Pooling of low flow regimes using cluster and principal component analysis

Abstract

This article deals with the regionalization of low flow regimes lower than Q 95 in Slovakia. For the regionalization of 219 small and medium-sized catchments, we used a catchment area running from 4 to 500 km 2 and observation periods longer than 20 years. The relative frequency of low flows lower than Q 95 was calculated. For the regionalization, the nonhierarchical clustering K-means method was applied. The Silhouette coefficient was used to determine the right number of clusters. The principal components were found from the pooling variables on the principal components. The K-means clustering method was applied. Next, we compared the differences between the two methods of pooling data into regional types. The results were compared using an association coefficient.