.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples\imod-wq\FreshwaterLens.py"
.. LINE NUMBERS ARE GIVEN BELOW.
.. only:: html
.. note::
:class: sphx-glr-download-link-note
:ref:`Go to the end <sphx_glr_download_examples_imod-wq_FreshwaterLens.py>`
to download the full example code.
.. rst-class:: sphx-glr-example-title
.. _sphx_glr_examples_imod-wq_FreshwaterLens.py:
Freshwater Lens
===============
This 2D examples illustrates the growth of a fresh water lens in an initially
fully saline domain.
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.. code-block:: Python
import matplotlib.pyplot as plt
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We'll start with the usual imports
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.. code-block:: Python
import numpy as np
import xarray as xr
import imod
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Discretization
--------------
We'll start off by creating a model discretization, since
this is a simple conceptual model.
The model is a 2D cross-section, hence ``nrow = 1``.
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.. code-block:: Python
nrow = 1 # number of rows
ncol = 40 # number of columns
nlay = 15 # number of layers
dz = 10
dx = 250
dy = -dx
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Set up tops and bottoms
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.. code-block:: Python
top1D = xr.DataArray(
np.arange(nlay * dz, 0.0, -dz), {"layer": np.arange(1, nlay + 1)}, ("layer")
)
bot = top1D - dz
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Set up ibound, which sets where active cells are `(ibound = 1.0)`
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.. code-block:: Python
bnd = xr.DataArray(
data=np.full((nlay, nrow, ncol), 1.0),
coords={
"y": [0.5],
"x": np.arange(0.5 * dx, dx * ncol, dx),
"layer": np.arange(1, 1 + nlay),
"dx": dx,
"dy": dy,
},
dims=("layer", "y", "x"),
)
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Boundary Conditions
-------------------
Set the constant heads by specifying a negative value in iboud,
that is: ``bnd[index] = -1```
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.. code-block:: Python
bnd[0, :, 0:12] = -1
bnd[0, :, 28:40] = -1
fig, ax = plt.subplots()
bnd.plot(y="layer", yincrease=False, ax=ax)
.. image-sg:: /examples/imod-wq/images/sphx_glr_FreshwaterLens_001.png
:alt: y = 0.5, dx = 250, dy = -250
:srcset: /examples/imod-wq/images/sphx_glr_FreshwaterLens_001.png
:class: sphx-glr-single-img
.. rst-class:: sphx-glr-script-out
.. code-block:: none
<matplotlib.collections.QuadMesh object at 0x0000016F448E1A00>
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Define the recharge rates
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.. code-block:: Python
rch_rate = xr.DataArray(
data=np.full((nrow, ncol), 0.0),
coords={"y": [0.5], "x": np.arange(0.5 * dx, dx * ncol, dx), "dx": dx, "dy": dy},
dims=("y", "x"),
)
rch_rate[:, 13:27] = 0.001
fig, ax = plt.subplots()
rch_rate.plot(ax=ax)
.. image-sg:: /examples/imod-wq/images/sphx_glr_FreshwaterLens_002.png
:alt: y = 0.5, dx = 250, dy = -250
:srcset: /examples/imod-wq/images/sphx_glr_FreshwaterLens_002.png
:class: sphx-glr-single-img
.. rst-class:: sphx-glr-script-out
.. code-block:: none
[<matplotlib.lines.Line2D object at 0x0000016F418FB830>]
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The model is recharged with fresh water
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.. code-block:: Python
rch_conc = xr.full_like(rch_rate, fill_value=0.0)
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Initial Conditions
------------------
Defining the starting concentrations
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.. code-block:: Python
sconc = xr.DataArray(
data=np.full((nlay, nrow, ncol), 35.0),
coords={
"y": [0.5],
"x": np.arange(0.5 * dx, dx * ncol, dx),
"layer": np.arange(1, nlay + 1),
"dx": dx,
"dy": dy,
},
dims=("layer", "y", "x"),
)
sconc[:, 13:27, 0] = 0.0
fig, ax = plt.subplots()
sconc.plot(y="layer", yincrease=False, ax=ax)
.. image-sg:: /examples/imod-wq/images/sphx_glr_FreshwaterLens_003.png
:alt: y = 0.5, dx = 250, dy = -250
:srcset: /examples/imod-wq/images/sphx_glr_FreshwaterLens_003.png
:class: sphx-glr-single-img
.. rst-class:: sphx-glr-script-out
.. code-block:: none
<matplotlib.collections.QuadMesh object at 0x0000016F41598320>
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Build
-----
Finally, we build the model.
