def test_D8_D4_fill(d4_grid):
"""
Tests the functionality of D4 filling.
"""
lfD8 = DepressionFinderAndRouter(
d4_grid.mg1, pits=None, routing="D8", reroute_flow=False
)
lfD4 = DepressionFinderAndRouter(
d4_grid.mg2, pits=None, routing="D4", reroute_flow=False
)
lfD8.map_depressions()
lfD4.map_depressions()
assert lfD8.number_of_lakes == 1
assert lfD4.number_of_lakes == 3
correct_D8_lake_map = np.empty(7 * 7, dtype=int)
correct_D8_lake_map.fill(XX)
correct_D8_lake_map[d4_grid.lake_nodes] = 10
correct_D4_lake_map = correct_D8_lake_map.copy()
correct_D4_lake_map[d4_grid.lake_nodes[5:]] = 32
correct_D4_lake_map[d4_grid.lake_nodes[-2]] = 38
correct_D8_depths = np.zeros(7 * 7, dtype=float)
correct_D8_depths[d4_grid.lake_nodes] = 2.0
correct_D4_depths = correct_D8_depths.copy()
correct_D4_depths[d4_grid.lake_nodes[5:]] = 4.0
correct_D4_depths[d4_grid.lake_nodes[-2]] = 3.0
assert_array_equal(lfD8.lake_map, correct_D8_lake_map)
assert_array_equal(lfD4.lake_map, correct_D4_lake_map)
assert d4_grid.mg1.at_node["depression__depth"] == approx(correct_D8_depths)
assert d4_grid.mg2.at_node["depression__depth"] == approx(correct_D4_depths)
def __init__(self, input_file=None, params=None):
"""Initialize the StochasticDischargeHortonianModel."""
# Call ErosionModel's init
super(StochasticDischargeHortonianModel,
self).__init__(input_file=input_file, params=params)
# Instantiate components
self.flow_router = FlowRouter(self.grid, **self.params)
self.lake_filler = DepressionFinderAndRouter(self.grid, **self.params)
self.rain_generator = \
PrecipitationDistribution(delta_t=self.params['dt'],
total_time=self.params['run_duration'],
**self.params)
# Add a field for discharge
if 'surface_water__discharge' not in self.grid.at_node:
self.grid.add_zeros('node', 'surface_water__discharge')
self.discharge = self.grid.at_node['surface_water__discharge']
# Get the infiltration-capacity parameter
self.infilt = self.params['infiltration_capacity']
# Run flow routing and lake filler (only once, because we are not
# not changing topography)
self.flow_router.run_one_step()
self.lake_filler.map_depressions()
def test_find_lowest_node_on_lake_perimeter_c():
"""
Ensures the key functionality of the cfunc is working.
"""
mg = RasterModelGrid((7, 7), xy_spacing=0.5)
z = mg.add_field("node", "topographic__elevation", mg.node_x.copy())
z += 0.01 * mg.node_y
mg.at_node["topographic__elevation"].reshape(mg.shape)[2:5, 2:5] *= 0.1
fr = FlowAccumulator(mg, flow_director="D8")
fr.run_one_step() # the flow "gets stuck" in the hole
df = DepressionFinderAndRouter(mg)
node_nbrs = df._node_nbrs
flood_status = df.flood_status
elev = df._elev
BIG_ELEV = df._BIG_ELEV
nodes_this_depression = mg.zeros("node", dtype=int)
nodes_this_depression[0] = 16
pit_count = 1
assert find_lowest_node_on_lake_perimeter_c(node_nbrs, flood_status, elev,
nodes_this_depression,
pit_count, BIG_ELEV) == (23, 1)
nodes_this_depression[1] = 8
pit_count = 2
assert find_lowest_node_on_lake_perimeter_c(node_nbrs, flood_status, elev,
nodes_this_depression,
pit_count, BIG_ELEV) == (0, 2)
def __init__(self, grid, routing_method):
self._grid = grid
if routing_method == "D8":
self.fd = FlowDirectorD8(self._grid)
elif routing_method == "Steepest":
self.fd = FlowDirectorSteepest(self._grid)
else:
raise ValueError("routing_method must be either D8 or Steepest.")
self.fa = FlowAccumulator(
self._grid,
surface="topographic__elevation",
flow_director=self.fd,
runoff_rate="average_surface_water__specific_discharge",
)
self.lmb = LakeMapperBarnes(
self._grid,
method=routing_method,
fill_flat=False,
surface="topographic__elevation",
fill_surface="topographic__elevation",
redirect_flow_steepest_descent=False,
reaccumulate_flow=False,
track_lakes=False,
ignore_overfill=True,
)
self.dfr = DepressionFinderAndRouter(self._grid)
def __init__(self, modern_dem_name, outlet_id, chi_mask_dem_name=None, from_file=None):
"""Initialize MetricCalculator with names of postglacial and modern
DEMs."""
if from_file is None:
# Read and remember the modern DEM (whether data or model)
(self.grid, self.z) = self.read_topography(modern_dem_name)
#print self.grid.x_of_node
self.grid.set_watershed_boundary_condition_outlet_id(outlet_id,
self.z, nodata_value=-9999)
# Instantiate and run a FlowRouter and lake filler, so we get
# drainage area for cumulative-area statistic, and also fields for chi.
fr = FlowRouter(self.grid)
dfr = DepressionFinderAndRouter(self.grid)
fr.route_flow()
dfr.map_depressions()
# Remember modern drainage area grid
self.area = self.grid.at_node['drainage_area']
# Instantiate a ChiFinder for chi-index
self.chi_finder = ChiFinder(self.grid, min_drainage_area=10000.,
reference_concavity=0.5)
core_nodes = np.zeros(self.area.shape, dtype=bool)
core_nodes[self.grid.core_nodes] = True
# Read and remember the MASK, if provided
if chi_mask_dem_name is None:
self.mask = (self.area>1e5)
self.till_mask = np.zeros(self.mask.shape, dtype=bool)
self.till_mask[self.grid.core_nodes] = 1
else:
(self.mask_grid, zmask) = self.read_topography(chi_mask_dem_name)
mask = (zmask>0)*1
self.mask = (self.area>1e5)*(mask==1)
mask_bool = (zmask>0)
self.till_mask = np.zeros(self.mask.shape, dtype=bool)
self.till_mask[mask_bool*core_nodes] = 1
#
# Create dictionary to contain metrics
self.metric = {}
else:
with open(from_file, 'r') as f:
metrics = load(f)
self.modern_dem_name = metrics.pop('Topo file')
self.metric = metrics
fn_split = from_file.split('.')
fn_split[-1] = 'chi'
fn_split.append('txt')
chi_filename = '.'.join(fn_split)
self.density_chi = np.loadtxt(chi_filename)
def d4_grid():
"""Test functionality of routing when D4 is specified.
