def test_deAlm_analytical():
from landlab import RasterModelGrid
grid = RasterModelGrid((32, 240), spacing = 25)
grid.add_zeros('node', 'surface_water__depth')
grid.add_zeros('node', 'topographic__elevation')
grid.set_closed_boundaries_at_grid_edges(True, True, True, True)
left_inactive_ids = left_edge_horizontal_ids(grid.shape)
deAlm = OverlandFlow(grid, mannings_n=0.01, h_init=0.001)
time = 0.0
while time < 500.:
grid['link']['surface_water__discharge'][left_inactive_ids] = (
grid['link']['surface_water__discharge'][left_inactive_ids + 1])
dt = deAlm.calc_time_step()
deAlm.overland_flow(dt)
h_boundary = (((7./3.) * (0.01**2) * (0.4**3) *
time) ** (3./7.))
grid.at_node['surface_water__depth'][grid.nodes[1: -1, 1]] = h_boundary
time += dt
x = np.arange(0, ((grid.shape[1]) * grid.dx), grid.dx)
h_analytical = (-(7./3.) * (0.01**2) * (0.4**2) * (x - (0.4 * 500)))
h_analytical[np.where(h_analytical > 0)] = (h_analytical[np.where(
h_analytical > 0)] ** (3./7.))
h_analytical[np.where(h_analytical < 0)] = 0.0
hdeAlm = deAlm.h.reshape(grid.shape)
hdeAlm = hdeAlm[1][1:]
hdeAlm = np.append(hdeAlm, [0])
np.testing.assert_almost_equal(h_analytical, hdeAlm, decimal=1)
def test_deAlm_analytical_imposed_dt_short():
grid = RasterModelGrid((32, 240), xy_spacing=25)
grid.add_zeros("surface_water__depth", at="node")
grid.add_zeros("topographic__elevation", at="node")
grid.set_closed_boundaries_at_grid_edges(True, True, True, True)
left_inactive_ids = _left_edge_horizontal_ids(grid.shape)
deAlm = OverlandFlow(grid, mannings_n=0.01, h_init=0.001)
time = 0.0
while time < 500.0:
grid.at_link["surface_water__discharge"][
left_inactive_ids] = grid.at_link["surface_water__discharge"][
left_inactive_ids + 1]
dt = 10.0
deAlm.overland_flow(dt)
h_boundary = ((7.0 / 3.0) * (0.01**2) * (0.4**3) * time)**(3.0 / 7.0)
grid.at_node["surface_water__depth"][grid.nodes[1:-1, 1]] = h_boundary
time += dt
x = np.arange(0, ((grid.shape[1]) * grid.dx), grid.dx)
h_analytical = -(7.0 / 3.0) * (0.01**2) * (0.4**2) * (x - (0.4 * 500))
h_analytical[np.where(h_analytical > 0)] = h_analytical[np.where(
h_analytical > 0)]**(3.0 / 7.0)
h_analytical[np.where(h_analytical < 0)] = 0.0
hdeAlm = deAlm.h.reshape(grid.shape)
hdeAlm = hdeAlm[1][1:]
hdeAlm = np.append(hdeAlm, [0])
np.testing.assert_almost_equal(h_analytical, hdeAlm, decimal=1)
def test_deAlm_analytical():
from landlab import RasterModelGrid
grid = RasterModelGrid((32, 240), spacing=25)
grid.add_zeros('node', 'water__depth')
grid.add_zeros('node', 'topographic__elevation')
grid.set_closed_boundaries_at_grid_edges(True, True, True, True)
left_inactive_ids = left_edge_horizontal_ids(grid.shape)
deAlm = OverlandFlow(grid, mannings_n=0.01, h_init=0.001)
time = 0.0
while time < 500:
grid['link']['water__discharge'][left_inactive_ids] = (
grid['link']['water__discharge'][left_inactive_ids + 1])
dt = deAlm.calc_time_step()
deAlm.overland_flow(dt)
h_boundary = (((7. / 3.) * (0.01**2) * (0.4**3) * time)**(3. / 7.))
grid.at_node['water__depth'][grid.nodes[1:-1, 1]] = h_boundary
time += dt
x = np.arange(0, ((grid.shape[1]) * grid.dx), grid.dx)
h_analytical = (-(7. / 3.) * (0.01**2) * (0.4**2) * (x - (0.4 * 500)))
h_analytical[np.where(h_analytical > 0)] = (h_analytical[np.where(
h_analytical > 0)]**(3. / 7.))
