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Susitna‐Watana Hydroelectric Project Document
ARLIS Uniform Cover Page
TK
1425
.S8
S92
no.303
Title:
SuWa 303
Letter from Socheata Lor to Wayne Dyok, October 8, 2014, providing U.S.
Fish and Wildlife Service's comments on the Initial Study Report for the
Susitna-Watana Hydroelectric Project
[Title devised by cataloger.]
Author(s) – Personal:
Socheata Lor (writer of cover letter)
Author(s) – Corporate:
U.S. Fish and Wildlife Service. Anchorage Fish and Wildlife Field Office
AEA‐identified category, if specified:
AEA‐identified series, if specified:
Series (ARLIS‐assigned report number): Existing numbers on document:
Susitna-Watana Hydroelectric Project document number 303 20151005-5355 (FERC posting)
Published by: Date published:
U.S. Fish and Wildlife Service, Anchorage Fish and Wildlife
Field Office
September 22, 2014
Published for: Date or date range of report:
Wayne Dyok ; Alaska Energy Authority
Volume and/or Part numbers: Final or Draft status, as indicated:
Document type: Pagination:
Letter with attachments 4, 4, 2 pages
Related work(s): Pages added/changed by ARLIS:
Comments to: Initial Study Report. (SuWa 223)
Notes:
Distributed also as a posting of FERC eSubscription to Docket 14241.
The attachments contain detailed information that supplements the comments in the letter.
All reports in the Susitna‐Watana Hydroelectric Project Document series include an ARLIS‐
produced cover page and an ARLIS‐assigned number for uniformity and citability. All reports
are posted online at http://www.arlis.org/susitnadocfinder/
United States Department of the Interior
FISH AND WILDLIFE SERVICE
Anchorage Field Office
605 W. 4th Avenue, Room G-61
Anchorage, Alaska 9950 I -2250
In Reply Refer To:
FWS/ AFES/AFWFO
Mr. WayneDyok
Susitna-Watana Project Manager
Alaska Energy Authority
813 West Northern Lights Boulevard
Anchorage, Alaska 99503
Dear Mr. Dyok:
SEP 2 2 2014
FERC Project P-14241, Susitna-Watana Hydropower
The U. S. Fish and Wildlife Service (Service) is providing comments on the Alaska Energy
Authority's (AEA) June 3, 2014, Initial Study Report (ISR) for the proposed Susitna-Watana
Hydropower project (Project). We provide AEA with our preliminary findings of concern so
that they may be meaningfully considered prior to and discussed at the October, 2014 ISR
meeting. The Service intends to provide full and detailed comments on these and other topics
by the November 30,2014, Federal Energy Regulatory Commission's (FER C) filing deadline.
As per the FERC Integrated Licensing Process (ILP; 18 CFR 5.15 (c)(2)), the ISR meeting
scheduled in October, 2014, provides an opportunity for AEA and licensing participants to
discuss the 2013 studies and identify potential modifications to study designs based on the first
year's data collection. The process allows for review and recommendation of changes to
sampling methodologies implemented by first year studies to ensure study objectives, as
specified in the PERC-approved Revised Study Plans (RSP), are met. Our filing to FERC by
November 30, 2014, will formalize our comprehensive comments and recommendations after
AEA has had the opportunity to address our concerns during the October, 2014 ISR meeting.
The Service has identified three topics of significant concern: 1) data collection and reporting,
2) effective model integration, and 3) development of decision support systems (DSS). These
three topics are closely tied together because precise and accurate data provide inputs to models
that are used to support Project decision-making.
In these preliminary comments, the Service identifies data collection and reporting concerns
(Attachment I) and recommends the data issues be resolved as soon as possible. Without robust
data from individual studies, we are concerned the data do not meet study objectives, that model
validation will be hindered, and model integration may lead to incorrect conclusions. Given the
magnitude of our concerns related to data collection and reporting, we believe it may not be
Mr. Wayne Dyok
possible to yield plausible model predictions describing baseline conditions or to predict
potential impacts. It is important that these issues be resolved prior to conducting additional
field studies.
