Scripting MODFLOW Model Development Using Python and FloPy

Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages avai...

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Bibliographic Details
Published in:	Ground water Vol. 54; no. 5; pp. 733 - 739
Main Authors:	Bakker, M., Post, V., Langevin, C. D., Hughes, J. D., White, J. T., Starn, J. J., Fienen, M. N.
Format:	Journal Article
Language:	English
Published:	Malden, US Blackwell Publishing Ltd 01.09.2016
Subjects:	computer software Groundwater groundwater flow Humans hydrologic models Models, Theoretical Programming Languages Python Water Movements
ISSN:	0017-467X, 1745-6584, 1745-6584
Online Access:	Get full text
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Abstract	Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis. For MODFLOW‐based models, the FloPy package was developed by the authors to construct model input files, run the model, and read and plot simulation results. Use of Python with the available scientific packages and FloPy facilitates data exploration, alternative model evaluations, and model analyses that can be difficult to perform with GUIs. Furthermore, Python scripts are a complete, transparent, and repeatable record of the modeling process. The approach is introduced with a simple FloPy example to create and postprocess a MODFLOW model. A more complicated capture‐fraction analysis with a real‐world model is presented to demonstrate the types of analyses that can be performed using Python and FloPy. Article Impact Statement: Python/FloPy scripts are a powerful approach to build and analyze MODFLOW‐based models and are a full record of the entire modeling process.
AbstractList	Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis. For MODFLOW‐based models, the FloPy package was developed by the authors to construct model input files, run the model, and read and plot simulation results. Use of Python with the available scientific packages and FloPy facilitates data exploration, alternative model evaluations, and model analyses that can be difficult to perform with GUIs. Furthermore, Python scripts are a complete, transparent, and repeatable record of the modeling process. The approach is introduced with a simple FloPy example to create and postprocess a MODFLOW model. A more complicated capture‐fraction analysis with a real‐world model is presented to demonstrate the types of analyses that can be performed using Python and FloPy. Article Impact Statement: Python/FloPy scripts are a powerful approach to build and analyze MODFLOW‐based models and are a full record of the entire modeling process. Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis. For MODFLOW-based models, the FloPy package was developed by the authors to construct model input files, run the model, and read and plot simulation results. Use of Python with the available scientific packages and FloPy facilitates data exploration, alternative model evaluations, and model analyses that can be difficult to perform with GUIs. Furthermore, Python scripts are a complete, transparent, and repeatable record of the modeling process. The approach is introduced with a simple FloPy example to create and postprocess a MODFLOW model. A more complicated capture-fraction analysis with a real-world model is presented to demonstrate the types of analyses that can be performed using Python and FloPy. Article Impact Statement: Python/FloPy scripts are a powerful approach to build and analyze MODFLOW-based models and are a full record of the entire modeling process. Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis. For MODFLOW-based models, the FloPy package was developed by the authors to construct model input files, run the model, and read and plot simulation results. Use of Python with the available scientific packages and FloPy facilitates data exploration, alternative model evaluations, and model analyses that can be difficult to perform with GUIs. Furthermore, Python scripts are a complete, transparent, and repeatable record of the modeling process. The approach is introduced with a simple FloPy example to create and postprocess a MODFLOW model. A more complicated capture-fraction analysis with a real-world model is presented to demonstrate the types of analyses that can be performed using Python and FloPy. Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis. For MODFLOW-based models, the FloPy package was developed by the authors to construct model input files, run the model, and read and plot simulation results. Use of Python with the available scientific packages and FloPy facilitates data exploration, alternative model evaluations, and model analyses that can be difficult to perform with GUIs. Furthermore, Python scripts are a complete, transparent, and repeatable record of the modeling process. The approach is introduced with a simple FloPy example to create and postprocess a MODFLOW model. A more complicated capture-fraction analysis with a real-world model is presented to demonstrate the types of analyses that can be performed using Python and FloPy.Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis. For MODFLOW-based models, the FloPy package was developed by the authors to construct model input files, run the model, and read and plot simulation results. Use of Python with the available scientific packages and FloPy facilitates data exploration, alternative model evaluations, and model analyses that can be difficult to perform with GUIs. Furthermore, Python scripts are a complete, transparent, and repeatable record of the modeling process. The approach is introduced with a simple FloPy example to create and postprocess a MODFLOW model. A more complicated capture-fraction analysis with a real-world model is presented to demonstrate the types of analyses that can be performed using Python and FloPy.
