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Presenters-0314 + (No abstract was required for this meeting)
Presenters-0315 + (No abstract was required for this meeting)
Presenters-0316 + (No abstract was required for this meeting)
Presenters-0317 + (No abstract was required for this meeting)
Presenters-0318 + (No abstract was required for this meeting)
Presenters-0319 + (No abstract was required for this meeting)
Presenters-0320 + (No abstract was required for this meeting)
Presenters-0395 + (No abstract was required for this meeting.)
Presenters-0197 + (No abstract was required for this workshop)
Presenters-0242 + (No abstracts was required for this meeting)
Presenters-0428 + (Numerical modeling is at the core of predi … Numerical modeling is at the core of prediction in coastal settings. Observational data is used in tandem with models for a variety of modeling tasks, but the perhaps the coupling could be tighter? I will discuss a range of Machine Learning tools that co-workers and I have integrated with coastal morphodynamic models that allow for a tight coupling of models and data, and provide morphodynamic insight.d data, and provide morphodynamic insight.)
Presenters-0573 + (Numerical models describe the world around … Numerical models describe the world around us mathematically, allowing us to visualize changes to physical systems through both space and time. These models are essential tools for geoscientists, but writing your own model can be a daunting task. In this clinic, we’ll develop an understanding of what numerical models are, and then we’ll delve into the math that functions as the basis for many models. Participants will learn how to apply basic conservation principles to developing equations that describe a physical system that changes through time. This workshop will expose participants to deriving differential equations, and using basic Python programming to visualize their solutions. Prior experience is not necessary.utions. Prior experience is not necessary.)
Presenters-0562 + (Numerical stratigraphic modelling of the i … Numerical stratigraphic modelling of the impact of paleoclimate changes on earthscape evolution and sedimentary basin stratigraphy is of great value to better understand and predict the impact of global warming and increasingly frequent extreme events on the environment. To illustrate the contribution of stratigraphic modelling, we propose a modular model, ArcaDES (a.k.a. Dionisos), able to simulate geological processes in 3D on large scales of space and times (tens to hundreds of kilometres, and thousands to tens of millions of years). ArcaDES is a 3D software written in C++ and implemented within the Arcane object-oriented high-performance computing platform co-developed by the CEA and IFPEN. This modular code includes three main components to handle hydrology, accommodation space and sediment transport. Taking into account precipitation, evaporation and soil infiltration capacity, the first component calculates steady-state runoff, surface and ground water flows, and water table elevation. The second component considers tectonic subsidence and uplift, flexure, sea level variations and sediment compaction to define the accommodation space. The third component deals with time-averaged physical laws describing erosion, transport by fluvial and marine currents, and deposition of sediments from fluvial to deep-marine systems to calculate sediment distribution and stratigraphic architecture. This stratigraphic forward model is applied to two case studies: the Congo basin and the Alboran sea, to illustrate the impact of the last Holocene glaciations on the deep-sea fan of the Congo and the contouritic systems in the Alboran Sea.he contouritic systems in the Alboran Sea.)
Presenters-0045 + (Observations in coastal environments show … Observations in coastal environments show that seabed resuspension can impact water quality and biogeochemical dynamics by vertically mixing sediment and water, and by redistributing material that has been entrained into the water column. Yet, ocean models that incorporate both sediment transport and biogeochemical processes are rare. The scientific community frequently utilizes hydrodynamic-sediment transport numerical models, but hydrodynamic-biogeochemical models ignore or simplify sediment processes, and have not directly accounted for the effect of resuspension on oxygen and nutrient dynamics. This presentation focuses on development and implementation of HydroBioSed, a coupled hydrodynamic-sediment transport-biogeochemistry model that was developed within the open-source Regional Ocean Modeling System (ROMS) framework. HydroBioSed can account for processes including advection, resuspension, diffusion within the seabed and at the sediment-water interface, organic matter remineralization, and oxidation of reduced chemical species. Implementation of the coupled HydroBioSed model for different locations, including the Rhone River subaqueous delta and the northern Gulf of Mexico, have helped to quantify the effects of both sediment transport and biogeochemical processes. Results indicate that resuspension-induced exposure of anoxic, ammonium-rich portions of the seabed to the more oxic, ammonium-poor water column can significantly affect seabed-water column fluxes of dissolved oxygen and nitrogen. Also, entrainment of seabed organic matter into the water column may significantly draw down oxygen concentrations in some environments. Ongoing work focuses on how resuspension and redistribution of organic matter and sediment may influence oxygen dynamics in the Chesapeake Bay.t may influence oxygen dynamics in the Chesapeake Bay.)