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Much of the data collected under FERC approved study plans are proposed for use in fish habitat
models, and the development of those models are based on changes to cha1mel geomorphology
and hydrology. Relationships among hydrologic models should be validated and models
calibrated for the Susitna River system before their use in fish habitat models. Likewise,
relationships among fish habitat models should be validated, and models calibrated for the
Susitna River system prior to their use in estimating Project effects under various operational
scenarios. To our knowledge there is currently no specific model integration process proposed
that will ensure sound relationships among models and their accurate calibration for the Susitna
River system. The Service believes that development and implementation of rigorous model
integration procedures is critical to our review of this project and we discuss our preliminary
concerns in detail (Attachment II).
A DSS is one of the end products of the studies, where data and models from the studies are
ultimately used to help make decisions on the effects of the Project on natural resources. We
understand AEA intends to develop a DSS using a manual matlix method by early 2015 (FERC
2013). As the DSS plays such an important role in the assessment ofProject impacts, the
Service requests its development be a collaborative process so that the fundamental objectives,
assumptions, critical inputs, weighting methods, and other pruis of the model are mutually agreed
upon. Furthermore, we are concerned that the timeline for DSS development is lagging other
efforts. The ILP process is founded under the principal of early identification of potential issues
and conducting studies needed to fill information gaps (FERC 2014). Data gaps may be revealed
once the fundamental objectives for the DSS are formulated. Until the DSS development
process occurs, it is uncertain all the data needed to implement the DSS has been gathered.
Because the DSS is not scheduled for development unti12015, it is distinctly possible that crucial
new data needs may be revealed when updated study reports are filed by AEA in 2016 (as per the
ILP extension approved by FERC on January 28, 2014). However, going forward, the Service
believes the development of a collaboratively designed DSS is of great importance to this Project
and recommends that, if practicable, the timeline for its development be accelerated.
Finally, FERC established a new schedule for the proposed Susitna-Watana hydroelectric project
ILP in their January, 2014 determination. In that determination, FERC ordered AEA to submit
fmal ISRs on June 3, 2014, for stakeholder review, to hold a meeting in October, 2014, to present
results of those ISRs, and to discuss AEA proposed changes to the studies or those proposed by
other licensing participants. During a meeting with the Service and National Mmine Fisheries
Service on September 2, 2014, AEA stated its intent to re]ease reports from 21 new or
continued studies conducted in 2014, with intent to discuss results at the October 15,2014, ISR
meeting. On September 17,2014, AEA filed 10 of2l reports to FERC. Because the data were
gathered outside timelines specified by the FERC -ordered process, and given the limited review
Mr. Wayne Dyok 3
time the Service will have, we will be unable to consider and comment on those study reports in
advance of the October, 2014 ISR meeting. Furthermore, we recommend AEA dedicate the
limited time at the October, 2014, ISR meeting to discuss concerns related to 2013 studies, as
reported in the June 3, 2014, ISR. Additionally, an email on May 6, 2014, copied to the Service
by FERC, indicated that studies carried out by AEA in 2014 were conducted outside of the ILP
process and would not be considered "second year" studies. This is procedurally very important
because ~'\either the Service, nor other licensing participants (Non-Govemmental Organizations
(NGO) Participants 2014), will have the opportunity to fully review or comment on the design
and implementation of the 2014 studies. The Service will be unable to meaningfully contribute
to the discussion of the 2014 studies and urge AEA to not discuss any work conducted in 2014 at
the ISR meeting. Instead, we suggest the interim results gathered between study years (i.e., 2014
data collection) be discussed at the next quatterly Technical Workgroup meeting, once we have
had sufficient opportunities to review those additional data.
