aaraney / hydrodata Goto Github PK

Package	Description	Status
Hydrodata	Access NWIS, HCDN 2009, NLCD, and SSEBop databases
PyGeoOGC	Send queries to any ArcGIS RESTful-, WMS-, and WFS-based services
PyGeoUtils	Convert responses from PyGeoOGC's supported web services to datasets
PyNHD	Navigate and subset NHDPlus (MR and HR) using web services
Py3DEP	Access topographic data through National Map's 3DEP web service
PyDaymet	Access Daymet for daily climate data both single pixel and gridded

🚨 This package is under heavy development and breaking changes are likely to happen. 🚨

Hydrodata is a stack of Python libraries designed to aid in watershed analysis through web services. Currently, it only includes hydrology and climatology data within the US. Some of the major capabilities of Hydrodata are:

• Easy access to many web services for subsetting data and returning the requests as masked xarrays or GeoDataFrames.
• Splitting large requests into smaller chunks under-the-hood since web services usually limit the number of items per request. So the only bottleneck for subsetting the data is the local available memory.
• Navigating and subsetting NHDPlus database (both meduim- and high-resolution) using web services.
• Cleaning up the vector NHDPlus data, fixing some common issues, and computing vector-based accumulation through the network.
• A URL inventory for some of the popular (and tested) web services.
• Some utilities for manipulating the data and visualization.

You can visit examples webpage to see some example notebooks. You can also try using Hydrodata without installing it on you system by clicking on the binder badge below the Hydrodata banner. A Jupyter notebook instance with the Hydrodata software stack pre-installed will be launched in your web browser and you can start coding!

The full documentation can be found at https://hydrodata.readthedocs.io.

Hydrodata itself has three main modules; hydrodata, plot, and helpers. The hydrodata module provides access to the following web services:

• NWIS for daily mean streamflow observations,
• HCDN 2009 for identifying sites where human activity affects the natural flow of the watercourse,
• NLCD 2016 for land cover/land use, imperviousness, and canopy data,
• SSEBop for daily actual evapotranspiration, for both single pixel and gridded data.

Also, it has two other functions:

• interactive_map: Interactive map for exploring NWIS stations within a bounding box.
• cover_statistics: Compute categorical statistics of land use/land cover data.

The plot module includes two main functions:

• signatures: Plot five hydrologic signature graphs.
• cover_legends: Return the official NLCD land cover legends for plotting a land cover dataset.

The helpers module includes:

• nlcd_helper: A roughness coefficients lookup table for each land cover type which is useful for overland flow routing among other applications.
• nwis_error: A dataframe for finding information about NWIS requests' errors.

Moreover, requests for additional databases and functionalities can be submitted via issue tracker.

You can install Hydrodata using pip after installing libgdal on your system (for example, in Ubuntu run sudo apt install libgdal-dev):

$ pip install hydrodata

Alternatively, Hydrodata can be installed from the conda-forge repository using Conda:

$ conda install -c conda-forge hydrodata

Hydrodata offers some limited analysis tools. It could be more useful for the watershed modeling community to integrate more data exploratory and analysis capabilities to the package. Additionally, adding support for more databases such as water quality, phenology, and water level, are very welcome. If you are interested please get in touch. You can find more information about contributing to Hydrodata at our Contributing webpage.

This package was created based on the audreyr/cookiecutter-pypackage project template.