hydroviz

Visualization of hydrological futures data from the Southeast CASC.

Read a project description here. Read a paper (Regan and others, 2018) about the Precipitation-Runoff Modeling System (PRMS) here. The source data can be found here.

How to use this codebase

• This codebase uses the snap-geo conda environment, details found here.

• Use download.ipynb if you want to download a copy of the data (requires install of sciencebasepy into snap-geo). Be warned, there are problems with downloading the data via the sciencebasepy API, and therefore some of this process is manual point-and-click tedium. For testing, it's recommended to just access the data from this directory instead: /import/beegfs/CMIP6/jdpaul3/hydroviz_data

• Use the eda.ipynb notebook to familiarize yourself with the dataset structure.

• To coerce the data into a netCDF format, run the following command to submit an sbatch script. Change the script locations to match your repo location, and change the --output_dir argument to save the netCDF files to a different location and avoid overwriting previous outputs. The script should only take ~5 minutes to run once compute resources are allocated.

python run_build_nc.py --data_dir /beegfs/CMIP6/jdpaul3/hydroviz_data/stats --output_dir /beegfs/CMIP6/jdpaul3/hydroviz_data/nc --conda_init_script /beegfs/CMIP6/jdpaul3/hydroviz/conda_init.sh --conda_env_name snap-geo --build_nc_script /beegfs/CMIP6/jdpaul3/hydroviz/build_nc.py

• Use the qc.ipynb notebook to compare values in the netCDFs to source values.