Summary
This letter describes some of the Service's concerns with studies reported in the June 3, 2014,
ISR, and we are providing them to AEA prior to the November 30, 2014, FERC filing deadline
so some issues can be discussed and resolved in a timely manner. The concerns address: 1) data
collection and reporting, 2) ability to recommend further studies under the FERC ILP licensing
process, 3) development of valid models to assess baseline conditions and effects from Project
operations on fish and wildlife resources, 4) capacity to formulate recommendations under
section 1 O(j) of the Federal Power Act for protection, mitigation, and enhancement measures
associated with the Project, and 5) formulation of informed decisions pursuant to our Section 18
Fishway Prescription authority under the Federal Power Act. We believe the modified ILP
schedule for the Project affords AEA the opportunity to make necessary changes to studies prior
to entering the second year of study. The Service believes this review process accommodates the
development and implementation of more accurate, effective, and cost-effective plans of study
for the Project.
Thank you for the opportunity to submit these comments in advance to the October, 2014 ISR
meeting. We hope they are useful to AEA and will generate valuable conversations at the
meeting. If you have questions, please contact Ellen Lance (907) 271-1467.
Sincerely,
~ Sochea~-
Anchorage Field Supervisor
Mr. Wayne Dyok
Cc: Sarah Goad, AIDEA
Betsy McGregor, AEA
Nicholas Jayjack, FERC
Joe Klein, ADFG, Sport Fish Division
Jeanne Hansen, NMFS
Sue Walker, NMFS
Mike Bethe, ADFG, Habitat Division
Matthew LaCroix, EPA
Literature Cited
[FERC] Federal Energy Regulatory Commission. 2013. Letter to Wayne Dyok. Study Plan
Detennination on 14 remaining studies for the Susitna-Watana Hydroelectric Project.
February 1, 2013.
__ 2014. Integrated Licensing Process. http://www.ferc.gov/industries/hydropower/gen-
info/licensing/ilp.asp, accessed September 18, 20 14).
[NGO Participants] Wood, M., W. Wolff, J. Konigsberg, M. Wood, R. Schryver, J. Seebach
(collectively the NGO Participants). 2014. Initial Study Report Meeting, Susitna-Watana
Hydroelectric Project (P-14241). Letter filed with FERC, September 16,2014.
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[USFWS] U.S. Fish and Wildlife Service. 2013. Letter to FERC Re: Alaska Energy Authmity's
Revised Study Plan for the Susitna-Watana Hydroelectric Project No. 14241-000. March l 8,
2013.
Attachment I. Data Issues
Below we discuss our preliminary concerns relating to deviations from study plans , quality
assurance and control , and statistical practices and procedures for the 2013 study year.
Deviations From Study Plans-Deviations from established sampling designs occurred in some
studies for various reasons , and in some cases resulted in reduced sample size or compromised
reliability of data . Below we provide examples .
• As currently planned , some two-year studies cannot be completed because access to all
Focus Areas (FAs) was not granted until after the first study year (e .g., ISRs 8.5 , 9.6 , 9 .7,
9.9). For example , a fish wheel was not installed and fish were not tagged near the
entrance to Devil 's Canyon (e .g., ISR 9 .7).
• Anomalous weather conditions prevented or delayed fieldwork on aquatic studies (e .g .,
ISR 8 .5), resulted in late installation of migrant traps , which were likely influenced by
environmental conditions associated with late breakup (e .g., ISR 9 .6). Moreover,
juvenile salmon distribution and abundance measured in 2013 were likely affected by the
record fall floods in 2012 (e .g., ISR 9.6).
• Sampling has not been temporally adequate across all seasons . ISR 9 .6 reports winter
fish sampling did not occur across all F As as proposed; early spring sampling occurred
only in three FAs ; initial sampling following breakup and installation of migrant traps did
not occur until the middle of June , and therefore , spring sampling for fish distribution and
abundance was not conducted (e.g ., ISRs 7.5, 8.5, 8.6). The extent to which fishes move
must be described through sampling; multiple sampling days across all seasons are
required to capture the full seasonality of a fish 's life-history strategy, which varies
considerably within a single season . A single-day of sampling is insufficient to
understand the habitat associations of different fish species with differing mobility and
life-stages.
