Revision as of 10:17, 10 April 2014

CSDMS 2014 Annual Meeting
Uncertainty and Sensitivity in Surface Dynamics Modeling

May 20 - 22, 2014, Boulder Colorado, USA

Optional May 23^rd: Post-meeting Software Bootcamp (Registration for bootcamp is full)

Deadline abstract submission & registration extended till April 14^th

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Objectives and general description

The CSDMS Meeting 2014 will bring Uncertainty and Sensitivity in Surface Dynamics Modeling to your attention.

The meeting includes: 1) State-of-the art keynote presentations in earth-surface dynamics and modeling; 2) Hands-on clinics related to community models, tools and approaches; 3) Transformative software products and approaches designed to be accessible, easy to use, and relevant; 4) Breakout sessions for Working, Focus Research Groups and the Initiatives ; 5) Poster Sessions; and more.

Poster Information: The poster boards are configured for 4' wide by 6' tall (portrait orientation) posters. The deadline to submit abstracts is April 1, 2014.

Invited Keynote speakers

Tom Hsu
University of Delaware
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Understanding wave-driven fine sediment transport through 3D turbulence resolving simulations – implications to offshore delivery of fine sediment

Tian-Jian Hsu (Tom), Associate Professor
Center for Applied Coastal Research, Civil & Environmental Engineering
University of Delaware, Newark, DE 19716, USA

One of the most intriguing issues in fine sediment transport, including turbidity currents, current-driven transport and wave-driven transport, is that the presence of sediments may significantly attenuate flow turbulence. Depending on the level of turbulence suppression, it may lead to the formation of lutocline (a sharp negative gradient of sediment concentration) which further encourages offshore-directed gravity flow; or it may cause catastrophic collapse of turbulence and sediment deposition. Through idealized 3D turbulence-resolving simulations of fine sediment (mud) transport in wave bottom boundary layer based on a pseudo-spectral scheme, our recent studies show that the transition of these flow modes can be caused by various degree of sediment-induced stable density stratification. This effort demonstrates the success of using a turbulence-resolving simulation tool to diagnose complex fine sediment transport processes. This talk further reports our recent development of this turbulence-resolving numerical model with a goal to provide a predictive tool for more realistic fine sediment transport applications.

Assuming a small Stokes number (St<0.3), which is appropriate for typical fine sediment, the Equilibrium approximation to the Eulerian two-phase flow equations is applied. The resulting simplified equations are solved with a high-accuracy hybrid spectral-compact finite difference scheme. The numerical approach extends the earlier pseudo-spectral model with a sixth-order compact finite difference scheme in the bed-normal direction. The compact finite difference scheme allows easy implementation of flow-dependent sediment properties and complex bottom boundary conditions. Hence, several new capabilities are included in the numerical simulation, such as rheological stress (enhance viscosity in high sediment concentration), hindered settling, erodible/depositional bottom boundary, and higher order inertia terms critical for fine sand fraction.

In the past decade, the role of wave bottom boundary layer in delivering fine sediment offshore via wave-supported gravity current (WSGC) has been well-recognized. We hypothesize that the generation, transport and termination of WSGC is directly associated with the flow modes discussed previously. In addition to the well-known Richardson number control (i.e., associated with sediment-induced density stratification), in this talk we will discuss how enhanced viscosity via rheological stress and high erodibility of the mud bed (e.g., low critical shear stress for unconsolidated mud bed) can trigger catastrophic collapse of turbulence and sediment deposition. The significance of bed erodibility in determining the resulting flow modes motivates future study regarding the effect of sand fraction on fine sediment transport via armoring.

Jim McElwaine
Durham University (UK)
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The Dynamics of Granular Flows

Professor of Geohazards

Department of Earth Sciences

Durham University UK

Granular materials are ubiquitous in the environment, in industry and in everyday life and yet are poorly understood. Modelling the behavior of a granular medium is critical to understanding problems ranging from hazardous landslides and avalanches in the Geosciences, to the design of industrial equipment. Typical granular systems contain millions of particles, but the underlying equations governing that collective motion are as yet unknown. The search for a theory of granular matter is a fundamental problems in physics and engineering and of immense practical importance for mitigating the risk of geohazards. Direct simulation of granular systems using the Discrete Element Method is a powerful tool for developing theories and modelling granular systems. I will describe the simulation technique and show its application to a diverse range of flows.

