4.7 Article

Spatial variability patterns of some Vertisol properties at a field scale using standardized data

期刊

SOIL & TILLAGE RESEARCH
卷 120, 期 -, 页码 76-84

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.still.2011.11.003

关键词

Vertisols; Geostatistics; Fragmentation dimension; Data standardization; Semivariogram; Multivariate spatial analysis

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Spatial variability of Vertisol properties is relevant for identifying those zones with physical degradation. In this sense, one has to face the problem of identifying the origin and distribution of spatial variability patterns. The objectives of the present work were (i) to quantify the spatial structure of different physical properties collected from a Vertisol, (ii) to search for potential correlations between different spatial patterns and (iii) to identify relevant components through multivariate spatial analysis. The study was conducted on a Vertisol (Typic Hapludert) dedicated to sugarcane (Saccharum officinarum L.) production during the last sixty years. We used six soil properties collected from a squared grid (225 points) (penetrometer resistance (PR), total porosity, fragmentation dimension (D-f), vertical electrical conductivity (ECv), horizontal electrical conductivity (ECh) and soil water content (WC)). All the original data sets were z-transformed before geostatistical analysis. Three different types of semivariogram models were necessary for fitting individual experimental semivariograms. This suggests the different natures of spatial variability patterns. Soil water content rendered the largest nugget effect (C-o = 0.933) while soil total porosity showed the largest range of spatial correlation (A = 43.92 m). The bivariate geostatistical analysis also rendered significant cross-semivariance between different paired soil properties. However, four different semivariogram models were required in that case. This indicates an underlying co-regionalization between different soil properties, which is of interest for delineating management zones within sugarcane fields. Cross-semivariograms showed larger correlation ranges than individual, univariate, semivariograms (A >= 29 m). All the findings were supported by multivariate spatial analysis, which showed the influence of soil tillage operations, harvesting machinery and irrigation water distribution on the status of the investigated area. (C) 2011 Elsevier B,V. All rights reserved.

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