Jupyter Notebooks to demonstrate RHESsys model on Paine run of Shenandoah National Park in Rivanna HPC

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