Author	Hughes, J. D. Post, V. Langevin, C. D. Bakker, M. White, J. T. Fienen, M. N. Starn, J. J.
Author_xml	– sequence: 1 givenname: M. surname: Bakker fullname: Bakker, M. email: mark.bakker@tudelft.nl, mark.bakker@tudelft.nl organization: E-mail: mark.bakker@tudelft.nl – sequence: 2 givenname: V. surname: Post fullname: Post, V. organization: Flinders University, Adelaide, South Australia – sequence: 3 givenname: C. D. surname: Langevin fullname: Langevin, C. D. organization: U.S. Geological Survey, VA, Reston – sequence: 4 givenname: J. D. surname: Hughes fullname: Hughes, J. D. organization: U.S. Geological Survey, VA, Reston – sequence: 5 givenname: J. T. surname: White fullname: White, J. T. organization: U.S. Geological Survey, Texas Water Science Center, TX, Austin – sequence: 6 givenname: J. J. surname: Starn fullname: Starn, J. J. organization: U.S. Geological Survey, CT, East Hartford – sequence: 7 givenname: M. N. surname: Fienen fullname: Fienen, M. N. organization: U.S. Geological Survey Wisconsin Water Science Center, WI, Middleton
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/27027984$$D View this record in MEDLINE/PubMed
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References	McKinney, W. 2012. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. Sebastopol, California: O'Reilly Media Sebastopol, CA. Leake, S.A., H.W. Reeves, and J.E. Dickinson. 2010. A new capture fraction method to map how pumpage affects surface water flow. Ground Water 48, no. 5: 690-700. Pérez, F., and B.E. Granger. 2007. IPython: A system for interactive scientific computing. Computing in Science & Engineering 9, no. 3: 21-29. Bakker, M., and V.A. Kelson. 2009. Writing analytic element programs in python. Ground Water 47, no. 6: 828-834. Oliphant, T.E. 2006. Guide to NumPy. USA: Trelgol Publishing. Pérez, F., B.E. Granger, and J.D. Hunter. 2011. Python: An ecosystem for scientific computing. Computing in Science & Engineering 13, no. 2: 13-21. Fienen, M.N., and R.J. Hunt. 2015. High-throughput computing versus high-performance computing for groundwater applications. Ground Water 53, no. 2: 180-184. Hunter, J. 2007. Matplotlib: A 2D graphics environment. Computing in Science & Engineering 9, no. 3: 90-95. Bakker, M. 2014. Python scripting: The return to programming. Ground Water 52, no. 6: 821-822. 2009; 47 2010; 48 2001 2012 2000 2015; 53 2007; 9 2008 2007 2006 2005 2011; 13 2014 2013 2014; 52 1999 e_1_2_8_17_1 e_1_2_8_18_1 e_1_2_8_19_1 e_1_2_8_15_1 e_1_2_8_16_1 e_1_2_8_3_1 Oliphant T.E. (e_1_2_8_14_1) 2006 e_1_2_8_2_1 e_1_2_8_5_1 e_1_2_8_4_1 e_1_2_8_7_1 McKinney W. (e_1_2_8_13_1) 2012 e_1_2_8_6_1 e_1_2_8_9_1 e_1_2_8_8_1 e_1_2_8_10_1 e_1_2_8_11_1 e_1_2_8_12_1
References_xml	– reference: Fienen, M.N., and R.J. Hunt. 2015. High-throughput computing versus high-performance computing for groundwater applications. Ground Water 53, no. 2: 180-184. – reference: Hunter, J. 2007. Matplotlib: A 2D graphics environment. Computing in Science & Engineering 9, no. 3: 90-95. – reference: McKinney, W. 2012. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. Sebastopol, California: O'Reilly Media Sebastopol, CA. – reference: Bakker, M., and V.A. Kelson. 