Checking for non-preferred file/folder path names (may take a long time depending on the number of files/folders) ...
This resource contains some files/folders that have non-preferred characters in their name. Show non-conforming files/folders.
This resource contains content types with files that need to be updated to match with metadata changes. Show content type files that need updating.
Authors: |
|
|
---|---|---|
Owners: |
|
This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource. |
Type: | Resource | |
Storage: | The size of this resource is 129.6 KB | |
Created: | Aug 31, 2021 at 4:21 a.m. | |
Last updated: | Oct 06, 2024 at 1:10 a.m. | |
Citation: | See how to cite this resource |
Sharing Status: | Public |
---|---|
Views: | 4495 |
Downloads: | 1451 |
+1 Votes: | Be the first one to this. |
Comments: | No comments (yet) |
Abstract
This resource contains a set of Jupyter Notebooks that provide Python code examples for using the Python dataretrieval package for retrieving data from the United States Geological Survey's (USGS) National Water Information System (NWIS).The dataretrieval package is a Python alternative to USGS-R's dataRetrieval package for the R Statistical Computing Environment used for obtaining USGS or Environmental Protection Agency (EPA) water quality data, streamflow data, and metadata directly from web services. The dataretrieval Python package is an alternative to the R package, not a port, in that it reproduces the functionality of the R package but its organization and functionality differ to some degree. The dataretrieval package was originally created by Timothy Hodson at USGS. Additional contributions to the Python package and these Jupyter Notebook examples were created at Utah State University under funding from the National Science Foundation. A link to the GitHub source code repository for the dataretrieval package is provided in the related resources section below.
Subject Keywords
Content
readme.md
Introduction
This resource contains Jupyter Notebooks that serve as examples of how to use the USGS dataretrieval Python package to retrieve data from the United States Geological Survey's National Water Information System. These notebooks can either be downloaded and run in your local environment, or they can be launched into the CUAHSI JupyterHub server. The following notebooks are provided:
- USGS_dataretrieval_DailyValues_Examples.ipynb: This notebook demonstrates how to use the
get_dv()
function to retrieve daily values (e.g., daily streamflow values) for USGS monitoring sites. - USGS_dataretrieval_GroundwaterLevels_Examples.ipynb: This notebook demonstrates how to use the
get_gwlevels()
function to retrieve groundwater level data for USGS monitoring sites. - USGS_dataretrieval_Measurements_Examples.ipynb: This notebook demonstrates how to use the
get_discharge_measurements()
function to retrieve surface water discharge measurements for USGS monitoring sites. - USGS_dataretrieval_NLDI_Examples.ipynb: This notebook demonstrations how to use multiple functions to access data from the USGS Hydro Network-Linked Data Index (NLDI).
- USGS_dataretrieval_ParameterCodes_examples.ipynb: This notebook demonstrates how to use the
get_pmcodes()
function to retrieve information about USGS NWIS parameter codes. - USGS_dataretrieval_Peaks_examples.ipynb: This notebook demonstrates how to use the
get_discharge_peaks()
function to retrieve peack discharge data for USGS NWIS monitoring sites. - USGS_dataretrieval_Ratings_Examples.ipynb: This notebook demonstrates how to use the
get_ratings()
function to retrieve rating curve data for USGS monitoring sites. - USGS_dataretrieval_SiteInfo_Examples.ipynb: This notebook demonstrates how to use the
get_info()
function to retrieve information about a USGS monitoring site. - USGS_dataretrieval_SiteInventory_Examples.ipynb: This notebook demonstrates how to use the
what_sites()
function to search NWIS for sites within a region with specific data. - USGS_dataretrieval_Statistics_Examples.ipynb: This notebook demonstrate how to use the
get_stats()
function to retrieve site statistics for USGS monitoring sites. - USGS_dataretrieval_UnitValues_Examples.ipynb: This notebook demonstrates how to use the
get_iv()
function to retrieve instantaneous (unit) value data for USGS monitoring sites. - USGS_dataretrieval_WaterSamples_Examples.ipynb: This notebook demonstrates how to use the
get_qwdata()
function to retrieve water quality sample data for USGS monitoring sites. - USGS_dataretrieval_WaterUse_Examples.ipynb: This notebook demonstrates how to use the
get_water_use()
function to retrieve water use data.
Run these Notebooks Locally
If you want to run these notebooks locally on your machine, you will need to be set up to run Jupyter notebooks. If you need help setting up Jupyter to run notebooks, you can consult the Jupyter/IPython Notebook Quick Start Guide.
There are also Python Interactive Development Environments (IDEs) like PyCharm that have support for creating, editing, and running Jupyter Notebooks.
Run these Notebooks on the CUAHSI JupyterHub Server
CUAHSI maintains a HydroShare linked JupyterHub server on which you can run these notebooks. To run these notebooks using CUAHSI's JupyterHub Server, do the following:
- Make sure you have a HydroShare user account and then join the CUAHSI Cloud Computing group in HydroShare.
- Make sure you are logged into HydroShare and then click on the "Open with" button at the top of this resource's landing page and select "CUAHSI JupyterHub."
- If prompted, agree to the terms of use and click the "Sign in with HydroShare" button. You will need to click the "Authorize" button to authorize CUAHSI JupyterHub to interact with your HydroShare account.
- Once your content has been copied to the CUAHSI JupyterHub server (this may take a couple of minutes), click on the name of the notebook you want to execute.
- This will launch the Jupyter Notebook and you can execute it using the controls at the top of the notebook.
Related Resources
This resource is described by | GitHub repository for the USGS Python dataretrieval package: https://github.com/USGS-python/dataretrieval |
Credits
Funding Agencies
This resource was created using funding from the following sources:
Agency Name | Award Title | Award Number |
---|---|---|
United States Geological Survey | ||
National Science Foundation | Collaborative Research: Elements: Advancing Data Science and Analytics for Water (DSAW) | 1931297 |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
Comments
There are currently no comments
New Comment