Simultaneous Regionalization of Gauged and Ungauged Watersheds Using a Missing Data Clustering Method

Abstract

Use of flood statistics in the regionalization of watersheds may improve the homogeneity of regions. However, it is not possible to use the feature vectors, including the flood statistics, to estimate the flood quantiles for ungauged watersheds by most of the regionalization methods, especially those based on cluster analysis. In the current study, the effect of merging a flood statistic into a feature vector consisting of watershed features has been assessed and then, some algorithms based on the cluster analysis have been proposed for regionalization of watersheds. The proposed algorithms can be applied to the feature vectors corresponding to the gauged and ungauged watersheds simultaneously. The algorithms were applied to the data related to the Karun-e-Bozorg basin in Iran. The results showed that joining a flood statistic with an appropriate weight to the feature vectors used in regionalization may improve the results of regionalization according to the number of the watersheds assigned to the homogeneous regions. Also, the proposed regionalization algorithms can increase the number of watersheds assigned to the homogeneous regions noticeably.