The elevation field in this test looks like::
1 2 3 4 5 6 7
1 2 3 0 5 0 7
1 2 3 4 0 0 7
1 2 3 0 5 6 7
1 2 0 0 0 6 7
1 2 3 0 5 6 7
1 2 3 4 5 6 7
"""
mg1 = RasterModelGrid(7, 7, 1.)
mg2 = RasterModelGrid(7, 7, 1.)
z = mg1.node_x.copy() + 1.
lake_nodes = np.array([10, 16, 17, 18, 24, 32, 33, 38, 40])
z[lake_nodes] = 0.
mg1.add_field("node", "topographic__elevation", z, units="-")
mg2.add_field("node", "topographic__elevation", z, units="-")
frD8 = FlowAccumulator(mg1, flow_director='D8')
frD4 = FlowAccumulator(mg2, flow_director='D4')
lfD8 = DepressionFinderAndRouter(mg1, routing="D8")
lfD4 = DepressionFinderAndRouter(mg2, routing="D4")
class DansGrid(object):
pass
d4_grid = DansGrid()
d4_grid.mg1 = mg1
d4_grid.mg2 = mg2
d4_grid.z = z
d4_grid.lake_nodes = lake_nodes
d4_grid.frD8 = frD8
d4_grid.frD4 = frD4
d4_grid.lfD8 = lfD8
d4_grid.lfD4 = lfD4
return d4_grid
def test_route_to_multiple_error_raised():
mg = RasterModelGrid((10, 10))
z = mg.add_zeros("topographic__elevation", at="node")
z += mg.x_of_node + mg.y_of_node
fa = FlowAccumulator(mg, flow_director="MFD")
fa.run_one_step()
with pytest.raises(NotImplementedError):
DepressionFinderAndRouter(mg)
def initialize(self, input_stream=None):
"""
The BMI-style initialize method takes an optional input_stream
parameter, which may be either a ModelParameterDictionary object or
an input stream from which a ModelParameterDictionary can read values.
"""
# Create a ModelParameterDictionary for the inputs
if input_stream is None:
inputs = None
elif type(input_stream) == ModelParameterDictionary:
inputs = input_stream
else:
inputs = ModelParameterDictionary(input_stream)
# Make sure the grid includes elevation data. This means either:
# 1. The grid has a node field called 'topographic__elevation', or
# 2. The input file has an item called 'ELEVATION_FIELD_NAME' *and*
# a field by this name exists in the grid.
try:
self._elev = self._grid.at_node["topographic__elevation"]
except FieldError:
try:
self.topo_field_name = inputs.read_string("ELEVATION_" +
"FIELD_NAME")
except AttributeError:
print("Error: Because your grid does not have a node field")
print('called "topographic__elevation", you need to pass the')
print("name of a text input file or ModelParameterDictionary,")
print("and this file or dictionary needs to include the name")
print("of another field in your grid that contains your")
print("elevation data.")
raise AttributeError
except MissingKeyError:
print("Error: Because your grid does not have a node field")
print('called "topographic__elevation", your input file (or')
print("ModelParameterDictionary) must include an entry with")
print('the key "ELEVATION_FIELD_NAME", which gives the name')
print("of a field in your grid that contains your elevation")
print("data.")
raise MissingKeyError("ELEVATION_FIELD_NAME")
try:
self._elev = self._grid.at_node[self.topo_field_name]
except AttributeError:
print(
"Your grid does not seem to have a node field called",
self.topo_field_name,
)
else:
self.topo_field_name = "topographic__elevation"
# create the only new output field:
self.sed_fill_depth = self._grid.add_zeros("node",
"sediment_fill__depth",
noclobber=False)
self._lf = DepressionFinderAndRouter(self._grid, routing=self._routing)
self._fr = FlowAccumulator(self._grid, flow_director=self._routing)
def __init__(self, input_file=None, params=None):
"""Initialize the LinearDiffusionModel."""
# Call ErosionModel's init
super(DrainageAreaModel, self).__init__(input_file=input_file,
params=params)
# Instantiate a FlowRouter and DepressionFinderAndRouter components
self.flow_router = FlowRouter(self.grid, **self.params)
self.lake_filler = DepressionFinderAndRouter(self.grid, **self.params)
def test_pits_as_IDs(dans_grid3):
"""
Smoke test for passing specific IDs, not an array, to the mapper.
"""
dans_grid3.fr.run_one_step()
pits = np.nonzero(dans_grid3.mg.at_node["flow__sink_flag"])[0]
lf = DepressionFinderAndRouter(dans_grid3.mg, pits=pits)
lf.map_depressions()
assert dans_grid3.mg.at_node["drainage_area"] == approx(dans_grid3.A_new)
def test_filling_supplied_pits(dans_grid3):
"""
Test the filler without rereouting, but confusingly, where there *is*
aready routing information available!
Also tests the supply of an array for 'pits'
"""
dans_grid3.fr.run_one_step()
lf = DepressionFinderAndRouter(
dans_grid3.mg, reroute_flow=False, pits="flow__sink_flag"
)
lf.map_depressions()
assert_array_equal(dans_grid3.mg.at_node["flow__receiver_node"], dans_grid3.r_old)
def test_filling_alone(dans_grid3):
"""
Test the filler alone, w/o supplying information on the pits.
Setting the the *pits* parameter to None causes the mapper to look for pits
using its _find_pits method.