• Sample site selections for integrated studies were inconsistently co-located. For example ,
invertebrate sampling locations (ISR 9 .8) were not co-located with fish sampling
locations (ISR 9 .6). Failure to co-locate sampling sites risks the magnification of data
discrepancies , and because the data will be used as inputs for predictive models , may
jeopardize the validity of the models .
• Detection arrays did not cover the entire channel and tagging efforts did not allow for
detection of fish migrating upstream, therefore the data were biased and efficiency
estimates cannot be calculated . Detection rate and recovery of passive integrated
transponder (PIT) tags is insufficient to yield useful data to meet study goals and
objectives (ISR 9 .6).
• Fish targets for fish Habitat Suitability Curve (HSC) sampling were not met (e .g., ISR
8.5), therefore , power to assess fish habitat-preferences and relationships is reduced .
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• Data collected on fish habitat for the Fish Passage Barrier Study (ISR 9 .12) and the
HSI/HSC component of the fish and aquatic Instream Flow Study (ISR 8.5) were
gathered at incompatible spatial scales to meet the study objectives .
Quality Assurance and Control Concerns-Below we preliminarily provide some discrete
examples where the Service has data quality concerns. Poor data quality has a rippling effect
throughout this assessment process because extrapolating inaccurate results throughout the river
would amplify errors across the river and associated habitat.
• Water quality samples were qualified as either estimated or rejected by the analytical
laboratory due to quality-related failures (ISR 5.5). Issues included failure to deliver
samples to the laboratories within the method-specified temperature range ; failure to
meet procedure specified holding times ; contaminated or missing field , trip , and method
blanks ; and Chain of Custody and bottle labeling discrepancies . AEA proposed to apply
a correction factor to the 2013 data to render it useable , but provided no details on how
that would be done .
• There is evidence that juvenile salmon may have been misidentified . A comparison of
juvenile fish collections from the Susitna River in the 1980s (Alaska Department ofFish
and Game 1983 as cited by R2 Consultants in the Fish Population Summary Document),
local Alaskan rivers (Alaska Department ofFish and Game , unpublished data ; Davis et
al. 2013), recent studies on the Susitna River (Kirsch et al. 2014), and nearby tributaries
(Miller et al. 2011 ), signal substantial differences in total fork length distribution and
habitat associations among juvenile salmon from that which is expected. Large numbers
of unidentified salmonid juveniles (some of which were PIT tagged), anomalous length
distributions and questionable habitat associations decrease our confidence in the
accuracy of species identification . For example , juvenile Chinook salmon measuring 150
mm fork-length were reported , juvenile Chinook salmon were reportedly most abundant
in beaver ponds , there was absence of pink salmon in any samples , and a disappearance
of sockeye salmon from Indian River between the February draft ISR and the June draft
I SR. We have strong reservations about the identification of these juvenile fish , and
suspect many juvenile salmons identified as Chinook salmon may be coho salmon .
• Information used to describe fish/habitat preferences were gathered using professional
best judgment, literature , and limited field data , but were not confirmed with an adequate
sample from the Susitna River system (ISR 8.5). Fish/habitat data gathered from the
Susitna River is necessary to identify preferential use of the habitats . It is vital that these
data are accurate as they will be used to: 1) develop Habitat Suitability Indices (HSI) and
Habitat Suitability Criteria (HSC); 2) describe fish-macrohabitat relationships , which
may be used to evaluate project effects ; 3) validate the Instream Flow Study (8 .5) habitat
model predictions ; and 4) extrapolate results from FAs to geomorphic reaches and river
segments . Ultimately the data will be used to develop protection and mitigation measures
and to provide a basis for post-project monitoring.
