This page was generated from
ex-gwf-sagehen.py.
It's also available as a notebook.
Sagehen UZF1 Package Problem 1
This script reproduces example 1 in the UZF1 Techniques and Methods (Niswonger et al., 2006).
Initial setup
Import dependencies, define the example name and workspace, and read settings from environment variables.
[1]:
import os
import pathlib as pl
import flopy
import git
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import pooch
from flopy.plot.styles import styles
from modflow_devtools.misc import get_env, timed
# Example name and workspace paths. If this example is running
# in the git repository, use the folder structure described in
# the README. Otherwise just use the current working directory.
sim_name = "ex-gwf-sagehen"
try:
root = pl.Path(git.Repo(".", search_parent_directories=True).working_dir)
except:
root = None
workspace = root / "examples" if root else pl.Path.cwd()
figs_path = root / "figures" if root else pl.Path.cwd()
data_path = root / "data" / sim_name if root else pl.Path.cwd()
# Settings from environment variables
write = get_env("WRITE", True)
run = get_env("RUN", True)
plot = get_env("PLOT", True)
plot_show = get_env("PLOT_SHOW", True)
plot_save = get_env("PLOT_SAVE", True)
Define parameters
Define model units, parameters and other settings.
[2]:
# Model units
length_units = "meters"
time_units = "days"
# Model parameters
nlay = 1 # Number of layers in parent model
nrow = 73 # Number of rows in parent model
ncol = 81 # Number of columns in parent model
delr = 90.0 # Parent model column width ($m$)
delc = 90.0 # Parent model row width ($m$)
k11 = "0.005 - 0.3" # Horizontal hydraulic conductivity ($m/d$)
k33 = "0.01 - 0.3" # Vertical hydraulic conductivity ($m/d$)
sydum = "0.1 - 0.2" # Specific Yield
dum1 = "0.15 - 0.25" # Saturated water content
dum2 = 0.10 # Extinction water content
dum3 = "0.005 - 0.3" # Saturated hydraulic conductivity of unsaturated zone
eps = 4.0 # Brooks-Corey Epsilon
sfrdum1 = 213 # Number of SFR stream reaches
sfrdum2 = 0.3 # Hydraulic conductivity of streambed ($m/d$)
sfrdum3 = 3 # Width of stream reaches ($m$)
sfrdum4 = 1 # Streambed thickness ($m$)
# Time related variables
num_ts = 399
perlen = [1] * num_ts
nper = len(perlen)
nstp = [1] * num_ts
tsmult = [1.0] * num_ts
# from mf-nwt .dis file
fname = "top1.txt"
fpath = pooch.retrieve(
url=f"https://github.com/MODFLOW-USGS/modflow6-examples/raw/master/data/{sim_name}/{fname}",
fname=fname,
path=data_path,
known_hash="md5:a93be6cf74bf376f696fc2fbcc316aea",
)
top = np.loadtxt(fpath)
fname = "bot1.txt"
fpath = pooch.retrieve(
url=f"https://github.com/MODFLOW-USGS/modflow6-examples/raw/master/data/{sim_name}/{fname}",
fname=fname,
path=data_path,
known_hash="md5:6503e01167875bd257479a2941d1d586",
)
bot1 = np.loadtxt(fpath)
# from mf-nwt .bas file
fname = "ibnd1.txt"
fpath = pooch.retrieve(
url=f"https://github.com/MODFLOW-USGS/modflow6-examples/raw/master/data/{sim_name}/{fname}",
fname=fname,
path=data_path,
known_hash="md5:7b33e2fba54eae694171c94c75e13d2e",
)
idomain1 = np.loadtxt(fpath)
fname = "strt1.txt"
fpath = pooch.retrieve(
url=f"https://github.com/MODFLOW-USGS/modflow6-examples/raw/master/data/{sim_name}/{fname}",
fname=fname,
path=data_path,
known_hash="md5:d49e24ec920472380787fd27c528123f",
)
strt = np.loadtxt(fpath)
# peel out locations of negative values for setting constant head data
tmp1 = np.where(idomain1 < 0)
listOfChdCoords = list(zip(np.zeros_like(tmp1[0]), tmp1[0], tmp1[1]))
# get the corresponding constant head values
if len(listOfChdCoords) > 0:
chd_lay1 = list(np.take(strt, np.ravel_multi_index(tmp1, strt.shape)))
chdspd = []
for i in np.arange(len(listOfChdCoords)):
chdspd.append([listOfChdCoords[i], chd_lay1[i]])
# finally, get rid of the negative values in idomain since mf6 treats
# negatives like zeros
idomain = np.abs(idomain1)
# from mf-nwt .upw file
fname = "kh1.txt"
fpath = pooch.retrieve(
url=f"https://github.com/MODFLOW-USGS/modflow6-examples/raw/master/data/{sim_name}/{fname}",
fname=fname,
path=data_path,
known_hash="md5:50c0a5bfd79b1c9d0e0900540c19d6cc",
)
k11 = np.loadtxt(fpath)
fname = "sy1.txt"
fpath = pooch.retrieve(
url=f"https://github.com/MODFLOW-USGS/modflow6-examples/raw/master/data/{sim_name}/{fname}",
fname=fname,
path=data_path,
known_hash="md5:6bc38fd082875633686732f34ba3e18b",
)
sy = np.loadtxt(fpath)
fname = "kv1.txt"
fpath = pooch.retrieve(
url=f"https://github.com/MODFLOW-USGS/modflow6-examples/raw/master/data/{sim_name}/{fname}",
fname=fname,
path=data_path,
known_hash="md5:7b6685bf35f1150bef553f81c2dfb2cb",
)
k33 = np.loadtxt(fpath)
icelltype = 1 # Water table resides in layer 1
iconvert = np.ones_like(strt)
# Solver settings
nouter, ninner = 300, 500
hclose, rclose, relax = 3e-2, 3e-2, 0.97
# #### Prepping input for SFR package
# Get package_data information
orig_seg = [
(1, 1, 9, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg1"),
(2, 1, 10, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg2"),
(3, 1, 9, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg3"),
(4, 1, 11, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg4"),