2009. Writing analytic element programs in python. Ground Water 47, no. 6: 828-834. – reference: Oliphant, T.E. 2006. Guide to NumPy. USA: Trelgol Publishing. – reference: Leake, S.A., H.W. Reeves, and J.E. Dickinson. 2010. A new capture fraction method to map how pumpage affects surface water flow. Ground Water 48, no. 5: 690-700. – reference: Pérez, F., B.E. Granger, and J.D. Hunter. 2011. Python: An ecosystem for scientific computing. Computing in Science & Engineering 13, no. 2: 13-21. – reference: Pérez, F., and B.E. Granger. 2007. IPython: A system for interactive scientific computing. Computing in Science & Engineering 9, no. 3: 21-29. – reference: Bakker, M. 2014. Python scripting: The return to programming. Ground Water 52, no. 6: 821-822. – volume: 13 start-page: 13 issue: 2 year: 2011 end-page: 21 article-title: Python: An ecosystem for scientific computing publication-title: Computing in Science & Engineering – volume: 47 start-page: 828 issue: 6 year: 2009 end-page: 834 article-title: Writing analytic element programs in python publication-title: Ground Water – year: 2005 – volume: 52 start-page: 821 issue: 6 year: 2014 end-page: 822 article-title: Python scripting: The return to programming publication-title: Ground Water – volume: 48 start-page: 690 issue: 5 year: 2010 end-page: 700 article-title: A new capture fraction method to map how pumpage affects surface water flow publication-title: Ground Water – volume: 53 start-page: 180 issue: 2 year: 2015 end-page: 184 article-title: High‐throughput computing versus high‐performance computing for groundwater applications publication-title: Ground Water – year: 2001 – year: 2008 – year: 2007 – year: 2006 – volume: 9 start-page: 90 issue: 3 year: 2007 end-page: 95 article-title: Matplotlib: A 2D graphics environment publication-title: Computing in Science & Engineering – year: 2000 – volume: 9 start-page: 21 issue: 3 year: 2007 end-page: 29 article-title: IPython: A system for interactive scientific computing publication-title: Computing in Science & Engineering – year: 2014 – year: 2013 – year: 2012 – year: 1999 – ident: e_1_2_8_5_1 – ident: e_1_2_8_10_1 – ident: e_1_2_8_15_1 doi: 10.1109/MCSE.2007.53 – ident: e_1_2_8_6_1 – ident: e_1_2_8_7_1 doi: 10.3133/tm6A16 – ident: e_1_2_8_19_1 – ident: e_1_2_8_11_1 doi: 10.3133/tm6A22 – volume-title: Guide to NumPy year: 2006 ident: e_1_2_8_14_1 – ident: e_1_2_8_4_1 doi: 10.1111/gwat.12320 – volume-title: Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython year: 2012 ident: e_1_2_8_13_1 – ident: e_1_2_8_16_1 doi: 10.1109/MCSE.2010.119 – ident: e_1_2_8_2_1 doi: 10.1111/gwat.12269 – ident: e_1_2_8_8_1 doi: 10.3133/ofr200092 – ident: e_1_2_8_12_1 doi: 10.1111/j.1745-6584.2010.00701.x – ident: e_1_2_8_17_1 doi: 10.3133/tm6A41 – ident: e_1_2_8_18_1 doi: 10.3133/sir20065228 – ident: e_1_2_8_9_1 doi: 10.1109/MCSE.2007.55 – ident: e_1_2_8_3_1 doi: 10.1111/j.1745-6584.2009.00583.x
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Snippet	Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development...
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SubjectTerms	computer software Groundwater groundwater flow Humans hydrologic models Models, Theoretical Programming Languages Python Water Movements
Title	Scripting MODFLOW Model Development Using Python and FloPy
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