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'''Derek Nueharth''' - "Evolution of divergent and strike-slip boundaries in response to surface processes"
Plate tectonics describes the movement of rigid plates at the surface of the Earth as well as their complex deformation at three types of plate boundaries: 1) divergent boundaries such as rift zones and mid-ocean ridges, 2) strike-slip boundaries where plates grind past each other, such as the San Andreas Fault, and 3) convergent boundaries that form large mountain ranges like the Andes. The generally narrow deformation zones that bound the plates exhibit complex strain patterns that evolve through time. During this evolution, plate boundary deformation is driven by tectonic forces arising from Earth’s deep interior and from within the lithosphere, but also by surface processes, which erode topographic highs and deposit the resulting sediment into regions of low elevation. Through the combination of these factors, the surface of the Earth evolves in a highly dynamic way with several feedback mechanisms. At divergent boundaries, for example, tensional stresses thin the lithosphere, forcing uplift and subsequent erosion of rift flanks, which creates a sediment source. Meanwhile, the rift center subsides and becomes a topographic low where sediments accumulate. This mass transfer from foot-to hanging wall plays an important role during rifting, as it prolongs the activity of individual normal faults. When rifting continues, continents are eventually split apart, exhuming Earth’s mantle and creating new oceanic crust. Because of the complex interplay between deep tectonic forces that shape plate boundaries and mass redistribution at the Earth’s surface, it is vital to understand feedbacks between the two domains and how they shape our planet.
Here, we use numerical models to provide insight on how surface processes influence tectonics at divergent and strike-slip boundaries through two studies. The first study takes a detailed look at the evolution of rift systems using two-dimensional models. Specifically, we extract faults from a range of rift models and correlate them through time to examine how fault networks evolve in space and time. By implementing a two-way coupling between the geodynamic code ASPECT and landscape evolution code FastScape, we investigate how the fault network and rift evolution are influenced by the system’s erosional efficiency, which represents many factors like lithology or climate. The second study uses the two-way numerical coupling between tectonics and landscape evolution to investigate how a strike-slip boundary responds to large sediment loads, and whether this is sufficient to form an entirely new type of flexural strike-slip basin.
'''Danghan Xie''' - "Responses of mangrove forests to sea-level rise and human interventions: a bio-morphodynamic modelling study"
Co-Authors - Christian Schwarz2,3, Maarten G. Kleinhans4 and Barend van Maanen5<br>
2Hydraulics and Geotechnics, Department of Civil Engineering, KU Leuven, Belgium <br>
3Department of Earth and Environmental Sciences, KU Leuven, Belgium <br>
4Department of Physical Geography, Utrecht University, Utrecht, the Netherlands<br>
5Department of Geography, University of Exeter, Exeter, UK <br>
Corresponding author: Danghan Xie (danghan@bu.edu) <br>
Mangroves preserve valuable coastal resources and services along tropical and subtropical shorelines. However, ongoing and future sea-level rise (SLR) is threatening mangrove habitats by increasing coastal flooding. Changing sediment availability, the development of coastal structures (such as barriers), and coastal restoration strategies (such as mangrove removal) not only constrain the living space of mangrove forests but also affect coastal landscape evolution. Due to limitations in studying various temporal and spatial scales in the field under SLR and human interventions, insights thus far remain inconclusive. Results of bio-morphodynamic model predictions can fill this gap by accounting for interactions between vegetation, hydrodynamic forces, and sediment transport.
Here, we present a numerical modeling approach to studying bio-morphodynamic feedbacks within mangrove forests through a coupled model technique using Delft3d and Matlab. This approach takes into account (1) multiple colonization restrictions that control not only the initial mangrove colonization but also the subsequent response to SLR, (2) the possibility of coastal progradation and seaward mangrove expansion despite SLR under high sediment supply, (3) modulation of tidal currents based on vegetation presence and coastal profile evolution which, in turn, affect mangrove growth and even species distributions, and (4) profile reconfiguration under SLR which may contribute to the infilling of new accommodation space.
Our model results display both spatial and temporal variations in sediment delivery across mangrove forests, leading to species replacements arising from landward sediment starvation and prolonged inundation. The strength of bio-morphodynamic feedbacks depends on variations in mangrove root density, which further steers the inundation-accretion decoupling and, as a result, mangrove distribution. Moreover, an extended analysis studying mangrove behaviors is conducted under varying coastal conditions, including varying tidal range, wave action, and sediment supply. The results indicate that mangroves in micro-tidal systems are most vulnerable, even if sediment availability is ample. Ultimately, coastal restoration strategies like mangrove removal aiming to reduce local mud might not be achieved due to sediment redistribution post mangrove removal, which could enhance coastal muddification.
