to kick up our session and our first beaker today will be Doctor
Alan Shapiro he is a senior research
hydrologist the US geological survey a member of the
water cycle branch in the Earth system process a division of the
water missionary in Doctor Shapiro conducts research on groundwater
flow and chemical transport and complex geological diamonds including
Fractured Rock and aquifers Doctor Shapiro's research focuses on development
appeal techniques and equipment bodily groundwater flow and chemical
transport and methods of integrating interpreting geologic geophysical
hydraulic and geochemical information in characterizing Fractured
Rock aquifers Doctor Shapiro is also actively
pursuing research in the characterization remediation of various contaminants
in Fractured Rock including solvents and other dense
nonaqueous liquids and a graduate of Princeton University with a PHD
and civil geological engineering and an edge of
magic Professor in the Department of Earth and biosciences at Columbia
University Doctor Shapiro is a fellow of the geological Society of America
and 22.004 National groundwater
Association GW I selected him as distinguished
[ Indiscernible] also served on National research Council panels
have produce excessive reports on key engineering and scientific issues
facing the nation.
>> I handed over to
>> Thank you very much Cindy.
I will start now if
that's okay.
This presentation was originally compared for FRTR meeting held in
May 2019 today's presentation is an abbreviated version of that earlier
presentation to fit within time constraints of today's Webinar and
I removed a variety of examples of developing conceptual site
models associated with groundwater remediation there is an interest
of anybody's part discussing those concepts presented
beyond the examples I give here in today's Webinar and I encourage
you to get in touch with me my contact information is available on the
slide and on the resources and as the title this
Webinar implies, topic of the presentation focuses on identifying critical
processes and scales appear formulating conceptual
site models the intention is that identifying critical processes allows
one to be efficient site characterization monitoring
and modeling to facilitate decisions at sites of
groundwater contamination.
However before one can begin discussing conceptual site models one needs
to address what motivates the development of a site
conceptual site model. CSMs are conceptual
site models cannot be viewed as academic exercises and
napping hydrological understanding development of CSMs and the understanding
built into CSMs are dictated by side
objective spirit the 2005 National research Council publication presents
a really excellent discussion
of objectives that govern activities at sites of groundwater
contamination. In that document the NRC panel identified what are
referred to as absolute and functional objective spirit or absolute objectives
are defined as those higher-order community and stakeholder requirements
for example mitigating adverse human and ecological
health effects is an absolute objective also minimizing disturbances to
the community can also be considered an absolute
objective. In conducting site activities these objectives
are nonnegotiable and transcend all other objectives and site activities.
Absolute objectives are usually defined in negotiations by among
multiple stakeholders at the on-site of activities at a
given site. Additionally, the NRC reports the signs
functional projection these are operational goals that are designed
to successfully accomplish the absolute objectives for example source on
removal and implementing mitigation procedures to prevent off-site contaminant
migration mitigation migration possible functional
objectives that can be formulated to achieve the absolute objectives
should be noted that it is possible to accomplish absolute
objectives using different combinations of
functional objectives.
In the conceptual site model however functional objectives are the driving
force for formulating conceptual site model in the
associated site characterization monitoring
and modeling that are needed as part of that GSM development this
is discussed here in the diagram from that 2005 NRC publication that
describes the workflow to identify technologies for source zone treatments
peer what is critical in this diagram is identifying those junctures with
data required to develop and update the CSM. Those
critical points make reference to satisfying the functional objectives.
This diagram the focus is on identifying
sources zone treatments however as I noted
earlier achieving absolute objectives for
example preventing adverse health impacts could be accomplished
with different combinations of functional objectives. For example,
absolute objectives could be accomplished through
institutional controls, institutional controls would prevent future
access to groundwater the data requirements in developing
the CSM for institutional controls would be
significantly different than the data requirements associated with
designing source on removal peer flossers not necessarily
affix methodology for achieving attributes of the CSM that
degree of detail needed to address functional objectives dictates the
informational requirements in developing the CSM.
However, functional objectives and the associated
daily requirements are potentially cumbersome. They require
conceptualizing and detailing
physical hydrologic biogeochemical human
processes and operational controls over multiples facial in
temporal scales.
For example design and mitigation scheme to
present off-site migration requires characterization of the source him
and all the physical and chemical process information associated with
the dimensions of the source zone and over time
frames that varies from daily operations associated with remediation
remedial treatments to time frames of years or decades to
evaluate contaminant persistence in the source zone. Additionally
characterizing the potential for off-site migration requires information
relevant to regional geological hydrologic topographic
controls additionally one may also move to incorporate
off-site operational controls for groundwater withdrawal such as community
wells and management of surface water resources for example releases
from reservoirs or contingencies for flooding and other
hydrologic events. These processes may extend over dimensions of hundreds
of meters to kilometers and may extend over time frames of decades
or longer period accumulating and synthesizing
all this information is somewhat daunting in the development of
the CSM.
In formulating CSMs to address functional objectives,
it helps to compartmentalize our thinking about processes and important
to the finding of CSM in particular thinking about
processes that affect various reservoirs of contaminant mass in the classes
of contamination between those reservoirs to a certain extent
this is articulated in the diagram shown here was put forward in various
IT RC documents also Tom sailed Chuck Newell and a variety
of other publications. This document
was prepared or this diagram was prepared primarily to look at organic
contaminants. The diagram protects various contaminant
phases that can exist for example the NAPL face
quiz phase sword phase and vapor phase and the recognition that mass
can reside in different types of industry -- transmissive materials
in the source zone and the down gradient plum
this diagram gives us a way of thinking about those processes that
affect the storage and releases of contaminant in each of these
reservoirs in the monitoring that may be needed to characterize the
mass of these reservoirs and the fluxes between
reservoirs. However even with compartmentalizing our approach to development
of CSM there continue to be multiple scales and multiple processes that
occur over a timeframe that extend over several orders of magnitude
so thinking about this diagram in the data requirements to address
the development of this continue to be
quite daunting. This brings us back to our elephant the
old joke how do we even open while the answer is one bite
at a time.
In looking at this diagram in formulating conceptual models to address the
specific shall objective we need to not
only compartmentalize our thinking but also prioritize
our thinking. We need to identify those contaminant reservoirs
and fluxes that dominate process outcomes and are relevant to the
functional objectives under consideration as well is identifying
the spatial and temporal scales that dominate the
process outcomes. This may then allow us to constrain and officially
focus our efforts in data collection and subsequent monitoring
frequency of monitoring and ultimately the modeling of these
processes peer. By way of example
let's consider developing a conceptual site model
associated with functional objective of mitigating off-site contaminant
migration and consider the scenario in a Fractured
Rock environment Fractured Rock aquifers are regarded as significant
challenge to quad water remediation environments are physically and
chemically complex and characterizing groundwater flow and chemical transport
unlike your surface consolidate porous
hydraulic properties of the formation and dramatically from one location
to neck depending on the location and type of discontinuities in
the rock there's a number of references that provide extensive overviews
of the complexity of Fractured Rock aquifers and three reports shown
here were published over the past several decades by the Nashville
research Council National Academy of Sciences, provide an excellent
starting point from which to gain understanding of site
characterization monitoring modeling groundwater flow and chemical transport
in Fractured Rock with applications to both waste
isolation groundwater remediation.
