CalibrateNewChannel.py

"""

This script uses the HKplus functions to generate a channel centerline,
run it for a certain number of years,
then save the resulting centerline for later use.

@JA 2021
"""
import math
import matplotlib.pyplot as plt
import HKplus as hkp
import numpy as np
import pandas as pd

# Set Variables for centerline and curvature calculation

D = 3.4  # constant width-average channel depth (m)
W = 100  # constant channel width (m)
deltas = W // 2
# spacing of nodes along centerline
nit = 10000  # number of iterations/how many timesteps to migrate the centerline
Cf = 0.005  # dimensionless Chezy friction factor
kl = 35 / (365 * 24 * 60 * 60.0)  # migration rate constant (m/s)
dt = 0.25 * 365 * 24 * 60 * 60.0  # time step (s)
pad = 100  # number of nodes for periodic boundary
saved_ts = 5000  # timesteps between saving centerlines
crdist = 4 * W  # how close banks get before cutoff in m
Length = (50 * W) * 10

# Set Variables fror Cutoff nonlocal efects
tau = 8  # e-folding timescale for nonlocal effects in years
decay_rate = dt / (tau * (365 * 24 * 60 * 60.0))
# this is the half-life on nonlocal effects, in units of seconds
bump_scale = 3  # this is the magntiude of nonlocal effects in relative difference


# Set Result Directory
result_dir = (
    "data/InitialChannel/"  ##change this to wherever you want to save your results
)

# Choose name for centerline
name = "66"

# Initiate Channel Object
ch = hkp.generate_initial_channel(W, D, deltas, pad, Length)

# Initiate Channel Belt for migrating channel object

chb = hkp.ChannelBelt(
    channels=[ch],
    cutoffs=[],
    cl_times=[0.0],
    cutoff_times=[],
    cutoff_dists=[],
    decay_rate=decay_rate,
    bump_scale=bump_scale,
    cut_thresh=1000,
    sinuosity=[1],
)

# Plot initial centerline
# chb.plot_channels()
# plt.title(str(int(nit*dt/(365*24*60*60.0)))+ " years at "+ str(kl*(365*24*60*60.0))+ "m/yr")
# plt.show()

# Migrate Centerline for nit
chb.migrate_years(nit, saved_ts, deltas, pad, crdist, Cf, kl, dt)

# Plot Resulting Centerline
chb.plot_channels()
plt.title(
    str(int(nit * dt / (365 * 24 * 60 * 60.0)))
    + " years at "
    + str(kl * (365 * 24 * 60 * 60.0))
    + "m/yr"
)
plt.show()

# Save Sinuosity time series
times = chb.cl_times
sins = chb.sinuosity

# uncomment to save sinuosity series
# sinseries = pd.DataFrame({'time':times, 'sinuosity': sins});
# sinseries.to_csv(result_dir+"InitialCL_"+name+"sinseries"+".csv", header = True, index = False)

hkp.plot_sinuosity(times, sins)
plt.show()

# Save Resulting Centerline
xes = chb.channels[-1].x
yes = chb.channels[-1].y
cl = pd.DataFrame({"x": xes, "y": yes})
cl.to_csv(result_dir + "InitialCL_" + name + ".csv", header=False, index=False)