Coupled Hydrogeophysical Inversion to Estimate Soil Organic Carbon Content in the Arctic Tundra
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 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.
sshubbard@lbl.gov
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). https://doi.org/10.5194/tc-11-2089-2017.