Alexey Voinov
University of Twente
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Exploring climate mitigation and low-carbon transitions: new challenges for model integration

Alexey Voinov
University of Twente, Netherlands
aavoinov@gmail.com

There are various visions of our future, but most policy-makers and scientists agree that life will be substantially different in the post-fossil era. The cheap and abundant supply of fossil energy has led to unprecedented population growth and to staggering levels of consumption of natural resources, undermining the carrying capacity of nature. Eroding ecosystems, the end of cheap oil and climate change call for new policies to support societal transformations toward low-carbon alternative futures. This understanding has already been expressed in recent EU legislation, which requires that domestic GHG emissions be cut by 80% between 1990 and 2050. Energy is a major driver of change and an important ‘currency’ that runs economic and social systems and influences environmental systems. Being so used to the abundant and uninterrupted supply of fossil energy, we tend to forget the important role that it plays in our everyday lives. Non-marginal, abrupt changes, such as during the Oil Crisis of the 1970s or the sudden sharp rise in oil prices in 2008 remind us how vulnerable societies are with respect to energy. Future transitions and climate induced changes are also unlikely to be smooth and require new modeling paradigms and methods that can handle step-change dynamics and work across a wide range of spatio-temporal scales, integrating the knowledge of many stakeholder communities.

Here we are operating in a generalized ‘socio-environmental model space’, which includes empirical models, conceptual stakeholder models, complex computer simulations, and data sets, and which can be characterized in several dimensions, such as model complexity, spatial and temporal resolution, disciplinary coverage, bias and focus, sensitivity and uncertainty, usability and relevance. In this space we need a ‘model calculus’ – a set of relationships and operations that can apply to individual models and groups of models. Model integration across disciplinary boundaries faces two big challenges. First we need to learn to deal with a variety of modeling paradigms and techniques, allowing different types of models to exchange information in a meaningful way (agent based models talk to systems dynamics, to computed global equilibrium models, to empirical models, etc.). Secondly, we need to provide integration techniques and tools that bring qualitative, conceptual, mental models of stakeholders together with the quantitative simulation models.

Greater transparency and accessibility can be achieved through enhancing documentation and communication of model functioning and strengths and limitations of various models and approaches. This extensive model documentation following improved and enhanced meta model standards is an important first step that makes sure that models (both qualitative and conceptual) ‘talk the same language’ and can exchange information and knowledge at various stages of research. This also helps us create the ontology, which can be further used for computer aided semantic mediation of models. This semantic mediation should include such functionality as consistency checks (checking for units, concepts, spatio-temporal resolution, etc.). This should also help to explore the different models along the complexity continuum to understand how information from more aggregated qualitative models can be transmitted to more elaborated and detailed quantitative simulations, and vice versa. This bears the promise of insight on the complex behavior of non-linear systems where regime shifts and non-equilibrium dynamics is usually better understood with simple models, while the more complicated models are easier to parametrize with data and can take into account more detailed information about particular systems and situations.

Peter Koons
University of Maine
{{{participants}}}

Unifying Tectonics and Surface Processes in Geodynamics

Unifying Tectonics & Surface Processes in Geodynamics

Peter Koons, Univ Maine, Earth and Climate Science Orono Maine, United States. peter.koons@maine.edu

Phaedra Upton, GNS , new zealand. p.upton@gns.cri.nz

Samuel Roy, U Mainel Earth and Climate Science Orono Maine, United States. sgroy27@gmail.com

In formulating tectono-geomorphic models of landscape evolution, Earth is typically divided into two domains; the surface domain in which “geomorphic” processes are solved for and a tectonic domain of earth deformation driven generally by differential plate movements. Here we present a single mechanical framework, Failure Earth Response Model (FERM), that unifies the physical description of dynamics within and between the two domains. FERM is constructed on the two, basic assumptions about the three-dimensional stress state and rheological memory: I) Material displacement, whether tectonic or geomorphic in origin, at or below Earth’s surface, is driven by local forces overcoming local resistance, and II) Large displacements, whether tectonic or geomorphic in origin, irreversibly alter Earth material properties enhancing a long term strain memory mapped into the topography. In addition to the gathering of stresses arising from far field tectonic processes, topographic relief, and the inertial surface processes into a single stress state for every point, the FERM formulation allows explicit consideration of the contributions to the evolving landscape of pore pressure fluctuations, seismic accelerations, and fault damage. Incorporation of these in the FERM model significantly influences the tempo of landscape evolution and leads to highly heterogeneous and anisotropic stress and strength patterns, largely predictable from knowledge of mantle kinematics. The resulting unified description permits exploration of surface-tectonic interactions from outcrop to orogen scales and allows elucidation of the high fidelity orogenic strain and climate memory contained in topography.

