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GP-GE-1Y8L4TAGeologyReady

Climate-Tectonic Controls on Drainage Divide Migration and Sediment Export

A completed landscape-evolution study testing how runoff and uplift gradients affect drainage-basin competition, local river capture, relief, soil storage, and sediment export.

Climate-Tectonic Controls on Drainage Divide Migration and Sediment Export project visual
GP-GE-1Y8L4TA · Geology
  • Python 3.14
  • Landlab 2.11.0
  • NumPy
  • Pandas
  • Matplotlib
  • Seaborn

Software compatibility

Landlab 2.11.0 and Python 3.14 only

The source, retained results, figures, tests, and documentation use Landlab 2.11.0 with the pinned Python 3.14 environment. Other Landlab or Python versions require a new verification run.

Project definition

Problem statement

Drainage divides are dynamic boundaries. Unequal uplift and runoff can change channel competition, trigger local capture, alter relief, and redistribute sediment even when one summary divide coordinate appears stable.

The geology problem is to isolate these coupled controls in a transparent synthetic landscape and retain enough spatial, temporal, and numerical evidence to distinguish process response from plotting artefacts.

Project objectives

  • Build a two-outlet synthetic landscape with soil, bedrock, channel incision, sediment transport, and hillslope diffusion.
  • Compare balanced, runoff-gradient, uplift-asymmetry, and compound-forcing scenarios over 100,000 years.
  • Measure basin area, outlet allegiance, capture events, relief, hypsometry, soil depth, and sediment export.
  • Test all nine combinations of three runoff contrasts and three uplift contrasts.
  • Check time-step convergence and retain reproducible tables, figures, tests, references, and documentation.

Project structure

Project components

01

Landscape model

Creates the deterministic terrain, opposing outlets, runoff field, uplift field, soil layer, and process components.

02

Scenario runner

Executes four primary scenarios with shared geometry, checkpoints, and reproducible parameters.

03

Capture analyser

Tracks core-node outlet allegiance, drainage-divide positions, basin areas, and local capture events.

04

Sediment analyser

Retains cumulative outlet export, soil depth, relief, hypsometry, profiles, and sediment budgets.

05

Verification layer

Runs the forcing matrix, convergence study, automated tests, dependency audit, document checks, and repository validation.

Methodology

Project workflow

  1. 01
    Define the landscape

    A validated JSON configuration declares grid geometry, process parameters, forcing scenarios, runtime, checkpoints, and random seed.

  2. 02
    Route flow

    Landlab resolves D8 drainage directions, accumulation, and outlet membership on the evolving surface.

  3. 03
    Evolve terrain

    Uplift, stream-power erosion, sediment transport, and linear diffusion advance the landscape through time.

  4. 04
    Measure response

    The workflow records divide, capture, basin, relief, soil, profile, and outlet-sediment evidence at fixed checkpoints.

  5. 05
    Compare and verify

    Primary scenarios, the full forcing matrix, and time-step cases are plotted, tested, audited, and retained.

Demonstration scenario

The compound-forcing case changes the final outlet allegiance of 10 core nodes while the resolved median divide coordinate remains unchanged. The retained event, basin, profile, and sediment evidence shows why a single divide coordinate is insufficient for diagnosing local reorganisation.

Engineering

Tools and method

Tools
The project uses Python 3.14, Landlab 2.11.0, NumPy, Pandas, Matplotlib, Seaborn for subject analysis, simulation, and results.
Terrain layer
Landlab raster grids store surface elevation, soil depth, drainage area, receiver relationships, and boundary conditions.
Process layer
Priority flood routing, SPACE erosion and deposition, uplift, and linear hillslope diffusion drive landscape change.
Experiment layer
Python executes four long scenarios, a three by three forcing matrix, and three numerical-resolution cases.
Evidence layer
Pandas, CSV, JSON, and PNG retain time series, node states, profiles, event records, comparisons, and figures.
Verification
Twenty-one automated tests, branch coverage, dependency audit, Docker execution, document audits, and repository validation verify the delivery.

Testing

Evaluation

Evaluation measures

  • Drainage-divide position and row-level migration
  • West and east basin areas and captured core nodes
  • Mean elevation, relief, and hypsometric integral
  • West, east, and total cumulative sediment export
  • Mean soil depth, maximum drainage area, and central profiles
  • Response across the nine forcing combinations
  • Relative differences across 125, 250, and 500-year steps

Project boundaries

  • The landscape is synthetic and is not calibrated to a named catchment.
  • Absolute erosion, capture, and sediment-export values depend on the declared geometry, grid, parameters, and process representation.
  • The experiment does not include lithological heterogeneity, landslides, groundwater, vegetation, glacial processes, or field-calibrated climate histories.
  • Application to a real basin requires field data, parameter calibration, uncertainty analysis, independent validation, and qualified geologists or geomorphologists.

Included

  1. 01Complete Python and Landlab source code
  2. 02Four completed 100,000-year landscape-evolution scenarios
  3. 03Nine-case runoff and uplift forcing experiment
  4. 04Three-case time-step convergence experiment
  5. 05Ten retained CSV evidence tables and eighteen generated figures
  6. 06Three attributed literature images
  7. 07Forty-five annotated references
  8. 08Twenty-one automated tests with 97.97 percent branch-aware coverage
  9. 09Complete project files, calculations, results, and analysis material in a private GitHub repository
  10. 1085-page project documentation in PDF and editable Word formats
  11. 113-page setup and usage guide in PDF and editable Word formats

Project record

No information is collected on this page.

Permanent project ID
GP-GE-1Y8L4TA
Catalogued
21 Aug 2026
Completed
28 Aug 2026
Verified
28 Aug 2026
Demonstration
Included in repository

Handover

After purchase

  1. 01
    Payment is confirmed

    The project is marked unavailable and cannot be purchased again.

  2. 02
    Repository access is granted

    The buyer's submitted GitHub account receives access to the private repository.

  3. 03
    The purchase record is delivered

    The certification sheet is prepared from the reviewed buyer details and sent privately by email.