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CSDMS 2022: Environmental Extremes and Earthscape Evolution (E4)


CSDMS 2022 annual meeting will hopefully be an in-person meeting and we'll do our best to make it an informative and enjoyable experience for all participants. A final decision on the meeting format (onsite or virtual) will be made by the opening of registration. Registration & abstract submissions will open mid to late January and accepted until 15 April 2022.


This year’s meeting will be broad in scope, showcasing modeling-oriented projects that range from fundamental research in evolution of the landscape and seascape to more specific experimental or applied work involving the impact of environmental extremes on the Earthscape. Were environmental extremes are widely defined to capture the morphodynamic impact of for example wildfires, hydrologic extremes, tsunamis, storm surges, or hurricanes, on the Earthscape.


The agenda will be posted closer to the meeting date.

Keynote presentations

Andrew Bell
Boston University
Modeling big unknowns in climate adaptation research – an example from mobility in coastal Bangladesh I will discuss an application of the Migration, Intensification, and Diversification as Adaptive Strategies (MIDAS) agent-based modeling framework to modeling labor migration across Bangladesh under the stressor of sea-level rise (SLR). With this example, I hope to highlight some hard-to-resolve challenges in representing adaptive decision-making under as-yet unexperienced stressors in models. Drawing together what is more and what is less known in projections for future adaptation, I will discuss strategies for ‘responsible’ presentation and dissemination of model findings.
Georgie Bennett
University of Exeter
Modeling Climate Change Impacts on Mountain Basin Sediment Transfer Sediment production and transfer processes shape river basins and networks and are driven by variability in precipitation, runoff and temperature. Changes in these hydrological and geomorphological processes are especially difficult to predict in temperature-sensitive environments such as the European Alps. We used a model chain to quantify possible impacts of climate change on sediment transfer and hazard in a debris flow-prone catchment in the Swiss Alps (Illgraben). We combined a stochastic weather generator1 with downscaled and bias-corrected climate change projections2 to generate climate simulations. These climate simulations then feed the hillslope-channel sediment cascade model, SedCas3, which is calibrated against observed debris-flow magnitudes estimated from force plate measurements4, to make predictions of sediment transfer and debris flow hazard in the Illgraben over the 21st century5. The results demonstrate the complex interplay between hydrology, sediment production and elevation in alpine catchment response to climate change. The hydrological potential to transport sediment and generate debris flows will increase, driven by increases in precipitation and air temperature. Indeed, if sediment supply to the channel by landslides were unlimited, this would result in an increase in future sediment yield of 48% by the end of the century. However, sediment transfer is also a function of sediment supply by landslides at the head of the catchment, driven by highly temperature sensitive freeze-thaw processes6. At the elevation of the Illgraben (<2000 m), freeze-thaw processes and thus sediment supply will decrease in a warming climate resulting in a decrease in sediment yield of 48% by the end of the century. This result and the competition between hydrological debris flow triggering potential and sediment supply is highly elevation dependent. As we increase mean catchment elevation, sediment production increases due to decreased snow cover and increased exposure of bedrock to freeze-thaw weathering, with implications for the application of findings to other catchments. Although uncertainties in our results are large, we show that these can mostly be attributed to irreducible internal climate variability. Our findings have important implications for the assessment of natural hazards and risks in mountain environments.REFERENCES1 Fatichi et al., 2011: Simulation of future climate scenarios with a weather generator2 National Centre for Climate Services, 2018: CH2018 - Climate Scenarios for Switzerland3 Bennett et al., 2014: A probabilistic sediment cascade model of sediment transfer in the Illgraben4 McArdell et al., 2007: Field observations of basal forces and fluid pressure in a debris flow5Hirshberg et al., 2021: Climate change impacts on sediment yield and debris flow activity6 Bennett et al., 2013: Patterns and controls of sediment production, transfer and yield in the Illgraben
Didier Granjeon
Exploring impact of climate changes on the stratigraphy of sedimentary systems using 3D stratigraphic forward model Numerical stratigraphic modelling of the impact of paleoclimate changes on earthscape evolution and sedimentary basin stratigraphy is of great value to better understand and predict the impact of global warming and increasingly frequent extreme events on the environment. To illustrate the contribution of stratigraphic modelling, we propose a modular model, ArcaDES (a.k.a. Dionisos), able to simulate geological processes in 3D on large scales of space and times (tens to hundreds of kilometres, and thousands to tens of millions of years). </br></br>ArcaDES is a 3D software written in C++ and implemented within the Arcane object-oriented high-performance computing platform co-developed by the CEA and IFPEN. This modular code includes three main components to handle hydrology, accommodation space and sediment transport. Taking into account precipitation, evaporation and soil infiltration capacity, the first component calculates steady-state runoff, surface and ground water flows, and water table elevation. The second component considers tectonic subsidence and uplift, flexure, sea level variations and sediment compaction to define the accommodation space. The third component deals with time-averaged physical laws describing erosion, transport by fluvial and marine currents, and deposition of sediments from fluvial to deep-marine systems to calculate sediment distribution and stratigraphic architecture. </br></br>This stratigraphic forward model is applied to two case studies: the Congo basin and the Alboran sea, to illustrate the impact of the last Holocene glaciations on the deep-sea fan of the Congo and the contouritic systems in the Alboran Sea.
Venkataraman Lakshmi
University of Virginia
Global Hydrological Water Cycle Extremes The variability of the water cycle causes extremes such as droughts and floods and these have an impact on society. In the past two decades with the advent of improved satellite sensors, modeling and in-situ observations, quantification of these extremes has become possible. This talk will be based on characterization of floods and droughts in global continental river basins that can be used for monitoring and lead to prediction of spatial distribution and temporal variability.
Lauren Lowman
Wake Forest University