Elowyn Yager
Center for Ecohydraulics, University of Idaho
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Predictions of bedload transport in vegetated channels: uncertainties and steps forward

Vegetation in river channels and on floodplains alters mean flow conditions, turbulence, sediment transport rates and local sedimentation patterns. Although many advances have been made to predict the impact of vegetation on flow conditions, relatively few studies have investigated how vegetation influences bedload fluxes. We first investigate how known vegetation impacts on flow turbulence can be used to better predict bedload transport and sedimentation within vegetation patches. To elucidate these mechanics we measured 2D velocity fields using PIV and bedload fluxes using high-speed video in simplified flume experiments. We used these laboratory measurements to test and develop bedload transport equations for vegetated conditions. Bedload transport equations did not accurately predict sediment fluxes unless they accounted for the spatial variability in the near-bed Reynolds stress. We then use this patch scale understanding to better predict how vegetation impacts channel morphology. Specifically, we investigate how vegetation influences point bar growth and shape through coupled laboratory experiments and 2D numerical modeling. We measured bedload fluxes, flow conditions and sedimentation rates on a point bar planted with natural vegetation at the Saint Anthony Falls Outdoor Stream Lab. We then calculated the detailed 2D flow field over the point bar throughout imposed flow hydrographs. Our results demonstrate that vegetation caused significant changes in the bar dimensions and depending on the flow level, led to the development of a side channel between the bar and the inner bank of the meander. Such a side channel could precipitate a change in channel morphology to a multi-thread channel. Accurate predictions of sedimentation caused by vegetation patches not only require an estimate of the spatial variation in shear stress (or velocity) within a patch but also how the vegetation alters the adjacent flow field and bedload sediment supply to the patch.

David Pyles
Chevron Center of Research Excellence, Colorado School of Mines
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Testing the efficacy and uncertainty of outcrop- and model-based studies through collaboration: A field geologist’s perspective

David R. Pyles
Chevron Center of Research Excellence
Department of Geology and Geological Engineering
Colorado School of Mines
Golden, Colorado

Recent technological advances in data collection techniques have yielded opportunities to better quantify stratigraphic stacking patterns, flow processes and sedimentation from outcrops of ancient sediment transport systems. These advancements created opportunities for field geologists to reduce uncertainty in the interpretation of the stratigraphic record and have likewise created data sets from which the efficacy of numerical models and physical experiments can be evaluated. The goals of this presentation are to (1) review some combined outcrop-model based studies, (2) discuss how these integrated studies test model and field-based uncertainty, and (3) share a vision for how field geologists and modelers can leverage from each other’s perspectives.

Five examples of studies that bridged the gap between outcrop stratigraphy and experimental and/or numerical models include: (1) documentation of how mineralogy varies spatially in submarine fans, (2) relating flow processes to sedimentation in sinuous submarine channels, (3) evaluating compensational stacking in deltas and submarine fans, (4) relating stratigraphic architecture of deltas to inherited water depth and seafloor gradient, and (5) testing how shelf-edge deltas pipe coarse-grained sediment to submarine fans. These and similarly focused studies are important because they used common workflows and quantitative methods to evaluate similarities and differences between modeled and natural systems, resulting in a more complete view of the processes and products being studied. Whereas common workflows can provide a means to test the efficacy of physical and numerical modeling, it is critical to consider how modeling sheds insight into how one interprets the stratigraphic record from outcrop and subsurface data sets.

Eric Larour
Jet Propulsion Laboratory
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Towards better quantifications of the uncertainty in polar ice-sheet projections using the open source framework ISSM

Eric Larour, Jet Propulsion Laboratory Pasadena California, United States

Helene Seroussi, Jet Propulsion Laboratory Pasadena California, United States.

Mathieu Morlighem, University of California at Irvine Irvine California, United States.

Eric Rignot, University of California at Irvine Irvine California, United States.

Nicole Schlegel, Jet Propulsion Laboratory Pasadena California, United States

Understanding and modeling the evolution of continental ice sheets such as Antarctica and Greenland can be a difficult task because a lot of the inputs used in transient ice flow models, either inferred from satellite or in-situ observations, carry large measurement errors that will propagate forward and impact projection assessments. Here, we aim at comprehensively quantifying error margins on model diagnostics such as mass outflux at the grounding line, maximum surface velocity and overall ice-sheet volume, applied to major outlet glaciers in Antarctica and Greenland. Our analysis relies on uncertainty quantification methods implemented in the Ice Sheet System Model (ISSM), developed at the Jet Propulsion Laboratory in collaboration with the University of California at Irvine. We focus in particular on sensitivity analysis to try and understand the local influence of specific inputs on model results, and sampling analysis to quantify error margins on model diagnostics. Our results demonstrate the expected influence of measurement errors in surface altimetry, bedrock position and basal friction

Mick van der Wegen
UNESCO-IHE & Deltares
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Estuarine morphodynamics : better be certain about uncertainty

Mick van der Wegen, UNESCO-IHE and Deltares Delft , Netherlands. m.vanderwegen@unesco-ihe.org
Bruce E. Jaffe, USGS Santa Cruz California, United States. bjaffe@usgs.gov
Gerard Dam, UNESCO-IHE Delft California, Netherlands. dam@svasek.nl
Dano Roelvink, UNESCO-IHE and Deltares and TU Delft Delft California, Netherlands. d.roelvink@unesco-ihe.org

Process-based models are able to predict velocity fields, sediment transport and associated morphodynamic developments over time. These models can generate realistic morphological patterns and stable morphodynamic developments over time scales of millennia under schematized model settings. However, more realistic case studies raise questions on model skill and confidence levels. Process-based models require detailed information on initial conditions (e.g. sediment characteristics, initial distribution of sediment fractions over the model domain), process descriptions (e.g. roughness and sediment transport formulations) and forcing conditions (e.g. time varying hydrodynamic and sediment forcing). The value of the model output depends to a high degree on the uncertainty associated with these model input parameters.