Among the complexity that are encountered in Fractured Rock as he characterization
of the hierarchy of white space shown here Fractured Rock
aquifers are characterized not only by discontinuities in the rock that
they extend over meters to tens of meters due
to local stress distribution but also by void space associated with
the trend intrinsic formation of the rock which is referred to as
the rock matrix. The rock matrix
does not necessarily contribute to both hydraulic properties of
the formation but it can add act as a reservoir for storage and release
of contaminants due to chemical diffusion this is illustrated here
on the left-hand side. Where we see bands of iron
hydroxide standing on the rock
adjacent to fractures this is the location where oxygen is diffuse
from fractures into the rock matrix resulting in this iron precipitate.
Fractured Rock aquifers are also characterized by
larger scale discontinuities caused by regional stress characteristics
that are shown on the right of this diagram this may give rise to extensive
zones that may either act as conduits or barriers to
groundwater flow.
In characterizing potential off-site contaminant
migration we recognize that fractures are the most likely mechanism for
the infection of
chemical mass outside the rock matrix also plays a role in there may be
a storage and release of mass in the rock matrix along groundwater
flow paths but to understand the movement of contaminant from one
location to the next is the fractures I control
this process.
However we recognize that there are numerous factors that constitute
groundwater flow in these fractures exist over dimensions from centimeters
to kilometers and perhaps larger much we have to ask in developing
a CSM is it necessary to characterize all
these fractures? So let's step back and review
what is known about fractures and the capacity to
transmit groundwater. On the left-hand side of the diagram are results
of testing in a bedrock borehole in crystalline
rock this is a testing site that was in central New Hampshire. The
acoustic elevator like provides an image
of the borehole wall it indicates fracture locations. Tell of
your log provides an open oriented view of
the borehole wall it is like opening up a wrapper on a soup can and features
that intersect the borehole will appear as sinusoidal as a soreness
will shape at the open oriented view that wraparound the
soup can is unfurled. We can see a large
number of flatline fractures intersecting this borehole but also there are
fractures that have a distinctive fit. The strike in different
fractures can be identified by the characteristics of the sinusoid
on the borehole image. Also shown on this diagram are
results are results of a drug test conducted in the
borehole the tests were conducted with a straddle pack wrapper is
shown on the right-hand side to isolate the discrete intervals of
boreholes in the either inject or withdraw water from discrete intervals
to estimate the transpacific the trans-is a measure of the ease of
which water can move through a given geologic material and thus the trans-acidity
is the ease of which water can move through those individual are closely
spaced fractures in that isolated interval period we see the trans-acidity
in these test berries over approximately five orders of magnitude contacts
element approximately 10 to the -10 square meters
per second two approximately 10 to the -5 square meters
per second. Also it should be noted that trans-acidity
is not excluded of function with depth
you see fractures at the maximum the trans-lucidity immediately fracture
-- at the detection limit of the downhole equipment use in conducting
these test additionally in looking at the configuration of trans-lucidity
versus depth we see two zones of high transited the zones of
high transited at our orders of magnitude larger
than the fractured intervals other fractured
intervals in borehole meeting that they have the capacity of transmitting
hundreds to thousands of tams or lighter than the other fractured
under the same hydraulic gradient and should be noted that
fractures trans-transmissivity is not related to
fracture density which of multiple sections of the borehole with high
fracture density but these areas of high fracture density not
always correlate to elevated measurements of transmissivity in fact sections
of that borehole retail of the sparse numbers of factors
have the highest transmissivity.
Continuing Harlequin measured hydraulic properties of fractures if we look
at results of those single hole hydraulic test conducted
in individual boreholes and compile them over original area of several
kilometers shown here we arrive at a frequency histogram shown in
the lower right of this diagram appear the frequency histogram shows
a number of tests that results in various bids for the hydraulic
conductivity here the hydraulic conductivity is taking that transmissivity
from those test intervals and dividing it by the length of that
test interval. The range of measurements berries over approximately six orders
of magnitude of all the tests that were conducted in more than
40 boreholes I should also note that there is
a large number of test intervals containing fractures where the transmissivity
of the test interval interval was below the detection limit of the
in situ of equipment those test below the detection limit are not
shown in this histogram but they would be to the left of
the -- line on the histogram. In looking at the
frequency histogram, we see there's relatively few
test intervals.
We see they are relatively few test intervals at the
highest order. Where the highest transmissivity these few
fractures control the majority of groundwater flow
the a copper hundreds to thousands to millions of times more water
than those fractures in the remainder of the distribution. Thus understanding
contaminant detection does not necessarily require us to interrogate all fractures
but instead to characterize those transmissive fractures and their
trans-passivity and connectivity --
so in looking at mitigating designing a mitigation
scheme for off-site contaminant migration we have narrowed the focus
of characterization for CSM to only those most
transmissive fractures in their connectivity. This information
allows us to design strategies that mitigate off-site contaminant
migration. Talk a little bit more about
methods of identifying the connectivity of fractures I will provide a very
brief example over the past 25 years there's been numerous advances
in identifying locations of transmissive fractures in their
connectivity including geologic mapping of brittle structures so
verse and borehole methods development of
multilevel monitoring equipment to use single boreholes for multiple
purposes of chemical for collecting chemical
information as well as hydraulic information, the design
and interpretation of hydraulic and
tracer test, various methods of modeling groundwater
flow including advances in parameter estimation to identify the spatial
distribution of formation properties. Identifying
transmissive fractures in their connectivity in the multidisciplinary
operation where data is synthesized or
multiple sources one of the approaches is through hydraulic testing which
I'll demonstrate here.
