examples/Notebooks/flopy3_drain_return.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-30T20:16:32.126287Z",
     "iopub.status.busy": "2022-07-30T20:16:32.125864Z",
     "iopub.status.idle": "2022-07-30T20:16:32.877268Z",
     "shell.execute_reply": "2022-07-30T20:16:32.876646Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.10.5 (v3.10.5:f377153967, Jun  6 2022, 12:36:10) [Clang 13.0.0 (clang-1300.0.29.30)]\n",
      "numpy version: 1.23.1\n",
      "matplotlib version: 3.5.2\n",
      "flopy version: 3.3.6\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "import os\n",
    "from tempfile import TemporaryDirectory\n",
    "import numpy as np\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# run installed version of flopy or add local path\n",
    "try:\n",
    "    import flopy\n",
    "except:\n",
    "    fpth = os.path.abspath(os.path.join(\"..\", \"..\"))\n",
    "    sys.path.append(fpth)\n",
    "    import flopy\n",
    "\n",
    "print(sys.version)\n",
    "print(\"numpy version: {}\".format(np.__version__))\n",
    "print(\"matplotlib version: {}\".format(mpl.__version__))\n",
    "print(\"flopy version: {}\".format(flopy.__version__))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-30T20:16:32.912142Z",
     "iopub.status.busy": "2022-07-30T20:16:32.911810Z",
     "iopub.status.idle": "2022-07-30T20:16:32.919706Z",
     "shell.execute_reply": "2022-07-30T20:16:32.919149Z"
    }
   },
   "outputs": [],
   "source": [
    "# temporary directory\n",
    "temp_dir = TemporaryDirectory()\n",
    "modelpth = temp_dir.name\n",
    "\n",
    "# creat the model package\n",
    "m = flopy.modflow.Modflow(\n",
    "    \"drt_test\",\n",
    "    model_ws=modelpth,\n",
    "    exe_name=\"mfnwt\",\n",
    "    version=\"mfnwt\",\n",
    ")\n",
    "d = flopy.modflow.ModflowDis(\n",
    "    m,\n",
    "    nlay=1,\n",
    "    nrow=10,\n",
    "    ncol=10,\n",
    "    nper=1,\n",
    "    perlen=1,\n",
    "    top=10,\n",
    "    botm=0,\n",
    "    steady=True,\n",
    ")\n",
    "b = flopy.modflow.ModflowBas(m, strt=10, ibound=1)\n",
    "u = flopy.modflow.ModflowUpw(m, hk=10)\n",
    "n = flopy.modflow.ModflowNwt(m)\n",
    "o = flopy.modflow.ModflowOc(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-30T20:16:32.922932Z",
     "iopub.status.busy": "2022-07-30T20:16:32.922656Z",
     "iopub.status.idle": "2022-07-30T20:16:32.927126Z",
     "shell.execute_reply": "2022-07-30T20:16:32.926458Z"
    }
   },
   "outputs": [],
   "source": [
    "# create the drt package\n",
    "spd = []\n",
    "for i in range(m.nrow):\n",
    "    spd.append([0, i, m.ncol - 1, 5.0, 50.0, 1, 1, 1, 1.0])\n",
    "d = flopy.modflow.ModflowDrt(m, stress_period_data={0: spd})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-30T20:16:32.930283Z",
     "iopub.status.busy": "2022-07-30T20:16:32.930013Z",
     "iopub.status.idle": "2022-07-30T20:16:32.958682Z",
     "shell.execute_reply": "2022-07-30T20:16:32.957681Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FloPy is using the following executable to run the model: /Users/wes/dev/usgs-executables/mfnwt\n",
      "\n",
      "                                  MODFLOW-NWT-SWR1 \n",
      "    U.S. GEOLOGICAL SURVEY MODULAR FINITE-DIFFERENCE GROUNDWATER-FLOW MODEL\n",
      "                             WITH NEWTON FORMULATION\n",
      "                             Version 1.2.0 03/01/2020                        \n",
      "                    BASED ON MODFLOW-2005 Version 1.12.0 02/03/2017                       \n",
      "\n",
      "                    SWR1 Version 1.04.0 09/15/2016                       \n",
      "\n",
      " Using NAME file: drt_test.nam \n",
      " Run start date and time (yyyy/mm/dd hh:mm:ss): 2022/07/30 16:16:32\n",
      "\n",
      " Solving:  Stress period:     1    Time step:     1    Groundwater-Flow Eqn.\n",
      " Run end date and time (yyyy/mm/dd hh:mm:ss): 2022/07/30 16:16:32\n",