Our study explores a methodology to quantify model output uncertainty levels and to determine which parameters are responsible for largest output uncertainty. Furthermore we explore how model skill and uncertainty develop over time. We describe the San Pablo Bay (USA) case study and the Western Scheldt (Netherlands) case study in a 100 year hindcast and a more than 100 year forecast.

Remarkably, model skill and uncertainty levels depend on model input parameter variations only to a limited extent. Model skill is low first decades, but increases afterwards to become excellent after 70 years. The possible explanation is that the interaction of the major tidal forcing and the estuarine plan form governs morphodynamic development in confined environments to a high degree.

Rebecca Caldwell
Indiana University
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A numerical modeling study of the effects of sediment properties on deltaic processes and morphology

Rebecca L. Caldwell and Douglas A. Edmonds, Department of Geological Sciences, Indiana University, Bloomington, Indiana, USA.

We use numerical modeling to explain how deltaic processes and morphology are controlled by properties of the sediment input to the delta apex. We conducted 36 numerical experiments of delta formation varying the following sediment properties: median grain size, grain-size distribution shape, and percent cohesive sediment. As the dominant grain size increases deltas undergo a morphological transition from elongate with few channels to semi-circular with many channels. This transition occurs because the critical shear stress for erosion and the settling velocity of grains in transport set both the number of channel mouths on the delta and the dominant delta-building process. Together, the number of channel mouths and dominant process – channel avulsion, mouth bar growth, or levee growth – set the delta morphology. Coarse-grained, non-cohesive deltas have many channels that are dominated by avulsion, creating semi-circular planforms with relatively smooth delta fronts. Intermediate-grained deltas have many channels that are dominated by mouth bar growth, creating semi-circular planforms with bifurcated channel networks and rugose delta fronts. Fine-grained, cohesive deltas have a few channels, the majority of which are dominated by levee growth, creating elongate planforms with smooth delta fronts. The process-based model presented here provides a previously lacking mechanistic understanding of the effects of sediment properties on delta channel network and planform morphology.

Mariela Perignon
University of Colorado
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Predicting the influence of floodplain vegetation on the geomorphic effects of large floods

The spatial distribution of vegetation along the banks and floodplains of a river can drastically affect its geomorphic response to large floods. Plants influence sediment transport dynamics and the resulting patterns of erosion and deposition by steering the flow, changing the scale and intensity of turbulence, and increasing the effective cohesiveness of surface material. Efficiently simulating these interactions over river reaches requires simplifying the small-scale processes into measurable parameters that can reproduce the large-scale behavior of the system.

We present simulations of the evolution of the morphology of vegetated, mobile sand-bed rivers during this flows that were obtained by coupling the existing hydrodynamic model ANUGA with modules for sediment transport and vegetation. This model captures the effects of vegetation on mean flow velocity by treating plant stems as cylinders of specified diameter and spacing and calculating the drag they impart on the flow.

The outputs of this model were tested against a well-constrained natural experiment to determine the accuracy of the model predictions. Multi-temporal airborne lidar datasets capture the topographic change that occurred along a 12-km reach of the Rio Puerco, New Mexico, as a result of a large flood in 2006. The magnitude of deposition on the floodplain was found to correlate with vegetation density as well as distance from the primary sediment source. This relationship is reproduced by the model using only the simplest drag formulation. The local variability in deposit thickness was seen to depend strongly on the dominant species present, suggesting that plant-scale processes are reflected in the patch-scale behavior of the system. This indicates a need for more complex parameters that reflect the changes in turbulent energy and shear stress that result from different plant characteristics.

Attila Lazar
University of Southampton
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Coupling terrestrial and marine biophysical processes with livelihood dynamics for analysis of poverty alleviation in Bangladesh

A.N. Lazar, R. J. Nicholls, C. Hutton, H. Adams, M.M. Rahman, M. Salehin, D. Clarke, A.R. Akanda, J. A. Dearing, Judith Wolf5, P.K. Streatfield

1 Faculty of Engineering and Environment, University of Southampton, University Road, Southampton, Hampshire, United Kingdom, SO17 1BJ. a.lazar@soton.ac.uk
2 College of Life and Environmental Sciences, University of Exeter, Prince of Wales Road, Exeter,Devon United Kingdom, EX4 4SB
3 Bangladesh University of Engineering & Technology, Dhaka-1000, Bangladesh
4 Bangladesh Agriculture Research Institute, Joydebpur, Gazipur-1701, Bangladesh
5 National Oceanography Centre, Brownlow Street, Liverpool, L3 5DA, United Kingdom
6 International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka-1000, Bangladesh

Summary
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.

