U.S. Department of Energy Office of Scientific and Technical Information
ELM–Wet: Inclusion of a Wet–Landunit With Sub–Grid Representation of Eco–Hydrological Patches and Hydrological Forcing Improves Methane Emission Estimations in the E3SM Land Model (ELM)
Journal Article·· Journal of Advances in Modeling Earth Systems
Wetlands are the largest emitters of biogenic methane (CH4) and represent the highest source of uncertainty in global CH4 budgets. Here, we aim to improve the realism of wetland representation in the U.S. Department of Energy's Exascale Earth System Model land surface model, ELM, thereby reducing uncertainty of CH4 flux predictions. We develop an updated version, ELM-Wet, where we activate a separate landunit for wetlands that handles multiple wetland-specific eco-hydrological patch functional types. We introduce more realistic hydrological forcing through prescribing site-level constraints on surface water elevation, which allows resolving different sustained inundation depth for different patches, and if data exists, prescribing inundation depth. We modified the calculation of aerenchyma transport diffusivity based on observed conductance per leaf area for different vegetation types. We use Bayesian Optimization to parameterize CO2 and CH4 fluxes in the developed wet-landunit. Site-level simulations of a coastal non-tidal freshwater wetland in Louisiana were performed with the updated model. Eddy covariance observations of CO2 and CH4 fluxes from 2012 to 2013 were used to train the model and data from 2021 were used for validation. Patch-specific chamber flux observations and observations of CH4 concentration profiles in the soil porewater from 2021 were used for evaluation of the model performance. Our results show that ELM-Wet reduces the model's CH4 emission root mean squared error by up to 33% and is able to represent inter-daily CO2 and CH4 flux variability across the wetland's eco-hydrological patches, including during periods of extreme dry or wet conditions.
Yazbeck, Theresia, et al. "ELM–Wet: Inclusion of a Wet–Landunit With Sub–Grid Representation of Eco–Hydrological Patches and Hydrological Forcing Improves Methane Emission Estimations in the E3SM Land Model (ELM)." Journal of Advances in Modeling Earth Systems, vol. 17, no. 2, Feb. 2025. https://doi.org/10.1029/2024ms004396
Yazbeck, Theresia, Bohrer, Gil, Scyphers, Madeline E., Missik, Justine E. C., Shchehlov, Oleksandr, Ward, Eric J., Merino, Sergio L., Bordelon, Robert, Taj, Diana, Villa, Jorge A., Wrighton, Kelly, Zhu, Qing, & Riley, William J. (2025). ELM–Wet: Inclusion of a Wet–Landunit With Sub–Grid Representation of Eco–Hydrological Patches and Hydrological Forcing Improves Methane Emission Estimations in the E3SM Land Model (ELM). Journal of Advances in Modeling Earth Systems, 17(2). https://doi.org/10.1029/2024ms004396
Yazbeck, Theresia, Bohrer, Gil, Scyphers, Madeline E., et al., "ELM–Wet: Inclusion of a Wet–Landunit With Sub–Grid Representation of Eco–Hydrological Patches and Hydrological Forcing Improves Methane Emission Estimations in the E3SM Land Model (ELM)," Journal of Advances in Modeling Earth Systems 17, no. 2 (2025), https://doi.org/10.1029/2024ms004396
@article{osti_2511346,
author = {Yazbeck, Theresia and Bohrer, Gil and Scyphers, Madeline E. and Missik, Justine E. C. and Shchehlov, Oleksandr and Ward, Eric J. and Merino, Sergio L. and Bordelon, Robert and Taj, Diana and Villa, Jorge A. and others},
title = {ELM–Wet: Inclusion of a Wet–Landunit With Sub–Grid Representation of Eco–Hydrological Patches and Hydrological Forcing Improves Methane Emission Estimations in the E3SM Land Model (ELM)},
annote = {Wetlands are the largest emitters of biogenic methane (CH4) and represent the highest source of uncertainty in global CH4 budgets. Here, we aim to improve the realism of wetland representation in the U.S. Department of Energy's Exascale Earth System Model land surface model, ELM, thereby reducing uncertainty of CH4 flux predictions. We develop an updated version, ELM-Wet, where we activate a separate landunit for wetlands that handles multiple wetland-specific eco-hydrological patch functional types. We introduce more realistic hydrological forcing through prescribing site-level constraints on surface water elevation, which allows resolving different sustained inundation depth for different patches, and if data exists, prescribing inundation depth. We modified the calculation of aerenchyma transport diffusivity based on observed conductance per leaf area for different vegetation types. We use Bayesian Optimization to parameterize CO2 and CH4 fluxes in the developed wet-landunit. Site-level simulations of a coastal non-tidal freshwater wetland in Louisiana were performed with the updated model. Eddy covariance observations of CO2 and CH4 fluxes from 2012 to 2013 were used to train the model and data from 2021 were used for validation. Patch-specific chamber flux observations and observations of CH4 concentration profiles in the soil porewater from 2021 were used for evaluation of the model performance. Our results show that ELM-Wet reduces the model's CH4 emission root mean squared error by up to 33% and is able to represent inter-daily CO2 and CH4 flux variability across the wetland's eco-hydrological patches, including during periods of extreme dry or wet conditions.},
doi = {10.1029/2024ms004396},
url = {https://www.osti.gov/biblio/2511346},
journal = {Journal of Advances in Modeling Earth Systems},
issn = {ISSN 1942-2466},
number = {2},
volume = {17},
place = {United States},
publisher = {American Geophysical Union (AGU)},
year = {2025},
month = {02}}
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); The Ohio State University, Columbus, OH (United States)
Sponsoring Organization:
NASA FINESST; US Department of Energy; USDOE; USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23), Climate and Environmental Sciences Division (SC-23.1 ); USDOE Office of Science (SC), Biological and Environmental Research (BER). Earth & Environmental Systems Science (EESS)
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 363, Issue 1837https://doi.org/10.1098/rsta.2005.1671
Sihi, Debjani; López-Lloreda, Carla; M. Brenner, Julia
Environmental System Science Data Infrastructure for a Virtual Ecosystem; A Comprehensive Framework for Modeling Emissions from Tropical Soils and Wetlandshttps://doi.org/10.15485/1618869
Environmental System Science Data Infrastructure for a Virtual Ecosystem; Functional-type modeling approach and data-driven parameterization of methane emissions in wetlandshttps://doi.org/10.15485/1997524
Environmental System Science Data Infrastructure for a Virtual Ecosystem; Functional-type modeling approach and data-driven parameterization of methane emissions in wetlandshttps://doi.org/10.15485/2403122