Form:CSDMS annual meeting

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

The online conference registration is a three step process:

Step 1: Log in	Log in (or create account for none CSDMS members) Forgot username? Search or email:CSDMSweb@colorado.edu
Step 2: Register	Start registration
Step 3: Pay registration fee ($200) or $240 when including Post-meeting Software Bootcamp Third party website

Note 1: You only are successfully registered by fulfilling the above steps
Note 2: Do you want to make changes to you abstract?

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2. Select your registration record in "participants" and start making changes by clicking "Edit registration".

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 {{{participants}}}

Computational Fluid Dynamics and Sediment Transport

Jim McElwaine Durham University (UK) {{{participants}}}

Modeling Granular Flows

Alexey Voinov Faculty of Geo-Information Science and Earth Observation (ITC) {{{participants}}}

COMPLEX

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

Unifying Tectonics and Surface Processes in Geodynamics

Elowyn Yager Center for Ecohydraulics, University of Idaho {{{participants}}}

Modeling the effects of vegetation on bedload transport

David Pyles Chevron Center of Research Excellence, Colorado School of Mines {{{participants}}}

What field geologists look for in numerical simulations

Eric Larour JPL {{{participants}}}

Ice Sheet Model Intercomparisons

Mick van der Wegen UNESCO-IHE {{{participants}}}

How to quantify uncertainty in morphodynamics model predictions.

Rebecca Caldwell Indiana University {{{participants}}}

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 {{{participants}}}

Coupling vegetation to the ANUGA flow model

Atilla Lazar University of Southampton {{{participants}}}

Linking social sciences, bio-physical sciences and governance in a dynamic framework

Rudy Slingerland Penn State {{{participants}}}

The FESD Delta Dynamics Modeling Collaboratory: A Progress Report

Andrew Nicholas University of Exeter {{{participants}}}

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Clinic Invitees

Fotis Sotiropoulos University of Minnesota {{{participants}}}

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 CIRES {{{participants}}}

Landlab

Eunseo Choi UTIG {{{participants}}}

SNAC

Courtney Harris VIMS {{{participants}}}

ROMS

Chris Jenkins INSTAAR {{{participants}}}

Carbonate

TBD {{{participants}}}

DAKOTA

CSDMS Staff CSDMS {{{participants}}}

CMTWeb

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

Introduction to the Basic Model Interface and CSDMS Standard Names

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

Chris Duffy (not yet confirmed) Penn State {{{participants}}}

PIHM

Monte Lunacek University of Colorado {{{participants}}}

Interactive Data Analysis with Python

Post-meeting Software Bootcamp

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