NC0005088_Amended_Cosler_Expert_Report_Cliffside_20160413

Amended Expert Report of
Douglas J. Cosler, Ph.D., P.E.
Chemical Hydrogeologist
Adaptive Groundwater Solutions LLC
Charlotte, North Carolina
Cliffside Steam Station Ash Basins
Mooresboro, North Carolina
April 13, 2016

Introduction
Site Backqround
The Cliffside Steam Station (CSS) is a coal-fired generating station owned by Duke Energy and located
on a 1,000-acre site in Mooresboro, Rutherford and Cleveland Counties, North Carolina, adjacent to the
Broad River. CSS began operations 1940 with Units 1-4, followed later by Unit 5 (1972) and Unit 6
(2013). Units 5 and 6 are currently operating, but Units 1-4 were retired from service in 2011. An ash
basin system has been historically used to dispose of coal combustion residuals ("coal ash") and other
liquid discharges from the CSS coal combustion process. The ash basin system consists of an active ash
basin (constructed in 1975 and expanded in 1980; used by Units 5 and 6), the Units 1-4 inactive ash
basin (retired in 1977 upon reaching its capacity), and the Unit 5 inactive ash basin (retired at capacity in
1980, but local stormwater collects and infiltrates within its footprint). The active ash basin also contains
an unlined dry ash storage area.
Duke Energy performed voluntary groundwater monitoring around the active ash basin from August 2008
to August 2010 using wells installed in 1995/1996, 2005, and 2007. Compliance groundwater monitoring,
required by a NPDES permit, has been performed by Duke starting in April 2011. Recent groundwater
sampling results at Cliffside have indicated exceedances of 15A NCAC 02L.0202 Groundwater Quality
Standards (2L Standards). In response to this, the North Carolina Department of Environmental Quality
(NC DEQ) required Duke Energy to perform a groundwater assessment at the site and prepare a
Comprehensive Site Assessment (CSA) report. The Coal Ash Management Act of 2014 (CAMA) also
required owners of surface impoundments containing coal combustion residuals (CCR) to conduct
groundwater monitoring and assessment and prepare a CSA report. The recently -completed CSA
(August 2015) prepared by HDR Engineering, Inc. of the Carolinas (HDR) determined that the source and
cause of certain constituent regulatory exceedances at the CSS site is leaching from coal ash contained
in the active and inactive ash basins and the ash storage area into underlying soil and groundwater. The
Cliffside CSA report defined Constituents of Interest (COI) in soil, groundwater, and seeps that are
attributable to coal ash handling and storage.
CAMA also requires the submittal of a Corrective Action Plan (CAP); the CAP for the Cliffside site
consists of two parts. CAP Part 1 (submitted to DEQ in November 2015) provides a summary of CSA
findings, further evaluation and selection of COI, a site conceptual model (SCM), the development of
groundwater flow and chemical transport models of the site, presentation and analysis of the results of
the modeling, and a quantitative analysis of groundwater and surface water interactions. The CAP Part 2
contains proposed remedial methods for achieving groundwater quality restoration, conceptual plans for
recommended corrective action, proposed future monitoring plans, and a risk assessment.
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Information Reviewed
My opinions are based upon an analysis and technical review of (i) hydrogeologic and chemical data
collected at the Cliffside site; (ii) the analyses, interpretations, and conclusions presented in site -related
technical documents and reports; (iii) the groundwater flow and chemical transport models constructed
for the site (including model development, calibration, and simulations of remedial alternatives); (iv) the
effectiveness of proposed remedial alternatives to achieve groundwater quality restoration; and (v)
proposed future site monitoring. This amended report contains additional opinions based on my review of
the recently -issued CAP Part 2 report. These opinions are subject to change as new information
becomes available.
As a basis for forming my opinions I reviewed the following documents and associated appendices:
(1) Comprehensive Site Assessment Report, Cliffside Steam Station Ash Basin (August 18, 2015);
(2) Corrective Action Plan, Part 1, Cliffside Steam Station Ash Basin (November 16, 2015);
(3) Corrective Action Plan, Part 2, Cliffside Steam Station Ash Basin (February 12, 2016);
(4) Miscellaneous historical groundwater and soil concentration data for the Cliffside site collected
prior to the CSA; and
(5) Specific references cited in and listed at the end of this report
Professional Qualifications
I have advanced graduate degrees in Hydrogeology (Ph.D. Degree from The Ohio State University) and
Civil and Environmental Engineering (Civil Engineer Degree from the Massachusetts Institute of
Technology), and M.S. and B.S. degrees from Ohio State in Civil and Environmental Engineering. I have
36 years of experience as a chemical hydrogeologist and environmental engineer investigating and
performing data analyses and computer modeling for a wide variety of projects. These projects include:
investigation, remediation, and regulation of Superfund, RCRA, and other hazardous waste sites involving
overburden and bedrock aquifers; ground water flow and chemical transport model development; natural
attenuation/biodegradation assessments for chlorinated solvent and petroleum contamination sites;
volatile organic compound vapor migration and exposure assessment; exposure modeling for health risk
assessments; hydrologic impact assessment for minerals and coal mining; leachate collection system
modeling and design for mine tailings disposal impoundments; and expert witness testimony and
litigation support. I also develop commercial groundwater flow and chemical transport modeling software
for the environmental industry.
The types of sites I have investigated include: landfills, mining operations, manufactured gas plants,
wood -treating facilities, chemical plants, water supply well fields, gasoline and fuel oil storage/delivery
facilities, nuclear waste disposal sites, hazardous waste incinerators, and various industrial facilities. I
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have investigated the following dissolved, nonaqueous-phase (LNAPL/DNAPL), and vapor -phase
contaminants: chlorinated solvents, various metals, gasoline and fuel oil constituents, wood -treating
products, coal tars, polychlorinated biphenyls, pesticides, dioxins and furans, phenolic compounds, flame
retardants (PBDE), phthalates, radionuclides, and biological constituents.
Summary of Opinions
The following is a brief summary of the opinions developed in my report:
• A total of 62 Compliance Boundary groundwater samples exceeded North Carolina groundwater
standards for these COI: antimony, boron, chromium, cobalt, iron, manganese, sulfate, total
dissolved solids, and vanadium. Of these 62 exceedances, 36 were greater than the proposed
provisional background concentrations by HDR;
• The statistical analyses of shallow background groundwater concentrations at the Cliffside site
(well MW-24D) are invalid due to the characteristically slow rate of COI migration in groundwater;
• There is a significant risk of chemical migration from the ash basin to neighboring private water
supply wells in fractured bedrock;
• Major limitations of the CAP groundwater flow and chemical transport models prevent simulation
and analysis of off -site migration;
• The CAP Closure Scenario simulations greatly underestimate (by factors of 10 or more) the time
frames required to achieve meaningful groundwater concentration reductions in response to
remedial actions;
• For either the Existing Condition or Cap -in -Place Model Scenario groundwater concentrations of
coal -ash constituents much higher than background levels will continue to exceed North Carolina
groundwater standards at the Compliance Boundary because saturated coal -ash material and
secondary sources will remain in place;
• Source -area mass removal included in the Excavation Scenario results in COI concentration
reductions at the Compliance Boundary that are generally two to ten (2 - 10x) times greater
compared to Cap -in -Place, best reduces impacts to surface water, and reduces cleanup times by
factors of two to five (2 - 5x). Additional excavation of secondary sources would further
accelerate concentration reductions;
• The CAP simulations show that source excavation reduces groundwater concentrations for many
COI below North Carolina groundwater standards (antimony, arsenic, chromium, hexavalent
chromium, cobalt, nickel, thallium, vanadium), but cap -in -place closure does not;
• CSA data show multiple exceedances of groundwater standards in bedrock not only at the
compliance boundary but also inside the CB. However, the CAP Closure Scenarios do not
address either concentration reduction or off -site chemical migration control in the fractured
bedrock aquifer;
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• Due to an incorrect boundary -condition representation of the active ash basin, the CAP models
underestimate by a factor of two or more both the mass loading of COI into the Broad River and
the corresponding Broad River water concentrations (attributable to coal ash ponds) estimated by
the groundwater/surface-water mixing model;
• The CAP Part 2 geochemical modeling and monitored natural attenuation (MNA) evaluations do
not provide the required quantitative analyses of COI attenuation rates necessary to support MNA
as a viable corrective action. The CAP 2 chemical transport modeling, which included attenuation
by sorption, demonstrated that MNA is not an effective remedial option for several COI (e.g.,
antimony, arsenic, beryllium, boron, chromium, hexavalent chromium, cobalt, lead, sulfate,
thallium, and vanadium);
• Future Compliance Monitoring at the Cliffside site should include much more closely -spaced
Compliance Wells to provide more accurate detection, and groundwater sampling frequency
should be re-evaluated to allow valid statistical analyses of concentration variations.
Hydrogeology of the Cliffside Site
Introduction
The groundwater system at the Cliffside site is an unconfined, connected system consisting of three basic
flow layers: shallow, deep, and fractured bedrock. The shallow and deep layers consist of residual soil,
saprolite (clay and coarser granular material formed by chemical weathering of bedrock), and weathered
fractured rock (regolith). A transition zone at the base of the regolith is also present and consists of
partially-weathered/fractured bedrock and lesser amounts of saprolite. The ash basin system overlies
native soil and was constructed in historical drainage features formed from tributaries that flowed toward
the Broad River using earthen embankment dams and dikes. As described in the CSA report, the active
ash basin was formed by construction of two dams across natural drainages. At the upstream dam, Suck
Creek was diverted through a canal and away from the ash basin to the Broad River, at its present-day
configuration. The active ash basin downstream dam is located near the historical discharge point of
Suck Creek into the Broad River. A large percentage of the coal ash lies below the groundwater table
and is saturated. Groundwater flow through saturated coal ash and downward infiltration of rainwater
through unsaturated coal ash leach COI into the subsurface beneath the basin and via seeps through the
embankments.
As described by HDR, groundwater flow in all three layers within the site boundary is generally from south
to north toward the Broad River. Vertical groundwater flow between the three layers also occurs, and
surface water ponding in the active ash basin effects flow directions locally. The CSA and CAP
investigations assumed that all groundwater north of the ash basin system (overburden and bedrock
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aquifers) discharges into the Broad River. However, these studies did not collect hydrogeologic data or
perform data analyses or groundwater flow modeling to support this assumption. The CSA and CAP
Parts 1 and 2 also did not analyze potential changes to site groundwater flow directions, or the risk of off -
site migration of COI in the overburden or bedrock aquifers, caused by groundwater extraction from
numerous private and public water supply wells located close to the site boundaries and near the Broad
River.
My report begins with a discussion of significant errors in CSA data analysis and conceptual model
development that contradict HDR's interpretation of three-dimensional groundwater flow patterns at the
Cliffside site. This is followed by a presentation and discussion of measured exceedances of North
Carolina groundwater standards at multiple locations on the ash basin compliance boundary. I then
address several limitations of the CAP Parts 1 and 2 groundwater flow and chemical transport models
and identify various model input data errors. Finally, I present my evaluations of the CAP Closure
Scenario simulations and provide my opinions regarding the effectiveness of various remedial alternatives
for restoring groundwater quality to North Carolina standards.
Errors in Hydraulic Conductivity Test Analyses
Background
Throughout the CSA and CAP reports HDR provides interpretations and conclusions regarding the
horizontal and vertical variations of groundwater flow directions and rates, and the fate and transport of
COI dissolved in groundwater. The most important site -specific parameter that controls these time -
dependent flow and transport mechanisms is the hydraulic conductivity (also referred to as "permeability")
of the underlying soils and fractured bedrock (Bear, 1979). Hydraulic conductivity (length/time) is a
media -specific measure of the rate at which water can flow through a porous (soil) or fractured (bedrock)
porous medium. Groundwater flow and chemical transport rates are directly proportional to the product of
hydraulic conductivity and the hydraulic gradient (hydraulic head difference between two points divided by
the separation distance; e.g., the water table elevation slope at the Cliffside site). Therefore, accurate
measurement of hydraulic conductivity is critical for understanding the current and future distributions of
COI in soil and groundwater and for evaluating the effectiveness (e.g., cleanup times) of alternative
remedial measures.
In addition, the contrast in hydraulic conductivity between adjacent hydrogeologic units is the key factor in
determining three-dimensional groundwater flow directions and the ultimate fate of dissolved COI. For
example, at the Cliffside site accurate measurement of hydraulic conductivity is critical in evaluating the
potential for: downward chemical migration into the fractured bedrock unit, off -site COI migration in the
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overburden (soil) or fractured bedrock aquifers, groundwater flow and COI transport into or beneath the
Broad River
A slug test is one of the standard field methods for measuring hydraulic conductivity (K) using a soil
boring or installed monitoring well. Slug tests were performed in most of the overburden and bedrock
wells at the Cliffside site. In this test the static water level in the open hole (boring) or well casing is
suddenly increased or decreased and the resulting transient change in water level is recorded. Two
commonly -used techniques for quickly changing the water level are the introduction (increases the water
level) and removal (decreases the water level) of a solid rod, or "slug" into the boring or well casing.
These tests are called "falling -head" and "rising -head" tests, respectively. Higher rates of water -level
recovery correspond to higher values of K. The measurements of water level versus time are analyzed
using mathematical models of the groundwater flow hydraulics and information regarding the well
installation (e.g., length of the slotted monitoring well screen and well casing diameter) to compute an
estimate of K.
As discussed below, HDR made significant errors in all of their analyses of field slug test data. Their
analysis errors caused the reported (CSA report) slug test hydraulic conductivity values to be as large as
a factor of two (almost 100 percent) smaller than the correct K values. I discuss the impacts of these
analysis errors on HDR's groundwater flow and chemical transport assessments and the CAP modeling
later in my report.
Overburden Slug Tests
HDR analyzed all of the CSA overburden slug tests in shallow and deep wells with the Bouwer-Rice
(1976) method using a vertical anisotropy, Av = Knorj,,t t / Kverttcat , that is as large as a factor of 100 lower
than the values presented in the CSA report (e.g., compare geometric mean values in CSA Tables 11-10
and 11-11) and used in the CAP modeling (e.g., CAP 1 report Appendix C, Table 2), where K is hydraulic
conductivity. Comparing CSA Tables 11-10 and 11-11, the measured Avforoverburden soil units ranges
from 4 to 50. In the calibrated CAP flow model Av is on the order of 100 for overburden soil. However,
the Bouwer-Rice slug test analyses assumed Av = 1 for every monitoring well (CSA Appendix H). If the
CAP 1 flow model results (Av — 100) are used in the Bouwer-Rice analyses all of the measured
overburden hydraulic conductivity values increase by about 70 percent (factor of 1.7), depending on how
the slug -test radius of influence was computed. Using the Tables 11-10/11-11 measured vertical
anisotropies (Av = 4 to 50) increases all of the measured overburden hydraulic conductivity values (CSA
Table 11-4) by about 20-60 percent.
Since every reported overburden K value in the CSA report (at least for new shallow and deep wells) is
up to 70 percent too low, the actual average chemical transport rates in overburden soils are up to 70
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percent greater than reported. This site -wide data reduction error also affects the CAP flow and transport
model calibrations. For example, the transport model developers significantly reduced laboratory
measurements of the soil -water partition coefficient, Kd, for various COI during the transport model
calibration based on comparisons of observed and simulated chemical migration rates. However, if the