Presenters-0522 + (One of the challenges for modelers is to g … 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).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. scientific communication and interaction.)
Presenters-0124 + (One of the most intriguing issues in fine … One of the most intriguing issues in fine sediment transport, including turbidity currents, current-driven transport and wave-driven transport, is that the presence of sediments may significantly attenuate flow turbulence. Depending on the level of turbulence suppression, it may lead to the formation of lutocline (a sharp negative gradient of sediment concentration) which further encourages offshore-directed gravity flow; or it may cause catastrophic collapse of turbulence and sediment deposition. Through idealized 3D turbulence-resolving simulations of fine sediment (mud) transport in wave bottom boundary layer based on a pseudo-spectral scheme, our recent studies show that the transition of these flow modes can be caused by various degree of sediment-induced stable density stratification. This effort demonstrates the success of using a turbulence-resolving simulation tool to diagnose complex fine sediment transport processes. This talk further reports our recent development of this turbulence-resolving numerical model with a goal to provide a predictive tool for more realistic fine sediment transport applications. Assuming a small Stokes number (St<0.3), which is appropriate for typical fine sediment, the Equilibrium approximation to the Eulerian two-phase flow equations is applied. The resulting simplified equations are solved with a high-accuracy hybrid spectral-compact finite difference scheme. The numerical approach extends the earlier pseudo-spectral model with a sixth-order compact finite difference scheme in the bed-normal direction. The compact finite difference scheme allows easy implementation of flow-dependent sediment properties and complex bottom boundary conditions. Hence, several new capabilities are included in the numerical simulation, such as rheological stress (enhance viscosity in high sediment concentration), hindered settling, erodible/depositional bottom boundary, and higher order inertia terms critical for fine sand fraction. In the past decade, the role of wave bottom boundary layer in delivering fine sediment offshore via wave-supported gravity current (WSGC) has been well-recognized. We hypothesize that the generation, transport and termination of WSGC is directly associated with the flow modes discussed previously. In addition to the well-known Richardson number control (i.e., associated with sediment-induced density stratification), in this talk we will discuss how enhanced viscosity via rheological stress and high erodibility of the mud bed (e.g., low critical shear stress for unconsolidated mud bed) can trigger catastrophic collapse of turbulence and sediment deposition. The significance of bed erodibility in determining the resulting flow modes motivates future study regarding the effect of sand fraction on fine sediment transport via armoring. the effect of sand fraction on fine sediment transport via armoring.)
Presenters-0091 + (OpenFoamÒ is an open-source computational … OpenFoamÒ is an open-source computational fluid dynamic platform, built upon a finite-volume framework with Messaging Passing Interface (MPI). In the past decade, OpenFoamÒ has become increasingly popular among researchers who are interested in fluvial and coastal processes. In this clinic, recent progress in developing OpenFoamÒ for several coastal applications will be discussed. In particular, we will focus on three subjects: (1) wave-induced seabed dynamics (pore-pressure response), (2) stratified flow application, particularly laboratory scale river plume modeling, and (3) 3D large-eddy simulation of wave-breaking and suspended sediment transport processes. In particular, hand-on exercise will be given for 3D large-eddy simulation of wave-breaking processes to illustrate several important insights on how to use OpenFoamÒ to carry out high quality large-eddy simulations. Some cautionary notes and limitations will also be discussed.ry notes and limitations will also be discussed.)
