Literature DB >> 30171327

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

John P Lovette1, Jonathan M Duncan2, Lindsey S Smart3, John P Fay4, Lydia P Olander5, Dean L Urban4, Nancy Daly6,7, Jamie Blackwell7, Anne B Hoos8, Ana María García9, Lawrence E Band10,11.   

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.

Entities:  

Keywords:  Catchment; Restoration; Watershed approach; Watershed function

Mesh:

Substances:

Year:  2018        PMID: 30171327     DOI: 10.1007/s00267-018-1100-z

Source DB:  PubMed          Journal:  Environ Manage        ISSN: 0364-152X            Impact factor:   3.266


  10 in total

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Journal:  Environ Sci Pollut Res Int       Date:  2003       Impact factor: 4.223

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Journal:  Proc Natl Acad Sci U S A       Date:  2004-09-21       Impact factor: 11.205

3.  Ecology. Synthesizing U.S. river restoration efforts.

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Journal:  Science       Date:  2005-04-29       Impact factor: 47.728

4.  Loose-coupling a cellular automaton model and GIS: long-term urban growth prediction for San Francisco and Washington/Baltimore.

Authors:  K C Clarke; L J Gaydos
Journal:  Int J Geogr Inf Sci       Date:  1998 Oct-Nov       Impact factor: 4.186

5.  The emergence of land change science for global environmental change and sustainability.

Authors:  B L Turner; Eric F Lambin; Anette Reenberg
Journal:  Proc Natl Acad Sci U S A       Date:  2007-12-19       Impact factor: 11.205

Review 6.  Global consequences of land use.

Authors:  Jonathan A Foley; Ruth Defries; Gregory P Asner; Carol Barford; Gordon Bonan; Stephen R Carpenter; F Stuart Chapin; Michael T Coe; Gretchen C Daily; Holly K Gibbs; Joseph H Helkowski; Tracey Holloway; Erica A Howard; Christopher J Kucharik; Chad Monfreda; Jonathan A Patz; I Colin Prentice; Navin Ramankutty; Peter K Snyder
Journal:  Science       Date:  2005-07-22       Impact factor: 47.728

Review 7.  Chesapeake Bay eutrophication: scientific understanding, ecosystem restoration, and challenges for agriculture.

Authors:  D F Boesch; R B Brinsfield; R E Magnien
Journal:  J Environ Qual       Date:  2001 Mar-Apr       Impact factor: 2.751

8.  Establishing aquatic restoration priorities using a watershed approach.

Authors:  B A Bohn; J L Kershner
Journal:  J Environ Manage       Date:  2002-04       Impact factor: 6.789

9.  A Regional Modeling Framework of Phosphorus Sources and Transport in Streams of the Southeastern United States.

Authors:  Ana María García; Anne B Hoos; Silvia Terziotti
Journal:  J Am Water Resour Assoc       Date:  2011-10

10.  The southern megalopolis: using the past to predict the future of urban sprawl in the Southeast U.S.

Authors:  Adam J Terando; Jennifer Costanza; Curtis Belyea; Robert R Dunn; Alexa McKerrow; Jaime A Collazo
Journal:  PLoS One       Date:  2014-07-23       Impact factor: 3.240

  10 in total
  1 in total

1.  Identifying corridors of river recovery in coastal NSW Australia, for use in river management decision support and prioritisation systems.

Authors:  Danelle Agnew; Kirstie Fryirs
Journal:  PLoS One       Date:  2022-06-23       Impact factor: 3.752

  1 in total

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