(5, 1, 15, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg5"),
(6, 1, 13, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg6"),
(7, 1, 12, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg7"),
(8, 1, 14, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg8"),
(9, 1, 10, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg9"),
(10, 1, 11, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg10"),
(11, 1, 12, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg11"),
(12, 1, 13, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg12"),
(13, 1, 14, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg13"),
(14, 1, 15, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg14"),
(15, 1, 0, 0, 0.00, 0.0, 0.0, 0, 0.04, "origSeg15"),
]
orig_rch = [
(1, 45, 9, 1, 1),
(1, 44, 9, 1, 2),
(1, 43, 9, 1, 3),
(1, 43, 10, 1, 4),
(1, 42, 10, 1, 5),
(1, 42, 11, 1, 6),
(1, 42, 12, 1, 7),
(1, 41, 12, 1, 8),
(1, 41, 13, 1, 9),
(1, 40, 13, 1, 10),
(1, 40, 14, 1, 11),
(1, 39, 14, 1, 12),
(1, 39, 15, 1, 13),
(1, 39, 16, 1, 14),
(1, 39, 17, 1, 15),
(1, 38, 17, 1, 16),
(1, 38, 18, 1, 17),
(1, 38, 19, 1, 18),
(1, 38, 20, 1, 19),
(1, 38, 21, 1, 20),
(1, 38, 22, 1, 21),
(1, 38, 23, 1, 22),
(1, 37, 24, 1, 23),
(1, 37, 25, 1, 24),
(1, 36, 25, 1, 25),
(1, 36, 26, 1, 26),
(1, 35, 26, 1, 27),
(1, 35, 27, 1, 28),
(1, 36, 28, 1, 29),
(1, 36, 29, 1, 30),
(1, 36, 30, 1, 31),
(1, 36, 31, 1, 32),
(1, 36, 32, 1, 33),
(1, 35, 32, 1, 34),
(1, 35, 33, 1, 35),
(1, 34, 33, 1, 36),
(1, 34, 34, 1, 37),
(1, 33, 34, 1, 38),
(1, 33, 35, 1, 39),
(1, 32, 35, 1, 40),
(1, 32, 36, 1, 41),
(1, 32, 37, 1, 42),
(1, 53, 37, 2, 1),
(1, 52, 37, 2, 2),
(1, 52, 38, 2, 3),
(1, 51, 38, 2, 4),
(1, 50, 38, 2, 5),
(1, 50, 39, 2, 6),
(1, 49, 39, 2, 7),
(1, 48, 39, 2, 8),
(1, 47, 39, 2, 9),
(1, 47, 40, 2, 10),
(1, 46, 40, 2, 11),
(1, 45, 40, 2, 12),
(1, 45, 39, 2, 13),
(1, 44, 39, 2, 14),
(1, 43, 38, 2, 15),
(1, 42, 38, 2, 16),
(1, 41, 38, 2, 17),
(1, 40, 38, 2, 18),
(1, 40, 39, 2, 19),
(1, 39, 39, 2, 20),
(1, 38, 39, 2, 21),
(1, 37, 40, 2, 22),
(1, 36, 40, 2, 23),
(1, 36, 41, 2, 24),
(1, 35, 41, 2, 25),
(1, 34, 41, 2, 26),
(1, 33, 41, 2, 27),
(1, 32, 41, 2, 28),
(1, 31, 42, 2, 29),
(1, 31, 33, 3, 1),
(1, 31, 34, 3, 2),
(1, 31, 35, 3, 3),
(1, 31, 36, 3, 4),
(1, 31, 37, 3, 5),
(1, 48, 48, 4, 1),
(1, 47, 48, 4, 2),
(1, 46, 48, 4, 3),
(1, 46, 47, 4, 4),
(1, 45, 47, 4, 5),
(1, 44, 47, 4, 6),
(1, 43, 47, 4, 7),
(1, 42, 47, 4, 8),
(1, 41, 47, 4, 9),
(1, 41, 48, 4, 10),
(1, 40, 48, 4, 11),
(1, 39, 48, 4, 12),
(1, 38, 47, 4, 13),
(1, 37, 47, 4, 14),
(1, 36, 48, 4, 15),
(1, 35, 48, 4, 16),
(1, 35, 49, 4, 17),
(1, 34, 49, 4, 18),
(1, 34, 50, 4, 19),
(1, 33, 50, 4, 20),
(1, 55, 72, 5, 1),
(1, 54, 72, 5, 2),
(1, 53, 72, 5, 3),
(1, 52, 72, 5, 4),
(1, 51, 72, 5, 5),
(1, 50, 73, 5, 6),
(1, 49, 73, 5, 7),
(1, 48, 73, 5, 8),
(1, 48, 74, 5, 9),
(1, 47, 74, 5, 10),
(1, 46, 75, 5, 11),
(1, 45, 75, 5, 12),
(1, 45, 76, 5, 13),
(1, 44, 76, 5, 14),
(1, 45, 62, 6, 1),
(1, 44, 62, 6, 2),
(1, 43, 62, 6, 3),
(1, 43, 63, 6, 4),
(1, 42, 63, 6, 5),
(1, 41, 63, 6, 6),
(1, 40, 63, 6, 7),
(1, 24, 55, 7, 1),
(1, 25, 55, 7, 2),
(1, 25, 56, 7, 3),
(1, 26, 56, 7, 4),
(1, 27, 56, 7, 5),
(1, 28, 57, 7, 6),
(1, 29, 57, 7, 7),
(1, 30, 57, 7, 8),
(1, 31, 57, 7, 9),
(1, 32, 57, 7, 10),
(1, 33, 57, 7, 11),
(1, 33, 58, 7, 12),
(1, 34, 58, 7, 13),
(1, 34, 59, 7, 14),
(1, 35, 59, 7, 15),
(1, 36, 59, 7, 16),
(1, 37, 60, 7, 17),
(1, 23, 71, 8, 1),
(1, 24, 71, 8, 2),
(1, 25, 71, 8, 3),
(1, 26, 71, 8, 4),
(1, 27, 72, 8, 5),
(1, 27, 73, 8, 6),
(1, 28, 73, 8, 7),
(1, 29, 73, 8, 8),
(1, 30, 73, 8, 9),
(1, 31, 73, 8, 10),
(1, 32, 73, 8, 11),
(1, 33, 73, 8, 12),
(1, 34, 73, 8, 13),
(1, 34, 74, 8, 14),
(1, 35, 74, 8, 15),
(1, 36, 74, 8, 16),
(1, 36, 73, 8, 17),
(1, 37, 73, 8, 18),
(1, 38, 72, 8, 19),
(1, 39, 72, 8, 20),
(1, 40, 72, 8, 21),
(1, 41, 72, 8, 22),
(1, 42, 72, 8, 23),
(1, 42, 73, 8, 24),
(1, 31, 38, 9, 1),
(1, 31, 39, 9, 2),
(1, 31, 40, 9, 3),
(1, 31, 41, 9, 4),
(1, 31, 42, 9, 5),
(1, 30, 42, 9, 6),
(1, 30, 43, 10, 1),
(1, 30, 44, 10, 2),
(1, 29, 44, 10, 3),
(1, 29, 45, 10, 4),
(1, 29, 46, 10, 5),
(1, 29, 47, 10, 6),
(1, 30, 47, 10, 7),
(1, 30, 48, 10, 8),
(1, 31, 49, 10, 9),
(1, 32, 50, 10, 10),
(1, 32, 51, 11, 1),
(1, 33, 52, 11, 2),
(1, 33, 53, 11, 3),
(1, 34, 53, 11, 4),
(1, 34, 54, 11, 5),
(1, 35, 54, 11, 6),
(1, 35, 55, 11, 7),
(1, 35, 56, 11, 8),
(1, 36, 57, 11, 9),
(1, 36, 58, 11, 10),
(1, 36, 59, 11, 11),
(1, 37, 59, 11, 12),
(1, 37, 60, 11, 13),
(1, 38, 60, 11, 14),
(1, 38, 61, 12, 1),
(1, 38, 62, 12, 2),
(1, 38, 63, 12, 3),
(1, 39, 63, 12, 4),
(1, 39, 64, 13, 1),
(1, 39, 65, 13, 2),
(1, 40, 65, 13, 3),
(1, 40, 66, 13, 4),
(1, 40, 67, 13, 5),
(1, 40, 68, 13, 6),
(1, 41, 69, 13, 7),
(1, 41, 70, 13, 8),
(1, 42, 71, 13, 9),
(1, 42, 72, 13, 10),
(1, 42, 73, 13, 11),
(1, 42, 73, 14, 1),
(1, 43, 73, 14, 2),
(1, 43, 74, 14, 3),
(1, 43, 75, 14, 4),
(1, 44, 75, 14, 5),
(1, 44, 76, 14, 6),
(1, 44, 77, 15, 1),
(1, 44, 78, 15, 2),
(1, 44, 79, 15, 3),
(1, 45, 79, 15, 4),
]
# These are zero based
sfrcells = [
(0, 44, 8),
(0, 43, 8),
(0, 42, 8),
(0, 42, 9),
(0, 41, 9),
(0, 41, 10),
(0, 41, 11),
(0, 40, 11),
(0, 40, 12),
(0, 39, 12),
(0, 39, 13),
(0, 38, 13),
(0, 38, 14),
(0, 38, 15),
