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Using FloPy to simplify the use of the MT3DMS SSM package

A multi-component transport demonstration

import os
import sys
from tempfile import TemporaryDirectory

import numpy as np

# run installed version of flopy or add local path
try:
    import flopy
except:
    fpth = os.path.abspath(os.path.join("..", ".."))
    sys.path.append(fpth)
    import flopy

print(sys.version)
print("numpy version: {}".format(np.__version__))
print("flopy version: {}".format(flopy.__version__))

3.10.10 | packaged by conda-forge | (main, Mar 24 2023, 20:08:06) [GCC 11.3.0]
numpy version: 1.24.3
flopy version: 3.3.7

First, we will create a simple model structure

nlay, nrow, ncol = 10, 10, 10
perlen = np.zeros((10), dtype=float) + 10
nper = len(perlen)

ibound = np.ones((nlay, nrow, ncol), dtype=int)

botm = np.arange(-1, -11, -1)
top = 0.0

Create the MODFLOW packages

# temporary directory
temp_dir = TemporaryDirectory()
model_ws = temp_dir.name

modelname = "ssmex"
mf = flopy.modflow.Modflow(modelname, model_ws=model_ws)
dis = flopy.modflow.ModflowDis(
    mf,
    nlay=nlay,
    nrow=nrow,
    ncol=ncol,
    perlen=perlen,
    nper=nper,
    botm=botm,
    top=top,
    steady=False,
)
bas = flopy.modflow.ModflowBas(mf, ibound=ibound, strt=top)
lpf = flopy.modflow.ModflowLpf(mf, hk=100, vka=100, ss=0.00001, sy=0.1)
oc = flopy.modflow.ModflowOc(mf)
pcg = flopy.modflow.ModflowPcg(mf)
rch = flopy.modflow.ModflowRch(mf)

We’ll track the cell locations for the SSM data using the MODFLOW boundary conditions.

Get a dictionary (dict) that has the SSM itype for each of the boundary types.

itype = flopy.mt3d.Mt3dSsm.itype_dict()
print(itype)
print(flopy.mt3d.Mt3dSsm.get_default_dtype())
ssm_data = {}

{'CHD': 1, 'BAS6': 1, 'PBC': 1, 'WEL': 2, 'DRN': 3, 'RIV': 4, 'GHB': 5, 'MAS': 15, 'CC': -1}
[('k', '<i8'), ('i', '<i8'), ('j', '<i8'), ('css', '<f4'), ('itype', '<i8')]

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

ghb_data = {}
print(flopy.modflow.ModflowGhb.get_default_dtype())
ghb_data[0] = [(4, 4, 4, 0.1, 1.5)]
ssm_data[0] = [(4, 4, 4, 1.0, itype["GHB"], 1.0, 100.0)]
ghb_data[5] = [(4, 4, 4, 0.25, 1.5)]
ssm_data[5] = [(4, 4, 4, 0.5, itype["GHB"], 0.5, 200.0)]

for k in range(nlay):
    for i in range(nrow):
        ghb_data[0].append((k, i, 0, 0.0, 100.0))
        ssm_data[0].append((k, i, 0, 0.0, itype["GHB"], 0.0, 0.0))

ghb_data[5] = [(4, 4, 4, 0.25, 1.5)]
ssm_data[5] = [(4, 4, 4, 0.5, itype["GHB"], 0.5, 200.0)]
for k in range(nlay):
    for i in range(nrow):
        ghb_data[5].append((k, i, 0, -0.5, 100.0))
        ssm_data[5].append((k, i, 0, 0.0, itype["GHB"], 0.0, 0.0))

[('k', '<i8'), ('i', '<i8'), ('j', '<i8'), ('bhead', '<f4'), ('cond', '<f4')]

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.

wel_data = {}
print(flopy.modflow.ModflowWel.get_default_dtype())
wel_data[0] = [(0, 4, 8, 10.0)]
ssm_data[0].append((0, 4, 8, 10.0, itype["WEL"], 10.0, 0.0))
ssm_data[5].append((0, 4, 8, 10.0, itype["WEL"], 10.0, 0.0))

[('k', '<i8'), ('i', '<i8'), ('j', '<i8'), ('flux', '<f4')]

Add the GHB and WEL packages to the mf MODFLOW object instance.

ghb = flopy.modflow.ModflowGhb(mf, stress_period_data=ghb_data)
wel = flopy.modflow.ModflowWel(mf, stress_period_data=wel_data)

Create the MT3DMS packages

mt = flopy.mt3d.Mt3dms(modflowmodel=mf, modelname=modelname, model_ws=model_ws)
btn = flopy.mt3d.Mt3dBtn(mt, sconc=0, ncomp=2, sconc2=50.0)
adv = flopy.mt3d.Mt3dAdv(mt)
ssm = flopy.mt3d.Mt3dSsm(mt, stress_period_data=ssm_data)
gcg = flopy.mt3d.Mt3dGcg(mt)

found 'rch' in modflow model, resetting crch to 0.0
SSM: setting crch for component 2 to zero. kwarg name crch2

Let’s verify that stress_period_data has the right dtype

print(ssm.stress_period_data.dtype)

[('k', '<i8'), ('i', '<i8'), ('j', '<i8'), ('css', '<f4'), ('itype', '<i8'), ('cssm(01)', '<f4'), ('cssm(02)', '<f4')]

Create the SEAWAT packages

swt = flopy.seawat.Seawat(
    modflowmodel=mf,
    mt3dmodel=mt,
    modelname=modelname,
    namefile_ext="nam_swt",
    model_ws=model_ws,
)
vdf = flopy.seawat.SeawatVdf(swt, mtdnconc=0, iwtable=0, indense=-1)

mf.write_input()
mt.write_input()
swt.write_input()

And finally, modify the vdf package to fix indense.

fname = modelname + ".vdf"
f = open(os.path.join(model_ws, fname), "r")
lines = f.readlines()
f.close()
f = open(os.path.join(model_ws, fname), "w")
for line in lines:
    f.write(line)
for kper in range(nper):
    f.write("-1\n")
f.close()

try:
    # ignore PermissionError on Windows
    temp_dir.cleanup()
except:
    pass