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Presenters-0678 + (There has been an explosion of interest in … There has been an explosion of interest in soil carbon sequestration as a natural carbon reduction strategy. Soil carbon stocks are an appealing reservoir for sequestering anthropogenic carbon dioxide due to their relatively low risk, low technological barrier, and potential for long residence time. But how much carbon sequestration potential is there globally? Where are the places soils currently accumulating anthropogenic carbon dioxide and would these locations lend themselves to more active management interventions? Two very contrasting approaches are being taken in soil science: digital soil mapping approaches rooted in soil carbon stock surveys and machine learning, as well as process models rooted in soil carbon flux studies and differential equations. In this talk we’ll explore where these representations deviate, how they could be reconciled, and how we can use modeling as a tool to expand our understanding of soil carbon potential for carbon dioxide draw down in the future.or carbon dioxide draw down in the future.)
Presenters-0651 + (There is global recognition to push forwar … There is global recognition to push forward mangrove restoration and conservation for climate mitigation and adaptation. Unfortunately, although our understanding of mangrove processes has significantly improved, 80-90% of the reported restoration projects have experienced failures. The main reasons are related to a poor understanding of the eco-geomorphological dynamics and mangrove species-specific ecological requirements. Mangrove restoration guidelines exist; however, they may be site-specific and cannot be easily replicated in other restoration cases. Hence, it emphasizes the need for a system understanding of mangrove ecosystem physical and ecological interactions. We developed a hybrid model by coupling the process-based hydro-morphodynamic model Delft3D-FM (DFM) and the individual-based mangrove model MesoFON (MFON). The model (DFMFON) allows us to resolve spatiotemporal processes, including tidal, seasonal, and decadal environmental changes with full-life-cycle mangrove interactions. The DFMFON model successfully reproduced observed spatiotemporal (seasonal-decadal) mangrove development, like the age-height relationship and morphodynamic delta features in a prograding Porong Delta, Indonesia.s in a prograding Porong Delta, Indonesia.)
Presenters-0679 + (Thermal inertia derived from infrared imag … Thermal inertia derived from infrared imagery offers a valuable tool for remotely mapping the physical structure and water content of soil and regolith. Unlike dry or airless bodies, however, Earth's abundant water and dense atmosphere lead to dynamic thermophysical conditions that are a greater challenge to model. In this work, an approach was developed using field experiments to inform and fine-tune a thermophysical model of terrestrial sediment. A Markov chain Monte Carlo optimization scheme is used to calculate an inherent thermal inertia value with higher precision and less initial knowledge of the sediment than has previously been achieved remotely on Earth. A more accurate thermal model for Earth has broad applications from local UAV-based geophysical surveys to climate modeling to improving interpretations of materials on Mars.ving interpretations of materials on Mars.)
Presenters-0176 + (This clinic aims to introduce the open sou … This clinic aims to introduce the open source computational fluid dynamics (CFD) platform, OpenFOAM®, to the earth surface dynamics research community and to foster collaborations. OpenFOAM® is essentially a computational toolbox which solves general physical models (differential equations) using finite volume method. This short clinic is tailored to be suitable for an audience at various levels (from beginners to experienced code developers). It will provide an overview of OpenFOAM. We will demonstrate its usage in a variety of applications, including hydrodynamics, sedimentation, groundwater flows, buoyant plumes, etc. Participants can also bring the problems in their fields of interest and explore ways to solve them in OpenFOAM®. Knowledge of C++, object-oriented programming, and parallel computing is not required but will be helpful.uting is not required but will be helpful.)
Presenters-0575 + (This clinic explores how to fully engage w … 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.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.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: https://csdms.colorado.edu/wiki/JupyterHub.ttps://csdms.colorado.edu/wiki/JupyterHub.)
Presenters-0117 + (This clinic is intended for early career r … This clinic is intended for early career researchers interested in gaining an understanding of basic integrated modeling concepts as they relate to modeling earth science systems. The class will present key literature in the field, core concepts and terminology, and different integrated modeling systems. Past, present, and future trends for designing integrating modeling systems will be discussed. Participants will also gain experience applying integrated modeling concepts using CSDMS for simplified integrated modeling examples.r simplified integrated modeling examples.)
Presenters-0574 + (This clinic provides a brief tutorial intr … 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. programming is helpful but not necessary.)
Presenters-0605 + (This clinic provides a brief tutorial intr … 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. programming is helpful but not necessary.)
Presenters-0514 + (This clinic provides a brief tutorial intr … 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. 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.ough the CSDMS Help Desk: https://csdms.github.io/help-desk.)
Presenters-0662 + (This clinic will describe a bit about glac … This clinic will describe a bit about glacier physics and then go on to show how to use the software package ICEPACK to simulate the flow of glaciers and ice sheets. We'll run through a few use cases, first on synthetic and then on real data. Then I'll show a few other useful features, like the ability to easily alter parts of the model physics like the sliding law. Finally I'll talk about some open problems and other things we're working on that might be of relevance to other disciplines within the earth sciences.her disciplines within the earth sciences.)