(0, 38, 16),
(0, 37, 16),
(0, 37, 17),
(0, 37, 18),
(0, 37, 19),
(0, 37, 20),
(0, 37, 21),
(0, 37, 22),
(0, 36, 23),
(0, 36, 24),
(0, 35, 24),
(0, 35, 25),
(0, 34, 25),
(0, 34, 26),
(0, 35, 27),
(0, 35, 28),
(0, 35, 29),
(0, 35, 30),
(0, 35, 31),
(0, 34, 31),
(0, 34, 32),
(0, 33, 32),
(0, 33, 33),
(0, 32, 33),
(0, 32, 34),
(0, 31, 34),
(0, 31, 35),
(0, 31, 36),
(0, 52, 36),
(0, 51, 36),
(0, 51, 37),
(0, 50, 37),
(0, 49, 37),
(0, 49, 38),
(0, 48, 38),
(0, 47, 38),
(0, 46, 38),
(0, 46, 39),
(0, 45, 39),
(0, 44, 39),
(0, 44, 38),
(0, 43, 38),
(0, 42, 37),
(0, 41, 37),
(0, 40, 37),
(0, 39, 37),
(0, 39, 38),
(0, 38, 38),
(0, 37, 38),
(0, 36, 39),
(0, 35, 39),
(0, 35, 40),
(0, 34, 40),
(0, 33, 40),
(0, 32, 40),
(0, 31, 40),
(0, 30, 41),
(0, 30, 32),
(0, 30, 33),
(0, 30, 34),
(0, 30, 35),
(0, 30, 36),
(0, 47, 47),
(0, 46, 47),
(0, 45, 47),
(0, 45, 46),
(0, 44, 46),
(0, 43, 46),
(0, 42, 46),
(0, 41, 46),
(0, 40, 46),
(0, 40, 47),
(0, 39, 47),
(0, 38, 47),
(0, 37, 46),
(0, 36, 46),
(0, 35, 47),
(0, 34, 47),
(0, 34, 48),
(0, 33, 48),
(0, 33, 49),
(0, 32, 49),
(0, 54, 71),
(0, 53, 71),
(0, 52, 71),
(0, 51, 71),
(0, 50, 71),
(0, 49, 72),
(0, 48, 72),
(0, 47, 72),
(0, 47, 73),
(0, 46, 73),
(0, 45, 74),
(0, 44, 74),
(0, 44, 75),
(0, 43, 75),
(0, 44, 61),
(0, 43, 61),
(0, 42, 61),
(0, 42, 62),
(0, 41, 62),
(0, 40, 62),
(0, 39, 62),
(0, 23, 54),
(0, 24, 54),
(0, 24, 55),
(0, 25, 55),
(0, 26, 55),
(0, 27, 56),
(0, 28, 56),
(0, 29, 56),
(0, 30, 56),
(0, 31, 56),
(0, 32, 56),
(0, 32, 57),
(0, 33, 57),
(0, 33, 58),
(0, 34, 58),
(0, 35, 58),
(0, 36, 59),
(0, 22, 70),
(0, 23, 70),
(0, 24, 70),
(0, 25, 70),
(0, 26, 71),
(0, 26, 72),
(0, 27, 72),
(0, 28, 72),
(0, 29, 72),
(0, 30, 72),
(0, 31, 72),
(0, 32, 72),
(0, 33, 72),
(0, 33, 73),
(0, 34, 73),
(0, 35, 73),
(0, 35, 72),
(0, 36, 72),
(0, 37, 71),
(0, 38, 71),
(0, 39, 71),
(0, 40, 71),
(0, 41, 71),
(0, 41, 72),
(0, 30, 37),
(0, 30, 38),
(0, 30, 39),
(0, 30, 40),
(0, 30, 41),
(0, 29, 41),
(0, 29, 42),
(0, 29, 43),
(0, 28, 43),
(0, 28, 44),
(0, 28, 45),
(0, 28, 46),
(0, 29, 46),
(0, 29, 47),
(0, 30, 48),
(0, 31, 49),
(0, 31, 50),
(0, 32, 51),
(0, 32, 52),
(0, 33, 52),
(0, 33, 53),
(0, 34, 53),
(0, 34, 54),
(0, 34, 55),
(0, 35, 56),
(0, 35, 57),
(0, 35, 58),
(0, 36, 58),
(0, 36, 59),
(0, 37, 59),
(0, 37, 60),
(0, 37, 61),
(0, 37, 62),
(0, 38, 62),
(0, 38, 63),
(0, 38, 64),
(0, 39, 64),
(0, 39, 65),
(0, 39, 66),
(0, 39, 67),
(0, 40, 68),
(0, 40, 69),
(0, 41, 70),
(0, 41, 71),
(0, 41, 72),
(0, 41, 72),
(0, 42, 72),
(0, 42, 73),
(0, 42, 74),
(0, 43, 74),
(0, 43, 75),
(0, 43, 76),
(0, 43, 77),
(0, 43, 78),
(0, 44, 78),
]
rlen = [
90.0,
90.0,
75.0,
75.0,
75.0,
90.0,
75.0,
75.0,
75.0,
75.0,
75.0,
75.0,
90.0,
90.0,
60.0,
30.0,
102.0,
90.0,
90.0,
90.0,
102.0,
102.0,
102.0,
72.0,
30.0,
72.0,
30.0,
90.0,
102.0,
90.0,
90.0,
102.0,
30.0,
72.0,
30.0,
72.0,
30.0,
60.0,
72.0,
30.0,
102.0,
90.0,
90.0,
72.0,
30.0,
102.0,
60.0,
30.0,
90.0,
102.0,
60.0,
30.0,
90.0,
30.0,
60.0,
102.0,
102.0,
90.0,
102.0,
30.0,
60.0,
102.0,
102.0,
102.0,
60.0,
30.0,
102.0,
90.0,
90.0,
102.0,
114.0,
90.0,
90.0,
102.0,
102.0,
90.0,
90.0,
102.0,
30.0,
60.0,
90.0,
102.0,
90.0,
90.0,
60.0,
30.0,
90.0,
90.0,
90.0,
90.0,
102.0,
30.0,
60.0,
72.0,
30.0,
114.0,
90.0,
90.0,
90.0,
102.0,
102.0,
102.0,
102.0,
30.0,
60.0,
102.0,
102.0,
30.0,
72.0,
30.0,
90.0,
102.0,
30.0,
60.0,
102.0,
90.0,
102.0,
60.0,
30.0,
60.0,
102.0,
90.0,
90.0,
90.0,
90.0,
90.0,
102.0,
72.0,
30.0,
72.0,
30.0,
102.0,
90.0,
114.0,
90.0,
102.0,
90.0,
102.0,
102.0,
30.0,
102.0,
90.0,
90.0,
90.0,
90.0,
90.0,
30.0,
60.0,
90.0,
30.0,
60.0,
102.0,
90.0,
90.0,
90.0,
90.0,
30.0,
30.0,
90.0,
90.0,
90.0,
90.0,
72.0,
30.0,
90.0,
60.0,
30.0,
90.0,
90.0,
30.0,
60.0,
102.0,
114.0,
114.0,
90.0,
102.0,
30.0,
72.0,
60.0,
30.0,
102.0,
102.0,
114.0,
90.0,
60.0,
30.0,
72.0,
30.0,
102.0,
102.0,
30.0,
60.0,
120.0,
60.0,
30.0,
90.0,
90.0,
90.0,
90.0,
114.0,
102.0,
90.0,
30.0,
30.0,
30.0,
102.0,
60.0,
30.0,
90.0,
90.0,
90.0,
60.0,
30.0,
]
rgrd = [
0.150,
0.120,
0.180,
0.160,
0.130,
0.111,
0.047,
0.060,
0.040,
0.100,
0.227,
0.090,
0.042,
0.064,
0.083,
0.081,
0.062,
0.065,
0.089,
0.097,
0.141,
0.186,
0.217,
0.203,
0.206,
0.206,
0.144,
0.147,
0.135,
0.129,
0.124,
0.136,
0.162,
0.147,
0.157,
0.147,
0.115,
0.117,
0.111,
0.120,
0.099,
0.073,
0.037,
0.038,
0.060,
0.048,
0.024,
0.029,
0.032,
0.028,
0.024,
0.029,
0.033,
0.038,
0.032,
0.038,
0.051,
0.047,
0.037,
0.063,
0.063,
0.049,
0.069,
0.077,
0.063,
0.045,
0.037,
0.043,
0.048,
0.054,
0.065,
0.067,
0.091,
0.091,
0.071,
0.073,
0.021,
0.031,
0.045,
0.033,
0.029,
0.042,
0.075,
0.103,
0.092,
0.095,
0.087,
0.083,
0.094,
0.102,
0.093,
0.081,
0.099,
0.077,
0.057,
0.056,
0.044,
0.050,
0.075,
0.076,
0.074,
0.074,
0.071,
0.072,
0.056,
0.060,
0.048,
0.043,
0.049,
0.039,
0.042,
0.056,
0.081,
0.071,
0.068,
0.068,
0.068,
0.044,
0.078,
0.071,
0.051,
0.054,
0.056,
0.056,
0.050,
0.048,
0.038,
0.022,
0.049,
0.059,
0.043,
0.043,
0.045,
0.049,
0.042,
0.031,
0.016,
0.010,
0.012,
0.015,
0.012,
0.011,
0.022,
0.044,
0.056,
0.060,
0.114,
0.100,
0.067,
0.086,
0.127,
0.141,
0.118,
0.100,
0.083,
0.087,
0.100,
0.067,
0.056,
0.083,
0.100,
0.076,
0.045,
0.020,
0.053,
0.042,
0.038,
0.047,
0.047,
0.057,
0.040,
