I have several distributions (10 distributions in the figure below).
In fact these are histograms: there are 70 values on the x-axis which are the sizes of some particles in a solution and for each value of x the corresponding value of y is the proportion of particles whose size is around the value of x.
I would like to cluster these distributions. Currently I use a hierarchical clustering with the Euclidean distance for example. I am not satisfied by the choice of the distance. I have tried information-theoretic distance such as Kullback-Leibler but there are many zeros in the data and this causes difficulties. Do you have a proposal of an appropriate distance and/or another clustering method ?