• The Service is concerned about AEA 's proposal to "scale up ", and requests rationale for
its implementation (Riverine Model Integration Meeting 2013). "Scaling up " is only
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appropriate when the sampling is conducted accurately, in a random fashion throughout
the population, and at a scale relevant to resource concerns . To assess impacts from the
Project on fish resources , sampling effort must be at a scale relevant to Susitna River fish
species at various life stages in order to adequately quantify baseline conditions with the
accuracy required for accurate extrapolation . For example , incorrect fish identification
and would lead to imprecise and inaccurate extrapolation of species-specific habitat
associations.
Statistical Practices and Procedures-Based on our preliminary reviews , we note (below) failures
to report standard statistical procedures and calculations required for complete analyses .
• Standard error was not reported for stated relationships between species of juvenile
salmonids at various life stages and their habitat (e.g ., ISRs 9 .5, 9 .6). A robust
assessment of statistical results must include calculations for standard error.
• Assumptions for the estimating numbers of Chinook salmon migrating above Devils
Canyon were not clearly specified and the standard error of that estimate was not reported
(e .g., ISRs 9.6 , 9 .7).
• Sampling and non-sampling errors were not clearly stated (e .g., ISR 9 . 7). Sampling error
is the error resulting from sampling only a part of the population and not the whole
population. Non-sampling errors are those errors resulting from selection bias ,
systematic non-representativeness of samples , and transcription or recording errors .
Sampling error is usually quantified and reported with confidence intervals or standard
errors and related to precision of the estimates . Non-sampling errors are harder to
recognize , yet very important, and more closely related to the accuracy of the estimates .
Sampling errors must be clearly accounted for in statistical analyses to assess data
reliability and interpret results .
• Consistent fish sampling methods were not applied (i.e ., different gear types used ,
different effort was applied within and across sampling units , concurrent use of non-
compatible gear types within a sampling unit). This resulted in inability to estimate
sampling error because (e .g ., ISR 9 .6) inconsistent sampling methods resulted in
individual datasets that are not comparable .
• No power analysis was reported (ISR 9.14), and it is unclear how sample size for both
adult and juvenile Chinook salmon was determined . Based on the number of genetic
markers sampled and the magnitude of genetic divergence measured in the population
documented thus far , a power analysis would inform determination of the number of
samples needed to provide a robust estimate of genetic diversity. Furthermore , three
years of samples may not be adequate to characterize genetic diversity among a species
with a life cycle of five to seven years ; this limitation must be addressed in the study
results .
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• Samples from presumed siblings were proposed for removal from the genetic analyses
(ISR 9 .14). Only if the samples have been collected in a non-random way may this
method be justified. Purging related animals as proposed will bias the results .
Furthermore , ISR 9 .14 proposes to exclude samples from juvenile Chinook salmon if
they show significant differences in allele frequency from adult Chinook salmon . Using
all data will produce a more robust estimate of allelic frequencies across the entire
population.
• Using a Bonferroni adjustment on the tests for Hardy-Weinberg Equilibrium (ISR 9.14)
will increase the risk of a Type-2 error and reduce the statistical power of the test to
detect a difference . Furthermore , estimates of genetic distance using F 51 must include a
correction for sample size otherwise small samples tend to look like outliers (ISR 9 .14).
Literature Cited
ADFG . Unpublished data for Willow Creek and Deshka River tagging study .
Alaska Department ofFish and Game . 1983 . Resident and Juvenile Anadromous Fish Studies
on the Susitna River Below Devil Canyon, 1982 . Phase II , Volume 3 Basic Data Report.
ADFG/Su Hydro Aquatic Studies Program . Anchorage , Alaska
Davis , J .C ., and G .A. Davis. 2013 . Water quality in the Lower Little Susitna River : Cumulative
draft report , July 2007 through June 2012 . Final Report for the Alaska Department of
Environmental Conservation. Aquatic Restoration and Research Institute , Talkeetna , AK.
Kirsch , J .M., J .D . Buckwalter, and D .J. Reed . 2014. Fish inventory and anadromous cataloging
in the Susitna River, Matanuska River, and Knik River basins , 2003 and 2011. Alaska
Department ofFish and Game , Fishery Data Series No 14-4 , Anchorage.