Presenters-0619 + (Opening of the CSDMS 2023 annual meeting)
Presenters-0095 + (Opening of the CSDMS annual meeting)
Presenters-0029 + (Opening of the meeting)
Presenters-0161 + (Opening of the meeting)
Presenters-0489 + (Opening of the meeting)
Presenters-0047 + (Our extensive transdisciplinary efforts si … Our extensive transdisciplinary efforts since 2010 in the northern Gulf of Mexico (Mississippi, Alabama, and the Florida panhandle) have resulted in an advanced capability to model and assess hydrodynamic and ecological impacts of climate change at the coastal land margin (visit http://agupubs.onlinelibrary.wiley.com/hub/issue/10.1002/(ISSN)2328-4277.GULFSEARISE1/). The concerted efforts of natural and social scientists as well as engineers have contributed to a paradigm shift that goes well beyond “bathtub” approaches. Potential deleterious effects to barrier islands, shorelines, dunes, marshes, etc., are now better understood. This is because the methodology enables assessment of not just eustatic sea level rise (SLR), but gets to the basis of projections of climate change and the associated impacts, i.e., carbon emission scenarios. The paradigm shift, input from coastal resource managers, and future expected conditions now provides a rationale to evaluate and quantify the ability of natural and nature-based feature (NNBF) approaches to mitigate the present and future effects of surge and nuisance flooding. Over the majority of the 20th century, the largely linear rate of eustatic SLR was realized by thermal expansion of seawater as a function of a gradual increase in the average annual global temperature. Global satellite altimetry indicates that the rate of global mean SLR has accelerated from approximately 1.6 to 3.4 mm/year. While the year-by-year acceleration of the rate of rise cannot be measured adequately, it is reasonable to assume that it was relatively stable throughout the 20th century. For the 21st century, general circulation models project that posed atmospheric carbon emission scenarios will result in higher global average temperatures. A warmer global system will introduce new mechanisms (e.g., land ice loss, isotatic adjustments, and changes in land water storage) that will contribute to relatively abrupt changes in sea state levels. The additions to thermal expansion will drive higher sea levels and the increases in sea level will be attained by further accelerations in the rate of the rise. Because of the nature of the new mechanisms that will govern sea levels, it is unlikely that future accelerations in the rate of rise will be smooth. To further address the complications associated with relatively abrupt changes in SLR and related impacts of climate change at the coastal land margin we intend to: (1) refine, enhance, and extend the coupled dynamic, bio-geo-physical models of coastal morphology, tide, marsh, and surge; (2) advance the paradigm shift for climate change assessments by linking economic impact analysis and ecosystem services valuation directly to these coastal dynamics; (3) pursue transdisciplinary outcomes by engaging a management transition advisory group throughout the entire project process; and (4) deliver our results via a flexible, multi-platform mechanism that allows for region-wide or place-based assessment of NNBFs. This presentation will share examples of our recent efforts and discuss progress to-date.es of our recent efforts and discuss progress to-date.)
Presenters-0422 + (Our understanding of human systems has bee … Our understanding of human systems has been synthesized and advanced by computationally representing human decision-making in agent-based models. Whether representing individuals, households, firms, or larger organization, agent-based modelling approaches are often used to model processes (e.g., urban growth, agricultural land management) that directly effect and are affected by natural systems. Contemporary efforts coupling models of human and natural systems have demonstrated that results significantly differ from isolated representations of either system. However, coupling models of human and natural systems is conceptually and computationally challenging. In addition to discussing these challenges and approaches to overcoming them, this talk will also suggest that research quantifying natural processes at the decision-making scale of the land user is needed. Using structure-from-motion and unmanned aerial vehicle (UAV) imagery, we can accurately quantify natural processes like soil erosion to a high level of accuracy and that frequently modelled processes (e.g., flow accumulation) typically differ from reality. Novel data from the field or parcel scale are needed to calibrate and validate our representation of natural processes if we are to advance our representation of feedbacks between natural processes and human decision-making. By improving our representation of both natural processes and human decision-making at the scale of the decision-maker, we add confidence in our ability to scale out to larger spatial extents that are reflective of natural processes (e.g., watershed) or policy driving human decisions from municipal, state, or national governments.municipal, state, or national governments.)
Presenters-0471 + (Overview and Update of CSDMS accomplishments)

Presenters-0583 + (Panel discussion)

Presenters-0446 + (Panel discussion on AI/ML)
Presenters-0412 + (Parametric insurance represents a major br … Parametric insurance represents a major breakthrough in the accessibility of risk financing for natural disasters. Instead of compensating for actual assessed loss, parametric (or index-based) insurance instead uses measurement of the hazard itself as a proxy for loss, paying out a pre-agreed amount for an event with certain intensity, location and, sometimes, duration. This allows for rapid settlement and reduced costs – of claims adjustment / processing and in the margin added by risk takers for uncertainty in projected outcomes. The quantitative, independent and objective nature of EO data, and also its availability in real time, makes it ideal as a basis for parametric insurance, particularly in the developing world where claims data for policy pricing is non-existent. Examples of parametric products based on EO data already in the market include protection against high and low rainfall, use of vegetation greenness indices, and footprint mapping as a basis for flood protection.t mapping as a basis for flood protection.)
