Revision as of 10:48, 30 September 2019 by WikiSysop (talk | contribs) (Redirected page to CSDMS meeting 2019)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)

Redirect page

Redirect to:

CSDMS 3.0 - Bridging Boundaries


Click here to view the final agenda.


Registration is closed. See you all soon!


The meeting will bring together experts in earth surface process modeling in a three-day hands-on workshop to identify challenges in bridging boundaries in our current process understanding, both fundamentally in the earth surface processes as well as in the modeling approaches and technology. This includes interdisciplinary boundaries and how best to identify and address these numerically.
The CSDMS3.0 - Bridging Boundaries 2019 Annual Meeting aims to:

  1. Identify new frontiers in fundamental process understanding of the earth surface. New algorithms, cyberinfrastructure development and new model couplings appear paramount to explore important process dynamics and linkages.
  2. Identify critical missing components in our ability to overcome model and process boundaries.
  3. Build researcher-to-researcher connections. Better connect earth surface process modelers with modelers of primary and secondary forcings, as well as social sciences and engineers to allow exploration of the human dimensions in earth surface processes.

As in past meetings, keynote speakers are by invitation only, and poster presentations are the general media. The meeting will include:

  • State-of-the art keynote presentations in earth-surface dynamics
  • Hands-on clinics related to community models, tools and approaches
  • Transformative software products and approaches designed to be accessible, easy to use, and relevant
  • Breakout sessions
  • Poster Sessions
  • Consider signing up for the pre-conference training sessions as well. See below for more information on these.

Poster Information: The poster boards are configured for 4' wide by 6' tall (portrait orientation) posters.

