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• CSDMS meeting 2021

CSDMS 2021: Changing Landscapes and Seascapes
Modeling for Discovery, Decision Making, and Communication

May 17 -21^th 2021

Registration

CSDMS 2021 annual meeting will be a free to attend, fully virtual meeting and we'll do our best to make it an informative and enjoyable experience for all participants. Registration & abstract submissions will be accepted until 30 April 2021.

Registration is now closed.

Introduction

This year’s meeting will be broad in scope, showcasing modeling-oriented projects that range from fundamental geoscientific discovery to applied work involving stakeholders. A novel addition this year is the theme of communication: how do we effectively communicate our research to diverse audiences—students, stakeholders, decision-makers, the general public, and one another? How can models help with communication (e.g., visualization, gamification, “what if” scenario analysis)?

Events

Click here to download the final more detailed agenda.

Monday May 17th

3:00 - 5:00pm MDT; Town Hall, Award Ceremony & Social hour

Tuesday May 18th

9:00 - 10:30am MDT; Plenary keynote presentations

Jacky Austermann
Lamont-Doherty Earth Observatory

Integrating numerical models with co-production to understand sea level change and its impact around Greenland Melting of the Greenland Ice Sheet contributes to rising global sea levels. However, local sea level along much of the Greenland coast is falling due to postglacial rebound and a decrease in gravitational attraction from the ice sheet. This affects Greenlandic coastal communities, which have to adapt their coastal infrastructure, shipping routes, and subsistence fisheries. The “Greenland Rising” project is a collaboration between Lamont-Doherty Earth Observatory and the Greenland Institute of Natural Resources that focuses on assessing and preparing for changing sea level along Greenland’s coastline. While sea level is predicted to fall, the exact magnitude varies widely depending on past and present ice change as well as the viscoelastic properties of the subsurface. I will demonstrate how current sea level change depends on these parameters and how we can integrate numerical models of glacial isostatic adjustment with observations of past sea level and present-day uplift to constrain them. I will further briefly describe the role of co-production in this project, which has allowed us to coordinate bathymetric surveys with local stakeholders from the municipality, industry, and local Hunters and Fishers organization. Combining numerical predictions of sea level change with baseline bathymetry and benthic mapping promises to provide communities with a clearer picture of future environmental change.

Arye Janoff
U.S. House of Representatives Transportation and Infrastructure Subcommittee on Coast Guard and Maritime Transportation; Formerly at Earth and Environmental Studies Department, Montclair State University

From Coastal Retreat to Seaward Growth: Emergent Behaviors from Paired Community Beach Nourishment Choices Coastal communities facing shoreline erosion preserve their beaches both for recreation and for property protection. One approach is nourishment, the placement of externally-sourced sand to increase the beach’s width, forming an ephemeral protrusion that requires periodic re-nourishment. Nourishments add value to beachfront properties, thereby affecting re-nourishment choices for an individual community. However, the shoreline represents an alongshore-connected system, such that morphodynamics in one community are influenced by actions in neighboring communities. Prior research suggests coordinated nourishment decisions between neighbors were economically optimal, though many real-world communities have failed to coordinate, and the geomorphic consequences of which are unknown. Toward understanding this geomorphic-economic relationship, we develop a coupled model representing two neighboring communities and an adjacent non-managed shoreline. Within this framework, we examine scenarios where communities coordinate nourishment choices to maximize their joint net benefit versus scenarios where decision-making is uncoordinated such that communities aim to maximize their independent net benefits. We examine how community-scale property values affect choices produced by each management scheme and the economic importance of coordinating. The geo-economic model produces four behaviors based on nourishment frequency: seaward growth, hold the line, slow retreat, and full retreat. Under current conditions, coordination is strongly beneficial for wealth-asymmetric systems, where less wealthy communities acting alone risk nourishing more than necessary relative to their optimal frequency under coordination. For a future scenario, with increased material costs and background erosion due to sea-level rise, less wealthy communities might be unable to afford nourishing their beach independently and thus lose their beachfront properties.