This is a plan view of the number of wells in a crystalline rock aquifer
the same aquifer setting that I showed earlier in the talk in for
simplicity have shown a cross-section
through wells one, four, five and nine insects in these test waters
pump from an isolated interval in well six include pressure responses
are measured on other isolated intervals in the adjacent boreholes and the
distances between the two fathers wells and the setting is approximately
100 meters perhaps a little bit more.'s the
hydraulic responses the aquifer test are shown here and drive down
any 12 is shown as a function of time in the
upper left. The drawdown is the difference in the
hydraulic head relative to the hydraulic head of the start of the aquifer
test thus it increases as a function of time. 6D
is the pump interval and shows the largest drawdown and drawdown in
the other intervals do not follow expectations associated
with homogeneous aquifers in homogeneous
aquifers drawdown decreases as a function of distance. Fractured
Rock however we see multiple intervals with same drawdown
even though they are different distances from the pump well for example drawdown
in 60 and 60 and 9B have the same drawdown even though they are different
distances from the pump well and additionally what
is also characteristic of these drawdown record is that there's
a clustering of drawdown records in particular specific intervals
had the same drawdown's this is explained by the presence of highly
conductive fractures that connect intervals in different wells per
for example pumping in six D produces drawdown and 9A that
tracks along the drawdown in 6B we hypothesize it is a series of
highly transmissive fractures that intersect both of these intervals
as we continue to pump fluid pressure prop
gets through less transmissive fractures until that pressure font
hits another series of highly transmissive fractures and was at
pressure front his hills highly transmissive fractures, all intervals
that intersect those fractures have similar responsive because
the rapid pressure propagation along those transmissive fractures this
is seen for example for interval 6C and
9B and we continue this as we continue with pumping
pressure propagates to a lesson transmissive fractures until his
the next series of high transmissive fractures and for example
intervals 1B or B in five have the same hydraulic
drawdown response.
Thus we have a conceptual understanding out with the most transmissive fractures
and connectivity in space in the field setting there is not necessarily
a backbone of highly conductive fractures that are connected over
distances greater than tens of meters highly conductive fractures tend
to be isolated in the rock and connected only through
lower transmissive essay the fracture we also see the same phenomena in
other locations at the setting.
That is not shown here but I've other test that can have similar
results. However more information is needed.
To characterize the potential for site
off-site migration that is not captured in identifying only
the most transmissive fractures interconnectivity.
In particular, characterization and chemical processes are native
for example the location source owns the strength of source zones
chemical reactions of various attenuation processes, -- we are
not done. One approach to the characterize of transport of
various contaminants is to attempt to explicitly incorporate
all of these processes into a groundwater flow model dictated by our understanding
of the connectivity of highly transmissive fractures. The diagram on the right
hand side gives an example of the wealth of chemical and physical
absorption absorption biologic processes that
may exist for example for
organic contaminants. The various chemical
processes depicted here, are highly complex
and it may not be conceivable incorporate all these
to a groundwater flow model to talk about Dayton transport with
the idea of understanding mitigating how one
can design a mitigation scheme for off-site
chemical migration.
Attempting to explicitly model these processes is
conceptually complex, computationally intensive and there's a high degree
of parameter uncertainty just to give you a sense of the complexity
of modeling chemical processes in Fractured Rock,
take a look at the iron hydroxide stain on a fractured on a road cut
that is shown here in the bottom and that fracture is a map those
fractures that have an iron hydroxide staining
which indicates the dissolved oxygen migrating through the fracture Network
we see a rather complex pattern of fractures that are impacted by
preferential flow. We see individual fractures where only a part of
the fracture is impacted by iron hydroxide staining whereas other
parts of the fracture are not even areas where there is high density
of fracture did not necessarily correlate to iron
hydroxide staining thus attempting to explicitly conceptualize
and modeling, these phenomena are likely to be highly
uncertain. Instead an alternative approach could be used to
conceptualize mass transport.
What we can potentially do is look at representative
groundwater flow models and along those representative groundwater
flow lines attempt to look at those processes and bound those
processes from chemical responses for example there are algorithms
such as bio core REM core matrix diffusion ToolKit that have been
developed and constructed to place downs on processes that affect
contaminant concentrations at down gradient locations. We could potentially
use these algorithms to bound chemical processes along
representative flowlines as a way of constraining our information
in looking at off-site migration
of contaminants.
Thus in the development of the CSM for the
purpose of designing mitigation of off-site contaminant migration,
we conceptualize that the most dominant process of chemical it infection
in the subsequent characterization of those highly transmissive fractures.
Other processes also play a role and
conceptualize in conceptualize those as bounding the
the outcome for chemical induction. Field information
will also be required for those bound calculations but we
are not expecting to explicitly model these process along groundwater
flow past, instead we recognize what is the most dominant process
that is the chemical induction instead we will be hypothesizing the magnitude
of these chemical processes and potential
impacts on contaminant they between starting
and ending location from the source some to an off-site compliance boundary
for example.
So in summary, it is
really beneficial to have an understanding of all processes and scales that
affect contaminant transport. To address
specific functional objectives however, all processes and scales do not
need to translate into a decision support tool. Recognizing critical
processes influxes is important in terms of focusing our data
collection and BD Session in economic and or data collection efforts.
With that I think I'd like to and and leave it up
to Cindy and Jean to entertain
questions here.
>> Okay thank you Alan. I had someone
ask about groundwater impacted with creosote are you doing any
work in that area?
>> Personally know I have reviewed a variety
of documents associated with creosote,
creosote is a different actor than TCE the time frames
associated with it because of its density and viscosity
will be different than those of TCE distribution, you may have a
very elongated time for to reach a stable distribution
of creosote following its emplacement
or release on land surface whereas with TCE
which has different viscosity and
density characteristics, you may reach a relatively stable distribution
of TCE much quicker than you do seen
creosote distributions.
>> Okay great.
I want to remind folks if you have questions for Alan you can
enter them into the Q&A pod at the lower right. We have a minute
for questions to come in otherwise we will go to our
next speaker. Alan is there any other --
>> I would like to note that at the end of this here's a series
of references for those who are
interested in topics related to what I
presented here if there's questions on these
references or need further information please don't hesitate to
contact me.
>> Great thank you so we do have one more question, how
was -- the pumping test done to identify
the fractures did use pectorals owned or some other method? Can
you describe that a little?
>> The cross all aquifer test that was conducted used packers
to isolate those most permeable intervals in the
boreholes over this area of 100 meters by
100 meters. We recognize that it was those most
transmissive fractures. -- That were going to be
some combination or backbone or some connectivity of those which
were going to affect groundwater flow
-- priority we did not know what that connection
would be. We have some idea based on various
other methods borehole geophysical methods but by isolating those highly
transmissive zones in each borehole, and monitoring pressure response,
we were able to see where this pressure propagated first where
propagated next etc.
>> Excellent thank you,. I think at
this point we are ready to move to our next speaker and thank you
Ellen for your presentation. Alan for your
presentation about some more questions for Alan that pop up in
your head in the presentation you can go ahead and write those and
if we have time at the end we will come back and asked those questions
of other speakers. Thank you again Alan.
>> Next up we are going to have Sophia and she is a Project
Manager and hydrolytic modules for the Naval facilities engineering
command expeditionary warfare Center also known as NAVFAC and
only recently joining the NAVFAC family Sophia
spent eight years working as a consultant in Denver and Boulder Colorado and
her experience in the design construction and calibration of regional and
site-specific models help develop the opinion
would come to modeling the lesson more philosophy is usually asked
for something most groundwater problems in addition to groundwater modeling
Nissley has been involved in well insulation aquifer
testing of groundwater wells for both remote and urban
environments and received her undergraduate degrees in geology and classical
in the eraser and
Bryn Mawr College in hydrological science engineering from Colorado
school of mines and currently a member of the environmental restoration
team and supports groundwater mitigation supply project for the Navy throughout
the world. Sophia if you are ready I will hand it
to you.
