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Pooling of low flow regimes using cluster and principal component analysis
Pooling of low flow regimes using cluster and principal component analysis 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.
Pooling of low flow regimes using cluster and principal component analysis
Pooling of low flow regimes using cluster and principal component analysis 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.
Pooling of low flow regimes using cluster and principal component analysis
Števková, Andrea (Autor:in) / Sabo, Miroslav (Autor:in) / Kohnová, Silvia (Autor:in)
2012
Aufsatz (Zeitschrift)
Englisch
Principal Component Analysis of Building Cluster Factors
Springer Verlag | 2017
|British Library Online Contents | 2011
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