Presenters-0589 + (Part 1 will focus on the use of Doodler (h … Part 1 will focus on the use of Doodler (https://github.com/Doodleverse/dash_doodler), a 'human-in-the-loop' labeling tool for image segmentation (described in this paper: https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021EA002085). We'll cover the two primary uses of Doodler; a) for relatively rapid image segmentation of a small set of images, and b) for making libraries of labeled imagery for training Machine Learning models to automate the process of image segmentation on larger datasets. We'd ideally like participants to label the same imagery in-class so we can discuss image interpretation and label agreement. This may even result in a publishable dataset; participants would receive co-authorship and could opt-in/out.We will provide example datasets and models, but participants will also be encouraged to bring their own imagery sets. That way, participants will have time to familiarize themselves with the burgeoning Doodleverse tools (https://github.com/Doodleverse) in between classes on their own data.rse) in between classes on their own data.)
Presenters-0590 + (Part 2 will focus on the use of Segmentati … Part 2 will focus on the use of Segmentation Gym (https://github.com/Doodleverse/segmentation_gym), for training and implementing deep-learning-based image segmentation models. Participants will be given datasets and models to use for their own model building and implementation, or optionally they may use their own data, for example label images they made in Part 1. Hardware needs, and common problems and their workarounds will be discussed.s and their workarounds will be discussed.)
Presenters-0141 + (Participants in this clinic will learn how … Participants in this clinic will learn how to compile and run a Regional Ocean Modeling (ROMS) test case for an idealized continental shelf. The hydrodynamic model that we will use includes wave forcing and suspended sediment transport. ROMS is an open source, three dimensional primitive equation hydrodynamic ocean model that uses a structured curvilinear horizontal grid and a stretched terrain following vertical grid. For more information see https://www.myroms.org. It currently has more than 4,000 registered users, includes modules for sediment transport and biogeochemistry, and has several options for turbulence closures and numerical schemes. Model input is specified using a combination of ASCII text files and NetCDF (Network Common Data Form) files. Output is written to NetCDF files. In part because ROMS was designed to provide flexibility for the choice of model parameterizations and processes, and to run in parallel, implementing the code can seem daunting, but in this clinic we will present an idealized ROMS model that can be run on the CSDMS cluster. As a group, we will compile and run an idealized ROMS model on the CSDMS computer, Beach. The group will choose a modification to the standard model. While the modified model runs, we will explore methods for visualizing model output. Participants who have an account on Beach can try to run the model themselves. Clinic participants who have Matlab set up to visualize NetCDF files will be able to browse model output files during the clinic. Following the clinic, participants should have access to tools for looking at ROMS output, an example ROMS model run, and experience with ROMS input and output files.t, an example ROMS model run, and experience with ROMS input and output files.)
Presenters-0090 + (Participants in this clinic will learn how … Participants in this clinic will learn how to run a Regional Ocean Modeling System (ROMS) test case for an idealized continental shelf model domain within the CSDMS Web Modeling Toolkit (WMT). The model implementation that we will use includes wave forcing, a riverine source, suspended sediment transport. ROMS is an open source, three-dimensional primitive equation hydrodynamic ocean model that uses a structured curvilinear horizontal grid and a stretched terrain following vertical grid. For more information see https://www.myroms.org. It currently has more than 4,000 registered users, and the full model includes modules for sediment transport and biogeochemistry, and several options for turbulence closures and numerical schemes. In part because ROMS was designed to provide flexibility for the choice of model parameterizations and processes, and to run in parallel, implementing the code can seem daunting, but in this clinic, we will present an idealized ROMS model that can be run on the CSDMS cluster via the WMT. One goal is to provide a relatively easy introduction to the numerical modeling process that can be used within upper level undergraduate and graduate classes to explore sediment transport on continental shelves. As a group, we will run an idealized ROMS model on the CSDMS computer, Beach. The group will choose a modification to the standard model. While the modified model runs, we will explore methods for visualizing model output. Participants who have access to WMT can run the model themselves. Clinic participants who have access to Matlab and/or Panoply will be able to browse model output files during the clinic. Following the clinic, participants should have access to an example ROMS model run, experience running ROMS within the WMT and with ROMS input and output files, and. ROMS lesson plans.S within the WMT and with ROMS input and output files, and. ROMS lesson plans.)