"""
lf = DepressionFinderAndRouter(dans_grid3.mg, reroute_flow=False, pits=None)
assert lf._user_supplied_pits is None
lf.map_depressions()
assert_array_equal(
dans_grid3.mg.at_node["flow__receiver_node"], XX * np.ones(49, dtype=int)
)
assert_array_equal(lf.depression_outlet_map, dans_grid3.depr_outlet_target)
def __init__(self, input_file=None, params=None):
"""Initialize the StreamPowerThresholdModel."""
# Call ErosionModel's init
super(StreamPowerThresholdModel, self).__init__(input_file=input_file,
params=params)
# Instantiate a FlowRouter and DepressionFinderAndRouter components
self.flow_router = FlowRouter(self.grid, **self.params)
self.lake_filler = DepressionFinderAndRouter(self.grid, **self.params)
# Instantiate a FastscapeEroder component
self.eroder = StreamPowerSmoothThresholdEroder(
self.grid,
K_sp=self.params['K_sp'],
threshold_sp=self.params['threshold_sp'])
def __init__(self, input_file=None, params=None):
"""Initialize the LinearDiffusionModel."""
# Call ErosionModel's init
super(EffectiveDrainageAreaModel, self).__init__(input_file=input_file,
params=params)
# Instantiate a FlowRouter and DepressionFinderAndRouter components
self.flow_router = FlowRouter(self.grid, **self.params)
self.lake_filler = DepressionFinderAndRouter(self.grid, **self.params)
# Add a field for effective drainage area
self.eff_area = self.grid.add_zeros('node', 'effective_drainage_area')
# Get the effective-area parameter
self.sat_param = self.params['saturation_area_scale']
def test_lake_mapper():
"""
Create a test grid and run a series of tests.
"""
# Make a test grid
rmg = create_test_grid()
# Instantiate a lake mapper
# (Note that we don't need to send it an input file name, because our grid
# already has a topographic__elevation field)
lm = DepressionFinderAndRouter(rmg)
# Run it on our test grid
lm.map_depressions()
# Run tests
check_fields1(rmg)
check_array_values1(rmg, lm)
check_fields2(rmg)
check_array_values2(rmg, lm)
def __init__(self, input_file=None, params=None):
"""Initialize the HybridAlluviumModel."""
# Call ErosionModel's init
super(HybridAlluviumModel, self).__init__(input_file=input_file,
params=params)
# Instantiate a FlowRouter and DepressionFinderAndRouter components
self.flow_router = FlowRouter(self.grid, **self.params)
self.lake_filler = DepressionFinderAndRouter(self.grid, **self.params)
#make area_field and/or discharge_field depending on discharge_method
if self.params['discharge_method'] is not None:
if self.params['discharge_method'] == 'area_field':
area_field = self.grid.at_node['drainage_area']
discharge_field = None
elif self.params['discharge_method'] == 'discharge_field':
discharge_field = self.grid.at_node['surface_water__discharge']
area_field = None
else:
raise (KeyError)
else:
area_field = None
discharge_field = None
# Instantiate a HybridAlluvium component
self.eroder = Space(self.grid,
K_sed=self.params['K_sed'],
K_br=self.params['K_br'],
F_f=self.params['F_f'],
phi=self.params['phi'],
H_star=self.params['H_star'],
v_s=self.params['v_s'],
m_sp=self.params['m_sp'],
n_sp=self.params['n_sp'],
sp_crit_sed=self.params['sp_crit_sed'],
sp_crit_br=self.params['sp_crit_br'],
method=self.params['method'],
discharge_method=self.params['discharge_method'],
area_field=area_field,
discharge_field=discharge_field)
def __init__(self, input_file=None, params=None):
"""Initialize the StreamPowerVarThresholdModel."""
# Call ErosionModel's init
super(StreamPowerVarThresholdModel, self).__init__(input_file=input_file,
params=params)
# Instantiate a FlowRouter and DepressionFinderAndRouter components
self.flow_router = FlowRouter(self.grid, **self.params)
self.lake_filler = DepressionFinderAndRouter(self.grid, **self.params)
# Create a field for the (initial) erosion threshold
self.threshold = self.grid.add_zeros('node', 'erosion__threshold')
self.threshold[:] = self.params['threshold_sp']
# Instantiate a FastscapeEroder component
self.eroder = StreamPowerSmoothThresholdEroder(
self.grid,
K_sp=self.params['K_sp'],
threshold_sp=self.threshold)
# Get the parameter for rate of threshold increase with erosion depth
self.thresh_change_per_depth = self.params['thresh_change_per_depth']
v_profile = profile * vmax
accum_disp = profile * float(dxy)
# This is an array for counting how many pixels need to be moved
nshift = np.zeros(np.size(yLocation))
n_buff = 0 # optional extra buffer zone incase you only want to move a subset.
################################################################################
## Last, we instantiate landlab components that will evolve the landscape #####
################################################################################
fr = FlowRouter(rmg) # standard D8 flow routing algorithm
sp = FastscapeEroder(rmg, K_sp='K_sp', m_sp=m, n_sp=n,
threshold_sp=0) # river eroder
lin_diffuse = LinearDiffuser(rmg, linear_diffusivity='D') #linear diffuser
fill = DepressionFinderAndRouter(rmg) #lake filling algorithm
nts = int(num_frames)
ds = xr.Dataset(
data_vars={
'topographic__elevation': (
('time', 'y', 'x'), # tuple of dimensions
np.empty((nts, rmg.shape[0], rmg.shape[1])), # n-d array of data
{
'units': 'meters'
})
}, # dictionary with data attributes
coords={
'x': (
('x'), # tuple of dimensions
rmg.x_of_node.reshape(
print('No pre-existing topography. Creating own random noise topo.')
