ELM-Wet: Inclusion of a wetland landunit with sub-grid representation of eco-hydrological patches and hydrological forcing in E3SM Land Model (ELM)

Yazbeck, Theresia; Bohrer, Gil; Zhu, Qing; Riley, William J.

doi:10.15485/2403122

Title: ELM-Wet: Inclusion of a wetland landunit with sub-grid representation of eco-hydrological patches and hydrological forcing in E3SM Land Model (ELM)

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Abstract

Wetlands emit the most biogenic methane (CH4) and present the greatest uncertainty in the global CH4 budget. Modeling these emissions is challenging due to the temporal and spatial variability in wetland structure and CH4 flux rates, along with complex interactions among hydrological, ecological, meteorological, and microbial processes that govern CH4 dynamics. To address these issues, we aim to enhance the accuracy of wetland representation in the U.S. Department of Energy’s Exascale Earth System Model (E3SM) Land Model, ELM. This effort led to the development of ELM-Wet, which incorporates a dedicated wetland landunit with subgrid representation of eco-hydrological patch types. We implement wetland-specific hydrology by imposing site-specific constraints on surface water levels, thereby allowing different patches to sustain varying depths of inundation. Additionally, we refined the calculation of aerenchyma transport diffusivity based on observed conductance across different vegetation types. We validated these enhancements through site-specific simulations of a coastal freshwater wetland, the Salvador WMA Freshwater Marsh (Ameriflux, site ID US-LA2), located in the coast of Louisiana (29.85N,90.29W) at an elevation of 0 m. The site was simulated with ELM-Wet and the default version ELMv1. We use Bayesian Optimization to parameterize CO2 and CH4 fluxes. Eddy covariance observations of CO2 and CH4more »« less

Authors:

;

; Zhu, Qing; Riley, William J.

Ohio State University; Ohio State University
Ohio State University
Lawrence Berkeley National Laboratory

Publication Date:: Mon Jan 01 04:00:00 UTC 2024

DOE Contract Number:: SC0022191; SC0021067; SC0022972; SC0023084; 89243020SSC000054

Research Org.:: Environmental System Science Data Infrastructure for a Virtual Ecosystem; Functional-type modeling approach and data-driven parameterization of methane emissions in wetlands

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER); National Aeronautics and Space Administration (NASA)

Subject:: 54 ENVIRONMENTAL SCIENCES; E3SM Land Model (ELM); ELM-Wet; ESS-DIVE CSV File Formatting Guidelines Reporting Format; ESS-DIVE File Level Metadata Reporting Format; Energy’s Exascale Earth System Model (E3SM); Land Surface Models; Methane Flux; Wetlands

OSTI Identifier:: 2403122

DOI:: https://doi.org/10.15485/2403122

Citation Formats


                    Yazbeck, Theresia, Bohrer, Gil, Zhu, Qing, and Riley, William J. ELM-Wet: Inclusion of a wetland landunit with sub-grid representation of eco-hydrological patches and hydrological forcing in E3SM Land Model (ELM).  United States: N. p., 2024. 
        Web.  doi:10.15485/2403122.

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                    Yazbeck, Theresia, Bohrer, Gil, Zhu, Qing, & Riley, William J. ELM-Wet: Inclusion of a wetland landunit with sub-grid representation of eco-hydrological patches and hydrological forcing in E3SM Land Model (ELM).  United States.  doi:https://doi.org/10.15485/2403122

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                    Yazbeck, Theresia, Bohrer, Gil, Zhu, Qing, and Riley, William J. 2024.  
"ELM-Wet: Inclusion of a wetland landunit with sub-grid representation of eco-hydrological patches and hydrological forcing in E3SM Land Model (ELM)".  United States.  doi:https://doi.org/10.15485/2403122.  https://www.osti.gov/servlets/purl/2403122. Pub date:Mon Jan 01 04:00:00 UTC 2024

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@article{osti_2403122,

  title        = {ELM-Wet: Inclusion of a wetland landunit with sub-grid representation of eco-hydrological patches and hydrological forcing in E3SM Land Model (ELM)},

  author       = {Yazbeck, Theresia and Bohrer, Gil and Zhu, Qing and Riley, William J.},

  abstractNote = {Wetlands emit the most biogenic methane (CH4) and present the greatest uncertainty in the global CH4 budget. Modeling these emissions is challenging due to the temporal and spatial variability in wetland structure and CH4 flux rates, along with complex interactions among hydrological, ecological, meteorological, and microbial processes that govern CH4 dynamics. To address these issues, we aim to enhance the accuracy of wetland representation in the U.S. Department of Energy’s Exascale Earth System Model (E3SM) Land Model, ELM. This effort led to the development of ELM-Wet, which incorporates a dedicated wetland landunit with subgrid representation of eco-hydrological patch types. We implement wetland-specific hydrology by imposing site-specific constraints on surface water levels, thereby allowing different patches to sustain varying depths of inundation. Additionally, we refined the calculation of aerenchyma transport diffusivity based on observed conductance across different vegetation types. We validated these enhancements through site-specific simulations of a coastal freshwater wetland, the Salvador WMA Freshwater Marsh (Ameriflux, site ID US-LA2), located in the coast of Louisiana (29.85N,90.29W) at an elevation of 0 m. The site was simulated with ELM-Wet and the default version ELMv1. We use Bayesian Optimization to parameterize CO2 and CH4 fluxes. Eddy covariance observations of CO2 and CH4 fluxes from 2012-2013 were used to train the model and data from 2021 were used for validation. In this repository, we include all the output of all the simulations performed using different versions of ELMv1 and ELM-Wet, all input required to the model, and the Matlab scripts we used to processed the output data. ELM-Wet_flmd.csv includes a detailed description of the datasets files.},

  doi          = {10.15485/2403122},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Mon Jan 01 04:00:00 UTC 2024},

  month        = {Mon Jan 01 04:00:00 UTC 2024}

}

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DOI: https://doi.org/10.15485/2403122

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