0.032,
0.045,
0.053,
0.042,
0.049,
0.094,
0.085,
0.036,
0.027,
0.030,
0.033,
0.024,
0.017,
0.025,
0.021,
0.015,
0.010,
0.010,
0.012,
0.018,
0.022,
0.017,
0.019,
0.010,
0.013,
0.022,
0.017,
0.021,
0.043,
0.044,
0.038,
0.050,
0.033,
0.021,
0.020,
0.024,
0.029,
0.020,
0.011,
0.024,
0.033,
0.022,
]
rtp = [
2458.0,
2449.0,
2337.0,
2416.0,
2413.0,
2397.0,
2393.0,
2390.0,
2386.0,
2384.0,
2367.0,
2360.0,
2355.0,
2351.0,
2344.0,
2341.0,
2335.0,
2331.0,
2323.0,
2315.0,
2305.0,
2287.0,
2267.0,
2246.0,
2239.0,
2225.0,
2218.0,
2209.0,
2195.0,
2183.0,
2171.0,
2160.0,
2149.0,
2141.0,
2134.0,
2125.0,
2119.0,
2114.0,
2106.0,
2101.0,
2092.0,
2085.0,
2146.0,
2143.0,
2141.0,
2136.0,
2134.0,
2133.0,
2131.0,
2128.0,
2126.0,
2125.0,
2123.0,
2121.0,
2119.0,
2117.0,
2112.0,
2107.0,
2103.0,
2101.0,
2096.0,
2093.0,
2087.0,
2079.0,
2073.0,
2071.0,
2068.0,
2065.0,
2060.0,
2056.0,
2048.0,
2115.0,
2109.0,
2098.0,
2091.0,
2084.0,
2112.0,
2110.0,
2108.0,
2106.0,
2104.0,
2101.0,
2096.0,
2087.0,
2079.0,
2076.0,
2069.0,
2063.0,
2054.0,
2046.0,
2035.0,
2031.0,
2026.0,
2020.0,
2017.0,
2013.0,
2000.0,
1996.0,
1991.0,
1982.0,
1976.0,
1967.0,
1961.0,
1955.0,
1953.0,
1948.0,
1942.0,
1940.0,
1937.0,
1935.0,
2003.0,
1999.0,
1994.0,
1990.0,
1985.0,
1978.0,
1972.0,
2032.0,
2030.0,
2025.0,
2021.0,
2016.0,
2011.0,
2006.0,
2001.0,
1997.0,
1992.0,
1990.0,
1989.0,
1985.0,
1983.0,
1980.0,
1976.0,
1971.0,
2051.0,
2047.0,
2045.0,
2044.0,
2043.0,
2042.0,
2041.0,
2040.0,
2039.0,
2036.0,
2031.0,
2026.0,
2022.0,
2014.0,
2010.0,
2005.0,
2001.0,
1989.0,
1976.0,
1967.0,
1958.0,
1952.0,
1945.0,
1943.0,
2076.0,
2071.0,
2061.0,
2053.0,
2048.0,
2047.0,
2041.0,
2037.0,
2036.0,
2033.0,
2029.0,
2026.0,
2023.0,
2021.0,
2017.0,
2011.0,
2006.0,
2002.0,
1998.0,
1991.0,
1988.0,
1987.0,
1985.0,
1982.0,
1978.0,
1977.0,
1975.0,
1974.0,
1973.0,
1972.0,
1970.0,
1969.0,
1968.0,
1967.0,
1966.0,
1965.0,
1964.0,
1963.0,
1961.0,
1959.0,
1958.0,
1955.0,
1949.0,
1946.0,
1943.0,
1942.0,
1941.0,
1940.0,
1938.0,
1937.0,
1935.0,
1934.0,
1933.0,
1930.0,
1929.0,
]
def get_sfrsegs():
return orig_seg
def get_sfrrchs():
return orig_rch
def get_sfrcells():
return sfrcells
def get_sfrlen():
return rlen
def get_rgrd():
return rgrd
def get_rtp():
return rtp
segs = get_sfrsegs()
rchs = get_sfrrchs()
sfrcells = get_sfrcells()
rlen = get_sfrlen()
rgrd = get_rgrd()
rtp = get_rtp()
# Define some utility functions.
def gen_mf6_sfr_connections(orig_seg, orig_rch):
"""
Defining a function that builds the new MF6 SFR connection information using
original SFR input. This is a generalized function that can be used to
convert MF2K5-based model to the new MF6 format. Currently applied to the
Sagehen and modsim models
"""
conns = []
for i in np.arange(0, len(orig_seg)):
tup = orig_seg[i]
segid = tup[0]
ioutseg = tup[2]
iupseg = tup[3]
# Get all reaches associated with segment
# Find an element in a list of tuples
allrchs = [item for item in orig_rch if item[3] == segid]
# Loop through allrchs and generate list of connections
for rchx in allrchs:
# rchx will be a tuple
upconn = []
dnconn = []
if rchx[4] == 1: # checks if first rch of segment
# Collect all segs that dump to the current one (there may not
# be any)
dumpersegs = [item for item in orig_seg if item[2] == segid]
# For every seg that outflows to current, set last reach of it
# as an upstream connection
for dumper in dumpersegs:
dumper_seg_id = dumper[0]
rch_cnt = len(
[item for item in orig_rch if item[3] == dumper_seg_id]
)
lastrch = [
item
for item in orig_rch
if item[3] == dumper_seg_id and item[4] == rch_cnt
]
idx = orig_rch.index(lastrch[0])
upconn.append(int(idx))
# Current reach is the most upstream reach for current segment
if iupseg == 0:
pass
elif iupseg > 0: # Lake connections, signified with negative
# numbers, aren't handled here
iupseg_rchs = [item for item in orig_rch if item[3] == iupseg]
# Get the index of the last reach of the segment that was
# the upstream segment in the orig sfr file
idx = orig_rch.index(iupseg_rchs[len(iupseg_rchs) - 1]) #
upconn.append(idx)
# Even if the first reach of a segment, it will have an outlet
# either the next reach in the segment, or first reach of
# outseg, which should be taken care of below
if len(allrchs) > 1:
idx = orig_rch.index(rchx)
# adjust idx for 0-based and increment to next item in list
dnconn.append(int(idx + 1) * -1)
elif rchx[4] > 1 and not rchx[4] == len(allrchs):
# Current reach is 'interior' on the original segment and
# therefore should only have 1 upstream & 1 downstream segment
idx = orig_rch.index(rchx)
# B/c 0-based, idx will already be incremented by -1
upconn.append(int(idx - 1))
# adjust idx for 0-based and increment to next item in list
dnconn.append(int(idx + 1) * -1) # all downstream connections
# are negative in MF6
if rchx[4] == len(allrchs):
# If the last reach in a multi-reach segment, always need to
# account for the reach immediately upstream (single reach segs
# dealt with above), unless of course we're dealing with a
# single reach segment like in the case of a spillway from a lk
if len(allrchs) != 1:
idx = orig_rch.index(rchx)
# B/c 0-based, idx will already be incremented by -1
upconn.append(int(idx - 1))
