A comparison of similarity indices for catchment classification using a cross-regional dataset

Genevieve Ali, Doerthe Tetzlaff, Christopher Soulsby, Jeffery McDonnell, Rene Capell

Research output: Contribution to journalArticlepeer-review

80 Citations (Scopus)


While there is currently much research activity on catchment classification, there is no agreement on relevant measures of catchment similarity. Here we investigate whether the use of different catchment characteristics as similarity measures leads to convergent catchment classification results. We fed a clustering algorithm called affinity propagation (AP) with different combinations of catchment forcing, form and function indicators collected over 36 Scottish sites (0.44–1712.10 km2). The AP algorithm was effective in determining the optimal number of groups needed to capture the most variability in each combination of variables. Catchment groupings obtained using physical properties only did not match those obtained using flow indices, mean transit times or storage estimates. The lack of correlation between flow-derived indicators and physical indicators was a surprising result. The combination of data which best approximated the interactions between catchment structural and functional properties included only topographic characteristics, soil properties and mean transit time estimates.
Original languageEnglish
Pages (from-to)11-22
Number of pages12
JournalAdvances in Water Resources
Issue number-
Early online date3 Feb 2012
Publication statusPublished - May 2012


  • catchment classification
  • catchment forcing
  • catchment form
  • catchment function
  • affinity propagation
  • Scotland


Dive into the research topics of 'A comparison of similarity indices for catchment classification using a cross-regional dataset'. Together they form a unique fingerprint.

Cite this