>> Thank you very much Cindy.
First I'd like to thank the federal remediation
technology Roundtable for the opportunity to speak with you all today. It
is wonderful we have an opportunity to talk about
modeling and specifically how can be used as a position to a for evaluating
remediation strategy. And want to point out the previous talk the
FRT meeting on this topic in May covered wine range of topics from
the use of models with specific locations to their applicability
at the program level and if you are not already
signed up I encourage you to sign up for part two of this discussion
as well.
While a number of the previous presenters at the FRTR meeting highlighted
the benefits of groundwater modeling tools including state and transport
codes and decision schemes as well as the
development of forecasting tools one topic that
is of ongoing interest is how these particular models are selected and
maintained. This question about selection
and maintenance is both simpler and more complicated than amazing
simply put a groundwater model needs to be as simple or as complicated
as the question posed to it. Like the three bears
in the classic fairytale, you don't want to model that is really simplistic
nor overly complex instead you want the model that is just right for
the questions you are trying to answer. This means the model
Canon most likely will change through time especially as the questions
posed change resulting in potentially multiple versions of the same system
and varying levels of complexity between model spirit so for my talk
today I am to cover three angles first I want to define
what I mean by a simple on compass modeling and second I'd like to
describe how the Navy has utilized these concepts to optimize pre-existing
groundwater models for site cleanup, and
three outline potential considerations when selecting the complexity
[Indiscernible] first I
want to clarify that those purposes of my discussion today are going
to be talking about groundwater model specifically related to groundwater
flow and transport and utilizing the groundwater model and code
mod flow and that's at the principles involved
to complicating or simplified model can and do apply to other types
of models as well so don't think this is exclusive. Without further
ado let's talk about it. What do I mean when I talk about complex
and simple models let's start there.
So a simple model I am described in the
following I am talking about limited domain size, maybe fewer boundary
conditions, larger good size, limited calibration
parameters, maybe along with that course or calibration statistic
and potentially less accurate source data and
in general more than a general model rather than site-specific
and I have an example here where you can see squares that are very
simplistically designed. As you can see we have four layers as opposed
to something more complex.
This model is not to be confused with a complex model and by complex
I mean that there's more very domain potentially regionwide detailed
boundary condition frequently derived from complex
data sets typically includes the extensive
calibration in potentially tighter calibration statistics, and you
have the potential to be more accurate or to a more detailed data
sources, and typically we like to think of these complex models as
being quote unquote more real-world to
site conditions.
Both simple and complex models have their pros and
cons and I've highlighted a few of these on this slide in front
of you but to summarize, simple models are just that they are usually
simpler cheaper in support a lower quality data and not necessarily
you can have really great data and to utilize simpler
model for accomplice modified just that they are more complex basically
can have tighter fit to observe data more refined and site-specific
more typically typically comes more caught
these typically typically more expensively either
computationally or physically and each of these pros and cons as well
however there comes in equal balance hopefully
between the two when choosing depending on
the situation.
Two things to bear in mind
when thinking about the pros and cons between sample and more
complex models, is that every piece of additional design increases the
complexity of the system, and each level of complexity increases the
chance for model errors due to unforeseen interactions. So if is danger to
miscalculate how simple or complex remodel could be then how does it
happen? Well there's a ton of explanations or excuses that could be is typically
impact the models in too complicated or simple
as they evolve and to illustrate this I wanted to present an example
and as I clarified it is easy to say these issues are caused by inexperience
in you see that a lot when modelers are talking about each other, but
frankly everyone is susceptible to too much complexity and that's
why want to give the following example. Let's take
a typical site in here we have a site with a plume and it and maybe
the boundary -- the boundary of the
site and you have a river over here and maybe some urban and
industrial operations. The first thing you do as everybody
knows is have a conceptual model and have my CSM and it looks like
there's some very geology as well as a plume at depth of
[Indiscernible] and take our CSM and
then we put it into a bunch of squares into a model and so here we have
four layers to represent these four different types in A or K are
hydraulic conductivity to each layer and after I have my cave there's
more going on to the system and set want to add
a variable [ Indiscernible] to incorporate
the urban and River on the edge and I also want to add some source
infiltration at.1 per day.
And that's not all that's going I might
have some flow-through I might have some leak in the
river and before you know what your model is a lot more complex than
when you were initially setting out to build it. Additional
considerations with potentially included in the model can include
regional pumping site remediation withdrawal barrier injection and
other remediation strategies tried historically
but add additional levels of complexity and requirements on
your data.
With this complexity this is added as
you construct the CSM but every single step in the process.
And in 2006 highlighted some ideas about when unnecessary complexities
which I highly recommend everyone take a look at as the suggestion
can be very helpful some of them are listed
in this table one on the right. Once you've built your
model, you then have to calibrate it. When it comes to
calibration there's many different things that can trip
you up encouraging the incorporation of more complexity that you try
to explain or fit your model to the best result I've
outlined some here but the key ones I want to point out include trying
to calibrate or implement too many parameters, the
over tightening of parameter values leading to overconfidence of parameter
estimations, and especially over fitting data and as you can see
on the figure here in figure 2B this is an example of
a fitting where a more linear set
may be more appropriate based on the quality of
your data. So some things to remember when it comes to added
complexities and calibration, are when you evaluate
the sensitivity of parameters to get a feel for the likelihood that
they can be estimated that in over fitted model can be equal or worse
than in under fitted model, and what is the complexity
necessary to the questions you are trying to answer and frankly what
is the accomplishable data limitations that you have speaking of
data limitations, I just want to briefly touch on this one
as well, it is so easy to want to answer questions
beyond the scope of data available especially historical questions
and this comes up a lot when doing groundwater bottling and is totally
okay to preface the complexity or simplicity can hinge on the level
of error in the data available as long as that's appropriate for the
questions and to highlight the present the following example let's say
you're collecting well measurements and collected
with by someone in the field with an
accuracy of plus or -.2 feet and what this means is
that going to quote a perfect fit for an observed measurement of 10
P at any given well location could be 9.8 and 10.2
P with any simulation therefore any prediction within the model
must be within the bounds of this error to be considered a perfect
fit. But that means that if you're getting something if you're not
getting 10 feet that 10 feet might not actually be
the accurate measurement value for your model.
This can come into play especially when you get to more complex models
to make you want to over fit your data beyond the level of accuracy
that is possible.
So bearing this in mind let's look at two examples to see how the Navy
has approached the complexity and simplicity implication of groundwater
flow models.