Miller, E.M ., J.C . Davis , and G .A. Davis . 2011. Monitoring juvenile salmon and resident fish in
the Matanuska-Susitna Basin . Final Report for the U.S . Fish and Wildlife Service , Mat-Su
Salmon Habitat Partnership . Aquatic Restoration and Research Institute , Talkeetna, AK.
Riverine Model Integration Meeting. 2013. AEA meeting minutes . November 2013 .
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Attachment II. Model Integration
Model integration is the manner in which all of the physical studies interact to assess baselines
and Project impacts on the Susitna River. Within the ISRs, methodologies for model integration
are not transparent and it is not possible to determine if model integration will iden~fy project
impacts with any degree of certainty.
As previously stated by the Service (USFWS 2013), we are concerned that time allotted to
develop methods for model integration is inadequate. Prior to the release of the June 3, 2014,
ISRs, a three-day Riverine Modeling Integration Meeting (RMIM) was held
(November 13-15, 20 13). The goal of this meeting was to provide a forum to review and discuss
various riverine-related modeling and study integration efforts (AEA Instream Flow Study-
Technical Team [ISF-TT] Riverine Modeling Integration Meeting Agenda, 2013). A
collaborative meeting such as this one was a good effort toward developing meaningful model
integration methods and the Service encourages AEA to continue this type of cooperative work.
During the RMIM, 25 and 50-year scenarios for predicting project impacts to the physical river
channel and habitats were proposed. While those timelines are consistent with what is specified
in RSP and may present a manageable timeframe for the modeling work (B. Fullerton, Personal
Communication, November, 2013 ), they may not be sufficient to assess impacts to fish and
wildlife resources in a biologically meaningful way.
: The Service is concerned the modeling capability to answer biological questions is not sensitive
enough to detect biologically meaningful changes to species and habitats likely to be affected by
project operations. We recommend that modelling capabilities be developed that incorporate
biological inputs and deliver outputs that are validated under an appropriate range of operational
scenarios (e.g., base load, ecological flows, load-following, run-of-river}. The temporal scales
(e.g., 25, 50-year) must have biological relevance. For example, 5, 10 and 15 year operational
scenarios should be considered to demonstrate the model's ability to detect generational impacts
to fish populations and habitat persistence (e.g., Susitna River Chinook salmon; five to seven
years).
Data collected for some studies do not provide the information needed for the proposed
integrated modeling efforts. During the RMIM, for example, it was revealed the Water Quality
Modeling study (ISR 5.6) would require data collected on the spatial distribution of groundwater
discharge to surface water bodies. Analytical or numerical groundwater 'flow simulation would
be one (of several) ways to satisfy this input requirement. However, the Groundwater Study
(ISR 7.5) does not explicitly state analytical or numerical groundwater flow simulations would
be undertaken in support of the other physical process models .
. As a follow up to the RMIM, a Proof of C,oncept ( POC) meeting was held April 15-17, 2014.
This meeting was to: 1) confirm successful integration of models and associated metrics in a
single FA (Slough 128); 2) examine the modeling process rather than focus on the actual POC
results; and 3) clarify many questions related to the integration of multiple models. The
discussions of modeling processes at the POC meeting was considered valuable by the Service,
but not fully effective in demonstrating successful mode] development and integration; many
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questions regarding model development and integration wete unanswered. To develop greater
stakeholder confidence in the models, the Service recommends conducting a fonnal model
integration meeting to: I) establish a model development process, 2) develop an understanding
of inputs and outputs, 3) demonstrate conceptual linkages, 4) demonstrate the predictive
capabilities of the models, and 4) conduct sensitivity analyses to better understand model
limitations and reduce uncertainty.
Literature Cited
IFS-TT: Riverine Modeling, Draft Meeting Agenda, November 13-15, 2013,
http://www.susitna-watanahydro.org/wp-contentluploads/2013/10/SuWa IFS-
TT Modeling2013Novl3-15 -Agenda.pdf
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