Aleja Ortiz
Colby College

Atolls & Ecogeomorphology: Investigating the feedbacks between physical, anthropogenic, and ecological processes under changing climates via remote sensing, computational modeling, and fieldwork Within our lifetime, climate change has the potential to drastically alter coastal resiliency. Atoll island nations are particularly vulnerable to climate change: from increasing ocean temperatures (causing coral die-off), to ocean acidification (decreasing coral resiliency), to increasing SLR. We must understand what will happen to the atoll islands because they are the inhabited portion of these systems. However, we lack a comprehensive understanding about the primary processes driving atoll island evolution under rising sea levels and varying wave climate. This uncertainty in predictions hinders local communities’ preparation for the future; we must understand how atoll islands respond and evolve with changing environmental forcings on a global scale. To predict the response of these islands to changing climate, we must understand the feedbacks between physical and ecological processes at different temporal and spatial scales. In addition, we must account for the actions and processes taken by humans driving landscape change on these islands. My lab has focused on investigating the feedbacks inherent in these landscapes using numerical modeling and remote sensing.

Allison Pfeiffer
Western Washington University

Modeling bed material abrasion at the basin scale: why the classic approach fails us Bed material abrasion is a key control on the partitioning of basin scale sediment fluxes between coarse and fine material. While abrasion is traditionally treated as a simple exponential function of transport distance and a rock-specific abrasion coefficient, experimental studies have demonstrated greater complexity in the abrasion process: the rate of abrasion varies with clast angularity, transport rate, and grain size. Yet, few studies have attempted to assess the importance of these complexities in the field setting. Furthermore, existing approaches generally neglect the heterogeneity in size, abrasion potential, and clast density of the source sediment.</br>Combining detailed field measurements and new modeling approaches, we quantify abrasion in the Suiattle River, a basin in the North Cascades of Washington State dominated by a single coarse sediment source: large, recurrent debris flows from a tributary draining Glacier Peak stratovolcano. Rapid downstream strengthening of river bar sediment and a preferential loss of weak, low-density vesicular volcanic clasts relative to non-vesicular ones suggest that abrasion is extremely effective in this system. The standard exponential model for downstream abrasion fails to reproduce observed downstream patterns in lithology and clast strength in the Suiattle, even when accounting for the heterogeneity of source material strength and the underestimate of abrasion rates by tumbler experiments. Incorporating transport-dependent abrasion into our model largely resolves this failure. These findings hint at the importance of abrasion and sediment heterogeneity in the morphodynamics of sediment pulse transport in river networks. A new modeling tool will allow us to tackle these questions: the NetworkSedimentTransporter, a Landlab component to model Lagrangian bed material transport and channel bed evolution. This tool will allow for future work on the interplay of bed material abrasion and size selective transport at the basin scale.</br>While a simplified approach to characterizing abrasion is tempting, our work demonstrates that sediment heterogeneity and transport-dependent abrasion are important controls on the downstream fate of coarse sediment in fluvial systems.

Tristan Salles
The University of Sydney

A geomorphic perspective on Quaternary biogeographic connectivities across South East Asia Sundaland, the name given to the emerged parts of the Sunda Shelf during low sea level, currently lies approximately 100 m</br>beneath the Java Sea and southwestern part of the South China Sea. The region is of particular interest in biogeography and biodiversity studies for its position at the junction between two major zoogeographic provinces that extend across the Equator and for its prevailing connection with mainland Southeast Asia. Using landscape evolution and connectivity analysis models, we will investigate how changes induced by drainage basins reorganisation and river captures have transformed the environment into fragmented habitats over the past million years. We will see that physiographic evolution has a strong control on the preferential connectivity pathways and triggers successive phases of expansion and compression of the migratory corridors across the shelf and is an important mechanism to consider in order to improve our understanding of species richness dynamics in the region.

11:00am - 1pm MDT; Clinics: choose clinic of interest (only 1 each day as these are given in parallel)

Doug Edmonds
University of Indiana & Planet Labs

An Introduction to using Google Earth Engine In this clinic we will explore how to use the cloud-based remote sensing platform from Google. Our hands-on clinic will teach you the basics of loading and visualizing data in Earth Engine, sorting through data, and creating different types of composite images. These techniques are a good starting point for more detailed investigations that monitor changes on earth’s surface. Prerequisites include having Chrome installed on your system: It will work with Firefox but has issues and an active Google account. Once you have those please register for an account with Google Earth Engine (https://earthengine.google.com/signup/)
Sold out

