Modelagem de fertilidade do solo por simulação estocástica com tratamento de incertezas

Ortiz, Jussara de Oliveira; Felgueiras, Carlos; Druck, Suzana; Monteiro, Antônio Miguel Vieira

doi:10.1590/s0100-204x2004000400012

Cited by 6 publications

(8 citation statements)

References 3 publications

(5 reference statements)

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“…However, these studies have in common many soils, moisture contents, textures, and different conditions in soil physical properties, which makes it hard to define the parameters of the compression curve for a specific study and more accurate analysis. Under these conditions, simulations can help create scenarios for reproducing experimental data (Tagar et al, 2015), which formalize and analyze some error propagation methods for modeling; among them, the Monte Carlo method has general applicability and can be used in models with mathematical formulations (Ortiz et al, 2004). This procedure was used by Ortiz et al (2004), and simulations based on other methods were used by Oliveira et al (2013Oliveira et al ( , 2014 for soil data in Brazil.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Methods for Determining Precompression Stress Based on Computational Simulation

Silva

Lima

2016

Rev. Bras. Ciênc. Solo

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There are many methods for determining precompression stress (σ p ), whose value is affected by the slope of the soil compression curve. This study was designed to evaluate the hypothesis that for a certain compression curve all methods used to determine σ p present the same value and accuracy. The aim of this study was to compare the accuracy and the relationship among seven of these methods by computational simulation of soil compression curves under nine scenarios. The following methods were used: Casagrande, Pacheco Silva, intersection of the initial void ratio with the virgin compression line (VCLzero), and the regression methods based on 2 (reg1), 3 (reg2), 4 (reg3), and 5 (reg4) points for modeling the elastic curve. Under each scenario, created by combining the swelling and the compression indices, 1,000 compression curves were computationally simulated via the Monte Carlo method. Subsequently, 95 % percentile confidence intervals were built using the 1,000 estimates of σ p from each method under each scenario. Most of the differences among the methods were detected under scenarios consisting of high swelling and low compression indices. In general, Casagrande, Pacheco Silva, and reg4 were strongly correlated and presented the highest values of σ p , as well as similar variability. The latter two can be considered as alternatives to the standard method of Casagrande, except for Pacheco Silva when the curve has a low compression index (≤0.2) and from medium to high swelling index (≥0.025), for which differences (p<0.05) were detected.

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Section: Introductionmentioning

confidence: 99%

Comparison of Methods for Determining Precompression Stress Based on Computational Simulation

Silva

Lima

2016

Rev. Bras. Ciênc. Solo

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“…A krigagem tem por objetivo obter a melhor estimativa local sem preocupar-se em reproduzir as estatísticas espaciais estimadas a partir do conjunto amostral. A simulação, por sua vez, tem como objetivo a reprodução dessas estatísticas e também tem a vantagem de integrar, de forma mais simples, vários atributos em um único modelo (ORTIZ et al, 2004).…”

Section: Introductionunclassified

Geoestatística E Simulações Condicionais Aplicadas a Ensaios De Uniformidade De Aspersão Convencional

Perboni¹,

José²,

Ullmann

et al. 2014

R_I

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The increased use of water by irrigation and its high-cost added on makes it necessary that high levels of uniformity and efficiency be provided by the irrigation systems. The description of variability and the structure of spatial dependence of the uniformity test of conventional sprinkler irrigation can contribute for an efficient management of irrigation. Geoestatística e simulações condicionais...

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“…Ela possui a vantagem de integrar, de forma mais simples, vários atributos em um único modelo visando à apresentação da estatística dos dados amostrais (Ortiz et al, 2004). Na SSG muitos mapas, igualmente prováveis da distribuição do atributo em estudo, são produzidos de acordo o mesmo modelo da correlação espacial tal como requerido para a krigagem.…”

Section: Introductionunclassified

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

Silva

Pereira

Camargo

et al. 2013

Rev. bras. eng. agríc. ambient.

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RESUMOUma 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 ε y 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.Palavras-chave: agricultura de precisão, krigagem ordinária, simulação sequencial gaussiana, pedometria Geostatistical methods in spatial modelling of the middle diameter of the goethite crystal ABSTRACT In precision agriculture it is necessary to assess the quality of the maps of soil attributes. This paper aimed to evaluate the performance of geostatistical methods: ordinary kriging and sequential Gaussian simulation on spatial prediction of mean diameter of the goethite crystal in a regular grid with 121 points collected in a grid of 1 ha with regular spacing of 10 to 10 m. After the particle size and concentration analysis of iron oxides the values of the mean diameter of the goethite crystal were calculated. These were analysed by descriptive statistics and geostatistics, ordinary kriging and sequential Gaussian simulation was used for production of maps. With the results which evaluated the method is more faithful to make statistics, the cumulative probability density function conditional epsilon statistics ε y . E-Type estimates were similar to ordinary kriging, due to the minimization of the variance. However, the ordinary kriging did not perform well in specific locations for crystallinity of goethite, while the E-Type map by sequential Gaussian simulation should be used instead of kriging maps. The E-type maps should be prefered as they present better performance in modeling.

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Modelagem de fertilidade do solo por simulação estocástica com tratamento de incertezas

Cited by 6 publications

References 3 publications

Comparison of Methods for Determining Precompression Stress Based on Computational Simulation

Comparison of Methods for Determining Precompression Stress Based on Computational Simulation

Geoestatística E Simulações Condicionais Aplicadas a Ensaios De Uniformidade De Aspersão Convencional

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

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