correct (i.e., higher) overburden K values had been used in the model calibration the Kd values would not
have been reduced as much (compared to laboratory values). The reason for this is, assuming linear
equilibrium partitioning of COI with soil, the chemical migration rate is proportional to KI Kd (except for Kd
<< 1). The CAP 1 and 2 transport model history matching indicated that the simulated transport rate was
too low, so the model developers reduced the model Kd. In other words, the reductions in calibrated Kd
values would not have been as great if the correct (higher) K values were used in the first place. As
discussed below, the CAP Part 2 transport modeling used Kd values that are generally a factor of about
10 larger than the CAP 1 values; however, the CAP 2 Kd's are still on the order of 10 times smaller than
the measured site -specific Kd's reported in CAP 1 Appendix D and CAP 2 Appendix C. COI sorption to
soil is important because, as discussed below, aquifer cleanup times (i.e., chemical flushing rates) are
generally proportional to the chemical retardation factor, which is directly proportional to Kd, except when
Kd << 1 (Zheng et al., 1991).
Groundwater Flow
Throughout the CSA and CAP reports HDR made several critical assumptions, not supported by data,
regarding the horizontal and vertical groundwater flow directions near the boundaries of the Cliffside site
which impacted their conclusions regarding the ultimate discharge locations for site groundwater and
dissolved COI. Two examples discussed in this section are (i) the relationship between site groundwater
and the Broad River and (ii) groundwater flow directions and the potential for offsite migration of COI.
Broad River and the LeGrand Conceptual Model
Most of the groundwater at the Cliffside site was apparently assumed to discharge into the Broad River
(other than groundwater discharges to small streams such as Suck Creek) according to a generalized
conceptual model (LeGrand, 2004) before actual site -specific hydrogeologic data were analyzed.
Statements to this effect were made at numerous points in the CSA and CAP reports. However, HDR did
not present any site -specific data analyses or groundwater flow modeling that would support this
assumption in either report. In fact, as discussed below, the boundary conditions for the CAP Parts 1 and
2 flow models effectively forced site groundwater to discharge into the river at the downgradient model
boundary.
HDR continued to state this assumption in the CAP 2 report (e.g., Section 3.3.2) even though strong
measured downward groundwater flow components exist next to the Broad River. In CAP 2 Section
3.3.2, HDR also states that "The Broad River serves as a hydrologic boundary for groundwater within the
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shallow, deep, and bedrock flow layers at the site." However, the river cannot be a "hydrologic boundary"
for the deep and bedrock layers when the measured vertical flow direction in these layers is consistently
downward at many locations next to the river (see discussion below), which demonstrates that HDR has
not delineated this inferred "lower boundary" used in the CAP models. HDR further states in CAP 2
Section 3.3.2 that "the approximate vertical extent of the groundwater impacts is generally limited to the
shallow and deep flow layers, and vertical migration of COls is limited by the underlying bedrock." This
statement ignores that fact that groundwater flow across the site is consistently downward from the
impacted deep flow layer to the highly -fractured bedrock aquifer at many locations and that, as discussed
below, 35 exceedances of North Carolina 2L and/or IMAC groundwater standards (and greater than
background concentrations) were measured in samples collected from bedrock wells located inside the
Compliance Boundary.
The LeGrand (2004) guidance document presents a general discussion of groundwater flow patterns that
may occur near streams in the Piedmont and Mountain Region of North Carolina based on ground
surface elevations (i.e., site topography and surface watershed boundaries). However, surface water and
groundwater watersheds commonly do not coincide (Winter et al., 2003). Further, groundwater flow
patterns and rates in bedrock have been found to be poorly related to topographic characteristics (Yin
and Brook, 1992). LeGrand does not present or derive any mathematical equations or quantitative
relationships for groundwater flow near rivers or streams. The author emphasizes that site -specific data
must be collected in order to correctly evaluate river inflow or outflow. In strong contrast to the LeGrand
generalizations, numerous detailed and sophisticated mathematical (analytical and numerical) river -
aquifer models and highly -monitored field studies have been published in the scientific and engineering
literature in the past several decades. What these investigations and applied hydraulic models show is
that the water flow rate into or out of a river or stream and the depth of hydraulic influence within an
underlying aquifer are highly sensitive to several factors, including: the transient river water surface
elevation and slope; river bed topography; bed permeability and thickness; horizontal and vertical
permeability (and thickness) of the different hydrogeologic units underlying the river; transient horizontal
and vertical hydraulic head variations in groundwater beneath and near the river; and groundwater
extraction rates and screen elevations for neighboring pumping wells (e.g., Simon et al. 2015; McDonald
and Harbaugh, 1988; Bear, 1979; Hantush, 1964).
The CSA investigation did not: measure river bed permeability or thickness; characterize the river
bathymetry; monitor transient water surface elevation variations at more than one location (one average
value was used); collect river bed hydraulic gradient data; measure horizontal or vertical overburden or
bedrock permeability beneath or on the northern side of the river; characterize the geology beneath or
north of the river; measure hydraulic heads in the overburden or bedrock beneath or north of the river; or
consider the hydraulic effects of groundwater extraction from nearby private water supply wells, as
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discussed in the following section. With regard to the Cliffside site, much of the data that were collected
in the CSA contradict the LeGrand hypothesis. A strong downward flow component (— 10 feet head
difference) from deep overburden to bedrock was measured at the following locations next to the Broad
River: GWA-21 (near several private bedrock supply wells), GWA-29, IB-3D/GWA-11 BRU, MW-
38D/MW-36BRU, and the entire area between the river and northern portion of the Active Ash Basin as
generally bounded by the 650- to 725-foot bedrock head contours (compare CSA Figures 6-6 and 6-7).
The vertical flow direction from shallow to deep overburden is also downward in this area located
between the Broad River and the Active Ash Basin (compare CSA Figures 6-5 and 6-6). In addition,
downward groundwater flow was measured at several other locations across the site (CSA Table 11-13).
A similar trend of downward groundwater flow from deep overburden to bedrock in these areas next to
the river was measured in the CAP 2 investigation. Contour maps of vertical hydraulic gradient variations
were not generated for the CSA or CAP Part 2, and HDR did not discuss the significance of downward
hydraulic gradients next to the Broad River and at many other deep/bedrock monitoring well clusters.
These downward groundwater flow measurements are consistent with the hydraulic conductivities of the
bedrock and overburden being of similar magnitude, as discussed above.
The strong and consistent measured downward groundwater flow components immediately adjacent to
the Broad River and at other well clusters indicate that site groundwater is entering the deep fractured
bedrock unit in these areas and that not all of the site groundwater discharges into the river as the site
Conceptual Model and the CAP flow and transport models assume. The downward flow into bedrock
may also be due in part to groundwater extraction from private bedrock water supply wells located near
the eastern property boundary, but in the CSA and CAP investigations HDR assumed these factors
related to the potential for off -site COI migration beneath the river were not important and did not evaluate
them.
Groundwater Flow Directions
The CSA assumptions and analysis errors discussed above have had a strong effect on: the Conceptual
Model development; the site hydrogeologic and COI transport assessment; the construction/calibration
of the CAP flow and transport models; and the simulations of CAP Close Scenarios. The hydrogeologic
assumptions should have been carefully evaluated and tested during the performance of the CSA and as
part of the CAP groundwater flow model construction and calibration to determine whether they were
valid. Instead, the hypotheses appear to have effectively guided the model development and led to
inaccurate interpretations.
As an illustration, because the permeability of the weathered bedrock is similar to the overlying soils at
the Cliffside site the CSA and CAP interpretation that the bedrock acts as a lower confining layer for
groundwater flow and chemical transport is incorrect. In addition, the similarity of the overburden and
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bedrock aquifer permeability values increases the potential for off -site COI migration toward private water
supply wells. Therefore, the CSA and CAP conclusions that (i) all site groundwater discharges into the
Broad River and (ii) groundwater and dissolved coal -ash constituents are restricted from migrating to
residential water supply wells are not consistent with the data.
The CSA and CAP reports also did not adequately evaluate the three-dimensional groundwater flow field
near and beneath the Broad River. Numerous private water supply wells are located in the following
areas (CSA Figure 4-2): a few hundred feet north of the Broad River and immediately east of the
Compliance Boundary for the Active Ash Basin, less than 1,500 feet from the Active and Unit 5 Inactive
Ash Basins, and less than 1,500 feet from the Active Ash Basin and on the southern shore of the Broad
River (close to the northeastern portion of the Compliance Boundary). Bedrock hydraulic head
measurements (CSA Figure 6-8) for monitoring wells located next to the river (e.g., Wells GWA-32BR,
GWA-11 BRU, GWA-29BR, and GWA-21 BR) indicate a strong easterly bedrock aquifer flow component
from downgradient areas of the site toward these private wells on the southern shoreline. However, CSA
Figure 6-8 does not show these head contours, and the CAP flow model boundary conditions artificially
prevent groundwater from either flowing east or northeast beneath the Broad River (as underflow), or
flowing toward the private wells near the northeast Compliance Boundary. The CSA and CAP reports
also do not address the large measured downward hydraulic gradients in the northern portion of the
Active Ash Basin and near the river, and their potential relationship to offsite groundwater extraction from
the bedrock aquifer. The CAP flow models were not properly constructed to allow evaluation of these
observed three-dimensional flow patterns due to: the model no -flow boundary condition on the eastern
and western sides of the grid; the uniform specified head boundary condition in grid cells underlying the
river (i.e., the sloping, west -to -east water surface elevation in the river was not represented in the model);
and the fact that the CAP flow models did not include the effects of groundwater extraction from off -site
water supply wells.
Exceedances of Groundwater Standards
In this section I compare measured groundwater concentrations in shallow, deep, and bedrock
groundwater samples to North Carolina 2L and IMAC standards and show the following: (i) 60 measured
exceedances for several COI at multiple locations on the Compliance Boundary (CB); (ii) an additional
two CB exceedances based on chemical transport modeling I performed; (iii) 36 of the 62 Compliance
Boundary exceedances were greater than the proposed provisional background concentrations (PPBC)
by HDR; (iv) 37 of the 62 Compliance Boundary exceedances were greater than the maximum
concentration at any background well from the same hydrogeologic unit (e.g., shallow, deep, or bedrock)
for a particular constituent; (v) 12 more exceedances were measured in wells located on the Broad River;
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(vi) 54 additional exceedances were observed in wells screened in the highly -permeable fractured
bedrock unit underlying the ash basin system and located inside the CB; and (vii) the statistical analyses
of groundwater concentrations at shallow monitoring well MW-24D for purposes of defining background
levels were performed incorrectly.
Throughout this report I reference the ash basin compliance boundary and the Duke Energy property
boundary for the Cliffside site as drawn on maps developed by HDR (e.g., CSA Figure 6-2). My reference
to the "compliance boundary" is only for identification purposes and not an opinion that this boundary as
drawn by HDR is accurate or legally correct.
Summary of Exceedances
Table 1 summarizes exceedances of 2L or IMAC standards in shallow, deep, and bedrock groundwater
samples obtained from monitoring wells located: (i) on the Ash Basin Compliance Boundary (CB) as
drawn by HDR; (ii) on the southern shore of the Broad River (RV), which is the downgradient boundary of
the CAP groundwater flow and chemical transport models; (iii) bedrock wells (BR) located inside the CB;
and (iv) modeled Compliance Boundary concentrations (CBM), using modeling techniques described
below. The proposed provisional background concentrations (PPBC) by HDR are also listed in Table 1.
A total of 33 Compliance Boundary groundwater samples exceeded North Carolina 2L standards, and
IMAC standards were exceeded in an additional 27 samples for these COI: antimony, boron, chromium,
cobalt, iron, manganese, sulfate, total dissolved solids, and vanadium. I estimated an additional two CB
exceedances dowgradient from wells MW-11S and GWA-27D for boron based on chemical transport
modeling and measured upgradient concentrations (designated CBM in Table 1). In addition, 39
exceedances of 2L regulatory limits were observed in wells screened in the highly fractured bedrock unit
located inside the CB. An additional 15 bedrock sample concentrations were greater than IMAC limits.
Ten more 2L (plus two IMAC) exceedances were measured in wells located on the Broad River.
A total of 29 of the 35 Compliance Boundary 2L (and 9 of 25 IMAC) exceedances were greater than the
maximum concentration at any background well (from the same hydrogeologic unit; e.g., shallow or
deep) for a particular constituent. All of the Broad River shoreline "RW exceedances were greater than
background levels. A total of 27 of the 39 bedrock 2L (and 8 of 15 IMAC) exceedances were greater than
the maximum background concentration.
A total of 36 of the 62 Compliance Boundary exceedances were greater than the proposed provisional
background concentrations (PPBC) by HDR.
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Note that the iso-concentration contours in all of the CSA Section 10 figures are not consistent, and are in
many cases misleading, with regard to chemical transport mechanisms in the subsurface. For example,
the iso-concentration contours in Section 10 generally closely encircle a monitoring well and infer no
subsequent transport downgradient from the well location. This contouring problem is especially
prevalent near the southern shore of the Broad River. Figure 10-65 (cobalt) is a good example of this
practice. These closed contours at the downgradient property boundary suggest that COI transport
beyond the farthest downgradient line of monitoring wells does not occur and that no COI migrate north of
the southern shore of the river. However, the simulated (CAP model) "existing conditions" cobalt
concentration contours in CAP Appendix C are 'open" at the Broad River, indicating transport beneath the
river.
Modeled Compliance Boundary Exceedances
I computed Compliance Boundary (CB) concentrations labeled "CBM" with footnote "e" in Table 1 (MW-
11S and GWA-27D) using a calibrated one-dimensional, analytical chemical transport model (van
Genuchten and Alves, 1982; Equation C5) because the CB at these locations was up to 400 feet
downgradient from the wells and boron is highly mobile in the subsurface. I calibrated the analytical
model to chemical -specific site conditions (i.e., determined model input parameter values) using CAP
transport model simulated concentration versus time curves for "Existing Conditions" (CAP report
Appendix C). The analytical model input parameters in my model were: groundwater pore velocity,
chemical retardation factor, and longitudinal dispersivity. For each constituent, I used the calibrated
analytical model to compute the concentration versus time curve immediately downgradient at the
Compliance Boundary.
Exceedances of Groundwater and Surface Water Standards in Seep Samples
Concentrations in seeps discharging from the active ash basin (upstream toe, adjacent to Suck Creek)
have exceeded North Carolina surface water standards (2B) and 2L and/or IMAC groundwater standards
(e.g., arsenic, chromium, iron, lead, manganese, nickel, selenium, and vanadium; CAP Figures 2-2 and
2-3, CSA Table 7-9). Groundwater discharges to Suck Creek were confirmed by the CAP flow modeling.
Elevated concentrations of boron, calcium, chloride, sulfate, and total dissolved solids were detected in a
surface water sample from Suck Creek (SW-3) collected downgradient from the toe of the active ash
basin upstream dam (page 90 of the CSA report).
The CSA also identified other continuously -flowing seeps as tributaries of the Broad River [e.g., S-1, S-3,
S-6, and S-8; refer to Table 1 in the Topographic Map and Discharge Assessment Plan(DAP)]. Seep S-3
is apparently part of a stream discharging to the Broad River north of inactive units 1-4 (DAP Figure 2).
Seep S-6 is located downgradient from the downstream dam of the active ash basin and coincides with
historical Suck Creek discharge (CSA Appendix I, Figure 1). Concentrations in samples from seep S-6
13

