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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #373261

Research Project: Improving Agroecosystem Services by Measuring, Modeling, and Assessing Conservation Practices

Location: Hydrology and Remote Sensing Laboratory

Title: Modeling sediment diagenesis processes on riverbed to better quantify aquatic carbon fluxes and stocks in a small watershed of the mid-Atlantic region

Author
item QI, J. - University Of Maryland
item ZHANG, X - Global Change Research Institute
item LEE, S. - University Of Maryland
item WU, Y. - Jiaotong University
item Moglen, Glenn
item McCarty, Gregory

Submitted to: Carbon Balance and Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/23/2020
Publication Date: 7/6/2020
Citation: Qi, J., Zhang, X., Lee, S., Wu, Y., Moglen, G.E., McCarty, G.W. 2020. Modeling sediment diagenesis processes on riverbed to better quantify aquatic carbon fluxes and stocks in a small watershed of the mid-Atlantic region. Carbon Balance and Management. 15:13. https://doi.org/10.1186/s13021-020-00148-1.
DOI: https://doi.org/10.1186/s13021-020-00148-1

Interpretive Summary: Despite the widely recognized importance of aquatic processes for bridging gaps in the global carbon cycle, there is still a lack of understanding of the role of riverbed processes for carbon flows and stocks in aquatic environments. The USDA Soil Water Assessment Tool (SWAT) model was modified to include two new modules that capture sediment dynamics for particulate and dissolved organic carbon. The revised model was tested on a four year observational dataset in a US mid-Atlantic watershed. The new modules showed good agreement with observations and emphasize the importance of modeling these dynamics so that carbon fluxes and stocks are properly understood at the watershed scale. Findings from the revised SWAT model are useful to inform ecosystem services for watershed assessment and planning.

Technical Abstract: Background Despite the widely recognized importance of aquatic processes for bridging gaps in the global carbon cycle, there is still a lack of understanding of the role of riverbed processes for carbon flows and stocks in aquatic environments. Here, we added a sediment diagenesis and sediment carbon (C) resuspension module into the SWAT-C model and tested it for simulating both particulate organic C (POC) and dissolved organic C (DOC) fluxes across four years of monthly observations (2014-2017) in the Tuckahoe watershed (TW) in the U.S. Mid-Atlantic region. Results Sensitivity analyses show that parameters that regulate POC deposition in river networks are more sensitive than those that determine C resuspension from sediments. Further analyses indicate that allochthonous contributions to POC and DOC are, respectively, about 36.6 and 46 kgC ha-1 year-1¬, while autochthonous contributions are less than 0.72 kgC ha-1 year-1 for both POC and DOC (less than 2% of allochthonous sources). The net deposition of POC on the riverbed (i.e., 11.4 kgC ha-1 year-1) retained ca. 31% of terrestrial inputs of POC. In addition, average annual buried C was 0.34 kgC ha-1 year-1, accounting for only 1% of terrestrial POC inputs or 3% of net POC deposition. The results indicate that about 79% of deposited organic C were converted to inorganic C (CH4 and CO2) in the sediment and eventually released into the overlying water column. Conclusion This study serves as an exploratory study on estimation of C fluxes from terrestrial to aquatic environments at the watershed scale. We demonstrated capabilities of the SWAT-C model to simulate C cycling from uplands to riverine ecosystems and estimate C sinks and sources in aquatic environments. Overall, the results highlight the importance of including carbon cycle dynamics within the riverbed in order to accurately estimate aquatic carbon fluxes and stocks. Additionally, new capabilities serve as a useful tool to account for those processes in watershed C assessment.