Nuclear fuel cycle activities of the Former Soviet Union have
resulted in significant contamination of the environment in
western Siberia. Pacific Northwest National Laboratory (PNNL) is
developing, jointly with their Russian counterparts in the
Ministry of Atomic Energy of the Russian Federation (MINATOM),
multi-scale, three-dimensional (3-D) models of the hydrogeology
and potential contaminant migration in the West Siberian Basin.
These models and this modeling strategy will be validated using
decades of data from measured contaminant migration at the Mayak,
Seversk (Tomsk-7), and Zhleznogorsk (Krasnoyarsk-26) sites. This
project is being conducted under the auspices of the Joint
Coordinating Committee for Environmental Remediation and Waste
Management (JCCEM).
The long-term goal of this work is to test and build confidence
in the capability of the U.S. Department of Energy's (DOE's)
contaminant transport models to predict future impacts of
radioactive contaminant releases at DOE sites on the environment
and humans. Our joint objectives are to develop semi-automated
approaches integrating site characterization, conceptual modeling,
and numerical modeling for radioactive contaminant transport and
to validate them in multi-scale, 3-D, transient contaminant
transport models for the Mayak and Seversk regions. This proven
technology will then be transferred for use at DOE sites. DOE uses
such models to evaluate the potential for risk from contaminated
U.S. sites, and will benefit both from model validation and from
technologies transferred from Russian site remediation work.
Current efforts in contaminant-transport model development are
frequently behind schedule and over budget. The overall system
architecture is muddled; i.e., site characterization data
management, numerical model development, and evaluation of results
are intermingled, and specialist roles are not well defined or
managed. Site models are slow to mature, difficult to revise as new
information or insights are gained, and difficult to document.
Further, the physical bases of these models have not been tested
"in combat"; i.e., at field scale, for substantial radionuclide
concentrations, over decades of migration.
The semi-automated approach being developed and implemented in
this project will result in significant cost savings and risk
reduction. Cost savings will result from separating the development
and implementation of the site-characterization/geographic
information system (GIS) database, conceptual model development,
numerical model development and implementation, and evaluation of
results. Further, automation of links between components and
development of the numerical representation of the conceptual
model will allow a rapid-turnaround evaluation of changes to site
characterization data and the site conceptual model. These savings
will allow expedited assimilation of new data and hypotheses,
reproducible, easily documented implementation of the numerical
model, and comparison with results of "full-scale field
experiments," all of which reduce the risks associated with
site modeling.