wells4hydrogeology

Wells 4 Hydrogeology (w4h)

The w4h Python package is a package designed jointly by the Illinois State Geological Survey and Illinois State Water Survey.

It is designed to read in geology data from wells and create a layered, gridded hydrogeologic model of a study region, all within a python environment, automating and performing tasks often carried out in a dedicated GIS software.

The w4h package contains all the functions needed for getting N layers of a hydrogeology grid. Though the source code is split into separate modules, all functions are designed to be accessed directly from the w4h module (example: w4h.read_study_area())

The w4h module is designed to be flexible and customizable, allowing various kinds of data to be read in, with many different kinds of initial structures.

Using well descriptions from these database tables, the code contained here extracts, manipulates, and organizes the data to be used for hydrogeologic modeling. The scripts here can be used for specific regions of interests/study areas within the state, or for the state as a whole.

API Documentation

API Documentation here

Dependencies

The w4h module has the following dependencies:

• numpy
• geopandas (and therefore pandas)
• rioxarray (and therefore xarray)
• matplotlib
• scipy
• owslib

Inputs

Required Inputs

Required inputs include are shown herewiki

Organization

Modules

The package is organized by module, but all functions can be accessed directly using w4h.function_name() as well.

• core: general utility functions used throughout
• classify: functions for classifying the data
• clean: functions for cleaning the data
• export: functions for exporting the data, both as tables and rasters
• layers: functinos for generating layer(ed) models
• mapping: functions for mapping or performing geospatial analysis
• read: functions for reading in various files

Intended workflow

Diagram for workflow available here.

Disclaimers

wells4hydrogeology is a python tool developed jointly by the Illinois State Water Survey and the Illinois State Geological Survey, both part of the Prairie Research Institute at the University of Illinois. By using this repository, you agree to the Terms of Use contained in the Data Use License Agreement.