Keynote Speakers

Follow the water: Post-glacial landscape evolution in the Central Lowlands
University of Illinois at Urbana-Champaign
United States
Repeated continental glaciation of the US Central Lowlands disrupted pre-Pleistocene fluvial drainage networks by filling valleys, rerouting major rivers, and incising oversize meltwater channels. Post-glacial landscapes are characterized by large fractions of non contributing area (NCA) which does not contribute flow to external drainage networks by steepest decent algorithms. Analysis of land surfaces most recently glaciated between 130,000 and 10,000 years ago suggests that NCA is lost over time as fluvial networks are reestablished. Low surface slopes combined with significant fractions of NCA make such fluvial network growth difficult to reconcile with standard treatments of flow routing. We develop modules in Land Lab that allow for connection of NCA via filling and spilling from closed depressions on the surface and through groundwater flow across subtle surface water divides to explore the impacts of these mechanisms of flow accumulation on the pace of evolution and morphology of resulting river networks. This work highlights the more general need to consider the relationship, or lack of relationship, between topography and river discharge.
JOSS: Journal of Open Source Software
University of Colorado, Boulder
United States
JOSS is a developer friendly, peer reviewed academic journal for research software packages, providing a path to academic credit for scholarship disseminated via software. I'll give a tour of the journal, its submission/review process, and opportunities to get involved.
How extensional tectonics and surface processes interact to shape continental plate boundaries
Geological Survey of Norway
Seismic observations document how substantial amounts of sediments may be transported from the onshore to the offshore during formation of extensional continental margins. Thick sedimentary packages are, for example, found on the margins of Norway, the eastern US coast, and the Gulf of Mexico. In contrast, the Goban Spur, Galicia Bank, and the Red Sea are examples of sediment-starved margins. Such variations in the amount of sediments impact not only the development of offshore sedimentary basins, but the changes in mass balance by erosion and sedimentation can also interact with extensional tectonic processes. In convergent settings, such feedback relationships between erosion and tectonic deformation have long been highlighted: Erosion reduces the elevation and width of mountain belts and in turn tectonic activity and exhumation are focused at regions of enhanced erosion. But what is the role played by surface processes during formation of extensional continental margins? In this lecture, I will discuss geodynamic experiments that explore the response of continental rifts to erosion and sedimentation from initial rifting to continental break-up. These experiments show how the interaction of extensional tectonics and surface processes can fundamentally alter the width and topography of continent-ocean boundaries.
2019 Diversity Panel
Boise State University
United States
This is a diversity panel discussion at the CSDMS 2019 annual meeting
Machine Learning and Coastal Morphodynamics
University of North Carolina at Greensboro
United States
Numerical modeling is at the core of prediction in coastal settings. Observational data is used in tandem with models for a variety of modeling tasks, but the perhaps the coupling could be tighter? I will discuss a range of Machine Learning tools that co-workers and I have integrated with coastal morphodynamic models that allow for a tight coupling of models and data, and provide morphodynamic insight.
The National Hydrologic Model: coordinated, comprehensive, and consistent hydrologic modeling at multiple scales for the conterminous United States
United States