Presenters-0435 + (This clinic will introduce CUAHSI products … This clinic will introduce CUAHSI products that support hydrologic modeling and analysis workflows. The HydroShare and JupyterHub platforms will be used to demonstrate the cyberinfrastructure capabilities that have been designed for community modeling and educational purposes. Participants should have a working knowledge of Python and should bring a laptop.ledge of Python and should bring a laptop.)
Presenters-0611 + (This clinic will introduce and demonstrate … This clinic will introduce and demonstrate use of a powerful, flexible approach being used by the Pangeo community for working with large model output which works effectively on a range of computing systems including local machines, HPC facilities and the Cloud. Xarray is used for working with CF-compliant model output, Dask for parallelization, and Holoviz for interactive visualization in the browser. Rechunking data to improve performance for a variety of analysis use cases will also be covered.f analysis use cases will also be covered.)
Presenters-0430 + (This clinic will introduce deep learning m … This clinic will introduce deep learning methods for semantic segmentation of fluvial sedimentary landforms and riparian environments, using high-resolution aerial imagery. Deep neural networks are the current state-of-the-art for discrete classification of remotely sensed imagery from Earth observation platforms. The clinic will guide users through the process of preparing training datasets, training models, and evaluation. A number of different deep convolutional neural network architectures for image feature extraction and pixel-scale classifications will be explored and compared. The clinic will use the keras and tensorflow libraries within the python programming language. This hands-on class will be taught using Google colab through a browser, with the materials hosted on github. Participants will require a working knowledge of python. Some working knowledge of machine learning would be helpful, but we will assume no prior experience with machine/deep learning, neural networks, tensorflow, or keras.ng, neural networks, tensorflow, or keras.)
Presenters-0635 + (This clinic will introduce participants to … This clinic will introduce participants to GRASS GIS tools with a focus on applications for coastal hazards analysis including flooding and coastal evolution. We will explain and practice GRASS GIS data management and concepts, and demonstrate them on examples of efficient LiDAR point cloud, raster, and vector data processing.The clinic will begin with a brief introduction to the GRASS GIS software and continue with a hands-on tutorial exploring coastal evolution through a LiDAR timeseries of Bald Head Island in North Carolina, USA. Finally, we will explore some of the inundation and flood modeling tools available in GRASS GIS. The tutorial will be formatted in a series of Jupyter Notebooks executed in a cloud-based (or locally installed) JupyterLab environment, taking advantage of the latest GRASS GIS Python features for Jupyter, including 2D, 3D, webmap, and temporal visualizations. By the end of the clinic, participants will have hands-on experience with:<ul> <li>Setting up GRASS GIS Projects and importing data</li> <li>Creating high-quality DEMs from LiDAR point clouds and computing topographic parameters</li> <li>Deriving shorelines from the DEMs</li> <li>Animating changes in topography over time and computing erosion rates</li> <li>Generating simplified storm surge inundation timeseries</li></ul>rosion rates</li> <li>Generating simplified storm surge inundation timeseries</li> </ul>)
Presenters-0665 + (This clinic will introduce the concept and … This clinic will introduce the concept and implementation of a hybrid Deep Learning (DL) framework, that integrates: Convolutional Neural Network (CNN) and Long-short Term Model (LSTM), to simulate two-dimensional flood scenarios. This advanced DL framework enables spatiotemporal predictions of hydrodynamic parameters, with a particular focus on predicting water depths of flood events. Participants will first acquire a brief introduction to both models and their integration concept, followed by hands-on experience in developing a simple hybrid model using the PyTorch library. The training process will utilize a small-scale 2D flume as a practical and time-efficient exercise; however, this technique can be scaled up and applied to large stream segments in real-world scenarios. The workshop will highlight the capabilities, applications, and best practices of the developed model within the water resources domain. Notably, it will showcase the DL models’ ability to generate predictions significantly faster than traditional hydrodynamic models like HEC-RAS, which face substantial computational challenges in simulating 2D flood scenarios, especially for large-scale or long-term simulations. This workshop will equip the participants with the necessary background and technical skills for various spatiotemporal applications, encompassing geomorphological processes, groundwater dynamics, and wave-driven simulations. For this workshop, a basic understanding of machine learning in Python is recommended to maximize the benefits of this session. to maximize the benefits of this session.)
Presenters-0178 + (This clinic will look at the CSDMS Modelin … This clinic will look at the CSDMS Modeling Tool (CMT). We share the philosophy behind CMT, will demo the functionality of CMT and show what models are incorporated into it. New educational material on several models allows scientists and students to more easily use CSDMS models for classes and simple simulations and we will provide clinic participants with the latest information on these resources. The CMT clinic will be hands-on, we will run a few simple runs and visualize them. Finally, we will spend some time on discussing common problems and strategic solutions.g common problems and strategic solutions.)