have exceeded relevant surface water 2B standards, and 2L and/or IMAC groundwater standards for
boron, cobalt, iron, manganese, and vanadium. Concentrations in samples from seep S-3 have
exceeded relevant surface water 2B standards for cobalt, iron, manganese, sulfate, thallium and total
dissolved solids. For the CAP 2 sampling round (September 2015) the 2B standard for mercury was also
exceeded at Seep S-1.
Referring to my Table 1, 122 of the seep samples exceeded North Carolina groundwater standards (84
2L exceedances and 38 IMAC exceedances; CSA Table 7-11) for these COI: arsenic, barium, beryllium,
boron, chromium, cobalt, iron, lead, manganese, nickel, sulfate, total dissolved solids, thallium, and
vanadium. These samples were collected at the active ash basin; inactive ash basins 1-4 and 5; and
the ash storage area.
Statistical Analyses of Background Concentrations
Appendix G of the CSA report presents statistical analyses of historical concentrations from Monitoring
Wells MW-24D and MW-24DR, which HDR described as following methods specified by the U.S.
Environmental Protection Agency (EPA, 2009), in an attempt to establish background groundwater
concentrations for the Cliffside site. As outlined in Sections 3.2.1 and 5.5.2 of the EPA guidance
document these data must be checked to ensure that they are statistically independent and exhibit no
pairwise correlation. Groundwater sampling data can be non -independent (i.e., autocorrelated) if the
sampling frequency is too high (i.e., time interval between sampling events is too small) compared to the
chemical migration rate in the aquifer (groundwater pore velocity divided by chemical retardation factor).
Section 14 of the EPA guidance presents methods for ensuring that the Wells MW-24D and MW-24DR
background data are not autocorrelated, but the analyses in CSA Appendix G did not include evaluations
for statistical independence.
As an illustration, "slow -moving" groundwater combined with high chemical retardation (i.e., large soil -
water partition coefficients, Kd), which is the case at the Cliffside site, can lead to the same general
volume of the chemical plume being repeatedly sampled when the monitoring events are closely spaced.
Examining shallow wells at the Cliffside site, the shallow groundwater pore velocity (Vp) is in the order of
70 ft/yr (CSA Table 11-14), which is representative of the pore velocity near well MW-241D. Note that
shallow pore velocities are as much as a factor of 100 greater in many areas downgradient of the ash
basin system (e.g., the active ash basin) due to much greater hydraulic gradients (- 10x larger) and larger
hydraulic conductivity (- 10x greater) in these areas. In addition, groundwater pore velocities in deep
overburden and in fractured bedrock are generally more than a factor of 1,000 greater than velocities in
the shallow overburden (CSA Table 11-14).
14

