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Hydrological Catchment Classification Using a Data-Based Mechanistic Strategy

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System Identification, Environmental Modelling, and Control System Design

Abstract

Catchment classification remains a significant challenge for hydrologists, with available schemes not providing a sufficient basis for consistently distinguishing between different types of hydrological behavior. We analyze 278 catchments distributed across the Eastern USA using a data-based mechanistic (DBM) strategy. We attempt to understand the catchment similarity that can be found with respect to both model parameters (if the same model structure is applied) and with respect to model structures identified as most suitable. Finally, we relate the identified structures and parameters to available physical and climatic catchment-scale characteristics to see whether a further generalization of our result is possible. A significant regional pattern emerged, reflecting the influences of aridity, elevation (steepness) and temperature. In terms of parameter estimates, the most interesting variability between catchments is seen in the response nonlinearity. Significant regional patterns in the non-linearity parameters emerged, and reasonable physical explanations were proposed. Overall, the results of our preliminary study provided here give the impression that the DBM method could be fruitfully applied towards the objective of catchment classification.

‘In plain words, Chaos was the law of nature; Order was the dream of man.’ Henry Adams (1918)

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Acknowledgements

We would like to thank Prof. Peter Young for supporting both of us since we first met while we were PhD students. His inquisitive nature, his openness and his friendly nature provided a great example to us. We’d like to thank the Symposium organizers and the editors of this book. Thanks to Keith Sawicz for producing Fig. 23.1. Partial funding to TW was provided by an EPA STAR Early Career Award. The CAPTAIN toolbox (www.es.lancs.ac.uk/cres/captain) was used under license from Lancaster University.

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Authors and Affiliations

  1. Department of Civil and Environmental Engineering, The Pennsylvania State University, University Park, PA, 16802, USA

    Thorsten Wagener

  2. Department of Civil and Environmental Engineering, Imperial College London, London, SW72AZ, UK

    Neil McIntyre

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  1. Thorsten Wagener
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  2. Neil McIntyre
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Correspondence to Thorsten Wagener .

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Editors and Affiliations

  1. Computer Engineering, RMIT University, Swanston Street 10, Melbourne, 3000, Victoria, Australia

    Liuping Wang

  2. Centre de Recherche en, Automatique de Nancy, Université Nancy I, Vandoeuvre-les-Nancy CX, France

    Hugues Garnier

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Wagener, T., McIntyre, N. (2012). Hydrological Catchment Classification Using a Data-Based Mechanistic Strategy. In: Wang, L., Garnier, H. (eds) System Identification, Environmental Modelling, and Control System Design. Springer, London. https://doi.org/10.1007/978-0-85729-974-1_23

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  • DOI: https://doi.org/10.1007/978-0-85729-974-1_23

  • Publisher Name: Springer, London

  • Print ISBN: 978-0-85729-973-4

  • Online ISBN: 978-0-85729-974-1

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