CSDMS 2024: Coastlines, Critical Zones and Cascading Hazards: Modeling Dynamic Interfaces from Deep Time to Human Time

Parameterizing human dynamics in geomorphic models: learning from coastal barrier evolution models

Katherine Anarde

North Carolina State University, United States
Ian Reeves USGS United States

Exploratory models that simulate landscape change incorporate only the most essential processes that are hypothesized to control a behavior of interest. These “rule-based” models have been used successfully to examine behaviors in natural landscapes over large spatial (many kms) and temporal scales (decades to millennia). In many geomorphic systems, the dynamics of developed landscapes differ significantly from natural landscapes. For example, humans can alter the physical landscape through the introduction of hard infrastructure and removal of vegetation. Humans can also modify the internal and external forces that naturally change landscapes, including flows of water, wind, and sediment as well as climatic factors. As with natural processes, in exploratory models human behavior must be parameterized. However, the level of detail to which human behavior can be reduced while still accurately reproducing feedbacks across the coupled human-natural landscape is a complex, user-based decision. In this clinic, we will work in small groups and through a Jupyter Notebook to parameterize a new human behavior within a modular coastal barrier evolution model (Barrier3D, within the CASCADE modeling framework). The clinic will incorporate discussions and prompts about how to broadly identify important model “ingredients” and reduce model complexity, and will therefore be generalizable to other geomorphic landscapes.

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Of interest for:
  • Marine Working Group
  • Terrestrial Working Group
  • Coastal Working Group
  • Cyberinformatics and Numerics Working Group
  • Hydrology Focus Research Group
  • Chesapeake Focus Research Group
  • Critical Zone Focus Research Group
  • Human Dimensions Focus Research Group
  • Geodynamics Focus Research Group
  • Ecosystem Dynamics Focus Research Group
  • River Network Modeling Initiative