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.. code-block:: Python
m = imod.wq.SeawatModel("FreshwaterLens")
m["bas"] = imod.wq.BasicFlow(ibound=bnd, top=150.0, bottom=bot, starting_head=0.0)
m["lpf"] = imod.wq.LayerPropertyFlow(
k_horizontal=10.0, k_vertical=20.0, specific_storage=0.0
)
m["btn"] = imod.wq.BasicTransport(
icbund=bnd, starting_concentration=sconc, porosity=0.35
)
m["adv"] = imod.wq.AdvectionTVD(courant=1.0)
m["dsp"] = imod.wq.Dispersion(longitudinal=0.0, diffusion_coefficient=0.0)
m["vdf"] = imod.wq.VariableDensityFlow(density_concentration_slope=0.71)
m["rch"] = imod.wq.RechargeHighestActive(rate=rch_rate, concentration=0.0)
m["pcg"] = imod.wq.PreconditionedConjugateGradientSolver(
max_iter=150, inner_iter=30, hclose=0.0001, rclose=0.1, relax=0.98, damp=1.0
)
m["gcg"] = imod.wq.GeneralizedConjugateGradientSolver(
max_iter=150,
inner_iter=30,
cclose=1.0e-6,
preconditioner="mic",
lump_dispersion=True,
)
m["oc"] = imod.wq.OutputControl(save_head_idf=True, save_concentration_idf=True)
m.create_time_discretization(additional_times=["1900-01-01T00:00", "2000-01-01T00:00"])
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Now we write the model, including runfile:
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.. code-block:: Python
modeldir = imod.util.temporary_directory()
m.write(modeldir, resultdir_is_workdir=True)
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Run
---
You can run the model using the comand prompt and the iMOD-WQ executable.
This is part of the iMOD v5 release, which can be downloaded here:
https://oss.deltares.nl/web/imod/download-imod5 .
This only works on Windows.
To run your model, open up a command prompt
and run the following commands:
.. code-block:: batch
cd c:\path\to\modeldir
c:\path\to\imod\folder\iMOD-WQ_V5_3_SVN359_X64R.exe FreshwaterLens.run
Note that the version name of your executable might differ.
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Visualise results
-----------------
After succesfully running the model, you can
plot results as follows:
.. code:: python
head = imod.idf.open(modeldir / "results/head/*.idf")
fig, ax = plt.subplots()
head.plot(yincrease=False, ax=ax)
conc = imod.idf.open(modeldir / "results/conc/*.idf")
fig, ax = plt.subplots()
conc.plot(levels=range(0, 35, 5), yincrease=False, ax=ax)
.. rst-class:: sphx-glr-timing
**Total running time of the script:** (0 minutes 0.766 seconds)
.. _sphx_glr_download_examples_imod-wq_FreshwaterLens.py:
.. only:: html
.. container:: sphx-glr-footer sphx-glr-footer-example
.. container:: sphx-glr-download sphx-glr-download-jupyter
:download:`Download Jupyter notebook: FreshwaterLens.ipynb <FreshwaterLens.ipynb>`
.. container:: sphx-glr-download sphx-glr-download-python
:download:`Download Python source code: FreshwaterLens.py <FreshwaterLens.py>`
.. container:: sphx-glr-download sphx-glr-download-zip
:download:`Download zipped: FreshwaterLens.zip <FreshwaterLens.zip>`
.. only:: html
.. rst-class:: sphx-glr-signature
`Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_