Delineation of homogeneous regions for streamflow via fuzzy c-means in the Amazon

Abstract

Abstract Lack of streamflow data is one of the main limitations in hydrologic studies. One method of solving this problem is by streamflow regionalization. The identification of hydrologically homogeneous regions is the main and most important stage of regionalization. In this study homogeneous flow regions are identified by fuzzy c-means (FCM) cluster analysis based on morpho-climatic characteristics from streamflow at 208 stream gauges in the Amazon region. The optimal number of clusters in the dataset was identified by applying the PBM validation index, maximized for ten clusters, with a fuzzing parameter of 1.6. The application dataset is best divided into 10 groups. These were well defined and demonstrated the Amazon's hydrologic similarity.