So welcome to Washington today we will talk about two facilities
in Washington state specifically the Puget Sound Region. These locations
were chosen because they average or site-specific models those have
been optimized so groundwater models have been modified to answer different
questions in both models address
more applicable answer to restoration question and specifically I'm talking
about locations with gold stars here. First let's go to
[Indiscernible] this is a situation where a
legacy model was simplified to better answer flow and
transport questions.
So where kicks off we are looking at OU to at site F this
is about.75 acre site surrounded by large Forest in a close basin
with no natural drainage though a canal is located about 1.5 metals
west of the site.
The Hydra logically speaking the impacted aquifer is a shallow zone
separated from regional conditions by confining unit
and the area of interest is approximately 80 to 100 feet thick in total of
until topsoil.
The site was originally a lagoon
and was used for disposal for approximately 12 years of initial investigations
were completed in the 1980s and 1990s, further groundwater modeling
was completed in 2015 to address new contamination discovered at
the site this 2015 modeling is what I'm referring to as
the legacy model that was utilized per so looking at the legacy
model itself, it included different geologic
formations however it was within the same order of magnitude in terms
of their hydraulic connectivity and also the approximate area of
interest remains the same between the legacy and
modern model. For your reference the figure including the approximate
mild domain with the applicable service geology on your screen.
And look at more at the legacy model,
we have four different
hydrologic flow zones highlighted with different
colors and these were meant to simulate the changes in geologic
formations as seen on the figure on
the right.
When we look at the calibration statistics we can see that there
were a total of a few thousand
observations and in general it was pretty good we see in IRMF see value
of lesson 10% this scaled
to residual meaning is below 10% in the scale residual standard deviation
is below 5% as well and using the percentages it is meant to be guidelines
but is good to see the model fit relatively well for
the area.
So if the model fit well, then why do we want to
change it? Well frankly the legacy model did not mimic the bands that
was being observed in the contamination data I think you see in this figure
on the right the plume was thought to start over here in the lower
right and then bend around the accident toward
the northwest. Whereas the initial model was much more
of a linear plume divide as seen on this figure on the left.
After review of the model, the general head boundary which were located
to the South
were determined to be forcing the water in the system to flow directly
across the site rather than curbing as previously described and therefore
the model simplified the model by removing the general had boundaries
in place he drains on the Northern edge to better simulate flow conditions
at the site.
To achieve the simplification it was determined
the boundary conditions were over influencing the flow directions
within the model and effectively eliminating the bend in the flow
direction and to eliminate this problem as I
described specific heads were moved from the model and traits were added
to the [ Indiscernible] what does this
result in we will compare them. When the
model was simplified the calibration statistics in general were less
precise than the model data that said, there's a few things to bear
in mind the number of targets between the two models increased as you
can see here, and the fit of the flow direction
of the observed plumes movement were considered
to be more applicable
and the simplified model than the legacy model even though they statistics
might not be as good the overall behavior of the plumes
was better. Again as a result you can see here. In summary
the simplification of the model allows for the addressing of questions
posed related to specific flow dynamics that were
otherwise unanswerable.
In conclusion this conclusion emphasizes
the following two points that the original model
typical modeling statistics however it may have been in over fit for
transport purposes, and simplifying the model boundary conditions allowed
for a more flexibility in flow directions.
Ultimately for a better transport model.
We have time for the second part and let's switch over to
across the plume here to enable their station Keyport
in this sense is adding complexity to the system was vital to addressing
the question posed to the remediation site as a word of note
this model is still undergoing a review process however the rollouts
of this investigation are already applicable to addressing
issues raised at the beginning of the talk. The location Keyport's
location OU one approximately a nine acre former landfill site surrounded
by a large forested area and potentially outflowing to surface
water and to the South and to the yeast. Groundwater flow
direction in this area ultimately flowed to dogfish Bay through
tidal flats.
This site like the last one was also disposal location
in this case however is also an online landfill and much larger
than that which was seen at Kip Sapp and the
site received paint waste residue solvents as well
as Jewel wastewater treatment plant and pesticides and
other landfill material and of particular note
at this location is proximity to tidal flat and surface water make
it really important that we address is model from a more
complex perspective.
Looking at the regional geology because of the proximity of the
site to type flats as well's deposition former marsh environment the area
of interest is the shallowest of 50 feet which is comprised of clay
silt and sand above a deeper confining unit and this confining unit could
be anywhere from 90 to 100 feet down. Looking at what models
were available at this location
the specific modeling had been constructed previously
instead of regional four model of the entire peninsula was used to
assess the flow direction due to southern portion of the site this
original model comprised of approximately 575 square Miles with 14 model layers
and pretty solid statistics from the calibration that said these
calibration statistics are for the whole regions not just the area
we are interested in which had [ Indiscernible]
with it.
The calibration statistics for the
whole model. Looking at the concerns of the regional model these concerns
included the following while the model
fit the pretty well regionally it did not mimic known groundwater
divide at the site, and the
model cell size was too large for transport modeling to answer the
questions posed at this location for shallow zones were not adequately
model as well to address the complexity of the clays and sands and the sub
service as well as flows to local streams and therefore a more
complex and focus models I was determined to
be necessary.
So when we began the refinement objectives, to address
these concerns the following objectives were proposed that we needed to
have a model refined of the area of interest
data vertical refinement in the area of interest the recalibration
of the area with more site-specific water levels in flows and to
convert the system to a more complex density driven environment to account
for the potential one of these associated with
dogfish Bay.
Just as a note on the vertical refinements of what I'm
referring to to get clarity on the upper zones the top layer of the
regional model was split into six distinctive layers that you can
see here based on the geologic modeling completed by the folks over at the
USGS which is translated into a flow model for the more
site-specific examples.
In terms of the refinement modeled domain a lot
can be said about this latest interpretation of the site Region but it
is not here it is that the regional flows were incorporated at the edges
of special emphasis being placed on
including the surface water features missing from the more generalized
reasonable interpretation you can see that in the figure here where
there was an emphasis placed on the title flat being added into
the model as well as these known creeks and ponds
and streams which were not necessarily present in the
original domain.
So once is more refined model was constructed it was
also calibrated, and by incorporating additional complexity to the model
area of interest was able to get a tighter fit in the area of the
site while the model calibration has in our messy at 15%
rather than the generic of 10% or lower the average air was in the
area of interest washas a ports 247 feet in the original
model so we considered even though additional
complexity and in terms of calibration fit. An additional
comparison look at the water level the
new model simulates the influences of the groundwater device
not exhibited in the regional model and this is most
likely due to the course of the regional model versus the more refined
areas within a smaller domain.
So some site conclusions in conclusion adding complexity as
well's refining the model allowed for us to have a better
tool with which to answer our site-specific concerns. Also by
implementing a more refined geology and boundary condition this
was especially important for the groundwater divide question and
flow direction. To provide our RPM with
transport tools or with tool to answer transport questions at
the site.