Presenters-0066 + (This clinic will offer you an introduction … This clinic will offer you an introduction to developing food web models using Ecopath with Ecosim software. Ecopath with Ecosim (EwE) is an ecological modeling software suite for personal computers that has been built and extended on for almost thirty years. EwE is the first ecosystem level simulation model to be widely and freely accessible. EwE is the most applied tool for modeling marine and aquatic ecosystems globally, with over 400 models published to date, making EwE an important modeling approach to explore ecosystem related questions in marine science. In addition, Ecopath software was recognized as one of NOAA’s top ten scientific breakthroughs in the last 200 years. In this clinic, we will start with a brief introduction, then download the freeware and start setting up some simple models which we will use in example exercises. Note: the software works in a Windows environment; Mac computers can be used if they are set up with Parallels Desktop or a similar application to run programs in a Windows environment on a Mac.rograms in a Windows environment on a Mac.)
Presenters-0462 + (This clinic will offer you an introduction … This clinic will offer you an introduction to developing food web models using Ecopath with Ecosim software. Ecopath with Ecosim (EwE) is an ecological modeling software suite for personal computers that has been built and extended on for over thirty-five years. EwE is the first ecosystem level simulation model to be widely and freely accessible. EwE is the most applied tool for modeling marine and aquatic ecosystems globally, with over 400 models published to date, making EwE an important modeling approach to explore ecosystem related questions in marine science. In addition, Ecopath software was recognized as one of NOAA’s top ten scientific breakthroughs in the last 200 years. In this clinic, we will start with a brief introduction, then download the freeware and start setting up some simple models which we will use in example exercises. Note: the software works in a Windows environment; Mac computers can be used if they are set up with Parallels Desktop or a similar application to run programs in a Windows environment on a Mac.rograms in a Windows environment on a Mac.)
Presenters-0059 + (This clinic will provide an introduction t … This clinic will provide an introduction to the MATLAB-based geodynamic modeling code SiStER (Simple Stokes solver with Exotic Rheologies, available at: https://csdms.colorado.edu/wiki/Model:SiStER), with particular emphasis on problems that couple solid-Earth deformation and surface processes. Attendees will develop and run simulations where fault evolution (in rifts or orogens), lithospheric flexure and/or mantle flow interact with surficial mass redistribution through erosion and sedimentation.ibution through erosion and sedimentation.)
Presenters-0175 + (This clinic will provide information on ho … This clinic will provide information on how laboratory scale flows and field scale flows can be simulated by direct numerical simulations (DNS) and large-eddy simulations (LES) using parallel, high-performance computing facilities. DNS results, from the software TURBINS, of gravity and turbidity currents propagating over complex sea floor topography will be discussed. The use of the PETSc software package within the DNS simulations will be highlighted. LES results of high Reynolds number gravity and turbidity currents, and reversing buoyancy currents over a flat topography will be discussed. Issues relevant to LES such as grid resolution, grid convergence, subgrid models and wall-layer modeling will also be discussed.all-layer modeling will also be discussed.)
Presenters-0639 + (This experiential clinic will introduce an … This experiential clinic will introduce and have attendees incorporate personal and social components into communications of their research from design stages to presentations. Participants will be encouraged at the start to try some pre-conference exercises related to professional networking and mentoring that will be examined and discussed during a reflective exercise near the end of the workshop. Comparisons will be made between conventional samples from publications that explain science motivations with motivations they might communicate after reflecting on the social relevance of their theoretical or modeling research. Workshop exercises will involve participants making slides, infographics, workflows, and/or writing text that practice weaving together the elements of their science with personal and social relevance. Feedback will be exchanged with other participants. The goals are to build confidence amongst participants in sharing aspects of human interest in their science and build skills they can practice in the future in their collaborations, research design, and presentations. An objective is to use self- and social- awareness skills when developing their science themes and notice differences when compared with when they are not used. The possibilities are endless. All career-stages are welcome and are expected to benefit from inter-career-stage and inter-subfield communications.r-stage and inter-subfield communications.)
Presenters-0661 + (This hands-on clinic will introduce Landla … This hands-on clinic will introduce Landlab’s NetworkSedimentTransporter (NST) component, giving participants an overview of the workings of the model and a chance to explore a simple use case. The NST is a 1D morphodynamic model for gravel riverbed evolution that allows for the Lagrangian tracking of sediment. The NST operates on a network model grid, tracking the transport of individual ‘parcels’ of sediment as they pass downstream according to sediment transport equations. As these parcels move from one link (reach) to another, the grid topographic elevation and bed surface grain size distributions evolve. By the end of the clinic, participants should be able to: - Explain how sediment is represented as discrete parcels that are tracked as they transport through the network model grid- Explain how sediment parcels are transported within a link and how the model selects which parcels to transport or store- Explain how grid topographic elevations evolve as a function of the volume of parcels present on the neighboring linksUnderstand the purpose of each of the essential sections of the code needed to run the NST - Make minor edits to an example NST model script to explore model sensitivity to input parameters- Propose several possible use cases of the NSTThis clinic is appropriate for beginners with little to no experience using the Landlab library. Participants will run the model on the OpenEarthscape JupyterHub (on the cloud), so there are no specialized software requirements. Prior experience with Python programming and some knowledge of sediment transport equations is helpful but not necessary.rt equations is helpful but not necessary.)