The National Hydrologic Model (NHM) was developed to support coordinated, comprehensive, and consistent hydrologic modeling at multiple scales for the conterminous United States. The NHM development has been driven for the past decade by specific applications to meet stakeholder needs for accessible, adaptable surface water models that address local hydrologic modeling needs. NHM-based applications provide information to scientists, water resource managers, and the public to support advanced scientific inquiry and effective decision-making. The NHM infrastructure supports the execution of the Monthly Water Balance Model (NHM-MWBM) and the daily Precipitation Runoff Modeling System (NHM-PRMS). The NHM-PRMS balances all components of the water budget and can include simulation of stream temperature. Complete local models can be subset from the NHM-PRMS, then adapted and applied with local expertise to address stakeholder needs, providing nationally-consistent, locally informed, stakeholder relevant results. The NHM represents an opportunity for collaboration in the hydrologic community.
The CSDMS Python Modeling Tool (PyMT)
University of Colorado, Boulder/CSDMS IF
United States
CSDMS’s newly released Python Modeling Tool (PyMT) is an open source python package that provides convenient tools for coupling of models that use the Basic Model Interface. Historically, earth-surface process models have often been complex and difficult to work with. To help improve this situation and make the discovery process more efficient, the CSDMS Python Modeling Tool (PyMT) provides an environment in which community-built numerical models and tools can be initialized and run directly from a Python command line or Jupyter notebook. To illustrate how PyMT works and the advantages it provides, we will present a demonstration of two coupled models. By simplifying the process of learning, operating, and coupling models, PyMT frees researchers to focus on exploring ideas, testing hypotheses, and comparing models with data.
The Machine Learning Landscape
University of Colorado
United States
Panel discussion on AI/ML
Modeled Postglacial Landscape Evolution at the Southern Margin of the Laurentide Ice Sheet: Hydrological Connection of Uplands Controls the Pace and Style of Fluvial Network Expansion
University of Illinois at Urbana-Champaign
United States
Landscapes of the US Central Lowland were repeatedly affected by the Laurentide Ice Sheet. Glacial processes diminished relief and disrupted drainage networks. Deep valleys carved by glacial meltwater were disconnected from the surrounding uplands. The upland area lacking surface water connection to the drainage network is referred to as non-contributing area (NCA). Decreasing fractions of NCA on older surfaces suggests that NCA becomes drained over time. We propose that the integration could occur via: 1) capture of NCA as channels propagate into the upland or, 2) subsurface or intermittent surface connection of NCA to external drainage networks providing increased discharge to promote channel incision. We refer the two cases as “disconnected” and “connected” since the crucial difference between them is the hydrological connection of the upland to external drainage. We investigate the differences in evolution and morphology of channel networks in low relief landscapes under disconnected and connected regimes using the LandLab landscape evolution modeling platform. We observe substantially faster rates of erosion and integration of the channel network in the connected case. The connected case also creates longer, more sinuous channels than the disconnected case. Sensitivity tests indicate that hillslope diffusivity has little influence on the evolution and morphology. The fluvial erosion coefficient has significant impact on the rate of evolution, and it influences the morphology to a lesser extent. Our results and a qualitative comparison with landscapes of the glaciated US Central Lowland suggest that connection of NCAs is a potential control on the evolution and morphology of post-glacial landscapes.
Modeling the degradation of ice-rich permafrost landscapes
Alfred Wegener Institute for Polar and Marine Research
Thawing of permafrost potentially affects the global climate system through the mobilization of greenhouse gases, and poses a risk to human infrastructure in the Arctic. The response of ice-rich permafrost landscapes to a changing climate is particularly uncertain, and challenging to be addressed with numerical models. A main reason for this is the rapidly changing surface topography resulting from melting of ground ice, which is referred to as thermokarst. It is expressed in characteristic landforms which alter the hydrology, the surface energy balance, and the redistribution of snow of the entire landscapes. Polygonal patterned tundra which is underlain by massive ice-wedges, is a prototype of a sensitive permafrost system which is increasingly subjected to thermokarst activity throughout the Arctic.