      " Elapsed run time:  0.005 Seconds\n",
      "\n",
      "  Normal termination of simulation\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(True, [])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# run the drt model\n",
    "m.write_input()\n",
    "m.run_model()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-30T20:16:32.964480Z",
     "iopub.status.busy": "2022-07-30T20:16:32.963976Z",
     "iopub.status.idle": "2022-07-30T20:16:33.159087Z",
     "shell.execute_reply": "2022-07-30T20:16:33.158226Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'data Layer 1'}>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot heads for the drt model\n",
    "hds = flopy.utils.HeadFile(os.path.join(m.model_ws, m.name + \".hds\"))\n",
    "hds.plot(colorbar=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-30T20:16:33.163808Z",
     "iopub.status.busy": "2022-07-30T20:16:33.163434Z",
     "iopub.status.idle": "2022-07-30T20:16:33.169913Z",
     "shell.execute_reply": "2022-07-30T20:16:33.168901Z"
    }
   },
   "outputs": [],
   "source": [
    "# remove the drt package and create a standard drain file\n",
    "spd = []\n",
    "for i in range(m.nrow):\n",
    "    spd.append([0, i, m.ncol - 1, 5.0, 1.0])\n",
    "m.remove_package(\"DRT\")\n",
    "d = flopy.modflow.ModflowDrn(m, stress_period_data={0: spd})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-30T20:16:33.174598Z",
     "iopub.status.busy": "2022-07-30T20:16:33.174183Z",
     "iopub.status.idle": "2022-07-30T20:16:33.202243Z",
     "shell.execute_reply": "2022-07-30T20:16:33.201143Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FloPy is using the following executable to run the model: /Users/wes/dev/usgs-executables/mfnwt\n",
      "\n",
      "                                  MODFLOW-NWT-SWR1 \n",
      "    U.S. GEOLOGICAL SURVEY MODULAR FINITE-DIFFERENCE GROUNDWATER-FLOW MODEL\n",
      "                             WITH NEWTON FORMULATION\n",
      "                             Version 1.2.0 03/01/2020                        \n",
      "                    BASED ON MODFLOW-2005 Version 1.12.0 02/03/2017                       \n",
      "\n",
      "                    SWR1 Version 1.04.0 09/15/2016                       \n",
      "\n",
      " Using NAME file: drt_test.nam \n",
      " Run start date and time (yyyy/mm/dd hh:mm:ss): 2022/07/30 16:16:33\n",
      "\n",
      " Solving:  Stress period:     1    Time step:     1    Groundwater-Flow Eqn.\n",
      " Run end date and time (yyyy/mm/dd hh:mm:ss): 2022/07/30 16:16:33\n",
      " Elapsed run time:  0.004 Seconds\n",
      "\n",
      "  Normal termination of simulation\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(True, [])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# run the drain model\n",
    "m.write_input()\n",
    "m.run_model()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-30T20:16:33.207320Z",
     "iopub.status.busy": "2022-07-30T20:16:33.206877Z",
     "iopub.status.idle": "2022-07-30T20:16:33.438531Z",
     "shell.execute_reply": "2022-07-30T20:16:33.437673Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'data Layer 1'}>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the heads for the model with the drain\n",
    "hds = flopy.utils.HeadFile(os.path.join(m.model_ws, m.name + \".hds\"))\n",
    "hds.plot(colorbar=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-30T20:16:33.442361Z",
     "iopub.status.busy": "2022-07-30T20:16:33.442072Z",
     "iopub.status.idle": "2022-07-30T20:16:33.447693Z",
     "shell.execute_reply": "2022-07-30T20:16:33.446763Z"
    }
   },
   "outputs": [],
   "source": [
    "try:\n",
    "    # ignore PermissionError on Windows\n",
    "    temp_dir.cleanup()\n",
    "except:\n",
    "    pass"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.10.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}