Skip to main content

Robust automation of MODFLOW model construction.

Project description

Modflow-setup

Modflow-setup is a Python package for automating the setup of MODFLOW groundwater models from grid-independent source data including shapefiles, rasters, and other MODFLOW models that are geo-located. Input data and model construction options are summarized in a single configuration file. Source data are read from their native formats and mapped to a regular finite difference grid specified in the configuration file. An external array-based Flopy model instance with the desired packages is created from the sampled source data and configuration settings. MODFLOW input can then be written from the flopy model instance.

Version 0.2

Tests codecov PyPI version Binder Project Status: Active – The project has reached a stable, usable state and is being actively developed.

Getting Started

For more details, see the modflow-setup documentation

Using a yaml-aware text editor, create a configuration file similar to one of the examples in the Configuration File Gallery.

The yaml file summarizes source data and parameter settings for setting up the various MODFLOW packages. To set up the model:

from mfsetup import MFnwtModel, MF6model

m = MF6model.setup_from_yaml(<path to configuration file>)

where m is a flopy MODFLOW-6 model instance that is returned. The MODFLOW input files can be written from the model instance:

m.simulation.write_simulation()

MODFLOW-NWT version:

m = MFnwtModel.setup_from_yaml(<path to configuration file>)
m.write_input()

Installation

See the Installation Instructions

How to cite

Citation for Modflow-setup

Leaf AT and Fienen MN (2022) Modflow-setup: Robust automation of groundwater model construction. Front. Earth Sci. 10:903965. https://doi.org/10.3389/feart.2022.903965

Software/Code Citation for Modflow-setup

Leaf, A.T. and Fienen, M.N. (2022). Modflow-setup version 0.1, U.S. Geological Survey Software Release, 30 Sep. 2022. https://doi.org/10.5066/P9O3QWQ1

MODFLOW Resources

Disclaimer

This software is preliminary or provisional and is subject to revision. It is being provided to meet the need for timely best science. The software has not received final approval by the U.S. Geological Survey (USGS). No warranty, expressed or implied, is made by the USGS or the U.S. Government as to the functionality of the software and related material nor shall the fact of release constitute any such warranty. The software is provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the software. It is the responsibility of the user to check the accuracy of the results.

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

modflow-setup-0.3.0.tar.gz (301.7 kB view details)

Uploaded Source

Built Distribution

modflow_setup-0.3.0-py3-none-any.whl (275.3 kB view details)

Uploaded Python 3

File details

Details for the file modflow-setup-0.3.0.tar.gz.

File metadata

  • Download URL: modflow-setup-0.3.0.tar.gz
  • Upload date:
  • Size: 301.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.4

File hashes

Hashes for modflow-setup-0.3.0.tar.gz
Algorithm Hash digest
SHA256 a7253936d86b8fec7c26b50e64c0e1cfd08132902215d859c0e63cd44421ecb5
MD5 ea5b47827cf7a6160d328926da313ece
BLAKE2b-256 8cce816dd30d489f3731f7c02226642ce79fe57781e0f38fdc1f7054b9be8cc6

See more details on using hashes here.

File details

Details for the file modflow_setup-0.3.0-py3-none-any.whl.

File metadata

File hashes

Hashes for modflow_setup-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 9b3a6f1de3202048b7656f350e185d5015451173b5b3b76ffa846691fbf245f7
MD5 9e8f3792e7902ed29f79528f637d234c
BLAKE2b-256 6a84fe856802b4e98794bbdf9e279828729b1cf28b60837f4ca34455f32440c3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page