Articles | Volume 15, issue 9
Hydrol. Earth Syst. Sci., 15, 2947–2962, 2011

Special issue: Catchment classification and PUB

Hydrol. Earth Syst. Sci., 15, 2947–2962, 2011

Research article 16 Sep 2011

Research article | 16 Sep 2011

Catchment classification by runoff behaviour with self-organizing maps (SOM)

R. Ley1, M. C. Casper1, H. Hellebrand2, and R. Merz3 R. Ley et al.
  • 1University of Trier, Forschungszentrum für Regional- und Umweltstatistik, Trier, Germany
  • 2Hydrosol, Technologie Zentrum Trier, Trier, Germany
  • 3Helmholtz Centre for Environmental Research, Department of Catchment Hydrology, Halle, Germany

Abstract. Catchments show a wide range of response behaviour, even if they are adjacent. For many purposes it is necessary to characterise and classify them, e.g. for regionalisation, prediction in ungauged catchments, model parameterisation.

In this study, we investigate hydrological similarity of catchments with respect to their response behaviour. We analyse more than 8200 event runoff coefficients (ERCs) and flow duration curves of 53 gauged catchments in Rhineland-Palatinate, Germany, for the period from 1993 to 2008, covering a huge variability of weather and runoff conditions. The spatio-temporal variability of event-runoff coefficients and flow duration curves are assumed to represent how different catchments "transform" rainfall into runoff. From the runoff coefficients and flow duration curves we derive 12 signature indices describing various aspects of catchment response behaviour to characterise each catchment.

Hydrological similarity of catchments is defined by high similarities of their indices. We identify, analyse and describe hydrologically similar catchments by cluster analysis using Self-Organizing Maps (SOM). As a result of the cluster analysis we get five clusters of similarly behaving catchments where each cluster represents one differentiated class of catchments.

As catchment response behaviour is supposed to be dependent on its physiographic and climatic characteristics, we compare groups of catchments clustered by response behaviour with clusters of catchments based on catchment properties. Results show an overlap of 67% between these two pools of clustered catchments which can be improved using the topologic correctness of SOMs.