Get access

A framework for hydrologic classification with a review of methodologies and applications in ecohydrology

Authors

  • Julian D. Olden,

    Corresponding author
    • School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, USA
    Search for more papers by this author
  • Mark J. Kennard,

    1. Tropical Rivers and Coastal Knowledge, National Environmental Research Program Northern Australia Hub and Australian Rivers Institute, Griffith University, Nathan, Queensland, Australia
    Search for more papers by this author
  • Bradley J. Pusey

    1. Tropical Rivers and Coastal Knowledge, National Environmental Research Program Northern Australia Hub and Australian Rivers Institute, Griffith University, Nathan, Queensland, Australia
    Search for more papers by this author

Julian D. Olden, School of Aquatic and Fishery Sciences, University of Washington, PO Box 355020 Seattle, WA 98195, USA.

E-mail: olden@u.washington.edu

ABSTRACT

Hydrologic classification is one of the most widely applied tasks in ecohydrology. During the last two decades, a considerable effort has gone into analysis and development of methodological approaches to hydrologic classification. We reviewed the process of hydrologic classification, differentiating between an approach based on deductive reasoning using environmental regionalization, hydrologic regionalization and environmental classification whereby environmental variables assumed to be key determinants of hydrology are analysed and one based on inductive reasoning using streamflow classification whereby hydrologic data are analysed directly. We explored past applications in ecohydrology, highlighting the utility of classifications in the extrapolation of hydrologic information across sparsely gauged landscapes, the description of spatial patterns in hydrologic variability, aiding water resource management, and in the identification and prioritization of conservation areas. We introduce an overarching methodological framework that depicts critical components of the classification process and summarize important advantages and disadvantages of commonly used statistical approaches to characterize and predict hydrologic classes. Our hope is that researchers and managers will be better informed when having to make decisions regarding the selection and proper implementation of methods for hydrologic classification in the future. Copyright © 2011 John Wiley & Sons, Ltd.

Ancillary