The identification of conceptual hydrological models for surface water acidification

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Abstract
Ambiguity in parameter identification represents a potentially serious limitation to the application of models of surface water acidification. Previous work has concentrated on manipulation of two of the three factors affecting model identifiability, namely model structure and estimator properties. A new technique is proposed which uses different modes of response within the data to improve parameter identification. Preliminary results, obtained using the Birkenes model of surface water acidification, appear to show promise. The technique is robust in recovering model parameters from synthetic data, with and without error, and in assimilating problems of structural error.