The retardation factors, Rd, based on laboratory Kd measurements (Kd -- 10 cm3/g, or greater) are on the
order of 100 (or greater) for many of the COI (except conservative parameters such as sulfate and
boron). Therefore, the average shallow chemical migration rate at Cliffside (Vp /Rd) is on the order of 0.7
ft/yr many of the non -conservative COI near well MW-241D, assuming linear equilibrium sorption (refer to
discussion below). For quarterly sampling, the chemical migration distance between sampling rounds is
about 0.2 feet for several COI, which is smaller than the sand pack diameter for the monitoring wells.
Therefore, based on either quarterly or annual monitoring the shallow groundwater samples at Cliffside
are basically representative of the same volume of the plume (i.e., the sandpack, depending on the well
purge volume) for many COI, and any measured sample concentration changes are not due to real
chemical transport effects in the aquifer. In this case, this means that the groundwater samples are non -
independent and that the statistical analyses of background concentrations at Wells MW-24D do not
satisfy the key requirements of the analysis method.
CAP Groundwater Flow Model Underestimates Potential for Off -Site Chemical Migration
My discussions in this section focus on limitations of the CAP groundwater flow model. I focus specifically
on model boundary conditions representing the Broad River; the overall size of the model grid and no -
flow boundary conditions on the western, southern, and eastern grid boundaries; groundwater flow in the
fractured bedrock aquifer; and the potential for off -site groundwater flow in relation to groundwater
extraction from numerous private and public water supply wells located close to the model boundaries,
but not incorporated into the flow model
Broad River Boundary Condition
The CAP Parts 1 and 2 groundwater flow models force all Cliffside site groundwater along the northern
model boundary to discharge directly into the Broad River and underestimate the potential for off -site flow
and chemical migration in fractured bedrock. No -flow boundary conditions defined along the entire
western, eastern, and southern model boundaries prevent any off -site groundwater flow and chemical
transport in these areas (refer to Figures 1 and 5 in Appendix C of the CAP 1 Report). The bottom
surface (bedrock) of the flow model is also assumed to be a no -flow boundary even though the hydraulic
conductivity data and measured downward hydraulic gradients at several monitoring well clusters do not
support this assumption. The only locations where groundwater and dissolved constituents are allowed
to leave the CAP models are streams (e.g., Suck Creek and unnamed tributaries to the west), top -layer
flood plain cells next to the Broad River, and the vertical array of cells underlying Broad River along the
northern grid boundary; these cells are specified as constant -head boundary conditions in which the
head is uniform with depth.
15

This hydraulic representation of the Broad River in the flow model is inaccurate for several reasons. First,
the river bottom is assumed to extend all the way through the unconsolidated deposits and the fractured
bedrock unit, which is not the case. Second, groundwater flow beneath and adjacent to the river is
assumed to be horizontal with zero vertical flow component. Because this boundary condition does not
allow groundwater to flow vertically in areas that underlie the river, the CAP models do not represent
actual site hydrologic conditions. Further, groundwater flow at the Cliffside site is not strictly horizontal
and, as discussed above, many of the vertical hydraulic gradient measurements (including next to the
river) are downward. Third, as represented in the CAP models, neither the lower -permeability river bed
sediments nor the smaller vertically hydraulic conductivity of underlying soils restricts the potential flow
rate into or out of the river (i.e., a perfect hydraulic connection exists between the aquifer and the Broad
River). The actual degree of aquifer -river hydraulic connection was not evaluated in the CSA. In
summary, due to all of these factors the potential for site groundwater and dissolved constituents to
migrate off -site northward beyond the Broad River or eastward as underflow beneath the river cannot be
evaluated with the model.
The CAP models should have represented the Broad River using a "leaky -type" (i.e., river) boundary
condition in the top model layer (McDonald and Harbaugh, 1988), and the model grid should have
extended farther north so that the above factors could have been evaluated during model calibration and
sensitivity analyses. In their reviews of both the CAP 1 and 2 models (submitted with the CAP modeling
appendices), the Electric Power Research Institute third -party peer review team also concluded that the
Broad River should be modeled as a leaky boundary condition instead of using constant heads. The
models also should have included groundwater extraction from the private water supply wells installed at
many points close to the river bank. A river boundary condition incorporates the bed permeability and
thickness, the river water surface elevation, and the simulated hydraulic head in the aquifer (at the base
of the river bed) to dynamically specify a flux (flow rate per unit bed area) into or out of the groundwater
model depending on the head difference between the river and aquifer. Typically, permeability and
vertical hydraulic gradient measurements for the river bed (not collected in the CSA) and flow model
calibration (three-dimensional matching of simulated and measured hydraulic head measurements in the
aquifer) are used to determine a best -fit estimate of river bed conductance (permeability divided by
thickness) in the model. HDR did not perform this routine analysis.
Limitations of No -Flow Boundary Conditions and Small Model Domain Size
The limited areal extent and depth of the CAP Parts 1 and 2 flow and transport model grids prevent the
use of the models as unbiased computational tools that can be used to evaluate off -site migration of coal -
ash constituents. For example, the model grids should have extended farther north and east to
incorporate groundwater extraction from off -site private water -supply wells and allow three-dimensional
16