Nicole Gasparini
Tulane University

Do the work: Building a more equitable research unit Many geoscientists and geoscience organizations vowed to work towards equity and committed to anti-racist action in 2020. But getting started on and staying committed to diversity, equity, and inclusion (DEI) work takes time, energy, and education. This clinic will be a learning and sharing space for everyone who is on a journey towards building a more equitable research unit. Everyone can participate in this clinic, regardless of whether you are just starting your journey or you have travelled many miles and whether your research unit is one person or 100 people.</br></br>The clinic will begin with discussion and thought exercises about your personal identity. We will then think about what it means for our individual research units to be diverse, equitable, and inclusive. Finally, we will discuss actions you can take to build an anti-racist research unit. Participants will be invited to share their current DEI actions and discuss how they can be adapted for, or expanded in, other settings. The clinic aims to foster an environment in which participants can learn from each other, but participants will not be required to share. Upon completion of this clinic every participant should have a plan for implementing at least one new DEI action, including milestones and accountability checks.

Chris Jenkins
AI/ML Initiative/CSDCS, UC, Boulder

Training Datasets for Modeling with AI across the Deep-Ocean Seafloor As agreed at earlier CSDMS forums, the major </br>impediment in using AI for modeling the deep-ocean</br>seafloor is a lack of training data, the data which guides the AI - </br>whichever set of algorithms is chosen. This clinic will expose participants to </br>globally-extensive datasets which are available through CSDMS.</br>It will debate the scientific questions of why certain data work well,</br>are appropriate to the processes, and are properly scaled.</br>Participants are encouraged to bring their own AI challenges to the clinic.

Allen Lee
CoMSES Net; Arizona State University

Git good with FAIR enough practices for scientific software development This hands-on virtual clinic will go over good practices for scientific software development to help you develop and publish FAIR (Findable, Accessible, Interoperable, and Reusable) scientific software. We will cover basic principles and examples from the field and then dive into common collaboration workflows in Git and GitHub that facilitate comprehension and reuse of your codebases. We will engage in live-coding exercises with test repositories on GitHub and help you develop a clear conceptual model of how Git works and how to keep a codebase commit history clean and comprehensible with branches, merging / rebasing, and pull requests.

Scott Peckham
University of Colorado

Component-based Hydrologic Modeling: Getting Started with the TopoFlow 3.6 Python Package TopoFlow is a plug-and-play, spatial hydrologic model distributed as an open-source Python package. The current version includes numerous hydrologic process components (all BMI-compliant), an extensive set of utilities for data preparation, river network delineation, visualization and basic calibration, the EMELI model coupling framework, sample data and a set of Jupyter notebooks for learning about the capabilities. The total package consists of around 90,000 lines of efficient code that uses NumPy and runs in Python 3.*. In this clinic, we will first cover some background information, install the package and then work through several Jupyter notebooks to explore the functionality.

1:30 - 3:00pm MDT; GroupMeeting / Posters

Wednesday May 19th

9:00 - 10:30am MDT; Plenary keynote presentations

Sondoss El Sawah
Australian Defense Force Academy

Eight grand challenges in socio-environmental systems modelling Socio-environmental systems (SES) modeling integrates knowledge and perspectives into conceptual and computational tools that explicitly recognize how human decisions affect the environment. With the advent of new techniques, data sources, and computational power on the one hand, and the growing sustainability challenges on the other, the expectation is that SES modeling should be more widely used to inform decision-making at multiple scales. This presentation will highlight the grand challenges that need to be overcome to accelerate the development and adaptation of SES modeling.</br>These challenges include: bridging epistemologies across disciplines; multi-dimensional uncertainty assessment and management; scales and scaling issues; combining qualitative and quantitative methods and data; furthering the adoption and impacts of SES modeling on policy; capturing structural changes; representing human dimensions in SES; and leveraging new data types and sources. The presentation will outline the steps required to surmount the underpinning barriers and priority research areas in SES modelling and propose clear directions for future generations of models and modeling, to both their developers and users.

Robert Lempert
RAND Corporation

Good Decisions Without Good Predictions: Decision Making Under Deep Uncertainty Quantitative analysis is often indispensable for making sound policy choices. But when decisionmakers confront today’s conditions of fast-paced, transformative, and even surprising change, they sometimes find that commonly used quantitative methods and tools prove counterproductive or lead them astray. Typically, quantitative analysis provides decisionmakers with information about the future by making predictions. But predictions are often wrong, and relying on them can be dangerous. Moreover, decisionmakers know that predictions are often wrong; this can cause them to discount or ignore the crucial information that quantitative analysis can provide. Fortunately, the combination of new information technology and new insights from the decision sciences now enables innovative ways to support decisions with quantitative analysis. This talk describes how one such approach—Robust Decision Making (RDM)—informs good decisions without requiring confidence in and agreement on predictions and offers examples of its increasing impact in a wide range of policy areas.

