{ "cells": [ { "cell_type": "markdown", "id": "de12f680", "metadata": {}, "source": [ "# Generating Input for MODFLOW\n", "\n", "This notebook shows how to convert hydraulic soil properties from `pedon` models into parameters that can be used in FloPy-based MODFLOW workflows.\n", "\n", "The workflow is:\n", "1. Build or load a soil hydraulic model in `pedon`.\n", "2. Evaluate water retention and conductivity over a pressure-head range.\n", "3. Fit a MODFLOW-oriented parameterization (here: `Panday`).\n", "4. Create MODFLOW-USG / MODFLOW 6 package inputs.\n", "\n", "## FloPy references\n", "- Bakker, M., Post, V., Langevin, C. D., Hughes, J. D., White, J. T., Starn, J. J., & Fienen, M. N. (2016). *Scripting MODFLOW Model Development Using Python and FloPy*. Groundwater, 54(5), 733-739. https://doi.org/10.1111/gwat.12413/epdf\n", "- Hughes, J. D., Langevin, C. D., Paulinski, S. R., Larsen, J. D., & Brakenhoff, D. (2024). *FloPy Workflows for Creating Structured and Unstructured MODFLOW Models*. Groundwater, 62, 124-139. https://doi.org/10.1111/gwat.13327" ] }, { "cell_type": "code", "execution_count": 1, "id": "0b6f8fd6", "metadata": {}, "outputs": [], "source": [ "import flopy as fp\n", "import numpy as np\n", "import pandas as pd\n", "\n", "import pedon as pe" ] }, { "cell_type": "markdown", "id": "eee696d7", "metadata": {}, "source": [ "## Converting soil models\n", "\n", "Here we generate synthetic retention and conductivity data from a `Genuchten` soil model and fit a `Panday` model to those data. This gives us a practical bridge from commonly available soil descriptions to parameters needed by MODFLOW packages.\n", "\n", "This routine is described in more detail in the curve_fitting notebook." ] }, { "cell_type": "code", "execution_count": 2, "id": "873db8e4", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(np.float64(0.0001), np.float64(1000000.0))" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "gen = pe.Soil(\"Sand\").from_name(pe.Genuchten, source=\"HYDRUS\").model\n", "# gen = pe.Genuchten(k_s=100.0, theta_s=0.4, theta_r=0.05, alpha=0.1, n=2.0)\n", "\n", "ax = gen.plot()\n", "\n", "# sample the SWRC and HCF at 11 points between 10^-4 and 10^6 cm of pressure head\n", "h = np.logspace(-4, 6, num=11)\n", "theta = gen.theta(h)\n", "k = gen.k(h)\n", "\n", "ax.scatter(theta, h, color=\"C0\", label=\"Sample for fitting\")\n", "ax.legend()\n", "ax.set_ylim(h[0], h[-1])" ] }, { "cell_type": "markdown", "id": "cddd6690", "metadata": {}, "source": [ "### Fit SWRC and HCF\n", "Normally, when fitting a soil model, we would fit both the soil water retention curve (SWRC) and the hydraulic conductivity function (HCF) simultaneously. This is because the parameters of these two functions are interrelated. However, in some cases, we might want to fit only the HCF, especially if we have more confidence in our retention data than in our conductivity data. In this example, we will fit both the SWRC and HCF simultaneously, and then we will fit only the HCF to see how it affects the resulting curve." ] }, { "cell_type": "code", "execution_count": 3, "id": "4e32a118", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Panday(k_s=np.float64(571.7082324246585), alpha=np.float64(0.14618016562833308), beta=np.float64(2.652658751825619), brook=np.float64(3.797937623049721), sr=np.float64(0.10452835579197751))" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pbounds = pe.get_params(pe.Panday)\n", "pbounds\n", "\n", "pan_both = pe.SoilSample(theta=theta, k=k, h=h).fit(pe.Panday, pbounds=pbounds)\n", "pan_both" ] }, { "cell_type": "markdown", "id": "c5dcccc0", "metadata": {}, "source": [ "### Fit only the HCF" ] }, { "cell_type": "code", "execution_count": 4, "id": "1de8dba5", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Panday(k_s=np.float64(712.8), alpha=np.float64(0.14500000009999997), beta=np.float64(2.679999999904514), brook=np.float64(3.7548440249344366), sr=np.float64(0.10465116278938343))" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Note that we set the bounds for theta_r, theta_s, alpha and n very small.\n", "# This is because we want to fix these parameters during optimization and only\n", "# optimize for the relative hydraulic conductivity curve with the brook parameter.