# Current reach is last reach in segment and may have multiple
# downstream connections, particular when dealing with
# diversions.
if ioutseg == 0:
pass
elif ioutseg > 0: # Lake connections, signified with
# negative numbers, aren't handled here
idnseg_rchs = [
item for item in orig_rch if item[3] == ioutseg and item[4] == 1
]
idx = orig_rch.index(idnseg_rchs[0])
# adjust idx for 0-based and increment to next item in list
dnconn.append(int(idx) * -1)
# In addition to ioutseg, look for all segments that may have
# the current segment as their iupseg
possible_divs = [item for item in orig_seg if item[3] == rchx[3]]
for segx in possible_divs:
# Next, peel out all first reach for any segments listed in
# possible_divs
first_rchs = [
item for item in orig_rch if item[3] == segx[0] and item[4] == 1
]
for firstx in first_rchs:
idx = orig_rch.index(firstx)
# adjust idx for 0-based & increment to nxt itm in list
dnconn.append(int(idx) * -1)
# Append the collection of upconn & dnconn as an entry in a list
idx = orig_rch.index(rchx)
# Adjust current index for 0-based
conns.append([idx] + upconn + dnconn)
return conns
def determine_runoff_conns_4mvr(elev_arr, ibnd, orig_rch, nrow, ncol):
# Get the sfr information stored in a companion script
sfr_dat = orig_rch.copy()
sfrlayout = np.zeros_like(ibnd)
for i, rchx in enumerate(sfr_dat):
row = rchx[1]
col = rchx[2]
sfrlayout[row - 1, col - 1] = i + 1
sfrlayout_new = sfrlayout.copy()
stop_candidate = False
for i in np.arange(0, nrow):
for j in np.arange(0, ncol):
# Check to ensure current cell is active
if ibnd[i, j] == 0:
continue
# Check to make sure it is not a stream cell
if not sfrlayout[i, j] == 0:
continue
# Recursively trace path by steepest decent back to a stream
curr_i = i
curr_j = j
sfrlayout_conn_candidate_elev = 10000.0
while True:
direc = 0
min_elev = elev_arr[curr_i, curr_j]
# Look straight left
if curr_j > 0:
if (
not sfrlayout[curr_i, curr_j - 1] == 0
and not ibnd[curr_i, curr_j - 1] == 0
): # Step in if neighbor is a stream cell
if elev_arr[curr_i, curr_j - 1] > 0 and (
elev_arr[curr_i, curr_j - 1] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i, curr_j - 1]
< sfrlayout_conn_candidate_elev
):
sfrlayout_conn_candidate = sfrlayout[curr_i, curr_j - 1]
sfrlayout_conn_candidate_elev = elev_arr[curr_i, curr_j - 1]
stop_candidate = True
elif (
not elev_arr[curr_i, curr_j - 1] == 0
and not ibnd[curr_i, curr_j - 1] == 0
): # Step here if neighbor is not an sfr cell
if (
elev_arr[curr_i, curr_j - 1] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i, curr_j - 1] < min_elev
):
elevcm1 = elev_arr[curr_i, curr_j - 1]
min_elev = elevcm1
direc = 2
# Look up and left
if curr_j > 0 and curr_i > 0:
if (
not sfrlayout[curr_i - 1, curr_j - 1] == 0
and not ibnd[curr_i - 1, curr_j - 1] == 0
): # Step in if neighbor is a stream cell
if elev_arr[curr_i - 1, curr_j - 1] > 0 and (
elev_arr[curr_i - 1, curr_j - 1] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i - 1, curr_j - 1]
< sfrlayout_conn_candidate_elev
):
sfrlayout_conn_candidate = sfrlayout[curr_i - 1, curr_j - 1]
sfrlayout_conn_candidate_elev = elev_arr[
curr_i - 1, curr_j - 1
]
stop_candidate = True
elif (
not elev_arr[curr_i - 1, curr_j - 1] == 0
and not ibnd[curr_i - 1, curr_j - 1] == 0
): # Step here if neighbor is not an sfr cell
if (
elev_arr[curr_i - 1, curr_j - 1] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i - 1, curr_j - 1] < min_elev
):
elevrm1cm1 = elev_arr[curr_i - 1, curr_j - 1]
min_elev = elevrm1cm1
direc = 5
# Look straight right
if curr_j < ncol - 1:
if (
not sfrlayout[curr_i, curr_j + 1] == 0
and not ibnd[curr_i, curr_j + 1] == 0
): # Step in if neighbor is a stream cell
if elev_arr[curr_i, curr_j + 1] > 0 and (
elev_arr[curr_i, curr_j + 1] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i, curr_j + 1]
< sfrlayout_conn_candidate_elev
):
sfrlayout_conn_candidate = sfrlayout[curr_i, curr_j + 1]
sfrlayout_conn_candidate_elev = elev_arr[curr_i, curr_j + 1]
stop_candidate = True
elif (
not elev_arr[curr_i, curr_j + 1] == 0
and not ibnd[curr_i, curr_j + 1] == 0
): # Step here if neighbor is not an sfr cell
if (
elev_arr[curr_i, curr_j + 1] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i, curr_j + 1] < min_elev
):
elevcm1 = elev_arr[curr_i, curr_j + 1]
min_elev = elevcm1
direc = 4
# Look straight right and down
if curr_i < nrow - 1 and curr_j < ncol - 1:
if (
not sfrlayout[curr_i + 1, curr_j + 1] == 0
and not ibnd[curr_i + 1, curr_j + 1] == 0
): # Step in if neighbor is a stream cell
if elev_arr[curr_i + 1, curr_j + 1] > 0 and (
elev_arr[curr_i + 1, curr_j + 1] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i + 1, curr_j + 1]
< sfrlayout_conn_candidate_elev
):
sfrlayout_conn_candidate = sfrlayout[curr_i + 1, curr_j + 1]
sfrlayout_conn_candidate_elev = elev_arr[
curr_i + 1, curr_j + 1
]
stop_candidate = True
elif (
not elev_arr[curr_i + 1, curr_j + 1] == 0
and not ibnd[curr_i + 1, curr_j + 1] == 0
): # Step here if neighbor is not an sfr cell
if (
elev_arr[curr_i + 1, curr_j + 1] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i + 1, curr_j + 1] < min_elev
):
elevrp1cp1 = elev_arr[curr_i + 1, curr_j + 1]
min_elev = elevrp1cp1
direc = 7
# Look straight up
if curr_i > 0:
if (
not sfrlayout[curr_i - 1, curr_j] == 0
and not ibnd[curr_i - 1, curr_j] == 0
): # Step in if neighbor is a stream cell
if elev_arr[curr_i - 1, curr_j] > 0 and (
elev_arr[curr_i - 1, curr_j] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i - 1, curr_j]
< sfrlayout_conn_candidate_elev
):
sfrlayout_conn_candidate = sfrlayout[curr_i - 1, curr_j]
sfrlayout_conn_candidate_elev = elev_arr[curr_i - 1, curr_j]
stop_candidate = True
elif (
not elev_arr[curr_i - 1, curr_j] == 0
and not ibnd[curr_i - 1, curr_j] == 0
): # Step here if neighbor is not an sfr cell
if (
elev_arr[curr_i - 1, curr_j] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i - 1, curr_j] < min_elev
):
elevcm1 = elev_arr[curr_i - 1, curr_j]
min_elev = elevcm1
direc = 3
# Look up and right
if curr_i > 0 and curr_j < ncol - 1:
if (
not sfrlayout[curr_i - 1, curr_j + 1] == 0
and not ibnd[curr_i - 1, curr_j + 1] == 0
): # Step in if neighbor is a stream cell
if elev_arr[curr_i - 1, curr_j + 1] > 0 and (
elev_arr[curr_i - 1, curr_j + 1] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i - 1, curr_j + 1]
< sfrlayout_conn_candidate_elev
):
sfrlayout_conn_candidate = sfrlayout[curr_i - 1, curr_j + 1]
sfrlayout_conn_candidate_elev = elev_arr[
curr_i - 1, curr_j + 1
]
stop_candidate = True
elif (
not elev_arr[curr_i - 1, curr_j + 1] == 0
and not ibnd[curr_i - 1, curr_j + 1] == 0
): # Step here if neighbor is not an sfr cell
if (
elev_arr[curr_i - 1, curr_j + 1] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i - 1, curr_j + 1] < min_elev
):
elevrm1cp1 = elev_arr[curr_i - 1, curr_j + 1]
min_elev = elevrm1cp1
direc = 6
# Look straight down
if curr_i < nrow - 1:
if (
not sfrlayout[curr_i + 1, curr_j] == 0
and not ibnd[curr_i + 1, curr_j] == 0
): # Step in if neighbor is a stream cell
if elev_arr[curr_i + 1, curr_j] > 0 and (
elev_arr[curr_i + 1, curr_j] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i + 1, curr_j]
< sfrlayout_conn_candidate_elev
):
sfrlayout_conn_candidate = sfrlayout[curr_i + 1, curr_j]
sfrlayout_conn_candidate_elev = elev_arr[curr_i + 1, curr_j]
stop_candidate = True
elif (
not elev_arr[curr_i + 1, curr_j] == 0
and not ibnd[curr_i + 1, curr_j] == 0
): # Step here if neighbor is not an sfr cell
if (
elev_arr[curr_i + 1, curr_j] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i + 1, curr_j] < min_elev
):
elevrp1 = elev_arr[curr_i + 1, curr_j]
min_elev = elevrp1
direc = 1
# Look down and left
if curr_i < nrow - 1 and curr_j > 0:
if (
not sfrlayout[curr_i + 1, curr_j - 1] == 0
and not ibnd[curr_i + 1, curr_j - 1] == 0
): # Step in if neighbor is a stream cell
if elev_arr[curr_i + 1, curr_j - 1] > 0 and (
elev_arr[curr_i + 1, curr_j - 1] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i + 1, curr_j - 1]
< sfrlayout_conn_candidate_elev
):
sfrlayout_conn_candidate = sfrlayout[curr_i + 1, curr_j - 1]
sfrlayout_conn_candidate_elev = elev_arr[
curr_i + 1, curr_j - 1
]
stop_candidate = True
elif (
not elev_arr[curr_i + 1, curr_j - 1] == 0
and not ibnd[curr_i + 1, curr_j - 1] == 0
): # Step here if neighbor is not an sfr cell
if (
elev_arr[curr_i + 1, curr_j - 1] < elev_arr[curr_i, curr_j]
and elev_arr[curr_i + 1, curr_j - 1] < min_elev
):
elevrp1cm1 = elev_arr[curr_i + 1, curr_j - 1]
min_elev = elevrp1cm1
direc = 8
# if stop candidate found, don't move the cell indices
if not stop_candidate:
# Direc corresponds to:
# |----------------------
# | 5 | 3 | 6 |
# |----------------------
# | 2 | cur_cel | 4 |
# |----------------------
# | 8 | 1 | 7 |
# |----------------------
if direc == 0:
break
elif direc == 1:
curr_i += 1
elif direc == 2:
curr_j -= 1
elif direc == 3:
curr_i -= 1
elif direc == 4:
curr_j += 1
elif direc == 5:
curr_i -= 1
curr_j -= 1
elif direc == 6:
curr_i -= 1
curr_j += 1
elif direc == 7:
curr_i += 1
curr_j += 1
elif direc == 8:
curr_i += 1
curr_j -= 1
if stop_candidate:
sfrlayout_new[i, j] = sfrlayout_conn_candidate
stop_candidate = False
break # Bust out of while loop
elif not stop_candidate:
# Check if encountered ibnd == 0, which may be a lake or
# boundary that drains out of model
if ibnd[curr_i, curr_j] == 0:
