Fig 1.
A schematic of our model illustrating the main variables and forcing conditions.
w represents the wave boundary conditions, ld the longshore drift, sl the sea-level, u the tectonic, f the flexural isostasy and r the rainfall patterns. The stratigraphic evolution and morphology are computed through time.
Fig 2.
Main components of pyBadlands workflow.
Fig 3.
Model space for implemented stream power-based incision laws.
It shows the dependence of river incision rate on sediment flux (adapted from Hobley et al. [7]).
Fig 4.
Illustration of the impact of detachment versus transport limited (tool & cover option 3) formulations on landscape dynamics.
Evolution of dissection of an uplifting landscape composed of a flat surfaces dotted with an isolated peak, after 5 and 9 Ma of dissection. The modeling shows how the abundant bedload shed by the isolated peak boosts incision along the receiving streams (tool effect).
Fig 5.
Erosion/deposition induced after 130 ka of hillslope diffusion using the linear and non-linear formulations.
Left: Linear diffusion produces convex upward slopes (κhl = κhn = 0.05). Right: non-linear approach tends to have convex to planar profiles as hillslope processes dominate when slopes approach or exceed the critical slope (Sc = 0.8) [33, 34].
Fig 6.
Example of cumulative wave-induced erosion/deposition during a transgression event in the southern portion of the Great Barrier Reef (simulated time: 14 ka).
Wave-induced shear stress and associated longshore sediment transport are evaluated every 50 years. Pink patches show location of produced coral reefs.
Fig 7.
Diagram of fuzzy logic process used to evaluate a specific coral assemblage growth rate.
Coral assemblage refers to a specific coral colony or community often derived from depth zonation.
Table 1.
Summary of hands-on examples provided with pyBadlands package.
Fig 8.
Example of stratal architecture resulting from oscillating sea level with a periodicity of 10 Ma.
(a) Stratal stacking patterns on a vertical cross-section crosswise to the continental margin. Solid black lines shown on each subplot are stratigraphic layers plotted at 0.5 Myr intervals. Different colours stand for different depositional environments that are defined based on water depth (c). (b) Wheeler diagram or chronostratigraphy chart. The black dots are shoreline positions through time. The coloured lines are stratigraphic surfaces identified based on stratal terminations, stacking trends, and shoreline trajectory (SB: sequence boundaries—TS: transgressive surfaces—MFS: maximum flooding surfaces). (c) Virtual cores P1 to P5 extracted at different positions across the shelf (see location in a). Solid lines connect condensed sections and unconformities produced at low to sea-level fall.
Fig 9.
Left: map shows the extend of the region of the GBR used in this example (source: Project 3DGBR—eAtlas.org.au). Right: background map shows the average rainfall annual distribution based on 30-year records (1961-1990) encompassing several ENSO events (7 El Niño—5 La Niña) (source: Bureau of Meteorology). White lines highlight precipitation 0.5 m/a contours. Red arrows define prevailing annual offshore wave directions scaled based on their annual activity. Wave heights (H) imposed for the considered 2 climatic scenarios from 14 to 5 ky and from 5 ky to present.
Fig 10.
Surface evolution and simulated erosion, deposition patterns.
Left: Model outputs for time steps 12 ky, 8 ky and present. Red color displays presence of coral reef at given time intervals. Right: cumulative erosion, deposition and reef evolution for the simulated 14 ky induced by the combination of fluvial and waves processes as well as reef growth.
Fig 11.
Cross sections through the model predicted stratigraphy showing time layers of mixed siliciclastic-carbonate accretion across Warden Reefs and Arlington Reefs (regional locations of these sections are presented in Fig 10).