When looking at the two case studies presented previously, a few take
away points can be seen. Both locations optimize
existing groundwater models to address new questions one by simplifying
the domain in one by adding complexity to address local shallow
zone dynamics. In addition while model Jasmine provided less
specific bits that were provided with the original models, the dynamics
under consideration approved in the case of
Kitcat the increasing packs of pumping a particle to transfer port the
Captain is of concern mimicking real-world observation
what that and with the Keyport
increasing complexity and sell refinement allowed for better localized fit
and field observed groundwater divides.
Ultimately those models provided quote unquote better
result than the original models for the modified questions posed
at both locations.
So modified differently how do you choose what model
modification may be necessary for addressing the particular site and
I wanted to provide the group with some potential questions and whether
or not a simpler or more complex model design might be
appropriate. It's important to recognize that every site is
unique and it's best to consult
an expert prior to model selection and that said here's some general
guidelines that could be applicable to addressing some of the questions
posed. For example what is the extent of the area of interest, if the
extent is not very large a small domainer simplified regional flows
might be more appropriate, however if you have a larger plume or more
complex geology than larger regional consideration might be necessary
leading to a more complex system.
In addition what is important is what deadline are you working under
even though we don't like to think about
physical and temporal constraints has been a concern there are very
applicable when it comes to groundwater modeling in the sense you might
be able to get a 70% answer with a simpler design rather than
waiting to get a more complex answer that could take months or
years to determine the best results.
Depending on what the specificity of the questions posed
looks like, the availability of reliable and accurate data in the
timeline or budget that you have should typically drive complexity
of your system.
So some final consideration to take into account,
we always should remove that garbage and equals garbage out which
is why the accuracy of your data can be so vital in deciding the
complexity of your model. In addition complex they can both add to and
detract from your accuracy of your results. In determining the
level of complexity you need is key to
adequately modeling your system this level of complexity needed
may change through time requiring an optimization or modification
of your interpretation and your model lady to multi-models for the
attempt -- [ Indiscernible] finally it's simple
model may be the best option even if result is more conceptual
than site-specific and ultimately this process was
proven useful at a number of Navy sites and continues to be considered
in the future it is vital to consider the level of complexity or complicity
needed when approving accepting and with that I like to thank you
for listening and open it up for questions.
Specs thank you,
>> Thank you Sophia we have a few questions for you in. Someone was
curious, whether you all considered title of
[ Indiscernible]
>> It wasn't included at the
tiptop site it was considered part of the close basin and far enough
away to not be impacted by title influences and the Keyport side
that is an ongoing question and
I believe they are still doing studies to determine what that impact would
look like. And might be included at a
later date.
>> Now we have another
person ask it looks like would evaluate them all complexity there's
ways to quantify parameter uncertainty, but it looks like the evaluation
of structural area is qualitative, can you comment on that?
Back yes, this is
>> This is one thing discussed a lot at the upper Q meeting we had
back in May and it is at the moment it is a qualitative gain
not -- it's a qualitative decision up to the modeler and I
am not aware of any particular official standards when it comes to estimating
model parameters so that is another reason why it's
really important to get an expert involved when making these decisions
to see if your model fits good enough to answer
the questions being posed and something to bear in mind when assessing that
are again I can't emphasize this enough but the accuracy of your
data as well as the
applicability or understanding of your system and that can really
when we step back and take a hard look at our selves and our data
what is really achievable with the scope of your modeling project in
order to determine what your model was accurate enough. I wish I
could say oh well we have that standard or set numbers you can
follow but unfortunately it is still a
quality or unquantifiable assessment
but qualitative assessment even though we use statistics in order
to give us numbers that can quantify what those values are.
>> Thank you,. Another participant asked when working on
developing a steady-state flow model?
>> For the concept site it was a steady-state
I think they had a transient civilization as well and for the Keyport they
had to, they had a steady-state in a
transient simulation.
>> Okay at this point I want to thank
you Sophia and if you stand I will come back to you for questions at
the end if those come in and now I want to move on to our
next speaker who is Doctor Wainwright research
scientist at Berkeley natural Tory and earned a Masters in nuclear
engineering and statistics in PHD in nuclear
engineering at the University of California Berkeley and focuses
on hydrological modeling
facial statistics data integration and uncertainty quantification she
has worked on various research topics in both nuclear engineering and
environmental sciences including nuclear waste groundwater
contamination Fukushima radiation monitoring and climate change impacts
on ecosystems Doctor Wainwright if you are ready
go ahead.
>> Thank you very much
for having me in this Webinar.
In this talk I will talk about importance of monitoring and how we can use
modeling particularly high performance computing
based reactive to optimize
[ Indiscernible] I work in one of the DOE Department
of Energy labs Berkeley lab Department of
Energy DOE monitors more than 100 sites in the US that
were used for nuclear weapon production over the last 30 years DOE
has made a significant progress in mitigation and the sides
have been closed or transition to the
close process and there are 16 sides remaining currently.
These 16 sides are challenging, the sites have complex
contamination including multiple radionuclides heavy metals
and other organic compounds some of the plumes are very hard
to access like deep betas owes
Vadose Zone's and some sites have very big plums large
volume plumes with low contamination so it is not practical
to remove all the contamination or soil and the treatment removal
technologies are getting not so effective because
of low contamination. So I want to
talk a little bit about the transition in the radiation and over
the 30 years that the timeframe of DOE
site mitigation soil and groundwater remediation has been evolving from
this doing nothing to very sorry I'm gonna
have -- to very intensive treatment
and now there are movements called sustainable or green
mitigation so over the last 30 years people
have realized that removing contaminants or remediation has a
[ Indiscernible] cost is of course one
thing but mitigation produces a lot of waste this is a particular
problem problematic for radionuclide becomes
Radioactive Waste also radiation produces a lot of CO2 and uses a
lot of energy and it has ecological disturbances and
environmental disturbances so now there's industry consortium
called sustainable radiation focused on
this topic.
Sustainable radiation is often coupled with attractive
in-state or redevelopment plan with
restrictive uses for example solar farms, parks, like major reserves
or factories, these kind of approaches particularly attractive
in important for the DOE sites since many of the sites
it has residual contaminants for an
extended time. So sustainable radiation aims
to reduce net environmental benefits in addition
to contaminants we would consider energy uses
or ecological impacts and waste and
tries to do a lot of recycling and reduce waste,
and also tends to focus on passive remediation and monitored
natural attenuation that reduce a lot of waste and energy
and water use however this requires increased burden of
proof such that we have to make sure that plumes are
stable and it does not have any significant
health effect.
