Note

This page was generated from a jupyter notebook.

Synthetic landscape animation

Simulate the runout extent, sediment transport and topographic change caused by the runout of a rectangular landslide over a synthetic terrain using MassWastingRunout

In this tutorial, the user defines the rectangular geometry of a landslide, parameterizes MassWastingRunout (MWR) and chooses one of 6 synthetic terrains on which the runout of the landslide is modeled.

Model overview

• MWR models the downslope progression of mass wasting processes such as debris flows or dry debris avalanches.

• Mass continuity is central to model conceptualization; at any node, the incoming flux (q_I), erosion (E) and aggradation (A) determine outgoing flux (q_O) and ultimately the runout extent and how the landscape evolves.

• MWR uses a set of rules and algorithms to numerically represent the release of the mass wasting source material and erosion, deposition and vegetation/debris impacts on the runout process as illustrated below:

1. Release of the initial mass wasting source material nodes (represented by red cells); (b) How q_O at node n (n = 45) is distributed downslope after incoming material q_I (here equal to flux from node 51) has aggraded (A) or eroded (E) node n; (c) Mass continuity determines the change in regolith thickness/topographic elevation. For a full description of the above parameters, see Keck et al. (2024).

To begin, first import packages and components necessary to load MWR inputs, run MWR and visualize model results.

import matplotlib.animation as animation
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import cm

from landlab.components import FlowDirectorMFD
from landlab.components.mass_wasting_runout.mass_wasting_runout import MassWastingRunout
from landlab.io import esri_ascii

Next, define the mass wasting source area (landslide) geometry.

In this notebook, we define the geometry of the landslide as a rectangular prism. In later notebooks, we will use the geometry of a landslide body observed in the field.

ls_width = 3  # number of cells wide, must be odd number
ls_length = 5  # number of cells long
ls_h = 3  # thickness, m
soil_thickness = 2  # thickness of soil (regolith) covering synthetic terrain, m

Then, define key MWR parameters S_c, q_c and k.

In MWR, S_c is a critical slope constraint. For some flows, it may be possible to approximate S_c from the surface slope of observed deposits. The parameter q_c is the threshold flux for deposition, that conceptually represents the flow depth below which flow resistance is large enough to cease the forward momentum of the flow, whether in the form of frictional resistance along the base of the flow or debris and vegetation in the path of the flow. Parameter k scales the erosion rate. We also specify the typical particle diameter found in the regolith because in this example, we will use an erosion rule that varies as a function of the flow grain size.

q_c = 0.2  # threshold flux, m
S_c = 0.03  # critical slope
k = 0.01  # erosion coefficient
Dp = 0.2  # particle diameter, m

Now, pick which terrain the landslide will runout on.

The planimetric curvature of each terrain ranges from divergent to steeply convergent. In profile, the terrains include concave-up, convex-up, planar and broken. Terrains are shaded with the DEM of Difference (DoD) of previous model results using ls_width = 3, ls_length = 5, ls_h = 3, soil_thickness = 2, qs_max = ls_h, q_c = .25, S_c = 0.03, k = 0.005, and Dp = 0.2. Red indicates a positive change in the elevation of the terrain (aggradation) and blue indicates a negative change (erosion).

terrain_id = "E"