Property:CSDMS meeting abstract presentation
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Ecosystems present spatial patterns controlled by climate, topography, soils, plant interactions, and disturbances. Geomorphic transport processes mediated by the state of the ecosystem leave biotic imprints on erosion rates and topography. This talk will address the following questions at the watershed scale: What are emergent properties of biotic landscapes, and how do they form? How do biotic landscapes respond to perturbations in space and time? First, formation of patterns and ecologic rates of change to perturbations in semiarid ecosystems will be investigated using Landlab. Second, we will examine eco-geosphere interactions and outcomes using a landscape evolution model. The role of solar radiation on ecogeomorphic forms, and watershed ecogeomorphic response to climate change will be elaborated. Finally, reflecting on the findings of previous research, some future directions in numerical modeling for linking ecosphere and geosphere will be discussed. +
Environmental management decisions increasingly rely on quantitative integrated ecological models to forecast potential outcomes of management actions. These models are becoming increasingly complex through the integration of processes from multiple disciplines (e.g., linking physical process, engineering and ecological models). These integrated modeling suites are viewed by many decision makers as unnecessarily complex black boxes, which can lead to mistrust, misinterpretation and/or misapplication of model results. Numerical models have historically been developed without decision makers and stakeholders involved in model development, which further complicates communication as diverse project teams have differing levels of understanding of models and their uses. For example, explaining to a group of non-modelers how hydrodynamic model output was aggregated at ecologically-relevant scales can be difficult to explain to someone who was not exposed to that modeling decision. The mistrust of models and associated outputs can lead to poor decision-making, increase the risk of ineffective decisions and can lead to litigation over decisions. Improved integrated ecological model development practices are needed to increase transparency, include stakeholders and decision makers throughout the entire modeling process from conceptualization through application.
This clinic describes a suite of techniques, best practices, and tools for rapid developing applied integrated ecological models in conjunction with technical stakeholder audiences and agency practitioners. First, a workshop approach for applied ecosystem modeling problems is described that cultivates a foundational understanding of integrated ecological models through hands-on, interactive model development. In this workshop environment, interdisciplinary and interagency working groups co-develop models in real-time which demystifies technical issues and educates participants on the modeling process. Second, a Toolkit for interActive Modeling (TAM) is presented as a simple platform for rapidly developing index-based ecological models, which we have found useful for developing a strong modeling foundation for large, multidisciplinary teams involved in environmental decision making. Third, the EcoRest R package is described, which provides a library of functions for computing habitat suitability and decision support via cost-effectiveness and incremental cost analysis. Based on 10 workshops over the last 8 years, these techniques facilitated rapid, transparent development and application of integrated ecological models, informed non-technical stakeholders of the complexity facing decision-makers, created a sense of model ownership by participants, built trust among partners, and ultimately increased “buy-in” of eventual management decisions.
Established in 2005, GEO (http://www.earthobservations.org/) is a voluntary partnership of governments and organizations that envisions “a future wherein decisions and actions for the benefit of humankind are informed by coordinated, comprehensive and sustained Earth observations and information.” GEO Member governments include 96 nations and the European Commission, and 87 Participating Organizations comprised of international bodies with a mandate in Earth observations. Together, the GEO community is creating a Global Earth Observation System of Systems (GEOSS) that will link Earth observation resources world-wide across multiple Societal Benefit Areas - agriculture, biodiversity, climate, disasters, ecosystems, energy, health, water and weather - and make those resources available for better informed decision-making. Through the GEOSS Common Infrastructure (GCI), GEOSS resources, including Earth observation data (satellite, airborne, in situ, models), information services, standards and best practices, can be searched, discovered and accessed by scientists, policy leaders, decision makers, and those who develop and provide information services across the entire spectrum of users.