Rudy Slingerland
Penn State
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The FESD Delta Dynamics Modeling Collaboratory: A Progress Report

Andrew Nicholas
University of Exeter
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Modelling the evolution of large river floodplains

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.

Ajay Limaye
California Institute of Technology
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A vector-based method for bank-material tracking in coupled models of meandering and landscape evolution

Sinuous channels commonly migrate laterally and interact with banks of different strengths—an interplay that links geomorphology and life, and shapes diverse landscapes from the seafloor to planetary surfaces. To investigate feedbacks between meandering rivers and landscapes over geomorphic timescales, numerical models typically represent bank properties using structured or unstructured grids. Grid-based models, however, implicitly include unintended thresholds for bank migration that can control simulated landscape evolution. I will present a vector-based approach to land surface- and subsurface-material tracking that overcomes the resolution-dependence inherent in grid-based techniques by allowing high-fidelity representation of bank-material properties for curvilinear banks and low channel lateral migration rates. The vector-based technique is flexible for tracking evolving topography and stratigraphy to different environments, including aggrading floodplains and mixed bedrock-alluvial river valleys. Because of its geometric flexibility, the vector-based material tracking approach provides new opportunities for exploring the co-evolution of meandering rivers and surrounding landscapes over geologic timescales.

Clinic Invitees

Fotis Sotiropoulos
University of Minnesota
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The SAFL Virtual StreamLab (VSL3D): High Resolution Simulation of Turbulent Flow, Sediment Transport, and Morphodynamics in Waterways

Ali Khosronejad and Fotis Sotiropoulos
St, Anthony Falls Laboratory and Department of Civil Engineering
University of Minnesota
Minneapolis, MN
fotis@umn.edu

The St. Anthony Falls Laboratory Virtual StreamLab (VSL3D) is a powerful multi-resolution and multi-physics Computational Fluid Dynamics (CFD) model for simulating 3D, unsteady, turbulent flows and sediment transport processes in real-life streams and rivers with arbitrarily complex structures, such as man-made hydraulic structures, woody debris, and even hydrokinetic turbine arrays. The code can handle arbitrarily complex geometry of waterways and embedded structures using novel immersed boundary strategies. Turbulence can be handled either via Reynolds-averaged Navier-Stokes (RANS) turbulence models or via large-eddy simulation (LES) coupled with wall models. Free-surface effects are simulated using a level-set, two-phase flow approach, which can capture complex free-surface phenomena, including hydraulic jumps, over arbitrarily complex bathymetry. A fully-coupled hydro-morphodynamic module has also been developed for simulating bedload and suspended load sediment transport in meandering rivers. A novel dual time-stepping quasi-synchronized approach has been developed to decouple the flow and sediment transport time scales, enabling efficient simulations of morphodynamic phenomena with long time scales, such as dune migration in rivers. The code is parallelized using MPI. This clinic will present a comphrehensive overview of the VSL3D, report extensive grid sensivity and validation studies with experimental data, and present a series of applications, including: 1) LES and unsteady RANS of turbulent flow and scalar transport in natural meandering streams; 2) LES of sand wave growth and evolution in a laboratory scale flume; 2) unsteady RANS of dune formation and migration in large scale meandering rivers with in stream rock structures (rock vanes, j-hooks, w-weirs, etc.); 3) LES of free-surface flows in natural and enginnered open channels; and 4) LES of gravity currents.

Representative references about the VSL3D code

1. Khosronejad, A., Hill, C., Kang, S., and Sotiropoulos, F., “Computational and Experimental Investigation of Scour Past Laboratory Models of Stream Restoration Rock Structures,” Advances in Water Resources, Volume 54, Pages 191–207, 2013.

2. Kang, S., and Sotiropoulos, F., “Assessing the predictive capabilities of isotropic, eddy-viscosity Reynolds-averaged turbulence models in a natural-like meandering channel,” Water Resources Research, Volume: 48, Article Number: W06505, DOI: 10.1029/2011WR011375, 2012.

3. Kang, S., Khosronejad, A., and Sotiropoulos, F., “Numerical simulation of turbulent flow and sediment transport processes in arbitrarily complex waterways,” Environmental Fluid Mechanics, Memorial Volume in Honor of Prof. Gerhard H. Jirka, Eds. W. Rodi & M Uhlmann, CRC Press (Taylor and Francis group), pp. 123-151, 2012.

