Source code for landlab.components.soil_moisture.infiltrate_soil_green_ampt

#!/usr/bin/env python

import numpy as np

from landlab import Component

[docs] class SoilInfiltrationGreenAmpt(Component): """Infiltrate surface water into a soil following the Green-Ampt method. This component calculates the infiltation of surface water into the soil, using the Green-Ampt method. The component tracks the depth of infiltrated water over time, in the field soil_water_infiltration__depth. It also modifies the depth of surface water (surface_water__depth) as surface water progressively infiltrates into the soil below. Examples -------- >>> from landlab import RasterModelGrid >>> from landlab.components import SoilInfiltrationGreenAmpt >>> mg = RasterModelGrid((4, 3), xy_spacing=10.0) >>> hydraulic_conductivity = mg.ones("node") * 1.0e-6 >>> hydraulic_conductivity.reshape((4, 3))[0:2, :] *= 10000.0 >>> h = mg.add_ones("surface_water__depth", at="node") >>> h *= 0.01 >>> d = mg.add_ones("soil_water_infiltration__depth", at="node", dtype=float) >>> d *= 0.2 >>> SI = SoilInfiltrationGreenAmpt( ... mg, hydraulic_conductivity=hydraulic_conductivity ... ) >>> for i in range(10): # 100s total ... SI.run_one_step(10.0) ... >>> mg.at_node["surface_water__depth"] array([1.00000000e-08, 1.00000000e-08, 1.00000000e-08, 1.00000000e-08, 1.00000000e-08, 1.00000000e-08, 9.88530416e-03, 9.88530416e-03, 9.88530416e-03, 9.88530416e-03, 9.88530416e-03, 9.88530416e-03]) >>> mg.at_node["soil_water_infiltration__depth"] array([0.20999999, 0.20999999, 0.20999999, 0.20999999, 0.20999999, 0.20999999, 0.2001147 , 0.2001147 , 0.2001147 , 0.2001147 , 0.2001147 , 0.2001147 ]) Notes ----- This code is based on an overland flow model by Francis Rengers and colleagues, after Julien et al., 1995. The infiltration scheme follows the Green and Ampt equation. It was implemented in Landlab by DEJH, March 2016. **Where to learn more** A description of the Green-Ampt infiltration equation can be found in many hydrology texts, as well as online resources. The original theory was published by Green and Ampt (1911). References ---------- **Required Software Citation(s) Specific to this Component** Rengers, F. K., McGuire, L. A., Kean, J. W., Staley, D. M., and Hobley, D.: Model simulations of flood and debris flow timing in steep catchments after wildfire, Water Resour. Res., 52, 6041–6061, doi:10.1002/2015WR018176, 2016. **Additional References** Julien, P. Y., Saghafian, B., and Ogden, F. L.: Raster-based hydrologic modeling of spatially-varied surface runoff, J. Am. Water Resour. As., 31, 523–536, doi:10.1111/j.17521688.1995.tb04039.x, 1995. Green, W. H., & Ampt, G. A. (1911). Studies on Soil Phyics. The Journal of Agricultural Science, 4(1), 1-24. """ _name = "SoilInfiltrationGreenAmpt" _unit_agnostic = False _cite_as = """ @article{rengers2016model, author = {Rengers, F K and McGuire, L A and Kean, J W and Staley, D M and Hobley, D E J}, title = {{Model simulations of flood and debris flow timing in steep catchments after wildfire}}, doi = {10.1002/2015wr018176}, pages = {6041 -- 6061}, number = {8}, volume = {52}, journal = {Water Resources Research}, year = {2016}, } """ _info = { "soil_water_infiltration__depth": { "dtype": float, "intent": "inout", "optional": False, "units": "m", "mapping": "node", "doc": ( "Water column height above the surface previously absorbed " "into the soil. Note that this is NOT the actual depth of " "the wetted front, which also depends on the porosity." ), }, "surface_water__depth": { "dtype": float, "intent": "inout", "optional": False, "units": "m", "mapping": "node", "doc": "Depth of water on the surface", }, } # This follows mean values from Rawls et al., 1992; lambda then h_b SOIL_PROPS = { "sand": (0.694, 0.0726), "loamy sand": (0.553, 0.0869), "sandy loam": (0.378, 0.1466), "loam": (0.252, 0.1115), "silt loam": (0.234, 0.2076), "sandy clay loam": (0.319, 0.2808), "clay loam": (0.242, 0.2589), "silty clay loam": (0.177, 0.3256), "sandy clay": (0.223, 0.2917), "silty clay": (0.150, 0.3419), "clay": (0.165, 0.3730), }
