examples/Notebooks/flopy3_multi-component_SSM.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FloPy\n",
    "\n",
    "## Using FloPy to simplify the use of the MT3DMS ```SSM``` package\n",
    "\n",
    "A multi-component transport demonstration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.8.6 | packaged by conda-forge | (default, Oct  7 2020, 18:42:56) \n",
      "[Clang 10.0.1 ]\n",
      "numpy version: 1.18.5\n",
      "flopy version: 3.3.3\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import sys\n",
    "import numpy as np\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('flopy version: {}'.format(flopy.__version__))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we will create a simple model structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "nlay, nrow, ncol = 10, 10, 10\n",
    "perlen = np.zeros((10), dtype=float) + 10\n",
    "nper = len(perlen)\n",
    "\n",
    "ibound = np.ones((nlay,nrow,ncol), dtype=int)\n",
    "\n",
    "botm = np.arange(-1,-11,-1)\n",
    "top = 0."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create the ```MODFLOW``` packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_ws = 'data'\n",
    "modelname = 'ssmex'\n",
    "mf = flopy.modflow.Modflow(modelname, model_ws=model_ws)\n",
    "dis = flopy.modflow.ModflowDis(mf, nlay=nlay, nrow=nrow, ncol=ncol, \n",
    "                               perlen=perlen, nper=nper, botm=botm, top=top, \n",
    "                               steady=False)\n",
    "bas = flopy.modflow.ModflowBas(mf, ibound=ibound, strt=top)\n",
    "lpf = flopy.modflow.ModflowLpf(mf, hk=100, vka=100, ss=0.00001, sy=0.1)\n",
    "oc = flopy.modflow.ModflowOc(mf)\n",
    "pcg = flopy.modflow.ModflowPcg(mf)\n",
    "rch = flopy.modflow.ModflowRch(mf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll track the cell locations for the ```SSM``` data using the ```MODFLOW``` boundary conditions.\n",
    "\n",
    "\n",
    "Get a dictionary (```dict```) that has the ```SSM``` ```itype``` for each of the boundary types."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'CHD': 1, 'BAS6': 1, 'PBC': 1, 'WEL': 2, 'DRN': 3, 'RIV': 4, 'GHB': 5, 'MAS': 15, 'CC': -1}\n",
      "[('k', '<i8'), ('i', '<i8'), ('j', '<i8'), ('css', '<f4'), ('itype', '<i8')]\n"
     ]
    }
   ],
   "source": [
    "itype = flopy.mt3d.Mt3dSsm.itype_dict()\n",
    "print(itype)\n",
    "print(flopy.mt3d.Mt3dSsm.get_default_dtype())\n",
    "ssm_data = {}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Add a general head boundary (```ghb```).  The general head boundary head (```bhead```) is 0.1 for the first 5 stress periods with a component 1 (comp_1) concentration of 1.0 and a component 2 (comp_2) concentration of 100.0.  Then ```bhead``` is increased to 0.25 and comp_1 concentration is reduced to 0.5 and comp_2 concentration is increased to 200.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('k', '<i8'), ('i', '<i8'), ('j', '<i8'), ('bhead', '<f4'), ('cond', '<f4')]\n"
     ]
    }
   ],
   "source": [
    "ghb_data = {}\n",
    "print(flopy.modflow.ModflowGhb.get_default_dtype())\n",
    "ghb_data[0] = [(4, 4, 4, 0.1, 1.5)]\n",
    "ssm_data[0] = [(4, 4, 4, 1.0, itype['GHB'], 1.0, 100.0)]\n",
    "ghb_data[5] = [(4, 4, 4, 0.25, 1.5)]\n",
    "ssm_data[5] = [(4, 4, 4, 0.5, itype['GHB'], 0.5, 200.0)]\n",
    "\n",
    "for k in range(nlay):\n",
    "    for i in range(nrow):\n",
    "        ghb_data[0].append((k, i, 0, 0.0, 100.0))\n",