# This condition is dealt with after looping through
# all cells, see comment "Last step is set..."
break
pass # Commence next downstream cell search
# Last step is set the 0's in the vicinity of the lake equal to the
# negative of the lake connection
for i in np.arange(0, nrow):
for j in np.arange(0, ncol):
if sfrlayout_new[i, j] == 0 and ibnd[i, j] > 0:
sfrlayout_new[i, j] = -1
return sfrlayout_new
# Define the connections
conns = gen_mf6_sfr_connections(segs, rchs)
rwid = 3.0
rbth = 1.0
rhk = 0.6
man = 0.04
ustrf = 1.0
ndv = 0
pkdat = []
for i in np.arange(len(rlen)):
ncon = len(conns[i]) - 1
pkdat.append(
(
i,
sfrcells[i],
rlen[i],
rwid,
rgrd[i],
rtp[i],
rbth,
rhk,
man,
ncon,
ustrf,
ndv,
)
)
# Instantiating MODFLOW 6 drain package
# Here, the drain (DRN) package is used to simulate groundwater discharge to
# land surface to keep this water separate from rejected infiltrated simulated
# by the UZF package. Need to cycle through all land surface cells and create a
# drain for handling groundwater discharge to land surface
drn_spd = []
drn_dict = {}
drn_dict_rev = {}
# Use an arbitrarily high conductance term to avoid impeding groundwater disch.
cond = 10000
# See definition of auxdepthname in DRN package doc to learn more about param
ddrn = -0.25
idrnno = 0
for i in np.arange(0, top.shape[0]):
for j in np.arange(0, top.shape[1]):
# Don't add drains to sfr and chd cells:
sfrCell_bool = (
1
if len([itm for itm in sfrcells if itm[1] == i and itm[2] == j]) > 0
else 0
)
chdCell_bool = (
1
if len([itm for itm in listOfChdCoords if itm[1] == i and itm[2] == j]) > 0
else 0
)
if idomain1[i, j] and not sfrCell_bool and not chdCell_bool:
drn_spd.append([(0, i, j), top[i, j], cond, ddrn]) # 'ddrn',
# append dictionary of drain indices
drn_dict.update({(i, j): idrnno})
drn_dict_rev.update({idrnno: (i, j)})
idrnno += 1
# Prepping input for UZF package
fname = "iuzbnd.txt"
fpath = pooch.retrieve(
url=f"https://github.com/MODFLOW-USGS/modflow6-examples/raw/master/data/{sim_name}/{fname}",
fname=fname,
path=data_path,
known_hash="md5:280faee0782e0de5f2046b38ac20c271",
)
iuzbnd = np.loadtxt(fpath)
fname = "thts.txt"
fpath = pooch.retrieve(
url=f"https://github.com/MODFLOW-USGS/modflow6-examples/raw/master/data/{sim_name}/{fname}",
fname=fname,
path=data_path,
known_hash="md5:6ebb033605c7e4700ddcf3f2e51ac371",
)
thts = np.loadtxt(fpath)
fname = "vks.txt"
fpath = pooch.retrieve(
url=f"https://github.com/MODFLOW-USGS/modflow6-examples/raw/master/data/{sim_name}/{fname}",
fname=fname,
path=data_path,
known_hash="md5:61892e6cff6dae1879112c9eb03a1614",
)
uzk33 = np.loadtxt(fpath)
fname = "finf_gradient.txt"
fpath = pooch.retrieve(
url=f"https://github.com/MODFLOW-USGS/modflow6-examples/raw/master/data/{sim_name}/{fname}",
fname=fname,
path=data_path,
known_hash="md5:e5ac0a0b27a66dd9f2eff63a63c6e6fe",
)
finf_grad = np.loadtxt(fpath)
# next, load time series of multipliers
fname = "uzf_ts.dat"
fpath = pooch.retrieve(
url=f"https://github.com/MODFLOW-USGS/modflow6-examples/raw/master/data/{sim_name}/{fname}",
fname=fname,
path=data_path,
known_hash="md5:969ed0391d64804ec8395a578eb08ed1",
)
uz_ts = pd.read_csv(fpath, delim_whitespace=True, header=0)
# Need to set iuzbnd inactive where there are constant head cells, or where the
# model grid is inactive
cells2inactivate = idomain1 - iuzbnd
iuzbnd = iuzbnd + cells2inactivate
for chd_cell in listOfChdCoords:
iuzbnd[chd_cell[1], chd_cell[2]] = 0
ha = 0.0
hroot = 0.0
rootact = 0.0
uzf_packagedata = []
pd0 = []
iuzno_cell_dict = {}
iuzno_dict_rev = {}
iuzno = 0
surfdep = 0.1
# Set up the UZF static variables
nuzfcells = 0
for k in range(nlay):
for i in range(0, iuzbnd.shape[0] - 1):
for j in range(0, iuzbnd.shape[1] - 1):
if iuzbnd[i, j] != 0:
nuzfcells += 1
if k == 0:
lflag = 1
# establish new dictionary entry for current cell
# addresses & iuzno connections are both 0-based
iuzno_cell_dict.update({(i, j): iuzno})
# For post-processing the mvr output, need reverse dict
iuzno_dict_rev.update({iuzno: (i, j)})
else:
lflag = 0
# Set the vertical connection, which is the cell below,
# but in this 1 layer model set to -1 which flopy adjusts to 0
ivertcon = -1
vks = uzk33[i, j]
thtr = uz_ts["extwc"].iloc[0]
thtsx = thts[i, j]
thti = thtr + 0.01
eps = 4.0
# Set the boundname for the land surface cells
bndnm = "sage"
uz = [
iuzno,
(k, i, j),
lflag,
ivertcon,
surfdep,
vks,
thtr,
thtsx,
thti,
eps,
bndnm,
]
uzf_packagedata.append(uz)
iuzno += 1
# Next prepare the stress period data for UZF
# Store the steady state uzf stresses in dictionary
uzf_perioddata = {}
for t in range(num_ts):
iuzno = 0
spdx = []
for i in range(0, iuzbnd.shape[0] - 1):
for j in range(0, iuzbnd.shape[1] - 1):
if iuzbnd[i, j] != 0:
finf = finf_grad[i, j] * uz_ts["finf"].iloc[t]
pet = uz_ts["pet"].iloc[t]
extdp = uz_ts["rootdepth"].iloc[t]
extwc = uz_ts["extwc"].iloc[t]
spdx.append([iuzno, finf, pet, extdp, extwc, ha, hroot, rootact])
iuzno += 1
uzf_perioddata.update({t: spdx})
# Set up runoff connections, which relies on a helper function inside a
# companion script
#
# Leverages a function that uses the top elevation array and SFR locations to
# calculate an array that is the equivalent of the irunbnd array from the UZF1
# package. The MVR package will be used to establish these connection in MF6
# since the IRUNBND functionality went away in the new MF6 framework.
irunbnd = determine_runoff_conns_4mvr(top, idomain1, rchs, nrow, ncol)
iuzno = 0
k = 0 # Hard-wire the layer no.
