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

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

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)1007-1024
Number of pages18
JournalEnvironmental Management
Volume62
Issue number6
DOIs
StatePublished - Dec 1 2018

Fingerprint

prioritization
Catchments
Restoration
catchment
Rivers
baseline conditions
hydrography
Wetlands
habitat quality
restoration
Big data
Watersheds
Water quality
Data structures
Phosphorus
persistence
river basin
wetland
Health
watershed

All Science Journal Classification (ASJC) codes

  • Global and Planetary Change
  • Ecology
  • Pollution

Cite this

Lovette, J. P., Duncan, J., Smart, L. S., Fay, J. P., Olander, L. P., Urban, D. L., ... Band, L. E. (2018). Leveraging Big Data Towards Functionally-Based, Catchment Scale Restoration Prioritization. Environmental Management, 62(6), 1007-1024. https://doi.org/10.1007/s00267-018-1100-z
Lovette, John P. ; Duncan, Jonathan ; 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. / Leveraging Big Data Towards Functionally-Based, Catchment Scale Restoration Prioritization. In: Environmental Management. 2018 ; Vol. 62, No. 6. pp. 1007-1024.
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Lovette, JP, Duncan, J, Smart, LS, Fay, JP, Olander, LP, Urban, DL, Daly, N, Blackwell, J, Hoos, AB, García, AM & Band, LE 2018, 'Leveraging Big Data Towards Functionally-Based, Catchment Scale Restoration Prioritization', Environmental Management, vol. 62, no. 6, pp. 1007-1024. https://doi.org/10.1007/s00267-018-1100-z

Leveraging Big Data Towards Functionally-Based, Catchment Scale Restoration Prioritization. / Lovette, John P.; Duncan, Jonathan; 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.

In: Environmental Management, Vol. 62, No. 6, 01.12.2018, p. 1007-1024.

Research output: Contribution to journalArticle

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