Fred L. Ogden
NOAA-NWS Office of Water Prediction

Next Generation Water Resources Modeling Framework: Opportunities for Community Involvement The current operational NOAA-NWS National Water Model applies a uniform formulation to make continental scale flow predictions on the NHD+ drainage network. However, the literature demonstrates that given the spatial variability in dominant runoff generation mechanism and associated uncertainties in processes and parameters, skillful predictions require scientific evaluation of different model formulations in different hydrologic regions. Providing timely inland and coastal continental-scale predictions requires operations in an HPC environment. Legacy water resources models have dissimilar inputs and setup workflows, run-time environments, discretizations, solvers, and required forcing data. The sheer variety of approaches impedes model comparison and interoperability. The WaterML 2.0 Hy_Features standard provides a stable meta-model to describe the hydrologic landscape, and includes four fundamental topological elements: “catchment”, “flowpath”, “water body”, and their “nexus” linkages, which represent internal boundary conditions and provide natural breakpoints between models. The Hy_Features data model standard helps to unify model setup workflows. The Next Generation Water Resources Modeling Framework that is currently under development promotes interoperability, inter-comparison, model-based testing of research hypotheses, and ultimately improved agency-specific operational predictions while incorporating rapid adoption of advancements from the academic and federal research communities. This is achieved by using the drainage network as a graph to organize parallelization, and by extending the CSDMS Basic Model Interface (BMI) to include state-serialization functionality and to accommodate models with parallel formulations. This work in progress uses the open source development paradigm and participation by the research community is welcomed.

11:00am - 1pm MDT; Clinics: choose clinic of interest (only 1 each day as these are given in parallel)

Rebecca Batchelor
Cooperative Institute for Research in Environmental Science (CIRES), CU Boulder & CU, Boulder & GeoLatinas

Inclusive Mentoring Great mentors engage early career scientists in research, open doors, speak the ‘unspoken rules’, and inspire the next generation. Yet many of us step into mentoring roles without feeling fully confident in the role, or uncertain how to create an inclusive environment that allows early career scientists from varied backgrounds to thrive. In this interactive workshop, we will share experiences and explore tools that can help build successful mentoring relationships, create supportive cohorts, and feel confident in becoming a great mentor.

Benoît Bovy
GFZ / Independent software engineer

Building Interactive Dashboards for Earth Surface Processes Modeling with Python and Jupyter Jupyter notebooks provide a very convenient way to communicate research results: they may contain narrative text, live code, equations and visualizations all in a single document. Beyond notebooks, the Jupyter ecosystem also provides many interactive, graphical components (widgets) that can be used within notebooks to further enhance the user experience. Those widgets serve a variety of purposes such as 2D (Ipympl, Bqplot, Ipycanvas) or 3D (Ipygany) scientific visualization, 2D (Ipyleaflet) or 3D (Pydeck) maps, etc. When the target audience is not familiar with coding, it is possible to turn Jupyter notebooks into interactive dashboards and publish them as stand-alone web applications (using Voilà).</br></br>In this workshop, we will learn how to leverage this powerful Jupyter environment to build custom, interactive dashboards for exploring models of Earth surface processes in contexts like research, teaching and outreach. After introducing the basics of Jupyter widgets, we will focus on more advanced examples based on Fastscape and/or Landlab. We willl also spend some time on hands-on exercises as well as brainstorming dashboard ideas.</br></br>Clinic materials and installation instructions can be found here: https://github.com/benbovy/jupyter-dash-csdms2021</br></br>Related links:</br></br>- https://github.com/fastscape-lem/gilbert-board</br>- https://github.com/fastscape-lem/ipyfastscape

