Large wood in low-gradient floodplain rivers: Spatial distribution, physical controls, and geomorphic effects

Information

  • NSF Award
  • 2112642
Owner
  • Award Id
    2112642
  • Award Effective Date
    6/15/2021 - 3 years ago
  • Award Expiration Date
    5/31/2024 - 27 days ago
  • Award Amount
    $ 353,216.00
  • Award Instrument
    Standard Grant

Large wood in low-gradient floodplain rivers: Spatial distribution, physical controls, and geomorphic effects

This project will advance understanding of the dynamics of large wood (LW) in Coastal Plain rivers of the Southeastern US. LW (logs within rivers) provides many benefits, affecting the transport of sediment, the form of river channels, and the functioning of aquatic ecosystems. Most previous research on LW has been conducted in small streams, often in mountainous regions, or in gravel-bedded rivers. This project will examine the distribution, mobility, and effects of LW in relatively large, gently sloped, and fine-bedded rivers of the Coastal Plain. The results will have implications for forest and river management in this region, where LW was once abundant but has been reduced because of human activities. The project will also provide benefits in terms of student training and in educating the public about the benefits of LW through a new citizen-science initiative that will be implemented in collaboration with Riverkeeper organizations across North Carolina.<br/><br/>The proposed research seeks to characterize the spatial distribution of large wood (LW) in low-gradient floodplain rivers, the physical controls on LW recruitment and transport, and the effects of LW on channel process and form. LW (generally defined as pieces of wood at least 1 m in length and 10 cm in diameter, located in the active channel) has long been recognized as a significant driver of physical and ecological processes in river systems. Nevertheless, most knowledge of LW in rivers is based on studies of small to medium-sized rivers in steep headwater catchments, such as in the mountains of the western United States. There is therefore a need for a systematic analysis of LW dynamics and their influence on geomorphic processes in low-gradient floodplain rivers. The research will investigate the spatial distribution of LW at reach and regional scales through field measurements and remote sensing, the physical controls on LW recruitment through statistical modeling, LW transport through episodic and continuous tracking, and the effects of LW on channel process and form and the physical drivers of those effects through physically based modeling. The results will contribute to the understanding of coupled physical and ecological dynamics in river systems. Broader impacts include training of students at a Minority Serving Institution, dissemination of research results to state land- and water-management agencies, and a new citizen-science initiative to collect data on LW in rivers and to educate the public about the benefits of LW.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

  • Program Officer
    Justin Lawrencejlawrenc@nsf.gov7032922425
  • Min Amd Letter Date
    6/21/2021 - 3 years ago
  • Max Amd Letter Date
    6/21/2021 - 3 years ago
  • ARRA Amount

Institutions

  • Name
    University of North Carolina Greensboro
  • City
    Greensboro
  • State
    NC
  • Country
    United States
  • Address
    1111 Spring Garden Street
  • Postal Code
    274125013
  • Phone Number
    3363345878

Investigators

  • First Name
    Derek
  • Last Name
    Martin
  • Email Address
    martindj1@appstate.edu
  • Start Date
    6/21/2021 12:00:00 AM
  • First Name
    Sarah
  • Last Name
    Praskievicz
  • Email Address
    sjpraski@uncg.edu
  • Start Date
    6/21/2021 12:00:00 AM

Program Element

  • Text
    Special Initiatives
  • Code
    1642
  • Text
    Geomorphology & Land-use Dynam
  • Code
    7458

Program Reference

  • Text
    COVID-Disproportionate Impcts Inst-Indiv