Model data for Flood Frequency Analysis using Stochastic Storm Transposition and an Integrated Surface-Subsurface Hydrological Model

Perez, Gabriel; Coon, Ethan; Rathore, Saubhagya; Le, Phong V. V.

doi:10.15485/2324641

Title: Model data for Flood Frequency Analysis using Stochastic Storm Transposition and an Integrated Surface-Subsurface Hydrological Model

Dataset
Other Related Research

Abstract

This archived provides scripts and input files used for the implementation of a novel approach to conduct process-based Flood Frequency Analysis using a Stochastic Storm Transposition (SST) and an Integrated Surface-Subsurface Hydrological Model (ISSHM). As a proof-of-concept, this study uses the ISSHM, Advanced Terrestrial Simulator (Amanzi-ATS) model, and the SST model, RainyDay, to conduct flood frequency analysis by simulating the flood response to 5,000 annual synthetic storm events in a ~2000 km2 Southeast Texas watershed.The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include TXT, CSV, DAT, SBATCH, SHP, TIF, NetCDF, and HDF5 files, which can be read through Python scripts. The input files for the ATS model and RainyDay model have .XML and .SST extensions, respectively, and can be edited in any commonly used text editors.This archive contains:* Scripts and data files essential for generating the ATS model input. It uses the Watershed Workflow package to produce both mesh and ATS input files. * Jupyter notebooks designated for the ATS model evaluation, covering both long-term simulations and 40 rainfall-runoff events.* Input files required to simulate SST storm eventsmore » using RainyDay.« less

Authors:

;

Oak Ridge National Laboratory; Oak Ridge National Laboratory
Oak Ridge National Laboratory

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

Research Org.:: Environmental System Science Data Infrastructure for a Virtual Ecosystem; Southeast Texas Urban Integrated Field Laboratory (SETx UIFL) – Equitable solutions for communities caught between floods and air pollution

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

Subject:: 54 ENVIRONMENTAL SCIENCES; Basin Inundation Fraction; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER; Flood Frequency Analysis; Flood Hazard; Integrated Surface-Subsurface Hydrological Model; Peak Flows; Population Flood Exposure; Process-based Hydrological Simulations; Stochastic Storm Transposition

OSTI Identifier:: 2324641

DOI:: https://doi.org/10.15485/2324641

Citation Formats


                    Perez, Gabriel, Coon, Ethan, Rathore, Saubhagya, and Le, Phong V. V. Model data for Flood Frequency Analysis using Stochastic Storm Transposition and an Integrated Surface-Subsurface Hydrological Model.  United States: N. p., 2024. 
        Web.  doi:10.15485/2324641.

Copy to clipboard


                    Perez, Gabriel, Coon, Ethan, Rathore, Saubhagya, & Le, Phong V. V. Model data for Flood Frequency Analysis using Stochastic Storm Transposition and an Integrated Surface-Subsurface Hydrological Model.  United States.  doi:https://doi.org/10.15485/2324641

Copy to clipboard


                    Perez, Gabriel, Coon, Ethan, Rathore, Saubhagya, and Le, Phong V. V. 2024.  
"Model data for Flood Frequency Analysis using Stochastic Storm Transposition and an Integrated Surface-Subsurface Hydrological Model".  United States.  doi:https://doi.org/10.15485/2324641.  https://www.osti.gov/servlets/purl/2324641. Pub date:Mon Jan 01 04:00:00 UTC 2024

Copy to clipboard


                    
@article{osti_2324641,

  title        = {Model data for Flood Frequency Analysis using Stochastic Storm Transposition and an Integrated Surface-Subsurface Hydrological Model},

  author       = {Perez, Gabriel and Coon, Ethan and Rathore, Saubhagya and Le, Phong V. V.},

  abstractNote = {This archived provides scripts and input files used for the implementation of a novel approach to conduct process-based Flood Frequency Analysis using a Stochastic Storm Transposition (SST) and an Integrated Surface-Subsurface Hydrological Model (ISSHM). As a proof-of-concept, this study uses the ISSHM, Advanced Terrestrial Simulator (Amanzi-ATS) model, and the SST model, RainyDay, to conduct flood frequency analysis by simulating the flood response to 5,000 annual synthetic storm events in a ~2000 km2 Southeast Texas watershed.The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include TXT, CSV, DAT, SBATCH, SHP, TIF, NetCDF, and HDF5 files, which can be read through Python scripts. The input files for the ATS model and RainyDay model have .XML and .SST extensions, respectively, and can be edited in any commonly used text editors.This archive contains:* Scripts and data files essential for generating the ATS model input. It uses the Watershed Workflow package to produce both mesh and ATS input files. * Jupyter notebooks designated for the ATS model evaluation, covering both long-term simulations and 40 rainfall-runoff events.* Input files required to simulate SST storm events using RainyDay.},

  doi          = {10.15485/2324641},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

