Optimization of a similarity measure for estimating ungauged streamflow

Abstract

One approach to predicting streamflow in an ungauged catchment is to select an ensemble of hydrological models previously identified for similar gauged catchments, where the similarity is based on some combination of important physical catchment attributes. The focus of this paper is the identification of catchment attributes and optimization of a similarity measure to produce the best possible ungauged streamflow predictions given a data set and a conceptual model structure. As a case study, the SimHyd rainfall-runoff model is applied to simulate monthly streamflow in 184 Australian catchments. Initial results show that none of 27 catchment attributes can be safely said to consistently give..