#Create boundary conditions of the model grid (either closed or fixed-head)
for edge in (mg.nodes_at_left_edge,mg.nodes_at_right_edge, mg.nodes_at_top_edge):
mg.status_at_node[edge] = CLOSED_BOUNDARY
for edge in (mg.nodes_at_bottom_edge):
mg.status_at_node[edge] = FIXED_VALUE_BOUNDARY
#Initialize Fastscape
fc = FastscapeEroder(mg,
K_sp = ksp ,
m_sp = msp,
n_sp = nsp,
rainfall_intensity = 1)
fr = FlowRouter(mg)
lm = DepressionFinderAndRouter(mg)
for i in range(nSteps):
fr.run_one_step(dt=1)
lm.map_depressions()
fc.run_one_step(dt=1)
mg.at_node['topographic__elevation'][mg.core_nodes] += 0.0002
z = mg.at_node['topographic__elevation']
plt.figure()
imshow_grid(mg,z)
plt.savefig('test.png')
plt.close()
np.save('iniTopo',z)
def test_steady_state_with_basic_solver_option():
"""
Test that model matches the transport-limited analytical solution
for slope/area relationship at steady state: S=((U * v_s) / (K * A^m)
+ U / (K * A^m))^(1/n).
Also test that model matches the analytical solution for steady-state
sediment flux: Qs = U * A * (1 - phi).
"""
#set up a 5x5 grid with one open outlet node and low initial elevations.
nr = 5
nc = 5
mg = RasterModelGrid((nr, nc), 10.0)
z = mg.add_zeros('node', 'topographic__elevation')
mg['node']['topographic__elevation'] += mg.node_y / 100000 \
+ mg.node_x / 100000 \
+ np.random.rand(len(mg.node_y)) / 10000
mg.set_closed_boundaries_at_grid_edges(bottom_is_closed=True,
left_is_closed=True,
right_is_closed=True,
top_is_closed=True)
mg.set_watershed_boundary_condition_outlet_id(0,
mg['node']['topographic__elevation'],
-9999.)
#Instantiate DepressionFinderAndRouter
df = DepressionFinderAndRouter(mg)
# Create a D8 flow handler
fa = FlowAccumulator(mg, flow_director='D8',
depression_finder='DepressionFinderAndRouter')
# Parameter values for detachment-limited test
K = 0.01
U = 0.0001
dt = 1.0
F_f = 0.0 #all sediment is considered coarse bedload
m_sp = 0.5
n_sp = 1.0
v_s = 0.5
phi=0.5
# Instantiate the ErosionDeposition component...
ed = ErosionDeposition(mg, K=K, F_f=F_f, phi=phi, v_s=v_s, m_sp=m_sp,
n_sp=n_sp, sp_crit=0, solver='basic')
# ... and run it to steady state (5000x1-year timesteps).
for i in range(5000):
fa.run_one_step()
flooded = np.where(df.flood_status==3)[0]
ed.run_one_step(dt=dt, flooded_nodes=flooded)
z[mg.core_nodes] += U * dt #m
#compare numerical and analytical slope solutions
num_slope = mg.at_node['topographic__steepest_slope'][mg.core_nodes]
analytical_slope = (np.power(((U * v_s) / (K
* np.power(mg.at_node['drainage_area'][mg.core_nodes], m_sp)))
+ (U / (K * np.power(mg.at_node['drainage_area'][mg.core_nodes],
m_sp))), 1./n_sp))
#test for match with analytical slope-area relationship
testing.assert_array_almost_equal(num_slope, analytical_slope,
decimal=8,
err_msg='E/D slope-area test failed',
verbose=True)
#compare numerical and analytical sediment flux solutions
num_sedflux = mg.at_node['sediment__flux'][mg.core_nodes]
analytical_sedflux = (U * mg.at_node['drainage_area'][mg.core_nodes]
* (1 - phi))
#test for match with anakytical sediment flux
testing.assert_array_almost_equal(num_sedflux, analytical_sedflux,
decimal=8,
err_msg='E/D sediment flux test failed',
verbose=True)
def dans_grid3():
"""
Create a 7x7 test grid with a well defined hole in it.
"""
mg = RasterModelGrid(7, 7, 1.)
z = np.array([
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 2.0, 2.0, 2.0, 2.0, 2.0, 0.0],
[0.0, 2.0, 1.6, 1.5, 1.6, 2.0, 0.0],
[0.0, 2.0, 1.7, 1.6, 1.7, 2.0, 0.0],
[0.0, 2.0, 1.8, 2.0, 2.0, 2.0, 0.0],
[0.0, 1.0, 0.6, 1.0, 1.0, 1.0, 0.0],
[0.0, 0.0, -0.5, 0.0, 0.0, 0.0, 0.0],
]).flatten()
r_old = np.array([
[0, 1, 2, 3, 4, 5, 6],
[7, 1, 2, 3, 4, 5, 13],
[14, 14, 17, 17, 17, 20, 20],
[21, 21, 17, 17, 17, 27, 27],
[28, 28, 37, 38, 39, 34, 34],
[35, 44, 44, 44, 46, 41, 41],
[42, 43, 44, 45, 46, 47, 48],
]).flatten()
r_new = np.array([
[0, 1, 2, 3, 4, 5, 6],
[7, 1, 2, 3, 4, 5, 13],
[14, 14, 23, 24, 24, 20, 20],
[21, 21, 30, 30, 24, 27, 27],
[28, 28, 37, 38, 39, 34, 34],
[35, 44, 44, 44, 46, 41, 41],
[42, 43, 44, 45, 46, 47, 48],
]).flatten()
A_old = np.array([
[0., 1., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 1., 0.],
[1., 1., 1., 6., 1., 1., 1.],
[1., 1., 1., 1., 1., 1., 1.],
[1., 1., 1., 1., 1., 1., 1.],
[0., 1., 2., 2., 2., 1., 1.],
[0., 0., 5., 0., 2., 0., 0.],
]).flatten()
A_new = np.array([
[0., 1., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 1., 0.],
