HS-1. Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems


Authors:
Owners: This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource.
Type: Collection
Storage: The size of this collection is 2.4 KB
Created: Nov 24, 2020 at 7:05 a.m.
Last updated: Jan 29, 2023 at 1 p.m.
Citation: See how to cite this resource
Sharing Status: Public
Views: 1586
Downloads: 41
+1 Votes: Be the first one to 
 this.
Comments: No comments (yet)

Abstract

This is a collection resource for "Comparing containerization-based approaches for reproducible computational modeling of environmental systems" manuscript in Environmental Modeling and Software Journal.
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

Then there is a HS resource for reproducible approaches in local computational environments.
HS-4. 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

Next, there are four HS resources and a GitHub repository for reproducible approaches in remote computational environments.
HS-5. Approach-6 Using CUAHSI JupyterHub
HS-6. Approach-7 Using CyberGIS-Jupyter for water
HS-7. Approach-8 Using Sciunit in CUAHSI JupyterHub
HS-8. Approach-9 Using Sciunit in CyberGIS-Jupyter for water
Git-1. Approach-10 Using Binder (https://github.com/uva-hydroinformatics/SUMMA_Binder.git)

Lastly, we created a notebook for performance tests using the different reproducible approaches.
HS-9. Jupyter notebook for performance test using the different reproducible approaches

For additional description, we created two GitHub repositories to show how to create Docker and Singularity image for Approach-2,3, and 4.
Git-2. Description of Approach-3 to show how to create Docker environments (https://github.com/uva-hydroinformatics/SUMMA_Docker_Training.git)
Git-3. Description of Approach-4 to show how to use a Singularity image (https://github.com/uva-hydroinformatics/SUMMA_Singularity_In_Rivanna.git)

As a result, we shared a created Singularity image for a model program resource.
HS-10: A singularity image for the reproducibility of SUMMA modeling

Subject Keywords

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:

Related Resources

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 (2023). HS-1. 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

Comments

There are currently no comments

New Comment

required