Please wait for the process to complete.
Checking for non-preferred file/folder path names (may take a long time depending on the number of files/folders) ...
This resource contains some files/folders that have non-preferred characters in their name. Show non-conforming files/folders.
||This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (email@example.com) for information on this resource.|
|Storage:||The size of this resource is 4.1 MB|
|Created:||Sep 19, 2019 at 8:27 p.m.|
|Last updated:|| Nov 11, 2019 at 4:37 p.m.
|Citation:||See how to cite this resource|
|+1 Votes:||1 other +1 this|
Hydrologic models are growing in complexity: spatial representations, model coupling, process representations, software structure, etc. New and emerging datasets are growing, supporting even more detailed modeling use cases. This complexity is leading to the reproducibility crisis in hydrologic modeling and analysis. We argue that moving hydrologic modeling to the cloud can help to address this reproducibility crisis.
- We create two notebooks:
1. The first notebook demonstrates the process of collecting and manipulating GIS and Time-series data using GRASS GIS, Python and R to create RHESsys Model input.
2. The second notebook demonstrates the process of model compilation, parallel simulation, and visualization.
- The first notebook includes:
1. Create Project Directory and Download Raw GIS Data from HydroShare
2. Set GRASS Database and GISBASE Environment
3. Preprocessing GIS Data for RHESsys Model using GRASS GIS and R script
4. Preprocess Time series data for RHESsys Model
5. Construct worldfile and flowtable to RHESSys
- The second notebook includes:
1. Download and compile RHESsys Execution file
2. Simulate RHESsys model
3. Plotting RHESsys output
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.http://creativecommons.org/licenses/by/4.0/