# coding: utf8
# !/usr/env/python
"""terrainbento **BasicStTh** model program.
Erosion model program using linear diffusion, smoothly thresholded stream
power, and stochastic discharge with a smoothed infiltration capacity
threshold.
Landlab components used:
1. `FlowAccumulator <https://landlab.readthedocs.io/en/master/reference/components/flow_accum.html>`_
2. `DepressionFinderAndRouter <https://landlab.readthedocs.io/en/master/reference/components/flow_routing.html>`_ (optional)
3. `StreamPowerSmoothThresholdEroder`
4. `LinearDiffuser <https://landlab.readthedocs.io/en/master/reference/components/diffusion.html>`_
5. `PrecipitationDistribution <https://landlab.readthedocs.io/en/master/reference/components/uniform_precip.html>`_
"""
from landlab.components import LinearDiffuser, StreamPowerSmoothThresholdEroder
from terrainbento.base_class import StochasticErosionModel
[docs]class BasicStTh(StochasticErosionModel):
r"""**BasicStTh** model program.
This model program uses a stochastic treatment of runoff and discharge, and
includes an erosion threshold in the water erosion law. It combines models
:py:class:`BasicSt` and :py:class:`BasicTh`. The model evolves a
topographic surface, :math:`\eta (x,y,t)`, with the following governing
equation:
.. math::
\frac{\partial \eta}{\partial t} = -(K_{q}\hat{Q}^{m}S^{n} - \omega_c)
+ D\nabla^2 \eta
where :math:`\hat{Q}` is the local stream discharge (the hat symbol
indicates that it is a random-in-time variable) and :math:`S` is the local
slope gradient. :math:`m` and :math:`n` are the discharge and slope
exponent, respectively, :math:`\omega_c` is the critical stream power
required for erosion to occur, :math:`K` is the erodibility by water, and
:math:`D` is the regolith transport parameter.
Refer to
`Barnhart et al. (2019) <https://doi.org/10.5194/gmd-12-1267-2019>`_
Table 5 for full list of parameter symbols, names, and dimensions.
The following at-node fields must be specified in the grid:
- ``topographic__elevation``
"""
_required_fields = ["topographic__elevation"]
[docs] def __init__(
self,
clock,
grid,
m_sp=0.5,
n_sp=1.0,
water_erodibility=0.0001,
regolith_transport_parameter=0.1,
water_erosion_rule__threshold=0.01,
infiltration_capacity=1.0,
**kwargs
):
"""
Parameters
----------
clock : terrainbento Clock instance
grid : landlab model grid instance
The grid must have all required fields.
m_sp : float, optional
Drainage area exponent (:math:`m`). Default is 0.5.
n_sp : float, optional
Slope exponent (:math:`n`). Default is 1.0.
water_erodibility : float, optional
Water erodibility (:math:`K`). Default is 0.0001.
water_erosion_rule__threshold : float, optional
Erosion rule threshold when no erosion has occured
(:math:`\omega_c`). Default is 0.01.
regolith_transport_parameter : float, optional
Regolith transport efficiency (:math:`D`). Default is 0.1.
infiltration_capacity: float, optional
Infiltration capacity (:math:`I_m`). Default is 1.0.
**kwargs :
Keyword arguments to pass to :py:class:`StochasticErosionModel`.
These arguments control the discharge :math:`\hat{Q}`.
Returns
-------
BasicStTh : model object
Examples
--------
This is a minimal example to demonstrate how to construct an instance
of model **BasicStTh**. For more detailed examples, including
steady-state test examples, see the terrainbento tutorials.
To begin, import the model class.
>>> from landlab import RasterModelGrid
>>> from landlab.values import random
>>> from terrainbento import Clock, BasicStTh
>>> clock = Clock(start=0, stop=100, step=1)
>>> grid = RasterModelGrid((5,5))
>>> _ = random(grid, "topographic__elevation")
Construct the model.
>>> model = BasicStTh(clock, grid)
Running the model with ``model.run()`` would create output, so here we
will just run it one step.
>>> model.run_one_step(1.)
>>> model.model_time
1.0
"""
# Call ErosionModel"s init
super().__init__(clock, grid, **kwargs)
# verify correct fields are present.
self._verify_fields(self._required_fields)
# Get Parameters:
self.m = m_sp
self.n = n_sp
self.K = water_erodibility
self.infilt = infiltration_capacity
if float(self.n) != 1.0:
raise ValueError("Model only supports n equals 1.")
# instantiate rain generator
self.instantiate_rain_generator()
# Run flow routing and lake filler
self.flow_accumulator.run_one_step()
# Instantiate a FastscapeEroder component
self.eroder = StreamPowerSmoothThresholdEroder(
self.grid,
K_sp=self.K,
m_sp=self.m,
n_sp=self.n,
threshold_sp=water_erosion_rule__threshold,
discharge_field="surface_water__discharge",
erode_flooded_nodes=self._erode_flooded_nodes,
)
# Instantiate a LinearDiffuser component
self.diffuser = LinearDiffuser(
self.grid, linear_diffusivity=regolith_transport_parameter
)
[docs] def run_one_step(self, step):
"""Advance model **BasicStTh** for one time-step of duration step.
The **run_one_step** method does the following:
1. Creates rain and runoff, then directs and accumulates flow.
2. Assesses the location, if any, of flooded nodes where erosion should
not occur.
3. Assesses if a :py:mod:`PrecipChanger` is an active boundary handler
and if so, uses it to modify the erodibility by water.
4. Calculates detachment-limited, threshold-modified erosion by water.
5. Calculates topographic change by linear diffusion.
6. Finalizes the step using the :py:mod:`ErosionModel` base class
function **finalize__run_one_step**. This function updates all
boundary handlers handlers by ``step`` and increments model time by
``step``.
Parameters
----------
step : float
Increment of time for which the model is run.
"""
# create and move water
self.create_and_move_water(step)
# Handle water erosion
self.handle_water_erosion(step)
# Do some soil creep
self.diffuser.run_one_step(step)
# Finalize the run_one_step_method
self.finalize__run_one_step(step)
[docs]def main(): # pragma: no cover
"""Executes model."""
import sys
try:
infile = sys.argv[1]
except IndexError:
print("Must include input file name on command line")
sys.exit(1)
em = BasicStTh.from_file(infile)
em.run()
if __name__ == "__main__":
main()