In this talk I will present a scalable modeling approach, based on the CryoGrid land surface model, to investigate the degradation of ice-wedges. The numerical model takes into account lateral fluxes of heat, water, and snow between different topographic units of polygonal tundra and simulates topographic changes resulting from melting of excess ground ice (i.e., thermokarst), and from lateral erosion of sediment. We applied the model to investigate the influence of hydrological conditions on the development of different types of ice-wedge polygons in a study area in northern Siberia. We further used projections of future climatic conditions to confine the evolution of ice-wedge polygons in a changing climate, and assessed the amount of organic matter which could thaw under different scenarios. In a related study for a study site in northern Alaska, we demonstrated that the model setup can be used to study the effect of infrastructure on the degradation of ice-wedges.

Altogether, our modeling approach can be seen as a blueprint to investigate complexly inter-related processes in ice-rich permafrost landscapes, and marks a step forward towards an improved representation of these landscapes in large-scale land surface models.
Understanding and Improving the Performance of Scientific Software and its Humans
University of Oregon
United States
Understanding the performance of scientific applications can be a challenging endeavor given the constant evolution of architectures, programming models, compilers, numerical methods and the applications themselves. Performance integration testing is still not a reality for the majority of high-performance applications because of the complexity, computational cost, and lack of reliable automation. Hence, as part of the DOE SciDAC program, we are working on creating robust performance analysis workflows that capture application-specific performance issues and can be maintained and extended by the application scientists without requiring an external performance “expert”. The consumers of performance data include application developers, performance models, and autotuners. Once appropriate and sufficient performance data is available, our approach to using it to guide optimization is three-fold: (i) we investigate the most effective way to present performance results to the code developers (ii) we automate the selection of numerical methods based on generic performance models (as part of the NSF-funded Lighthouse project) and (iii) we explore the use of different types of performance models in low-level autotuning systems to reduce the size of the parameter search space. While code generation and autotuning are important for achieving performance portability, the majority of code development (including optimization) is still performed by humans. As part of the DOE IDEAS project, we are developing data-based methodologies to try to understand better how human teams work most effectively in developing high-quality, high-performance, enduring scientific software.
Exploring delta morphodynamics using the CSDMS BMI to couple fluvial and coastal processes
ORISE Postdoctoral Fellow, US EPA
United States
Using the CSDMS tools and resources, we have developed a new model coupling river, floodplain, and coastal processes to explore how interactions between upstream and downstream controls in a fluvio-deltaic system affect river channel processes and large-scale delta morphology. The River Avulsion and Floodplain Evolution Model (RAFEM, written in Python) and Coastline Evolution Model (CEM, written in C) are coupled using the CSDMS Basic Model Interface (BMI) and are available as part of the CSDMS software stack. Using the CSDMS High Performance Computing Cluster and the Dakota toolkit, we have explored how the wave climate (wave heights and offshore approach angles), sea-level rise rate, and the amount of in-channel aggradation required to trigger an avulsion (superelevation) influence avulsion frequency and location, impacting both delta morphology and the resulting stratigraphy. The model is structured modularly to invite further couplings with additional model components in the future.
Coupling natural-human systems at the decision-making scale
University of Waterloo
Our understanding of human systems has been synthesized and advanced by computationally representing human decision-making in agent-based models. Whether representing individuals, households, firms, or larger organization, agent-based modelling approaches are often used to model processes (e.g., urban growth, agricultural land management) that directly effect and are affected by natural systems. Contemporary efforts coupling models of human and natural systems have demonstrated that results significantly differ from isolated representations of either system. However, coupling models of human and natural systems is conceptually and computationally challenging. In addition to discussing these challenges and approaches to overcoming them, this talk will also suggest that research quantifying natural processes at the decision-making scale of the land user is needed. Using structure-from-motion and unmanned aerial vehicle (UAV) imagery, we can accurately quantify natural processes like soil erosion to a high level of accuracy and that frequently modelled processes (e.g., flow accumulation) typically differ from reality. Novel data from the field or parcel scale are needed to calibrate and validate our representation of natural processes if we are to advance our representation of feedbacks between natural processes and human decision-making. By improving our representation of both natural processes and human decision-making at the scale of the decision-maker, we add confidence in our ability to scale out to larger spatial extents that are reflective of natural processes (e.g., watershed) or policy driving human decisions from municipal, state, or national governments.
Sequence Stratigraphic Modeling in Landlab
LDEO, Columbia U
United States
Sequence is a modular 2D (i.e., profile) sequence stratigraphic model that is written in Python and implemented within the Landlab framework. Sequence represents time-averaged fluvial and marine sediment transport via differential equations. The modular code includes components to deal with sea level changes, sediment compaction, local or flexural isostasy, and tectonic subsidence and uplift. Development of the code was spurred by observations of repetitive stratigraphic sequences in western Turkey that are distorted by tectonics.
meanderpy: A simple model of meandering sheds light on channel kinematics and autogenic counter point bars
Bureau of Economic Geology, The University of Texas at Austin
United States
meanderpy is a Python implementation of a simple kinematic model of meandering, based on the Howard and Knutson (1984) model. In contrast with previous implementations, we assume a simple linear relationship between curvature and migration rate and, using time-lapse satellite imagery, show that the model predicts 55% of the variance in migration rates in seven rivers of the Amazon Basin. It also predicts the formation of autogenic counter point bars: deposits related to channel segments along which the curvature and migration rate vectors have opposing orientations. These finer-grained deposit types tend to form on the upstream side of high-curvature, short bends that rapidly translate downstream. Wrapping simple geomorphic surfaces around the centerlines allows us to build three-dimensional stratigraphic models of both fluvial and submarine meandering systems.
CSDMS 3.0 updates
University of Colorado
United States
CSDMS 3.0 updates