[1., 1., 1., 1., 1., 1., 1.],
[1., 1., 2., 4., 1., 1., 1.],
[1., 1., 7., 1., 1., 1., 1.],
[0., 1., 8., 2., 2., 1., 1.],
[0., 0., 11., 0., 2., 0., 0.],
]).flatten()
s_new = np.array([
[0, 1, 8, 2, 9, 3, 10],
[4, 11, 5, 12, 6, 7, 13],
[14, 15, 20, 19, 21, 22, 27],
[26, 28, 29, 34, 33, 35, 41],
[40, 42, 43, 44, 36, 37, 30],
[23, 16, 24, 17, 18, 25, 38],
[31, 45, 46, 39, 32, 47, 48],
]).flatten()
links_old = np.array([
[-1, -1, -1, -1, -1, -1, -1],
[-1, 7, 8, 9, 10, 11, -1],
[-1, 26, 28, -1, 29, 31, -1],
[-1, 39, 113, 35, 114, 44, -1],
[-1, 52, 60, 61, 62, 57, -1],
[-1, 146, 73, 149, 75, 70, -1],
[-1, -1, -1, -1, -1, -1, -1],
]).flatten()
links_new = np.array([
[-1, -1, -1, -1, -1, -1, -1],
[-1, 7, 8, 9, 10, 11, -1],
[-1, 26, 34, 35, 115, 31, -1],
[-1, 39, 47, 125, 42, 44, -1],
[-1, 52, 60, 61, 62, 57, -1],
[-1, 146, 73, 149, 75, 70, -1],
[-1, -1, -1, -1, -1, -1, -1],
]).flatten()
depr_outlet_target = np.array([
[XX, XX, XX, XX, XX, XX, XX],
[XX, XX, XX, XX, XX, XX, XX],
[XX, XX, 30, 30, 30, XX, XX],
[XX, XX, 30, 30, 30, XX, XX],
[XX, XX, XX, XX, XX, XX, XX],
[XX, XX, XX, XX, XX, XX, XX],
[XX, XX, XX, XX, XX, XX, XX],
]).flatten()
mg.add_field("node", "topographic__elevation", z, units="-")
fr = FlowAccumulator(mg, flow_director='D8')
lf = DepressionFinderAndRouter(mg)
class DansGrid(object):
pass
dans_grid = DansGrid()
dans_grid.mg = mg
dans_grid.fr = fr
dans_grid.lf = lf
dans_grid.z = z
dans_grid.r_new = r_new
dans_grid.r_old = r_old
dans_grid.A_new = A_new
dans_grid.A_old = A_old
dans_grid.s_new = s_new
dans_grid.depr_outlet_target = depr_outlet_target
dans_grid.links_old = links_old
dans_grid.links_new = links_new
return dans_grid
def test_degenerate_drainage():
"""
This "hourglass" configuration should be one of the hardest to correctly
re-route.
"""
mg = RasterModelGrid(9, 5)
z_init = mg.node_x.copy() * 0.0001 + 1.
lake_pits = np.array([7, 11, 12, 13, 17, 27, 31, 32, 33, 37])
z_init[lake_pits] = -1.
z_init[22] = 0. # the common spill pt for both lakes
z_init[21] = 0.1 # an adverse bump in the spillway
z_init[20] = -0.2 # the spillway
z = mg.add_field("node", "topographic__elevation", z_init)
fr = FlowRouter(mg)
lf = DepressionFinderAndRouter(mg)
fr.route_flow()
lf.map_depressions()
# correct_A = np.array([ 0., 0., 0., 0., 0.,
# 0., 1., 3., 1., 0.,
# 0., 5., 1., 2., 0.,
# 0., 1., 10., 1., 0.,
# 21., 21., 1., 1., 0.,
# 0., 1., 9., 1., 0.,
# 0., 3., 1., 2., 0.,
# 0., 1., 1., 1., 0.,
# 0., 0., 0., 0., 0.])
correct_A = np.array(
[
0.,
0.,
0.,
0.,
0.,
0.,
1.,
3.,
1.,
0.,
0.,
2.,
4.,
2.,
0.,
0.,
1.,
10.,
1.,
0.,
21.,
21.,
1.,
1.,
0.,
0.,
1.,
9.,
1.,
0.,
0.,
2.,
2.,
2.,
0.,
0.,
1.,
1.,
1.,
0.,
0.,
0.,
0.,
0.,
0.,
]
)
thelake = np.concatenate((lake_pits, [22])).sort()
assert mg.at_node["drainage_area"] == approx(correct_A)
def test_matches_transport_solution():
"""
Test that model matches the transport-limited analytical solution
for slope/area relationship at steady state: S=((U * v_s) / (K_sed * A^m)
+ U / (K_sed * A^m))^(1/n).
Also test that model matches the analytical solution for steady-state
sediment flux: Qs = U * A * (1 - phi).
"""
# set up a 5x5 grid with one open outlet node and low initial elevations.
nr = 5
nc = 5
mg = RasterModelGrid((nr, nc), xy_spacing=10.0)
z = mg.add_zeros("node", "topographic__elevation")
br = mg.add_zeros("node", "bedrock__elevation")
soil = mg.add_zeros("node", "soil__depth")
mg["node"]["topographic__elevation"] += (
mg.node_y / 100000 + mg.node_x / 100000 +
np.random.rand(len(mg.node_y)) / 10000)
mg.set_closed_boundaries_at_grid_edges(
bottom_is_closed=True,
left_is_closed=True,
right_is_closed=True,
top_is_closed=True,
)
mg.set_watershed_boundary_condition_outlet_id(
0, mg["node"]["topographic__elevation"], -9999.0)
soil[:] += 100.0 # initial soil depth of 100 m
br[:] = z[:]
z[:] += soil[:]
# Instantiate DepressionFinderAndRouter
df = DepressionFinderAndRouter(mg)
# Create a D8 flow handler
fa = FlowAccumulator(mg,
flow_director="D8",
depression_finder="DepressionFinderAndRouter")
# Parameter values for detachment-limited test
K_sed = 0.01
U = 0.0001
dt = 1.0
F_f = 1.0 # all detached rock disappears; detachment-ltd end-member
m_sp = 0.5
n_sp = 1.0
v_s = 0.5
phi = 0.5
# Instantiate the Space component...
sp = Space(
mg,
K_sed=K_sed,
K_br=0.01,
F_f=F_f,
phi=phi,
H_star=1.0,
v_s=v_s,
m_sp=m_sp,
n_sp=n_sp,
sp_crit_sed=0,
sp_crit_br=0,
)
