Welcome to the Data-Acquisition-Processing-Analysis Tutorial repository. The modules in this repository are designed to provide a comprehensive introduction to modern, programmatic workflows for hydrological and meteorological data retrieval and analysis.
In the modules, we move away from manual data downloads (CSV/Excel) and toward API-driven reproducible research. You will learn how to delineate watersheds, pull long-term streamflow records, and integrate satellite-based snow and vegetation data.
Watershed Data: Automated delineation and catchment characteristic retrieval.
Streamflow: Accessing USGS NWIS and global runoff databases.
Meteorological Data: Integrating precipitation, temperature, and evapotranspiration grids.
Snow Hydrology: Analyzing Snow Water Equivalent (SWE) and snow cover extent.
Landsat & Remote Sensing: Utilizing multispectral imagery for land cover and water quality monitoring.
We utilize three primary library ecosystems to handle these complex datasets:
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HyRiver The HyRiver suite is a powerful collection of Python packages designed for easy access to hydro-geospatial data via various web services (USGS, NHDPlus, etc.).
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NSIDC (National Snow and Ice Data Center) We utilize the NSIDC data access tools to pull critical snow-pack data. This is essential for understanding the seasonal water availability in mountain-west watersheds.
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Google Earth Engine (GEE) For large-scale remote sensing (Landsat), we use the ee Python API. This allows us to process petabytes of satellite imagery on Google's cloud infrastructure without downloading massive files locally.
Environment Setup To ensure all libraries (especially GDAL and HyRiver dependencies) work correctly, each module will have its own conda environment.