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
Department of Civil Environmental and Geodetic Engineering Ohio State University Columbus OH USA
Earth System Science Interdisciplinary Center University of Maryland College Park MD USA, Biospheric Sciences Laboratory NASA Goddard Space Flight Center Greenbelt MD USA
U.S. Geological Survey Wetland and Aquatic Research Center Gainesville FL USA
School of Geosciences University of Louisiana at Lafayette Lafayette LA USA
Soil and Crop Sciences Colorado State University Fort Collins CO USA
Climate and Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley CA USA
Wetlands are the largest emitters of biogenic methane (CH 4 ) and represent the highest source of uncertainty in global CH 4 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 CH 4 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 CO 2 and CH 4 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 CO 2 and CH 4 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 CH 4 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 CH 4 emission root mean squared error by up to 33% and is able to represent inter‐daily CO 2 and CH 4 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 = {Abstract Wetlands are the largest emitters of biogenic methane (CH 4 ) and represent the highest source of uncertainty in global CH 4 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 CH 4 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 CO 2 and CH 4 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 CO 2 and CH 4 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 CH 4 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 CH 4 emission root mean squared error by up to 33% and is able to represent inter‐daily CO 2 and CH 4 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}}
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
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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