\n", "\n", "eps = 1e-10\n", "pbounds_brook = pbounds.copy()\n", "pbounds_brook.loc[[\"theta_r\", \"theta_s\", \"alpha\", \"beta\"], :] = pd.DataFrame(\n", " {\n", " \"p_ini\": [gen.theta_r, gen.theta_s, gen.alpha, gen.n],\n", " \"p_min\": [gen.theta_r - eps, gen.theta_s - eps, gen.alpha - eps, gen.n - eps],\n", " \"p_max\": [gen.theta_r + eps, gen.theta_s + eps, gen.alpha + eps, gen.n + eps],\n", " },\n", " index=[\"theta_r\", \"theta_s\", \"alpha\", \"beta\"],\n", ")\n", "\n", "pan = pe.SoilSample(h=h, theta=theta, k=k).fit(\n", " pe.Panday,\n", " pbounds=pbounds_brook,\n", " k_s=gen.k_s, # fit relative hydraulic conductivity curve\n", ")\n", "pan" ] }, { "cell_type": "code", "execution_count": 5, "id": "055d8b05", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "axes = pe.plot.curves(gen, label=\"Van Genuchten\")\n", "axes = pe.plot.curves(pan, axes=axes, label=\"Panday (fit only HCF)\")\n", "axes = pe.plot.curves(pan_both, axes=axes, label=\"Panday (fit SWRC & HCF)\")\n", "axes[0].scatter(theta, h, color=\"C0\", label=\"Sample for fitting\", zorder=10)\n", "axes[1].scatter(k, h, color=\"C0\", label=\"Sample for fitting\", zorder=10)\n", "axes[0].set_ylim(1e-2, 1e4)\n", "axes[0].set_xlim(0.0, 0.45)\n", "axes[0].set_title(\"Soil Water\\nRetention Curve\")\n", "axes[1].set_ylabel(\"\")\n", "axes[1].set_xscale(\"linear\")\n", "axes[1].set_xlim(-10.0, 800.0)\n", "axes[1].set_title(\"Hydraulic Conductivity\\nFunction\")\n", "axes[1].legend(fontsize=9)" ] }, { "cell_type": "markdown", "id": "70973416", "metadata": {}, "source": [ "From this we can see that fitting only the HCF curve follows the original van Genuchten curve more closely than fitting both the SWRC and HCF simultaneously. When we fit both curves simultaneously, the parameters are adjusted to fit both datasets, which can lead to a compromise that does not fit either dataset as well as fitting only one curve." ] }, { "cell_type": "markdown", "id": "2aea8611", "metadata": {}, "source": [ "## MODFLOW-USG Transport Parameters\n", "\n", "The fitted `Panday` object (`pan`) can be mapped directly to `MfUsgLpf` soil-related inputs. Please make sur that the units are consistent with your MODFLOW model. " ] }, { "cell_type": "code", "execution_count": 6, "id": "319134fb", "metadata": {}, "outputs": [], "source": [ "# This code does not work but shows you how to parse the parameters\n", "# to the MODFLOW USG Tranport LPF package.\n", "try:\n", " fp.mfusg.MfUsgLpf(\n", " ...,\n", " hk=pan.k_s / 100.0, # convert from cm/day to m/day\n", " sy=pan.theta_s,\n", " ss=pan.ss,\n", " alpha=pan.alpha * 100, # convert from 1/cm to 1/m\n", " beta=pan.beta,\n", " sr=pan.sr,\n", " brook=pan.brook,\n", " )\n", "except AssertionError:\n", " pass" ] }, { "cell_type": "markdown", "id": "25df2a91", "metadata": {}, "source": [ "## MODFLOW 6 UZF\n", "\n", "For MODFLOW 6 UZF (Unsaturated Zone Flow) package, we provide effective unsaturated-zone parameters through `packagedata` (for example `vks`, `thtr`, `thts`, and `eps`). Unlike full retention-curve formulations, UZF uses a reduced parameterization of unsaturated flow behavior." ] }, { "cell_type": "code", "execution_count": null, "id": "f844758d", "metadata": {}, "outputs": [], "source": [ "# packagedata : [(ifno, cellid, landflag, ivertcon, surfdep, vks, thtr, thts, thti, eps, boundname)]\n", "packagedata = [\n", " (\n", " ..., # ifno\n", " ..., # cellid\n", " ..., # landflag\n", " ..., # ivertcon\n", " ..., # surfdep\n", " pan.k_s / 100.0, # vks, convert from cm/day to m/day\n", " pan.theta_r, # thtr\n", " pan.theta_s, # thts\n", " ..., # thti, can be any value between thtr and thts\n", " pan.brook, # eps\n", " ..., # boundname\n", " ),\n", "]\n", "try:\n", " fp.mf6.ModflowGwfuzf(\n", " ...,\n", " packagedata=packagedata,\n", " )\n", "except AttributeError:\n", " pass" ] }, { "cell_type": "markdown", "id": "e9c700cb", "metadata": {}, "source": [ "In MODFLOW 6, via the MODFLOW API it should be possible to update the soil water retention curve iteratively during a simulation. This would allow for dynamic feedback between soil moisture conditions and flow behavior, for example under hysteresis conditions. The MODFLOW API is available via FloPy, but this would require more custom coding to achieve." ] } ], "metadata": { "kernelspec": { "display_name": "pedon (3.13.5)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.13.5" } }, "nbformat": 4, "nbformat_minor": 5 }