Property:CSDMS meeting abstract presentation
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<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. +