Presenters-0667 + (This hands-on clinic will introduce partic … This hands-on clinic will introduce participants to GRASS GIS, an open-source geospatial processing engine, and Tangible Landscape, a tangible user interface for GRASS GIS. We will explain and practice GRASS GIS concepts, and work through example Python-based workflows for topics such as hydrology, flood modeling, and viewshed analysis. These workflows will be implemented as a series of computational notebooks. Then, we will show how these workflows can be configured as activities on Tangible Landscape. Using GRASS GIS as a backend, Tangible Landscape is an interactive, open-source platform that integrates physical sand models of landscapes with digital simulations by using a scanner (xBox Kinect) and projector. It allows users to interact in real-time with models by, for example, carving the sand and seeing the resulting water flow pattern. By the end of the clinic, participants will have hands-on experience with: - Setting up GRASS projects and importing data - Visibility analysis - Configuring and running overland flow models - Creating timeseries of inundation flooding - Building Tangible Landscape activities - Building Tangible Landscape activities)
Presenters-0524 + (This hands-on virtual clinic will go over … 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.es, merging / rebasing, and pull requests.)
Presenters-0535 + (This interactive clinic will provide atten … 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. 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.honing their science communication skills.)

Presenters-0448 + (This is a diversity panel discussion at the CSDMS 2019 annual meeting)

Presenters-0171 + (This model of the subglacial drainage syst … This model of the subglacial drainage system simulates the pressurised flow of water at the ice-bed interface of glaciers and ice sheets. It includes both distributed and channelized water flow. Notably the model determines the geometry of the channel network as part of the solution. The resulting channel network is similar to subaerial stream networks with channels carving out hydraulic potential "valleys". However, there are some pronounced differences to subaerial drainage, for example that the time for a network to form (and decay) is on the order of weeks to months; or that, channels originating at point sources can lie on ridges of the hydraulic potential. The model employs a novel finite element approach to solve the parabolic equations for the hydraulic potential simultaneously on the 1D channel network and 2D distributed system.channel network and 2D distributed system.)
Presenters-0002 + (This presentation provides an overview of … This presentation provides an overview of two important concepts in natural hazards—social vulnerability and community resilience. Conceptually, vulnerability and resilience are related, but they are not the opposite extensions of one another. Instead they are driven by different questions: 1) what circumstances create the social burdens of risk and how do these affect the distribution of risks and losses (e.g. vulnerability); and 2) what enhances or reduces the ability of communities to prepare for, respond to, recover from, successfully adapt to, or anticipate hazard threats, and how does this vary geographically (resilience). In order to provide the scientific basis for hazard reduction policies and practices, measurement schemes for social vulnerability and community resilience are required. This presentation reviews an existing tool for measuring social vulnerability, the Social Vulnerability Index or SoVI®, which is widely used in the USA in both hazard mitigation planning and disaster recovery. Emerging metrics for monitoring community resilience are also described, beginning with the Baseline Resilience Indicators for Communities (or BRIC) Index. The spatial patterning and temporal variability in the indices as well as the importance of scale are described. Practical examples of how BRIC and SoVI have been used in the USA by emergency managers and hazards (spatial) planning are illustrated.azards (spatial) planning are illustrated.)
Presenters-0493 + (This presentation was part of a mini virtu … This presentation was part of a mini virtual workshop around coupling of Agent Based Models (ABM) and Grid Based Models, and shows how relatively easy it is to couple Grid Based Models with ABMs.Demonstrated notebooks can be found at: https://github.com/gregtucker/abm-landlab-mini-workshopb.com/gregtucker/abm-landlab-mini-workshop)
Presenters-0492 + (This presentation was part of a mini virtu … This presentation was part of a mini virtual workshop around coupling of Agent Based Models (ABM) and Grid Based Models, and shows how relatively easy it is to couple Grid Based Models with ABMs.Demonstrated notebooks can be found at: https://github.com/gregtucker/abm-landlab-mini-workshopb.com/gregtucker/abm-landlab-mini-workshop)
Presenters-0165 + (This presentation will briefly introduce t … This presentation will briefly introduce the formulation, numerics, and parallel implementation of the coastal circulation model ADCIRC, discuss the strategy of coupling with the SWAN wave model, and provide background on recent enhancements of the bottom-friction formulation. Several recent applications of the coupled modeling system will be presented.coupled modeling system will be presented.)