4. Kang, S., and Sotiropoulos, F., “Numerical modeling of 3D turbulent free surface flow in natural waterways,” Advances in Water Resources, Volume: 40, Pages: 23-36, DOI: 10.1016/j.advwatres.2012.01.012, 2012.

5. Kang, S., and Sotiropoulos, F., “Flow phenomena and mechanisms in a field-scale experimental meandering channel with a pool-riffle sequence: Insights gained via numerical simulation,” Journal of Geophysical Research – Earth Surface, Volume: 116, Article Number: F03011 DOI: 10.1029/2010JF001814 Published: AUG 20 2011.

6. Khosronejad, A., Kang, S., Borazjani, I., and Sotiropoulos, F., “Curvilinear Immersed Boundary Method For Simulating Coupled Flow and Bed Morphodynamic Interactions due to Sediment Transport Phenomena,” Advances in Water Resources, Volume: 34, Issue: 7, Pages: 829-843 DOI: 10.1016/j.advwatres.2011.02.017, Published: JUL 2011.

7. Kang, S., Lightbody, A., Hill, C., and Sotiropoulos, F., “High-resolution numerical simulation of turbulence in natural waterways,” Advances in Water Resources, Volume 34, Issue 1, January 2011, Pages 98-113.

Greg Tucker & Daniel Hobley
CIRES
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Creative computing with Landlab: A flexible Python package for rapidly building and exploring 2D surface-dynamics models

Daniel E. J. Hobley(Daniel.hobley@colorado.edu)(2), Jordan M. Adams(2), Nicole M. Gasparini(2), Eric Hutton(3), Erkan Istanbulluoglu(4), Sai Siddhartha(4), Gregory E. Tucker(1)

1. CIRES and Department of Geological Sciences, University of Colorado, Boulder, CO, USA
2. Department of Earth and Environmental Sciences, Tulane University, New Orleans, LA, USA
3. Community Surface Dynamics Modeling System (CSDMS), University of Colorado, CO, USA
4. Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA

Computer models help us explore the consequences of scientific hypotheses at a level of precision and quantification that is impossible for our unaided minds. The process of writing and debugging the necessary code is often time-consuming, however, and this cost can inhibit progress. The code-development barrier can be especially problematic when a field is rapidly unearthing new data and new ideas, as is presently the case in surface dynamics.

To help meet the need for rapid, flexible model development, we have written a prototype software framework for two-dimensional numerical modeling of planetary surface processes. The Landlab software can be used to develop new models from scratch, to create models from existing components, or a combination of the two. Landlab provides a gridding module that allows you to create and configure a model grid in just a few lines of code. Grids can be regular or unstructured, and can readily be used to implement staggered-grid numerical solutions to equations for various types of geophysical flow. The gridding module provides built-in functions for common numerical operations, such as calculating gradients and integrating fluxes around the perimeter of cells. Landlab is written in Python, a high-level language that enables rapid code development and takes advantage of a wealth of libraries for scientific computing and graphical output. Landlab also provides a framework for assembling new models from combinations of pre-built components.

In this clinic we introduce Landlab and its capabilities. We emphasize in particular its flexibility, and the speed with which new models can be developed under its framework. In particular, we will introduce the many tools available within Landlab that make development of new functionality and new descriptions of physical processes both easy and fast. Participants will finish the clinic with all the knowledge necessary to build, run and visualize 2D models of various types of earth surface systems using Landlab.

Eunseo Choi
University of Memphis
{{{participants}}}

SNAC: A 3D parallel explicit finite element code for long-term lithospheric deformation modeling

Eunseo Choi
echoi2@memphis.edu
Center for Earthquake Research and Information, University of Memphis

SNAC (StGermaiN Analysis of Continua) is a 3D parallel explicit finite element code for modeling long-term deformations of lithosphere. It is an open source being distributed through Computational Infrastructure for Geodynamics (http://geodynamics.org/cig/software/snac/) as well as through CSDMS web site (http://csdms.colorado.edu/wiki/Model:SNAC).

This clinic will provide an overview of SNAC and lead participants through a typical work procedure for producing a 3D lithospheric deformation model on a high performance cluster. Specifically, participants will take the following steps: 0) acquiring an account on the CSDMS HPC (to be done before the clinic); 1) checking out the source code through a version control system; 2) building SNAC on the cluster; 3) getting familiar with SNAC by running a cookbook example in parallel and visualizing outputs; 4) modifying the source codes to customize a model.

Courtney Harris
VIMS
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Regional Ocean Modeling System (ROMS)

Chris Jenkins
INSTAAR
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Carbonate Models Clinic - carbo* suite

Chris Jenkins, Peter Burgess, Donald Potts

The carbo* set of modules use Lotka-Volterra population ecology, hydrodynamics, mesoscale simulators, an organism knowledge base (OKB), and habitat suitability indexes to model benthic carbonate production. The modeling covers coral reef, Halimeda and maerl, oyster, deep-water coral and bryozoan facies but can be extended to other types using the OKB. Recently the creation of rubble bioclasts has been addressed by modeling bioerosion, skeleton breakage, water column turbulence statistics, and clast ballistic trajectories in extreme weather.

