Presenters-0553

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CSDMS 2021 Webinars


ESPIn Student Project Presentations


Registration link: https://cuboulder.zoom.us/meeting/register/tJApfu2tqT4oHNT3WgfR4GCTr9dAWKkbHeKf

- Student presentations

ESPIn EKT Team, United States
csdms@colorado.edu


Abstract
11:00AM Introductions


11:05AM Project Team 1: "Simulating Shoreline Change Using Coupled CoastSat and Coastline Evolution Model (CEM)", Ahmed Elghandour, TU Delft, Benton Franklin, UNC, Conner Lester, Duke U, Megan Gillen, MIT/WHOI, Meredith Leung, Oregon State U & Samuel Zapp, LSU. Sandy shorelines are areas of dynamic geomorphic change, evolving on timescales ranging from hours to centuries. As part of the CSDMS ESPIn workshop, this educational lab was designed to allow users to observe firsthand the long-term change of a sandy coast of their choosing and explore the processes driving that change. The CEM was developed by Ashton et al. (2001) as an exploratory model that uses wave climate characteristics to model the evolution of an idealized coastline. In this educational lab, we couple CoastSat (a python tool that extracts shoreline geometry from satellite imagery (Vos et al., 2019)) to the CEM by initializing the model with observed shorelines from anywhere in the world. The CEM is then further driven by an average wave climate derived from local buoy data. This allows users to visualize the evolution of any sandy beach in the world through time. Through an introductory-level coding exercise, users will learn how to extract complex datasets, run a geomorphic model, and explore the impact of different wave climates on a beach they care about.


11:15AM Project Team 2: "Including wildfires in a landscape evolution model", Kevin Pierce, UBC, Laurent Roberge, Tulane U Nishani Moragoda, U Alabama. Wildfires modify sediment inputs to streams by removing vegetation and encouraging overland flow. Unfortunately our ability to calculate sediment delivery from wildfires remains limited. Here, we present a stochastic wildfire component we recently developed for Landlab. This work provides a new computational method to relate stream sediment yields to the frequency and magnitude of wildfires.

11:25AM Project Team 3: "Landscape-Scale Modeling across a variable-slip fault ", Emery Anderson-Merritt, U Mass, Tamara Aranguiz, UW, Katrina Gelwick, ETH Zurich, Francesco Pavano, Lehigh U, & Josh Wolpert, U Toronto. The accommodation of deformation along a strike-slip fault can result in oblique kinematics featuring along-strike gradients in horizontal and vertical components of movement. While strike-slip fault models often simplify factors such as channel sedimentation, erosion processes and channel geometry, complex rock uplift fields related to oblique faulting may significantly impact the dynamics of a drainage system. With the objective of representing these along-strike kinematic variations commonly observed in strike-slip fault settings, we modify an existing Landlab component for lateral faulting (Reitmann et al., 2019) to incorporate spatially variable rock uplift. Our simulations demonstrate landscape evolution in an oblique faulting setting, highlighting the complicated response of a landscape’s drainage network and other geomarkers.

11:35AM Project Team 4: "Paleoclimate and Elevation Data Used to Implement the Frost Cracking Window Concept”, Risa Madoff, U North Dakota, Jacob Hirschberg, Swiss Federal Research Inst, Allie Balter LDEO/Columbia U. Frost cracking is a key weathering process in cold environments (e.g., Hales & Roering). Concepts from previous work on frost cracking (Anderson, 1998) provide foundations for understanding regional controls on landscape evolution. Recent research applying transient climate records and the frost-cracking model to estimate weathering rates (Marshall et al., 2021) represent ways that computational approaches are being adopted in the community. To bring a frost-cracking model into the CSDMS framework, we combined elevation-scaled PMIP6 paleoclimate data with a soil thermal profile model extant in the CSDMS repository (Tucker, 2020) to estimate frost-cracking intensity at a landscape scale. Our frost-cracking model is hosted in an EKT Jupyter notebook for instructional and exploratory applications of the thermal diffusion equation and the relationship between temperature and landscape development. In the future, our model could be implemented to compare modeled frost-cracking intensities with contemporary geomorphology in regions with differing climate histories.

11:45AM Project Team 5: "Make storms, make erosion: How do storm intensity, duration, and frequency influence river channel incision.", Angel Monsalve, U Idaho, Sam Anderson, Tulane U, Safiya Alpheus, Penn State U, Muriel Bruckner, U Exeter, Mariel Nelson, UT, Austin, Grace Guryan, UT, Austin. Erosion in the river bed is usually associated with a representative scale of stream power or shear stress of a given flow discharge. However, on a catchment scale, assuming a constant, steady-state flow of water in channels may not be adequate to represent the erosion process because of the temporal and spatial variability in rainfall. We coupled three different landLab components (OveralndFlow, DetachmentLimitedErosion, and SpatialPrecipitationDistribution) to create a more realistic representation of the topography evolution at a basin-scale and analyze the influence of storm intensity, duration, and frequency on channel incision.

11:55AM Project Team 6: "Simulation of sediment pulses in Landlab NetworkSedimentTransporter (NST) component", Se Jong Cho, USGS, Muneer Ahammad, Virginia Tech, Marius Huber, U de Lorraine, Mel Guirro, Durham U. We synthetically introduce sediment pulses to simulate erosive conditions, which may be caused by fire or landslide occurrences in the landscape, and sediment yield across river network using the Landlab NetworkSedimentTransporter (NST) component. The goal of the project is to couple existing landlab models with external drivers of sediment sources and other input conditions that drive sediment transport.

12:05-12:15PM Team 7: "Simulating Craters on Planetary Surfaces", Emily Bamber, UT Austin, Gaia Stucky de Quay, Harvard

Impact cratering has been and still is the main geomorphic process on many planetary bodies, and is therefore key to understanding the evolution of planetary surfaces and their habitability. There are existing numerical models of planetary surface evolution that include cratering, but they are written in Fortran. As part of the CSDMS ESPIn 2021 summer workshop, we used the concepts for simulating crater shape and frequency on the surface from Howard (2007), and wrote a python code to simulate cratering, specifically on Mars. This code is freely available on GitHub, and currently utilises the LandLab model grid, which means our model integrates easily with the numerous landscape evolution modules that already exist as part of LandLab. An educational lab detailing the approach to simulating craters has also been produced and is available on the CSDMS website.

Please acknowledge the original contributors when you are using this material. If there are any copyright issues, please let us know (CSDMSweb@colorado.edu) and we will respond as soon as possible.

Of interest for:
  • Terrestrial Working Group
  • Coastal Working Group
  • Marine Working Group
  • Education and Knowledge Transfer (EKT) Working Group
  • Cyberinformatics and Numerics Working Group
  • Hydrology Focus Research Group
  • Carbonates and Biogenics Focus Research Group"Carbonates and Biogenics Focus Research Group" is not in the list (Terrestrial Working Group, Coastal Working Group, Marine Working Group, Education and Knowledge Transfer (EKT) 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, ...) of allowed values for the "Working group member" property.
  • Chesapeake Focus Research Group
  • Critical Zone Focus Research Group
  • Human Dimensions Focus Research Group
  • Geodynamics Focus Research Group
  • Ecosystem Dynamics Focus Research Group
  • Coastal Vulnerability Initiative
  • Continental Margin Initiative
  • Artificial Intelligence & Machine Learning Initiative
  • Modeling Platform Interoperability Initiative
  • River Network Modeling Initiative