The presentation will cover the GCI overall architecture and some possible future developments. +
Exchanges of sediment between marshes and estuaries affect coastal geomorphology, wetland stability and habitat, but can be difficult to predict due to the many processes that influence dynamics in these systems. This study uses a modeling approach to analyze how spatially variability in marsh-edge erosion, vegetation, and hydrodynamic conditions affect sediment fluxes between marshes and estuaries in Barnegat Bay, New Jersey. Specifically, the three-dimensional Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) numerical model was used. Model results showed that marsh-estuarine sediment fluxes varied spatially due to changes in wave thrust, currents, and sediment availability. +
Exploratory models that simulate landscape change incorporate only the most essential processes that are hypothesized to control a behavior of interest. These “rule-based” models have been used successfully to examine behaviors in natural landscapes over large spatial (many kms) and temporal scales (decades to millennia). In many geomorphic systems, the dynamics of developed landscapes differ significantly from natural landscapes. For example, humans can alter the physical landscape through the introduction of hard infrastructure and removal of vegetation. Humans can also modify the internal and external forces that naturally change landscapes, including flows of water, wind, and sediment as well as climatic factors. As with natural processes, in exploratory models human behavior must be parameterized. However, the level of detail to which human behavior can be reduced while still accurately reproducing feedbacks across the coupled human-natural landscape is a complex, user-based decision.
In this clinic, we will work in small groups and through a Jupyter Notebook to parameterize a new human behavior within a modular coastal barrier evolution model (Barrier3D, within the CASCADE modeling framework). The clinic will incorporate discussions and prompts about how to broadly identify important model “ingredients” and reduce model complexity, and will therefore be generalizable to other geomorphic landscapes. +
Fill-Spill-Merge (FSM) is an algorithm that distributes runoff on a landscape to fill or partially fill depressions. When a depression fills, excess water can overflow into neighbouring depressions or the ocean. In this clinic, we will use FSM to assess changes in a landscape’s hydrology when depressions in a DEM are partially or fully filled with water. We will discuss why it may be important to consider depressions more closely than just with removal. I will describe the design of the FSM algorithm, and then we will use FSM on a DEM to look at how landscape hydrology changes under different hydrologic conditions.
This clinic may be helpful to those interested in topics such as landscape hydrology, landscape evolution, flow routing, hydrologic connectivity, and lake water storage. +
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. +
Flood hazard in rivers can evolve from changes in the frequency and intensity of flood-flows (hydrologic effects) and in the channel capacity to carry flood-flows (morphologic effects). However, river morphology is complex and often neglected in flood planning. Here, we separate the impacts of morphology vs. hydrology on flood risk for 48 river gauges in Northwestern Washington State. We find that morphologic vs. hydrologic forcings are comparable but not regionally consistent. Prominent morphologic effects on flood-risk are forced by extreme natural events and anthropogenic disturbances. Based on morphologic changes, we identify five categories of river behavior relevant for flood-risk management. +
Flood modelling at global scales represents a revolution in hydraulic science and has the potential to transform decision-making and risk management in a wide variety of fields. Such modelling draws on a rich heritage of algorithm and data set development in hydraulic modelling over the last 20 years, and is now beginning to yield new insights into current and future flood risk. This paper reviews this progress and outlines recent efforts to develop a 30m resolution true hydrodynamic model of the entire conterminous US. The model is built using an automated framework which uses US National Elevation Dataset, the HydroSHEDS river network, regionalised frequency analysis to determine extreme flow and rainfall boundary conditions and the USACE National Levee Dataset to characterize flood defences. Comparison against FEMA and USGS flood maps shows the continental model to have skill approaching that of bespoke models built with local data. The paper describes the development and testing of the model, and it use to estimate current and future flood risk in the US using high resolution population maps and development projections. +