groundwater flow patterns to naturally develop. The eastern and western no -flow boundaries in the
current CAP models artificially prevent any off -site flow or transport in either the bedrock or overburden
aquifers. The same is true for the entire northern and southern model boundaries despite the fact that
several private homes are located north and east of the Active Ash Basin, and the bedrock hydraulic head
map (CSA Figure 6-7) exhibits a strong easterly flow component in this area. Some additional private
water supply wells are also located close to the northern shore of the Broad River (CSA Figure 4-2).
Artificial limitations created by the northern Broad River boundary condition are outlined above.
The bottom boundaries of the CAP models should extend much deeper because the hydraulic
conductivity of the fractured bedrock zone is of the same order of magnitude as the overburden soils
based on slug test results. In the present configuration the lower boundaries of the CAP Parts 1 and 2
model grids are only about 50 feet below the bedrock surface (Figure 2 in both the CAP 1 & 2 modeling
appendices). Because several bedrock wells were screened to this depth the bedrock hydraulic
conductivity data collected for the CSA demonstrate that imposing an impermeable model boundary at
this depth is incorrect (compare similarities of mean overburden and bedrock aquifer permeabilities in
CSA Table 11-10). As discussed above, the strong downward hydraulic gradients between deep and
bedrock wells in the northern portion of the Active Ash Basin also demonstrate that vertical and horizontal
groundwater flow in bedrock is important, and these transport mechanisms need to be accurately
simulated in the CAP models in order to accurately assess the potential for off -site chemical migration.
Off -Site Groundwater Extraction Ignored
The CSA and CAP Parts 1 and 2 failed to examine the strong potential for coal -ash constituents from the
Cliffside site to migrate with groundwater to private water supply wells located immediately east and
northeast of the Active Ash Basin. COI may also potentially migrate to private wells located close to the
northern Duke Energy property boundary on the northern side of the Broad River. CSA Figure 4-2 shows
the locations of water supply wells near the site. The basis of my opinion includes the following:
hydraulic conductivity measurements for the overburden and bedrock formations; three-dimensional
variations in measured hydraulic head in the bedrock and overburden units; groundwater concentration
data; and calculations of potential hydraulic head reductions (i.e., drawdown) that could be caused by off -
site groundwater extraction. As discussed throughout my report, neither the CSA nor CAP Parts 1 or 2
investigations addressed the potential for off -site migration.
COI's were detected in several water supply well samples (CSA Appendix B), but the CSA report did not
plot these detections on a map and did not discuss their possible relationship to the Cliffside site.
Appendix B also did not present the well construction details (e.g., well diameter and elevation range of
the well screen or open bedrock interval) so that well dilution effects and potential chemical transport
pathways in the bedrock unit could be evaluated. In addition, the CSA investigations and CAP Part 1
17

modeling did not include these areas east and north of the Cliffside site. The CAP Part 2 flow model did
include a small number of residential wells (13 of the 100 neighboring private wells) located inside the
undersized model domain (east of the active ash basin), but the CAP 2 modeling report (CAP 2, Appendix
B) did not show simulated hydraulic head maps with these residential wells pumping and did not provide
any discussion or analyses of the potential for these wells to capture COI dissolved in groundwater. The
CAP Part 2 also did not increase the model grid size to incorporate the large number of residential water
supply wells located immediately north of the Broad River and downgradient from the active ash basin in
the northeastern portion of the site (CAP 2 Figure 3-3); fix the boundary condition problems; or correct
the model input data errors I have outlined so that the flow and transport models could be used to more
accurately analyze the potential for off -site chemical transport.
Another important model input data error is the bedrock hydraulic conductivity, which is assumed in the
CAP 1 and 2 flow models to be about a factor of ten (10x) lower than the overburden aquifer in different
areas (Tables 2 in CAP 1 Appendix C and CAP 2 Appendix B). The bedrock slug test results show that
the mean bedrock permeability is approximately the same as the overburden permeability. Also, in the
CAP 1 model HDR assumed that the vertical bedrock permeability [ (K81),,t ] was the same as the
horizontal value (i.e., vertical anisotropy, A, = 1). Without justification or any field measurement of
(KBR) e,t the CAP 2 model assumed A = 10-1,000 in bedrock; at several locations the model assumes
the vertical bedrock permeability is 100 to 1,000 times smaller than the horizontal permeability. These
vertical anisotropy values are extremely large, are highly variable across the site, and do not appear to be
supported by data. By comparison, HDR assumed A = 2 in their hydraulic modeling of bedrock slug
tests (CSA Appendix H). In an extensive hydrogeologic study and groundwater model of the Indian
Creek Basin in the southwestern Piedmont of North Carolina by the U.S. Geological Survey (Daniel et al.,
1989) a value of A = 1 in bedrock was used by the USGS. This study is especially relevant because the
146-square-mile Indian Creek model area lies in parts of Catawba, Lincoln, and Gaston Counties, North
Carolina and is located in the general vicinity of the Cliffside site. Therefore, the CAP 1 and 2 flow
models significantly restrict (incorrectly) groundwater from flowing from the overburden aquifer into the
fractured bedrock unit, which causes the CAP transport models to underestimate the potential for off -site
chemical migration.
Model Significantly Underestimates Leakage Rate from Active Ash Basin
The CAP Part 2 flow model underestimates leachate discharge from the active ash basin by as much as
a factor of 180 in areas of ponded surface water (e.g., refer to CSA Figures 4-5 and 8-2). The CAP 1
model underestimates active basin leakage by as much as a factor of 330. As shown in Figure 5 of CAP
1, Appendix C, the CAP 1 flow model assumes a constant groundwater recharge rate (i.e., leakage rate)
equal to 6.0 inches/year in the active ash basin and all other unlined areas of the site. In the CAP 2 flow
model the active basin leakage rate is assumed to be 11 inches/year (Figure 5 of CAP 2, Appendix B).
18

However, CSA Figure 8-2 (cross-section A -A) shows that the vertical hydraulic gradient through the coal
ash in the downgradient portion of the active ash basin is on the order of unity. Using Darcy's law and the
mean vertical coal -ash permeability of 1.6E-4 cm/sec in CSA Table 11-11, the approximate vertical
leakage rate out of the active basin is about 2,000 inches/year near the Broad River (i.e., — 180 times
greater than the specified CAP 2 recharge rate of 11 inches/year; and -- 330 times greater than the
specified CAP 1 recharge rate of 6 inches/year).
The CAP flow models should have represented ponded areas of the active ash basin as either constant -
head or leaky -type boundary conditions, which would have allowed the model to simulate a realistic
leakage rate for the active ash basin. The major discrepancies between the measured shallow hydraulic
head maps (CSA Figure 6-5 and CAP 2 Figure 2-2) and the CAP 1 and 2 simulated shallow head maps
(Figure 14 in CAP 1, Appendix C; Figure 15 in CAP 2, Appendix B) clearly show that the CAP flow
models significantly underestimate the hydraulic head beneath the active ash basin due to the fact that
the modeled leakage rate from the active basin is much too low.
Three related impacts of this incorrect active basin boundary condition are that the CAP models
significantly underestimate: (i) vertical groundwater flow rates (by on the order of a factor of 200) through
coal -ash source material in the vicinity of the downgradient portion of the active ash basin; (ii) horizontal
groundwater flow and chemical transport rates downgradient from the active ash basin; and (iii) vertical
flow rates from the overburden aquifer into the fractured bedrock unit beneath ponded areas. This
incorrect boundary condition representation of the active ash basin also causes the CAP models to
significantly underestimate (by on the order of a factor of two or more) both the mass loading of COI into
the Broad River and the corresponding Broad River surface water concentrations (attributable to coal ash
ponds) that HDR estimated with their mixing model (e.g., CAP 2 report Table 4-2 and Appendix D).
CAP Chemical Transport Modeling
Due to model calibration, model construction, and boundary -condition and input -data errors the CAP
models significantly underestimate remediation time frames. As discussed in this section, reasons for this
include significant underestimation of the chemical mass sorbed to soil, failure to account for slow
chemical desorption rates, inaccurate analyses of water -table lowering due to capping, and flaws in the
transport model calibration.
Soil -Water Partition Coefficients and Model Calibration
The fraction of chemical mass sorbed to soil can be represented by the soil -water partition coefficient, Kd
(Lyman et al., 1982). Kd is an especially important parameter at the Cliffside site because for most of the
19

