Leveraging Big Data Towards Functionally-Based, Catchment Scale Restoration Prioritization

Lovette, John P.; Duncan, Jonathan M.; Smart, Lindsey S.; Fay, John P.; Olander, Lydia P.; Urban, Dean L.; Daly, Nancy; Blackwell, Jamie; Hoos, Anne B.; García, Ana María; Band, Lawrence E.

doi:10.1007/s00267-018-1100-z

Published: 31 August 2018

Leveraging Big Data Towards Functionally-Based, Catchment Scale Restoration Prioritization

John P. Lovette ORCID: orcid.org/0000-0001-7530-4656¹,
Jonathan M. Duncan²,
Lindsey S. Smart³,
John P. Fay⁴,
Lydia P. Olander⁵,
Dean L. Urban⁴,
Nancy Daly^6,7,
Jamie Blackwell⁷,
Anne B. Hoos⁸,
Ana María García⁹ &
Lawrence E. Band^10,11

Environmental Management volume 62, pages 1007–1024 (2018)Cite this article

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Abstract

The persistence of freshwater degradation has necessitated the growth of an expansive stream and wetland restoration industry, yet restoration prioritization at broad spatial extents is still limited and ad-hoc restoration prevails. The River Basin Restoration Prioritization tool has been developed to incorporate vetted, distributed data models into a catchment scale restoration prioritization framework. Catchment baseline condition and potential improvement with restoration activity is calculated for all National Hydrography Dataset stream reaches and catchments in North Carolina and compared to other catchments within the river subbasin to assess where restoration efforts may best be focused. Hydrologic, water quality, and aquatic habitat quality conditions are assessed with peak flood flow, nitrogen and phosphorus loading, and aquatic species distribution models. The modular nature of the tool leaves ample opportunity for future incorporation of novel and improved datasets to better represent the holistic health of a watershed, and the nature of the datasets used herein allow this framework to be applied at much broader scales than North Carolina.

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Acknowledgements

This project was funded by the North Carolina Department of Natural Resources, Ecosystem Enhancement Program. We would like to thank two anonymous reviewers for their helpful contributions to this manuscript, as well as Steve Preston and Chad Wagner of USGS for their review comments. We would also like to thank staff at NC DEQ for their guidance in developing, implementing, and continuing to improve this tool.

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Affiliations

Department of Geography, University of North Carolina, Chapel Hill, NC, USA
John P. Lovette
Department of Ecosystem Science and Management, Pennsylvania State University, State College, PA, USA
Jonathan M. Duncan
Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, USA
Lindsey S. Smart
Nicholas School of the Environment, Duke University, Durham, NC, USA
John P. Fay & Dean L. Urban
Nicholas Institute for Environmental Policy Solutions, Duke University, Durham, NC, USA
Lydia P. Olander
Wake County Department of Environmental Services, Raleigh, NC, USA
Nancy Daly
North Carolina Department of Environmental Quality, Division of Mitigation Services, Raleigh, NC, USA
Nancy Daly & Jamie Blackwell
U.S. Geological Survey, Lower Mississippi-Gulf Water Science Center, Nashville, TN, USA
Anne B. Hoos
U.S. Geological Survey, South Atlantic Water Science Center, Raleigh, NC, USA
Ana María García
Department of Environmental Sciences, University of Virginia, Charlottesville, VA, USA
Lawrence E. Band
Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA, USA
Lawrence E. Band

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John P. Lovette
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Jonathan M. Duncan
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Lindsey S. Smart
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John P. Fay
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Lydia P. Olander
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Dean L. Urban
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Nancy Daly
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Jamie Blackwell
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Anne B. Hoos
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Ana María García
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Lawrence E. Band
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Lovette, J.P., Duncan, J.M., Smart, L.S. et al. Leveraging Big Data Towards Functionally-Based, Catchment Scale Restoration Prioritization. Environmental Management 62, 1007–1024 (2018). https://doi.org/10.1007/s00267-018-1100-z

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Received: 21 August 2017
Accepted: 21 August 2018
Published: 31 August 2018
Issue Date: December 2018
DOI: https://doi.org/10.1007/s00267-018-1100-z

Keywords

Restoration
Watershed approach
Catchment
Watershed function