Modeling the impacts of hydrology and management on carbon balance at the Great Dismal Swamp, Virginia and North Carolina, USA

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Edited by: Ken W. KraussZhiliang Zhu, and Camille L. Stagg

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Abstract

The impact of drainage on the stability of peatland carbon sinks is well known; however, much less is understood regarding the way active management of the water-table affects carbon balance. In this study, we determined the carbon balance in the Great Dismal Swamp, a large, forested peatland in the southeastern USA, which has been drained for over two hundred years and is now being restored through hydrologic management. We modeled future net ecosystem carbon balance over 100 years (2012 to 2112) using in situ field observations paired with simulations of water-table depth. The three scenarios used in the model were baseline conditions, flooded/wet conditions, and drained/dry conditions, which represent a range of potential management actions and climate conditions at the Great Dismal Swamp. In the Baseline scenario, results show a carbon sink of 0.7 Tg, or an average annual rate of 0.23 Mg C/ha/yr. The Flooded/Wet scenario produced a net ecosystem carbon balance of 4.6 Tg C or an average annual rate of 1.06 Mg C/ha/yr. For the Drained/Dry scenario, under which no management was conducted, and typically dry conditions were assumed, the Great Dismal Swamp becomes a net carbon source at –2.07 Tg C or an average annual rate of –0.38 Mg C/ha/yr.

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Publication type Book chapter
Publication Subtype Book Chapter
Title Modeling the impacts of hydrology and management on carbon balance at the Great Dismal Swamp, Virginia and North Carolina, USA
Chapter 21
DOI 10.1002/9781119639305.ch21
Year Published 2021
Language English
Publisher American Geophysical Union
Contributing office(s) WMA - Observing Systems Division
Description 18 p.
Larger Work Type Book
Larger Work Subtype Monograph
Larger Work Title Wetland carbon and environmental management
First page 385
Last page 402
Country United States
State North Carolina, Virginia
Other Geospatial Great Dismal Swamp
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