covariance functions proposed for analyzing longitudinal familial data, using empirical semi-variogram plots, indicated that the observed trait dispersion pattern follows the assumptions adopted. Conclusion The corrections for censored phenotypes based on ordinary linear models may be an appropriate simple model to correct the data, ensuring that the original variability in the data was retained. In addition, empirical semi-variogram plots are useful for diagnosis of the (co)variance model adopted.