Presenters-0612 + (Participatory modeling (PM) is a collabora … Participatory modeling (PM) is a collaborative approach to formalize shared representations of a problem and design and test solutions through a joint modeling process. PM is well-suited for addressing complex social and environmental problems like climate change, social and economic injustice, and sustainable resource management. This workshop will introduce and test a prototype version of Fora.ai, a new PM platform developed at Northeastern University. Fora.ai is a simple digital environment that enables groups to collaboratively understand real world problems and create novel solutions. Stakeholders interact through this digital representation with input from other stakeholders, then iteratively revise and test solutions until diverse needs are addressed. Fora.ai provides quick simulation results for data-driven proof of concepts that are ready to be presented, designed, and implemented in the real world, giving everyone in a team the power to share their unique perspective and build the world they want to live in together.d the world they want to live in together.)
Presenters-0638 + (Participatory modeling (PM) is a collabora … Participatory modeling (PM) is a collaborative approach to formalize shared representations of a problem and design and test solutions through a joint modeling process. PM is well-suited for addressing complex social and environmental problems like climate change, social and economic injustice, and sustainable resource management. This workshop will introduce and test a prototype version of Fora.ai, a new PM platform developed at Northeastern University. Fora.ai is a simple digital environment that enables groups to collaboratively understand real world problems and create novel solutions. Stakeholders interact through this digital representation with input from other stakeholders, then iteratively revise and test solutions until diverse needs are addressed. Fora.ai provides quick simulation results for data-driven proof of concepts that are ready to be presented, designed, and implemented in the real world, giving everyone in a team the power to share their unique perspective and build the world they want to live in together.d the world they want to live in together.)
Presenters-0061 + (Permafrost is one of the Arctic climate in … Permafrost is one of the Arctic climate indicators, and feedback of thawing permafrost to the global climate system through the impacts on the carbon cycle remains an important research topic. Observations can assess the current state of permafrost, but models are eventually essential to make predictions of future permafrost state. In this 2hr clinic, we will present a new, easy-to-access and comprehensive cyberinfrastructure for permafrost modeling. The ‘PermaModel Integrated Modeling Toolbox’ includes three permafrost models of increasing complexity. The IMT is embedded within the Community Surface Dynamics Modeling System Web Modeling Tool (WMT). We include multiple sets of sample inputs, representing a variety of climate and soil conditions and locations, to enable immediate use of the IMT. The hands-on clinic teaches students and researchers how to run and use several permafrost models. The presented models are envisioned to be the suitable for quick exploration of hypotheses and for teaching purposes.k exploration of hypotheses and for teaching purposes.)
Presenters-0015 + (Permafrost is one of the Arctic climate in … Permafrost is one of the Arctic climate indicators, and feedback of thawing permafrost to earth surface processes and vice versa is a research frontier. Observations can assess the current state of permafrost, but models are eventually essential to make predictions of future permafrost state and impacts on surface processes. In this 2hr clinic, we will present a new, easy-to-access and comprehensive cyberinfrastructure for permafrost modeling. The ‘Permafrost Modeling Toolbox’ includes three permafrost models of increasing complexity. The tools are embedded within the Community Surface Dynamics Modeling System Web Modeling Tool. We include multiple sets of sample inputs, representing a variety of climate and soil conditions and locations, to enable immediate use of the tools. The hands-on clinic teaches students and researchers how to run and use several permafrost models with associated datasets. The presented models are envisioned to be the suitable for quick exploration of hypotheses and for teaching purposes. We will also explore options for model coupling, demonstrating an example of a model of coastal/delta sedimentation in permafrost environments./delta sedimentation in permafrost environments.)
Presenters-0603 + (Plastic pollution is a ubiquitous issue im … Plastic pollution is a ubiquitous issue impacting the health of marine ecosystems worldwide. Yet, critical knowledge gaps surrounding the fate and transport of plastic once it enters the ocean impede remediation and prevention efforts. Predicting transport is difficult for any particle in the ocean, but microplastics present a particular challenge because their size and density fall outside the regimes of traditionally studied environmental particles such as low-density bubbles and high-density sediment. In this talk I will discuss recent work addressing these challenges with both modelling and experiments.enges with both modelling and experiments.)