Modeling Eco-hydrologic Processes Across Scales in Montane Cloud Forests Montane Cloud Forests (MCFs) are globally relevant ecological zones that spend the majority of their growing season in cloud and fog. Prior eco-physiological studies have demonstrated that MCFs are incredibly efficient at assimilating CO2 during photosynthesis. This increased efficiency is attributed to how plants in these ecosystems operate within their unique microclimates. Specifically, MCF trees maintain high photosynthesis rates under fog and low cloud conditions. While this has been observed and quantified in lab and field experiments, current sub-models of plant-atmosphere interactions within Earth systems models (ESMs) cannot recreate enhanced levels of gas exchange measured in ecophysiology studies. This lack of understanding leads to high uncertainty in ESM estimates of evapotranspiration and carbon assimilation rates for MCF ecosystems. It is critical to improve our estimates of MCF hydrologic and photosynthetic processes as these ecosystems are vulnerable to drought and microclimatic conditions are likely to be altered by climate change. This talk will explore the gaps in our process-based understanding of water, energy, and carbon budgets for MCFs, how these gaps lead to uncertainties in ESMs at different spatial and temporal scales, and how we can address these gaps in future work.
Luke McGuire
University of Arizona
Modeling the transient effects of fire on runoff and erosion: Implications for debris-flow hazards Fire temporarily alters soil and vegetation properties, driving increases in runoff and erosion that can dramatically increase the likelihood of debris flows. In the immediate aftermath of fire, debris flows most often initiate when surface water runoff rapidly erodes sediment on steep slopes. Due to the complex interactions between runoff generation, sediment transport, and post-fire debris-flow initiation and growth, models that couple these processes can provide valuable insights into the ways in which topography, burn severity, and post-fire recovery influence debris-flow activity. Here, we describe such a model as well as attempts to parameterize temporal changes in model parameters throughout the post-fire recovery process. Simulations of watershed-scale response to individual rainstorms in several southern California burned areas suggest substantial reductions in debris-flow likelihood and volume within the first 1-2 years following fire. Results highlight the importance of considering local rainfall characteristics and sediment supply when using process-based numerical models to assess debris-flow potential. More generally, results provide a methodology for estimating the intensity and duration of rainfall associated with the initiation of runoff-generated debris flows as well as insights into the persistence of debris-flow hazards following fire.
Andrew Moodie
University of Texas
A Flexible Delta Model to Assess Land Building Potential of Sediment Diversions under Various External Forcings Sediment diversions costing billions of dollars are planned on deltas globally, to mitigate land loss due to rising sea levels and subsidence. Downstream of engineered levee breaks, land building will rely on natural delta processes to disperse sediment. But, external factors known to affect natural delta processes vary between possible diversion sites (e.g., wave energy, basin substrate, marsh activity), making it difficult to quantitatively compare land-building potential between sites and optimally allocate engineering resources. We have implemented the pyDeltaRCM numerical model to provide an easily extensible platform for simulating delta evolution under arbitrary environmental factors. With the computationally efficient model, we isolate (and combine) these factors to observe effects on land building, and build a framework to quickly assess land-building potential at different sites. In this presentation, I will describe pyDeltaRCM model design, and show ongoing studies to assess land-building potential of diversions under different forcings. Model computational efficiency enables uncertainty quantification that will benefit diversion planning and resource allocation, by identifying relative impact of different external factors.
Virginia Ruiz-Villanueva
University of Lausanne
Modelling flow, sediment, and wood transport in rivers When a tree falls in a river promotes fundamental changes in river hydraulics and morphology, playing a relevant role in river ecology but also in flood hazards. By interacting with the flow and sediment, the instream large wood (i.e., downed trees, trunks, root wads, and branches) contributes to maintaining the river's physical and ecological integrity. However, during floods, large quantities of wood can be transported and deposited, enhancing the negative effects of flooding at critical sections like bridges. Accurate predictions of large wood dynamics in terms of fluxes, depositional patterns, trajectories, and travel distance, are still lacking, and only recently numerical models can help to this end. In contrast to other fluvial components such as fluid flow and sediment, for which numerical models have been extensively developed and applied over decades, numerical modeling of wood transport is still in its infancy. In this talk, I will describe the most recent advances and remaining challenges related to numerical modeling of instream large wood transport in rivers, with a particular focus on the numerical model Iber-Wood. Iber-Wood is a two-dimensional computational fluid dynamics model that couples a Eulerian approach for hydrodynamics and sediment transport to a discrete element (i.e., Lagrangian) approach for wood elements. The model has been widely validated using flume and field observations and applied to several case studies and has been proven to accurately reproduce wood trajectories, patterns of wood deposition, and impacts of wood accumulations during floods.
D. Sarah Stamps
Virginia Tech
3D Computational Modeling of Lithospheric Deformation, Asthenospheric Flow, and Deep Melt Generation with ASPECT Surface processes are influenced by viscous coupling of the deforming lithosphere to asthenospheric flow, as well as magma that migrates upward from the upper asthenosphere. Over the past few decades, significant advances have been made in finite element numerical methods that enable modeling of lithospheric deformation, viscous coupling to asthenospheric flow, and melt generation in the upper asthenosphere. In this work, we present new developments based on the NSF Computational Infrastructure for Geodynamics finite element code ASPECT (Advanced Solver for Problems in Earth’s Convection) that allow users to easily investigate these processes in distinct tectonic and geographic locations. . Users have the options to constrain their initial temperature and density conditions with laterally varying lithospheric thickness, layers of crustal thickness, and shear wave seismic velocity models in the sublithospheric mantle. We present case studies from regions along the East African Rift System that demonstrate these capabilities.


