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Pooling of low flow regimes using cluster and principal component analysis Cover

Pooling of low flow regimes using cluster and principal component analysis

Open Access
|Jul 2012

Abstract

This article deals with the regionalization of low flow regimes lower than Q95 in Slovakia. For the regionalization of 219 small and medium-sized catchments, we used a catchment area running from 4 to 500 km2 and observation periods longer than 20 years. The relative frequency of low flows lower than Q95 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.

DOI: https://doi.org/10.2478/v10189-012-0010-y | Journal eISSN: 1338-3973 | Journal ISSN: 1210-3896
Language: English
Page range: 19 - 27
Published on: Jul 19, 2012
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2012 Andrea Števková, Miroslav Sabo, Silvia Kohnová, published by Slovak University of Technology in Bratislava
This work is licensed under the Creative Commons License.

Volume 20 (2012): Issue 2 (June 2012)