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

R Ley,R Merz,H Hellebrand,M C Casper

doi:10.5194/hess-15-2947-2011

Abstract

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.

Highlights

An important task of science in any particular field is to “perpetually organize a body of knowledge gained by scientific inquiry” (Wagener et al, 2007)
There is a large variability in the Event Runoff Coefficients (ERCs)
The 18 selected catchments represent a wide range of catchment behaviour and show differences of ERC between catchments

Summary

Introduction

An important task of science in any particular field is to “perpetually organize a body of knowledge gained by scientific inquiry” (Wagener et al, 2007) Classification groups together those systems that are similar, limiting the variability within classes (McDonnell and Woods, 2004). Hall and Minns (1999) demonstrated that Representative Regional Catchments (RRC) whose characteristics are hydrologically more appealing than geographical proximity might define classes. They employed techniques like Kohonen networks and fuzzy c-means, which are straightforward in application and were found to identify broadly similar RRCs. ERCs are highly correlated with mean annual precipitation, but poorly with soil type and land use. Oudin et al (2010) defined similarity of catchments on the basis of model parameter transferability and compared them with a pool of apparently physically similar catchments

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Conclusion