COI the bulk of the chemical mass in the soil is associated with the solid phase (i.e., sorbed to soil grains
rather than dissolved in pore water). In effect, the solid fraction of the soil matrix acts as a large "storage
reservoir" for chemical mass when Kd is large [e.g., metals, many chlorinated solvents, and highly -
chlorinated polycyclic aromatic hydrocarbon (PAH) compounds associated with coal tars and wood -
treating fluids]. Kd is also a very important chemical transport parameter which is used to compute the
chemical retardation factor, Rd, assuming linear equilibrium partitioning of mass between the soil (solid)
and pore -water phases (Hemond and Fechner, 1994):
Rd=1+p6KdIn,
where Pb is the soil matrix bulk dry density and ne is the effective soil porosity. For example, the
chemical migration rate is directly proportional to hydraulic conductivity and inversely proportional to Rd .
The total contaminant mass in an aquifer is also directly proportional to Rd, as well as aquifer cleanup
times once the source is removed (e.g., Zheng et al., 1991).
Accordingly, it is very important to use accurate Kd values in the CAP Closure Scenario modeling.
Specifically, the CAP Part 1 transport modeling used Kd values that were typically factors of 10 - 100 (i.e.,
one to two orders of magnitude) smaller than the measured site -specific Kd's reported in CAP Appendix
D. In contrast, the CAP Part 2 transport modeling used Kd values that are generally a factor of about 10
larger than the CAP 1 values; however, the CAP 2 Kd's are still on the order of 10 times smaller than the
measured site -specific Kd's reported in CAP 1 Appendix D and CAP 2 Appendix C. Further, soil -water
partition coefficients for the CAP Parts 1 and 2 models are much smaller than most values presented in
the literature for the COI (e.g., EPRI, 1984; Baes and Sharp, 1983). This means that, using the actual
measured Kd's for the Cliffside site, the times required to reach North Carolina water quality standards at
the Compliance Boundary are at least a factor of 10 longer (see additional discussion below) than
cleanup times predicted by the CAP Parts 1 and 2 transport models for many COI.
The CAP 1 modeling report (CAP 1 Appendix C; Section 4.8) argues that the major Kd reductions were
needed due to the following:
"The conceptual transport model specifies that COis enter the model from the shallow saturated source
zones in the ash basins. When the measured Kd values are applied in the numerical model to COls
migrating from the source zones, some COls do not reach the downgradient observation wells where they
were observed in June/July 2015 at the end of the simulation period. The most appropriate method to
calibrate the transport model in this case is to lower the Kd values until an acceptable agreement
between measured and modeled concentrations is achieved. Thus, an effective Kd value results that
likely represents the combined result of intermittent activities over the service life of the ash basin. These
may include pond dredging, dewatering for dike construction, and ash grading and placement. This
approach is expected to produce conservative results, as sorbed constituent mass is released and
transported downgradient."
20

First, considering the approach that was used to develop the chemical transport model (history matching),
it is not true that "the most appropriate method to calibrate the transport model is to lower the Kd values."
The CAP Parts 1 and 2 transport models used an incorrect value (2.65 g/cm3) for the bulk density of
overburden materials; this value is the density of a solid mass of mineral (e.g., quartz) with zero porosity.
The bulk density should have been computed using the total porosity (n) values in CSA Table 11-1 using
the following formula (e.g., Baes and Sharp, 1983):
Pb = 2.65 (1— n)
Based on the Table 11-1 values Pb — 1.0 - 1.9 g/cm3, which means that the Rd values for the CAP 1 and
2 models were as much as a factor of 2.65 (2.65/1.0) too high before HDR adjusted the Kd values during
calibration. Also, as discussed earlier, the overburden slug test values were about 70 percent too low
due to HDR's data analysis errors. Both of these errors (sorption rate and hydraulic conductivity) resulted
in a modeled transport rate that was up to five times (5x) too low before calibration simply due to data
input errors.
At least two other important factors were not considered during the transport model calibration. At least
two other important factors were not considered during the CAP 1 and 2 transport model calibrations.
First, the groundwater flow models are based on average hydraulic conductivity (K) values within a
material zone, but K distributions in aquifers are highly variable (e.g., varying by factors of 3-10, or more,
over distances as small as a few feet: Gelhar, 1984, 1986, 1987; Gelhar and Axness, 1983; Rehfeldt et
al., 1992; Rehfeldt and Gelhar, 1992; Molz, 2015). The Cliffside site hydrogeology certainly qualifies as
"heterogeneous". This is very important to consider for the CAP transport model calibrations because it is
the high -permeability zones and/or layers that control the time required (Ttra,,l ) for a constituent to reach
a downgradient observation point, and HDR used differences in observed versus simulated Trraveq (i.e.,
time to travel from sources zones to downgradient monitoring wells) as the justification for lowering
measured Kd values.
Second, the history matching that HDR performed is very sensitive to the assumed time at which the
source (i.e., coal ash) is "turned on" and to the assumed distribution of source concentrations (fixed pore
water concentrations) in source area cells. Section 5.3 of CAP 1 Appendix C explains that the source
was activated 58 years ago in the model:
"The model assumed an initial concentration of 0 within the groundwater system for all COls at the
beginning of operations approximately 58 years ago. A source term matching the pore water
concentrations for each COI was applied within the Units 1-4 inactive ash basin, Unit 5 inactive ash basin,
active ash basin and the ash storage area at the start of the calibration period. The source concentrations
21

were adjusted to match measured values in the downgradient monitoring wells that had exceedances of
the 2L Standard for each COI in June 2015. "
For several reasons it is a major simplification (and generally inaccurate) to use 2015 ash pore water
concentrations to define year-1957 source zone (fixed concentration) boundary conditions. These
reasons include: coal ash was gradually and nonuniformly distributed (spatially and temporally) in ash
basins throughout the 58-year simulation period (not instantaneously in 1957); it is very difficult (or not
possible) to accurately extrapolate geochemical or ash -water leaching conditions (i.e., predict COI pore -
water concentrations) that existed during the 2015 sampling round to conditions that may have existed in
1957 and thereafter; the actual source -area concentration distributions are highly nonuniform, but it is not
clear from the CAP modeling reports how "... source concentrations were adjusted to match measured
values ... ", or if the source area concentrations were nonuniform. All of these uncertainties are further
magnified when using history matching to calibrate a chemical transport model.
Based on the above model input errors and major uncertainties in hydraulic -conductivity variations and
source -term modeling, it is incorrect to simply reduce Kd values by factors of 10 to 100 below site
measurements (and the large database of literature Kd values) based only on the transport model "history
matching" exercises that HDR performed. My additional comments on the CAP Parts 1 and 2 transport
modeling of Closure Scenarios are listed in the following section.
Geochemical Modeling and Evaluation of Monitored Natural Attenuation
The CAP Part 2 geochemical modeling results do not include quantitative analyses of COI attenuation
rates at the Cliffside site and are only qualitative in nature. In addition, HDR did not incorporate any
source/sink (e.g., precipitation/dissolution) terms representing geochemical reaction mechanisms in the
CAP 2 chemical transport model to evaluate whether such reactions are important compared to
groundwater concentration changes caused by advection, dispersion, and soil -water partitioning. In this
regard, HDR states in Section 2.10 of CAP 2 Appendix B : "A physical -type modeling approach was
used, as site -specific geochemical conditions are not understood or characterized at the scale and extent
required for inclusion in the model." Indeed, the Electric Power Research Institute (e.g., EPRI, 1984;
page S-8) has extensively reviewed subsurface chemical attenuation mechanisms applicable to the "utility
waste environment" and concluded: (i) precipitation/dissolution has not been adequately studied; and (ii)
"Quantitative predictions of chemical attenuation rates based upon mineralogy and groundwater
composition cannot be made because only descriptive and qualitative information are available for
adsorption/desorption mechanisms."
Nonetheless, HDR performed the geochemical modeling to evaluate the technical basis for its MNA
analysis; however, any quantitative MNA analysis must compare mass transport rates and changes (e.g.,
22

grams/year per unit area normal to a groundwater pathline) in the aquifer for the various active transport
mechanisms in order to determine whether MNA is a viable alternative (e.g., produces meaningful
groundwater concentration reductions) at the Cliffside site. In Section 6.3.2 of the CAP 2 report HDR
acknowledges that these quantitative evaluations were not performed in CAP 2 and indicated that they
would need to be completed as part of a Tier III MNA assessment. Nevertheless, HDR suggested in the
CAP 2 report that COI concentrations "will" or "may" attenuate over time without completing the
necessary evaluations to reach these conclusions. HDR also states in CAP 2 Section 6.3.4 that "MNA is
an effective correction action because COls will attenuate over time to restore groundwater quality at the
CSS site...." and in CAP 2 Section 6.3.3 that "the groundwater model did not allow for removal of COI via
co -precipitation with iron oxides, which likely resulted in an over -prediction of COI transport. Completion
of the Tier 11 assessment described in Appendix H has addressed this issue." I saw no quantitative
analysis or evidence in the CAP 2 report or related appendices to support these claims. In fact, the CAP
2 Appendix H emphasizes that much more geochemical data need to be collected and chemical transport
modeling with a source/sink term must be performed in a Tier III assessment to further assess whether
MNA is a viable remedial alternative.
Therefore, the CAP 2 report fails to provide any quantitative evidence supporting COI attenuation due to
co -precipitation with iron or manganese. The second component of COI attenuation evaluated in
Appendix H is chemical sorption to soil. It is important to note that, although the CAP models did not
incorporate a mechanism for co -precipitation with iron or manganese (or any COI sink term), the CAP
models did simulate attenuation due to sorption. Even with the sorption attenuation mechanism included,
CAP 2 Table 4-1 shows that for both the "existing conditions" and "cap -in -place" scenarios the following
COI will exceed North Carolina groundwater standards at the Compliance Boundary 100 years into the
future: antimony, arsenic, beryllium, boron, chromium, hexavalent chromium, cobalt, lead, sulfate,
thallium, and vanadium. Further, my Table 1 shows that groundwater standards are currently exceeded
at the Compliance Boundary for barium, cobalt, iron, manganese, nickel, and total dissolved solids (i.e.,
barium, cobalt, iron, manganese, nickel, and TDS contaminant plumes originating in the source areas
have already reached the Compliance Boundary). The conclusions of the MNA Tier I analyses (CAP 2
Appendix H, page 18) were that arsenic, barium, beryllium, boron, chromium, cobalt, lead, thallium, and
vanadium showed some evidence of attenuation and should be evaluated further in a Tier II evaluation.
However, the CAP 2 modeling results in Table 4-1 (which included a significant amount of sorption
attenuation) show that all of these COI currently exceed North Carolina groundwater standards at the
Compliance Boundary and are expected to exceed those standard 100 years into the future. All of these
data and CAP 2 modeling results strongly contradict the CAP 2 conclusion that MNA is a viable corrective
action at the Cliffside site.
23