Further reading:
* Xie, D., Schwarz, C., Brückner, M. Z., Kleinhans, M. G., Urrego, D. H., Zhou, Z., & Van Maanen, B. (2020). Mangrove diversity loss under sea-level rise triggered by bio-morphodynamic feedbacks and anthropogenic pressures. Environmental Research Letters, 15(11), 114033. https://doi.org/10.1088/1748-9326/abc122
* Xie, D., Schwarz, C., Kleinhans, M. G., Zhou, Z., & van Maanen, B. (2022). Implications of Coastal Conditions and Sea‐Level Rise on Mangrove Vulnerability: A Bio‐Morphodynamic Modeling
(Thanks to Adam LeWinter and Tim Stanton)</i></span><br><br>Rates of coastal cliff erosion are a function of the geometry and substrate of the coast; storm frequency, duration, magnitude, and wave field; and regional sediment sources. In the Arctic, the duration of sea ice-free conditions limits the time over which coastal erosion can occur, and sea water temperature modulates erosion rates where ice content of coastal bluffs is high. Predicting how coastal erosion rates in this environment will respond to future climate change requires that we first understand modern coastal erosion rates.<br><br>Arctic coastlines are responding rapidly to climate change. Remotely sensed observations of coastline position indicate that the mean annual erosion rate along a 60-km reach of Alaska’s Beaufort Sea coast, characterized by high ice content and small grain size, doubled from 7 m yr-1 for the period 1955-1979 to 14 m yr-1 for 2002-2007. Over the last 30 years the duration of the open water season expanded from ∼45 days to ∼95 days, increasing exposure of permafrost bluffs to seawater by a factor of 2.5. Time-lapse photography indicates that coastal erosion in this environment is a halting process: most significant erosion occurs during storm events in which local water level is elevated by surge, during which instantaneous submarine erosion rates can reach 1-2 m/day. In contrast, at times of low water, or when sea ice is present, erosion rates are negligible.<br><br>We employ a 1D coastal cross-section numerical model of the erosion of ice-rich permafrost bluffs to explore the sensitivity of the system to environmental drivers. Our model captures the geometry and style of coastal erosion observed near Drew Point, Alaska, including insertion of a melt-notch, topple of ice-wedge-bounded blocks, and subsequent degradation of these blocks. Using consistent rules, we test our model against the temporal pattern of coastal erosion over two periods: the recent past (~30 years), and a short (~2 week) period in summer 2010. Environmental conditions used to drive model runs for the summer of 2010 include ground-based measurements of meteorological conditions (air temperature, wind speed, wind direction) and coastal waters (water level, wave field, water temperature), supplemented by high temporal frequency (4 frames/hour) time-lapse photography of the coast. Reconstruction of the 30-year coastal erosion history is accomplished by assembling published observations and records of meteorology and sea ice conditions, including both ground and satellite-based records, to construct histories of coastline position and environmental conditions. We model wind-driven water level set-up, the local wave field, and water temperature, and find a good match against the short-term erosion record. We then evaluate which environmental drivers are most significant in controlling the rates of coastal erosion, and which melt-erosion rule best captures the coastal history, with a series of sensitivity analyses. The understanding gained from these analyses provides a foundation for evaluating how continuing climate change may influence future coastal erosion rates in the Arctic.
* Project Team 1: '''Exploring the effects of rainstorm sequences on a river hydrograph''', Brooke Hunter presenting (Brooke Hunter, University of Oregon, Celia Trunz, University of Arkansas, Lisa Luna, University of Potsdam, Tianyue Qu, University of Pittsburgh and Yuval Shmilovitz, The Hebrew University of Jerusalem ).
* Project Team 2: '''Coupling grids with different geometries and scales: an example from fluvial geomorphology''', Rachel Bosch presenting (Rachel Bosch, University of Cincinnati, Shelby Ahrendt, University of Washington, Francois Clapuyt, Université Catholique de Louvain, Eric Barefoot, Rice University, Mohit Tunwal, Penn State University, Vinicius Perin, North Carolina State University, Edwin Saavedra Cifuentes, Northwestern University, Hima Hassenruck-Gudipati, University of Texas Austin and Josie Arcuri, Indiana University).
* Project Team 3: '''Lagrangian particle transport through a tidal estuary''', Rachel Allen presenting (Rachel Allen, UC Berkeley, Ningjie Hu, Duke University, Jayaram Hariharan, University of Texas, Aleja Geiger-Ortiz, Colby College and Collin Roland, University of Wisconsin).
* Project Team 4: '''Using Landlab to Model Tectonic Activities in a Landscape Evolution Model''', Gustav Pallisgaard-Olesen presenting (Gustav Pallisgaard-Olesen, Aarhus University, Xiaoni Hu, Penn State University, Eyal Mardar, Colorado State University, Liang Xue, Bowling Green State University, and Chris Sheehan, University of Cincinnati).
* Project Team 5: '''Land geomorphology evolution over a continuous permafrost region by applying Ku-model and hillslope diffusion model''', Zhenming Wu presenting( Zhenming Wu, University of Reeding and Fien De Doncker, University of Lausanne).