Flooding is one of the costliest natural disasters and recent events, including several hurricanes as well as flash floods, have been particularly devastating. In the US alone, the last few years have been record-breaking in terms of flood disasters and triggered many reactions in public opinions. Governments are now reviewing the available information to better mitigate the risks from flooding.<br>Typically, in the US, flood hazard mapping is done by federal agencies (USACE, FEMA and USGS), with traditionally, little room and need for research model development in flood hazard applications. Now, with the advent of the National Water Model, the status quo of flood hazard prediction in the US may be changing; however, inundation extent and floodplain depths in the National Water Model are still under early-stage development.<br>This Clinic provides a beginner introduction to the latest capabilities in large-scale 2-D modeling using the LISFLOOD-FP model developed by the University of Bristol with a nearly 20-year code history. This model has a very long history in research applications, while the algorithms behind the model made their way also into many existing industry model codes. The session will give participants insights into 2-D flood inundation modeling with LISFLOOD-FP and also a look at more sophisticated sub-grid channel implementations for large-scale application. More specifically, we will look at the data sets needed by the model and then run a simulation of the annual flooding on the Inner Niger Delta in Mali. The Clinic will also give participants the opportunity to look at some high-resolution LiDAR-based model results. +
Floodplain construction involves the interplay between channel belt sedimentation and avulsion, overbank deposition of fines, and sediment reworking by channel migration. There has been considerable progress in numerical modelling of these processes over the past few years, for example, by using high resolution flow and sediment transport models to simulate river morphodynamics, albeit over relatively small time and space scales. Such spatially-distributed hydrodynamic models are also regularly used to simulate floodplain inundation and overbank sedimentation during individual floods. However, most existing models of long-term floodplain construction and alluvial architecture do not account for flood hydraulics explicitly. Instead, floodplain sedimentation is typically modelled as an exponential function of distance from the river, and avulsion thresholds are defined using topographic indices (e.g., lateral:downstream slope ratios or metrics of channel belt super-elevation). This presentation aims to provide an overview of these issues, and present results from a hydrodynamically-driven model of long-term floodplain evolution. This model combines a simple network-based model of channel migration with a 2D grid-based model of flood hydrodynamics and overbank sedimentation. The latter involves a finite volume solution of the shallow water equations and an advection-diffusion model for suspended sediment transport. Simulation results are compared with observations from several large lowland floodplains, and the model is used to explore hydrodynamic controls on long-term floodplain evolution and alluvial ridge construction. +
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.
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. +
Fluvial incision since late Miocene time (5 Ma) has shaped the transition between the Central Rocky Mountains and adjacent High Plains. Despite a clear contrast in erodibility between the mountains and plains, erodibility has not been carefully accounted for in previous attempts to model the geomorphic evolution of this region. The focus of this work to date has been to constrain erodibility values with a simplistic, toy model, and to reconstruct the paleosurface of the Miocene Ogallala Formation prior to its dissection beginning at 5 Ma. This surface reconstruction will be used as an initial condition in subsequent modeling. +
Food security and poverty in Bangladesh are very dependent on natural resources, which fluctuate with a changing environment. The ecosystem services supporting the rural population are affected by several factors including climate change, upstream river flow modifications, commercial fish catches in the Bay of Bengal, and governance interventions. The ESPA Deltas project aims to holistically describe the interaction between the interlinked bio-physical environment and the livelihoods of the rural poorest in coastal Bangladesh, who are highly dependent on natural resources and live generally on less than US$1.50 per day. Here we describe a new integrated model that allows a long-term analysis of the possible changes in this system by linking projected changes in physical processes (e.g. river flows, nutrients), with productivity (e.g. fish, rice), social processes (e.g. access, property rights, migration) and governance (e.g. fisheries, agriculture, water and land use management). Bayesian Networks and Bayesian Processes allow multidisciplinary integration and exploration of specific scenarios. This integrated approach is designed to provide Bangladeshi policy makers with science-based evidence of possible development trajectories. This includes the likely robustness of different governance options on natural resource conservation and poverty levels. Early results highlight the far reaching implications of sustainable resource use and international cooperation to secure livelihoods and ensure a sustainable environment in coastal Bangladesh. +
For about two decades the Distributed and Unified Numerics Environment (DUNE) has been an active part in the scientific development of computational software and technology and it's C++ routines are the basis for several other well established open source projects, for example, DuMux.