h_analytical[np.where(h_analytical < 0)] = 0.0
hdeAlm = deAlm.h.reshape(grid.shape)
hdeAlm = hdeAlm[1][1:]
hdeAlm = np.append(hdeAlm, [0])
np.testing.assert_almost_equal(h_analytical, hdeAlm, decimal=1)
def test_deAlm_analytical_imposed_dt_short():
grid = RasterModelGrid((32, 240), xy_spacing=25)
grid.add_zeros("node", "surface_water__depth")
grid.add_zeros("node", "topographic__elevation")
grid.set_closed_boundaries_at_grid_edges(True, True, True, True)
left_inactive_ids = left_edge_horizontal_ids(grid.shape)
deAlm = OverlandFlow(grid, mannings_n=0.01, h_init=0.001)
time = 0.0
while time < 500.0:
grid.at_link["surface_water__discharge"][left_inactive_ids] = grid.at_link[
"surface_water__discharge"
][left_inactive_ids + 1]
dt = 10.0
deAlm.overland_flow(dt)
h_boundary = ((7.0 / 3.0) * (0.01 ** 2) * (0.4 ** 3) * time) ** (3.0 / 7.0)
grid.at_node["surface_water__depth"][grid.nodes[1:-1, 1]] = h_boundary
time += dt
x = np.arange(0, ((grid.shape[1]) * grid.dx), grid.dx)
h_analytical = -(7.0 / 3.0) * (0.01 ** 2) * (0.4 ** 2) * (x - (0.4 * 500))
h_analytical[np.where(h_analytical > 0)] = h_analytical[
np.where(h_analytical > 0)
] ** (3.0 / 7.0)
h_analytical[np.where(h_analytical < 0)] = 0.0
hdeAlm = deAlm.h.reshape(grid.shape)
hdeAlm = hdeAlm[1][1:]
hdeAlm = np.append(hdeAlm, [0])
np.testing.assert_almost_equal(h_analytical, hdeAlm, decimal=1)
# Running the overland flow component.
while elapsed_time < model_run_time:
# The storm starts when the model starts. While the elapsed time is less
# than the storm duration, we add water to the system as rainfall.
if elapsed_time < storm_duration:
of.rainfall_intensity = 4.07222 * (10**-7) # Rainfall intensity (m/s)
# Then the elapsed time exceeds the storm duration, rainfall ceases.
else:
of.rainfall_intensity = 0.0
# Generating overland flow based on the deAlmeida solution.
of.overland_flow()
# Append time and discharge to their lists to save data and for plotting.
hydrograph_time_sec.append(elapsed_time)
hydrograph_time_hrs.append(round(elapsed_time / 3600., 2))
discharge_at_outlet.append(of.q[link_to_sample])
# Add the time step, repeat until elapsed time >= model_run_time
print(elapsed_time)
elapsed_time += of.dt
plt.figure(1)
plt.imshow(z.reshape(rmg.shape), origin="left", cmap="pink")
plt.tick_params(axis="both", labelbottom="off", labelleft="off")
cb = plt.colorbar()
cb.set_label("Elevation (m)", rotation=270, labelpad=15)
left_inactive_ids = links.left_edge_horizontal_ids(rmg.shape)
# Let's see how long this run takes...
starttime = time()
while elapsed_time < run_time:
# Now we are going to set the left edge horizontal links to their
# neighboring discharge value
rmg["link"]["surface_water__discharge"][left_inactive_ids] = rmg["link"][
"surface_water__discharge"
][left_inactive_ids + 1]
# Now, we can generate overland flow.
of.overland_flow()
# Recalculate water depth at the boundary ...
# water depth at left side (m)
h_boundary = (
seven_over_three * n * n * u * u * u * elapsed_time
) ** three_over_seven
# And now we input that water depth along the left-most interior column,
# in all rows that are not boundary rows.
rmg.at_node["surface_water__depth"][inside_left_edge] = h_boundary
# Increased elapsed time
elapsed_time += of.dt
class FloodWorld(ActiveCellWorld):
"""
FloodWorld class. This ActiveCellWorld implementation uses Landlab to simulate floods.