[docs] def __init__( self, grid, hydraulic_conductivity=0.005, soil_bulk_density=1590.0, rock_density=2650.0, initial_soil_moisture_content=0.15, soil_type="sandy loam", volume_fraction_coarse_fragments=0.2, coarse_sed_flag=False, surface_water_minimum_depth=1.0e-8, soil_pore_size_distribution_index=None, soil_bubbling_pressure=None, wetting_front_capillary_pressure_head=None, ): """ Parameters ---------- grid : RasterModelGrid A grid. hydraulic_conductivity : float, array, or field name (m/s) The soil effective hydraulic conductivity. soil_bulk_density : float (kg/m**3) The dry bulk density of the soil. rock_density : float (kg/m**3) The density of the soil constituent material (i.e., lacking porosity). initial_soil_moisture_content : float (m**3/m**3, 0. to 1.) The fraction of the initial pore space filled with water. soil_type : str A soil type to automatically set soil_pore_size_distribution_index and soil_bubbling_pressure, using mean values from Rawls et al., 1992. The following options are supported: 'sand', loamy sand', 'sandy loam', 'loam', 'silt loam', 'sandy clay loam', 'clay loam', 'silty clay loam', 'sandy clay', 'silty clay', or 'clay'. volume_fraction_coarse_fragments : float (m**3/m**3, 0. to 1.) The fraction of the soil made up of rocky fragments with very little porosity, with diameter > 2 mm. coarse_sed_flag : boolean, optional If this flag is set to true, the fraction of coarse material in the soil column with be used as a correction for phi, the porosity factor. surface_water_minimum_depth : float (m), optional A minimum water depth to stabilize the solutions for surface flood modelling. Leave as the default in most normal use cases. soil_pore_size_distribution_index : float, optional An index describing the distribution of pore sizes in the soil, and controlling effective hydraulic conductivity at varying water contents, following Brooks and Corey (1964). Can be set by soil_type. Typically denoted "lambda". soil_bubbling_pressure : float (m), optional The bubbling capillary pressure of the soil, controlling effective hydraulic conductivity at varying water contents, following Brooks and Corey (1964). Can be set by soil_type. Typically denoted "h_b". wetting_front_capillary_pressure_head : float (m), optional The effective head at the wetting front in the soil driven by capillary pressure in the soil pores. If not set, will be calculated by the component from the pore size distribution and bubbling pressure, following Brooks and Corey. """ super().__init__(grid) self._min_water = surface_water_minimum_depth self._hydraulic_conductivity = hydraulic_conductivity if not coarse_sed_flag: volume_fraction_coarse_fragments = 0.0 self._moisture_deficit = self.calc_moisture_deficit( soil_bulk_density=soil_bulk_density, rock_density=rock_density, volume_fraction_coarse_fragments=volume_fraction_coarse_fragments, soil_moisture_content=initial_soil_moisture_content, ) if wetting_front_capillary_pressure_head is None: self._capillary_pressure = self.calc_soil_pressure( soil_type=soil_type, soil_pore_size_distribution_index=soil_pore_size_distribution_index, soil_bubbling_pressure=soil_bubbling_pressure, ) else: self._capillary_pressure = wetting_front_capillary_pressure_head
[docs] @staticmethod def calc_soil_pressure( soil_type=None, soil_pore_size_distribution_index=1.0, soil_bubbling_pressure=0.0, ): """Calculate capillary pressure in a soil type. Parameters ---------- soil_type : str, optional The name of a soil type. soil_pore_size_distribution_index : float Pore-size distribution index [-]. soil_bubbling_pressure : float Bubbling pressure [m]. """ if soil_type is None: soil_props = (soil_pore_size_distribution_index, soil_bubbling_pressure) else: try: soil_props = SoilInfiltrationGreenAmpt.SOIL_PROPS[soil_type] except KeyError as exc: raise ValueError(f"{soil_type}: unknown soil type") from exc return SoilInfiltrationGreenAmpt.calc_pressure_head(*soil_props)