# ... and run it to steady state (5000x1-year timesteps).
for i in range(5000):
fa.run_one_step()
flooded = np.where(df.flood_status == 3)[0]
sp.run_one_step(dt=dt, flooded_nodes=flooded)
br[mg.core_nodes] += U * dt # m
soil[
0] = 100.0 # enforce constant soil depth at boundary to keep lowering steady
z[:] = br[:] + soil[:]
# compare numerical and analytical slope solutions
num_slope = mg.at_node["topographic__steepest_slope"][mg.core_nodes]
analytical_slope = np.power(
((U * v_s * (1 - phi)) /
(K_sed * np.power(mg.at_node["drainage_area"][mg.core_nodes], m_sp)))
+
((U * (1 - phi)) /
(K_sed * np.power(mg.at_node["drainage_area"][mg.core_nodes], m_sp))),
1.0 / n_sp,
)
# test for match with analytical slope-area relationship
testing.assert_array_almost_equal(
num_slope,
analytical_slope,
decimal=8,
err_msg="SPACE transport-limited slope-area test failed",
verbose=True,
)
# compare numerical and analytical sediment flux solutions
num_sedflux = mg.at_node["sediment__flux"][mg.core_nodes]
analytical_sedflux = U * mg.at_node["drainage_area"][mg.core_nodes] * (1 -
phi)
# test for match with anakytical sediment flux
testing.assert_array_almost_equal(
num_sedflux,
analytical_sedflux,
decimal=8,
err_msg="SPACE transport-limited sediment flux test failed",
verbose=True,
)
fa = FlowAccumulator(grid,
surface='topographic__elevation',
flow_director='D8')
lmb = LakeMapperBarnes(
grid,
method='D8',
fill_flat=False,
surface="topographic__elevation",
fill_surface="topographic__elevation",
redirect_flow_steepest_descent=False,
reaccumulate_flow=False,
track_lakes=False,
ignore_overfill=True,
)
dfr = DepressionFinderAndRouter(grid)
ld = LinearDiffuser(grid, D)
sp = FastscapeEroder(grid, K_sp=Ksp, m_sp=0.5, n_sp=1.0, threshold_sp=E0)
for i in range(N):
dfr._find_pits()
if dfr._number_of_pits > 0:
lmb.run_one_step()
z[grid.core_nodes] += U * dt
ld.run_one_step(dt)
fa.run_one_step()
sp.run_one_step(dt)
def test_composite_pits():
"""
A test to ensure the component correctly handles cases where there are
multiple pits, inset into each other.
"""
mg = RasterModelGrid((10, 10))
z = mg.add_field("topographic__elevation", mg.node_x.copy(), at="node")
# a sloping plane
# np.random.seed(seed=0)
# z += np.random.rand(100)/10000.
# punch one big hole
z.reshape((10, 10))[3:8, 3:8] = 0.0
# dig a couple of inset holes
z[57] = -1.0
z[44] = -2.0
z[54] = -10.0
# make an outlet
z[71] = 0.9
fr = FlowAccumulator(mg, flow_director="D8")
lf = DepressionFinderAndRouter(mg)
fr.run_one_step()
lf.map_depressions()
flow_sinks_target = np.zeros(100, dtype=bool)
flow_sinks_target[mg.boundary_nodes] = True
# no internal sinks now:
assert_array_equal(mg.at_node["flow__sink_flag"], flow_sinks_target)
# test conservation of mass:
assert mg.at_node["drainage_area"].reshape(
(10, 10))[1:-1, 1].sum() == approx(8.0**2)
# ^all the core nodes
# test the actual flow field:
# nA = np.array([ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
# 8., 8., 7., 6., 5., 4., 3., 2., 1., 0.,
# 1., 1., 1., 1., 1., 1., 1., 1., 1., 0.,
# 1., 1., 1., 4., 2., 2., 8., 4., 1., 0.,
# 1., 1., 1., 8., 3., 15., 3., 2., 1., 0.,
# 1., 1., 1., 13., 25., 6., 3., 2., 1., 0.,
# 1., 1., 1., 45., 3., 3., 5., 2., 1., 0.,
# 50., 50., 49., 3., 2., 2., 2., 4., 1., 0.,
# 1., 1., 1., 1., 1., 1., 1., 1., 1., 0.,
# 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
nA = np.array([
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
8.0,
8.0,
7.0,
6.0,
5.0,
4.0,
3.0,
2.0,
1.0,
0.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
0.0,
1.0,
1.0,
1.0,
4.0,
2.0,
2.0,
6.0,
4.0,
1.0,
0.0,
1.0,
1.0,
1.0,
6.0,
3.0,
12.0,
3.0,
2.0,
1.0,
0.0,
1.0,
1.0,
1.0,
8.0,
20.0,
4.0,
3.0,
2.0,
1.0,
0.0,
1.0,
1.0,
1.0,
35.0,
5.0,
4.0,
3.0,
2.0,
1.0,
0.0,
50.0,
50.0,
49.0,
13.0,
10.0,
8.0,
6.0,
4.0,
1.0,
0.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
])
assert_array_equal(mg.at_node["drainage_area"], nA)
# the lake code map:
lc = np.array([
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
57,
57,
57,
57,
57,
XX,
XX,
XX,
XX,
XX,
57,
57,
57,
57,
57,
XX,
XX,
XX,
XX,
XX,
57,
57,
57,
57,
57,
XX,
XX,
XX,
XX,
XX,
57,
57,
57,
57,
57,
XX,
XX,
XX,
XX,
XX,
57,
57,
57,
57,
57,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
])
# test the remaining properties:
assert lf.lake_outlets.size == 1
assert lf.lake_outlets[0] == 72
outlets_in_map = np.unique(lf.depression_outlet_map)
assert outlets_in_map.size == 2
assert outlets_in_map[1] == 72
assert lf.number_of_lakes == 1
assert lf.lake_codes[0] == 57
assert_array_equal(lf.lake_map, lc)
assert lf.lake_areas[0] == approx(25.0)
assert lf.lake_volumes[0] == approx(63.0)
def test_three_pits():
"""
A test to ensure the component correctly handles cases where there are
multiple pits.