Anderson Banihirwe
National Center for Atmospheric Research
Xarray for Scalable Scientific Data Analysis This tutorial introduces Xarray which is a Python library that provides (1) data structures for multi-dimensional labeled arrays, (2) a toolkit for scalable data analysis on large, complex datasets using Dask which extends the SciPy ecosystem (e.g. NumPy, Pandas, Scikit-Learn) to larger-than-memory or distributed environments.</br></br>Attendees should be comfortable with basic Python programming (e.g., data structures, functions, etc.). Some prior exposure to Python data science libraries (e.g., NumPy, Pandas) is helpful. No specific domain knowledge is required to effectively participate in this tutorial.
Daniel Buscombe
Marda Science
Image Segmentation using Deep Learning and Human-In-the-Loop Machine Learning Segmentation, or the classification of pixels (grid cells) in imagery, is ubiquitously applied in the natural sciences. An example close to the CSDMS community might be translating images of earth surface into arrays of land cover to be used as model initial conditions, or to test model output. Manual segmentation is often prohibitively time-consuming, especially when images have significant spatial heterogeneity of colors or textures.</br></br>This Clinic is focused on demonstrating a machine learning method for image segmentation using two software tools: The first is “Doodler”, a fast, semi-automated, method for interactive segmentation of N-dimensional (x,y,N) images into two-dimensional (x,y) label images. It uses human-in-the-loop ML to achieve consensus between the labeler and a model in an iterative workflow. Second, we will demonstrate Segmentation Zoo, a python toolbox to segment imagery with a variety of deep learning models that uses output from Doodler with existing models, or train entirely new models.</br></br>Ideally the clinic will be divided into two separate days. Day 1 would be a short introductory lecture, a live code demo, and then homework — participants will doodle imagery to gain familiarity with the software and create training data for a segmentation model. Day 2 would be a short introductory lecture on machine learning, and a live code demo for how to use doodled images in Segmentation Zoo (i.e., the images that participants doodled).</br></br>There are two concrete goals for the clinic: 1) demonstrate how participants can use these two tools, and; 2) a group authored dataset of doodled images that will be placed in a Zenodo repository with all participants who contribute as coauthors.</br></br>Doodler preprint:</br></br>Doodler repository:</br></br>Doodler Website: </br></br>Segmentation Zoo repository:
Benjamin Campforts
Clinic 3: Component Creation with Landlab This clinic explores how to fully engage with the Landlab library by creating your own components. It is designed for those who already have some basic familiarity with Landlab and with scientific Python programming (registration for the “Introduction to Landlab” is recommended for those who have not already learned the basics).. In this workshop we will cover an overview of object-oriented programming (OOP), and will look at several examples of existing Landlab components to understand how they are written in an OOP framework. We will write a demo component as a group, and will then move on to writing our own components in small groups.</br></br>Participants should come prepared with an idea of a process model they’d like to implement as a component. It is recommended, but not required, that participants in this workshop also register for the clinic “The Art of Modeling: From Concept to Math with Mass Balance,” in order to be equipped with an understanding of the math that will form the basis of their Landlab component.</br></br>This workshop will involve coding in Python using the CSDMS JupyterHub. If you don't already have an account, follow the instructions to sign up at:
Vanessa Gabel
University of Colorado, Boulder
Clinic 2: Introduction to Landlab: Getting to know the Grid and Coupling Components This clinic provides a brief tutorial introduction to the theory and implementation of Landlab for landscape evolution modeling. Topics include grid representation, working with data fields, and using Landlab components to create new integrated models. This clinic is intended for beginners with little to no experience using the Landlab library. Prior experience with Python programming is helpful but not necessary.
Jayaram Hariharan
University of Texas
Rapid hypothesis testing and analysis with the open-source delta model pyDeltaRCM In this clinic, we will introduce and experiment with open-source tools designed to promote rapid hypothesis testing for river delta studies. We will show how pyDeltaRCM, a flexible Python model for simulating river delta evolution, can be extended to incorporate any arbitrary processes or forcings. We will highlight how object-oriented model design enables community-driven model development, and how this promotes reproducible science. Our clinic will develop an extended model to simulate deltaic evolution into receiving basins with different slopes. Then, the clinic will step through some basic analyses of the model runs, interrogating both surface processes and subsurface structure. Our overall goal is to familiarize you with the tools we are developing and introduce our approach to software design, so that you may adopt these tools or strategies in your research.</br></br>Please note that familiarity with Python will be beneficial for this clinic, but is not required. Hands-on examples will be made available via an online programming environment (Google CoLab or similar); instructions for local installation on personal computers will be provided prior to the workshop as well.
