Click here to download the final meeting agenda (5/3/2022).
North Carolina State University
Simulating linkages between landscape evolution and coastal real estate markets with the CoAStal Community-lAnDscape Evolution (CASCADE) model Developed barriers are tightly-coupled systems driven by feedbacks between natural processes and human decisions to maintain development. Coastal property markets are dynamically linked to the physical environment: large tax revenues and high-value infrastructure necessitate defensive coastal management through beach nourishment, dune development, overwash removal, and construction of hard structures. In turn, changes to environmental characteristics such as proximity to the beach, beach width, and the height of dunes influence coastal property values. In this talk I will use a new exploratory model framework – the CoAStal Community-lAnDscape Evolution (CASCADE) model – to explore the coupled evolution of coastal real estate markets and barrier landscapes. The framework couples two geomorphic models of barrier evolution (Barrier3D and BRIE) with an agent-based real estate model – the Coastal Home Ownership Model (CHOM). CHOM receives information about the coastal environment and acts on that information to cause change to the environment, including decisions about beach nourishment and dune construction and maintenance. Through this coupled model framework, I will show how the effects of dune and beach management strategies employed in the wake of extreme storms cascade through decades to alter the evolution of barriers, inadvertently inhibiting their resilience to sea level rise and storms, and ultimately unraveling coastal real estate markets.
Modeling big unknowns in climate adaptation research – an example from mobility in coastal Bangladesh I will discuss an application of the Migration, Intensification, and Diversification as Adaptive Strategies (MIDAS) agent-based modeling framework to modeling labor migration across Bangladesh under the stressor of sea-level rise (SLR). With this example, I hope to highlight some hard-to-resolve challenges in representing adaptive decision-making under as-yet unexperienced stressors in models. Drawing together what is more and what is less known in projections for future adaptation, I will discuss strategies for ‘responsible’ presentation and dissemination of model findings.
University of Exeter
Modeling Climate Change Impacts on Mountain Basin Sediment Transfer Sediment production and transfer processes shape river basins and networks and are driven by variability in precipitation, runoff and temperature. Changes in these hydrological and geomorphological processes are especially difficult to predict in temperature-sensitive environments such as the European Alps. We used a model chain to quantify possible impacts of climate change on sediment transfer and hazard in a debris flow-prone catchment in the Swiss Alps (Illgraben). We combined a stochastic weather generator1 with downscaled and bias-corrected climate change projections2 to generate climate simulations. These climate simulations then feed the hillslope-channel sediment cascade model, SedCas3, which is calibrated against observed debris-flow magnitudes estimated from force plate measurements4, to make predictions of sediment transfer and debris flow hazard in the Illgraben over the 21st century5. The results demonstrate the complex interplay between hydrology, sediment production and elevation in alpine catchment response to climate change. The hydrological potential to transport sediment and generate debris flows will increase, driven by increases in precipitation and air temperature. Indeed, if sediment supply to the channel by landslides were unlimited, this would result in an increase in future sediment yield of 48% by the end of the century. However, sediment transfer is also a function of sediment supply by landslides at the head of the catchment, driven by highly temperature sensitive freeze-thaw processes6. At the elevation of the Illgraben (<2000 m), freeze-thaw processes and thus sediment supply will decrease in a warming climate resulting in a decrease in sediment yield of 48% by the end of the century. This result and the competition between hydrological debris flow triggering potential and sediment supply is highly elevation dependent. As we increase mean catchment elevation, sediment production increases due to decreased snow cover and increased exposure of bedrock to freeze-thaw weathering, with implications for the application of findings to other catchments. Although uncertainties in our results are large, we show that these can mostly be attributed to irreducible internal climate variability. Our findings have important implications for the assessment of natural hazards and risks in mountain environments.REFERENCES1 Fatichi et al., 2011: Simulation of future climate scenarios with a weather generator2 National Centre for Climate Services, 2018: CH2018 - Climate Scenarios for Switzerland3 Bennett et al., 2014: A probabilistic sediment cascade model of sediment transfer in the Illgraben4 McArdell et al., 2007: Field observations of basal forces and fluid pressure in a debris flow5Hirshberg et al., 2021: Climate change impacts on sediment yield and debris flow activity6 Bennett et al., 2013: Patterns and controls of sediment production, transfer and yield in the Illgraben
Neil Chue Hong
University of Edinburgh
Software sustainability and FAIR for research software - what does this mean for research into environmental extremes? Software sustainability - the ability for software to continue to function - and the FAIR principles (Findable, Accessible, Interoperable and Reusable) are important features of software used in research. But how do they apply to research into environmental extremes? In this presentation, I will summarise the work of the Software Sustainability Institute, including my work on the FAIR principles for research software, and what we understand about the challenges and benefits of applying software sustainability and FAIR to this area.