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11:00AM '''Introductions'''
'''11:05AM Project Team 1: "Simulating Shoreline Change Using Coupled CoastSat and Coastline Evolution Model (CEM)"''', Ahmed Elghandour, TU Delft, Benton Franklin, UNC, Conner Lester, Duke U, Megan Gillen, MIT/WHOI, Meredith Leung, Oregon State U & Samuel Zapp, LSU.
Sandy shorelines are areas of dynamic geomorphic change, evolving on timescales ranging from hours to centuries. As part of the CSDMS ESPIn workshop, this educational lab was designed to allow users to observe firsthand the long-term change of a sandy coast of their choosing and explore the processes driving that change. The CEM was developed by Ashton et al. (2001) as an exploratory model that uses wave climate characteristics to model the evolution of an idealized coastline. In this educational lab, we couple CoastSat (a python tool that extracts shoreline geometry from satellite imagery (Vos et al., 2019)) to the CEM by initializing the model with observed shorelines from anywhere in the world. The CEM is then further driven by an average wave climate derived from local buoy data. This allows users to visualize the evolution of any sandy beach in the world through time. Through an introductory-level coding exercise, users will learn how to extract complex datasets, run a geomorphic model, and explore the impact of different wave climates on a beach they care about.
'''11:15AM Project Team 2: "Including wildfires in a landscape evolution model"''', Kevin Pierce, UBC, Laurent Roberge, Tulane U Nishani Moragoda, U Alabama.
Wildfires modify sediment inputs to streams by removing vegetation and encouraging overland flow. Unfortunately our ability to calculate sediment delivery from wildfires remains limited. Here, we present a stochastic wildfire component we recently developed for Landlab. This work provides a new computational method to relate stream sediment yields to the frequency and magnitude of wildfires.
'''11:25AM Project Team 3: "Landscape-Scale Modeling across a variable-slip fault "''', Emery Anderson-Merritt, U Mass, Tamara Aranguiz, UW, Katrina Gelwick, ETH Zurich, Francesco Pavano, Lehigh U, & Josh Wolpert, U Toronto.
The accommodation of deformation along a strike-slip fault can result in oblique kinematics featuring along-strike gradients in horizontal and vertical components of movement. While strike-slip fault models often simplify factors such as channel sedimentation, erosion processes and channel geometry, complex rock uplift fields related to oblique faulting may significantly impact the dynamics of a drainage system. With the objective of representing these along-strike kinematic variations commonly observed in strike-slip fault settings, we modify an existing Landlab component for lateral faulting (Reitmann et al., 2019) to incorporate spatially variable rock uplift. Our simulations demonstrate landscape evolution in an oblique faulting setting, highlighting the complicated response of a landscape’s drainage network and other geomarkers.
'''11:35AM Project Team 4: "Paleoclimate and Elevation Data Used to Implement the Frost Cracking Window Concept”''', Risa Madoff, U North Dakota, Jacob Hirschberg, Swiss Federal Research Inst, Allie Balter LDEO/Columbia U.
Frost cracking is a key weathering process in cold environments (e.g., Hales & Roering). Concepts from previous work on frost cracking (Anderson, 1998) provide foundations for understanding regional controls on landscape evolution. Recent research applying transient climate records and the frost-cracking model to estimate weathering rates (Marshall et al., 2021) represent ways that computational approaches are being adopted in the community. To bring a frost-cracking model into the CSDMS framework, we combined elevation-scaled PMIP6 paleoclimate data with a soil thermal profile model extant in the CSDMS repository (Tucker, 2020) to estimate frost-cracking intensity at a landscape scale. Our frost-cracking model is hosted in an EKT Jupyter notebook for instructional and exploratory applications of the thermal diffusion equation and the relationship between temperature and landscape development. In the future, our model could be implemented to compare modeled frost-cracking intensities with contemporary geomorphology in regions with differing climate histories.
'''11:45AM Project Team 5: "Make storms, make erosion: How do storm intensity, duration, and frequency influence river channel incision."''', Angel Monsalve, U Idaho, Sam Anderson, Tulane U, Safiya Alpheus, Penn State U, Muriel Bruckner, U Exeter, Mariel Nelson, UT, Austin, Grace Guryan, UT, Austin.
Erosion in the river bed is usually associated with a representative scale of stream power or shear stress of a given flow discharge. However, on a catchment scale, assuming a constant, steady-state flow of water in channels may not be adequate to represent the erosion process because of the temporal and spatial variability in rainfall. We coupled three different landLab components (OveralndFlow, DetachmentLimitedErosion, and SpatialPrecipitationDistribution) to create a more realistic representation of the topography evolution at a basin-scale and analyze the influence of storm intensity, duration, and frequency on channel incision.
'''11:55AM Project Team 6: "Simulation of sediment pulses in Landlab NetworkSedimentTransporter (NST) component"''', Se Jong Cho, USGS, Muneer Ahammad, Virginia Tech, Marius Huber, U de Lorraine, Mel Guirro, Durham U.
