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Title: Hydrologic Model Data for the East Fork Poplar Creek Watershed Simulated with the Advanced Terrestrial Simulator (ATS): Streamflow and Network Expansion–Contraction Dynamics

Abstract

This dataset supports hydrologic modeling and stream network expansion–contraction analysis for the East Fork Poplar Creek (EFPC) Watershed in Tennessee. It includes a Jupyter notebook for model setup, model configuration files, simulation outputs, and derived products used to evaluate model performance and investigate stream dynamics under varying hydrologic conditions. The dataset was generated using the Watershed Workflow Python package and the Advanced Terrestrial Simulator (ATS), enabling integrated surface–subsurface hydrologic simulations using a stream-aligned mesh. Outputs include high-resolution time series of streamflow, active network length, water table depth, and related hydrologic variables. Also included are spatially explicit stream persistency indices and classifications of reaches as perennial or non-perennial. These data facilitate reproducibility and support further research on stream intermittency and variability in network extent.The model data archive is organized in following directories:1) model_setup_inputsContains the Watershed Workflow Jupyter notebooks (accessed through any open source code editor), selected input datasets, and resulting ATS input files, including XML files (access through any open source code editor), computational mesh (.exo files can be viewed using Paraview), and meteorological forcing files (.h5 files can be accessed through h5py python package and HDFView open source software). 2) model_outputsIncludes ATS simulation outputs relevant to this study. Time seriesmore » of spatially integrated or averaged variables (e.g., streamflow, water table depth) are provided as CSV files. Select spatial fields (e.g., ponded depth and water table depth) are saved as pickled Python objects to reduce file size, and can be accessed through pickle package in Python. Key geometry objects from Watershed Workflow—such as the surface mesh and river tree—are also included to support analysis of streamflow persistency and expansion–contraction dynamics. These files can also be accessed through Watershed Workflow Python package.3) model_evaluationProvides observed streamflow time series and field survey-based flow regime classifications used to evaluate model performance. Jupyter notebooks for processing ATS outputs and comparing model predictions with observations to build confidence in the model prior to scientific analysis are also included.4) Q_L_relationshipsContains workflows for generating time series of discharge, active network length, and related hydrologic variables used in the stream network expansion–contraction analysis. Includes routines for delineating baseflow-dominated periods. For each catchment, notebooks and processed data (as pickled DataFrames accessed through Pandas Python package) are provided. 5) figure_scriptsProvides the Jupyter notebooks used to generate the figures presented in the paper.« less

Authors:
ORCiD logo ; ORCiD logo ; ORCiD logo ; ORCiD logo
  1. Oak Ridge National Laboratory
Publication Date:
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 > BIOSPHERE > ECOSYSTEMS > FRESHWATER ECOSYSTEMS > RIVERS/STREAM > EPHEMERAL STREAM; EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > FRESHWATER ECOSYSTEMS > RIVERS/STREAM > HEADWATER STREAM; EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > FRESHWATER ECOSYSTEMS > RIVERS/STREAM > INTERMITTENT STREAM; EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > FRESHWATER ECOSYSTEMS > RIVERS/STREAM > PERENNIAL STREAM/RIVER; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > GROUND WATER; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > GROUND WATER > GROUND WATER FEATURES > WATER TABLE > WATER TABLE DEPTH; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER > SURFACE WATER PROCESSES/MEASUREMENTS > DISCHARGE/FLOW > BASE FLOW; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER > SURFACE WATER PROCESSES/MEASUREMENTS > DISCHARGE/FLOW > PEAK FLOW; ESS-DIVE Model Data Archiving Guidelines
OSTI Identifier:
2569197
DOI:
https://doi.org/10.15485/2569197

Citation Formats

Rathore, Saubhagya, Herndon, Elizabeth, Gomez-Velez, Jesus, and Painter, Scott. Hydrologic Model Data for the East Fork Poplar Creek Watershed Simulated with the Advanced Terrestrial Simulator (ATS): Streamflow and Network Expansion–Contraction Dynamics. United States: N. p., 2024. Web. doi:10.15485/2569197.
Rathore, Saubhagya, Herndon, Elizabeth, Gomez-Velez, Jesus, & Painter, Scott. Hydrologic Model Data for the East Fork Poplar Creek Watershed Simulated with the Advanced Terrestrial Simulator (ATS): Streamflow and Network Expansion–Contraction Dynamics. United States. doi:https://doi.org/10.15485/2569197
Rathore, Saubhagya, Herndon, Elizabeth, Gomez-Velez, Jesus, and Painter, Scott. 2024. "Hydrologic Model Data for the East Fork Poplar Creek Watershed Simulated with the Advanced Terrestrial Simulator (ATS): Streamflow and Network Expansion–Contraction Dynamics". United States. doi:https://doi.org/10.15485/2569197. https://www.osti.gov/servlets/purl/2569197. Pub date:Tue Dec 31 23:00:00 EST 2024
@article{osti_2569197,
title = {Hydrologic Model Data for the East Fork Poplar Creek Watershed Simulated with the Advanced Terrestrial Simulator (ATS): Streamflow and Network Expansion–Contraction Dynamics},
author = {Rathore, Saubhagya and Herndon, Elizabeth and Gomez-Velez, Jesus and Painter, Scott},
abstractNote = {This dataset supports hydrologic modeling and stream network expansion–contraction analysis for the East Fork Poplar Creek (EFPC) Watershed in Tennessee. It includes a Jupyter notebook for model setup, model configuration files, simulation outputs, and derived products used to evaluate model performance and investigate stream dynamics under varying hydrologic conditions. The dataset was generated using the Watershed Workflow Python package and the Advanced Terrestrial Simulator (ATS), enabling integrated surface–subsurface hydrologic simulations using a stream-aligned mesh. Outputs include high-resolution time series of streamflow, active network length, water table depth, and related hydrologic variables. Also included are spatially explicit stream persistency indices and classifications of reaches as perennial or non-perennial. These data facilitate reproducibility and support further research on stream intermittency and variability in network extent.The model data archive is organized in following directories:1) model_setup_inputsContains the Watershed Workflow Jupyter notebooks (accessed through any open source code editor), selected input datasets, and resulting ATS input files, including XML files (access through any open source code editor), computational mesh (.exo files can be viewed using Paraview), and meteorological forcing files (.h5 files can be accessed through h5py python package and HDFView open source software). 2) model_outputsIncludes ATS simulation outputs relevant to this study. Time series of spatially integrated or averaged variables (e.g., streamflow, water table depth) are provided as CSV files. Select spatial fields (e.g., ponded depth and water table depth) are saved as pickled Python objects to reduce file size, and can be accessed through pickle package in Python. Key geometry objects from Watershed Workflow—such as the surface mesh and river tree—are also included to support analysis of streamflow persistency and expansion–contraction dynamics. These files can also be accessed through Watershed Workflow Python package.3) model_evaluationProvides observed streamflow time series and field survey-based flow regime classifications used to evaluate model performance. Jupyter notebooks for processing ATS outputs and comparing model predictions with observations to build confidence in the model prior to scientific analysis are also included.4) Q_L_relationshipsContains workflows for generating time series of discharge, active network length, and related hydrologic variables used in the stream network expansion–contraction analysis. Includes routines for delineating baseflow-dominated periods. For each catchment, notebooks and processed data (as pickled DataFrames accessed through Pandas Python package) are provided. 5) figure_scriptsProvides the Jupyter notebooks used to generate the figures presented in the paper.},
doi = {10.15485/2569197},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Dec 31 23:00:00 EST 2024},
month = {Tue Dec 31 23:00:00 EST 2024}
}