University of Colorado
Panel discussion on environmental extremes Panel discussion
University of Arizona
ProDF: A reduced-complexity model for debris-flow inundation Debris flows pose a substantial threat to downstream communities in mountainous regions across the world, and there is a continued need for methods to delineate hazard zones associated with debris-flow inundation. Here we present ProDF, a reduced-complexity debris-flow inundation model. We calibrated and tested ProDF against observed debris-flow inundation from eight study sites across the western United States. While the debris flows at these sites varied in initiation mechanism, volume, and flow characteristics, results show that ProDF is capable of accurately reproducing observed inundation in different settings and geographic areas. ProDF reproduced observed inundation while maintaining computational efficiency, suggesting the model may be applicable in rapid hazard assessment scenarios.
University of Virginia
Global Hydrological Water Cycle Extremes The variability of the water cycle causes extremes such as droughts and floods and these have an impact on society. In the past two decades with the advent of improved satellite sensors, modeling and in-situ observations, quantification of these extremes has become possible. This talk will be based on characterization of floods and droughts in global continental river basins that can be used for monitoring and lead to prediction of spatial distribution and temporal variability.
Wake Forest University
Modeling Eco-hydrologic Processes Across Scales in Montane Cloud Forests Montane Cloud Forests (MCFs) are globally relevant ecological zones that spend the majority of their growing season in cloud and fog. Prior eco-physiological studies have demonstrated that MCFs are incredibly efficient at assimilating CO2 during photosynthesis. This increased efficiency is attributed to how plants in these ecosystems operate within their unique microclimates. Specifically, MCF trees maintain high photosynthesis rates under fog and low cloud conditions. While this has been observed and quantified in lab and field experiments, current sub-models of plant-atmosphere interactions within Earth systems models (ESMs) cannot recreate enhanced levels of gas exchange measured in ecophysiology studies. This lack of understanding leads to high uncertainty in ESM estimates of evapotranspiration and carbon assimilation rates for MCF ecosystems. It is critical to improve our estimates of MCF hydrologic and photosynthetic processes as these ecosystems are vulnerable to drought and microclimatic conditions are likely to be altered by climate change. This talk will explore the gaps in our process-based understanding of water, energy, and carbon budgets for MCFs, how these gaps lead to uncertainties in ESMs at different spatial and temporal scales, and how we can address these gaps in future work.
University of Arizona
Modeling the transient effects of fire on runoff and erosion: Implications for debris-flow hazards Fire temporarily alters soil and vegetation properties, driving increases in runoff and erosion that can dramatically increase the likelihood of debris flows. In the immediate aftermath of fire, debris flows most often initiate when surface water runoff rapidly erodes sediment on steep slopes. Due to the complex interactions between runoff generation, sediment transport, and post-fire debris-flow initiation and growth, models that couple these processes can provide valuable insights into the ways in which topography, burn severity, and post-fire recovery influence debris-flow activity. Here, we describe such a model as well as attempts to parameterize temporal changes in model parameters throughout the post-fire recovery process. Simulations of watershed-scale response to individual rainstorms in several southern California burned areas suggest substantial reductions in debris-flow likelihood and volume within the first 1-2 years following fire. Results highlight the importance of considering local rainfall characteristics and sediment supply when using process-based numerical models to assess debris-flow potential. More generally, results provide a methodology for estimating the intensity and duration of rainfall associated with the initiation of runoff-generated debris flows as well as insights into the persistence of debris-flow hazards following fire.
