Application of Principal Component Analysis in Grouping Geomorphic Parameters for Hydrologic Modeling

Principal component analysis has been applied to thirteen dimensionless geomorphic parameters for sixteen watersheds of the Chambal catchment of Rajasthan, India, in order to group the parameters under different components based on significant correlations. Results of the principal component analysis clearly revealed that first two principal components are strongly correlated with some of the geomorphic parameters. However, the third principal component is not found to be strongly correlated with any of the parameters but is moderately correlated with stream length ratio and bifurcation ratio. Furthermore, on the basis of the results, it is evident that some parameters are highly correlated with components but the parameters of hypsometric integral and drainage factor could not be grouped with any of the component because of its poor correlation with them. The principal component loadings matrix obtained using correlation matrix of ten parameters reveals that first three components together account for 87.01% of the total explained variance. Therefore, principal component lading matrix is applied in order to get better correlations and clearly grouped the parameters in physically significant components. Copyright Springer Science+Business Media B.V. 2009