"""
mg = RasterModelGrid((10, 10))
z = mg.add_field("topographic__elevation", mg.node_x.copy(), at="node")
# a sloping plane
# np.random.seed(seed=0)
# z += np.random.rand(100)/10000.
# punch some holes
z[33] = 1.0
z[43] = 1.0
z[37] = 4.0
z[74:76] = 1.0
fr = FlowAccumulator(mg, flow_director="D8")
lf = DepressionFinderAndRouter(mg)
fr.run_one_step()
lf.map_depressions()
flow_sinks_target = np.zeros(100, dtype=bool)
flow_sinks_target[mg.boundary_nodes] = True
# no internal sinks now:
assert_array_equal(mg.at_node["flow__sink_flag"], flow_sinks_target)
# test conservation of mass:
assert mg.at_node["drainage_area"].reshape(
(10, 10))[1:-1, 1].sum() == approx(8.0**2)
# ^all the core nodes
# test the actual flow field:
nA = np.array([
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
8.0,
8.0,
7.0,
6.0,
5.0,
4.0,
3.0,
2.0,
1.0,
0.0,
2.0,
2.0,
1.0,
1.0,
2.0,
1.0,
1.0,
1.0,
1.0,
0.0,
26.0,
26.0,
25.0,
15.0,
11.0,
10.0,
9.0,
8.0,
1.0,
0.0,
2.0,
2.0,
1.0,
9.0,
2.0,
1.0,
1.0,
1.0,
1.0,
0.0,
2.0,
2.0,
1.0,
1.0,
5.0,
4.0,
3.0,
2.0,
1.0,
0.0,
2.0,
2.0,
1.0,
1.0,
1.0,
1.0,
3.0,
2.0,
1.0,
0.0,
20.0,
20.0,
19.0,
18.0,
17.0,
12.0,
3.0,
2.0,
1.0,
0.0,
2.0,
2.0,
1.0,
1.0,
1.0,
1.0,
3.0,
2.0,
1.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
])
assert_array_equal(mg.at_node["drainage_area"], nA)
# test a couple more properties:
lc = np.empty(100, dtype=int)
lc.fill(XX)
lc[33] = 33
lc[43] = 33
lc[37] = 37
lc[74:76] = 74
assert_array_equal(lf.lake_map, lc)
assert_array_equal(lf.lake_codes, [33, 37, 74])
assert lf.number_of_lakes == 3
assert lf.lake_areas == approx([2.0, 1.0, 2.0])
assert lf.lake_volumes == approx([2.0, 2.0, 4.0])
def test_degenerate_drainage():
"""
This "hourglass" configuration should be one of the hardest to correctly
re-route.
"""
mg = RasterModelGrid((9, 5))
z_init = mg.node_x.copy() * 0.0001 + 1.0
lake_pits = np.array([7, 11, 12, 13, 17, 27, 31, 32, 33, 37])
z_init[lake_pits] = -1.0
z_init[22] = 0.0 # the common spill pt for both lakes
z_init[21] = 0.1 # an adverse bump in the spillway
z_init[20] = -0.2 # the spillway
mg.add_field("topographic__elevation", z_init, at="node")
fr = FlowAccumulator(mg, flow_director="D8")
lf = DepressionFinderAndRouter(mg)
fr.run_one_step()
lf.map_depressions()
# correct_A = np.array([ 0., 0., 0., 0., 0.,
# 0., 1., 3., 1., 0.,
# 0., 5., 1., 2., 0.,
# 0., 1., 10., 1., 0.,
# 21., 21., 1., 1., 0.,
# 0., 1., 9., 1., 0.,
# 0., 3., 1., 2., 0.,
# 0., 1., 1., 1., 0.,
# 0., 0., 0., 0., 0.])
correct_A = np.array([
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
1.0,
3.0,
1.0,
0.0,
0.0,
2.0,
4.0,
2.0,
0.0,
0.0,
1.0,
10.0,
1.0,
0.0,
21.0,
21.0,
1.0,
1.0,
0.0,
0.0,
1.0,
9.0,
1.0,
0.0,
0.0,
2.0,
2.0,
2.0,
0.0,
0.0,
1.0,
1.0,
1.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
])
assert mg.at_node["drainage_area"] == approx(correct_A)
def test_edge_draining():
"""
This tests when the lake attempts to drain from an edge, where an issue
is suspected.
"""
# Create a 7x7 test grid with a well defined hole in it, AT THE EDGE.
mg = RasterModelGrid((7, 7))
z = mg.node_x.copy()
guard_sides = np.concatenate((np.arange(7, 14), np.arange(35, 42)))
edges = np.concatenate((np.arange(7), np.arange(42, 49)))
hole_here = np.array(([15, 16, 22, 23, 29, 30]))
z[guard_sides] = z[13]
z[edges] = -2.0 # force flow outwards from the tops of the guards
z[hole_here] = -1.0
A_new = np.array([[[
0.0,
1.0,
1.0,
1.0,
1.0,
1.0,
0.0,
0.0,
1.0,
1.0,
1.0,
1.0,
1.0,
0.0,
15.0,
5.0,
4.0,
3.0,
2.0,
1.0,
0.0,
0.0,
10.0,
4.0,
3.0,
2.0,
1.0,
0.0,
0.0,
1.0,
4.0,
3.0,
2.0,
1.0,
0.0,
0.0,
1.0,
1.0,
1.0,
1.0,
1.0,
0.0,
0.0,
1.0,
1.0,
1.0,
1.0,
1.0,
0.0,
]]]).flatten()
depr_outlet_target = np.array([
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
14,
14,
XX,
XX,
XX,
XX,
XX,
14,
14,
XX,
XX,
XX,
XX,
XX,
14,
14,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
XX,
]).flatten()
mg.add_field("topographic__elevation", z, at="node", units="-")
fr = FlowAccumulator(mg, flow_director="D8")
lf = DepressionFinderAndRouter(mg)
fr.run_one_step()
lf.map_depressions()
assert mg.at_node["drainage_area"] == approx(A_new)
assert lf.depression_outlet_map == approx(depr_outlet_target)
def get_ordered_cells_for_soil_moisture(grid, outlet_id=None):
"""
Runs Landlab's FlowRouter and DepressionFinderAndRouter to
route flow. Also orders the cells in the descending order of
channel length (upstream cell order).
