Hyporheic-zone Processes and Stream Oxygen Dynamics: Insights from a Multiscale Reactive Transport Model: Modeling Archive

Gomez-Velez, Jesus; Rathore, Saubhagya; Painter, Scott; Cohen, Matthew

doi:10.15485/3003420

Title: Hyporheic-zone Processes and Stream Oxygen Dynamics: Insights from a Multiscale Reactive Transport Model: Modeling Archive

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Abstract

This archive contains the data and Python scripts required to reproduce the analyses and figures in the study: Gomez-Velez, J. D., Rathore, S. S., Cohen, M. J., & Painter, S. L. (2025). Hyporheic-zone Processes and Stream Oxygen Dynamics: Insights from a Multiscale Reactive Transport Model. Submitted to Water Resources Research. The analysis utilizes the subgrid model Advection Dispersion Equation with Lagrangian Subgrids (ADELS) implemented in the Advanced Terrestrial Simulator (ATS; https://amanzi.github.io/ats/stable/). In this case, the ATS and Amanzi versions are (1) ATS version 1.5.1_f5ba18f8 and (2) Amanzi version 1.6-dev_53444cca4. The repository includes a Jupyter Notebook and the necessary data (Pandas DataFrames stored as pickle files) to generate the figures for the manuscript. Additionally, it contains Python scripts to create ATS input files, run the ATS simulations, and post-process the results. Finally, it provides routines for parameter estimation using the Single-Station Metabolism (SSM) model with the Differential Evolution Adaptive Metropolis (DREAM) Markov Chain Monte Carlo (MCMC) algorithm with ZS enhancements (DREAM-ZS).

Authors:

;

University of Iowa
Oak Ridge National Laboratory
Water Institute, University of Florida, Gainesville, FL, USA

Publication Date:: Tue Dec 31 23:00:00 EST 2024

DOE Contract Number:: AC02-05CH11231

Research Org.:: Watershed Dynamics and Evolution (WaDE) SFA

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Subject:: 54 ENVIRONMENTAL SCIENCES; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > GROUND WATER; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > WATER QUALITY/WATER CHEMISTRY

OSTI Identifier:: 3003420

DOI:: https://doi.org/10.15485/3003420

Citation Formats


                    Gomez-Velez, Jesus, Rathore, Saubhagya, Painter, Scott, and Cohen, Matthew. Hyporheic-zone Processes and Stream Oxygen Dynamics: Insights from a Multiscale Reactive Transport Model: Modeling Archive.  United States: N. p., 2024. 
        Web.  doi:10.15485/3003420.

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                    Gomez-Velez, Jesus, Rathore, Saubhagya, Painter, Scott, & Cohen, Matthew. Hyporheic-zone Processes and Stream Oxygen Dynamics: Insights from a Multiscale Reactive Transport Model: Modeling Archive.  United States.  doi:https://doi.org/10.15485/3003420

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                    Gomez-Velez, Jesus, Rathore, Saubhagya, Painter, Scott, and Cohen, Matthew. 2024.  
"Hyporheic-zone Processes and Stream Oxygen Dynamics: Insights from a Multiscale Reactive Transport Model: Modeling Archive".  United States.  doi:https://doi.org/10.15485/3003420.  https://www.osti.gov/servlets/purl/3003420. Pub date:Tue Dec 31 23:00:00 EST 2024

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@article{osti_3003420,

  title        = {Hyporheic-zone Processes and Stream Oxygen Dynamics: Insights from a Multiscale Reactive Transport Model: Modeling Archive},

  author       = {Gomez-Velez, Jesus and Rathore, Saubhagya and Painter, Scott and Cohen, Matthew},

  abstractNote = {This archive contains the data and Python scripts required to reproduce the analyses and figures in the study: Gomez-Velez, J. D., Rathore, S. S., Cohen, M. J., & Painter, S. L. (2025). Hyporheic-zone Processes and Stream Oxygen Dynamics: Insights from a Multiscale Reactive Transport Model. Submitted to Water Resources Research. The analysis utilizes the subgrid model Advection Dispersion Equation with Lagrangian Subgrids (ADELS) implemented in the Advanced Terrestrial Simulator (ATS; https://amanzi.github.io/ats/stable/). In this case, the ATS and Amanzi versions are (1) ATS version 1.5.1_f5ba18f8 and (2) Amanzi version 1.6-dev_53444cca4. The repository includes a Jupyter Notebook and the necessary data (Pandas DataFrames stored as pickle files) to generate the figures for the manuscript. Additionally, it contains Python scripts to create ATS input files, run the ATS simulations, and post-process the results. Finally, it provides routines for parameter estimation using the Single-Station Metabolism (SSM) model with the Differential Evolution Adaptive Metropolis (DREAM) Markov Chain Monte Carlo (MCMC) algorithm with ZS enhancements (DREAM-ZS).},

  doi          = {10.15485/3003420},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Tue Dec 31 23:00:00 EST 2024},

  month        = {Tue Dec 31 23:00:00 EST 2024}

}

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DOI: https://doi.org/10.15485/3003420

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