Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems


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Created: Nov 24, 2020 at 7:05 a.m.
Last updated: May 28, 2021 at 1:33 a.m.
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Abstract

This is a collection resource for "Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems" manuscript in Environmental Modeling and Software.

HS-1: Collection Resource for Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems

For SUMMA simulation, we created two SUMMA model instances.
HS-2. Model Instance for the Impact of Stomatal Resistance Parameterizations on ET of SUMMA Model in Aspen stand at Reynolds Mountain East
HS-3. Model Instance for the Impact of Lateral Flow Parameterizations on Runoff of SUMMA Model at Reynolds Mountain East

For SUMMA simulation, we created a SUMMA model program
HS-4: Remote Approach-11: Using HPC Cluster (Rivanna: HPC at University of Virginia) for the reproducibility of SUMMA modeling

There are five HS resources for reproducible approaches.
HS-5. A Virtual Box image that includes five local approaches:
- Approach-1 Compiling the core model software
- Approach-2 Containerizing the core model software only with Docker
- Approach-3 Containerizing all software with Docker
- Approach-4 Containerizing all software with Singularity
- Approach-5 Containerizing all software and modeling workflows with Sciunit
HS-6. Approach-6 Using CUAHSI JupyterHub
HS-7. Approach-7 Using CyberGIS-Jupyter for water
HS-8. Approach-8 Using Sciunit in CUAHSI JupyterHub
HS-9. Approach-9 Using Sciunit in CyberGIS-Jupyter for water

Lastly, we created a notebook for performance tests using the different reproducible approaches.
HS-10. Jupyter notebook for performance test using the different reproducible approaches

In addition, there are three GitHub repositories for reproducible approaches in related resources in the reference section.
Git-1. Approach-10 Using Binder
Git-2. Description of Approach-3 to show how to create Docker environments
Git-3. Description of Approach-4 and 11 to show how to use a Singularity image in HPC

Subject Keywords

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Resource Level Coverage

Spatial

Coordinate System/Geographic Projection:
WGS84 EPSG:4326
Coordinate Units:
['Decimal degrees']
North Latitude
43.0707°
East Longitude
-116.7495°
South Latitude
43.0630°
West Longitude
-116.7592°

Temporal

Start Date:
End Date:

Collection Contents

Add Title Type Owners Sharing Status My Permission Remove
Remote Approach-11: Using HPC Cluster (Rivanna: HPC at University of Virginia) for the reproducibility of SUMMA modeling ModelProgramResource Zhiyu/Drew Li Public & Shareable Open Access
The Impact of Lateral Flow Parameterizations on Runoff of SUMMA Model at Reynolds Mountain East1 ModelInstanceResource Young-Don Choi Public & Shareable Open Access
The Impact of Stomatal Resistance Parameterizations on ET of SUMMA Model in Aspen stand at Reynolds Mountain East ModelInstanceResource Young-Don Choi Public & Shareable Open Access
Remote Approach-7: Using CyberGIS-Jupyer for water for the reproducibility of SUMMA modeling CompositeResource Young-Don Choi Public & Shareable Open Access
Remote Approach-6: Using CUAHSI JupyterHub for the reproducibility of SUMMA modeling CompositeResource Young-Don Choi Public & Shareable Open Access
Remote Approach-9: Using Sciunit in CyberGIS-Jupyer for water for the reproducibility of SUMMA modeling CompositeResource Young-Don Choi Public & Shareable Open Access
Remote Approach-8: Using Sciunit in CUAHSI JupyterHub for the reproducibility of SUMMA modeling CompositeResource Young-Don Choi Public & Shareable Open Access
Virtual Box image for reproducibility of SUMMA modeling using Local Approach-1, 2, 3, 4, and 5 CompositeResource Young-Don Choi Public & Shareable Open Access
Jupyter notebook for performance test using the different reproducible approaches CompositeResource Young-Don Choi Public & Shareable Open Access

References

Credits

Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
National Science Foundation EarthCube Data Capabilities: Collaborative Research: Integration of Reproducible Methods into Community Cyberinfrastructure ICER-1928369, ICER-1928315

How to Cite

Choi, Y., J. Goodall, J. Nguyen, R. Ahmad, T. Malik, Z. Li, A. M. Castronova, S. Wang, I. Maghami, D. Tarboton (2021). Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems, HydroShare, http://www.hydroshare.org/resource/3a2686a69e6e4f07a85e4dcc4f017ba9

This resource is shared under the Creative Commons Attribution CC BY.

 http://creativecommons.org/licenses/by/4.0/
CC-BY

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