Multivariate Analysis of Erosivity Indices and Rainfall Physical Characteristics Associated with Rainfall Patterns in Rio de Janeiro

Abstract

The identification of areas with greater erosive potential is important for planning soil and water conservation. The objective of this study was to evaluate the physical characteristics of rainfall events in the state of Rio de Janeiro, Brazil, and their interactions with rainfall patterns through multivariate statistical analysis. Rainfall depth, kinetic energy, 30-min intensity (I 30), duration of rainfall events, and the erosivity indices KE >10, KE >25, and EI 30 in 36 locations (stations) were subjected to principal component analysis (PCA) and canonical discriminant analysis (CDA). Based on evaluation of the respective historical series of hyetographs, it was found that the advanced pattern occurs with highest frequency (51.8 %), followed by the delayed pattern (26.1 %), and by the intermediate pattern (22.1 %). All the evaluated rainfall characteristics have high response capacity in describing localities and rainfall patterns through PCA and CDA. In CDA, the Tukey test (p<0.05) applied to the scores of the first canonical discriminant function (CDF 1) allowed differentiation of the stations with respect to the rainfall and erosivity characteristics for the advanced and delayed patterns. In the delayed pattern, the localities of Angra dos Reis,

Physicochemical properties and metal speciation in gas flare-impacted soils in Ibeno, NigeriaPhysicochemical properties and metal speciation in gas flare-impacted soils in Ibeno, NigeriaPhysicochemical properties and metal speciation in gas flare-impacted

“…The Principal Component Analysis (PCA) was employed to establish the actual sources of the metals determined in the studied soils [49,50]. Components with Eigenvalues of one and above were considered while parameters with values of 0.549 and above were used for the explanation of the results in Table 5.…”