Technical Papers
Apr 27, 2013

Catchment Classification Framework in Hydrology: Challenges and Directions

Publication: Journal of Hydrologic Engineering
Volume 20, Issue 1

Abstract

The past few decades have witnessed the development of numerous catchment models, often with increasing structural complexity and mathematical sophistication. While such models have certainly provided a better understanding of catchments and associated processes, they are also often catchment-specific, region-specific, or process-specific. Serious concerns on this modeling trend have been increasingly raised in recent times and, consequently, the need for a generic catchment classification framework in hydrology has been emphasized. There have indeed been some attempts to advance the idea of such a classification framework. Such studies have investigated different ways of developing a framework, including river morphology, river regimes, hydroclimatic factors, landscape and land use parameters, hydrologic similarity indexes, hydrologic signatures, ecohydrologic factors, geostatistical properties, entropy, nonlinear and chaotic properties, data mining, and other relevant characteristics and methods. Although useful in their own ways, these studies are largely inadequate for a generic classification framework. In addition to the limitations that exist in each of the different forms, a coherent effort to bring these disparate forms together for a workable classification is also missing. This study highlights the challenges that the existing approaches pose in the development of a generic classification framework. It argues for an appropriate basis, a suitable methodology, and key components for such a framework. In particular, it discusses the vital role of system complexity as an appropriate basis for the classification framework and the potential of nonlinear dynamics, networks, and other modern concepts of complex systems science for assessing system complexity. The study also offers a three-step procedure for formulation and verification of a catchment classification framework.

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Acknowledgments

This work was financially supported by the Australian Research Council (ARC). B. Sivakumar acknowledges the support from ARC through the Future Fellowship grant (FT110100328). R. Berndtsson acknowledges the support from the MECW project at the Center for Middle Eastern Studies at Lund University. The authors thank the three reviewers for their constructive comments and useful suggestions.

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 20Issue 1January 2015

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Received: Nov 8, 2012
Accepted: Apr 25, 2013
Published online: Apr 27, 2013
Discussion open until: Nov 2, 2014
Published in print: Jan 1, 2015

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Bellie Sivakumar, M.ASCE [email protected]
Associate Professor and Australian Research Council (ARC) Future Fellow, School of Civil and Environmental Engineering, Univ. of New South Wales, Sydney, NSW 2052, Australia (corresponding author). E-mail: [email protected]
Vijay P. Singh, F.ASCE [email protected]
Caroline & William N. Lehrer Distinguished Chair in Water Engineering and Professor, Dept. of Biological and Agricultural Engineering and Dept. of Civil and Environmental Engineering, Texas A&M Univ., College Station, TX 77843-2117. E-mail: [email protected]
Ronny Berndtsson [email protected]
Professor, Center for Middle Eastern Studies and Dept. of Water Resources Engineering, Lund Univ., P.O. Box 118, S-22100 Lund, Sweden. E-mail: [email protected]
Shakera K. Khan [email protected]
Ph.D. Student, School of Civil and Environmental Engineering, Univ. of New South Wales, Sydney, NSW 2052, Australia. E-mail: [email protected]

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