iMOD-Python: make massive MODFLOW models

The imod Python package is designed to help you in your MODFLOW groundwater modeling efforts. It makes it easy to go from your raw data to a fully defined MODFLOW model, with the aim to make this process reproducable. Whether you want to build a simple 2D conceptual model, or a complex 3D regional model with millions of cells, imod-python scales automatically by making use of dask.

By building on top of popular Python packages like xarray, pandas, rasterio and geopandas, a lot of functionality comes for free.

Currently we support the creation of the following MODFLOW-based models:


Source code:

Interactive notebook examples:

Getting started

Install the latest release using conda install -c conda-forge imod, or, when not using Anaconda, pip install imod. For more detailed installation information see Installation.

import imod

# read and write IPF files to pandas DataFrame
df ='wells.ipf')'wells-out.ipf', df)

# get all calculated heads in a xarray DataArray
# with dimensions time, layer, y, x
da ='path/to/results/head_*.idf')

# create a groundwater model
# abridged example, see examples for the full code
gwf_model = imod.mf6.GroundwaterFlowModel()
gwf_model["dis"] = imod.mf6.StructuredDiscretization(
    top=200.0, bottom=bottom, idomain=idomain
gwf_model["chd"] = imod.mf6.ConstantHead(
    head, print_input=True, print_flows=True, save_flows=True
simulation = imod.mf6.Modflow6Simulation("ex01-twri")
simulation["GWF_1"] = gwf_model
simulation.time_discretization(times=["2000-01-01", "2000-01-02"])


This Python package was written primarily by Martijn Visser and Huite Bootsma at Deltares.

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