:param world_size:
:param grid_size:
:param torus:
:param agent_dynamic:
"""
def __init__(self, world_size, grid_size, torus, agent_dynamic):
super(FloodWorld, self).__init__(world_size, grid_size, torus, agent_dynamic)
# World generation parameters
self.vertical_scale = 200 # (m)
self.inputs = {'nrows': 100, 'ncols': 100, 'dx': 0.02, 'dt': 0.5, 'total_time': 50.0, 'uplift_rate': 0.001,
'K_sp': 0.3, 'm_sp': 0.5, 'n_sp': 1.0, 'rock_density': 2.7, 'sed_density': 2.7,
'linear_diffusivity': 0.0001}
# Flood parameters
self.h_init = 5 # initial thin layer of water (m)
self.n = 0.01 # roughness coefficient, (s/m^(1/3))
self.alpha = 0.7 # time-step factor (nondimensional; from Bates et al., 2010)
self.u = 0.4 # constant velocity (m/s, de Almeida et al., 2012)
self.cell_update_period = 10 # (s)
self.mg = None
self.fr = None
self.sp = None
self.of = None
self.swd = None
self.z = None
self.flood_threshold = 0.05 # minimum water depth detected as flood (m)
def reset(self):
"""
Reset function. Resets the world to its initial state.
"""
super(FloodWorld, self).reset()
# Terrain generation
shape = (self.grid_size,) * 2
size = self.grid_size * self.grid_size
# Set initial simple topography
z = self.vertical_scale * self.simple_topography(shape)
# Create raster model if it does not exist
if self.mg is None:
self.mg = RasterModelGrid(shape, int(round(self.world_size/self.grid_size)))
self.mg.set_closed_boundaries_at_grid_edges(True, True, True, True)
self.z = self.mg.add_field('node', 'topographic__elevation', z)
self.swd = self.mg.add_zeros('node', 'surface_water__depth')
else:
self.mg.at_node['topographic__elevation'] = z
self.swd[:] = np.zeros(size)
import matplotlib.pyplot as plt
plt.figure()
from landlab.plot import imshow_grid
imshow_grid(self.mg, 'topographic__elevation',
colorbar_label='m')
plt.draw()
# Set evolution parameters
uplift_rate = self.inputs['uplift_rate']
total_t = self.inputs['total_time']
dt = self.inputs['dt']
nt = int(total_t // dt) # Loops
uplift_per_step = uplift_rate * dt
self.fr = FlowAccumulator(self.mg, **self.inputs)
self.sp = FastscapeEroder(self.mg, **self.inputs)
# Erode terrain
for i in range(nt):
self.fr.run_one_step() # Not time sensitive
self.sp.run_one_step(dt)
self.mg.at_node['topographic__elevation'][self.mg.core_nodes] += uplift_per_step # add the uplift
if i % 10 == 0:
print('Erode: Completed loop %d' % i)
plt.figure()
imshow_grid(self.mg, 'topographic__elevation',
colorbar_label='m')
plt.draw()
plt.show()
# Setup surface water flow
self.of = OverlandFlow(self.mg, steep_slopes=True, mannings_n=0.01)
# Setup initial flood
self.swd[[5050, 5051, 5150, 5151]] += self.h_init
self.active = np.greater(np.flip(np.reshape(self.swd, shape), axis=0), self.flood_threshold)
def update_cells(self):
"""
Update cells function. Updates water level and cell status.
"""
self.of.overland_flow(dt=self.cell_update_period)
shape = (self.grid_size,) * 2
self.active = np.greater(np.flip(np.reshape(self.swd, shape), axis=0), self.flood_threshold)
@staticmethod
def noise_octave(shape, f):
"""
Noise octave function. Generates a noise map.
:param shape: (array) shape of the map.
:param f: (float) frequency bounds parameter.
"""
return te3w_util.fbm(shape, -1, lower=f, upper=(2 * f))
def simple_topography(self, shape):
"""
Simple topography function. Generates an elevation map.
:param shape: (array) shape of the map.
"""
values = np.zeros(shape)
for p in range(1, 10):
a = 2 ** p
values += np.abs(self.noise_octave(shape, a) - 0.5) / a
result = (1.0 - te3w_util.normalize(values)) ** 2
return result