Tian Gan
CSDMS IF

CSDMS@HydroShare: find, access, operate and couple data-model integration tools for reproducible research As global population grows and infrastructure expands, the need to understand and predict processes</br>at and near the Earth’s surface—including water cycling, soil erosion, landsliding, flood</br>hazards, permafrost thaw, and coastal change—becomes increasingly acute. Progress in understanding</br>and predicting these systems requires an ongoing integration of data and numerical</br>models. Advances are currently hampered by technical barriers that inhibit finding, accessing,</br>and operating modeling software and related tools and data sets. To address these challenges, we present the CSDMS@HydroShare, a cloud-based platform for accessing and running models, developing model-data workflows, and sharing reproducible results. </br></br>CSDMS@HydroShare brings together cyberinfrastructure developed by two important community facilities: HydroShare (https://www.hydroshare.org/), which is an online collaboration environment for sharing data, models, and tools, and CSDMS Workbench (https://csdms.colorado.edu/wiki/Workbench), which is the integrated system of software tools, technologies, and standards for building, interfacing, and coupling models. </br></br>This workshop presents how to use CSDMS@HydroShare to discover, access, and operate the Python Modeling Tool (PyMT). PyMT is one of the tools from the CSDMS Workbench, which allows users to interactively run and couple numerical models contributed by the community. In PyMT, there are already model components for coastal & permafrost modeling, stratigraphic and subsidence modeling, and terrestrial landscape evolution modeling. It also includes data components to access and download hydrologic and soil datasets from remote servers to feed the model components as inputs.</br></br>This workshop aims to encourage the community to use existing or develop new model or data components under the PyMT modeling framework and share them through CSDMS@HydroShare to support reproducible research. This workshop includes hands-on exercises using tutorial Jupyter Notebooks and provides general steps for how to develop new components.

Wei Wu
The University of Southern Mississippi

Introduction to R programming and R applications in landscape ecology R has been widely used by ecologists. It is a powerful language to build statistical models. However, R applications in landscape ecology are relatively limited. In this model clinic, we will introduce R programming and two recently developed packages “NLMR” and “landscapetools” in generating and visualizing neutral landscapes. </br>Neutral models are useful tools for testing the effect of different spatial processes on observed patterns, as they create landscape patterns in the absence of specific processes. Comparisons between a landscape model and a neutral model simulation will provide insights into how these specific processes affect landscape patterns. Different algorithms exist to generate neutral landscapes and they have been traditionally included in different programs. Now the NLMR package in R integrated all these different algorithms into one place. </br>In addition to providing instructions on how to use R, “NLMR and “landscapetools packages”, we will showcase real-world examples on neutral landscapes’ applications in ecology, such as predicting coastal wetland change in response to sea-level rise.

Moira Zellner
Northeastern University

Decision Framing Decision framing is a key, early step in any effective decision support engagement in which modelers aim to inform decision and policy making. In this clinic participants will work through and share the results of decision framing exercises for a variety of policy decisions. We will organize the exercise using the XLRM elicitation, commonly used in decision making under deep uncertainty (DMDU) stakeholder engagements. The XLRM framework is useful because it helps organize relevant factors into the components of a decision-centric analysis. The letters X, L, R, and M refer to four categories of factors important to RDM analysis: outcome measures (M) that reflect decision makers’ goals; policy levers (L) that decision makers use to pursue their goals; uncertainties (X) that may affect the connection between policy choices and outcomes; and relationships (R), often instantiated in mathematical simulation models, between uncertainties and levers and outcomes.

1:30 - 3:00pm MDT; GroupMeeting / Posters

Thursday May 20th

8:00 - 9:00am MDT; Social/Coffee Hour

9:00 - 10:30am MDT; Plenary keynote presentations

Fedor Baart
Deltares

Models in virtual environments and digital twins One of the challenges for modelers is to get their results into the hands of potential users. We do this by creating informative and relevant maps, charts, and indicators. Sometimes we try to go further. We want end-users to 'feel' the model, using techniques like haptic interactions, extended reality. We do this to help the user to get a better understanding (exploration, interaction) or to develop a shared concept (by socializing around the model), or to provide the user with an immersive experience (using photorealistic rendering).</br>Using the BMI interface, which we also use for model coupling, we have changed several models from passive to interactive. We integrated these interactive models into different environments, such as the recently developed Virtual River Game, the Coastal Sandbox. Here we present recent developments, technical considerations and the results of the user studies that helped shape our vision towards more effective scientific communication and interaction.

