Get access



Correspondence to: T. Snelder, NIWA, National Institute of Water and Atmospheric Research, Christchurch, New Zealand.



The correspondence and performance of six classifications of flow regimes of New Zealand rivers that were all mapped onto the same digital river network were assessed. Classification 1 was defined deductively, based on expert-defined rules. Classifications 2 to 6 were defined inductively using hydrological indices calculated from 321 natural daily flow records. Classifications 2 to 4 were defined by first clustering the gauges based on the hydrological indices and then predicting the class of each segment of the network using a Random Forest classifier. Classifications 5 and 6 were defined by first predicting the indices for each segment of the network using Random Forest regression models. Cluster analysis was then used to group the network segments into classes. Further differences between classifications were due to differences in the standardisation of the hydrological indices and clustering algorithms. Correspondence (extent to which the patterns defined by the classifications were similar) was assessed formally using the adjusted Rand index and visually. The performance of the classifications was assessed using classification strength calculated using the hydrological indices and ANOVA calculated for individual indices. Correspondence between the classifications was low (adjusted Rand index range, 0.1–0.5). Classification strength and ANOVA statistics assessed using cross validation indicated that the inductive classifications performed better than the deductively defined classification and that there were some significant differences in performance between the inductive classifications. However, these differences were not large from a practical point of view. Our results indicate that there are many credible classifications of the flow regimes of a study region. When considering methods for defining flow regime classifications, aspects other than the predictive performance, such as flow data requirements and how easily the final classification can be explained, should be considered. Copyright © 2012 John Wiley & Sons, Ltd.

Get access to the full text of this article