landlab.components.hack_calculator.hack_calculator¶
Calculate Hack parameters.
- class HackCalculator[source]¶
Bases:
Component
This component calculates Hack’s law parameters for drainage basins.
Hacks law is given as
- ..:math:
L = C * A**h
Where \(L\) is the distance to the drainage divide along the channel, \(A\) is the drainage area, and \(C`and :math:`h\) are parameters.
The HackCalculator uses a ChannelProfiler to determine the nodes on which to calculate the parameter fit.
Examples
>>> import pandas as pd >>> pd.set_option("display.max_columns", None) >>> import numpy as np >>> from landlab import RasterModelGrid >>> from landlab.components import FlowAccumulator, FastscapeEroder, HackCalculator >>> np.random.seed(42) >>> mg = RasterModelGrid((50, 100), xy_spacing=100) >>> z = mg.add_zeros("node", "topographic__elevation") >>> z[mg.core_nodes] += np.random.randn(mg.core_nodes.size) >>> fa = FlowAccumulator(mg) >>> fs = FastscapeEroder(mg, K_sp=0.001) >>> for i in range(100): ... fa.run_one_step() ... fs.run_one_step(1000) ... z[mg.core_nodes] += 0.01 * 1000 ... >>> hc = HackCalculator(mg) >>> hc.calculate_hack_parameters() >>> largest_outlet = mg.boundary_nodes[ ... np.argsort(mg.at_node["drainage_area"][mg.boundary_nodes])[-1:] ... ][0] >>> largest_outlet 4978 >>> hc.hack_coefficient_dataframe.loc[largest_outlet, "A_max"] 2830000.0 >>> hc.hack_coefficient_dataframe.round(2) A_max C h basin_outlet_id 4978 2830000.0 0.31 0.62
>>> hc = HackCalculator( ... mg, number_of_watersheds=3, main_channel_only=False, save_full_df=True ... ) >>> hc.calculate_hack_parameters() >>> hc.hack_coefficient_dataframe.round(2) A_max C h basin_outlet_id 39 2170000.0 0.13 0.69 4929 2350000.0 0.13 0.68 4978 2830000.0 0.23 0.64 >>> hc.full_hack_dataframe.head().round(2) basin_outlet_id A L_obs L_est node_id 39 39.0 2170000.0 3200.0 2903.43 139 39.0 2170000.0 3100.0 2903.43 238 39.0 10000.0 0.0 71.61 239 39.0 2160000.0 3000.0 2894.22 240 39.0 10000.0 0.0 71.61
References
Required Software Citation(s) Specific to this Component
None Listed
Additional References
Hack, J. T. Studies of longitudinal stream profiles in Virginia and Maryland (Vol. 294). U.S. Geological Survey Professional Paper 294-B (1957). https://doi.org/10.3133/pp294B
- Parameters:
grid (Landlab Model Grid instance, required)
save_full_df (bool) – Flag indicating whether to create the
full_hack_dataframe
.**kwds – Values to pass to the ChannelProfiler.
- __init__(grid, save_full_df=False, **kwds)[source]¶
- Parameters:
grid (Landlab Model Grid instance, required)
save_full_df (bool) – Flag indicating whether to create the
full_hack_dataframe
.**kwds – Values to pass to the ChannelProfiler.
- static __new__(cls, *args, **kwds)¶
- cite_as = ''¶
- property coords¶
Return the coordinates of nodes on grid attached to the component.
- property current_time¶
Current time.
Some components may keep track of the current time. In this case, the
current_time
attribute is incremented. Otherwise it is set to None.- Return type:
current_time
- definitions = (('distance_to_divide', 'Distance from drainage divide.'), ('drainage_area', "Upstream accumulated surface area contributing to the node's discharge"), ('flow__link_to_receiver_node', 'ID of link downstream of each node, which carries the discharge'), ('flow__receiver_node', 'Node array of receivers (node that receives flow from current node)'), ('flow__upstream_node_order', 'Node array containing downstream-to-upstream ordered list of node IDs'), ('topographic__elevation', 'Land surface topographic elevation'))¶
- classmethod from_path(grid, path)¶
Create a component from an input file.
- property full_hack_dataframe¶
Full Hack calculation dataframe.
This dataframe is optionally created and stored on the component when the keyword argument
full_hack_dataframe=True
is passed to the component init.It is pandas dataframe with a row for every model grid cell used to estimate the Hack parameters. It has the following index and columns.
- Index
node_id*: The node ID of the model grid cell.
- Columns
basin_outlet_id: The node IDs of watershed outlet
A: The drainage are of the model grid cell.
L_obs: The observed distance to the divide.
L_est: The predicted distance to divide based on the Hack coefficient fit.
- property grid¶
Return the grid attached to the component.
- property hack_coefficient_dataframe¶
Hack coefficient dataframe.
This dataframe is created and stored on the component.
It is a pandas dataframe with one row for each basin for which Hack parameters are calculated. Thus, there are as many rows as the number of watersheds identified by the ChannelProfiler.
The dataframe has the following index and columns.
- Index
basin_outlet_id: The node ID of the watershed outlet where each set of Hack parameters was estimated.
- Columns
A_max: The drainage area of the watershed outlet.
C: The Hack coefficient as defined in the equations above.
h: The Hack exponent as defined in the equations above.
- initialize_optional_output_fields()¶
Create fields for a component based on its optional field outputs, if declared in _optional_var_names.
This method will create new fields (without overwrite) for any fields output by the component as optional. New fields are initialized to zero. New fields are created as arrays of floats, unless the component also contains the specifying property _var_type.
- initialize_output_fields(values_per_element=None)¶
Create fields for a component based on its input and output var names.
This method will create new fields (without overwrite) for any fields output by, but not supplied to, the component. New fields are initialized to zero. Ignores optional fields. New fields are created as arrays of floats, unless the component specifies the variable type.
- Parameters:
values_per_element (int (optional)) – On occasion, it is necessary to create a field that is of size (n_grid_elements, values_per_element) instead of the default size (n_grid_elements,). Use this keyword argument to acomplish this task.
- input_var_names = ('drainage_area', 'flow__link_to_receiver_node', 'flow__receiver_node', 'flow__upstream_node_order', 'topographic__elevation')¶
- name = 'HackCalculator'¶
- optional_var_names = ()¶
- output_var_names = ('distance_to_divide',)¶
- property shape¶
Return the grid shape attached to the component, if defined.
- unit_agnostic = True¶
- units = (('distance_to_divide', 'm'), ('drainage_area', 'm**2'), ('flow__link_to_receiver_node', '-'), ('flow__receiver_node', '-'), ('flow__upstream_node_order', '-'), ('topographic__elevation', 'm'))¶
- classmethod var_definition(name)¶
Get a description of a particular field.
- Parameters:
name (str) – A field name.
- Returns:
A description of each field.
- Return type:
tuple of (name, *description*)
- classmethod var_help(name)¶
Print a help message for a particular field.
- Parameters:
name (str) – A field name.
- classmethod var_loc(name)¶
Location where a particular variable is defined.
- var_mapping = (('distance_to_divide', 'node'), ('drainage_area', 'node'), ('flow__link_to_receiver_node', 'node'), ('flow__receiver_node', 'node'), ('flow__upstream_node_order', 'node'), ('topographic__elevation', 'node'))¶