Performing k-means analysis to drought principal components of Turkish rivers - Demirel, M. Cüneyd, author; Mariano, Arthur J., author; Kahya, Ercan, author; Colorado State University, publisher (Colorado State University. Libraries, 2007)
In this study, the principal component analysis (here after PCA) was applied to 31- year (1964-1994) monthly minimum streamflow data from 23 catchments in Turkey. Ephemeral flows in winter are associated with non melted snow or even ice and summer low flows are related to the semi-arid climate of Turkey with topography, leading high temperature in lowland catchments. The PC matrix (80x2), explaining the highest variance of the main data, was chosen as an input to k-means routine to define drought regions. The first 4 PCs explains more than 80% of the total variance, the first PC presents 52.44% by itself. The resulting maps and silhouette plots for two level (6 and 10 clusters) scheme reveal that the clustering scheme is not successful when the principal components are used for defining the drought zones of Turkey.
Hydrology days 2007
AGU hydrology days 2007
2007 annual AGU hydrology days was held at Colorado State University on March 19 - March 21, 2007.