Model runs are initiated for modern situations by automatically gathering data from global database and remote sensed resources such as MODIS AQUA, World Ocean Atlas, WaveWatch, GEBCO. Idealized scenarios – from paleogeography - can also be constructed and submitted for modeling. Time spans of up to 10,000 years have been run, using a burst technique with annual time-stepping. Seasonal stepping for shorter time span is also possible. The model outputs include profiles of organism biofacies, accumulation geometries, (1m3) ‘block of rock’ fabric & porosity models for generated materials, and 3D and animated mappings of the sediment facies.

The clinic will go through a typical setup and run, with some variations within the group. One of the modeled areas will be Molokai, Hawaii. Participants on the day will receive a copy of the software. Images of recent outputs are shown at http://instaar.colorado.edu/~jenkinsc/carboClinic2014/carboClinicImages2014.htm. Future developments will be discussed, particularly integration with terrigenous sediment and suspendate models, and nutrient loadings.

Laura Swiler
Sandia National Laboratories
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Dakota: A Toolkit for Sensitivity Analysis, Uncertainty Quantification, and Calibration

Dakota is an open-source toolkit with several types of algorithms, including sensitivity analysis (SA), uncertainty quantification (UQ), optimization, and parameter calibration. Dakota provides a flexible, extensible interface between computational simulation codes and iterative analysis methods such as UQ and SA methods. Dakota has been designed to run on high-performance computing platforms and handles a variety of parallelism. In this clinic, we will provide an overview of Dakota algorithms, specifically focusing on uncertainty quantification (including various types of sampling, reliability analysis, stochastic expansion, and epistemic methods), sensitivity analysis (including variance-based decomposition methods and design of experiments), and parameter calibration (including nonlinear least squares and Bayesian methods). The tutorial will provide an overview of the methods and discuss how to use them. In addition, we will briefly cover how to interface your simulation code to Dakota.

Mark Piper & Irina Overeem
CSDMS
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WMT: The CSDMS Web Modeling Tool

Mark Piper, Eric Hutton and Irina Overeem, CSDMS Integration Facility Boulder Colorado, United States
(mark.piper@colorado.edu)

The CSDMS Web Modeling Tool (WMT) is the web-based successor to the desktop Component Modeling Tool (CMT). WMT presents a drag-and-drop interface that allows users to build and run coupled surface dynamics models from a web browser on a desktop, laptop or tablet computer.

With WMT, a user can:
 Design a coupled model from a list of available components
 Edit the parameters of the model components
 Save the coupled model to a server, where it can be accessed from any computer
 Set run parameters, including the computer/cluster on which to run the model
 Share saved modeling projects with others in the community
 Submit jobs to the high-performance computing system

Although WMT is web-based, the building and configuration of a model can be done offline. The user can then reconnect to save a model and submit it for a run.
In this clinic we present an overview of WMT, including an explanation of the user interface, a listing of the currently available models and a discussion of how models can be run in operational mode or in reduced-input mode for teaching. We cap the clinic with a live demonstration of setting up, saving and running a coupled model on the CSDMS supercomputer system.

Scott Peckham
University of Colorado
{{{participants}}}

Introduction to the Basic Model Interface and CSDMS Standard Names

In order to simplify conversion of an existing model to a reusable, plug-and-play model component, CSDMS has developed a simple interface called the Basic Model Interface or BMI that model developers are asked to implement. In this context, an interface is a named set of functions with prescribed function names, argument types and return types. By design, the BMI functions are straightforward to implement in any of the languages supported by CSDMS, which include C, C++, Fortran (all years), Java and Python. Also by design, the BMI functions are noninvasive. A BMI-compliant model does not make any calls to CSDMS components or tools and is not modified to use CSDMS data structures. BMI therefore introduces no dependencies into a model and the model can still be used in a "stand-alone" manner. Any model that provides the BMI functions can be easily converted to a CSDMS plug-and-play component that has a CSDMS Component Model Interface or CMI.

Once a BMI-enabled model has been wrapped by CSDMS staff to become a CSDMS component, it automatically gains many new capabilities. This includes the ability to be coupled to other models even if their (1) programming language, (2) variable names, (3) variable units, (4) time-stepping scheme or (5) computational grid is different. It also gains (1) the ability to write output variables to standardized NetCDF files, (2) a "tabbed-dialog" graphical user interface (GUI), (3) a standardized HTML help page and (4) the ability to run within the CSDMS Modeling Tool (CMT).