Presenters-0072 + (Plate tectonics is the primary process con … Plate tectonics is the primary process controlling the Earth’s surface topography. In recent years, geodynamicists have emphasised the role that deep mantle flow may play in directly creating long wavelength, low amplitude topography (a so-called “dynamic” contribution to surface topography). In parallel, geomorphologists have investigated how surface processes (erosion, transport and sedimentation) may affect dynamic topography, with the aim of better understanding its signature in the geological record. To achieve this, we have developed a new class of surface processes models that represent the combined effects of physical erosion and chemical alteration within continental interiors. In developing these models, we have paid much attention to maintaining high efficiency and stability such that they could be used to model large continental areas with sufficient spatial resolution to represent the processes at the appropriate scale. I will briefly present these algorithms as well as the results of two separate studies in which we explain the anomalously rapid erosion of surface material during the passage of a continent over a fixed source of dynamic topography driven by upward flow in the mantle. I will also comment on how these models are strongly dependent on precipitation patterns and, ultimately, will need to be fully coupled to climate models to provide more meaningful constraints on the past evolution of surface topography. the past evolution of surface topography.)
Presenters-0468 + (Predicting long-term Earth surface change, … Predicting long-term Earth surface change, the impacts of short-term natural hazards and biosphere/geosphere dynamics requires computational models. Many existing numerical models quantitatively describe sediment transport processes, predicting terrestrial and coastal change at a great variety of scales. However, these models often address a single process or component of the earth surface system. The Community Surface Dynamics Modeling System is an NSF-funded initiative that supports the open software efforts of the surface processes community. CSDMS distributes >200 models and tools, and provides cyberinfrastructure to simulate lithosphere, hydrosphere, atmosphere, or cryosphere dynamics. Many of the most exciting problems in these fields arise at the interfaces of different environments and through complex interactions of processes.This workshop presents recent cyberinfrastructure tools for hypothesis-driven modeling— the Python Modeling Tool (PyMT) and LandLab. PyMT allows users to interactively run and couple numerical models contributed by the community. There are already tools for coastal & permafrost modeling, stratigraphic and subsidence modeling, and terrestrial landscape evolution modeling (including hillslope, overflow, landslide processes, and a suite of erosion processes with vegetation interactions), and these are easy to run and further develop in a Python environment. This 2-part tutorial aims to provide a short overview of the PyMT and Landlab, a demonstration of running a coupled model, and hands-on exercises using Jupyter notebooks in small groups of attendees. The organizers will facilitate break-out groups for discussion of pressing research needs and then have a plenary discussion with reports of each of the breakouts on future frontier applications of coupled landscape/bioscape process modeling.Materials for this clinic can be found at: https://github.com/csdms/csdms-2020 be found at: https://github.com/csdms/csdms-2020)
Presenters-0485 + (Predicting long-term Earth surface change, … Predicting long-term Earth surface change, the impacts of short-term natural hazards and biosphere/geosphere dynamics requires computational models. Many existing numerical models quantitatively describe sediment transport processes, predicting terrestrial and coastal change at a great variety of scales. However, these models often address a single process or component of the earth surface system. The Community Surface Dynamics Modeling System is an NSF-funded initiative that supports the open software efforts of the surface processes community. CSDMS distributes >200 models and tools, and provides cyberinfrastructure to simulate lithosphere, hydrosphere, atmosphere, or cryosphere dynamics. Many of the most exciting problems in these fields arise at the interfaces of different environments and through complex interactions of processes.This workshop presents recent cyberinfrastructure tools for hypothesis-driven modeling— the Python Modeling Tool (PyMT) and LandLab. PyMT allows users to interactively run and couple numerical models contributed by the community. There are already tools for coastal & permafrost modeling, stratigraphic and subsidence modeling, and terrestrial landscape evolution modeling (including hillslope, overflow, landslide processes, and a suite of erosion processes with vegetation interactions), and these are easy to run and further develop in a Python environment. This 2-part tutorial aims to provide a short overview of the PyMT and Landlab, a demonstration of running a coupled model, and hands-on exercises using Jupyter notebooks in small groups of attendees. The organizers will facilitate break-out groups for discussion of pressing research needs and then have a plenary discussion with reports of each of the breakouts on future frontier applications of coupled landscape/bioscape process modeling.Materials for this clinic can be found at: https://github.com/csdms/csdms-2020 be found at: https://github.com/csdms/csdms-2020)
Presenters-0643 + (Process-based modeling offers interpretabi … Process-based modeling offers interpretability and physical consistency in many domains of geosciences but struggles to leverage large datasets efficiently. Machine-learning methods, especially deep networks, have strong predictive skills yet are not easily interpretable and are unable to answer specific scientific questions. A recently proposed genre of physics-informed machine learning, called “differentiable” modeling (DM, https://t.co/qyuAzYPA6Y), trains neural networks (NNs) with process-based equations (priors) together in one stage (so-called “end-to-end”) to benefit from the best of both NNs and process-based paradigms. The NNs do not need target variables for training but can be indirectly supervised by observations matching the outputs of the combined model, and differentiability critically supports learning from big data. We propose that differentiable models are especially suitable as global- or continental-scale geoscientific models because they can harvest information from big earth observations to produce state-of-the-art predictions (https://mhpi.github.io/benchmarks/), enable physical interpretation naturally, extrapolate well (due to physical constraints) in space and time, enforce known physical laws and sensitivities, and leverage progress in modern AI computing architecture and infrastructure. Differentiable models can also synergize with existing process-based models in terms of providing to them parameters or identifying optimal processes, learning from the lessons of the community. Differentiable models can answer pressing societal questions on water resources availability, climate change impact assessment, water management, and disaster risk mitigation, among others. We demonstrate the power of differentiable modeling using computational examples in rainfall-runoff modeling, river routing, ecosystem and water quality modeling, and forcing fusion. We discuss how to address potential challenges such as implementing gradient tracking for implicit numerical schemes and addressing process tradeoffs. Furthermore, we show how differentiable modeling can enable us to ask fundamental questions in hydrologic sciences and get robust answers from big global data.d get robust answers from big global data.)
