def find_avulsion(riv_i, riv_j, n, super_ratio, current_SL, ch_depth,
short_path, splay_type, splay_dep, dx=1., dy=1.):
new = riv_i, riv_j
old = riv_i, riv_j
avulsion_type = 0
for a in xrange(1, len(riv_i)):
if channel_is_superelevated(n, (riv_i[a], riv_j[a]), ch_depth,
super_ratio):
# if superelevation greater than trigger ratio, determine
# length of new steepest descent path
new = steep_desc.find_course(n, riv_i[:a], riv_j[:a],
sea_level=current_SL)
# if using the shortest path as an avulsion criterion, then
# the lengths of the previous and newly calculated paths will
# be compared
if short_path == 1:
new_length = find_path_length(new, dx=dx, dy=dy)
old_length = find_path_length(old, dx=dx, dy=dy)
if new_length < old_length:
# if new river course < length of old
# river course, then an avulsion will occur
avulsion_type = 1
new, avulsion_type = avulse_to_new_path(n,
(riv_i[a - 1:], riv_j[a - 1:]),
(new[0][a - 1:], new[1][a - 1:]),
current_SL, ch_depth, avulsion_type,
dx=dx, dy=dy)
new = (np.append(riv_i[:a - 1], new[0]),
np.append(riv_j[:a - 1], new[1]))
break
elif splay_type > 0:
avulsion_type = 3
FP.dep_splay(n, (new[0][a], new[1][a]), (riv_i, riv_j),
splay_dep, splay_type=splay_type)
# if shortest path is not an avulsion criterion, then the new
# steepest descent path will become the new course regardless
# of new course length relative to the old course
return new, avulsion_type, a
def _init_from_dict(self, params):
# seed random number generator
np.random.seed(params['rand_seed'])
# Spatial parameters
self._dy = params['spacing'][0] * 1000.
self._dx = params['spacing'][1] * 1000.
n_rows = int(params['shape'][0])
n_cols = int(params['shape'][1])
# Initialize elevation grid
# transverse and longitudinal space
self._x, self._y = np.meshgrid(np.arange(n_cols) * self._dx,
np.arange(n_rows) * self._dy)
# eta, elevation
n0 = params['n0']
self._slope = params['nslope']
self._max_rand = params['max_rand'] * params['nslope']
self._n = n0 - (self._slope * self._y +
np.random.rand(n_rows, n_cols) * self._max_rand)
self._n -= 0.05
# self._dn_rc = np.zeros((self._imax)) # change in elevation along river course
# self._dn_fp = np.zeros_like(self._n) # change in elevation due to floodplain dep
self._riv_i = np.zeros(1, dtype=np.int) # defines first x river locations
self._riv_j = np.zeros(1, dtype=np.int) # defines first y river locations
self._riv_j[0] = self._n.shape[1] / 2
# Time parameters
self._dt = params['dt_day'] * _SECONDS_PER_DAY # convert timestep to seconds
self._time = 0.
# Sea level and subsidence parameters
self._SL = params['Initial_SL'] # starting sea level
self._SLRR = params['SLRR_m'] / _SECONDS_PER_YEAR * self._dt # sea level rise rate in m (per timestep)
self._SubRate = params['SubRate_m'] / _SECONDS_PER_YEAR * self._dt # subsidence rate in m (per timestep)
self._SubStart = params['Sub_Start'] # row where subsidence begins
# River parameters
self._nu = ((8. * (params['ch_discharge'] / params['ch_width']) * params['A']
* np.sqrt(params['c_f'])) / (params['C_0'] * (params['sed_sg'] - 1)))
### NEED TO REDO DIFFUSE.PY TO HAVE SIGN OF NU CORRECT (NEG) ABOVE ###
init_cut = params['init_cut_frac'] * params['ch_depth']
self._super_ratio = params['super_ratio']
self._short_path = params['short_path']
self._ch_depth = params['ch_depth']
# Floodplain and wetland characteristics
self._WL_Z = params['WL_Z']
self._WL_dist = params['WL_dist']
self._blanket_rate = (params['blanket_rate_m'] / _SECONDS_PER_YEAR) * self._dt # blanket deposition in m
self._splay_type = params['splay_type']
self._frac_fines = params['fine_dep_frac']
self._sed_flux = 0.
