3 resultados para successive linearization

em University of Queensland eSpace - Australia


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Spatial characterization of non-Gaussian attributes in earth sciences and engineering commonly requires the estimation of their conditional distribution. The indicator and probability kriging approaches of current nonparametric geostatistics provide approximations for estimating conditional distributions. They do not, however, provide results similar to those in the cumbersome implementation of simultaneous cokriging of indicators. This paper presents a new formulation termed successive cokriging of indicators that avoids the classic simultaneous solution and related computational problems, while obtaining equivalent results to the impractical simultaneous solution of cokriging of indicators. A successive minimization of the estimation variance of probability estimates is performed, as additional data are successively included into the estimation process. In addition, the approach leads to an efficient nonparametric simulation algorithm for non-Gaussian random functions based on residual probabilities.

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The appropriate use of wastes is a significant issue for the pig industry due to increasing pressure from regulatory authorities to protect the environment from pollution. Nitrogen contained in piggery pond sludge ( PPS) is a potential source of supplementary nutrient for crop production. Nitrogen contribution following the application of PPS to soil was obtained from 2 field experiments on the Darling Downs in southern Queensland on contrasting soil types, a cracking clay ( Vertosol) and a hardsetting sandy loam (Sodosol), and related to potentially mineralisable N from laboratory incubations conducted under controlled conditions and NO3- accumulation in the field. Piggery pond sludge was applied as-collected ( wet PPS) and following stockpiling to dry ( stockpiled PPS). Soil NO3- levels increased with increased application rates of wet and stockpiled PPS. Supplementary N supply from PPS estimated by fertiliser equivalence was generally unsatisfactory due to poor precision with this method, and also due to a high level of NO3- in the clay soil before the first assay crop. Also low recoveries of N by subsequent sorghum ( Sorghum bicolor) and wheat ( Triticum aestivum) assay crops at the 2 sites due to low in-crop rainfall in 1999 resulted in low apparent N availability. Over all, 29% ( range 12 - 47%) of total N from the wet PPS and 19% ( range 0 - 50%) from the stockpiled PPS were estimated to be plant-available N during the assay period. The high concentration of NO3- for the wet PPS application on sandy soil after the first assay crop ( 1998 barley, Hordeum vulgare) suggests that leaching of NO3- could be of concern when high rates of wet PPS are applied before infrequent periods of high precipitation, due primarily to the mineral N contained in wet PPS. Low yields, grain protein concentrations, and crop N uptake of the sorghum crop following the barley crop grown on the clay soil demonstrated a low residual value of N applied in PPS. NO3- in the sandy soil before sowing accounted for 79% of the variation in plant N uptake and was a better index than anaerobically mineralisable N ( 19% of variation explained). In clay soil, better prediction of crop N uptake was obtained when both anaerobically mineralisable N (39% of variation explained) and soil pro. le NO3- were used in combination (R-2 = 0.49).