Presenters-0131 + (Process-based models are able to predict v … Process-based models are able to predict velocity fields, sediment transport and associated morphodynamic developments over time. These models can generate realistic morphological patterns and stable morphodynamic developments over time scales of millennia under schematized model settings. However, more realistic case studies raise questions on model skill and confidence levels. Process-based models require detailed information on initial conditions (e.g. sediment characteristics, initial distribution of sediment fractions over the model domain), process descriptions (e.g. roughness and sediment transport formulations) and forcing conditions (e.g. time varying hydrodynamic and sediment forcing). The value of the model output depends to a high degree on the uncertainty associated with these model input parameters. Our study explores a methodology to quantify model output uncertainty levels and to determine which parameters are responsible for largest output uncertainty. Furthermore we explore how model skill and uncertainty develop over time. We describe the San Pablo Bay (USA) case study and the Western Scheldt (Netherlands) case study in a 100 year hindcast and a more than 100 year forecast. Remarkably, model skill and uncertainty levels depend on model input parameter variations only to a limited extent. Model skill is low first decades, but increases afterwards to become excellent after 70 years. The possible explanation is that the interaction of the major tidal forcing and the estuarine plan form governs morphodynamic development in confined environments to a high degree.rphodynamic development in confined environments to a high degree.)
Presenters-0543 + (Proposed in 2018, the Open Modeling Founda … Proposed in 2018, the Open Modeling Foundation (OMF) initiative aims to establish an international open science community to enable the next generation modeling of human and natural systems. The OMF is envisioned as an alliance of modeling organizations that develops and administers a community-wide open modeling standards and best practices for the social, ecological, environmental, and geophysical sciences. It will support these efforts though informational, data, and technological resources for the scientific communities it serves. This webinar reviews the history of the OMF, its current status, future plans, and how scientists can participate in this initiative.ntists can participate in this initiative.)
Presenters-0436 + (PyMT is the “Python Modeling Toolkit”. It … PyMT is the “Python Modeling Toolkit”. It is an Open Source Python package, developed by the Community Surface Dynamics Modeling System, that provides tools used to couple models that expose the Basic Model Interface (BMI). PyMT is:* a toolbox for coupling models of disparate time and space scales,* a collection of Earth-surface models, and* an extensible plug-in framework for user-contributed models.In this hands-on clinic we will use Jupyter Notebooks to explore how to run standalone models within PyMT. Since all PyMT models are based on the BMI, they all share the same user interface and so if you know how to run one model, you know how to run all PyMT models. We will then look at some of the model-coupling tools packaged with PyMT and how they can be used for more complex couplings. We will then run through examples that use these tools to couple models to data as well as to other PyMT models.We highly recommend that clinic attendees come with a laptop with the Anaconda Python distribution installed.he Anaconda Python distribution installed.)
Presenters-0538 + (Quantitative analysis is often indispensab … 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.ng impact in a wide range of policy areas.)
Presenters-0536 + (R has been widely used by ecologists. It i … 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. 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. 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.land change in response to sea-level rise.)
