Bakker, Mark

Francés, Alain

Hughes, Joseph

Langevin, Christian

Post, Vincent

White, Jeremy

Francés, Alain Pascal

Repositório do LNEG

Enhanced FloPy scripts for Constructing and Running MODFLOW-Based Models  Mark Bakker1, Vincent Post2, Joseph Hughes3, Christian Langevin4, Alain Francés5, Jeremy White6 1Delft University of Technology, mark.bakker@tudelft.nl, Delft, The Netherlands 2Flinders University, vincent.post@flinders.edu.au, Adelaide, Australia 3U.S. Geological Survey, jdhughes@usgs.gov, Tampa, FL, USA 4U.S. Geological Survey, langevin@usgs.gov, Reston, VA, USA  5University of Twente, frances.alain@gmail.com, Enschede, The Netherlands  6U.S. Geological Survey, jwhite@usgs.gov, Tampa, FL, USA   ABSTRACT  The FloPy package is a community project that is being developed by volunteers. It consists of a set of scripts to run MODFLOW, MT3DMS, SEAWAT, SWI, PHT3D, and other MODFLOW-related groundwater programs. The package is written in Python, a powerful scripting language that is free, easy to learn, and rapidly becoming popular among hydrologists. Input scripts are confined to a single, readable file, which makes it easy to build, run, compare, reproduce, and archive models. FloPy is functional for most MODFLOW Packages, but it is still under development.  Those interested in FloPy can download the code or binary installer for PC or Mac from flopy.googlecode.com.  INTRODUCTION  The FloPy project started a few years ago — a FloPy example was presented on a poster at the MODFLOW and More 2011 conference. The latest version contains several enhancements over the 2011 version: (1) arrays are now defined in the MODFLOW standard form (nlays,nrows,ncols), (2) the code is redesigned to improve memory management and handle larger models, (3) online documentation is available for all modules, (4) indexing is implemented for post processing of binary output files so that large files can be processed in an efficient manner, (5) a number of examples have been developed using the iPython Notebooks, and (6) default values for many input parameters are set in a configuration file that can be customized by the user.   DEMONSTRATION BY EXAMPLE  FloPy’s capabilities are presented through an example. Consider a square model with a specified head equal to h1 along all boundaries. The head at the cell in the center in the top layer is fixed to h2. First, set the name of the model and the parameters of the model: the number of layers Nlay, the number of rows and columns N, the lengths of the sides of the model L, the aquifer thickness H, and the hydraulic conductivity k   name = 'mf2013_example' h1 = 100    # Head along boundary of model (m) h2 = 90     # Head at center cell (m) Nlay = 10   # Number of layers  N = 101     # Number of cells in x and y direction L = 400.0   # Length of model (m) H = 50.0    # Aquifer thickness (m) k = 1.0     # Hydraulic conductivity (m/d)  Create a MODFLOW model and store it (in this case in the variable ml, but you can call it whatever you want). The modelname will be the name given to all MODFLOW files (input and output). The exe_name should be the full path to your MODFLOW executable. The version is either 'mf2k' for MODFLOW2000 or 'mf2005' for MODFLOW2005.  ml = Modflow(modelname=name, exe_name='/your_path/mf2005', version='mf2005')   MODFLOW and More 2013: Translating Science into Practice - Conference Proceedings, Maxwell, Hill, Zheng & Tonkin - igwmc.mines.edu307Define the discretization of the model. In this example, all layers are given equal thickness. The bot array consists of the bottom elevations of all layers, and delrow and delcol are computed from model size L and number of cells N. Once these are all computed, the Discretization and the LPF packages are entered.  bot = linspace(-H/Nlay,-H,Nlay)  delrow = delcol = L/(N-1)  ModflowDis(ml,nlay=Nlay,nrow=N,ncol=N,delr=delrow,delc=delcol,top=0.0,botm=bot,laycbd=0) ModflowLpf(ml,hk=k)  Next we specify the boundary conditions and starting heads with the Basic package. The ibound array is 1 in all cells in all layers, except for along the boundary and in the cell at the center in the top layer where it is set to -1 to indicate fixed heads. The starting heads are used to define the heads in the fixed head cells. This is a steady simulation, so none of the other starting values matter. The starting heads are set to h1 everywhere, except for the head at the center of the model in the top layer, which is set to h2.   Nhalf = (N-1)/2  ibound = ones((Nlay,N,N))  ibound[:,0,:] = -1; ibound[:,-1,:] = -1; ibound[:,:,0] = -1; ibound[:,:,-1]=-1  ibound[0,Nhalf,Nhalf] = -1  start = h1 * ones((N,N))  start[Nhalf,Nhalf] = h2  ModflowBas(ml,ibound=ibound,strt=start)   Finally, we need to specify the solver we want to use (PCG with default values), and the output control (using the default values). Then we are ready to write all MODFLOW input files and run MODFLOW.  ModflowPcg(ml) ModflowOc(ml)  ml.write_input() ml.run_model3()                                     MODFLOW-2005-SWI      U.S. GEOLOGICAL SURVEY MODULAR FINITE-DIFFERENCE GROUND-WATER FLOW MODEL                              Version 1.8 11/11/2010                             Using NAME file: mf2013_example.nam   Run start date and time (yyyy/mm/dd hh:mm:ss): 2012/12/14 17:33:33   Solving:  Stress period:     1    Time step:     1    Ground-Water Flow Eqn.  Run end date and time (yyyy/mm/dd hh:mm:ss): 2012/12/14 17:33:35  Elapsed run time:  1.953 Seconds    Normal termination of simulation  MODFLOW ran in less than 2 seconds and no errors were reported. The next step is to read the heads from the output file and make a contour plot. The read statements are being modified at the time this paper is written, so please check the FloPy website to find out how to read the model results. Once the results are read, it is easy to create a contour plot with the Python package matplotlib:  # This is a placeholder – the real read statements is under development h = read_modflow_head_output(name+'.hds')   x = y = linspace(0,L,N) figure() # Head at time 0, layer 0 (top), see Figure 1 c = plt.contour(x,y,h[0,0],arange(90,100.1,.2)) clabel(c,fmt='%1.1f')  axis('scaled') MODFLOW and More 2013: Translating Science into Practice - Conference Proceedings, Maxwell, Hill, Zheng & Tonkin - igwmc.mines.edu308figure() # Head at timestep 0 layer -1 (bottom layer), see Figure 1 c = plt.contour(x,y,h[0,-1],arange(90,100.1,.2)) clabel(c,fmt='%1.1f')   axis('scaled') figure() z = linspace(-H/Nlay/2,-H+H/Nlay/2,Nlay) # Vertical cross-section along row 50, see Figure 2 c = plt.contour(x,z,h[0,:,50,:],arange(90,100.1,.2))      Figure. 1. Contour plot of heads in top layer (left) and bottom layer (right)    Figure. 2. Contour plot of heads in vertical cross-section through center of model   CONCLUSIONS  The FloPy package is a set of scripts to run MODFLOW and friends. FloPy can be downloaded from flopy.googlecode.com. We encourage contributions of code, documentation, or examples (preferably as iPython Notebooks).  MODFLOW and More 2013: Translating Science into Practice - Conference Proceedings, Maxwell, Hill, Zheng & Tonkin - igwmc.mines.edu309

Enhanced FloPy scripts for constructing and running MODFLOW-based models

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Enhanced FloPy scripts for constructing and running MODFLOW-based models

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