Although the C++ interfaces of DUNE are highly flexible and customizable, a solid knowledge of C++ is necessary to make use of this powerful tool. In this talk we give an overview on recent development towards a Python interface for DUNE and in particular DUNE-FEM, a module which provides highly efficient implementations of hp-adaptive Discontinuous Galerkin (DG) methods for solving a wide range of nonlinear partial differential equations. Providing easier user interfaces based on Python and the Unified Form Language (UFL) opens DUNE-FEM to a broader audience, for example, Bachelor and Master students. This talk will also briefly discuss how Python and DUNE are embedded in teaching of Scientific Computing courses at Lund University and Warwick University. +
Fora.ai is an intuitive digital environment that enables groups with diverse expertise to collaboratively interact with embedded simulation models to understand real world socio-environmental problems and create novel and impactful solutions. Participants interact with this digital representation and with each other, iteratively creating, revising and testing solutions until diverse needs are addressed. Workshop participants will use Fora.ai’s interactive game-board to collectively build solutions to environmental hazards (e.g., flooding and wildfires). The virtual environment allows for participation in a facilitated process in which users: 1) input their individual priorities, 2) collaboratively run simulations to understand the complexity of the hazards, 3) co-design solutions to address these problems, 4) see how their solutions affect outputs of interest, and 5) deliberate on the tradeoffs that arise from each solution due to competing priorities. Participants will be introduced to the environmental hazard model and, with facilitator assistance, engage in multiple iterations of the process of prioritization, solution-building, and reflection on results. This process will allow them to refine their proposed solutions towards intervention strategies that they would jointly support for implementation, with an understanding of its benefits and drawbacks. The workshop will end with a focus group debrief. Laptops or tablets required. +
Fora.ai is an intuitive digital environment that enables diverse stakeholder groups to collaboratively interact with embedded simulation models to understand real world socio-environmental problems and create novel and impactful solutions. Stakeholders interact with this digital representation and with each other, iteratively creating, revising and testing solutions until diverse needs are addressed. Workshop participants will use fora.ai’s interactive game-board to collectively build green infrastructure solutions to flooding in a neighborhood in Chelsea, Massachusetts. The virtual environment allows for participation in a facilitated process in which users will: 1) input their individual priorities, 2) collaboratively run simulations to understand flooding issues in the neighborhood, 3) co-design green infrastructure scenarios to address these problems, 4) see how their changes affect the simulation, and 5) deliberate on the tradeoffs that arise from each solution due to competing priorities. Participants will be introduced to the flooding model and, with facilitator assistance, engage in multiple iterations of the process of prioritization, solution-building, and reflection on results. This process will allow them to refine their proposed solutions towards a design they would jointly support for implementation, with an understanding of its benefits and drawbacks. The workshop will end with a focus group debrief. Laptops or tablets required. +
From G.K. Gilbert's "The Convexity of Hilltops" to highly-optimized numerical implementations of drainage basin evolution, models of landscape evolution have been used to develop insight into the development of specific field areas, create testable predictions of landform development, demonstrate the consequences of our current theories for geomorphic processes, and spark imagination through hypothetical scenarios. In this talk, I discuss how the types questions tackled with landscape evolution models have changed as observational data (e.g., high-resolution topography) and computational technology (e.g., accessible high performance computing) have become available. I draw on a natural experiment in postglacial drainage basin incision and a synthetic experiment in a simple tectonic setting to demonstrate how landscape evolution models can be used to identify how much information the topography or other observable quantities provide in inferring process representation and tectonic history. In the natural example, comparison of multiple calibrated models provides insight into which process representations improve our ability to capture the geomorphic history of a site. Projections into the future characterize where in the landscape uncertainty in the model structure dominates over other sources of uncertainty. In the synthetic case, I explore the ability of a numerical inversion to recover geomorphic-process relevant (e.g., detachment vs. transport limited fluvial incision) and tectonically relevant (e.g., date of fault motion onset) system parameters. +
GCAM is an open-source, global, market equilibrium model that represents the linkages between energy, water, land, climate, and economic systems. One of GCAM's many outputs is projected land cover/use by subregion. Subregional projections provide context and can be used to understand regional land dynamics; however, Earth System Models (ESMs) generally require gridded representations of land at finer scales. Demeter, a land use and land cover disaggregation model, was created to provide this service. Demeter directly ingests land projections from GCAM and creates gridded products that match the desired resolution, and land class requirements of the user. +
GPUs can make models, simulations, machine learning, and data analysis much faster, but how? And when? In this clinic we'll discuss whether you should use a GPU for your work, whether you should buy one, which one to buy, and how to use one effectively. We'll also get hands-on and speed up a landscape evolution model together. This clinic should be of interest both to folks who would like to speed up their code with minimal effort as well as folks who are interested in the nitty gritty of pushing computational boundaries. +