[docs] @staticmethod def calc_pressure_head(lam, h_b): """Calculate pressure head. Pressure head is set using *lambda* and *h_b*, using an equation after Brooks-Corey (1964), following Rawls et al., 1992. Parameters ---------- lam : float, optional Pore-size distribution index. Exponent that describes the distribution of pore sizes in the soil, and controls effective hydraulic conductivity at varying water contents, following Brooks and Corey (1964) [-]. h_b : float (m), optional Bubbling pressure. Capillary pressure of the soil, controlling effective hydraulic conductivity at varying water contents, following Brooks and Corey (1964) [m] """ return (2.0 + 3.0 * lam) / (1.0 + 3.0 * lam) * h_b * 0.5
[docs] @staticmethod def calc_moisture_deficit( soil_bulk_density=1590.0, rock_density=2650.0, volume_fraction_coarse_fragments=0.0, soil_moisture_content=0.0, ): """Calculate the moisture deficit in a soil. Parameters ---------- soil_bulk_density : float or array of float Bulk density of the soil [kg / m3]. rock_density : float or array of float Density of rock [kg / m3]. volume_fraction_coarse_fragments : float or array of float Volume fraction of sediment made up of coarse grains [-]. soil_moisture_content : float or array of float Fraction of soil filled with water [-]. Returns ------- float or array of float Moisture deficit. """ if np.any(soil_bulk_density <= 0.0): raise ValueError("non-positive soil bulk density") if np.any(rock_density < soil_bulk_density): raise ValueError("soil bulk density greater than rock density") if np.any(volume_fraction_coarse_fragments < 0.0): raise ValueError("negative volume fraction of coarse grains") if np.any(volume_fraction_coarse_fragments > 1.0): raise ValueError("volume fraction of coarse grains") soil_porosity = 1.0 - np.true_divide(soil_bulk_density, rock_density) soil_porosity *= 1.0 - volume_fraction_coarse_fragments if np.any(soil_moisture_content > soil_porosity): raise ValueError("soil moisture greater than porosity") return soil_porosity - soil_moisture_content
@property def min_water(self): """Minimum surface water depth.""" return self._min_water @min_water.setter def min_water(self, new_value): if np.any(new_value <= 0.0): raise ValueError("minimum water depth must be positive") self._min_water = new_value @property def hydraulic_conductivity(self): """Hydraulic conductivity of soil.""" return self._hydraulic_conductivity @hydraulic_conductivity.setter def hydraulic_conductivity(self, new_value): if isinstance(new_value, str): new_value = self._grid.at_node[new_value] if np.any(new_value < 0.0): raise ValueError("hydraulic conductivity must be positive") self._hydraulic_conductivity = new_value @property def moisture_deficit(self): """Moisture deficit of soil.""" return self._moisture_deficit @moisture_deficit.setter def moisture_deficit(self, new_value): if np.any(new_value < 0.0): raise ValueError("negative moisture deficit") self._moisture_deficit = new_value @property def capillary_pressure(self): """Capillary pressure of soil.""" return self._capillary_pressure @capillary_pressure.setter def capillary_pressure(self, new_value): if np.any(new_value < 0.0): raise ValueError("negative capillary pressure") self._capillary_pressure = new_value
[docs] def run_one_step(self, dt): """Update fields with current hydrologic conditions. Parameters ---------- dt : float (s) The imposed timestep for the model. """ water_depth = self._grid.at_node["surface_water__depth"] infiltration_depth = self._grid.at_node["soil_water_infiltration__depth"] assert np.all(infiltration_depth >= 0.0) wettingfront_depth = infiltration_depth / self._moisture_deficit potential_infilt = ( dt * self._hydraulic_conductivity * ( (wettingfront_depth + self._capillary_pressure + water_depth) / wettingfront_depth ) ) np.clip(potential_infilt, 0.0, None, out=potential_infilt) available_water = water_depth - self._min_water np.clip(available_water, 0.0, None, out=available_water) actual_infiltration = np.choose( potential_infilt > available_water, (potential_infilt, available_water) ) water_depth -= actual_infiltration infiltration_depth += actual_infiltration