Clinic Leaders

Model Calibration with Dakota
University of Colorado, Boulder
United States
Many geophysical models require parameters that are not tightly constrained by observational data. Calibration represents methods by which these parameters are estimated by minimizing the difference between observational data and model simulated equivalents (the objective function). Additionally, uncertainty in estimated parameters is determined.

In this clinic we will cover the basics of model calibration including: (1) determining an appropriate objective function, (2) major classes of calibration algorithms, (3) interpretation of results.

In the hands-on portion of the the clinic, we will apply multiple calibration algorithms to a simple test case. For this, we will use Dakota, a package that supports the application of many different calibration algorithms.
Landcover and landform classification using deep neural networks
Northern Arizona University
United States
This clinic will introduce deep learning methods for semantic segmentation of fluvial sedimentary landforms and riparian environments, using high-resolution aerial imagery. Deep neural networks are the current state-of-the-art for discrete classification of remotely sensed imagery from Earth observation platforms. The clinic will guide users through the process of preparing training datasets, training models, and evaluation. A number of different deep convolutional neural network architectures for image feature extraction and pixel-scale classifications will be explored and compared. The clinic will use the keras and tensorflow libraries within the python programming language. This hands-on class will be taught using Google colab through a browser, with the materials hosted on github. Participants will require a working knowledge of python. Some working knowledge of machine learning would be helpful, but we will assume no prior experience with machine/deep learning, neural networks, tensorflow, or keras.
Real Time ADCIRC Modelling for Coastal Zone Decision Support
Seahorse Coastal Consulting
United States
The ADCIRC finite element coastal ocean model is used in real time decision support services for coastal and riverine hydrodynamics, tropical cyclone winds, and ocean wave modelling for public sector agencies including NOAA, FEMA, Coast Guard, and the US Army Corps of Engineers, among others. Recent developments in ADCIRC's real time automation system, the ADCIRC Surge Guidance System (ASGS), have now enabled real time modelling of active flood control scenarios (manipulation of pumps and flood gates) for decision support during riverine floods and tropical cyclone events. During these events, the results are presented to official decision makers with the Coastal Emergency Risks Assessment (CERA) web application, an intuitive and interactive tool that integrates model data with measured data to provide situational awareness across the area of responsibility. Case study events will be described, including official decisions that have been made with the ADCIRC in North Carolina (Irene 2011), Louisiana (Mississippi River flooding in 2016), and during the 2017 and 2018 hurricane seasons for Hurricanes Harvey, Irma, Maria, Florence, and Michael.
Pangeo: Scalable Geoscience Tools in Python — Xarray, Dask, and Jupyter
United States
Earth scientists face serious challenges when working with large datasets. Pangeo is a rapidly growing community initiative and open source software ecosystem for scalable geoscience using Python. Three of Pangeo’s core packages are 1) Jupyter, a web-based tool for interactive computing, 2) Xarray, a data-model and toolkit for working with N-dimensional labeled arrays, and 3) Dask, a flexible parallel computing library. When combined with distributed computing, these tools can help geoscientists perform interactive analysis on datasets up to petabytes in size. In this interactive tutorial we will demonstrate how to employ this platform using real science examples from hydrology, remote sensing, and oceanography. Participants will follow along using Jupyter notebooks to interact with Xarray and Dask running in Google Cloud Platform.
Making your models and data FAIR - Findable, Accessible, Interoperable, and Reusable
U.S. Geological Survey
United States
Are you confused about the best way to make your models and data accessible, reusable, and citable by others? In this clinic we will give you tools, information, and some dedicated time to help make your models and data FAIR - findable, accessible, interoperable and reusable. Models in the CSDMS ecosystem are already well on their way to being more FAIR than models that are not. But here, you will learn more about developments, guidelines, and tools from recent gatherings of publishers, repository leaders, and information technology practitioners at recent FAIR Data meetings, and translate this information into steps you can take to make your scientific models and data FAIR.
Hands-on with the Python Modeling Toolkit
United States
PyMT is the “Python Modeling Toolkit”. It is an Open Source Python package, developed by the Community Surface Dynamics Modeling System, that provides tools used to couple models that expose the Basic Model Interface (BMI). PyMT is:
  • a toolbox for coupling models of disparate time and space scales,
  • a collection of Earth-surface models, and
  • an extensible plug-in framework for user-contributed models.

In this hands-on clinic we will use Jupyter Notebooks to explore how to run standalone models within PyMT. Since all PyMT models are based on the BMI, they all share the same user interface and so if you know how to run one model, you know how to run all PyMT models. We will then look at some of the model-coupling tools packaged with PyMT and how they can be used for more complex couplings. We will then run through examples that use these tools to couple models to data as well as to other PyMT models.