Kerry Callaghan
Lamont-Doherty Earth Observatory

Coupled Groundwater and Dynamic Lake Modelling using the Water-Table Model (WTM) Changing depth to water table and the associated stored water volume is a crucial component of the global hydrological cycle, with impacts on climate and sea level. However, long-term changes in global water-table distribution are not well understood. Coupled ground- and surface-water models are key to understanding the hydrologic evolution of post-glacial landscapes, the significance of terrestrial water storage, and the interrelationships between freshwater and climate. Here, I present the Water Table Model (WTM), which is capable of computing changes in water table elevation at large spatial scales and over long temporal scales. The WTM comprises groundwater and dynamic lake components to incorporate lakes into water-table elevation estimates. Sample results on both artificial and real-world topographies demonstrate the two-way coupling between dynamic surface-water and groundwater levels and flow.

Sai S. Nudurupati
Jacobs

Modeling transient Ecosystem Response to Climate Variability since Late Pleistocene using Landlab Ecosystems are in transition globally with critical societal consequences. Global warming, growing climatic extremes, land degradation, human-introduced herbivores, and climate-related disturbances (e.g., wildfires) drive rapid changes in ecosystem productivity and structure, with complex feedbacks in watershed hydrology, geomorphology, and biogeochemistry. There is a need to develop models that can represent ecosystem changes by incorporating the role of individual plant patches. We developed ecohydrologic components in Landlab that can be coupled to create models to simulate local soil moisture dynamics and plant dynamics with spatially-explicit cellular automaton plant establishment, mortality, fires, and grazing. In this talk, I will present a model developed to explore the interplay between ecosystem state, change in climate, resultant grass connectivity, fire frequency, and topography. A transition from a cool-wet climate to a warm-dry climate leads to shrub expansion due to drought-induced loss of grass connectivity. Shrubs dominate the ecosystem if dry conditions persist longer. The transition back to a tree or grass-dominated ecosystem from a shrub-dominated ecosystem can only happen when climate shifts from dry to wet. The importance of the length of dry or wet spells on ecosystem structure is highlighted. Aspect plays a critical role in providing topographical refugia for trees during dry periods and influences the rate of ecosystem transitions during climate change.

Paola Passalacqua
The University of Texas at Austin

Grid or subgrid? Analysis of river systems under change at the intersection of modeling and high resolution data analysis The analysis of river systems under change involves a wide range of spatial and temporal scales. Channel features range from sub-meter to kilometer scale and processes along river networks vary from instantaneous to geologic time scales. In the face of changes in forcings and anthropogenic modifications on the Earth surface, analysis and modeling of river systems is challenged by this vast range of scales and lack of measurements capable of capturing the heterogeneity that characterizes river systems. Remotely sensed data provide access to spatial and temporal information that can be integrated with modeling and field observations. In this presentation, I will show examples of river network studies that integrate multiple sources of data to address issues of flooding and coastal resilience. I will also discuss existing challenges and opportunities for future research.

Fernando Perez
University of California, Berkeley

Jupyter Technology TBD

11:00am - 1pm MDT; Clinics: choose clinic of interest (only 1 each day as these are given in parallel)

Fedor Baart
Deltares

Digital Twins in Earth Sciences A recent trend in the Earth Sciences is the adaptation of so-called “Digital Twins”. In Europe multi-million and even multi-billion projects are initiated for example, the Digital Twin of the Ocean and the Digital Twin Earth. But also many smaller digital-twin projects are popping up in the fields of city management, tunnels, hydraulic structures, waterways and coastal management. </br>But what are Digital Twins really? Why are they now trending? What makes a Digital Twin different from a serious game, a numerical model or a simulator? In this session we will look at examples of digital twins, we will compare them to more traditional platforms and together define our expectations on future digital twins.

Benjamin Campforts
CSDMS IF

Looking Under the Hood: Landscape Evolution Modeling with TerrainBento and Landlab This clinic provides a brief tutorial introduction to the theory and implementation of Landscape Evolution Modeling. Participants will have the opportunity to work with simple models in the TerrainBento package, which provides a set of models that are built on the Landlab library. Topics include grid representation, working with data fields, and using Landlab Components to create new integrated models.To get to the clinic materials:* Load the notebooks in your Hub, just go to our GitHub page https://github.com/csdms/csdms2021_landlab_terrainbento* On that page, click the link under the agenda* Go to notebooks>landlab>Landlab_grids_csdms2021.ipynb for the landlab clinic * And to notebooks> landlab-terrainbento> Welcome_to_TerrainBento.ipynb for the terrainbento clinic. Note that for the terrainbento clinic, you will have to activate the TTBB kernel.There is even more material in the folder to practice your skills further. <br>This clinic runs on the CSDMS JupyterHub. If you don't already have an account, follow the instructions to sign up at: https://csdms.colorado.edu/wiki/JupyterHub. Run the lab Notebook by clicking the "start" link under the Run online heading at the top of this page. For more information, please contact us through the CSDMS Help Desk: https://csdms.github.io/help-desk.