    "        ssm_data[0].append((k, i, 0, 0.0, itype['GHB'], 0.0, 0.0))\n",
    "    \n",
    "ghb_data[5] = [(4, 4, 4, 0.25, 1.5)]\n",
    "ssm_data[5] = [(4, 4, 4, 0.5, itype['GHB'], 0.5, 200.0)]\n",
    "for k in range(nlay):\n",
    "    for i in range(nrow):\n",
    "        ghb_data[5].append((k, i, 0, -0.5, 100.0))\n",
    "        ssm_data[5].append((k, i, 0, 0.0, itype['GHB'], 0.0, 0.0))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Add an injection ```well```.  The injection rate (```flux```) is 10.0 with a comp_1 concentration of 10.0 and a comp_2 concentration of 0.0 for all stress periods.  WARNING: since we changed the ```SSM``` data in stress period 6, we need to add the well to the ssm_data for stress period 6."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('k', '<i8'), ('i', '<i8'), ('j', '<i8'), ('flux', '<f4')]\n"
     ]
    }
   ],
   "source": [
    "wel_data = {}\n",
    "print(flopy.modflow.ModflowWel.get_default_dtype())\n",
    "wel_data[0] = [(0, 4, 8, 10.0)]\n",
    "ssm_data[0].append((0, 4, 8, 10.0, itype['WEL'], 10.0, 0.0))\n",
    "ssm_data[5].append((0, 4, 8, 10.0, itype['WEL'], 10.0, 0.0))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Add the ```GHB``` and ```WEL``` packages to the ```mf``` ```MODFLOW``` object instance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "ghb = flopy.modflow.ModflowGhb(mf, stress_period_data=ghb_data)\n",
    "wel = flopy.modflow.ModflowWel(mf, stress_period_data=wel_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create the ```MT3DMS``` packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "found 'rch' in modflow model, resetting crch to 0.0\n",
      "SSM: setting crch for component 2 to zero. kwarg name crch2\n"
     ]
    }
   ],
   "source": [
    "mt = flopy.mt3d.Mt3dms(modflowmodel=mf, modelname=modelname, model_ws=model_ws)\n",
    "btn = flopy.mt3d.Mt3dBtn(mt, sconc=0, ncomp=2, sconc2=50.0)\n",
    "adv = flopy.mt3d.Mt3dAdv(mt)\n",
    "ssm = flopy.mt3d.Mt3dSsm(mt, stress_period_data=ssm_data)\n",
    "gcg = flopy.mt3d.Mt3dGcg(mt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's verify that ```stress_period_data``` has the right ```dtype```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('k', '<i8'), ('i', '<i8'), ('j', '<i8'), ('css', '<f4'), ('itype', '<i8'), ('cssm(01)', '<f4'), ('cssm(02)', '<f4')]\n"
     ]
    }
   ],
   "source": [
    "print(ssm.stress_period_data.dtype)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create the ```SEAWAT``` packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "swt = flopy.seawat.Seawat(modflowmodel=mf, mt3dmodel=mt, \n",
    "                          modelname=modelname, namefile_ext='nam_swt', model_ws=model_ws)\n",
    "vdf = flopy.seawat.SeawatVdf(swt, mtdnconc=0, iwtable=0, indense=-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "mf.write_input()\n",
    "mt.write_input()\n",
    "swt.write_input()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And finally, modify the ```vdf``` package to fix ```indense```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "fname = modelname + '.vdf'\n",
    "f = open(os.path.join(model_ws, fname),'r')\n",
    "lines = f.readlines()\n",
    "f.close()\n",
    "f = open(os.path.join(model_ws, fname),'w')\n",
    "for line in lines:\n",
    "    f.write(line)\n",
    "for kper in range(nper):\n",
    "    f.write(\"-1\\n\")\n",
    "f.close()    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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