Jointly using multiple datasets helps to better estimate the organic carbon content.
The project developed and tested a novel inversion scheme that can flexibly use single or multiple datasets including soil liquid water content, temperature, and electrical resistivity tomography (ERT) data to estimate the vertical distribution of organic carbon content and its associated uncertainty in the Arctic tundra. The results show that jointly using multiple datasets helps to better estimate the organic carbon content, especially at the active layer.
Quantitative characterization of soil organic carbon (SOC) content is essential due to its significant impacts on surface-subsurface hydrological-thermal processes and microbial decomposition of organic carbon, which both in turn are important for predicting carbon-climate feedbacks. The scientists present a novel approach to estimate this soil property and its impacts on a hydrological-thermal regime including the freeze-thaw transition in the Arctic tundra based on observations of soil moisture, soil temperature, and electrical resistivity data.
This study developed and tested a novel approach to estimating SOC content using inverse modeling that can incorporate diverse hydrological, thermal, and ERT datasets. In addition, the study permitted exploration of surface-subsurface hydrological-thermal dynamics and spatiotemporal variations associated with freeze-thaw transitions. Given the importance of characterizing organic carbon content as part of ecosystem and climate studies, the typical challenges associated with collecting and analyzing “sufficient” core data to characterize the vertical and horizontal variability of organic carbon associated with a field study site, and the increasing use of electrical resistivity data to characterize vertical, horizontal, and temporal variability in shallow systems, the new inversion approach offers significant potential for improved characterization of organic carbon content over field-relevant conditions and scales. It also offers significant potential for improving the understanding of hydrological-thermal behavior of naturally heterogeneous permafrost systems.
BER Program Manager
Terrestrial Ecosystem Science, SC-23.1
Earth & Environmental Sciences
Lawrence Berkeley National Laboratory
firstname.lastname@example.org (510-486-5266, Fax: 510-486-5686)
The Next-Generation Ecosystem Experiments (NGEE)–Arctic project is supported by the Office of Biological and Environmental Research within the U.S. Department of Energy Office of Science. This NGEE-Arctic research is supported through Contract No. DE-AC02-05CH11231 to Lawrence Berkeley National Laboratory.
Tran, A.P., B. Dafflon, and S.S. Hubbard. “Coupled land surface-subsurface hydrogeophysical inverse modeling to estimate soil organic carbon content and explore associated hydrological and thermal dynamics in the Arctic tundra.” The Cryosphere 11(5), 2089–2109 (2017). [DOI:10.5194/tc-11-2089-2017].
SC-33.1 Earth and Environmental Sciences Division, BER
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