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Inductive Modeling of Carbon Fluxes in Lakes and Reservoirs and Implications for the Global Carbon Cycle: Cory McDonald

Project Title: Inductive Modeling of Carbon Fluxes in Lakes and Reservoirs and Implications for the Global Carbon Cycle
Mendenhall Fellow: Cory McDonald, (303) 541-3056,
Duty Station: Boulder, CO
Start Date: October 25, 2010
Education: Ph.D., Environmental Engineering, Michigan Technological University (2010)
Research Advisor: Rob Striegl, (303) 541-3091,
Project Description: Current models of regional- to global-scale carbon cycling typically assume that the role of inland water bodies (lakes, ponds, and reservoirs) is negligible. However, only about half of the carbon delivered to these water bodies is exported to the oceans; the remainder is either buried in sediments or lost to the atmosphere as CO2 and CH4 (Cole and others, 2007). While lakes and reservoirs contain a relatively small volume of water and occupy a relatively small portion of the landscape, they represent “hot spots” for biogeochemical carbon cycling. Carbon burial in lakes and reservoirs is estimated to be several times larger than in the oceans (Downing and others, 2008; Dean and Gorham, 1998), and the amount of methane evasion from lakes is also likely greater than that from the oceans (Bastviken and others, 2004). Current large-scale estimates of net carbon fluxes and sequestration in inland waters are coarse, however, and a refined model of these systems is required.

Diagram showing major carbon fluxes in lakes and reservoirs   Figure 1. Major carbon fluxes in lakes and reservoirs: (1) air-water gas (CO2 and CH4) exchange, (2) surface water inflow plus atmospheric C inputs, (3) groundwater seepage (4) phytosynthetic uptake of dissolved inorganic carbon, (5) respiration, (6) settling of particulate organic carbon, (7) sediment C burial, (8) methane evasion, (9) calcification (biotic and abiotic), (10) tributary outflows, and (11) groundwater outflows.

A number of factors influence the amount of organic and inorganic carbon delivered to a given lake, including land use and land cover in the catchment and upstream, surface and groundwater hydrology, climate, and geomorphology. In-lake fate and transport processes are also regulated by many interrelated factors, including primary productivity, water chemistry, hydrologic setting, climate, and bathymetry (fig. 1). Given the complexity of the problem, an exceedingly large number of calibration data (that is, measurements describing whole-lake carbon budgets) would be required to properly constrain a process-based model (McDonald, 2010). Relatively few of such whole-lake budgets have been compiled to date. Thus, an inductive, data-based approach utilizing artificial neural-networks (ANNs) is being developed to utilize readily quantified and widely available geospatial data (for example, lake area, base flow, land cover, geology, and so on) to characterize carbon efflux and burial. The model will then be applied to estimate carbon budgets for all of the water bodies mapped in the national hydrography dataset (NHD) and corrected for small, unmapped waterbodies. Finally, an estimate of carbon efflux and sequestration for the nation’s inland water bodies will be made.

Bastviken, D., Cole, J., Pace, M., and Tranvik, L., 2004, Methane emissions from lakes: Dependence of lake characteristics, two regional assessments, and a global estimate: Global Biogeochemical Cycles, v. 18, GB4009.

Cole, J., Prairie, Y., Caraco, N., McDowell, W., Tranvik,L.G., Striegl, R.G., Duarte, C.M., Kortelainen, P., Downing, J.A., Middelburg, J.J., and Melack, J., 2007, Plumbing the global carbon cycle: Integrating inland waters into the terrestrial carbon budget: Ecosystems, v. 10, 171–184.

Dean, W., and Gorham, E., 1998, Magnitude and significance of carbon burial in lakes, reservoirs, and peatlands: Geology, v. 26, p. 535–538.

Downing, J., Cole, J., and Middelburg, J., 2008, Sediment organic carbon burial in agriculturally eutrophic impoundments over the last century: Global Biogeochemical Cycles, v. 22, GB1018.

McDonald, C.P., 2010, Improving the reliability of aquatic biogeochemical models: Integrating information and optimizing complexity: Houghton, Mich., Michigan Technological University, Ph.D. dissertation.

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