Presenters-0146 + (Recent additions to Python have made it an … Recent additions to Python have made it an increasingly popular language for data analysis. In particular, the pandas library provides an R-like data-fame in Python, which is data structure that resembles a spreadsheet. This provides an efficient way to load, slice, reshape, query, summarize, and visualize your data. Combining this with numpy, maplotlib, and scikit-learn creates a powerful set of tools for data analysis. In this hands-on tutorial, we will cover the basics of numpy, matplotlib, pandas, and introduce scikit-learn.otlib, pandas, and introduce scikit-learn.)
Presenters-0129 + (Recent technological advances in data coll … Recent technological advances in data collection techniques have yielded opportunities to better quantify stratigraphic stacking patterns, flow processes and sedimentation from outcrops of ancient sediment transport systems. These advancements created opportunities for field geologists to reduce uncertainty in the interpretation of the stratigraphic record and have likewise created data sets from which the efficacy of numerical models and physical experiments can be evaluated. The goals of this presentation are to (1) review some combined outcrop-model based studies, (2) discuss how these integrated studies test model and field-based uncertainty, and (3) share a vision for how field geologists and modelers can leverage from each other’s perspectives. Five examples of studies that bridged the gap between outcrop stratigraphy and experimental and/or numerical models include: (1) documentation of how mineralogy varies spatially in submarine fans, (2) relating flow processes to sedimentation in sinuous submarine channels, (3) evaluating compensational stacking in deltas and submarine fans, (4) relating stratigraphic architecture of deltas to inherited water depth and seafloor gradient, and (5) testing how shelf-edge deltas pipe coarse-grained sediment to submarine fans. These and similarly focused studies are important because they used common workflows and quantitative methods to evaluate similarities and differences between modeled and natural systems, resulting in a more complete view of the processes and products being studied. Whereas common workflows can provide a means to test the efficacy of physical and numerical modeling, it is critical to consider how modeling sheds insight into how one interprets the stratigraphic record from outcrop and subsurface data sets.igraphic record from outcrop and subsurface data sets.)
Presenters-0102 + (Recent theoretical work suggests that auto … Recent theoretical work suggests that autogenic processes in sediment transport systems have the capacity to shred signals of environmental and tectonic perturbations prior to transfer to the stratigraphic record. We view this theory as a major conceptual and quantitative breakthrough in long time scale Earth-surface processes and stratigraphy, but the general theory still needs to be adapted to deal with specific types of signals. Many argue that the tug of Relative Sea Level (RSL) change represents the most important boundary condition forcing affecting continental margin transport systems. However, we still lack quantitative theory to explain what properties RSL cycles must have to be stored in stratigraphy, thus limiting the usefulness of stratigraphy for defining paleo-environments. Results from our previously conducted laboratory experiments suggest that RSL cycles with amplitudes less than a channel depth and of periodicities less than the amount of time necessary to deposit, on average, one channel depth of stratigraphy over a delta-top are susceptible to signal shredding. Our hypothesis is supported using existing data sets and new numerical and physical experiments in which the surface process response and preserved record of RSL cycles of varying magnitudes and periodicities is constrained. Quantitative theory and predictions produced from this work is benchmarked against stratigraphy from the Late Miocene to Quaternary stratigraphy of the Mississippi Delta. During this time interval a significant change in the magnitude and periodicity of RSL cycles occurred. RSL cycles in the Late Miocene for the Mississippi Delta are predicted to be shredded, while more recent cycles are predicted to be preserved.cent cycles are predicted to be preserved.)
Presenters-0419 + (Repeated continental glaciation of the US … Repeated continental glaciation of the US Central Lowlands disrupted pre-Pleistocene fluvial drainage networks by filling valleys, rerouting major rivers, and incising oversize meltwater channels. Post-glacial landscapes are characterized by large fractions of non contributing area (NCA) which does not contribute flow to external drainage networks by steepest decent algorithms. Analysis of land surfaces most recently glaciated between 130,000 and 10,000 years ago suggests that NCA is lost over time as fluvial networks are reestablished. Low surface slopes combined with significant fractions of NCA make such fluvial network growth difficult to reconcile with standard treatments of flow routing. We develop modules in Land Lab that allow for connection of NCA via filling and spilling from closed depressions on the surface and through groundwater flow across subtle surface water divides to explore the impacts of these mechanisms of flow accumulation on the pace of evolution and morphology of resulting river networks. This work highlights the more general need to consider the relationship, or lack of relationship, between topography and river discharge.p, between topography and river discharge.)
Presenters-0043 + (Reporting to the community of what CSDMS has accomplished and what can be expected with CSDMS 3.0)