We synthetically introduce sediment pulses to simulate erosive conditions, which may be caused by fire or landslide occurrences in the landscape, and sediment yield across river network using the Landlab NetworkSedimentTransporter (NST) component. The goal of the project is to couple existing landlab models with external drivers of sediment sources and other input conditions that drive sediment transport.
'''12:05-12:15PM Team 7: "Simulating Craters on Planetary Surfaces"''', Emily Bamber, UT Austin, Gaia Stucky de Quay, Harvard
Impact cratering has been and still is the main geomorphic process on many planetary bodies, and is therefore key to understanding the evolution of planetary surfaces and their habitability. There are existing numerical models of planetary surface evolution that include cratering, but they are written in Fortran. As part of the CSDMS ESPIn 2021 summer workshop, we used the concepts for simulating crater shape and frequency on the surface from Howard (2007), and wrote a python code to simulate cratering, specifically on Mars. This code is freely available on GitHub, and currently utilises the LandLab model grid, which means our model integrates easily with the numerous landscape evolution modules that already exist as part of LandLab. An educational lab detailing the approach to simulating craters has also been produced and is available on the CSDMS website.
<i>Background</i><br>When it comes to building a general, efficient, surface process code, there are a couple of significant challenges that stand in our way. One is to address the interesting operators that appear in the mathematical formulation that are not commonly encountered in computational mechanics. The other is to cater for the many different formulations that have been put forward in the literature as no single, universal set of equations has been agreed upon by the community.<br><br><i>Computational Approach</i><br>We view Quagmire as a community toolbox and acknowledge that this means there is no one best way to formulate any of the landscape evolution models. We instead provide a collection of useful operators and examples of how to assemble various kinds of models. We do assume that:<br><ul><li>the surface is a single-valued height field described by the coordinates on a two-dimensional plane</li><li>the vertical evolution can be described by the time-derivative of the height field</li><li>the horizontal evolution can be described by an externally imposed velocity field</li><li>the formulation can be expressed through (non-linear) operators on the two dimensional plane</li><li>any sub-grid parameterisation (e.g. of stream bed geometry) is expressible at the grid scale</li><li>a parallel algorithm is desirable</li></ul>We don't make any assumptions about:<br><ul><li>the nature of the mesh: triangulation or a regular array of 'pixels'</li><li>the parallel decomposition (except that it is assumed to be general)</li><li>the specific erosion / deposition / transport model</li></ul>Quagmire is a collection of python objects that represent parallel vector and matrix operations on meshes and provide a number of useful surface-process operators in matrix-vector form. The implementation is through PETSc, numpy, and scipy. Quagmire is open source and a work in progress.<br><br><i>Mathematical Approach</i><br>Matrix-vector multiplication is the duct tape of computational science: fast, versatile, ubiquitous. Any problem that can be formulated in terms of basic linear algebra operations can usually be rendered into an abstract form that opens up multiple avenues to solve the resulting matrix equations and it is often possible to make extensive use of existing fast, parallel software libraries. Quagmire provides parallel, matrix-based operators on regular Cartesian grid and unstructured triangulations for local operations such as gradient evaluation, diffusion, smoothing but also for non-local, graph-based operations that include catchment identification, upstream summation, and flood-filling. <br>The advantage of the formulation is in the degree of abstraction that is introduced, separating the details of the discrete implementation from the solution phase. The matrix-based approach also makes it trivial to introduce concepts such as multiple-pathways in graph traversal / summation operations without altering the structure of the solution phase in any way. Although we have not yet done so, there are obvious future possibilities in developing implicit, non-linear solvers to further improve computational performance and to place the model equations in an inverse modelling framework.
A comprehensive understanding of hydrologic processes affecting streamflow is required to effectively manage water resources to meet present and future human and environmental needs. The National Hydrologic Model (NHM), developed by the U.S. Geological Survey, can address these needs with an approach supporting coordinated, comprehensive, and consistent hydrologic modeling at multiple scales for the conterminous United States. The NHM fills knowledge gaps in ungaged areas, providing nationally consistent, locally informed, stakeholder relevant results. In this presentation, we will introduce the NHM and a publicly available Dockerized version that is currently providing daily operational results of water availability and stream temperature. We finish with a quick demonstration of a new experimental version of PRMS, the NHMs underlying hydrologic model, available through the CSDMS Python Modeling Toolkit (pymt). +
A presentation from Phaedra and Greg, that was presented at the Modeling Collaboratory
for Subduction Research Coordination Network Webinar Series, that features conversations between the leaders of successful interdisciplinary collaborations (see also https://www.sz4dmcs.org/webinars). +
A range of Earth surface processes may drive rapid ice sheet retreat in the future, contributing to equally rapid global sea level rise. Though the pace of discovering these new feedback processes has accelerated in the past decade, predictions of future evolution of ice sheets are still subject to considerable uncertainty, originating from unknown future carbon emissions, and poorly understood ice sheet processes. In this talk, I explain why sea level rise projections past the next few decades are so uncertain, and how we are developing new stochastic ice sheet modeling methods to reduce uncertainty in projections, and the limits of uncertainty reduction. I also discuss the ongoing debate over whether uncertainty is important to consider at all in developing sea level projections that are usable by coastal planners. +
A recent trend in the Earth Sciences is the adaptation of so-called “Digital Twins”. In Europe multi-million and even multi-billion projects are initiated for example, the Digital Twin of the Ocean and the Digital Twin Earth. But also many smaller digital-twin projects are popping up in the fields of city management, tunnels, hydraulic structures, waterways and coastal management.
