Monitoring Greenhouse Gas Flux and Soil Moisture in the Great Dismal Swamp National Wildlife Refuge
Date
2020
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
This dissertation seeks to quantify the relationships between soil carbon gas flux, surface soil moisture and forest class in the Great Dismal Swamp, and to map these variables by combining satellite remote sensing and in situ measurements with model simulation. Forest type classification is done using freely available multispectral and synthetic aperture radar data combined with ground sampling. This study finds a 79% accurate classification of six classes of interest (maple-gum, Atlantic white cedar, pocosin, cypress, open water and disturbed habitat) using multispectral bands combined with the Normalized Difference Vegetation Index (NDVI). Two years of monthly carbon dioxide and methane flux were measured in nine sites across three forest types (maple-gum, Atlantic white cedar and pocosin) along with temperature and soil moisture. On average, as soil moisture increased by 1 unit of soil moisture content, CH4 flux increased by 457 g CH4-C/m2/hr. On average, as soil temperature increased by 1C, CO2 flux increased by 5,109 g CO2-C/m2/hr. The total area of Atlantic white cedar in the study boundary has an average yearly flux of 8.6 metric tons (t) of carbon from CH4 and 3,270 t of carbon from CO2; maple-gum has an average yearly flux of 923 t of carbon from CH4 and 59,843 t of carbon from CO2; pocosin has an average yearly flux of 431 t of carbon from CH4 and 15,899 t of carbon from CO2. Total Cha-1yr-1 ranged from 1,845 kg of Cha-1yr-1 in maple-gum to 2,024 kg Cha-1yr-1 for Atlantic white cedar. The driest sites lost the most carbon (up to 817 g C/m2/y), while the wettest sites lost the least (down to 575 g C/m2/y). These results show that soil carbon gas flux depends on soil moisture, temperature and forest type, which are all affected by anthropogenic activities in these peatlands. Soil moisture from 0-5 cm was a better fit with CH4 flux than soil moisture 5-10 cm. Satellite data products were derived from Sentinel-1 C-band synthetic aperture radar (SAR). For validating the satellite surface soil moisture data products, ground measurements were taken on three dates at 9 sites and include: surface soil moisture content, litter moisture content, soil density, aboveground biomass density, and forest type. The results indicate that up to 38% of the variation in backscatter values is explained by biomass, soil density, and surface litter moisture. Despite biomass reducing SAR interaction with the soil, we found it is still possible to model surface soil moisture. Given the ability to measure surface soil moisture and forest class using multispectral and synthetic aperture radar data, as well as the relationships derived from the ground sampling of greenhouse gas flux, it is possible to estimate total soil carbon gas flux over the Great Dismal Swamp. This has implications for management of the Great Dismal Swamp and other forested peat wetlands, as well as other similar ecosystems globally. The major contributions of this study include the relationships between: multispectral data and ground measurements of forest type; soil carbon gas flux, soil temperature and soil moisture; and synthetic aperture radar and soil moisture, as well as the methods for measuring these relationships and monitoring conditions in the Great Dismal Swamp in the future. Remote sensing of soil carbon gas is one important application of mapping surface soil moisture, which itself is essential for mapping of soil carbon gas flux.