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docs: update version; release history; add applications and workflow sections
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Readme.md

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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](https://github.com/modflowpy/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.
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### Version 0.3
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### Version 0.4
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![Tests](https://github.com/doi-usgs/modflow-setup/workflows/Tests/badge.svg)
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[![codecov](https://codecov.io/gh/doi-usgs/modflow-setup/branch/develop/graph/badge.svg?token=aWN47DYeIv)](https://codecov.io/gh/doi-usgs/modflow-setup)
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[![PyPI version](https://badge.fury.io/py/modflow-setup.svg)](https://badge.fury.io/py/modflow-setup)
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Applications of Modflow-setup
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Fienen, M.N., Corson-Dosch, N.T., White, J.T., Leaf, A.T. and Hunt, R.J. (2022), Risk-Based Wellhead Protection Decision Support: A Repeatable Workflow Approach. Groundwater, 60: 71-86. https://doi.org/10.1111/gwat.13129
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Fienen, M.N., Haserodt, M.J., Leaf, A.T., and Westenbroek, S.M., 2022, Simulation of regional groundwater flow and groundwater/lake interactions in the Central Sands, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2022–5046, 111 p., https://doi.org/10.3133/sir20225046.
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Leaf, A.T., Duncan, L.L., Haugh, C.J., Hunt, R.J., and Rigby, J.R., 2023, Simulating groundwater flow in the Mississippi Alluvial Plain with a focus on the Mississippi Delta: U.S. Geological Survey Scientific Investigations Report 2023–5100, 143 p., https://doi.org/10.3133/sir20235100.
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Workflow examples
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-----------------------------------------------
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Fienen, M.N, and Corson-Dosch, N.T., 2021, Groundwater Model Archive and Workflow for Neversink/Rondout Basin, New York, Source Water Delineation: U.S. Geological Survey data release, https://doi.org/10.5066/P9HWSOHP.
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Fienen, M.N., Corson-Dosch, N.T., White, J.T., Leaf, A.T. and Hunt, R.J. (2022), Risk-Based Wellhead Protection Decision Support: A Repeatable Workflow Approach. Groundwater, 60: 71-86. https://doi.org/10.1111/gwat.13129
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Leaf, A.T., Duncan, L.L., and Haugh, C.J., 2023, MODFLOW 6 models for simulating groundwater flow in the Mississippi Embayment with a focus on the Mississippi Delta: U.S. Geological Survey data release, https://doi.org/10.5066/P971LPOB.
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MODFLOW Resources
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docs/source/references.rst

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Langevin, C.D., Hughes, J.D., Banta, E.R., Niswonger, R.G., Panday, Sorab, and Provost, A.M., 2017, Documentation for the MODFLOW 6 Groundwater Flow Model: U.S. Geological Survey Techniques and Methods, book 6, chap. A55, 197 p., https://doi.org/10.3133/tm6A55.
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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
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Niswonger, R.G., Panday, S., and Ibaraki, M., 2011, MODFLOW–NWT—A Newton formulation for MODFLOW–2005: U.S. Geological Survey Techniques and Methods, book 6, chap. A37, 44 p. https://doi.org/10.3133/tm6A45
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Westenbroek, S.M., Engott, J.A., Kelson, V.A., and Hunt, R.J., 2018, SWB Version 2.0—A soil-water-balance code for estimating net infiltration and other water-budget components: U.S. Geological Survey Techniques and Methods, book 6, chap. A59, 118 p., https://doi.org/10.3133/tm6A59.
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Wisconsin Department of Natural Resources (WDNR), 2021. Central Sands Lake Study Report: Findings and Recommendations. Report to the Wisconsin State Legislature. https://doi.org/10.5281/zenodo.5708791
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Modflow-setup applications
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######################################
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Fienen, M.N., Corson-Dosch, N.T., White, J.T., Leaf, A.T. and Hunt, R.J. (2022), Risk-Based Wellhead Protection Decision Support: A Repeatable Workflow Approach. Groundwater, 60: 71-86. https://doi.org/10.1111/gwat.13129
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Fienen, M.N., Haserodt, M.J., Leaf, A.T., and Westenbroek, S.M., 2022, Simulation of regional groundwater flow and groundwater/lake interactions in the Central Sands, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2022–5046, 111 p., https://doi.org/10.3133/sir20225046.
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Leaf, A.T., Duncan, L.L., Haugh, C.J., Hunt, R.J., and Rigby, J.R., 2023, Simulating groundwater flow in the Mississippi Alluvial Plain with a focus on the Mississippi Delta: U.S. Geological Survey Scientific Investigations Report 2023–5100, 143 p., https://doi.org/10.3133/sir20235100.
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Workflow examples
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################################
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Fienen, M.N, and Corson-Dosch, N.T., 2021, Groundwater Model Archive and Workflow for Neversink/Rondout Basin, New York, Source Water Delineation: U.S. Geological Survey data release, https://doi.org/10.5066/P9HWSOHP.
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Leaf, A.T., Duncan, L.L., and Haugh, C.J., 2023, MODFLOW 6 models for simulating groundwater flow in the Mississippi Embayment with a focus on the Mississippi Delta: U.S. Geological Survey data release, https://doi.org/10.5066/P971LPOB.

docs/source/release-history.rst

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Release History
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===============
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Version 0.4.0 (2024-01-15)
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* Improvements to lake package
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* Add automatic writing of lake polygon and lake cell connection shapefiles
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* Add name_column arg to shapefile input (which adds names to lake auxiliary tables)
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* Allow PRISM input to be specified for all lakes (via single filename instead of dictionary)
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* Allow specification of lakes_shapefile: without include_ids: item
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* Move output tables to tables/ folder
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* Pre-defined stress periods
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* Allow stress period data to be pre-defined in a CSV file, which allows for more complicated or irregular stress period configurations that would otherwise require many group blocks; for example 7-day periods that always start on the same day of the year, which results in an extra period of 1 or 2 days at the end of each year.
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* Bug fixes
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* fix issue with identifier column dtypes, so that NHDPlus Hi-Res COMIDs (which require 64-bits as integers) work more robustly on Windows.
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* in case of pre-defined (csvfile) stress periods, base perlen on end_datetime - start_datetime (what you see is what you get, and so that gaps between stress periods don't affect perlen); add trap for missing required columns
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* see commit history for other misc. fixes
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Version 0.3.1 (2023-08-17)
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* change 'boundname_col' argument in basic stress CSV input to 'boundname_column' for consistency with other inputs.
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* fixes to `grid.rasterize()` to better handle 64-bit integer and `object` dtypes
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* update example configuration files to use new length unit arguments in `sfrmaker>=0.11.1`
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Version 0.3.0 (2023-07-25)
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