Heidi Roop
University of Minnesota

Communication & Engagement: Tips, Tricks, Traps and Opportunities This interactive clinic will provide attendees with the opportunity to learn and practice some key concepts for communicating technical knowledge to a range of audiences, from the general public to decision-makers. We will explore effective communication methods, messaging, and platforms, including social media and working with the press. This clinic will also provide attendees with the opportunity to workshop ideas for designing more impactful broader impacts or engagement programs. </br></br>Attendees will leave with refined skills and useful resources for informing their science communication goals. This workshop is suitable for all skill and interest levels, and all career stages. The only requirement is an interest in interacting with your peers, sharing your unique perspective and experiences, and a willingness to support other attendees in building or honing their science communication skills.
Cancelled

Jon Schwenk
Los Alamos National Laboratory

Exploring river and delta channel networks with RivGraph In this clinic, we will explore RivGraph, a Python package for extracting and analyzing fluvial channel networks from binary masks. We will first look at some background and motivation for RivGraph's development, including some examples demonstrating how RivGraph provides the required information for building models, developing new metrics, analyzing model outputs, and testing hypotheses about river network structure. We will then cover--at a high level--some of the logic behind RivGraph's functions. The final portion of this clinic will be spent working through examples showing how to process a delta and a braided river with RivGraph and visualizing results.</br></br></br>Please note: This clinic is designed to be accessible to novice Python users, but those with no Python experience may also find value. If you'd like to work through the examples during the workshop, please install RivGraph beforehand, preferably to a fresh Anaconda environment. Instructions can be found here: https://github.com/jonschwenk/RivGraph. It is also recommended that you have a GIS (e.g. QGIS) available for use for easy display/interrogation of results.
Sold out

Chris Vernon
Pacific Northwest National Laboratory

GCAM and Demeter: A global, integrated human-Earth systems perspective to modeling land projections Researchers and decision makers are increasingly interested in understanding the many ways in which human and Earth systems interact with one another, at scales from local (e.g., a city) to regional to global. For example, how might changes in population, income, or technology development alter crop production, energy demand, or water withdrawals? How do changes in one region's demand for energy affect energy, water, and land in other regions? This session will focus on two models – GCAM and Demeter – that provide capabilities to address these types of questions.</br></br></br>GCAM is an open-source, global, market equilibrium model that represents the linkages between energy, water, land, climate, and economic systems. A strength of GCAM is that it can be used to quickly explore, and quantify the uncertainty in, a large number of alternate future scenarios while accounting for multi-sector, human-Earth system dynamics. One of GCAM’s many outputs is projected land cover/use by subregion. Subregional projections provide context and can be used to understand regional land dynamics; however, Earth System Models (ESMs) generally require gridded representations of land at finer scales. Demeter, a land use and land cover disaggregation model, was created to provide this service. Demeter directly ingests land projections from GCAM and creates gridded products that match the desired resolution and land class requirements of the user. </br></br>This clinic will introduce both GCAM and Demeter at a high-level. We will also provide a hands-on walk through for a reference case so attendees can become familiar with configuring and running these two models. Our goal will be for attendees to leave the clinic with an understanding of 1) the value of capturing a global perspective when informing subregional and local analysis, 2) possibilities to conduct scenario exploration experiments that capture multi-sector/scale dynamics, 3) and a hands-on experience with GCAM and Demeter.

1:30 - 3:00pm MDT; Science Jam

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

Participants

Who is registered as of 12/07/2024?

• Participants meeting
• Submitted abstracts

Poster guidelines

Please follow these poster guidelines to help you in presenting your poster virtual.

Syvitski Student Modeler Award 2021

Submission is now closed for this award

Important dates

• January 29: Application deadline Syvitski Student Modeler Award 2021
• April 30: Abstract submission deadline
• April 30: Meeting registration deadline
• May 17-21: CSDMS annual meeting
• May 21: CSDMS Executive and Steering committees meetings (by invitation only)