Estimating Carbon Fluxes using Remotely Sensed River Discharge
Jaclyn Gehring, Northeastern University, gehring.j@northeastern.edu (Presenter)
Aron Stubbins, Northeastern University, aron.stubbins@northeastern.edu
Ed Beighley, Northeastern University, r.beighley@northeastern.edu
Claire G Griffin, Southern Oregon University, griffinc1@sou.edu
Robert G.M. Spencer, Florida State University, rgspencer@fsu.edu
Karen Frey, Clark University, kfrey@clarku.edu
The flux of riverine dissolved organic carbon is a critical component of the global carbon cycle. Current estimates are based on measuring these concentrations at gauged streamflow locations, allowing for the approximation of flux. Despite the significance of carbon transport through terrestrial and marine systems, there is a decline in global discharge information—thus limiting our knowledge of discharge and constituent fluxes to well-monitored locations. Recent advances in satellite observations provide alternative methods for estimating river discharge. Here, we use remotely-sensed estimates and in-situ measurements of discharge to determine the sensitivity of derived carbon fluxes. This project focuses on larger (> 50-100 m in width, such that they can be observed from space) rivers globally. The methods leveraged to estimate river discharge from remotely-sensed observations include: (1) Manning’s Equation forced with remotely-sensed, dynamic, estimates of water surface elevations (i.e., satellite altimetry), and (2) functional relationships between river discharge and GRACE/GRACE-FO Total Water Storage Anomalies (TWSA). State-of-the-science techniques (e.g., LOADEST and EGRET models) are used to predict the concentrations and fluxes of carbon provided measured or modeled discharge and sample data. The sensitivity of carbon flux is evaluated by comparing the measured flux of carbon (e.g., using in-situ discharge and DOC data) to the estimated fluxes (e.g., using remotely sensed discharges and DOC data). Preliminary results suggest that the use of remotely-sensed discharges may result in the underestimation of flux, as it is difficult to capture peak flow events due to the temporal sampling of remote sensing platforms. This research will enable the estimation of carbon fluxes from roughly 20% of global river basins which are currently unmonitored.
Associated Project(s):
Poster Location ID: 1-54
Presentation Type: Poster
Session: Poster Session 1
Session Date: Tue (May 9) 5:00-7:00 PM
CCE Program: OBB