Simulation of Closure Scenarios
As discussed below, CAP 1 Closure Scenario simulations greatly underestimate (by factors of 10 or
more) the time frames required to achieve meaningful groundwater concentration reductions in response
to remedial actions. Compared to the Cap -in -Place (CIP) remedial alternative evaluated in the CAP Part
1, the Excavation Scenario results in COI concentration reductions at the Compliance Boundary that are
generally two to ten times greater compared to Cap -in -Place and best reduces impacts to surface water.
In addition, the time frames to achieve equivalent concentration reductions are at least factors of 2 to 5 (2
- 5x) shorter for excavation compared to cap -in -place for most of the COI; further, several COI
concentrations reduce below 2L or IMAC standards with excavation but remain significantly higher than
the groundwater standards with cap -in -place.
Although the CAP 1 modeling showed that Source Excavation outperforms CIP, the CAP 2 modeling did
not simulate an Excavation closure scenario. Nonetheless, the following comparisons between CIP and
Excavation impacts on groundwater concentrations are valid for both the CAP 1 and 2 model results.
This is because the main difference with the CAP 2 transport model (compared to CAP 1) is that
concentration changes resulting from either CIP or Excavation (if it was evaluated in CAP 2) occur much
more slowly (i.e., — 10x slower) in the CAP 2 model due to the much larger Kd (and Rd) values. The CAP
2 transport model also assumed uniform initial COI concentrations equal to HDR's proposed provisional
background concentrations (PPBC), even though the PPBC exaggerate background levels (see above
discussion) and there are no data to suggest that background concentrations should be spatially uniform.
Despite these changes in the CAP 1 and 2 models, the relative differences in groundwater concentrations
between the two closure scenarios remain about the same if the uniform starting (PPBC) COI
concentrations are subtracted from the simulated concentration versus time curves. For these reasons
the following discussions focus on the CAP 1 modeling results.
Source Concentrations for Cap -in -Place Scenario
In this scenario the CAP 1 flow model predicts cap -induced water -table declines equal to approximately 5
feet (relative to the Existing Conditions simulation) within the Units 1-4 inactive ash basins, 12 feet within
the Unit 5 inactive ash basin (11 feet in the CAP 2 flow modeling), and 10 feet within the active ash basin
(10 feet in CAP 2). However, the geologic cross -sections presented in the CSA show that the saturated
coal ash thickness at several borings is as great as 30-60 feet. This means that under the simulated
Cap -In -Place Scenario most of the coal ash, which is the source of dissolved COI, would remain
saturated and continue to leach constituents into groundwater in several parts of the ash basin system.
The CAP 1 simulations ignored this fact and set all source concentrations equal to zero (i.e., assumed all
coal ash was dewatered). Therefore, the simulated Cap -in -Place concentrations should be much higher
than the values presented in the CAP Part 1.
24

The groundwater flow model simulations also exaggerate the hydraulic effects of the cap (i.e., overstates
water table lowering) because the no -flow boundary conditions along the entire western, southern, and
eastern grid boundaries prevent flow into the Ash Basin System when the laterally inward hydraulic
gradients are created by capping. In addition, the base of the flow model is assumed to be impervious
even though the bedrock aquifer hydraulic conductivity is about the same as the overburden aquifer; this
artificially restricts upward flow from bedrock into the capped area and exaggerates predicted water table
lowering.
In addition, a site -specific distribution of groundwater recharge values should have been developed for
this and the other simulation scenarios to take into account site -specific topography and soil types (e.g.,
runoff estimation) and climate data (precipitation, evapotranspiration, etc.; e.g., using the U.S. Army
Corps of Engineers HELP Model; Schroeder et al., 1994). The CAP 1 flow model uses an assumed
value of 6 inches year uniformly throughout the model domain even though the actual value is highly
variable across the Ash Basin System and site land surface. Further, as discussed above, HDR should
have used a leaky -type boundary condition to model ponded areas of the active ash basin. The predicted
water table lowering due to capping is very sensitive to the model recharge value, so more effort should
have been made to develop a site -specific recharge -rate distribution.
Slow and Multirate Nonequilibrium Desorption of COI
Since the 1980's the groundwater industry has learned how difficult it is to achieve water quality
standards at remediation sites without using robust corrective actions such as source removal (Hadley
and Newell, 2012, 2014; Siegel, 2014). Two of the key reasons for this in aqueous -phase contaminated
soil are inherently low groundwater or remediation fluid flushing rates in low -permeability zones and slow,
nonequilibrium chemical desorption from the soil matrix (Culver et al., 1997, 2000; Zheng et al., 2010). A
good example of this is the "tailing effect" (i.e., very slow concentration reduction with time) that is
commonly observed with pump -and -treat, hydraulic containment systems. These factors are also related
to the "rebound effect" in which groundwater concentrations sometimes increase shortly after a
remediation system is turned off (Sudicky and Illman, 2011; Hadley and Newell, 2014; Culver et al.,
1997).
The CAP 1 and 2 flow models use different permeability (K) zones, but the scale of these zones is very
large and within each zone K is homogeneous even though large hydraulic conductivity variations (e.g.,
lognormal distribution) are known to exist at any field site over relatively small length scales (Molz, 2015).
Moreover, the CAP transport models assume linear, equilibrium soil -water partitioning which corresponds
to instantaneous COI release into flowing groundwater. The transport code (MT3D) has the capability of
simulating single -rate nonequilibrium sorption, but the Close Scenario simulations did not utilize this
modeling feature. Slow desorption of COI can also be expected at the Allen site because sorption rates
25

are generally highly variable, and multi -rate (Culver et al., 1997, 2000; Zheng et al., 2010), and Kd
values are nonuniform spatially (Baes and Sharp, 1983; EPRI, 1984; De Wit et al., 1995). The CAP flow
and transport models can be expected to significantly underestimate cleanup times required to meet
groundwater standards at the compliance boundary because they do not incorporate these important
physical mechanisms.
Adequacy of the Kd Model for Transport Simulation
The laboratory column experiment effluent data (e.g., CAP 1 Appendix D) generally gave very poor
matches with the analytical (one-dimensional) transport model used to compute Kd values. Since the
CAP transport model solves the same governing equations in three dimensions, the adequacy of the Kd
modeling approach for long-term remedial simulations should have been evaluated in much more detail in
the modeling appendix.
The transport modeling also did not evaluate alternative nonlinear sorption models such as the Freundlich
and Langmuir isotherms (Hemond and Fechner, 1994), which are input options in the MT31D transport
code. Several of the batch equilibrium sorption experiments (CAP 1 Appendix D) exhibited nonlinear
behavior, and such behavior is commonly observed in other studies (e.g., EPRI, 1984). However, HDR
only computed linear sorption coefficients (i.e., Kd) for the Cliffside site in CAP Part 1. In CAP Part 2 HDR
did fit Freundlich isotherms to the batch sorption data for selected COI (CAP 2 Appendix C, Tables 1-8)
but did not use these Freundlich isotherm results in the CAP 2 transport modeling. De Wit et al. (1995)
showed that the nonlinear sorption mechanism is similar in importance to aquifer heterogeneities in
extending remediation time frames.
Closure Scenario Time Frames
As outlined in my report, the CAP Part 1 chemical transport model underestimates the time intervals
required to achieve groundwater concentration reductions (i.e., achieve groundwater quality restoration)
by factors that are at least on the order of 10 to 100. In other words, the CAP 1 transport model
significantly overestimates the rate at which concentrations may reduce in response to remedial actions
such as capping or source removal. This is due to several factors, including major errors in model input
data, model calibration mistakes, field data analysis errors, and oversimplified model representation of
field conditions (e.g., hydraulic conductivity) and transport mechanisms (e.g., chemical
sorption/desorption). These limitations of transport models for realistically predicting cleanup times have
been recognized by the groundwater industry for the past few decades based on hands-on experience at
hundreds of extensively -monitored remediation sites.
Even if we ignore the factors of 10 or more errors in cleanup time predictions with the CAP 1 model, the
remediation time frames for the Excavation Scenarios are still more than two centuries for several
26