We highly recommend that clinic attendees come with a laptop with the Anaconda Python distribution installed.
Morphological modelling using Delft3D Flexible Mesh
During the clinic we'll introduce the new Delft3D Flexible Mesh modeling environment. We'll discuss the basic features and set up a simple 2D morphological model. The ongoing developments and the possibility to use BMI for runtime interaction will be presented as well. The user interface runs on Windows, so make sure that you have a Windows computer or virtual machine available during the meeting. The user interface will be provided precompiled; the computational kernels you'll have to compile yourself. We'll provide instructions on how to compile the FORTRAN/C kernels before the clinic.
Model sensitivity analysis using SALib
Tulane University
United States
Interested in which variables influence your model outcome? SALib (Sensitivity Analysis Library) provides commonly used sensitivity analysis methods implemented in a Python programming language package. In this clinic we will use these methods with example models to apportion uncertainty in model output to model variables. We will use models built with the Landlab Earth-surface dynamics framework, but the analyses can be easily adapted for other model software. No prior experience with Landlab or Python is necessary.
Developing and teaching interactive sedimentology and stratigraphy computer activities
Rice University
United States
In this clinic, we will first demonstrate existing interactive computer-based activities used for teaching concepts in sedimentology and stratigraphy. This will be followed by a hands-on session for creating different modules based on the participants’ teaching and research interests. Active learning strategies improve student exam performance, engagement, attitudes, thinking, writing, self-reported participation and interest, and help students become better acquainted with one another (Prince, 2004). Specifically, computer-based active learning is an attractive educational approach for post-secondary educators, because developing these activities takes advantage of existing knowledge and skills the educator is likely to already have.

The demonstration portion of the clinic will focus on the existing rivers2stratigraphy ( activity, which illustrates basin-scale development of fluvial stratigraphy through adjustments in system kinematics including sandy channel migration and subsidence rates. The activity allows users to change these system properties, so as to drive changing depositional patterns. The module utilizes a rules based model, which produces realistic channel patterns, but simplifies the simulation to run efficiently, in real-time. The clinic will couple rivers2stratigraphy to a conventional laboratory activity which interprets an outcrop photograph of fluvial stratigraphy, and discuss logistics of using the module in the classroom.

For the second part of the clinic, familiarity with Python will be beneficial (but is not required); we will utilize existing graphical user interface (GUI) frameworks in developing new activities, aimed to provide a user-friendly means for students to interact with model codes while engaging in geological learning. Participants should plan to have Python installed on their personal computers prior to the workshop, and a sample module will be emailed beforehand to let participants begin exploring the syllabus.

Prince, M. (2004). Does Active Learning Work? A Review of the Research. Journal of Engineering Education, 93(3), 223-231. doi: 10.1002/j.2168-9830.2004.tb00809.x.
BMI Live!
CSDMS IF, University of Colorado, Boulder
United States
In software engineering, an interface is a group of functions with prescribed names, argument types, and return types. When a developer implements an interface for a piece of software, they fill out the details for each function while keeping the signatures intact. CSDMS has developed the Basic Model Interface (BMI) for facilitating the conversion of a model written in C, C++, Fortran, Python, or Java into a reusable, plug-and-play component. By design, BMI functions are simple. However, when trying to implement them, the devil is often in the details.

In this hands-on clinic, we'll take a simple model of the two-dimensional heat equation, written in Python, and together we'll write the BMI functions to wrap it, preparing it for transformation into a component. As we develop, we’ll explore how to use the wrapped model with a Jupyter Notebook.

To get the most out of this clinic, come prepared to code! We'll have a lot to write in the time allotted for the clinic. We recommend that clinic attendees have a laptop with the Anaconda Python distribution installed. We also request that you review the

before the start of the clinic.
CUAHSI Services for Hydrologic Modeling and Data
United States
This clinic will introduce CUAHSI products that support hydrologic modeling and analysis workflows. The HydroShare and JupyterHub platforms will be used to demonstrate the cyberinfrastructure capabilities that have been designed for community modeling and educational purposes. Participants should have a working knowledge of Python and should bring a laptop.
An Introduction to CUDA-enabled DES3D
CERI, University of Memphis
United States
DES3D (Dynamic Earth Solver in Three Dimensions) is a flexible, open-source finite element solver that models momentum balance and heat transfer in elasto-visco-plastic material in the Lagrangian form using unstructured meshes. It provides a modeling platform for long-term tectonics as well as various problems in civil and geotechnical engineering. On top of the OpenMP multi-thread parallelism, DES3D has recently adopted CUDA for GPU computing. The CUDA-enabled version shows speedup of two to three orders of magnitude compared to the single-thread performance, making high-resolution 3D models affordable. This clinic will provide an introduction to DynEarthSol3D’s features and capabilities and hands-on tutorials to help beginners start using the code for simple tectonic scenarios. Impact of the two types of parallelization on performance will be demonstrated as well.