University of Texas
A Flexible Delta Model to Assess Land Building Potential of Sediment Diversions under Various External Forcings Sediment diversions costing billions of dollars are planned on deltas globally, to mitigate land loss due to rising sea levels and subsidence. Downstream of engineered levee breaks, land building will rely on natural delta processes to disperse sediment. But, external factors known to affect natural delta processes vary between possible diversion sites (e.g., wave energy, basin substrate, marsh activity), making it difficult to quantitatively compare land-building potential between sites and optimally allocate engineering resources. We have implemented the pyDeltaRCM numerical model to provide an easily extensible platform for simulating delta evolution under arbitrary environmental factors. With the computationally efficient model, we isolate (and combine) these factors to observe effects on land building, and build a framework to quickly assess land-building potential at different sites. In this presentation, I will describe pyDeltaRCM model design, and show ongoing studies to assess land-building potential of diversions under different forcings. Model computational efficiency enables uncertainty quantification that will benefit diversion planning and resource allocation, by identifying relative impact of different external factors.
D. Sarah Stamps
3D Computational Modeling of Lithospheric Deformation, Asthenospheric Flow, and Deep Melt Generation with ASPECT Surface processes are influenced by viscous coupling of the deforming lithosphere to asthenospheric flow, as well as magma that migrates upward from the upper asthenosphere. Over the past few decades, significant advances have been made in finite element numerical methods that enable modeling of lithospheric deformation, viscous coupling to asthenospheric flow, and melt generation in the upper asthenosphere. In this work, we present new developments based on the NSF Computational Infrastructure for Geodynamics finite element code ASPECT (Advanced Solver for Problems in Earth’s Convection) that allow users to easily investigate these processes in distinct tectonic and geographic locations. . Users have the options to constrain their initial temperature and density conditions with laterally varying lithospheric thickness, layers of crustal thickness, and shear wave seismic velocity models in the sublithospheric mantle. We present case studies from regions along the East African Rift System that demonstrate these capabilities.
Spring School Student Presentations
University of Colorado
Spring School Student Presentations Spring School Student Presentations
Politecnico di Milano
D-CASCADE: a basin-scale, dynamic model to analyze river sediment (dis)connectivity and its response to anthropic pressures Modelling network-scale sediment (dis)connectivity and its response to anthropic pressures provides a foundation understanding of river processes and sediment dynamics that can be used to forecast future trajectories of river form and process.</br>We present the basin-scale, dynamic sediment connectivity model D-CASCADE, which combines concepts of network modelling with empirical sediment transport formulas to quantify spatiotemporal sediment (dis)connectivity in river networks. The D-CASCADE framework describes sediment connectivity in terms of transfer rate through space and time while accounting for several hydro-morphological and anthropic factors affecting sediment transport. Add-ons can be integrated into D-CASCADE to model local changes in river geomorphology driven by sediment-induced variations in features.</br>Here, we show an application of D-CASCADE to the well-documented Bega River catchment, NSW, Australia, where major geomorphic changes have occurred in the network post-European settlement (ES) after the 1850s, including widespread channel erosion and sediment mobilization. By introducing historic drivers of change in the correct chronological sequence, the D-CASCADE model successfully reproduced the timing and magnitude of major phases of sediment transport and associated channel adjustments over the last two centuries. With this confidence, we then ran the model to test how well it performs at estimating future trajectories of basin-scale sediment transport and sediment budgets at the river reach scale.
University of Colorado
State of CSDMS State of CSDMS
Nanjing Normal University
Interoperability engine design for model sharing and reuse among OpenMI, BMI and OpenGMS-IS model standards Modelling and simulation are critical approaches to addressing geographic and environmental issues. To date, enormous relevant geo-analysis models have been developed to simulate geographic phenomena and processes that can be used to solve environmental, atmospheric and ecological problems. These models developed by different groups or people are heterogeneous and difficult to share with others. As a result, numerous international groups or organizations have designed and developed standards to unify geo-analysis models, such as OpenMI, BMI and OpenGMS-IS. Models that follow a specific standard can be shared and reused in their own standard framework, however, they still can't be reused by other standards. Thus, model interoperation may help models be shared and reused by different standards.</br>This research aims at designing an interoperability solution that can help users reuse geo-analysis models based on other standards. In this research, we discussed several solutions for model interoperation and analyzed the features of different standards. Firstly, we developed three solutions for models interoperation between different standards and discussed their advantages and disadvantages. Then, we analyzed the key features of model interoperation, including model field mapping, function conversion, data exchange, and component reorganization. Finally, we have developed an interoperability engine for interoperation between models based on OpenMI, BMI, or OpenGMS-IS. We also provided case studies (using e.g. SWMM, FDS, and the Permamodel Frost Number component) to successfully demonstrate the model interoperation.