But what are Digital Twins really? Why are they now trending? What makes a Digital Twin different from a serious game, a numerical model or a simulator? In this session we will look at examples of digital twins, we will compare them to more traditional platforms and together define our expectations on future digital twins. +
A wide variety of hydrological models are used by hydrologists: some differ because they were designed for different applications, some because of personal preferences of the modeller. All of them share the property that, like most scientific research code, it is rather hard to get someone elses model to run. The recently launched eWaterCycle platform takes away the headache of working with each other's models. In eWaterCycle models are run in containers and communicate with the central (Jupyter based) runtime environment through BMI. In this way a user can be talking to a Fortran model from Python without having to know anything about Fortran.
Removing this headache allows hydrologists to easily run and couple each other's models facilitating science questions like the impact of model choice on results, or coupling different (regional, processes) models together with ease. In this talk I will highlight (and demonstrate) both the technology behind the eWaterCycle platform as well as the current and future research being done using the platform. +
ANUGA is an open source software package capable of simulating small-scale hydrological processes such as dam breaks, river flooding, storm surges and tsunamis. ANUGA is a Python-language model that solves the Shallow Water Wave Equation on an unstructured triangular grid and can simulate shock waves and rapidly changing flows. It was developed by the Australian National University and Geosciences Australia and has an active developer and user community.<br><br>The package supports discontinuous elevation, or ‘jumps’ in the bed profile between neighbouring cells. This has a number of benefits. Firstly it can preserve lake-at-rest type stationary states with wet-dry fronts. It can also simulate very shallow frictionally dominated flow down sloping topography, as typically occurs in direct-rainfall flood models. A further benefit of the discontinuous-elevation approach, when combined with an unstructured mesh, is that the model can sharply resolve rapid changes in the topography associated with e.g. narrow prismatic drainage channels, or buildings, without the computational expense of a very fine mesh. The boundaries between such features can be embedded in the mesh using break-lines, and the user can optionally specify that different elevation datasets are used to set the elevation within different parts of the mesh (e.g. often it is convenient to use a raster digital elevation model in terrestrial areas, and surveyed channel bed points in rivers). The discontinuous-elevation approach also supports a simple and computationally efficient treatment of river walls. These are arbitrarily narrow walls between cells, higher than the topography on either side, where the flow is controlled by a weir equation and optionally transitions back to the shallow water solution for sufficiently submerged flows. This allows modelling of levees or lateral weirs which are much finer than the mesh size.<br><br>This clinic will provide a hands-on introduction to hydrodynamic modeling using ANUGA. We will discuss the structure and capabilities of the model as we build and run increasingly complex simulations involving channels and river walls. No previous knowledge of Python is required. Example input files will be provided and participants will be able to explore the code and outputs at their own pace.