So for this environmental monitoring is very
important to provide such proof and I think particularly
reason is there are similar instances that monitor is
not just issuing public safety but is good
for operators to prepare for liability issues so I have good
examples and bad examples here and here is a good example for instance
this article said activists ignore the signs that says Rocky Flats
is safe based on at this site a lot
of monitoring data has proved the site
is safe and can it was able to dismiss false
claims in the right hand side I have a bad example,
so the current fish market in Japan is constructed as a former
[ Indiscernible] groundwater contamination and called [ Indiscernible]
and found a number in groundwater data and cannot explain it so
they had to spend extra $100
million so it's very important to prove that the site is safe
and it can satisfy -- [ Indiscernible] otherwise could
have big consequences. Our research goal
has been to support the transition from active to passive
remediation and ultimately monitor natural attenuation.
Monitoring can provide additional lines of evidence for
such transition for example at this cost
implication at SRS F
area they transition from active to passive radiation and saves a
lot of taxpayers dollars from $12 million per
year to $1 million per year.
And we aimed to improve long-term monitoring status strategies because
long-term monitoring becomes a big part of the lifecycle
cost and not just saving cost we want to improve the safety of the
site and bring in new technology to detect new lakes
or new migration and
also ensure long-term stability of the plumes for example
there are a lot of discussions about the impact of climate
change [ Indiscernible].
Have been cooperating to develop new paradigm of
long-term monitoring, by taking advantage of recent
advances in in situ sensors, wireless
networks telecommunications, and also Cloud Computing and also
machine learning methods so now there is very key
or affordable sensors that can measure many groundwater quality
parameters like water
table, pH, electrical connectivity or specific contaminants and we
might call these parameters
master viable's since these parameters can control
the permeability -- we can detect changes of the
plume availability by looking at these parameters real-time
and also by looking at the correlation between these variables
and contaminant concentration we could be able to
that we can estimate contaminant concentrations in
situ real-time. So we have established the data analytics
framework for this paradigm so it starts from exploratory
data analysis and we can identify correlations
between contaminant concentrations and other viable's for example I
hope you can say it but in this plot I'll explain in the next
slide that we found correlation between pH and radium of
course pH is driving the [ Indiscernible] the next
step we quantify the correlations for example
we found a correlation between radium
concentration and specific conductors in the
groundwater. And the first step based on this quantified correlation
we can predict contaminant concentration real-time
based on [ Indiscernible] so in
terms of big data analytics we found that PCA principle
can talk -- component analysis is useful
to find the correlation between master variables and contaminant
concentration here as I mentioned pH
and radium are opposite and arrows and this has
limited correlation and we have the groove of
nitrate and mission specific conducted -- reactive
tracers and Kalman filter is a way
to integrate the data set and site knowledge so that we
can do in situ real-time estimation
of contaminant concentration and this is actually
the demonstration by historical data sets and we have data sets
from 96 to 2014 and this is
the tritium concentration estimation and uranium concentration
so this is the the [ Indiscernible]
the red line is predicted or
estimated concentrations and blue dots are measurements and we
see that the predicted concentrations are well
agreed with the measured concentration and also we can capture
little bumps in the concentration data set
spirit so we published this work last year. It got a lot of
press attention and we published in ESD and
I think people are interested in the use
of new technologies like [ Indiscernible]
and groundwater in environmental mom -- the question
now is why we do monitoring and how we can use monitoring
to support these strategies. We
think that modeling is important to confirm and also understand the
correlations and between master variables answer to
measurable variables versus contaminant concentrations. We
also like to investigate the impact of the climate
change or climate disturbances and investigate for
example how to place monitoring wells so that we can capture
the responses to flooding or other events. The third one
is we started working on it but this is our
next step. We want to use modeling results
to place -- we want to use monitoring results
to optimize well placement for
example modeling can produce simulated plume evolutions
and we can place monitoring wells based
on those. Are demonstration site is this area so this
site has former disposal basins where
lower-level radioactive acid way solution were disposed
even in [ Indiscernible] currently the site has a big acidic plume
with multiple radionuclides radium strung
them in iodine and tritium and the pH is low
up to 3.5. This
site has many remediation activities including
pump and treat as I mentioned they transition to passive
remediation based on the pH neutralization and organization
of radium and excite --
transition to natural attenuation in
the future. We are using a
Manzi and under
DOE advance simulation capability for Environmental Management so
a Manzi is HVC ready transport quarter and it has
a unique interoperable structure such that
a Manzi deals with flow and
transport and advanced method and can couple with any chemistry
engine depending on the [ Indiscernible]
it has flexible framework that
can represent geochemical reactions in the interface is enabled
by the elk we via
interphase -- chemical model includes many
reaction networks particularly to capture pH dependency of
the mobility of radium and has acquiescent surface complex Asian
and mineral dissolution precipitation
and so on.
We have a pretty good hydrogeological conceptual
model here, there are two aquifers
permeable aquifers upper and lower aquifers
separated by [ Indiscernible]
this is the basin and the plume starts from
here and the plume eventually goes out in the seepage
base and to the river. So we have developed 3-D maps
including the [ Indiscernible] clay rich stone
and also has via structures for
passive integration. This is
the plume [ Indiscernible]
the plume goes down vertically at first
and spreads laterally in the groundwater and now
it meets the river and
you can see the water contaminant in this
case radium is stuck in the zone and also the clay zone
because Clay does not have mobility.
And we are interested in this residual
contaminant and the [ Indiscernible] in the clay
rich zone.
In terms of the simulation, we have agreement
with observations not just radium but
other analytes and using this model
we can see the correlation between master
variables and uranium concentration so we have figures here for
this is the simulated correlation between radium and
nitrate concentrations basically nitrate is a specific
conducted for conductivity at the side and this
arrow represents the 1950s to current conditions to
the future a time
[ Indiscernible] the time
consumed -- corresponded to measure time we can see that in the measured
correlation we can see radium and nitrate and we have very good
correlation and the nitrate correlation will change
in the future it is not linear.
On the other hand the
correlation between [ Indiscernible] and pH
from the 1950s and this is a current time and goes
to the future the correlation between radium concentration and pH
would be linear into the future so from this
result we can know what to expect in our monitoring strategies and
we can plan
for this.
The next topic is the resilience to climate disturbances and we expect
increasing [ Indiscernible] like flooding and
drought and we want to know that what happens to the residual
contaminants that we saw
[ Indiscernible] know what we can do better
with monitoring. We published two papers on this topic and
my students worked hard for the papers references but could
not find so many and I think these are the first sets of papers
that address climate change impact from radiation or
contamination period in this paper in particular the
second paper, we investigated the impact of flooding and drought on
residual contaminants using modeling. The flooding and
drought impacts can be considered by class and increasing
or decreasing precipitation or temperature, that can be translated
to infiltration amount or ET and basically
how much goes into this
aquifer appeared it sounds simple but it is not because more water
for example has trade-offs in more water could mean it
could mobilize contaminants but also more water can mean
dilution so there could be competing effects and we need
to investigate for quantitatively using
modeling. So this is the timeline that we assumed so
the basin was operated between 1956 and 1989
and now the basin is closed and capped and
we assume that something will happen in 2020 next year
and we assume in this case large flooding
very extreme [ Indiscernible] two times to
10 times.