Presenters-0561 + (This tutorial introduces Xarray which is a … 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.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. effectively participate in this tutorial.)
Presenters-0452 + (This two-part clinic will introduce deep l … This two-part clinic will introduce deep learning methods for semantic segmentation of high-resolution aerial imagery for the purposes of landuse/cover/form classification. The datasets we will use consist of images of shoreline environments, with a focus on general-purpose classification in terrestrial, fluvial and coastal ecology and geomorphology. Deep neural networks are the current state-of-the-art for discrete classification of remotely sensed imagery from Earth observation platforms. The clinic will guide users through the process of preparing training datasets, training models, and evaluation. A number of different deep convolutional neural network architectures for image feature extraction and pixel-scale classifications will be explored and compared. The clinic will use the keras and tensorflow libraries within the python programming language. This hands-on class will be taught using Google colab through a browser, with the materials hosted on github. Participants will require a working knowledge of python. Some working knowledge of machine learning would be helpful, but we will assume no prior experience with machine/deep learning, neural networks, tensorflow, or keras. Both the concepts and specific software would apply to many similar classification tasks at landscape scales. This clinic is composed of two, 2-hr sessions. You should sign up to both; the first clinic introduces the topic, data, and technology we use to solve the problem, and the second clinic implements these ideas and evaluates the results.'''Clinic materials can be found at:'''* https://mardascience.gitlab.io/deep_learning_landscape_classification* https://colab.research.google.com/drive/1krjeCmKoAng0BWy-4mzHVX-eAqQ9qy22?usp=sharing* https://colab.research.google.com/drive/1_ddXkrZCRne7qJ2RXHV5l3qOnk98KIyp?usp=sharingrch.google.com/drive/1_ddXkrZCRne7qJ2RXHV5l3qOnk98KIyp?usp=sharing)
Presenters-0484 + (This two-part clinic will introduce deep l … This two-part clinic will introduce deep learning methods for semantic segmentation of high-resolution aerial imagery for the purposes of landuse/cover/form classification. The datasets we will use consist of images of shoreline environments, with a focus on general-purpose classification in terrestrial, fluvial and coastal ecology and geomorphology. Deep neural networks are the current state-of-the-art for discrete classification of remotely sensed imagery from Earth observation platforms. The clinic will guide users through the process of preparing training datasets, training models, and evaluation. A number of different deep convolutional neural network architectures for image feature extraction and pixel-scale classifications will be explored and compared. The clinic will use the keras and tensorflow libraries within the python programming language. This hands-on class will be taught using Google colab through a browser, with the materials hosted on github. Participants will require a working knowledge of python. Some working knowledge of machine learning would be helpful, but we will assume no prior experience with machine/deep learning, neural networks, tensorflow, or keras. Both the concepts and specific software would apply to many similar classification tasks at landscape scales. This clinic is composed of two, 2-hr sessions. You should sign up to both; the first clinic introduces the topic, data, and technology we use to solve the problem, and the second clinic implements these ideas and evaluates the results.'''Clinic materials can be found at:'''* https://mardascience.gitlab.io/deep_learning_landscape_classification* https://colab.research.google.com/drive/1krjeCmKoAng0BWy-4mzHVX-eAqQ9qy22?usp=sharing* https://colab.research.google.com/drive/1_ddXkrZCRne7qJ2RXHV5l3qOnk98KIyp?usp=sharingrch.google.com/drive/1_ddXkrZCRne7qJ2RXHV5l3qOnk98KIyp?usp=sharing)
Presenters-0550 + (This webinar presents an overview of Landl … This webinar presents an overview of Landlab 2.0, a Python programming toolkit for rapidly building and exploring numerical models of various Earth-surface processes. We’ll look at how to set up a numerical grid in just a few lines of code, and how to populate your grid with fields of data. We will also take a look at some of Landlab’s numerical functions, input-output utilities, and plotting routines. Finally, we will explore Landlab components: what they are, how to assemble them into integrated numerical models, and how to create new ones. Examples include surface-water hydrology, landscape evolution, tidal-marsh flow, and lithosphere flexure, among others.ow, and lithosphere flexure, among others.)
Presenters-0407 + (This webinar presents an overview of the L … This webinar presents an overview of the Landlab Toolkit: a Python package that makes it much easier to create two-dimensional grid-based models of various earth-surface processes. The webinar will provide a basic overview of Landlab, and illustrate some of its key capabilities in creating grids and working with modular "process components". The webinar will also present some example applications of Landlab for model-building, and provide pointers to tutorials, user guides, and other resources for those who wish to learn more.esources for those who wish to learn more.)