first0ok = True
static_mvrperioddata = []
for i in range(0, iuzbnd.shape[0]):
for j in range(0, iuzbnd.shape[1]):
if irunbnd[i, j] > 0: # This is a uzf -> sfr connection
iuzno = iuzno_cell_dict.get((i, j))
if iuzno or first0ok:
static_mvrperioddata.append(
("UZF-1", iuzno, "SFR-1", irunbnd[i, j] - 1, "FACTOR", 1.0)
)
drn_idx = drn_dict.get((i, j))
if drn_idx:
static_mvrperioddata.append(
("DRN-1", drn_idx, "SFR-1", irunbnd[i, j] - 1, "FACTOR", 1.0)
)
first0ok = False
mvrspd = {0: static_mvrperioddata}
mvrpack = [["UZF-1"], ["SFR-1"], ["DRN-1"]]
maxpackages = len(mvrpack)
maxmvr = 10000 # Something arbitrarily high
# ### Model setup
#
# Define functions to build models, write input files, and run the simulation.
/tmp/ipykernel_12502/4017089857.py:1780: FutureWarning: The 'delim_whitespace' keyword in pd.read_csv is deprecated and will be removed in a future version. Use ``sep='\s+'`` instead
uz_ts = pd.read_csv(fpath, delim_whitespace=True, header=0)
[3]:
def build_models(silent=False):
# Instantiate the MODFLOW 6 simulation
sim_ws = os.path.join(workspace, sim_name)
sim = flopy.mf6.MFSimulation(
sim_name=sim_name,
version="mf6",
sim_ws=sim_ws,
exe_name="mf6",
)
# Instantiating MODFLOW 6 time discretization
tdis_rc = []
for i in range(len(perlen)):
tdis_rc.append((perlen[i], nstp[i], tsmult[i]))
flopy.mf6.ModflowTdis(sim, nper=nper, perioddata=tdis_rc, time_units=time_units)
# Instantiating MODFLOW 6 groundwater flow model
gwfname = sim_name
gwf = flopy.mf6.ModflowGwf(
sim,
modelname=gwfname,
save_flows=True,
newtonoptions="newton",
model_nam_file=f"{gwfname}.nam",
)
# Instantiating MODFLOW 6 solver for flow model
imsgwf = flopy.mf6.ModflowIms(
sim,
print_option="summary",
outer_dvclose=hclose,
outer_maximum=nouter,
under_relaxation="dbd",
linear_acceleration="BICGSTAB",
under_relaxation_theta=0.7,
under_relaxation_kappa=0.08,
under_relaxation_gamma=0.05,
under_relaxation_momentum=0.0,
inner_dvclose=hclose,
rcloserecord="1000.0 strict",
inner_maximum=ninner,
relaxation_factor=relax,
number_orthogonalizations=2,
preconditioner_levels=8,
preconditioner_drop_tolerance=0.001,
filename=f"{gwfname}.ims",
)
sim.register_ims_package(imsgwf, [gwf.name])
# Instantiating MODFLOW 6 discretization package
flopy.mf6.ModflowGwfdis(
gwf,
nlay=nlay,
nrow=nrow,
ncol=ncol,
delr=delr,
delc=delc,
top=top,
botm=bot1,
idomain=idomain,
filename=f"{gwfname}.dis",
)
# Instantiating MODFLOW 6 initial conditions package for flow model
flopy.mf6.ModflowGwfic(gwf, strt=strt, filename=f"{gwfname}.ic")
# Instantiating MODFLOW 6 node-property flow package
flopy.mf6.ModflowGwfnpf(
gwf,
save_flows=False,
alternative_cell_averaging="AMT-HMK",
icelltype=icelltype,
k=k11,
k33=k33,
save_specific_discharge=False,
filename=f"{gwfname}.npf",
)
# Instantiate MODFLOW 6 storage package
flopy.mf6.ModflowGwfsto(
gwf,
ss=2e-6,
sy=sy,
iconvert=iconvert,
steady_state={0: True},
transient={1: True},
filename=f"{gwfname}.sto",
)
# Instantiating MODFLOW 6 output control package for flow model
flopy.mf6.ModflowGwfoc(
gwf,
budget_filerecord=f"{gwfname}.bud",
head_filerecord=f"{gwfname}.hds",
headprintrecord=[("COLUMNS", 10, "WIDTH", 15, "DIGITS", 6, "GENERAL")],
saverecord=[("HEAD", "LAST"), ("BUDGET", "LAST")],
printrecord=[("HEAD", "LAST"), ("BUDGET", "LAST")],
)
# Instantiating MODFLOW 6 constant head package
chdspdx = {0: chdspd}
flopy.mf6.ModflowGwfchd(
gwf,
maxbound=len(chdspd),
stress_period_data=chdspdx,
save_flows=False,
pname="CHD-1",
filename=f"{gwfname}.chd",
)
maxbound = len(drn_spd) # The total number
spd = {0: drn_spd}
flopy.mf6.ModflowGwfdrn(
gwf,
pname="DRN-1",
auxiliary=["ddrn"],
auxdepthname="ddrn",
print_input=False,
print_flows=False,
maxbound=maxbound,
mover=True,
stress_period_data=spd, # wel_spd established in the MVR setup
boundnames=False,
save_flows=True,
filename=f"{gwfname}.drn",
)
# Instantiating MODFLOW 6 streamflow routing package
flopy.mf6.ModflowGwfsfr(
gwf,
print_stage=False,
print_flows=False,
budget_filerecord=gwfname + ".sfr.bud",
save_flows=True,
mover=True,
pname="SFR-1",
time_conversion=86400.0,
boundnames=True,
nreaches=len(conns),
packagedata=pkdat,
connectiondata=conns,
perioddata=None,
filename=f"{gwfname}.sfr",
)
# Instantiating MODFLOW 6 unsaturated zone flow package
flopy.mf6.ModflowGwfuzf(
gwf,
nuzfcells=nuzfcells,
boundnames=True,
mover=True,
ntrailwaves=15,
nwavesets=150,
print_flows=False,
save_flows=True,
simulate_et=True,
linear_gwet=True,
packagedata=uzf_packagedata,
perioddata=uzf_perioddata,
budget_filerecord=f"{gwfname}.uzf.bud",
pname="UZF-1",
filename=f"{gwfname}.uzf",
)
flopy.mf6.ModflowGwfmvr(
gwf,
pname="MVR-1",
maxmvr=maxmvr,
print_flows=False,
maxpackages=maxpackages,
packages=mvrpack,
perioddata=mvrspd,
budget_filerecord=gwfname + ".mvr.bud",
filename=f"{gwfname}.mvr",
)
return sim
def write_models(sim, silent=True):
sim.write_simulation(silent=silent)
@timed
def run_models(sim, silent=True):
success, buff = sim.run_simulation(silent=silent)
assert success, buff
Plotting results
Define functions to plot model results.