National Center for Atmospheric Research
Xarray for Scalable Scientific Data Analysis This tutorial introduces Xarray which is a Python library that provides (1) data structures for multi-dimensional labeled arrays, (2) a toolkit for scalable data analysis on large, complex datasets using Dask which extends the SciPy ecosystem (e.g. NumPy, Pandas, Scikit-Learn) to larger-than-memory or distributed environments.</br></br>Attendees should be comfortable with basic Python programming (e.g., data structures, functions, etc.). Some prior exposure to Python data science libraries (e.g., NumPy, Pandas) is helpful. No specific domain knowledge is required to effectively participate in this tutorial.
Vanessa Gabel & Ethan Pierce
University of Colorado, Boulder
Clinic 2: Introduction to Landlab: Getting to know the Grid and Coupling Components This clinic provides a brief tutorial introduction to the theory and implementation of Landlab for landscape evolution modeling. Topics include grid representation, working with data fields, and using Landlab components to create new integrated models. This clinic is intended for beginners with little to no experience using the Landlab library. Prior experience with Python programming is helpful but not necessary.
University of Texas
Rapid hypothesis testing and analysis with the open-source delta model pyDeltaRCM In this clinic, we will introduce and experiment with open-source tools designed to promote rapid hypothesis testing for river delta studies. We will show how pyDeltaRCM, a flexible Python model for simulating river delta evolution, can be extended to incorporate any arbitrary processes or forcings. We will highlight how object-oriented model design enables community-driven model development, and how this promotes reproducible science. Our clinic will develop an extended model to simulate deltaic evolution into receiving basins with different slopes. Then, the clinic will step through some basic analyses of the model runs, interrogating both surface processes and subsurface structure. Our overall goal is to familiarize you with the tools we are developing and introduce our approach to software design, so that you may adopt these tools or strategies in your research.</br></br>Please note that familiarity with Python will be beneficial for this clinic, but is not required. Hands-on examples will be made available via an online programming environment (Google CoLab or similar); instructions for local installation on personal computers will be provided prior to the workshop as well.
Eric Hutton & Greg Tucker
Clinic 3: Component Creation with Landlab This clinic explores how to fully engage with the Landlab library by creating your own components. It is designed for those who already have some basic familiarity with Landlab and with scientific Python programming (registration for the “Introduction to Landlab” is recommended for those who have not already learned the basics).. In this workshop we will cover an overview of object-oriented programming (OOP), and will look at several examples of existing Landlab components to understand how they are written in an OOP framework. We will write a demo component as a group, and will then move on to writing our own components in small groups.</br></br>Participants should come prepared with an idea of a process model they’d like to implement as a component. It is recommended, but not required, that participants in this workshop also register for the clinic “The Art of Modeling: From Concept to Math with Mass Balance,” in order to be equipped with an understanding of the math that will form the basis of their Landlab component.</br></br>This workshop will involve coding in Python using the CSDMS JupyterHub. If you don't already have an account, follow the instructions to sign up at: https://csdms.colorado.edu/wiki/JupyterHub.
