landlab

landlab.utils.watershed module

Functions to work with watersheds of model grids.

get_watershed_mask(grid, outlet_id)[source]

Get the watershed of an outlet returned as a boolean array.

Parameters:
  • grid (RasterModelGrid) – A landlab RasterModelGrid.
  • outlet_id (integer) – The id of the outlet node.
Returns:

watershed_mask – True elements of this array correspond to nodes with flow that is received by the outlet. The length of the array is equal to the grid number of nodes.

Return type:

boolean ndarray

Examples

>>> import numpy as np
>>> from landlab import RasterModelGrid
>>> from landlab.components import FlowAccumulator
>>> from landlab.utils import get_watershed_mask
>>> rmg = RasterModelGrid((7, 7))
>>> z = np.array([
...     -9999., -9999., -9999., -9999., -9999., -9999., -9999.,
...     -9999.,    26.,     0.,    30.,    32.,    34., -9999.,
...     -9999.,    28.,     1.,    25.,    28.,    32., -9999.,
...     -9999.,    30.,     3.,     3.,    11.,    34., -9999.,
...     -9999.,    32.,    11.,    25.,    18.,    38., -9999.,
...     -9999.,    34.,    32.,    34.,    36.,    40., -9999.,
...     -9999., -9999., -9999., -9999., -9999., -9999., -9999.])
>>> rmg.at_node['topographic__elevation'] = z

Only the bottom boundary is set to open. >>> rmg.set_closed_boundaries_at_grid_edges(True, True, True, False) >>> rmg.set_fixed_value_boundaries_at_grid_edges(False, False, False, True)

Route flow. >>> fr = FlowAccumulator(rmg, flow_director=’D8’) >>> fr.run_one_step()

>>> get_watershed_mask(rmg, 2).reshape(rmg.shape)
array([[False, False,  True, False, False, False, False],
       [False, False,  True, False, False, False, False],
       [False,  True,  True,  True, True,  True,  False],
       [False,  True,  True,  True,  True,  True, False],
       [False,  True,  True,  True,  True,  True, False],
       [False,  True,  True,  True,  True,  True, False],
       [False, False, False, False, False, False, False]], dtype=bool)
get_watershed_masks(grid)[source]

Assign the watershed outlet id to all nodes in the grid.

Parameters:grid (RasterModelGrid) – A landlab RasterModelGrid.
Returns:watershed_masks – The length of the array is equal to the grid number of nodes. Values of this array are the watershed ids. The value of a watershed id is the node id of the watershed outlet.
Return type:integer ndarray

Examples

>>> import numpy as np
>>> from landlab import RasterModelGrid
>>> from landlab.components import FlowAccumulator
>>> from landlab.utils import get_watershed_masks

Create a grid with a node spacing of 200 meter. >>> rmg = RasterModelGrid((7, 7), xy_spacing=200) >>> z = np.array([ … -9999., -9999., -9999., -9999., -9999., -9999., -9999., … -9999., 26., 0., 26., 30., 34., -9999., … -9999., 28., 1., 28., 5., 32., -9999., … -9999., 30., 3., 30., 10., 34., -9999., … -9999., 32., 11., 32., 15., 38., -9999., … -9999., 34., 32., 34., 36., 40., -9999., … -9999., -9999., -9999., -9999., -9999., -9999., -9999.]) >>> rmg.at_node[‘topographic__elevation’] = z >>> rmg.set_closed_boundaries_at_grid_edges(True, True, True, False)

Route flow.

>>> fr = FlowAccumulator(rmg, flow_director='D8')
>>> fr.run_one_step()

Assign mask.

>>> mask = get_watershed_masks(rmg)
>>> mask.reshape(rmg.shape)
array([[ 0,  1,  2,  3,  4,  5,  6],
       [ 7,  1,  2,  3,  4,  5, 13],
       [14,  2,  2,  2, 18, 18, 20],
       [21,  2,  2,  2, 18, 18, 27],
       [28,  2,  2,  2, 18, 18, 34],
       [35,  2,  2,  2, 18, 18, 41],
       [42, 43, 44, 45, 46, 47, 48]])
get_watershed_masks_with_area_threshold(grid, critical_area)[source]

Get masks of all of the watersheds with a minimum drainage area size.

Parameters:
  • grid (RasterModelGrid) – A landlab RasterModelGrid.
  • critical_area (integer or float) – The minimum drainage area of the watersheds to identify.
Returns:

watershed_masks – The length of the array is equal to the grid number of nodes. Values of this array are the watershed ids. The value of a watershed id is the node id of the watershed outlet. Nodes with a value of -1 have only downstream nodes with drainage areas below critical_area.

Return type:

integer ndarray

Examples

>>> import numpy as np
>>> from landlab import RasterModelGrid
>>> from landlab.components import FlowAccumulator
>>> from landlab.utils import get_watershed_masks_with_area_threshold

Create a grid with a node spacing of 200 meter.

