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Research article

Water-smart growth planning: linking water and land in the arid urbanizing American West

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Pages 1056-1072 | Received 23 Aug 2015, Accepted 20 May 2016, Published online: 26 Sep 2016
 

Abstract

Linking water and land is essential in planning for the future of the western United States. We propose the concept of ‘water-smart growth’ and explore its implications through incorporating water considerations into the SLEUTH land-use model. The urban growth trajectory in Cache County, Utah, is modeled from 2007 to 2030 under four different scenarios: current trend; smart growth; water-smart growth with moderate implementation; and water-smart growth with full implementation. Comparisons of simulation results illustrate the extent and ways in which water-smart growth would alter current established land-use growth patterns. The approach represents an initial step to better integrate land and water in urban growth modeling and planning. This study's purposes are to provide improved understanding and representation of linkages between water and land in urbanizing environments, offer insights from a set of modeled options, and demonstrate the significance of integrating land and water in planning practices.

Acknowledgements

This research was supported by NSF EPSCoR grant EPS 1208732 awarded to Utah State University, as part of the State of Utah Research Infrastructure Improvement Award. Additional support was provided by the Ecology Center at Utah State University in collaboration with the iUTAH EPSCoR Program. Any opinions, findings, and conclusions or recommendations expressed are those of the authors and do not necessarily reflect the views of the National Science Foundation. We thank two reviewers, Mark Brunson, Jeff Horsburgh, and Christopher Lant for reviewing an earlier version of the manuscript and for their insightful comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

NSF EPSCoR grant EPS 1208732; Ecology Center at Utah State University in collaboration with the iUTAH EPSCoR Program