[docs]
class ExponentialWeatherer(Component):
"""Calculate exponential weathering of bedrock on hillslopes.
Uses exponential soil production function in the style of Ahnert (1976).
Consider that ``w0`` is the maximum soil production rate and
that ``w_star`` is the characteristic soil production depth. The
soil production rate ``w0`` is given as a function of the soil
depth::
soil_production = w0 * exp(-soil__depth / w_star)
The :class:`~.ExponentialWeatherer` only calculates soil production at core nodes.
An alternative version which uses the analytical integral of
production through time is available at the component
:py:class:`~.ExponentialWeathererIntegrated`.
Examples
--------
>>> import numpy as np
>>> from landlab import RasterModelGrid
>>> from landlab.components import ExponentialWeatherer
>>> mg = RasterModelGrid((5, 5))
>>> soilz = mg.add_zeros("soil__depth", at="node")
>>> soilrate = mg.add_ones("soil_production__rate", at="node")
>>> expw = ExponentialWeatherer(mg)
>>> expw.calc_soil_prod_rate()
>>> np.allclose(mg.at_node["soil_production__rate"], 1.0)
True
References
----------
**Required Software Citation(s) Specific to this Component**
Barnhart, K., Glade, R., Shobe, C., Tucker, G. (2019). Terrainbento 1.0: a
Python package for multi-model analysis in long-term drainage basin
evolution. Geoscientific Model Development 12(4), 1267--1297.
https://dx.doi.org/10.5194/gmd-12-1267-2019
**Additional References**
Ahnert, F. (1976). Brief description of a comprehensive three-dimensional
process-response model of landform development Z. Geomorphol. Suppl. 25,
29 - 49.
Armstrong, A. (1976). A three dimensional simulation of slope forms.
Zeitschrift für Geomorphologie 25, 20 - 28.
"""
_name = "ExponentialWeatherer"
_unit_agnostic = True
_cite_as = """
@article{barnhart2019terrain,
author = {Barnhart, Katherine R and Glade, Rachel C and Shobe, Charles M
and Tucker, Gregory E},
title = {{Terrainbento 1.0: a Python package for multi-model analysis in
long-term drainage basin evolution}},
doi = {10.5194/gmd-12-1267-2019},
pages = {1267---1297},
number = {4},
volume = {12},
journal = {Geoscientific Model Development},
year = {2019},
}
"""
_info = {
"soil__depth": {
"dtype": float,
"intent": "in",
"optional": False,
"units": "m",
"mapping": "node",
"doc": "Depth of soil or weathered bedrock",
},
"soil_production__rate": {
"dtype": float,
"intent": "out",
"optional": False,
"units": "m/yr",
"mapping": "node",
"doc": "rate of soil production at nodes",
},
}
[docs]
def __init__(
self, grid, soil_production_maximum_rate=1.0, soil_production_decay_depth=1.0
):
"""
Parameters
----------
grid: ModelGrid
Landlab ModelGrid object
soil_production_maximum_rate : float, array of float
Maximum weathering rate for bare bedrock
soil_production_decay_depth : float, array of float
Characteristic weathering depth
"""
super().__init__(grid)
# Store grid and parameters
# soil_production_maximum_rate, value set in setter below
self._w0 = None
# soil_production_decay_depth, value set in setter below
self._wstar = None
self.maximum_weathering_rate = soil_production_maximum_rate
self.decay_depth = soil_production_decay_depth
# weathering rate
if "soil_production__rate" not in grid.at_node:
grid.add_zeros("soil_production__rate", at="node")
[docs]
def calc_soil_prod_rate(self):
"""Calculate soil production rate."""
core = self._grid.core_nodes
self.grid.at_node["soil_production__rate"][core] = self._w0[core] * np.exp(
-self.grid.at_node["soil__depth"][core] / self._wstar[core]
)
[docs]
def run_one_step(self):
"""
Parameters
----------
dt: float
Used only for compatibility with standard run_one_step.
"""
self.calc_soil_prod_rate()
@property
def maximum_weathering_rate(self):
"""Maximum rate of weathering (m/yr)."""
return self._w0
@maximum_weathering_rate.setter
def maximum_weathering_rate(self, new_val):
if np.any(new_val <= 0):
raise ValueError("Maximum weathering rate must be positive.")
self._w0 = np.broadcast_to(new_val, self.grid.number_of_nodes)
@property
def decay_depth(self):
"""Maximum rate of weathering (m/yr)."""
return self._wstar
@decay_depth.setter
def decay_depth(self, new_val):
if np.any(new_val <= 0):
raise ValueError("Maximum decay depth must be positive.")
self._wstar = np.broadcast_to(new_val, self.grid.number_of_nodes)