This is the concentration as a function
of time of source zone well and also down gradient well and this
is the export to the river.
This is yellow is extreme case and terms of
participation and we can see increase in
concentration because the [ Indiscernible] at the down
gradient well the Canton station that concentration
there's a dilution and mobilize contaminant and
concentration increased. We were surprised to see that effect
actually linger to this case and if
we don't know this effect it probably we could wonder what happened like
no one expects that that event in 2020 would have an
effect in 2030 and that is kind of modeling results can sort
of guide are [ Indiscernible] this is something
that we need to -- these results show the impact
on export to the river the
risk pathway, it does not have huge exact
because export is an integrated measure over time and
space increasing the fissures from the lower aquifer with not impacted
by flooding significantly.
And we found that source zone well is
very important to monitor because we
can detect mobilization of residual contaminants.
So are moving onto the last topic monitoring optimization so we
just started this and I don't have significant results
but I want to show you some aspirations and currently
there are many technologies to map contaminant distribution surface
and subsurface like geophysics -- geophysics for
example in some nucleotides can be mapped airborne and
of course simulated plume can be considered as a map
and highlight maybe we can use this information to
optimize well placement and we can identify
key locations. I want to show one example from the monitoring
project in Fukushima. We have a big monitoring data
analytics project we developed algorithms to
integrate different large-scale radiation measurements that
have different types and footprint of data sets and we can
quantify it contingency and provide integrated map
of radiation at those sites and this has been
adapted by -- [ Indiscernible] in Japan and this
is now being used to guide the contamination
in other activities and also we are using this map to
guide monitoring post optimization so it has been 10 years
since the Fukushima accident and there is a need to transition from
more emergency response type monitoring to [ Indiscernible]
we want to capture the heterogeneity of this contamination with
fewer sensors. We have [ Indiscernible] effectively
reduce the number of monitoring locations from
the blue like 255 locations to 100 locations and
confirmed that as a number of monitoring post increases
the error of capturing heterogeneity decreased but
monitoring locations around 100 we can say
[ Indiscernible] this way we can say 100 locations would be enough
and capture the spatial heterogeneity in this case
we have radiation map over entire Region and the groundwater
case of course it is not the case subsurface there's
-- we can use simulated plumes as a contaminant map to guide
monitoring optimization and we are
working for approach extending this approach to the monitoring wells
optimization at the [ Indiscernible]
groundwater plume.
I showed a couple examples but basically here is the family we
are developing cost-effective strategies for long-term monitoring,
based on in situ sensors for continuous monitoring,
rather than just relying on groundwater sampling
or EA and we can -- [ Indiscernible
- Poor Audio ] that [ Indiscernible] and we have developed
data analytics methods Kalman filter methods for example to
estimate concentrations based on measurable
fireballs and we think monitoring is important
to support such monitoring strategies and
can confirm for example correlations between
master variables or in situ variables versus contaminant concentrations
and we can extrapolate that to the future
to determine the efficacy of the monitoring strategies in the
future. We can see or can investigate the impact
of climate change or climate disturbances like flooding,
drought, what to expect, and also where to
monitor and eventually we want to use this approach of monitoring
two more better optimizing
monitoring locations.
I hope you got the sense of our activities in thank you very much
for the opportunity. I would be happy
to answer any questions.
>> Thank you Doctor Wainwright and it seems I have lost
my Internet connection so I will try to get that back
online for let me ask you a question not necessarily mildly related but
I'm curious, how did SR or SN RL
or L BNL become involved with this Fukushima modeling obviously
this is an international event so I'm curious how you
all got chosen on that and what has it been like working
with another country?
>> DOE has been actually contributing to
Fukushima radiation effort significantly. Even during
the accident the Japanese government conducted US
government and asked for a lot of help. US
government has contributed to
revision activities at the sites and also monitoring for example
the first airborne radiation mapping that was
done by the American equipment and we have a lot of
interactions and collaborations between DOE or National labs and
Japanese government and this is one of
the activities.
>> Right now I need to see
if Jean is on the phone and can jump in and help me out here I have
actually lost my connection. Back that is not a problem I am here
and happy to step in and like Cindy said I'll
remind me out as you do have a Q&A window in the lower
right corner we can show
your questions and comments to our speakers and if you don't have any
questions or comments you can enter that and it helps us get a sense
of where the audiences sometimes people are busy typing their messages
away and cannot see the keystrokes.
I did see a question that had come in and I think this might be directed
towards you Doctor Wainwright but let me just ask, when you were looking
at locations for monitoring, how did you
include location into your decision-making when you are
determining the density at which you would then locate these
monitoring spots?
>> For the Fukushima case,
how we can do incorporation based on sparse
locations and decided -- sorry computed
estimation error or interpretation there and we have
decided that [ Indiscernible] by looking at
convergence in operations.
>> I will ask one more time if there's
other questions or comments for our speakers you can enter those
into the Q&A window if you don't have any questions you can
enter in and we can move on with the seminar if anybody happens
to be on the phone lines and like to ask a question on the
telephone line you are welcome to come off of me by pressing pound
six if you have time and you are certainly welcome to unmute and
feel free to ask a question directly on the
phone.'s back
>> Don't hear anybody came in off mute and got a couple thank you
messages for the Webinar environment I think we might be okay in terms
of Q&A Cindy whether some closing statements are thought you'd
like to share before we wrap up today's Webinar?
>> I think I'm good if you can control the slides over for closing out
I can go ahead and read off the announcement spirit
>> Have a couple thank you messages from the audience and pulling up
closing slides now and feel free to begin.
>> Thank you I want to remind folks that if you enjoy today's session
we do have a part two coming up and thanks to Sophia for mentioning
that and next week on Wednesday December 4 we will have session
2 of our FRTR presents Modeling in Support of Site Remediation
and that Webinar will be joined by Doctor noma
from EPA and Scott Morgan and John of US Army Corps of
Engineers and we will continue with this topic with those three talks.
So I'd like to feel free to connect
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the certificate. You may find a copy of your registration email
the seminar slides and feedback confirmation email enough to document
your participation to today's event
for your own accrediting institution for PDH or see EUP if you participate
as group each person can fill out the online feedback form to get
thrown certificate this applies to those watching the recorded version
as well. We look at your comments as we continue to try to improve
the content and delivery mechanisms so please go ahead and fill those
out. We also suggest or requested confirmation email from the feedback
age as a record of your participation in today's event if you require
further assistance feel free to contact Jean Balent at Ballin @EPA.gov.
Lastly today's session was recorded in the future you will be able to
access the slides and do the presentation as it was given as part of our
archive. You'll automatically receive an email once the archive is
available and testing of our final reminder thank you for joining on
today's session I hope you find it to be a valuable use of your
time and we will see you in the future Webinars this is a formal
conclusion of today's broadcast.'s back