Interested in providing a clinic during a next annual meeting? Contact CSDMS@Colorado.EDU.


Nikolai Ulltang.jpg

Within its budget, CSDMS intends to partially 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.

CSDMS is able to provide the following meeting support:
NOTICE: The maximum number of participants that can be supported for lodging was reached on March 5th, 2019. Feel free to register for the meeting but realize that you are responsible for supporting your own lodging. CSDMS has negotiated a preferred rate for attendees still needing lodging at the Millennium Harvest House Hotel. You can view and book rooms through this link: Millennium Preferred Meeting Rates

  • Breakfast and lunch each day of the meeting and one dinner, shuttle service between the Boulder Marriott/Residence Inn/Millennium Harvest House Hotel and meeting venue will be provided for all registrants.

Scholarship recipients, Keynote presenters, Clinic leaders and Awardees - travel support, registration support and lodging as specified in your invitation letter, breakfast and lunch each day of the meeting and one dinner, shuttle service between meeting hotel and meeting venue.

Specific reimbursement procedures will be emailed to qualified attendees along with your final confirmation early May, 2019.

Important for foreign travelers: If you need a visa to travel to USA, select a business visa. Please email CSDMS@Colorado.EDU as soon as possible if you need an invitation letter along with your passport number, affiliation and entry/exit dates and indicate any specific wording if required. 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 (especially when dealing with airfare reimbursements).

Travel, Lodging and Conference Center Information

Meeting venue: SEEC at the University of Colorado's East Campus in Boulder.
Hotel: The CSDMS supported hotel block will be split between adjacent hotels, the Boulder Marriott and the Residence Inn. On March 5th the CSDMS-supported rooms were fully booked and therefore, no additional hotel support is available for registrants after that date. CSDMS has negotiated a preferred rate at the Millennium Harvest House Hotel for those still needing lodging (Unfortunately, the CSDMS meeting budget does not allow us to provide hotel support or reimbursement for these rooms).
Transportation: You can book transportation between DIA and Boulder here: Green Ride Boulder. And information on how to find Green Ride Boulder at DIA.

A bus between the designated Hotels (Marriott/Residence Inn and Millennium) and the meeting venue will be provided each day (the shuttle is not able to stop at other hotels). We will also provide transportation from the designated Hotel to the banquet (again, the shuttle is not able to stop at other hotels). Please note that the parking adjacent to the SEEC building requires payment for non-permit holders. You will need to park in the limited designated areas and provide payment in the adjacent kiosks.

Pre-conference events

The following will apply to two of the pre-conference events: Software Carpentry workshop, and Quantifying Uncertainty in Earth Systems :

  • Registration is open until April 1st (or until program fills) and is handled through the 2019 meeting site.
  • Each is capped at 30 participants (all first paid first serve), and it has a $30 registration fee.
  • Participant will be responsible for cost / organization of their extra day of hotel accommodation and dinner. Costs will not be reimbursed.
  • We will cover coffee, continental breakfast and lunch during each of the events.

1) Software Carpentry workshop

CSDMS will host a one-day pre-conference Software Carpentry workshop on Monday, May 20, 2019. The goal of the workshop is to teach basic programming skills that will be useful for scientific research and model development. This is an intensive, hands-on workshop, during which certified instructors will cover basic elements of:

  • the Unix bash shell,
  • Python programming, and
  • Github for version control.

The instructors, Mariela Perignon and Mark Piper, are earth scientists, so lessons and examples will be targeted toward relevant problems in your field. The workshop intentionally precedes the CSDMS Annual Meeting so that the skills you develop can be used in the clinics during the meeting.

2) Quantifying Uncertainty in Earth Systems

This one-day pre-conference workshop provided by Professor Jef Caers, Stanford University on Monday, May 20, 2019 will cover the quantification of uncertainty in Earth Systems using a protocol termed Bayesian Evidential Learning. The course will walk through the steps of this protocol consisting of prior model specification, monte Carlo & model falsification, global sensitivity analysis, Mont-Carlo based inverse modeling and posterior model falsification.