ANUGA is an open source software package capable of simulating small-scale hydrological processes such as dam breaks, river flooding, storm surges and tsunamis. Thanks to its modular structure, we’ve incorporated additional components to ANUGA that allow it to model suspended sediment transport and vegetation drag. ANUGA is a Python-language model that solves the Shallow Water Wave Equation on an unstructured triangular grid and can simulate shock waves and rapidly changing flows. It was developed by the Australian National University and Geosciences Australia and has an active developer and user community.<br><br>This clinic will provide a hands-on introduction to hydrodynamic modeling using ANUGA. We will discuss the structure and capabilities of the model as we build and run increasingly complex simulations. No previous knowledge of Python is required. Example input files will be provided and participants will be able to explore the code and outputs at their own pace. +
Accurately characterizing the spatial and temporal variability of water and energy fluxes in many hydrologic systems requires an integrated modeling approach that captures the interactions and feedbacks between groundwater, surface water, and land- surface processes. Increasing recognition that these interactions and feedbacks play an important role in system behavior has lead to exciting new developments in coupled surface-subsurface modeling, with coupled surface-subsurface modeling becoming an increasingly useful tool for describing many hydrologic systems.<br><br>This clinic will provide a brief background on the theory of coupled surface-subsurface modeling techniques and parallel applications, followed by examples and hands-on experience using ParFlow, an open-source, object-oriented, parallel watershed flow model. ParFlow includes fully-integrated overland flow; the ability to simulate complex topography, geology and heterogeneity; and coupled land-surface processes including the land-energy budget, biogeochemistry, and snow processes. ParFlow is multi-platform and runs with a common I/O structure from laptop to supercomputer. ParFlow is the result of a long, multi-institutional development history and is now a collaborative effort between CSM, LLNL, UniBonn, and UC Berkeley. Many different configurations related to common hydrologic problems will be discussed through example problems. +
Addressing society's water and energy challenges requires sustainable use of the Earth's critical zones and subsurface environment, as well as technological innovations in treatment and other engineered systems. Reactive transport models (RTMs) provide a powerful tool to inform engineering design and provide solutions for these critical challenges. In this keynote, I will showcase the flexibility and value of RTMs using real-world applications that focus on (1) assessing groundwater quality management with respect to nitrate under agricultural managed aquifer recharge, and (2) systematically investigating the physical, chemical and biological conditions that enhance CO2 drawdown rates in agricultural settings using enhanced weathering. The keynote will conclude with a discussion of the possibilities to advance the use of reactive transport models and future research opportunities therein. +
Agent-Based Modeling (ABM) or Individual-Based Modeling is a research method rapidly increasing in popularity -- particularly among social scientists and ecologists interested in using simulation techniques to better understand the emergence of interesting system-wide patterns from simple behaviors and interactions at the individual scale. ABM researchers frequently partner with other scientists on a wide variety of topics related to coupled natural and human systems. Human societies impact (and are impacted by) various earth systems across a wide range of spatial and temporal scales, and ABM is a very useful tool for better understanding the effect of individual and social decision-making on various surface processes. The clinic will focus on introducing the basic toolkit needed to understand and pursue ABM research, and consider how ABM work differs from other computational modeling approaches. The clinic: - Will explore examples of the kinds of research questions and topics suited to ABM methods. - Will (attempt to) define some key concepts relevant to ABM research, such as emergence, social networks, social dilemmas, and complex adaptive systems. - Will provide an introduction to ABM platforms, particularly focused on NetLogo. - Discuss approaches to verification, validation, and scale dependency in the ABM world. - Introduce the Pattern-Oriented Modeling approach to ABM. - Discuss issues with reporting ABM research (ODD specification, model publishing). - Brainstorm tips and tricks for working with social scientists on ABM research. +
Agent-Based Models (ABMs) can provide important insights into the nonlinear dynamics that emerge from the interactions of individual agents. While ABMs are commonly used in the social and ecological sciences, this rules-based modeling approach has not been widely adopted in the Surface Dynamics Modeling community. In this clinic, I will show how to build mixed models that utilize ABMs for some processes (e.g., forest dynamics and soil production) and numerical solutions to partial differential equations for other processes (e.g., hillside sediment transport). Specifically, I will introduce participants to pyNetLogo, a library that enables coupling between NetLogo ABMs and Python-based Landlab components. While active developers in either the NetLogo or Landlab communities will find this clinic useful, experience in both programming languages is not needed. +
Agent-based modeling (ABM) developed as a method to simulate systems that include a number of agents – farmers, households, governments as well as biological organisms – that make decisions and interact according to certain rules. In environmental modeling, ABM is one of the best ways to explicitly account for human behavior, and to quantify cumulative actions of various actors distributed over the spatial landscape. This clinic provides an introduction to ABM and covers such topics as:<ol><li>Modeling heterogeneous agents that vary in attributes and follow different decision-strategies</li><li>Going beyond rational optimization and accommodating bounded rationality</li><li>Designing/representing agents’ interactions and learning.</ol>The clinic provides hands-on examples using the open-source modeling environment NetLogo https://ccl.northwestern.edu/netlogo. While no prior knowledge of NetLogo is required, participants are welcome to explore its super user-friendly tutorial. The clinic concludes with highlighting the current trends in ABM such as its applications in climate change research, participatory modeling and its potential to link with other types of simulations. +
