Developed with funding from the U.S. EPA Exchange Network

Well Application

Set of tools for groundwater level and water chemistry analysis. Allows for rapid download and graphing of data from the USGS NWIS database and the Water Quality Portal.

Installation

Wellapplication should be compatible with both Python 2.7 and 3.5. It has been tested most rigously on Python 2.7. It should work on both 32 and 64-bit platforms. I have used it on Linux and Windows machines. To install the most recent version, use pip.

pip install wellapplication

Modules

transport

This module:

• allows a user to upload data from an .xle file common with some water well transducers.

• matches well and barometric data to same sample intervals

• adjust with manual measurements

• removes skips and jumps from data

This class has functions used to import transducer data and condition it for analysis. The most important function in this library is newxleimp, which uses the path and filename of an xle file, commonly produced by pressure transducers, to convert that file into a Pandas DataFrame. A Jupyter Notebook using some of the transport functions can be found WLData.ipynb>here.

usgs

This module has functions used to apply the USGS's rest-based api to download USGS data by leveraging requests package and Pandas. The most powerful class in this module is nwis. It is called by nwis(service, location value, location type). The main USGS services are dv for daily values, iv for instantaneous values, gwlevels for groundwater levels, and site for site information. The nwis class allows for rapid download of NWIS data.

>>> import wellapplication as wa
 >>> discharge = wa.nwis('dv','10109000','sites')
 >>> site_data = discharge.sites
 >>> flow_data = discharge.data

A Jupyter Notebook using some of the usgs functions can be found here.