[4]:
# Figure properties
figure_size = (6, 6)
figure_size_ts = (6, 3)
def plot_results(mf6):
with styles.USGSPlot():
# Generate a plot of FINF distribution
finf_plt = finf_grad.copy()
finf_plt[idomain1 == 0] = np.nan
fig = plt.figure(figsize=figure_size, dpi=300, tight_layout=True)
ax = fig.add_subplot(1, 1, 1)
plt.imshow(finf_plt, cmap="jet")
title = "Precipitation distribution"
cbar = plt.colorbar(shrink=0.5)
cbar.ax.set_title("Infiltration\nrate\nfactor", pad=20)
plt.xlabel("Column Number")
plt.ylabel("Row Number")
styles.heading(heading=title)
if plot_show:
plt.show()
if plot_save:
fpth = figs_path / f"{mf6.name}-finfFact.png"
fig.savefig(fpth)
# Start by retrieving some output
gwf = mf6.get_model(next(iter(mf6.model_names)))
hdsobj = gwf.output.head()
modobj = gwf.output.budget()
sfrobj = gwf.sfr.output.budget()
uzfobj = gwf.uzf.output.budget()
ckstpkper = modobj.get_kstpkper()
hds = []
depths = []
hd_tmp = hdsobj.get_data(kstpkper=ckstpkper[0])
hd_tmp = np.where(hd_tmp == 1e30, 0, hd_tmp)
hds.append(hd_tmp)
depths.append(top - hd_tmp[0, :, :])
depths = np.array(depths)
depths = depths[0, :, :]
# Generate a plot of the gw table depths for the steady state stress per
depths[idomain1 == 0] = np.nan
fig = plt.figure(figsize=figure_size, dpi=300, tight_layout=True)
ax = fig.add_subplot(1, 1, 1)
plt.imshow(depths, vmin=0, vmax=25, cmap="jet")
cbar = plt.colorbar(shrink=0.5, ticks=[0, 5, 10, 15, 20, 25])
cbar.ax.set_yticklabels(["0", "5", "10", "15", "20", "> 25"])
cbar.ax.set_title("Depth to\nwater\ntable,\nin m", pad=20)
plt.xlabel("Column Number")
plt.ylabel("Row Number")
title = "Depth To Groundwater"
styles.heading(heading=title)
if plot_show:
plt.show()
if plot_save:
fpth = figs_path / f"{mf6.name}-gwDepth.png"
fig.savefig(fpth)
drn_disQ = []
uzrech = []
finf_tot = []
sfr_gwsw = []
sfr_flow = []
rejinf = []
uzet = []
gwet = []
outflow = []
for kstpkper in ckstpkper:
# 1. Compile groundwater discharge to land surface
drn_tmp = modobj.get_data(kstpkper=kstpkper, text=" DRN-TO-MVR")
drn_arr = np.zeros_like(top)
for itm in drn_tmp[0]:
i, j = drn_dict_rev[itm[1] - 1]
drn_arr[i, j] = itm[2]
drn_disQ.append(drn_arr)
# 2. Compile groundwater discharge to stream cells
sfr_tmp = sfrobj.get_data(kstpkper=kstpkper, text=" GWF")
sfr_arr = np.zeros_like(top)
for x, itm in enumerate(sfr_tmp[0]):
i = sfrcells[x][1]
j = sfrcells[x][2]
sfr_arr[i, j] = itm[2]
sfr_gwsw.append(sfr_arr)
# 3. Compile Infiltrated amount
uzf_tmp = uzfobj.get_data(kstpkper=kstpkper, text=" INFILTRATION")
finf_arr = np.zeros_like(top)
for itm in uzf_tmp[0]:
i, j = iuzno_dict_rev[itm[0] - 1]
finf_arr[i, j] = itm[2]
finf_tot.append(finf_arr)
# 4. Compile recharge from UZF
uzrch_tmp = uzfobj.get_data(kstpkper=kstpkper, text=" GWF")
uzrch_arr = np.zeros_like(top)
for itm in uzrch_tmp[0]:
i, j = iuzno_dict_rev[itm[0] - 1]
uzrch_arr[i, j] = itm[2]
uzrech.append(uzrch_arr)
# 5. Compile rejected infiltration
rejinf_tmp = uzfobj.get_data(kstpkper=kstpkper, text=" REJ-INF-TO-MVR")
rejinf_arr = np.zeros_like(top)
for itm in rejinf_tmp[0]:
i, j = iuzno_dict_rev[itm[0] - 1]
rejinf_arr[i, j] = itm[2]
rejinf.append(rejinf_arr)
# 6. Compile unsat ET
uzet_tmp = uzfobj.get_data(kstpkper=kstpkper, text=" UZET")
uzet_arr = np.zeros_like(top)
for itm in uzet_tmp[0]:
i, j = iuzno_dict_rev[itm[0] - 1]
uzet_arr[i, j] = itm[2]
uzet.append(uzet_arr)
# 7. Compile groundwater ET
gwet_tmp = modobj.get_data(kstpkper=kstpkper, text=" UZF-GWET")
gwet_arr = np.zeros_like(top)
for itm in gwet_tmp[0]:
i, j = iuzno_dict_rev[itm[1] - 1]
gwet_arr[i, j] = itm[2]
gwet.append(gwet_arr)
# 8. Get flows at outlet
outletQ = sfrobj.get_data(kstpkper=kstpkper, text=" FLOW-JA-FACE")
outflow.append(outletQ[0][-1][2])
drn_disQ = np.array(drn_disQ)
sfr_gwsw = np.array(sfr_gwsw)
finf_tot = np.array(finf_tot)
uzrech = np.array(uzrech)
rejinf = np.array(rejinf)
uzet = np.array(uzet)
gwet = np.array(gwet)
outflow = np.array(outflow)
drn_disQ_ts = drn_disQ.sum(axis=-1).sum(axis=-1)
sfr_gwsw_ts = sfr_gwsw.sum(axis=-1).sum(axis=-1)
finf_tot_ts = finf_tot.sum(axis=-1).sum(axis=-1)
uzrech_ts = uzrech.sum(axis=-1).sum(axis=-1)
rejinf_ts = rejinf.sum(axis=-1).sum(axis=-1)
uzet_ts = uzet.sum(axis=-1).sum(axis=-1)
gwet_ts = gwet.sum(axis=-1).sum(axis=-1)
rng = pd.date_range(start="11/1/1999", end="10/31/2000", freq="D")
data = {
"Recharge": abs(uzrech_ts[0:366]),
"Infiltration": abs(finf_tot_ts[0:366]),
"GroundwaterET": abs(gwet_ts[0:366]),
"UnsaturatedZoneET": abs(uzet_ts[0:366]),
}
vals1 = pd.DataFrame(data, index=rng)
fig = plt.figure(figsize=figure_size_ts, dpi=300, tight_layout=True)
ax = fig.add_subplot(1, 1, 1)
vals1.Infiltration.plot(style="k-", linewidth=0.3)
vals1.Recharge.plot(style="b-", linewidth=0.7)
vals1.GroundwaterET.plot(
style="-", color="darkgreen", linewidth=0.7, label="Groundwater ET"
)
vals1.UnsaturatedZoneET.plot(
style="-", color="orange", linewidth=1, label="Unsaturated Zone ET"
)
ax.set_ylim(0, 700000)
plt.tick_params(
axis="x", # changes apply to the x-axis
which="both", # both major and minor ticks are affected
bottom=False, # ticks along the bottom edge are off
top=False, # ticks along the top edge are off
labelbottom=True,
) # labels along the bottom edge are off
ax.set_xlabel("Month")
ax.set_ylabel("Volumetric Rate, $m^3$ per day")
styles.graph_legend(ax)
title = "Unsaturated Zone Flow Budget"
styles.heading(heading=title)
if plot_show:
plt.show()
if plot_save:
fpth = figs_path / f"{mf6.name}-uzFlow.png"
fig.savefig(fpth)
data_sfr = {
"GroundwaterDischarge": abs(drn_disQ_ts[0:366]),
"RejectedInfiltration": abs(rejinf_ts[0:366]),
"gwswExchange": abs(sfr_gwsw_ts[0:366]),
"outflow": outflow[0:366],
}
vals2 = pd.DataFrame(data_sfr, index=rng)
fig = plt.figure(figsize=figure_size_ts, dpi=300, tight_layout=True)
ax = fig.add_subplot(1, 1, 1)
vals2.outflow.plot(
style="-", linewidth=0.5, color="royalblue", label="Streamflow at Outlet"
)
vals2.GroundwaterDischarge.plot(
style="k-", linewidth=0.7, label="Groundwater Discharge"
)
vals2.RejectedInfiltration.plot(
style="-", linewidth=0.7, color="brown", label="Rejected Infiltration"
)
vals2.gwswExchange.plot(
style="-", color="darkgreen", linewidth=0.7, label="GW Discharge to Streams"
)
ax.set_ylim(0, 350000)
plt.tick_params(
axis="x", # changes apply to the x-axis
which="both", # both major and minor ticks are affected
bottom=False, # ticks along the bottom edge are off
top=False, # ticks along the top edge are off
labelbottom=True,
) # labels along the bottom edge are off
ax.set_xlabel("Month")
ax.set_ylabel("Volumetric Rate, $m^3$ per day")
styles.graph_legend(ax)
title = "Surface Water Flow"
styles.heading(heading=title)
if plot_show:
plt.show()
if plot_save:
fpth = figs_path / f"{mf6.name}-swFlow.png"
fig.savefig(fpth)
Running the example
Define and invoke a function to run the example scenario, then plot results.
[5]:
def scenario(silent=True):
sim = build_models(sim_name)
if write:
write_models(sim, silent=silent)
if run:
run_models(sim, silent=silent)
if plot:
plot_results(sim)
scenario()
<flopy.mf6.data.mfstructure.MFDataItemStructure object at 0x7f1a9bb57760>
run_models took 134072.61 ms