Agent-based modeling (ABM) is a powerful simulation tool with applications across disciplines. ABM has also emerged as a useful tool for capturing complex processes and interactions within socio-environmental systems. This workshop will offer a brief introduction to ABM for socio-environmental systems modeling including an overview of opportunities and challenges. Participants will be introduced to NetLogo, a popular programming language and modeling environment for ABM. In groups, participants will have the hands-on opportunity to program different decision-making methods in an existing model and observe how outcomes change. We will conclude with an opportunity for participants to raise questions or challenges they are experiencing with their own ABMs and receive feedback from the group. +
An abstract was not required for this meeting +
An overview of what the interagency Working Group stands for. +
An update of what CSDMS has accomplished so far. +
An update of what CSDMS has accomplished so far. +
An update on CoMSES. +
Answers to scientific questions often involve coupled systems that lie within separate fields of study. An example of this is flexural isostasy and surface mass transport. Erosion, deposition, and moving ice masses change loads on the Earth surface, which induce a flexural isostatic response. These isostatic deflections in turn change topography, which is a large control on surface processes. We couple a landscape evolution model (CHILD) and a flexural isostasy model (Flexure) within the CSDMS framework to understand interactions between these processes. We highlight a few scenarios in which this feedback is crucial for understanding what happens on the surface of the Earth: foredeeps around mountain belts, rivers at the margins of large ice sheets, and the "old age" of decaying mountain ranges. We also show how the response changes from simple analytical solutions for flexural isostasy to numerical solutions that allow us to explore spatial variability in lithospheric strength. This work places the spotlight on the kinds of advances that can be made when members of the broader Earth surface process community design their models to be coupleable, share them, and connect them under the unified framework developed by CSDMS. We encourage Earth surface scientists to unleash their creativity in constructing, sharing, and coupling their models to better learn how these building blocks make up the wonderfully complicated Earth surface system. +
Are you confused about the best way to make your models and data accessible, reusable, and citable by others? In this clinic we will give you tools, information, and some dedicated time to help make your models and data FAIR - findable, accessible, interoperable and reusable. Models in the CSDMS ecosystem are already well on their way to being more FAIR than models that are not. But here, you will learn more about developments, guidelines, and tools from recent gatherings of publishers, repository leaders, and information technology practitioners at recent FAIR Data meetings, and translate this information into steps you can take to make your scientific models and data FAIR. +
Are you interested in expanding the reach of your scientific data or models? One way of increasing the FAIRness of your digital resources (i.e., making them more findable, accessible, interoperable, and reproducible) is by annotating them with metadata about the scientific variables they describe. In this talk, we provide a simple introduction to the Scientific Variables Ontology (SVO) and show how, with only a small number of design patterns, it can be used to neatly unpack the definitions of even quite complex scientific variables and translate them into machine-readable form. +
Are you tired of hearing about the FAIR Principles? This clinic is for you then, because after you participate you’ll never need to attend another one!*
Good science depends on the careful and meticulous management and documentation of our research process. This includes our computational models, the datasets we use, the data transformation, analysis, and visualization scripts and workflows we build to evaluate and assess our models, and the assumptions and design decisions we make while writing our software.
Join us for a Carpentries-style interactive clinic with hands-on exercises where we will provide concrete guidance and examples for how to approach, conceptualize, and transform your computational models of earth systems into FAIR contributions to the scientific record whether they are greenfield projects or legacy code with a focus on existing, open infrastructure (GitHub / GitLab / Zenodo). We’ll also cover containerization (Docker, Apptainer) as a way to transparently document system and software dependencies for your models, and how it can be used to support execution on the Open Science Grid Consortium’s Open Science Pool fair-share access compute resources. Big parallel fun! https://osg-htc.org
∗ individual results may vary, this statement is provably false +
As agreed at earlier CSDMS forums, the major
impediment in using AI for modeling the deep-ocean
seafloor is a lack of training data, the data which guides the AI -
whichever set of algorithms is chosen. This clinic will expose participants to
globally-extensive datasets which are available through CSDMS.
It will debate the scientific questions of why certain data work well,
are appropriate to the processes, and are properly scaled.
Participants are encouraged to bring their own AI challenges to the clinic. +
As global population grows and infrastructure expands, the need to understand and predict processes
at and near the Earth’s surface—including water cycling, soil erosion, landsliding, flood
hazards, permafrost thaw, and coastal change—becomes increasingly acute. Progress in understanding
and predicting these systems requires an ongoing integration of data and numerical
models. Advances are currently hampered by technical barriers that inhibit finding, accessing,
and operating modeling software and related tools and data sets. To address these challenges, we present the CSDMS@HydroShare, a cloud-based platform for accessing and running models, developing model-data workflows, and sharing reproducible results.
CSDMS@HydroShare brings together cyberinfrastructure developed by two important community facilities: HydroShare (https://www.hydroshare.org/), which is an online collaboration environment for sharing data, models, and tools, and CSDMS Workbench (https://csdms.colorado.edu/wiki/Workbench), which is the integrated system of software tools, technologies, and standards for building, interfacing, and coupling models.
This workshop presents how to use CSDMS@HydroShare to discover, access, and operate the Python Modeling Tool (PyMT). PyMT is one of the tools from the CSDMS Workbench, which allows users to interactively run and couple numerical models contributed by the community. In PyMT, there are already model components for coastal & permafrost modeling, stratigraphic and subsidence modeling, and terrestrial landscape evolution modeling. It also includes data components to access and download hydrologic and soil datasets from remote servers to feed the model components as inputs.
This workshop aims to encourage the community to use existing or develop new model or data components under the PyMT modeling framework and share them through CSDMS@HydroShare to support reproducible research. This workshop includes hands-on exercises using tutorial Jupyter Notebooks and provides general steps for how to develop new components.
