.. 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 Click :ref:here  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. .. GENERATED FROM PYTHON SOURCE LINES 8-11 .. code-block:: default import matplotlib.pyplot as plt .. GENERATED FROM PYTHON SOURCE LINES 12-13 We'll start with the usual imports .. GENERATED FROM PYTHON SOURCE LINES 13-19 .. code-block:: default import numpy as np import xarray as xr import imod .. GENERATED FROM PYTHON SOURCE LINES 21-27 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. .. GENERATED FROM PYTHON SOURCE LINES 27-36 .. code-block:: default nrow = 1 # number of rows ncol = 40 # number of columns nlay = 15 # number of layers dz = 10 dx = 250 dy = -dx .. GENERATED FROM PYTHON SOURCE LINES 37-38 Set up tops and bottoms .. GENERATED FROM PYTHON SOURCE LINES 38-45 .. code-block:: default top1D = xr.DataArray( np.arange(nlay * dz, 0.0, -dz), {"layer": np.arange(1, nlay + 1)}, ("layer") ) bot = top1D - dz .. GENERATED FROM PYTHON SOURCE LINES 46-47 Set up ibound, which sets where active cells are (ibound = 1.0) .. GENERATED FROM PYTHON SOURCE LINES 47-60 .. code-block:: default 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"), ) .. GENERATED FROM PYTHON SOURCE LINES 61-66 Boundary Conditions ------------------- Set the constant heads by specifying a negative value in iboud, that is: bnd[index] = -1 .. GENERATED FROM PYTHON SOURCE LINES 66-73 .. code-block:: default 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 .. GENERATED FROM PYTHON SOURCE LINES 74-75 Define the recharge rates .. GENERATED FROM PYTHON SOURCE LINES 75-86 .. code-block:: default 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 [] .. GENERATED FROM PYTHON SOURCE LINES 87-88 The model is recharged with fresh water .. GENERATED FROM PYTHON SOURCE LINES 88-91 .. code-block:: default rch_conc = xr.full_like(rch_rate, fill_value=0.0) .. GENERATED FROM PYTHON SOURCE LINES 92-96 Initial Conditions ------------------ Defining the starting concentrations .. GENERATED FROM PYTHON SOURCE LINES 96-115 .. code-block:: default 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 .. GENERATED FROM PYTHON SOURCE LINES 116-120 Build ----- Finally, we build the model. .. GENERATED FROM PYTHON SOURCE LINES 120-146 .. code-block:: default 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"]) .. GENERATED FROM PYTHON SOURCE LINES 147-148 Now we write the model, including runfile: .. GENERATED FROM PYTHON SOURCE LINES 148-151 .. code-block:: default modeldir = imod.util.temporary_directory() m.write(modeldir, resultdir_is_workdir=True) .. GENERATED FROM PYTHON SOURCE LINES 152-170 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. .. GENERATED FROM PYTHON SOURCE LINES 172-190 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 0.571 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-python :download:Download Python source code: FreshwaterLens.py  .. container:: sphx-glr-download sphx-glr-download-jupyter :download:Download Jupyter notebook: FreshwaterLens.ipynb  .. only:: html .. rst-class:: sphx-glr-signature Gallery generated by Sphinx-Gallery `_