Presenters-0456 + (This webinar will describe the efforts of … This webinar will describe the efforts of our NSF-funded Research Coordination Network '''Building capacity to deepen the critical zone: expanding boundaries and exploring gradients through data-model synergy.''' Our mission is to enhance the diversity of participants and ideas in the critical zone (CZ) community, integrating scientists with broad interests in biology, hydrology, geology, atmospheric science, and computational sciences with the scientific goal of understanding the structure and evolution of the deep CZ through data-model integration across scales, and an equally important outreach goal of increasing diversity and inclusion in the earth sciences. We will hold a series of small conferences, workshops and webinars, focusing on such themes as the co-evolution of the land surface and the CZ “base”, scaling up local observations to global models, the response of the CZ structure to the Anthropocene, and the emerging tools for measuring such processes, among others. This first webinar will give a broad introduction to our RCN and describe opportunities that you can partner with us if you are developing a proposal for the upcoming NSF CZ Collaboration Network call for proposals (NSF 19-586). We hope you consider working with us as part of your Broader Impacts should your theme be scientifically relevant to our mission.theme be scientifically relevant to our mission.)
Presenters-0681 + (This workshop aims to explore the capabili … This workshop aims to explore the capabilities of the Jupyter ecosystem in supporting the entire lifecycle of geospatial research. Participants will gain hands-on experience with core Jupyter tools and workflows for interactive computing, enabling collaborative engagement with geospatial data while prioritizing reproducibility and seamless sharing. A hosted JupyterHub environment will provide the foundation for practical exercises, highlighting modern workflows and demonstrating how research outcomes can be published as websites, books, or academic papers from Jupyter Notebooks and MyST Markdown.A key component of this workshop is sharing and soliciting feedback on developments from GeoJupyter, an early-stage open community initiative designed to enhance research and education workflows for geospatial data users. As much of GeoJupyter’s work is in the prototype phase, this workshop offers a unique opportunity to collaborate with our target audience to shape the ongoing evolution of geospatial interactive computing.ution of geospatial interactive computing.)
Presenters-0641 + (This workshop introduces Swiftscape, a CPU … This workshop introduces Swiftscape, a CPU/GPU-hybrid landscape evolution library with C++ and Python interfaces that can run hundreds of times faster than previous models. Participants will gain hands-on experience in both interfaces, offering flexibility and accessibility for diverse applications. Special focus will be given to the model's ability to run many simulations in parallel as well as its utility for solving inverse problems. its utility for solving inverse problems.)
Presenters-0184 + (This workshop will showcase three differen … This workshop will showcase three different models of carbonate sedimentation, produced under the CSDMS umbrella: carboCat for facies, carboCell for guilds, carboPop for communities. Participants will be able to download and run (on own or provided machines) these models in Python and Matlab environments, discuss how to select appropriate parameters for them using the various databases being developed in concert with the models, and contribute to plans for further development of models and databases.rther development of models and databases.)
Presenters-0167 + (Though it enhances the exchange of porewat … Though it enhances the exchange of porewater and solids with the overlying water, the role that sediment resuspension and redeposition play in biogeochemistry of coastal systems is debated. Numerical models of geochemical processes and diagenesis have traditionally parameterized relatively long timescales, and rarely attempted to include resuspension. Meanwhile, numerical models developed to represent sediment transport have largely ignored geochemistry. Here, we couple the Community Sediment Transport Modeling System (CSTMS) to a biogeochemical model within the Regional Ocean Modeling System (ROMS). The multi-layered sediment bed model accounts for erosion, deposition, and biodiffusion. It has recently been modified to include dissolved porewater constituents, particulate organic matter, and geochemical reactions. For this talk, we explore the role that resuspension and redeposition play in biogeochemical cycles within the seabed and in benthic boundary layer by running idealized, one-dimensional test cases designed to represent a 20-m deep site on the Louisiana Shelf. Results from this are contrasted to calculations from an implementation similar to a standard diagenesis model. Comparing these, the results indicate that resuspension acts to enhance sediment bed oxygen consumption.nsion acts to enhance sediment bed oxygen consumption.)
Presenters-0586 + (To Join: Zoom link: https://ncsu.zoom.us/j/6167058485?pwd=QUo1VUlKTTR4bWxRSEkxcTZ0SXMwZz09 Zoom ID 616-705-8485 passcode: 2021)
Presenters-0530 + (TopoFlow is a plug-and-play, spatial hydro … 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.er notebooks to explore the functionality.)