Chang Liao & Tian Zhou
Pacific Northwest National Laboratory
Variable resolution mesh based flow direction and hydrologic modeling: An introduction to HexWatershed Flow routing map is the cornerstone of spatially distributed hydrologic models. In this clinic we will introduce HexWatershed, a scale-free, mesh independent flow direction model. It supports DOE’s Energy Exascale Earth System Model (E3SM) to generate hydrologic parameters and river network representations on both structured and unstructured meshes. </br></br>In this presentation, we will overview the capabilities of HexWatershed with an emphasis on river network representation and flow direction modeling. We will also provide participants with the tools to begin their own research with hydrologic model workflows. Through hands-on tutorials and demonstrations, participants will gain some insights into the relationship between meshes and flow direction, and how HexWatershed handles river network in various meshes. We will also demonstrate how to use the HexWatershed model outputs in the large-scale hydrologic model, Model for Scale Adaptive River Transport (MOSART). Participants will be provided with additional resources that can be used to extend the tutorial problems and gain additional familiarity with the tools and workflows introduced. Participants are welcome to bring and utilize their own computers capable of accessing the internet and running a web browser. Tutorials will involve simple scripting operations in the Python language. The conda utility will be used to install libraries. Both QGIS and VisIt packages will be used for visualization.
University of Illinois Urbana-Champaign
Publishing Reproducible Computational Research with the Whole Tale Scientific communities and peer-review journals are increasingly requiring authors to make available the code and data behind computational results reported in published research. This tutorial will introduce participants to the NSF-funded Whole Tale platform, an open-access and open-source system designed to enable authors to package and archive their code, data, computational workflow and information about the computational environment to better enable others to repeat their results. We will walk through the basic features of the platform with hands-on exercises.
University of Colorado
Teaching with Jupyter NoteBooks Jupyter Notebooks can be powerful tools for classroom teaching. This clinic explores different ways to use notebooks in teaching, common pitfalls to avoid, and best practices. It also introduces the CSDMS OpenEarthscape Hub, an online resource that instructors can use that eliminates the need to install software and provides students with direct access to various CSDMS tools.
Danica Roth & Eileen Martin
Colorado School of Mines
Environmental seismology and distributed acoustic sensing (DAS) Seismo-acoustic techniques can provide continuous, real-time observations with high temporal resolution and broad spatial coverage for process monitoring, detection and characterization in accessible environments. These capabilities are rapidly advancing with the growing use of distributed acoustic sensing (DAS) systems, which use fiber optic cables to provide continuous records of ground motion comparable to large-N arrays of single-component accelerometers or geophones. Compared to traditional seismic arrays, DAS arrays can be tens of kilometers in length with spatial resolution of meters and sampling frequencies from millihertz to kilohertz. </br></br>In this clinic, participants will learn about the basics of DAS instrumentation and deployment in an introductory lecture, and be introduced to hands-on DAS data input, analysis and visualization concepts through Jupyter notebooks. The clinic will also provide participants with resources for further exploring and utilizing DAS, including guides to open DAS datasets, and the growing resource lists and GitHub organization managed by the NSF-funded DAS Research Coordination Network (https://www.iris.edu/hq/initiatives/das_rcn).
Travis Thurber & Chris Vernon
Pacific Northwest National Laboratory
Modeling Water Movement and Reservoir Operations with mosartwmpy Water -- we drink it, we bathe in it, we feed it to our plants, we gaze admiringly as it falls off cliffs -- but how does it get from the sky to your tap? Will it always be free to chisel windingly through the countryside and leap from dazzling heights?</br></br>The open-source model mosartwmpy (aka "wimpy") offers researchers a bird's eye view of water movement and reservoir operations across the conterminous United States. Wimpy has been translated into Python from its ancestor MOSART-WM (Model Of Scale Adaptive River Transport and Water Management) without sacrificing performance, leading to a more widely accessible and extensible model. By implementing the Basic Model Interface (BMI), Wimpy provides a familiar workflow with interoperability at the heart.</br></br>This clinic will introduce mosartwmpy at a high-level and provide a hands-on, interactive tutorial demonstrating its capabilities for studying water shortages. Attendees should leave armed with a stronger understanding of the interplay between water movement and reservoir storage, and with the confidence to utilize mosartwmpy in their own research.
Greg Tucker & CSDMS Integration Facility Staff
Clinic 1: The Art of Modeling: From Concept to Math with Mass, Energy, and Momentum Balance 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. </br></br>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.
Interested in providing a clinic during the next annual meeting? Contact CSDMS@Colorado.EDU.