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Improving wetland model realism: Activating and parametrizing sub-grid level wetland land-unit in the E3SM land model (ELM)

Presentation Date
Friday, December 16, 2022 at 2:45pm - Friday, December 16, 2022 at 6:15pm
McCormick Place - Poster Hall, Hall - A



Wetlands, and other inlands water bodies, represent the highest source of uncertainty in global earth system models (ESMs) methane budgets, and they are estimated to account for 20-40% of global methane emissions. Modeling challenges include the small-scale temporal and spatial heterogeneity of wetland structure and associated methane flux rates and the interactions between different underground and aboveground processes (hydrological, ecological, meteorological, and microbial) that control methane production and consumption. In this project, we aim to improve the realism of wetland representation in ESMs using the DOE’s Energy Exascale Earth System Model (E3SM), and simulate methane and carbon biogeochemical processes within wetland ecological patch-level. E3SM Land Model (ELM) v1 resolves wetland processes as a module that is activated within vegetation land-units when they are flooded. We modified the model using a designated wetland land-unit in prescribed flooded areas (i.e., wetlands). This land-unit includes different patch-types representing different ecological functional types and growth forms within a wetland namely floating vegetation, emergent vegetation, open water, and mud flats. To evaluate our model, we used eddy covariance fluxes, chamber fluxes, and porewater concentrations at Old Woman Creek freshwater estuarine marsh at lake Erie shore in Huron, Ohio and Barataria Bay Saline Saltmarsh in Louisiana. Our multi-scale field observations allowed us to optimize the parameters of each of the patches independently and in combination. We also improved the patch-level model and parameters for plant aerenchyma resistance to methane flux based on porewater and chamber measurements and a Bayesian optimization. ELMv1 simulation results of daily methane fluxes in Old Woman Creek were more than 50% less than observations, while the saltmarsh simulations were matching observations (+-20%). We hypothesize it is likely that the high observed methane fluxes in Ohio are due to high dissolved carbon and nutrient influxes from the upstream agricultural watershed, i.e. boundary conditions that are not included in the model.

Funding Program Area(s)