Spatial variability of the chemical, physical and biological properties in lowland cultivated with irrigated rice

Abstract

In the areas where irrigated rice is grown in the south of Brazil, few studies have been carried out to investigate the spatial variability structure of soil properties and to establish new forms of soil management as well as determine soil corrective and fertilizer applications. In this sense, this study had the objective of evaluating the spatial variability of chemical, physical and biological soil properties in a lowland area under irrigated rice cultivation in the conventional till system. For this purpose, a 10 x 10 m grid of 100 points was established, in an experimental field of the Embrapa Clima Temperado, in the County of Capão do Leão, State of Rio Grande do Sul. The spatial variability structure was evaluated by geostatistical tools and the number of subsamples required to represent each soil property in future studies was calculated using classical statistics. Results showed that the spatial variability structure of sand, silt, SMP index, cation exchange capacity (pH 7.0), Al3+ and total N properties could be detected by geostatistical analysis. A pure nugget effect was observed for the nutrients K, S and B, as well as macroporosity, mean weighted diameter of aggregates, and soil water storage. The cross validation procedure, based on linear regression and the determination coefficient, was more efficient to evaluate the quality of the adjusted mathematical model than the degree of spatial dependence. It was also concluded that the combination of classical with geostatistics can in many cases simplify the soil sampling process without losing information quality.

Delineation of irrigation management zones in a Quartzipsamment of the Brazilian semiarid region

“…bras., Brasília, v.51, n.9, p.1283-1294, set. 2016 DOI: 10.1590/S0100-204X2016000900028 Our study corroborate the results of the following authors: Terra (2012), who found that the same models adjusted for the attributes sand (exponential), clay, and Ds (spherical); Parfitt et al (2009), who obtained a Gaussian fit for silt; and Molin & Faulin (2013), who found a spherical model for ECa in different time periods.…”

Spatial variability of some soil properties varies in oil palm (<i>Elaeis guineensis</i> Jacq.) plantations of west coastal area of India

“…Accuracies of interpolated maps of studied soil properties were checked by G values. According to Parfitt et al (2009), positive G values indicate that the map Skewness values of 0.18 to 3.89 for different soil proprieties revealed that some soil properties were not normally distributed. This variation and non-normal distribution of soil properties in the studied areas may be due to adoption of different soil management practices including variation in fertilizer application and other crop management practices (Tesfahunegn et al, 2011;Srinivasarao et al, 2014;Ferreira et al, 2015).…”

Impacts of land leveling on lowland soil physical properties

“…Thematic maps were generated before and after leveling (Parfitt, 2009;Parfitt et al, 2009) through kriging when the spatial variability of the properties was properly defined and identified through semivariograms, and through the inverse of the squares of the distances when the spatial variability was not properly defined by semivariograms. Therefore, a visual analysis of the spatial distribution of the properties was made.…”

“…The spatial variability, before and after leveling (Parfitt, 2009;Parfitt et al, 2009), of clay, sand, silt, Disp clay and Bd properties as well as Micro (after leveling) were well described by semivariograms, and therefore their thematic maps were generated by kriging. For the other properties, the inverse of the squares of the distances was used to generate the thematic maps.…”