The workshop will focus on the high-level principles and understanding, and on actual practical examples rather than the technical or theoretical details. There will be no software exercises on-site, but such resources will be made available during the workshop with some demos using Jupyter notebooks.

The application will focus on subsurface systems as an example of Earth systems, in particular, I will cover application in groundwater hydrology as well as shallow and deep geothermal energy as specific examples.

Prerequisites: participant will need to have taken a basic course in statistics and probability theory, know about Bayes Rule, probability distributions, expectation, conditional probability and the basics of statistical calculations and exploratory data analysis.

Reference: Quantifying Uncertainty in Subsurface Systems, Scheidt, C., Li, L. & Caers, J., 2018, Wiley-AGU Monograph.


Student Scholarships and travel awards

CSDMS Scholarships

This year CSDMS is offering a limited number of scholarships (up to 7) for graduate students to attend the CSDMS annual meeting. These scholarships will be offered for the purpose of increasing participation of underrepresented students or those that have not previously attended a CSDMS Annual Meeting. To be eligible, graduate students need to meet the following requirements:

  • Attend the whole meeting (May 21-23, 2019)
  • Submit an abstract
  • Be enrolled as a graduate student at the time of the meeting (bring proof)
  • Submit a letter of motivation that states why you wish to participate in the meeting, and explain how your participation would enhance diversity in the field of natural hazards and surface dynamics modeling. Be sure to mention if it is your first time attending.

Send your application materials to by February 8th, 2019. The CSDMS scholarships will cover:

  • Registration costs (you will still need to pay the registration fee, but will be reimbursed after attending the meeting)
  • Hotel accommodations for three nights, May 20, 21 and 22st. (as outlined in Travel/Lodging section above - 100% paid if you agree to a roommate)
  • Travel (air fare ONLY within the United States and local shuttle transport)
  • Per diem to help reimburse the cost of meals from 21-23 May 2019 not offered in the conference schedule

All applicants will receive confirmation of their submission. Please notify us at if you do not receive confirmation within 24 hours of submission.

LAND Travel Awards


The journal LAND is inviting applications for two Travel Awards for postdoctoral fellows and PhD students in the area of land systems science to attend the CSDMS annual meeting. The nominations and applications will be assessed by an Evaluation Committee chaired by the Editor-in-Chief of Land: Prof. Andrew Millington.

Candidates’ Requirements:

  • Applicants must be postdoctoral fellows or PhD students involved in land systems science;
  • Applicants will attend an international conference in 2019 to present their research (oral presentation or poster).

Applicants need to submit the following documents:

  • An abstract of your work (500 words);
  • A short CV with complete list of publications;
  • The conference you plan to attend and the oral or poster abstract that will be presented;
  • A letter of recommendation from a supervisor or PI (Principal Investigator). The supervisor or PI should sign and confirm that the applicant fulfills requirements.

The Award will consist of 800 (Swiss Francs) each. Please send the applications here ( by 15 January 2019. The winner will be announced in Land by 1 March 2019.

Important dates

  • January 14th: Deadline for student modeler competition submission
  • January 14th: Registration opens and early registration fees ($200) apply till April 1st
  • January 15th: Deadline LAND travel awards
  • February 1st: Student modeler competition results announced
  • February 8th: Deadline for student scholarship applications CSDMS
  • February 28th: Scholarship awardees notified
  • April 1st: Deadline: a) abstract submission, b) discounted early registration ($200), and c) meeting supported hotel reservations (unless our cap of 75 lodgers has already been met). After this deadline, reservations and accommodation costs will be responsibility of participant. Regular registration fee ($400) April 2 to May 1.
  • May 9th: Deadline registration
  • May 20th: CSDMS 1day pre conference workshops
  • May 21-23rd: CSDMS annual meeting
  • May 24th: CSDMS Executive and Steering committees meetings (by invitation only)

CSDMS-logo-color-tagline-hor high.png