- Introduction: Water data, Python and You (presentation) - Bart Nijssen
- Access and analyze point time series data (notebook) - Yifan Cheng
- Access and analyze raster and multi-dimensional gridded data - Steven Pestana
- Notebook 0: NumPy and the ndarray
- Notebook 1: Introduction to xarray
- Notebook 2: Daymet data access
- Notebook 3: Investigating SWE at Mt. Rainier with Daymet
- Water data mash up (notebook) - Emilio Mayorga
For a quick and easy exploration of this watershed (or any other HUC in the lower 48), you can go to https://modelmywatershed.org. Type "upper yakima" in the text box in the upper right, select the HUC 8 Upper Yakima entry, then click on the Select button that comes up. You can add geospatial context via the Layers box (streams/grids/boundaries), and get quick view of the distribution of general watershed properties (precip/air temp/elev/slope/stream order) on the column to the left.
Use the environment.yml file found in this repository.
conda env create -f environment.yml
conda activate whwwaterdata- Data access and time-series statistics cyberseminar
- Gridded climate data(sets) cyberseminar
- Observatory for Gridded Hydrometeorology (OGH)? See also this OGH presentation.. We didn't use this package in these tutorials, but they share goals.
- GeoHackWeek 2019 vector tools. https://geohackweek.github.io/vector/
- GeoHackWeek 2019 raster tools. https://github.com/geohackweek/raster-2019
- GeoHackWeek 2020 tutorials: https://oceanhackweek.github.io/ohw-resources/schedule/ and https://github.com/oceanhackweek/ohw20-tutorials