constituents due to slow groundwater flushing rates from secondary sources (surrounding residual soil)
left in place after excavation and due to high chemical retardation factors for most of the COI. However,
excavation of secondary -source material would further accelerate cleanup rates under this alternative.
The CAP 1 simulated Cap -In -Place concentration reduction rates are much slower, compared to
excavation, but are also incorrect (i.e., overestimated) because the cap -induced water -table lowering is
insufficient to dewater all of the source -area coal ash, as discussed above, and the CAP 1 and 2 flow
models overestimate cap -induced water -table lowering due to boundary condition errors. Furthermore,
these simulation times are well beyond the prediction capabilities of any chemical transport model for a
complex field site (especially one that is as geochemically complex as the Cliffside site). The historical
model -calibration dataset (1957-2015) is also significantly smaller than the predictive (remediation) time
frames. In addition, the "history matching" technique used to calibrate the transport model (e.g., major
reduction in measured Kd values) was not performed correctly by HDR.
Cap -In -Place versus Excavation Closure Scenarios
Although the the CAP 1 model underestimates remediation time frames, the CAP 1 Closure Scenario
simulations demonstrate several significant advantages of excavation for restoring site groundwater
quality versus cap -in -place. First, predicted COI concentration reductions in groundwater downgradient
from the ash basin system are generally factors of 2-10 greater with excavation compared to cap -in -place
(e.g., refer to most of the simulated concentration versus time curves in CAP 1 Appendix C). Further, if
HDR had correctly performed the CAP 1 cap -in -place simulations the predicted CIP concentrations would
be much higher because predicted water -table lowering due to the cap would be insufficient to dewater all
of the coal ash. Second, North Carolina 2L or IMAC standards for many COI (antimony, arsenic,
chromium, hexavalent chromium, cobalt, nickel, thallium, vanadium) are not achieved by cap -in -place but
are achieved by excavation (e.g., CAP 1 Appendix C Figures 13, 20, 21, 26, 27, 28, 29, 30, 31, 33, 34,
36, 37, and 39). Third, the time frames to achieve equivalent concentration reductions are at least factors
of 2 to 5 shorter for excavation compared to cap -in -place; further, several COI concentrations reduce
below 2L or IMAC standards with excavation but remain significantly higher than the groundwater
standards with cap -in -place.
Even though the CAP 1 modeling demonstrated that the CIP closure alternative would be much less
effective than excavation, and that CIP would only dewater about 20-40 percent of the saturated coal -ash
thickness in many areas, HDR eliminated excavation from consideration in CAP 2. In Section 7.1 of the
CAP 2 report HDR assumes that "Evaluation of the geochemical modeling indicated COls are attenuated
by a combination of sorption and/or precipitation" and that "Based on review of the groundwater modeling
results, COls with sorption coefficients similar to or greater than arsenic are immobilized by sorption
and/or precipitation .....". As discussed above, HDR provided no quantitative analysis or evidence in the
CAP 2 report or related appendices to support this claim. Further, sorption is not a mechanism that
27

"immobilizes" a dissolved consituent; sorption only slows down the rate of transport proportional the
chemical retardation factor. Considering that up to 80 percent of the coal -ash source material would
remain saturated with CIP and that multiple exceedances of groundwater standards at the Compliance
Boundary currently exist (with no historical data to indicate that these Compliance Boundary
concentrations are decreasing with time), it is not reasonable to make sweeping assumptions about future
concentration changes. Tier III MNA analyses require rigorous quantitative evaluations using the CAP
transport model with a source/sink term that incorporates geochemical reactions to support MNA as a
viable corrective action. CAP 2 did not provide this information.
As discussed above, the CAP Part 2 flow model did include a small number of residential wells (13 of the
100 neighboring private wells), but the CAP 2 modeling report (CAP 2, Appendix B) did not show
simulated hydraulic head maps with these residential wells pumping and did not provide any discussion
or analyses of the long-term potential for these wells to capture COI dissolved in groundwater. Further,
the private bedrock wells that HDR chose to include in the CAP 2 model appear to be located upgradient
from the active ash basin; HDR should have included all of the private wells located near the northern
bank of the Broad River (in a downgradient direction from the ash basin system) and near the
northeastern site boundary which is downgradient from the active ash basin, as I describe above. In CAP
2 section 4.1.5 HDR discusses that fact that the CAP 2 flow model was used to compute 1-year, reverse
particle pathlines for these bedrock residential wells (Figure 18 in CAP 2 Appendix B) to determine their
short-term groundwater capture zones. However, the residential well reverse pathline tracing should
have been performed for a much longer time period (e.g., from the beginning of coal ash disposal to the
present) to evaluate whether COI may have migrated from source areas to these wells. In addition, if
HDR had extended the CAP 2 model grid much farther to the north and east the capture zones for the
remaining 87 private water supply wells could have been determined, as I discuss earlier in my report.
The CAP Closure Scenarios do not include hydraulic containment remedial alternatives (e.g., gradient
reversal) for the bedrock aquifer that would address the risk of off -site COI transport. As discussed
above, the CSA data show many exceedances of groundwater standards in bedrock not only at the
compliance boundary but also inside the CB. In addition, strong downward groundwater flow components
from the deep overburden to bedrock aquifers were measured during the CSA at multiple locations
across the site, including the southern shoreline of the Broad River. The cap -in -place alternative does not
address either concentration reduction or off -site chemical migration control in the fractured bedrock
aquifer.
The CAP Parts 1 and 2 do not assess whether water quality standards will be achieved in the tributaries
and wetlands between the ash basins and the Broad River [e.g., seep locations S-3 or S-6 (Broad River
tributaries) or the wetland located along Suck Creek downgradient from the upstream dam of the active
28

ash basin] under any closure scenario. As discussed above, for the cap -in -place scenario a significant
fraction of the source material will remain saturated and dissolved COI will continue to migrate with
groundwater toward these seep locations. Although unaddressed by the model, COI concentration
decreases in groundwater and unsaturated zone pore water due to source removal would also reduce
impacts to tributaries and wetlands that are influenced by the ash basins.
Conclusions
Based on my technical review and analyses of the referenced information for the Cliffside site I have
reached the following conclusions:
• A total of 62 Compliance Boundary groundwater samples exceeded North Carolina groundwater
standards for these COI: antimony, boron, chromium, cobalt, iron, manganese, sulfate, total
dissolved solids, and vanadium. Of these 62 exceedances, 36 were greater than the proposed
provisional background concentrations by HDR;
• The statistical analyses of shallow background groundwater concentrations at the Cliffside site
(well MW-24D) are invalid. The time periods between groundwater sample collection from this
well are too small and the concentration data are not independent;
• There is a significant risk of chemical migration from the ash basin to neighboring private water
supply wells in fractured bedrock. The design of the CAP flow and transport models prevents the
potential for off -site migration from being evaluated;
• The limited CAP model domain size; the no -flow boundary conditions along the western,
southern, and eastern boundaries; and incorrect hydraulic boundary condition representations of
the Broad River and the active ash basin prevent simulation and analysis of off -site COI
migration;
• The CAP Closure Scenario simulations greatly underestimate (by factors of 10 or more) the time
frames required to achieve meaningful groundwater concentration reductions in response to
remedial actions. This is due to oversimplification of field fate and transport mechanisms in the
CAP model and several model input errors;
• The simulated water table lowering for the Cap -in -Place Scenario is more than a factor of five too
small at several locations in the ash basin system in order to dewater all source material; and the
actual cap -induced water table elevation reduction would be much less than predicted due to the
incorrect no -flow boundary conditions. Therefore, the remediation time frames for this scenario
would be much greater because a large percentage of the source zone would still be active with
the cap installed;
29

• For either the Existing Condition or Cap -in -Place Model Scenario groundwater concentrations of
coal -ash constituents much higher than background levels will continue to exceed North Carolina
groundwater standards at the Compliance Boundary because saturated coal -ash material and
secondary sources will remain in place;
• Due to an incorrect boundary -condition representation of the active ash basin, the CAP models
underestimate by a factor of two or more both the mass loading of COI into the Broad River and
the corresponding Broad River water concentrations (attributable to coal ash ponds) estimated by
the groundwater/surface-water mixing model;
• Source -area mass removal included in the Excavation Scenario results in COI concentration
reductions at the Compliance Boundary that are generally two to ten (2 - 10x) times greater
compared to Cap -in -Place and best reduces impacts to surface water. In addition, the time
frames to achieve equivalent concentration reductions are factors of two to five (2 - 5x) shorter for
excavation compared to cap -in -place, and source removal reduces the number of COI that will
exceed North Carolina groundwater standards in the future. Additional excavation of secondary
sources would further accelerate concentration reductions;
• The CAP simulations show that source excavation reduces groundwater concentrations for many
COI below North Carolina groundwater standards (antimony, arsenic, chromium, hexavalent
chromium, cobalt, nickel, thallium, vanadium), but cap -in -place closure does not;
• The CAP Part 2 geochemical modeling and monitored natural attenuation (MNA) evaluations do
not provide the required quantitative analyses (e.g., numerical transport modeling) of COI
attenuation rates necessary to support MNA as a viable corrective action and are only qualitative
in nature. The CAP 2 chemical transport modeling, which included attenuation by sorption,
demonstrated that MNA is not an effective remedial option for several COI (e.g., antimony,
arsenic, beryllium, boron, chromium, hexavalent chromium, cobalt, lead, sulfate, thallium, and
vanadium);
• The CAP Closure Scenarios do not include hydraulic containment remedial alternatives for the
bedrock aquifer and do not address the risk of off -site COI transport. CSA data show multiple
exceedances of groundwater standards in bedrock not only at the compliance boundary but also
inside the CB. The cap -in -place alternative does not address either concentration reduction or
off -site chemical migration control in the fractured bedrock aquifer; and
• Future Compliance Monitoring at the site should include much more closely -spaced Compliance
Wells to provide more accurate detection, and the time intervals between sample collection
should be large enough to ensure that the groundwater sample data are statistically independent
to allow accurate interpretation of concentration trends.
30

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