Parameters:
==========
grid: grid object
RasterModelGrid
outlet_id: int (Optional)
Outlet id to be set
Returns:
=======
ordered_cells: np.array(dtype=int)
cells ordered in descending order of channel length
grid: grid object
updated RasterModelGrid
"""
if outlet_id == None:
outlet_id = np.argmin(grid.at_node['topographic__elevation'])
outlet = grid.set_watershed_boundary_condition_outlet_id(outlet_id,
grid.at_node['topographic__elevation'], nodata_value=-9999.,)
grid.set_closed_boundaries_at_grid_edges(True, True, True, True)
flw_r = FlowRouter(grid)
flw_r.run_one_step()
df = DepressionFinderAndRouter(grid)
df.map_depressions()
r = grid.at_node['flow__receiver_node'][grid.node_at_core_cell]
R = np.zeros(grid.number_of_nodes, dtype=int)
R[grid.node_at_core_cell] = r
channel_length = np.zeros(grid.number_of_nodes, dtype=int)
# Compute channel lengths for each node in the wtrshd (node_at_core_cell)
for node in grid.node_at_core_cell:
node_c = node.copy()
while R[node_c] != node_c:
channel_length[node] += 1
node_c = R[node_c]
grid.at_node['channel_length'] = channel_length
# Sorting nodes in the ascending order of channel length
# NOTE: length of ordered_nodes = grid.number_of_core_cells
ordered_nodes = grid.node_at_core_cell[
np.argsort(channel_length[grid.node_at_core_cell])]
# Sorting nodes in the descending order of channel length
ordered_nodes = ordered_nodes[::-1]
dd = 1 # switch 2 for while loop
count_loops = 0 # No. of loops while runs
while dd:
dd = 0
count_loops += 1
sorted_order = list(ordered_nodes)
alr_counted_ = []
for node_ in sorted_order:
donors = []
donors = list(grid.node_at_core_cell[np.where(r==node_)[0]])
if len(donors) != 0:
for k in range(0, len(donors)):
if donors[k] not in alr_counted_:
sorted_order.insert(donors[k], sorted_order.pop(sorted_order.index(node_)))
dd = 1
alr_counted_.append(node_)
ordered_nodes = np.array(sorted_order)
ordered_cells = grid.cell_at_node[ordered_nodes]
return ordered_cells, grid
def test_matches_bedrock_alluvial_solution():
"""
Test that model matches the bedrock-alluvial analytical solution
for slope/area relationship at steady state:
S=((U * v_s * (1 - F_f)) / (K_sed * A^m) + U / (K_br * A^m))^(1/n).
Also test that the soil depth everywhere matches the bedrock-alluvial
analytical solution at steady state:
H = -H_star * ln(1 - (v_s / (K_sed / (K_br * (1 - F_f)) + v_s))).
"""
#set up a 5x5 grid with one open outlet node and low initial elevations.
nr = 5
nc = 5
mg = RasterModelGrid((nr, nc), 10.0)
z = mg.add_zeros('node', 'topographic__elevation')
br = mg.add_zeros('node', 'bedrock__elevation')
soil = mg.add_zeros('node', 'soil__depth')
mg['node']['topographic__elevation'] += (
mg.node_y / 100000 + mg.node_x / 100000 +
np.random.rand(len(mg.node_y)) / 10000)
mg.set_closed_boundaries_at_grid_edges(bottom_is_closed=True,
left_is_closed=True,
right_is_closed=True,
top_is_closed=True)
mg.set_watershed_boundary_condition_outlet_id(
0, mg['node']['topographic__elevation'], -9999.)
soil[:] += 0. #initial condition of no soil depth.
br[:] = z[:]
z[:] += soil[:]
#Instantiate DepressionFinderAndRouter
df = DepressionFinderAndRouter(mg)
# Create a D8 flow handler
fa = FlowAccumulator(mg,
flow_director='D8',
depression_finder='DepressionFinderAndRouter')
# Parameter values for detachment-limited test
K_br = 0.02
K_sed = 0.02
U = 0.0001
dt = 1.0
F_f = 0.2 #all detached rock disappears; detachment-ltd end-member
m_sp = 0.5
n_sp = 1.0
v_s = 0.25
H_star = 0.1
# Instantiate the Space component...
sp = Space(mg,
K_sed=K_sed,
K_br=K_br,
F_f=F_f,
phi=0.0,
H_star=H_star,
v_s=v_s,
m_sp=m_sp,
n_sp=n_sp,
sp_crit_sed=0,
sp_crit_br=0)
# ... and run it to steady state (10000x1-year timesteps).
for i in range(10000):
fa.run_one_step()
flooded = np.where(df.flood_status == 3)[0]
sp.run_one_step(dt=dt, flooded_nodes=flooded)
br[mg.core_nodes] += U * dt #m
soil[0] = 0. #enforce 0 soil depth at boundary to keep lowering steady
z[:] = br[:] + soil[:]
#compare numerical and analytical slope solutions
num_slope = mg.at_node['topographic__steepest_slope'][mg.core_nodes]
analytical_slope = (np.power(
((U * v_s * (1 - F_f)) /
(K_sed * np.power(mg.at_node['drainage_area'][mg.core_nodes], m_sp)))
+
(U /
(K_br * np.power(mg.at_node['drainage_area'][mg.core_nodes], m_sp))),
1. / n_sp))
#test for match with analytical slope-area relationship
testing.assert_array_almost_equal(
num_slope,
analytical_slope,
decimal=8,
err_msg='SPACE bedrock-alluvial slope-area test failed',
verbose=True)
#compare numerical and analytical soil depth solutions
num_h = mg.at_node['soil__depth'][mg.core_nodes]
analytical_h = -H_star * np.log(1 - (v_s / (K_sed / (K_br *
(1 - F_f)) + v_s)))
#test for match with analytical sediment depth
testing.assert_array_almost_equal(
num_h,
analytical_h,
decimal=5,
err_msg='SPACE bedrock-alluvial soil thickness test failed',
verbose=True)