Chang Liao
Pacific Northwest National Laboratory
Variable resolution mesh based flow direction and hydrologic modeling: An introduction to HexWatershed Flow routing map is the cornerstone of spatially distributed hydrologic models. In this clinic we will introduce HexWatershed, a scale-free, mesh independent flow direction model. It supports DOE’s Energy Exascale Earth System Model (E3SM) to generate hydrologic parameters and river network representations on both structured and unstructured meshes. </br></br>In this presentation, we will overview the capabilities of HexWatershed with an emphasis on river network representation and flow direction modeling. We will also provide participants with the tools to begin their own research with hydrologic model workflows. Through hands-on tutorials and demonstrations, participants will gain some insights into the relationship between meshes and flow direction, and how HexWatershed handles river network in various meshes. We will also demonstrate how to use the HexWatershed model outputs in the large-scale hydrologic model, Model for Scale Adaptive River Transport (MOSART). Participants will be provided with additional resources that can be used to extend the tutorial problems and gain additional familiarity with the tools and workflows introduced. Participants are welcome to bring and utilize their own computers capable of accessing the internet and running a web browser. Tutorials will involve simple scripting operations in the Python language. The conda utility will be used to install libraries. Both QGIS and VisIt packages will be used for visualization.
Irina Overeem
University of Colorado
Teaching with Jupyter NoteBooks Jupyter Notebooks can be powerful tools for classroom teaching. This clinic explores different ways to use notebooks in teaching, common pitfalls to avoid, and best practices. It also introduces the CSDMS OpenEarthscape Hub, an online resource that instructors can use that eliminates the need to install software and provides students with direct access to various CSDMS tools.
Danica Roth
Colorado School of Mines
Environmental seismology and distributed acoustic sensing (DAS) Seismo-acoustic techniques can provide continuous, real-time observations with high temporal resolution and broad spatial coverage for process monitoring, detection and characterization in accessible environments. These capabilities are rapidly advancing with the growing use of distributed acoustic sensing (DAS) systems, which use fiber optic cables to provide continuous records of ground motion comparable to large-N arrays of single-component accelerometers or geophones. Compared to traditional seismic arrays, DAS arrays can be tens of kilometers in length with spatial resolution of meters and sampling frequencies from millihertz to kilohertz. </br></br>In this clinic, participants will learn about the basics of DAS instrumentation and deployment in an introductory lecture, and be introduced to hands-on DAS data input, analysis and visualization concepts through Jupyter notebooks. The clinic will also provide participants with resources for further exploring and utilizing DAS, including guides to open DAS datasets, and the growing resource lists and GitHub organization managed by the NSF-funded DAS Research Coordination Network (
Travis Thurber
Pacific Northwest National Laboratory
Modeling Water Movement and Reservoir Operations with mosartwmpy Water -- we drink it, we bathe in it, we feed it to our plants, we gaze admiringly as it falls off cliffs -- but how does it get from the sky to your tap? Will it always be free to chisel windingly through the countryside and leap from dazzling heights?</br></br>The open-source model mosartwmpy (aka "wimpy") offers researchers a bird's eye view of water movement and reservoir operations across the conterminous United States. Wimpy has been translated into Python from its ancestor MOSART-WM (Model Of Scale Adaptive River Transport and Water Management) without sacrificing performance, leading to a more widely accessible and extensible model. By implementing the Basic Model Interface (BMI), Wimpy provides a familiar workflow with interoperability at the heart.</br></br>This clinic will introduce mosartwmpy at a high-level and provide a hands-on, interactive tutorial demonstrating its capabilities for studying water shortages. Attendees should leave armed with a stronger understanding of the interplay between water movement and reservoir storage, and with the confidence to utilize mosartwmpy in their own research.
Greg Tucker
Clinic 1: The Art of Modeling: From Concept to Math with Mass, Energy, and Momentum Balance Numerical models describe the world around us mathematically, allowing us to visualize changes to physical systems through both space and time. These models are essential tools for geoscientists, but writing your own model can be a daunting task. </br></br>In this clinic, we’ll develop an understanding of what numerical models are, and then we’ll delve into the math that functions as the basis for many models. Participants will learn how to apply basic conservation principles to developing equations that describe a physical system that changes through time. This workshop will expose participants to deriving differential equations, and using basic Python programming to visualize their solutions. Prior experience is not necessary.

