M3: Open Science for Water Resources

What tools and datasets are available to quantify water quantity and availability?

The third module of our open climate-science curriculum focuses on how to begin a reproducible computational science project, using water resources as a thematic example. At the end of this module, you should be able to:

• Describe the major fluxes and pools of the terrestrial water cycle;
• Know where to access remotely sensed or modeled data on water storage anomalies, evapotranspiration, and soil moisture;
• Calculate a water budget.

Contents

1. Creating a Research Software Environment
2. Analyzing a Global Precipitation Data Cube
3. Tracking Changes to Research Code
4. Creating a Basin-Scale Water Budget
5. Documenting our Water Budget Workflow

Getting Started

See our installation guide here.

You can run the notebooks in this repository using Github Codespaces or as a VSCode Dev Container. Once your container is running, launch Jupyter Notebook by:

# Create your own password when prompted
jupyter server password

# Then, launch Jupyter Notebook; enter your password when prompted
jupyter notebook

The Python libraries required for the exercises can be installed using the pip package manager:

pip install xarray netcdf4 dask

The required data for this lesson can be downloaded here, from Zenodo.

Learning Outcomes

This course covers the following Core Competencies in Computational Data Science:

• Chooses meaningful filenames (CC1.3)
• Records relationships between code, results, and metadata (CC1.5)
• Uses a package manager to install and manage software dependencies (CC1.10)
• Understands multi-dimensional arrays (CC2.3)
• Can scale up a computational workflow (CC2.6)
• Chooses variable names that are clear and informative (CC3.8)
• Understands software releases and versioning (CC4.4)
• Uses assertions to verify assumptions as runtime (CC4.7)
• Writes short, simple functions that have no side effects (CC4.9)

In addition, learners will see how to:

• Install and manage Python packages
• Merge multiple HDF files together into an xarray.Dataset
• Subset an xarray.Dataset using an ERSI Shapefile
• Clip and reproject raster data based on an ESRI Shapefile
• Compute a water budget using precipitation, evapotranspiration, and runoff data
• Use Git and Github to track and back-up changes to research software

Climate Datasets Used

• Monthly precipitation totals from NASA IMERG-Final
• Annual evapotranspiration data from NASA's MODIS MOD16 product
• Terrestrial water storage anomalies from the NASA GRACE and GRACE-FO missions
• Runoff data from the HYSETS database

Acknowledgements

This curriculum was enabled by a grant from NASA's Transition to Open Science (TOPS) Training program (80NSSC23K0864), part of NASA's TOPS Program