Revista Brasileira de Ciência do Solo
Print version ISSN 0100-0683
MIQUELONI, Daniela Popim and BUENO, Célia Regina Paes. Multivariate analysis and spatial variability to estimate soil erodibility of an anfisol. Rev. Bras. Ciênc. Solo [online]. 2011, vol.35, n.6, pp. 2175-2182. ISSN 0100-0683. http://dx.doi.org/10.1590/S0100-06832011000600032.
Erodibility is an important factor for soil loss quantification, representing the processes that regulate water infiltration and soil resistance to the breakdown and transport of particles. Thus, by analyzing the spatial dependence of the principal components of erodibility (K-factor), aimed to estimate soil erodibility in a headwaters area in the watershed Córrego do Tijuco, Monte Alto, SP, and analyze the spatial variability of soil texture variables across the landscape. The mean erodibility of the area was high and the analysis of k-means clustering indicated the formation of five groups: the first high, with coarse (AG) and intermediate sand was distributed in the plane areas, the second with high content of fine sand (AF), was distributed in more convex slopes, and the third, with high levels of silt and very fine sand, was concentrated on steeper slopes and in hollows, the fourth with highest clay content, was concentrated in drainage areas, and the fifth, with high content of organic matter (MO) and coarse sand was distributed near the urban area. The principal component analysis (PCA) showed four components with 87.4% of the information. The first principal component (PC1) discriminated the selective transport of particles, mainly in specific areas of greatest slope and sediment buildup, the second component (PC2) discriminated the low cohesion between the particles, shows accumulation of fine sand at lower altitudes of the entire area of water concentration, the third component (PC 3) discriminated the greatest soil aggregation, mainly at the bases of high slopes and the fourth component (PC4) discriminated very fine sand, distributed along the slope at higher elevations. The results indicate the behavior of soil granulometry, which appears susceptible to erosion due to the surface textural conditions and the relief movement.
Keywords : Principal components; cluster analysis; kriging; erosion.