def run_day(mg, precipitation: float, duration=1800):
"""
Calculates the mm of water that has infiltrated into soil after a rainfall event.
Rainfall events are assumed to be instantaneous and constant over the model grid.
:param dem: model grid
:param precipitation: rainfall in mm/hr
:param duration: seconds of rainfall
:return: mm of water infiltrated into the soil at every coordinate in the grid
"""
elapsed_time = 0.0
swd = mg.add_zeros('surface_water__depth', at='node', clobber=True)
swd += precipitation
swid = mg.add_zeros('soil_water_infiltration__depth',
at='node',
clobber=True)
swid += 1e-6
siga = SoilInfiltrationGreenAmpt(mg)
of = OverlandFlow(mg, steep_slopes=True)
while elapsed_time < duration:
dt = of.calc_time_step()
dt = dt if dt + elapsed_time < duration else duration - elapsed_time
of.run_one_step(dt=dt)
siga.run_one_step(dt=dt)
elapsed_time += dt
return xr.DataArray(mg.at_node['soil_water_infiltration__depth'].reshape(
mg.shape),
dims=('x', 'y'))
def test_deAlm_analytical():
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 = deAlm.calc_time_step()
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', '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():
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)
isChannel = np.logical_and(rmg.x_of_node < channel_left,
rmg.x_of_node > channel_right)
highInfBand = np.logical_and(rmg.x_of_node < channel_left + infBandWidth,
rmg.x_of_node > channel_right - infBandWidth)
inf_mask = np.logical_xor(highInfBand, isChannel)
hc[inf_mask] *= 10
of = OverlandFlow(rmg, steep_slopes=True)
SI = SoilInfiltrationGreenAmpt(rmg, hydraulic_conductivity=hc)
elapsed_time = 0
run_time = 1e4
iters = 0
while elapsed_time < run_time:
# First, we calculate our time step.
dt = of.calc_time_step()
# Now, we can generate overland flow.
of.overland_flow()
SI.run_one_step(dt)
# Increased elapsed time
if iters % 1000 == 0:
print('Elapsed time: ', elapsed_time)
elapsed_time += dt
iters += 1
imshow_grid(rmg, 'surface_water__depth', cmap='Blues')