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

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

}

Copy to clipboard

Dataset:

View Dataset

DOI: https://doi.org/10.15485/2324641

Save / Share:

Export Metadata

Save to My Library

Similar records in DOE Data Explorer and OSTI.GOV collections:

Data and code for Daily and Multi-Day Extreme Rainfall Analysis Under Future Climates Using Stochastic Storm Transposition and NEX-GDDP-CMIP6 Over CONUS

Dataset Perez, Gabriel ; Coon, Ethan ; V. V. Le, Phong ; ...

This data package provides inputs, codes, and outputs for a comprehensive analysis of projected changes in extreme precipitation across 10 regions of the continental United States, using 34 downscaled Earth System Models (ESMs) from the NASA Earth Exchange Global Daily Downscaled Projections, Coupled Model Intercomparison Project Phase 6 (NEX-GDDP-CMIP6) dataset. These models are part of the Coupled Model Intercomparison Project Phase 6 (CMIP6), a coordinated climate modeling framework widely used to assess climate change impacts. The analysis applies a stochastic storm transposition method to quantify changes in extreme rainfall under two Shared Socioeconomic Pathway (SSP) climate scenarios—SSP2-4.5 (moderate emissions) andmore »« less
Evaluating Integrated Surface/Subsurface Permafrost Thermal Hydrology Models in ATS (v0.88) Against Observations from a Polygonal Tundra Site: Modeling Archive

Dataset Jan, Ahmad ; Coon, Ethan ; Painter, Scott

This Modeling Archive supports the NGEE Arctic publication "Evaluating integrated surface/subsurface permafrost thermal hydrology models in ATS (v0.88) against observations from a polygonal tundra site" available in the Geoscientific Model Development journal. We evaluated the integrated surface/subsurface permafrost thermal hydrology models in the Advanced Terrestrial Simulator (ATS) against field observations in polygonal tundra at the Barrow Environmental Observatory. We simulated thermal hydrology of three-dimensional ice-wedge polygons with generic but broadly representative surface microtopography. We drove the simulations with meteorological data and observed water table elevations in ice-wedge polygon troughs. With limited calibration of the soil properties and evaporation model parameters,more »« less
Influence of hydrological, biogeochemical and temperature transients on subsurface carbon fluxes in a flood plain environment, Biogeochemistry: Dataset

Dataset Arora, Bhavna ; Bill, Markus ; Conrad, Mark ; ...

Data tables used in Arora et al. 2016b Influence of hydrological, biogeochemical and temperature transients on subsurface carbon fluxes in a flood plain environment. Biogeochemistry, 127(2-3), 367-396. Files include reactive transport model parameters describing soil physical and thermal parameters, geochemical reaction network and rate laws, as well as initial and boundary conditions. The last table documents modeling results with respect to annual carbon fluxes from the site to the river.
Modeling the Effects of Artificial Drainage on Agriculture-dominated Watersheds using a Fully Distributed Integrated Hydrology Model: Datasets, code, models files

Dataset Rathore, Saubhagya Singh ; Svyatsky, Daniil ; Coon, Ethan ; ...

This model-data archive is for a modeling study focused on the effects of artificial drainage on agriculture-dominated watersheds using a fully distributed integrated hydrology model. This study introduced a novel strategy to represent the effects of tile drains and agricultural ditches in a fully distributed basin-scale integrated hydrology model. The numerical experiments in this study reveal the effects of surface and subsurface drainage on various hydrological states and fluxes. The details about the datasets can be found in the "readme" document attached with the dataset.
Modeling the Effects of Artificial Drainage on Agriculture-dominated Watersheds using a Fully Distributed Integrated Hydrology Model: Datasets, scripts, model files

Dataset Rathore, Saubhagya S. ; Svyatsky, Daniil ; Coon, Ethan T. ; ...

This model-data archive supports the research paper that demonstrates the integration of agricultural drainage features—specifically, narrow engineered ditches and tile drains—into a fully distributed, basin-scale integrated surface-subsurface hydrology model (ISSHM), Amanzi-ATS. The model employs innovative computational meshes aligned with agricultural ditches and incorporates the physically based Hooghoudt's drainage equation to simulate tile drainage, offering a novel strategy that enhances the accuracy of hydrological simulations.The archived dataset includes input parameters, model configurations, and select simulation outputs for the Amanzi-ATS model that successfully captured the streamflow patterns in the Portage River Watershed as validated by USGS gauge readings. Jupyter notebook for themore »« less

Similar Records