Source code for landlab.components.weathering.exponential_weathering_integrated

#!/usr/bin/env python
"""Created on Fri Apr  8 08:32:48 2016.

@author: RCGlade
@author: dylanward
Integrated version created by D. Ward on Tue Oct 27 2020

import numpy as np

from landlab import Component

[docs]class ExponentialWeathererIntegrated(Component): """ This component implements exponential weathering of bedrock on hillslopes. Uses exponential soil production function in the style of Ahnert (1976). Consider that ``w_0`` is the maximum soil production rate and that ``d_start`` is the characteristic soil production depth. The soil production rate ``w`` is given as a function of the soil depth ``d``:: w = w_0 exp(-d / d_star) The :class:`~.ExponentialWeathererIntegrated` uses the analytical solution for the amount of soil produced by an exponential weathering function over a timestep dt, and returns both the thickness of bedrock weathered and the thickness of soil produced. The solution accounts for the reduction in rate over the timestep due to the increasing depth. This enables accuracy over arbitrarily large timesteps, and better compatiblity with the `run_one_step()` interface. Compared to :class:`~.ExponentialWeatherer`, upon which it is based... - This maintains the field I/O behavior of the original, but adds new return fields for the weathered thickness and soil produced thickness. - Density adjustments are needed inside the integral and the density ratio is intialized on instantiation. The default value of 1.0 assumes no change in density. - Returns both weathered depth of bedrock and produced depth of soil over the timestep. - The primary ``soil__depth`` field that is input is NOT updated by the component. This is left as an exercise for the model driver, as different applications may want to integrate soil depth and weathering in different sequences among other processes. - SHOULD maintain drop-in compatiblity with the plain :class:`~.ExponentialWeatherer`, just import and instantiate this one instead and existing code should work with no side effects other than the creation of the two additional (zeros) output fields. Examples -------- >>> import numpy as np >>> from landlab import RasterModelGrid >>> from landlab.components import ExponentialWeathererIntegrated >>> mg = RasterModelGrid((5, 5)) >>> soilz = mg.add_zeros("soil__depth", at="node") >>> soilrate = mg.add_ones("soil_production__rate", at="node") >>> expw = ExponentialWeathererIntegrated(mg) >>> dt = 1000 >>> expw.run_one_step(dt) >>> np.allclose(mg.at_node['soil_production__rate'][mg.core_nodes], 1.) True >>> np.allclose( ... mg.at_node['soil_production__dt_produced_depth'][mg.core_nodes], 6.9088 ... ) 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. **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 = "ExponentialWeathererIntegrated" _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", }, "soil_production__dt_produced_depth": { "dtype": float, "intent": "out", "optional": False, "units": "m", "mapping": "node", "doc": "thickness of soil produced at nodes over time dt", }, "soil_production__dt_weathered_depth": { "dtype": float, "intent": "out", "optional": False, "units": "m", "mapping": "node", "doc": "thickness of bedrock weathered at nodes over time dt", }, }
[docs] def __init__( self, grid, soil_production__maximum_rate=1.0, soil_production__decay_depth=1.0, soil_production__expansion_factor=1.0, ): """ Parameters ---------- grid: ModelGrid Landlab ModelGrid object soil_production__maximum_rate : float Maximum weathering rate for bare bedrock soil_production__decay_depth : float Characteristic weathering depth soil_production__expansion_factor : float Expansion ratio of regolith (from relative densities of rock and soil) """ super().__init__(grid) # Store grid and parameters self._wstar = soil_production__decay_depth self._w0 = soil_production__maximum_rate self._fexp = soil_production__expansion_factor # Create fields: # soil depth self._depth = grid.at_node["soil__depth"] # weathering rate if "soil_production__rate" not in grid.at_node: grid.add_zeros("soil_production__rate", at="node") self._soil_prod_rate = grid.at_node["soil_production__rate"] # soil produced total over dt if "soil_production__dt_produced_depth" not in grid.at_node: grid.add_zeros("soil_production__dt_produced_depth", at="node") self._soil_prod_total = grid.at_node["soil_production__dt_produced_depth"] # bedrock weathering total over dt if "soil_production__dt_weathered_depth" not in grid.at_node: grid.add_zeros("soil_production__dt_weathered_depth", at="node") self._rock_weathered_total = grid.at_node["soil_production__dt_weathered_depth"]
[docs] def calc_soil_prod_rate(self): """Calculate soil production rate.""" # apply exponential function self._soil_prod_rate[self._grid.core_nodes] = self._w0 * np.exp( -self._depth[self._grid.core_nodes] / self._wstar )
def _calc_dt_production_total(self, dt): """Calculate integrated production over 1 timestep dt""" # analytical solution self._soil_prod_total[self._grid.core_nodes] = self._wstar * np.log( ( self._fexp * self._soil_prod_rate[self._grid.core_nodes] * dt / self._wstar ) + 1 ) # and back-convert to find rock thickness converted over the timestep: self._rock_weathered_total[self._grid.core_nodes] = ( self._soil_prod_total[self._grid.core_nodes] / self._fexp )
[docs] def run_one_step(self, dt=0): """ Parameters ---------- dt: float Used only for compatibility with standard run_one_step. If dt is not provided, the default of zero maintains backward compatibility """ self.calc_soil_prod_rate() self._calc_dt_production_total(dt)
@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 new_val <= 0: raise ValueError("Maximum weathering rate must be positive.") self._w0 = new_val