Multivariate Statistical Analysis of Morphometric Parameters in Watersheds of Peru

Abstract

AbstractPeru is a country recognized for its natural resources, but it is the third most vulnerable country, different research projects have predicted natural. The objective of the research was to hold out the Multivariate Statistical Analysis to 91 watersheds of Peru to get homogeneous water characteristics in different regions. Twenty morphometric parameters were determined to characterize the watersheds in qualitative and quantitative terms. The principal component analysis was applied, including Factor analysis, Hierarchical Cluster analysis in R and Ward's method. It had been obtained that 75.52% of the watershed studied are favoured by morphometric parameters that contribute to a high frequency of streams, which allows adequate use of water resources. The steep slopes are vulnerable watersheds product to their immediate hydrological response and water erosion, which means a greater need for hydraulic works. Six main components were defined that specify 94.58% of the entire variance denominated as geometric, shape, drainage, and relief factors. The results of the Cluster Analysis showed that 35% of the watersheds have homogeneous zones within the geometric and shape factor, while 65% within the drainage and relief factor.KeywordsClimate changeCluster analysisFactor analysisPrincipal componentRiver