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("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)
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)
# Now, we need to set a fixed value on the left edge, so we find the
# link neighbor arrays...
of.set_up_neighbor_arrays()
# ... and get a list of all horizonal ids, not just active ids (which is what
# the deAlmeida solution uses)
all_horizontal_ids = links.horizontal_link_ids(rmg.shape)
# from there, we are going to reset our west neighbor array...
of.west_neighbors = (links.horizontal_west_link_neighbor(
rmg.shape, all_horizontal_ids))
# and find the ids of the arrays along the west edge of the grid. We actually
# will set the discharge values here at every time step in the loop.
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']['water__discharge'][left_inactive_ids] = (
rmg['link']['water__discharge'][left_inactive_ids + 1])
# Now, we can generate overland flow.
of.overland_flow()
of = OverlandFlow(rmg, mannings_n=n, theta=0.8, h_init=0.001)
# Now, we need to set a fixed value on the left edge, so we find the
# link neighbor arrays...
of.set_up_neighbor_arrays()
# ... and get a list of all horizonal ids, not just active ids (which is what
# the deAlmeida solution uses)
all_horizontal_ids = links.horizontal_link_ids(rmg.shape)
# from there, we are going to reset our west neighbor array...
of.west_neighbors = links.horizontal_west_link_neighbor(rmg.shape, all_horizontal_ids)
# and find the ids of the arrays along the west edge of the grid. We actually
# will set the discharge values here at every time step in the loop.
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()
