Application of Clustering Techniques Using Prioritized Variables in Regional Flood Frequency Analysis—Case Study of Mahanadi Basin

The selection of suitable site characteristics and the number of clusters play an important role for finding homogeneous regions in regional flood frequency analysis. The present study investigates the partition of the Mahanadi basin into homogeneous regions by applying different clustering techniques by using fewer but influential variables. As such, the entire basin is not hydrometeorologically homogeneous. Principal component analysis has been initiated in finding appropriate site characteristics (variables) as per priority. Out of seven variables, four variables are selected on priority. Possible numbers of cluster are found by applying the Kohonen self-organization map and Andrews plot. Other clustering techniques, such as hierarchical clustering fuzzy C-mean (FCM) and K -mean, are applied on prioritized variables to verify the result of clustering. The intercomparison of clustering techniques gives the optimum number of sites to be placed in a particular cluster. The sites clustered as per FCM give ...