At a global scale, deltas significantly concentrate people by providing diverse ecosystem services and benefits for their populations. At the same time, deltas are also recognized as one of the most vulnerable coastal environments, due to a range of adverse drivers operating at multiple scales. These include global climate change and sea-level rise, catchment changes, deltaic-scale subsidence and land cover changes, such as rice to aquaculture. These drivers threaten deltas and their ecosystem services, which often provide livelihoods for the poorest communities in these regions. Responding to these issues presents a development challenge: how to develop deltaic areas in ways that are sustainable, and benefit all residents? In response to this broad question we have developed an integrated framework to analyze ecosystem services in deltas and their linkages to human well-being. The main study area is part of the world’s most populated delta, the Ganges-Brahmaputra-Meghna Delta within Bangladesh. The framework adopts a systemic perspective to represent the principal biophysical and socio-ecological components and their interaction. A range of methods are integrated within a quantitative framework, including biophysical and socio-economic modelling, as well as analysis of governance through scenario development. The approach is iterative, with learning both within the project team and with national policy-making stakeholders. The analysis allows the exploration of biophysical and social outcomes for the delta under different scenarios and policy choices. Some example results will be presented as well as some thoughts on the next steps. +
Bed material abrasion is a key control on the partitioning of basin scale sediment fluxes between coarse and fine material. While abrasion is traditionally treated as a simple exponential function of transport distance and a rock-specific abrasion coefficient, experimental studies have demonstrated greater complexity in the abrasion process: the rate of abrasion varies with clast angularity, transport rate, and grain size. Yet, few studies have attempted to assess the importance of these complexities in the field setting. Furthermore, existing approaches generally neglect the heterogeneity in size, abrasion potential, and clast density of the source sediment.
Combining detailed field measurements and new modeling approaches, we quantify abrasion in the Suiattle River, a basin in the North Cascades of Washington State dominated by a single coarse sediment source: large, recurrent debris flows from a tributary draining Glacier Peak stratovolcano. Rapid downstream strengthening of river bar sediment and a preferential loss of weak, low-density vesicular volcanic clasts relative to non-vesicular ones suggest that abrasion is extremely effective in this system. The standard exponential model for downstream abrasion fails to reproduce observed downstream patterns in lithology and clast strength in the Suiattle, even when accounting for the heterogeneity of source material strength and the underestimate of abrasion rates by tumbler experiments. Incorporating transport-dependent abrasion into our model largely resolves this failure. These findings hint at the importance of abrasion and sediment heterogeneity in the morphodynamics of sediment pulse transport in river networks. A new modeling tool will allow us to tackle these questions: the NetworkSedimentTransporter, a Landlab component to model Lagrangian bed material transport and channel bed evolution. This tool will allow for future work on the interplay of bed material abrasion and size selective transport at the basin scale.
While a simplified approach to characterizing abrasion is tempting, our work demonstrates that sediment heterogeneity and transport-dependent abrasion are important controls on the downstream fate of coarse sediment in fluvial systems.
Biostabilizing organisms, such as saltmarsh and microphytobenthos, can play a crucial role in shaping the morphology of estuaries and coasts by locally stabilizing the sediment. However, their impact on large-scale morphology, which highly depends on the feedback between spatio-temporal changes in their abundance and physical forcing, remains highly uncertain.
We studied the effect of seasonal growth and decay of biostabilizing organisms, in response to field calibrated physical forcings, on estuarine morphology over decadal timescales using a novel eco-morphodynamic model. The code includes temporal saltmarsh an microphytobenthos growth and aging as well as spatially varying vegetation fractions determined by mortality pressures. Growth representations are empirical and literature-based to avoid prior calibration.
Novel natural patterns emerged in this model revealing that observed density gradients in vegetation are defined by the life-stages that increase vegetation resilience with age. The model revealed that the formation of seasonal and long term mud layering is governed by a ratio of flow velocity and hydroperiod altered by saltmarsh and microphytobenthos differently, showing that the type of biostabilizer determines the conditions under which mud can settle and be preserved. The results show that eco-engineering effects define emerging saltmarsh patterns from a combination of a positive effect reducing flow velocities and a negative effect enhancing hydroperiod. Consequently, saltmarsh and mud patterns emerge from their bilateral interactions that hence strongly define morphological development. +
CSDMS 3.0 updates +
CSDMS Basic Model Interface (BMI) - When equipped with a Basic Model Interface, a model is given a common set of functions for configuring and running the model (as well as getting and setting its state). Models with BMIs can communicate with each other and be coupled in a modeling framework. The coupling of models from different authors in different disciplines may open new paths to scientific discovery. In this first of a set of webinars on the CSDMS BMI, we'll provide an overview of BMI and the functions that define it. This webinar is appropriate for new users of BMI, although experienced users may also find it useful.
'''Instructor:''' Mark Piper, Research Software Engineer, University of Colorado, Boulder
'''When:''' November 13th, 12PM Eastern Time +