self._splay_deposit = np.zeros_like(self._n)
# Saving information
self._saveavulsions = params['saveavulsions']
self._saveupdates = params['savecourseupdates']
self._riv_i, self._riv_j = steep_desc.find_course(self._n, self._riv_i, self._riv_j,
len(self._riv_i), self._ch_depth,
sea_level=self._SL)
# downcut into new river course by amount determined by init_cut
downcut.cut_init(self._riv_i, self._riv_j, self._n, init_cut)
# smooth initial river course elevations using linear diffusion equation
diffuse.smooth_rc(self._dx, self._dy, self._nu, self._dt, self._ch_depth,
self._riv_i, self._riv_j, self._n, self._SL, self._slope)
# initial profile
self._profile = self._n[self._riv_i, self._riv_j]
# Initial elevation grid
# this part sets up the grid for stand-alone module, won't be needed after
# module is coupled to sedfux (grid would be imported instead)
for i in range(imax):
for j in range(jmax):
x[i][j] = i * dx
y[i][j] = j * dy
if Linear == 1:
n[i][j] = n0 - (nslope * float(x[i][j]) + max_rand*random())
elif Concave == 1:
n[i][j] = n0 - (drop * np.sqrt(x[i][j]) + max_rand*random())
j += 1
i += 1
# Determine initial river course
riv_x, riv_y = steep_desc.find_course(dx, dy, imax, jmax, n, riv_x, riv_y)
# downcut into new river course by amount determined by init_cut
n = downcut.cut_init(dx, dy, riv_x, riv_y, n, init_cut, Initial_SL)
# smooth initial river course elevations using linear diffusion equation
n, dn_rc = diffuse.smooth_rc(dx, dy, nu, dt, riv_x, riv_y, n, nslope)
# Determine initial river profile
profile = prof.make_profile(dx, dy, n, riv_x, riv_y, profile)
# make directories and save initial condition files
if savefiles == 1:
# os.mkdir("run" + str(run_num) + "_out")
os.mkdir("elev_grid")
os.mkdir("riv_course")
def find_avulsion(riv_i, riv_j, n, super_ratio, current_SL, ch_depth,
short_path, splay_type, slope, splay_depth,
nu, dt, dx=1., dy=1.):
new = riv_i, riv_j
old = riv_i, riv_j
avulsion_type = 0
a = 0
loc = 0
avulse_length = 0
new_length = 0
new_course_length = 0
avul_locs = np.zeros(0, dtype=np.int)
path_slopes = np.zeros(0)
crevasse_locs = np.zeros(3, dtype=np.int)
path_diff = np.zeros(0)
path_difference = 0
old_length = find_riv_path_length(n, old, current_SL, ch_depth,
slope, dx=dx, dy=dy)
for a in xrange(1, len(riv_i)-1):
if channel_is_superelevated(n, (riv_i[a], riv_j[a]),
(riv_i[a-1], riv_j[a-1]),
ch_depth, super_ratio, current_SL):
# if superelevation greater than trigger ratio, determine
# new steepest descent path
new = steep_desc.find_course(n, riv_i, riv_j, a, ch_depth,
sea_level=current_SL)
if n[new[0][-1], new[1][-1]] < current_SL:
new_length = find_riv_path_length(n, new, current_SL, ch_depth,
slope, dx=dx, dy=dy)
else:
new_length = find_path_length(n, new, current_SL, ch_depth,
slope, dx=dx, dy=dy)
if new_length < old_length:
# calculate slope of new path
if len(new[0][a:]) <= 1:
avulsed_length = find_path_length(n, (new[0][a-1:], new[1][a-1:]),
current_SL, ch_depth, slope,
dx=dx, dy=dy)
slope_new_path = ((n[new[0][-2], new[1][-2]] - n[new[0][-1], new[1][-1]])
/ avulsed_length)
elif n[new[0][-1], new[1][-1]] < current_SL:
avulsed_length = find_riv_path_length(n, (new[0][a:], new[1][a:]),
current_SL, ch_depth,
slope, dx=dx, dy=dy)
slope_new_path = ((n[new[0][a], new[1][a]] - n[new[0][-1], new[1][-1]])
/ avulsed_length)
else:
avulsed_length = find_path_length(n, (new[0][a:], new[1][a:]),
current_SL, ch_depth, slope,
dx=dx, dy=dy)
slope_new_path = ((n[new[0][a], new[1][a]] - n[new[0][-1], new[1][-1]])
/ avulsed_length)
avul_locs = np.append(avul_locs, a)
path_slopes = np.append(path_slopes, slope_new_path)
path_diff = np.append(path_diff, (old_length - new_length))
crevasse_locs = np.vstack((crevasse_locs, [new[0][a], new[1][a], a]))
if (crevasse_locs.sum() > 0):
crevasse_locs = np.delete(crevasse_locs, 0, 0)
if avul_locs.size > 0:
max_slope = np.argmax(path_slopes)
loc = avul_locs[max_slope]
path_difference = path_diff[max_slope]
new = steep_desc.find_course(n, riv_i, riv_j, loc, ch_depth,
sea_level=current_SL)
avulsion_type = 1
new, avulsion_type = avulse_to_new_path(n,
(riv_i[loc - 1:], riv_j[loc - 1:]),
(new[0][loc - 1:], new[1][loc - 1:]),
current_SL, ch_depth, avulsion_type,
slope, dx=dx, dy=dy)
new = (np.append(riv_i[:loc - 1], new[0]),
np.append(riv_j[:loc - 1], new[1]))
avulse_length = find_riv_path_length(n, (riv_i[loc:], riv_j[loc:]),
current_SL, ch_depth,
slope, dx=dx, dy=dy)
# fill up old channel... could be some fraction in the future
# (determines whether channels are repellors or attractors)
fill_abandoned_channel(loc, n, new, riv_i, riv_j, current_SL,
ch_depth, slope, dx)
crevasse_locs = np.delete(crevasse_locs, max_slope, 0)
else:
new = riv_i, riv_j
if (crevasse_locs.sum() > 0) and (splay_type > 0):
n_before_splay = np.copy(n)
# Don' think we need to worry about preserving old river elevations??
# old_river_elevations = n[riv_i, riv_j]
new_river_elevations = n[new[0], new[1]]
for i in xrange(crevasse_locs.shape[0]):
splay_dep = calc_crevasse_dep(dx, dy, nu, dt, ch_depth, riv_i, riv_j, n,
current_SL, slope, crevasse_locs[i][2])
if splay_dep > 0:
FP.dep_splay(n, (crevasse_locs[i][0], crevasse_locs[i][1]),
splay_dep, splay_type=splay_type)
# n[riv_i, riv_j] = old_river_elevations
n[new[0], new[1]] = new_river_elevations
n_splay = n - n_before_splay
splay_depth += n_splay
return (new, avulsion_type, loc, avulse_length, path_difference, splay_depth)