Presenters-0084 + (TopoFlow is a spatially distributed hydrol … TopoFlow is a spatially distributed hydrologic model that includes meteorology, snow melt, evapotranspiration, infiltration and flow routing components. It can model many different physical processes in a watershed with the goal of accurately predicting how various hydrologic variables will evolve in time in response to climatic forcings. In the past year, CSDMS IF staff integrated TopoFlow into the CSDMS Web Modeling Tool (WMT, https://csdms.colorado.edu/wmt) and developed new lesson plans for use with it. The first part of this clinic focuses on the technical aspects of working with TopoFlow in WMT, including how to: load and couple components, get information on a component, set parameters, upload data files, save a model, and run a model. We’ll discuss features of the TopoFlow implementation in WMT, and explain choices that were made in bringing TopoFlow to the web. In the second part of the clinic, we’ll focus on science and education. We will run several TopoFlow simulations on the CSDMS HPCC through WMT. Participants will explore parameter settings, submit runs, and view netCDF output using NASA’s Panoply tool. The learning outcomes of this clinic are to have better insight into the behavior of TopoFlow components, and the implementation of these in WMT. Participants will learn how to do TopoFlow model runs, and will have access to TopoFlow online labs and teaching resources lesson plans. will have access to TopoFlow online labs and teaching resources lesson plans.)
Presenters-0013 + (Tsunami deposits can imperfectly record th … Tsunami deposits can imperfectly record the hydraulic conditions of devastating extreme events. Sand entrainment, advection and deposition in these events occurs under strongly disequilibrium conditions in which traditional sediment transport models behave poorly. Quantitative models relating sediment characteristics to flow hydraulics hold the potential to improve coastal hazard assessments. However, data from recent natural tsunamis have rarely been accurate enough, over a range of parameter space, to quantitatively test proposed inverse models for predicting flow characteristics. To better understand how to “read” flow depth and velocity from disequilibrium deposits, we conducted controlled and repeatable laboratory flume experiments in which different grain size distributions (GSDs) of sand were entrained, transported and deposited by hydraulic bores. The bores were created by impounding and instantaneously releasing ~6 m^unding and instantaneously releasing ~6 m^)
Presenters-0166 + (Turbulence, bedload, and suspended sedimen … Turbulence, bedload, and suspended sediment transport are directly simulated by a coupled large eddy simulation of the fluid and a distinct element method for every sediment grain. This modeling system directly calculates the motion of all grains by resolved turbulence structures. The model directly calculates modification of the flow and turbulence by the grains, such as the effects of grain momentum extraction and density stratification. Simulations such as these can be used in the future to parameterize sediment transport in large-scale morphodynamic simulations. in large-scale morphodynamic simulations.)
Presenters-0130 + (Understanding and modeling the evolution o … Understanding and modeling the evolution of continental ice sheets such as Antarctica and Greenland can be a difficult task because a lot of the inputs used in transient ice flow models, either inferred from satellite or in-situ observations, carry large measurement errors that will propagate forward and impact projection assessments. Here, we aim at comprehensively quantifying error margins on model diagnostics such as mass outflux at the grounding line, maximum surface velocity and overall ice-sheet volume, applied to major outlet glaciers in Antarctica and Greenland. Our analysis relies on uncertainty quantification methods implemented in the Ice Sheet System Model (ISSM), developed at the Jet Propulsion Laboratory in collaboration with the University of California at Irvine. We focus in particular on sensitivity analysis to try and understand the local influence of specific inputs on model results, and sampling analysis to quantify error margins on model diagnostics. Our results demonstrate the expected influence of measurement errors in surface altimetry, bedrock position and basal frictionmetry, bedrock position and basal friction)
Presenters-0632 + (Understanding and predicting large scale w … Understanding and predicting large scale watershed-ecosystem dynamics requires datasets that empower research at both the local and continental scale. Yet, creating, maintaining and delivering diverse harmonized datasets to researchers and decision-makers is costly and a relatively rare endeavor. In our lab, we have been working on two different projects meant to make it easier for anyone to better understand and predict the hydrobiogeochemical behavior of watersheds, big and small. In Macrosheds, we have harmonized all of the small watershed-ecosystem datasets in the LTER, CZO, USFS, and other programs where there is, at a minimum, data on streamflow and concentration of at least one dissolved constituent (e.g. Nitrate). This dataset provides a critical complement to datasets from larger watersheds like CAMELS and CAMELS-Chem, enabling more focused interrogation of watershed behavior at the scale of small streams. Second, we are actively rebuilding and improving on AquaSat - a dataset built to empower broader use of remote sensing for water quality. This data is focused on large rivers and lakes, visible to LandSat satellites (typically wider than 60 meters). Through both of these projects, we have learned critical lessons about what data end-users actually need, how to make their lives easier, the limits of data portals, and the community required to maintain open source software.required to maintain open source software.)