>>> rmg = RasterModelGrid((7, 7), xy_spacing=200)
>>> z = np.array([
...     -9999., -9999., -9999., -9999., -9999., -9999., -9999.,
...     -9999.,    26.,     0.,    26.,    30.,    34., -9999.,
...     -9999.,    28.,     1.,    28.,     5.,    32., -9999.,
...     -9999.,    30.,     3.,    30.,    10.,    34., -9999.,
...     -9999.,    32.,    11.,    32.,    15.,    38., -9999.,
...     -9999.,    34.,    32.,    34.,    36.,    40., -9999.,
...     -9999., -9999., -9999., -9999., -9999., -9999., -9999.])
>>> rmg.at_node['topographic__elevation'] = z
>>> rmg.set_closed_boundaries_at_grid_edges(True, True, True, False)

Route flow.

>>> fr = FlowAccumulator(rmg, flow_director='D8')
>>> fr.run_one_step()

Get the masks of watersheds greater than or equal to 80,000 square-meters.

>>> critical_area = 80000
>>> mask = get_watershed_masks_with_area_threshold(rmg, critical_area)

Verify that all mask null nodes have a drainage area below critical area.

>>> null_nodes = np.where(mask == -1)[0]
>>> A = rmg.at_node['drainage_area'][null_nodes]
>>> below_critical_area_nodes = A < critical_area
>>> np.all(below_critical_area_nodes)
True
get_watershed_nodes(grid, outlet_id)[source]

Get the watershed of an outlet returned as a list of nodes.

Parameters:
  • grid (RasterModelGrid) – A landlab RasterModelGrid.
  • outlet_id (integer) – The id of the outlet node.
Returns:

watershed_nodes – The ids of the nodes that flow to the node with the id, outlet_id.

Return type:

integer ndarray

Examples

>>> import numpy as np
>>> from landlab import RasterModelGrid
>>> from landlab.components import FlowAccumulator
>>> from landlab.utils import get_watershed_nodes
>>> rmg = RasterModelGrid((7, 7))
>>> z = np.array([
...     -9999., -9999., -9999., -9999., -9999., -9999., -9999.,
...     -9999.,    26.,     0.,    30.,    32.,    34., -9999.,
...     -9999.,    28.,     1.,    25.,    28.,    32., -9999.,
...     -9999.,    30.,     3.,     3.,    11.,    34., -9999.,
...     -9999.,    32.,    11.,    25.,    18.,    38., -9999.,
...     -9999.,    34.,    32.,    34.,    36.,    40., -9999.,
...     -9999., -9999., -9999., -9999., -9999., -9999., -9999.])
>>> rmg.at_node['topographic__elevation'] = z
>>> rmg.set_watershed_boundary_condition_outlet_id(2, z,
...                                                nodata_value=-9999.)

Route flow. >>> fr = FlowAccumulator(rmg, flow_director=’D8’) >>> fr.run_one_step()

Get the nodes of two watersheds. >>> mainstem_watershed_nodes = get_watershed_nodes(rmg, 2) >>> tributary_watershed_nodes = get_watershed_nodes(rmg, 24)

Given the watershed boundary conditions, the number of mainstem watershed nodes should be equal to the number of core nodes plus the outlet node. >>> len(mainstem_watershed_nodes) == rmg.number_of_core_nodes + 1 True

get_watershed_outlet(grid, source_node_id)[source]

Get the downstream-most node (the outlet) of the source node.

Parameters:
  • grid (RasterModelGrid) – A landlab RasterModelGrid.
  • source_node_id (integer) – The id of the node in which to identify its outlet.
Returns:

outlet_node – The id of the node that is the downstream-most node (the outlet) of the source node.

Return type:

integer

Examples

>>> import numpy as np
>>> from landlab import RasterModelGrid
>>> from landlab.components import FlowAccumulator
>>> from landlab.utils import get_watershed_outlet
>>> rmg = RasterModelGrid((7, 7))
>>> z = np.array([
...     -9999., -9999., -9999., -9999., -9999., -9999., -9999.,
...     -9999.,    26.,     0.,    30.,    32.,    34., -9999.,
...     -9999.,    28.,     1.,    25.,    28.,    32., -9999.,
...     -9999.,    30.,     3.,     3.,    11.,    34., -9999.,
...     -9999.,    32.,    11.,    25.,    18.,    38., -9999.,
...     -9999.,    34.,    32.,    34.,    36.,    40., -9999.,
...     -9999., -9999., -9999., -9999., -9999., -9999., -9999.])
>>> rmg.at_node['topographic__elevation'] = z
>>> imposed_outlet = 2
>>> rmg.set_watershed_boundary_condition_outlet_id(imposed_outlet, z,
...                                                nodata_value=-9999.)

Route flow. >>> fr = FlowAccumulator(rmg, flow_director=’D8’) >>> fr.run_one_step()

Get the grid watershed outlet. >>> determined_outlet = get_watershed_outlet(rmg, 40) >>> determined_outlet == imposed_outlet True