This clinic will explain the key concepts of BMI, with step-by-step examples. It will also include an overview of the new CSDMS Standard Names, which provide a standard way to map input and output variable names between component models as part of BMI implementation. Participants are encouraged to read the associated CSDMS wiki pages in advance and bring model code with specific questions. See
1) BMI Page: BMI_Description
2) Standard Names Page: CSDMS_Standard_Names

Monte Lunacek
University of Colorado
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Interactive Data Analysis with Python

Recent additions to Python have made it an increasingly popular language for data analysis. In particular, the pandas library provides an R-like data-fame in Python, which is data structure that resembles a spreadsheet. This provides an efficient way to load, slice, reshape, query, summarize, and visualize your data. Combining this with numpy, maplotlib, and scikit-learn creates a powerful set of tools for data analysis. In this hands-on tutorial, we will cover the basics of numpy, matplotlib, pandas, and introduce scikit-learn.

Joshua Watts
Arizona State University
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Agent-Based Modeling Research: Topics, Tools, and Methods

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.

Participants

Interested to see who registered for the meeting?

Reimbursement

Within its budget, CSDMS intends to support member applicants to attend the annual meeting. Towards this goal, we encourage members to fully or partially cover their expenses if capable. We additionally thank those in the industry and agency fields for understanding that 1) we cannot compensate federal agency participants since our own funding is from NSF, and 2) we request that our industrial/ corporate participants cover their own costs thereby allowing more academic participants to attend.

To the extent possible, CSDMS intends to reimburse the registration fee, lodging (shared rooms at 100% and single rooms at 50% at Millennium Harvest House Hotel), and a limited amount of travel expenses of qualified registrants - those members who have attended all three days of the meeting and are not industry or federal employees.

Registration fee, lodging and possible additional travel costs for the one day Post-meeting Software Bootcamp will not be reimbursed.

Important for foreign travelers requesting reimbursement: If you need a visa to travel to USA, select a business visa. If you need an invitation letter, please email csdms@colorado.edu soonest. Also indicate whether specific wording is required in the letter. Second, we will need to copy the entry stamp in your passport sometime during the meeting as proof that you were here on business as required by US tax laws for reimbursement (especially when dealing with airfare.) We are only able to provide reimbursement for airfare within the U.S.

Travel, Lodging and Conference Center Information

The meeting will be held at UCAR Conference Center
Lodging for meeting participants is at the Millennium Harvest House Hotel
Please visit the CSDMS contact page for advice on ways to reach Boulder from the Denver Airport.

Student Scholarships

Note: Scholarship submissions closed. For those who applied, we will reveal soon if you won a student scholarship.

Important dates

February 1^st: Registration opens
March 1^st: Deadline student scholarship applications
April 14^th: Deadline abstract submission & registration (extended)
May 20-22^th: CSDMS annual meeting
May 23^rd: Post-meeting Software Bootcamp
May 23^rd: CSDMS Executive and Steering committees meeting (by invitation only)

@@ Line 90: / Line 90: @@
 | affiliation = UNESCO-IHE & Deltares
 | title = Estuarine morphodynamics : better be certain about uncertainty
-| abstract =
+| abstract = Mick van der Wegen, UNESCO-IHE and Deltares Delft , Netherlands. m.vanderwegen@unesco-ihe.org<br />Bruce E. Jaffe, USGS Santa Cruz California, United States. bjaffe@usgs.gov<br />Gerard Dam, UNESCO-IHE Delft California, Netherlands. dam@svasek.nl<br />Dano Roelvink, UNESCO-IHE and Deltares and TU Delft Delft California, Netherlands. d.roelvink@unesco-ihe.org<br /><br />Process-based models are able to predict velocity fields, sediment transport and associated morphodynamic developments over time. These models can generate realistic morphological patterns and stable morphodynamic developments over time scales of millennia under schematized model settings. However, more realistic case studies raise questions on model skill and confidence levels. Process-based models require detailed information on initial conditions (e.g. sediment characteristics, initial distribution of sediment fractions over the model domain), process descriptions (e.g. roughness and sediment transport formulations) and forcing conditions (e.g. time varying hydrodynamic and sediment forcing). The value of the model output depends to a high degree on the uncertainty associated with these model input parameters.<br /><br />Our study explores a methodology to quantify model output uncertainty levels and to determine which parameters are responsible for largest output uncertainty. Furthermore we explore how model skill and uncertainty develop over time. We describe the San Pablo Bay (USA) case study and the Western Scheldt (Netherlands) case study in a 100 year hindcast and a more than 100 year forecast.<br /><br />Remarkably, model skill and uncertainty levels depend on model input parameter variations only to a limited extent. Model skill is low first decades, but increases afterwards to become excellent after 70 years. The possible explanation is that the interaction of the major tidal forcing and the estuarine plan form governs morphodynamic development in confined environments to a high degree.
 }}{{Keynote-clinics
 | name = Rebecca Caldwell

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