Presenters-0109 + (Understanding and predicting the response … Understanding and predicting the response of vegetated ecosystems to climate change and quantifying the resulting carbon cycle feedbacks requires a coherent program of field and laboratory experiments, data synthesis and integration, model development and evaluation, characterization of knowledge gaps, and understanding of ecosystem structure and function. The U.S. Department of Energy supports such a program, which produces community data, models, and analysis capabilities aimed at projecting the impacts of environmental change on future atmospheric carbon dioxide levels, predicting changes in extreme events, and assessing impacts on energy production and use. Two computational approaches--one for quantifying representativeness of field sites and one for systematically assessing model performance--will be presented. Resource and logistical constraints limit the frequency and extent of observations, particularly in the harsh environments of the arctic and the tropics, necessitating the development of a systematic sampling strategy to maximize coverage and objectively represent variability at desired scales. These regions host large areas of potentially vulnerable ecosystems that are poorly represented in Earth system models (ESMs), motivating two new field campaigns, called Next Generation Ecosystem Experiments (NGEE) for the Arctic and Tropics, funded by the U.S. Department of Energy. We developed a Multivariate Spatio-Temporal Clustering (MSTC) technique to provide a quantitative methodology for stratifying sampling domains, informing site selection, and determining the representativeness of measurement sites and networks. We applied MSTC to model results and data for the State of Alaska to characterize projected changes in ecoregions and to identify field sites for sampling important environmental gradients. As ESMs have become more complex, there is a growing need for comprehensive and multi-faceted evaluation, analysis, and diagnosis of model results. The relevance of model predictions hinges in part on the assessment and reduction of uncertainty in predicted biogeochemical cycles, requiring repeatable, automated analysis methods and new observational and experimental data to constrain model results and inform model development. The goal of the International Land Model Benchmarking (ILAMB) project is to assess and improve the performance of land models by confronting ESMs with best-available observational data sets. An international team of ILAMB participants is developing a suite of agreed-upon model evaluation metrics and associated data at site, regional, and global scales. We are developing Open Source software tools for quantifying the fidelity of model performance, allowing modeling groups to assess confidence in the ability of their models to predict responses and feedbacks to global change. their models to predict responses and feedbacks to global change.)
Presenters-0445 + (Understanding the performance of scientifi … Understanding the performance of scientific applications can be a challenging endeavor given the constant evolution of architectures, programming models, compilers, numerical methods and the applications themselves. Performance integration testing is still not a reality for the majority of high-performance applications because of the complexity, computational cost, and lack of reliable automation. Hence, as part of the DOE SciDAC program, we are working on creating robust performance analysis workflows that capture application-specific performance issues and can be maintained and extended by the application scientists without requiring an external performance “expert”. The consumers of performance data include application developers, performance models, and autotuners. Once appropriate and sufficient performance data is available, our approach to using it to guide optimization is three-fold: (i) we investigate the most effective way to present performance results to the code developers (ii) we automate the selection of numerical methods based on generic performance models (as part of the NSF-funded Lighthouse project) and (iii) we explore the use of different types of performance models in low-level autotuning systems to reduce the size of the parameter search space. While code generation and autotuning are important for achieving performance portability, the majority of code development (including optimization) is still performed by humans. As part of the DOE IDEAS project, we are developing data-based methodologies to try to understand better how human teams work most effectively in developing high-quality, high-performance, enduring scientific software.performance, enduring scientific software.)
Presenters-0037 + (Understanding the processes that shape and … Understanding the processes that shape and reshape the earth's surface is a fundamental challenge in the geosciences. Numerical modeling—the glue between data and theory—is a key component of the effort to meet this challenge. The Community Surface Dynamics Modeling System (CSDMS) was formed to provide support for earth-surface dynamics modeling, and to accelerate the pace of discovery through software development, resource sharing, community coordination, knowledge exchange, and technical training. The CSDMS approach is bottom-up: models, typically developed within the community, are nominated by the community for inclusion within the CSDMS Modeling Framework (CMF). The CMF provides loose, two-way coupling in a Python-based framework that can scale from an individual laptop to a high-performance computing environment. The CMF has a web-based front-end, the Web Modeling Tool (WMT), that's available for use by all community members. The CMF is built on four key software technologies:<ul><li>Basic Model Interface. A Basic Model Interface (BMI), consisting of a common set of functions for initializing, running, and finalizing a model, is added to each model to be incorporated into the CMF.</li><li>Standard Names. Given variables from two models, Standard Names provides a semantic matching mechanism for determining whether—and the degree to which—the variables refer to the same quantity.</li><li>Babel. C, C++, Fortran, Java, and Python language bindings for a BMI-enabled model are generated by Babel.</li><li>Python Modeling Toolkit. The Python Modeling Toolkit (PyMT) is the framework part of the CMF, allowing Babel-wrapped models to be coupled and run in a Python environment. PyMT includes tools for time interpolation, grid mapping, data exchange, and visualization.</li></ul> In this presentation, I'll provide an overview of these core CSDMS software technologies, describing the problems they solve, how they benefit the community, and how they may accelerate scientific productivity. I'll include a Jupyter Notebook demonstration of using PyMT to interactively couple and run a landscape evolution model with a sediment transport model. I'll conclude with a list of issues still to be addressed by CSDMS.ape evolution model with a sediment transport model. I'll conclude with a list of issues still to be addressed by CSDMS.)