Interested in providing a clinic during the next annual meeting? Contact CSDMS@Colorado.EDU.

Poster guidelines

Poster guidelines will be posted as soon as the registration opens.

Travel Scholarships

Applications due by February 28, 2022
This year CSDMS is offering a limited number of travel scholarships for graduate students, post docs, early career faculty and faculty from minority serving institutions to attend the CSDMS annual meeting. A number of these scholarships will be offered for the purpose of increasing participation of underrepresented students. To be eligible, applicants need to meet the following requirements:

  • Attend the whole meeting (May 17-19, 2022) in Boulder, Colorado
  • Submit an abstract for and provide a poster presentation at the meeting (this requirement may be waved under limited conditions, i.e. 1st year graduate student that has not started their research, etc.)
  • Submit a letter of motivation that states why you wish to participate in the meeting and explain how/if your participation would enhance diversity in the field of surface dynamics modeling.

The CSDMS travel scholarships will cover:

  • Registration costs (to be reimbursed after attending the meeting)
  • Travel (for US participants air fare and local transport, for international participants up to $1500 of transportation costs will be reimbursed)
  • Per diem to help reimburse the cost of meals from 16-19 May 2022 not offered in the conference schedule

Please submit your letter of motivation and contact information to by February 28th, 2022. Applicants will be notified of decision in early March.

Syvitski Student Modeler Award 2022

Applications due by January 28, 2022
CSDMS invites graduate students from earth and computer sciences to compete for the annual “CSDMS Student Modeler Award.” If you have completed an outstanding research project in 2021, which involved developing an earth science model, a modeling tool, or module linking technology, you can qualify for this award! Read more on how to apply.

Land Acknowledgement

We acknowledge that the land, on which we will hold our meeting in the Boulder, Colorado, is part of the land within the Traditional Territories of the Arapaho, Cheyenne, and Ute peoples. Further we acknowledge that 48 contemporary tribal nations are historically tied to the lands that make up the state of Colorado. For more information, see the official CU-Boulder Acknowledgement.

Code of Conduct

CSDMS is committed to fostering a professional, respectful, inclusive environment at the annual meeting, such that all participants can participate to the fullest in a welcoming, respectful, inclusive, and collaborative environment that is free of harassment and discrimination. CSDMS expects all participants and staff to comply with this code of conduct, as outlined at CSDMS code of conduct.

Important dates

  • January 28: Application deadline Syvitski Student Modeler Award 2022
  • February 28: Application deadline travel scholarships
  • April 15: Abstract submission deadline
  • April 15: Meeting registration deadline
  • May 17-19: CSDMS annual meeting
  • May 20: CSDMS Executive and Steering committees meetings (by invitation only)

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