REFDSS_FundApplLimnolManuscript

An integrated Riverine Environmental Flow Decision
Support System (REFDSS) to evaluate the ecological
effects of alternative flow scenarios on river
ecosystems
Kelly O. Maloney1,
*, Colin B. Talbert2
, Jeffrey C. Cole1
, Heather S. Galbraith1
,
Carrie J. Blakeslee1
, Leanne Hanson2
and Christopher L. Holmquist-Johnson2
With 4 figures and 7 tables
Abstract: In regulated rivers, managers must evaluate competing flow release scenarios that attempt to balance
both human and natural needs. Meeting these natural flow needs is complex due to the myriad of interacting physi-
cal and hydrological factors that affect ecosystems. Tools that synthesize the voluminous scientific data and models
on these factors will facilitate management of these systems. Here, we present the Riverine Environmental Flow
Decision Support System (REFDSS), a tool that enables evaluation of competing flow scenarios and other variables
on instream habitat. We developed a REFDSS for the Upper Delaware River, USA, a system that is regulated by
three headwater reservoirs. This version of the REFDSS has the ability to integrate any set of spatially explicit data
and synthesizes modeled discharge for three competing management scenarios, flow-specific 2-D hydrodynamic
modeled estimates of local hydrologic conditions (e.g., depth, velocity, shear stress, etc.) at a fine pixel-scale (1 m2),
and habitat suitability criteria (HSC) for a variety of taxa. It contains all individual model outputs, computationally
integrates these data, and outputs the amount of potentially available habitat for a suite of species of interest under
each flow release scenario. Users have the flexibility to change the time period of interest and vary the HSC. The
REFDSS was developed to enable side-by-side evaluation of different flow management scenarios and their ef-
fects on potential habitat availability, allowing managers to make informed decisions on the best flow scenarios.
An exercise comparing two alternative flow scenarios to a baseline scenario for several key species is presented.
The Upper Delaware REFDSS was robust to minor changes in HSC (± 10 %). The general REFDSS platform was
developed as a user-friendly Windows desktop application that was designed to include other potential parameters
of interest (e.g., temperature) and for transferability to other riverine systems.
Key words: ecological flow, management tool, hydrodynamic modeling, habitat suitability criteria, instream flow
incremental methodology, fish, mussels, REFDSS v1.1.2.
Fundam. Appl. Limnol. Vol. 186/1–2 (2015), 171–192Article
published online 26 January 2015, published in print February 2015
© 2015 E. Schweizerbart’sche Verlagsbuchhandlung, Stuttgart, Germany www.schweizerbart.de
DOI: 10.1127/fal/2015/0611 1863 - 9135/15/0611 $ 5.50
Introduction
Streamflow is considered a master variable in riverine
systems (Power et al. 1995) and its natural variability
(the natural flow regime, Richter et al. 1996, Poff et
al. 1997) exerts strong controls on associated physi-
cal, chemical, and biological components. Native bio-
diversity is maintained by natural flow regimes and
resident species have developed evolutionary adapta-
tions to these regimes (Bunn Arthington 2002, Lytle
Poff 2004). However, because of human needs for
freshwater, the flow regime of many of the world’s
Authors’ addresses:
1 Northern Appalachian Research Branch, USGS Leetown Science Center, Wellsboro, Pennsylvania, U.S.A. 16901
2 USGS Fort Collins Science Center, Fort Collins, Colorado, U.S.A.
* Author for correspondence; kmaloney@usgs.gov
E
eschweizerbart_XXX

172 Kelly O. Maloney et al.
rivers has been altered by anthropogenic activities
(Nilsson et al. 2005), consequently affecting native
plants and animals both directly and indirectly (Bunn
Arthington 2002). Human water needs are predicted
to increase (Vörösmarty et al. 2010), thus affecting na-
tive biota across larger portions of the globe. To medi-
ate or assuage the effects of altered flows on riverine
biota, much research has been devoted to understand-
ing and assessing the flow requirements of riverine
taxa (i.e., environmental or ecological flows; Tharme
2003, Arthington 2012).
Numerous methods have been developed to assess
environmental flows in rivers (see review by Arthing-
ton 2012). In North America, the instream flow incre-
mental methodology (IFIM) approach is widely used
(Reiser et al. 1989, Bovee et al. 1998, Tharme 2003)
and has been applied for a variety of taxa and river
systems (Bovee et al. 2007, Auble et al. 2009, Bovee
et al. 2008, Waddle Holmquist 2013). The IFIM
framework utilizes a habitat simulation technique that
integrates scientifically developed taxa–specific habi-
tat suitability criteria (HSC), high quality hydrody-
namic modeling efforts that provide flow-specific es-
timates of key habitat variables (e.g., depth, velocity,
and shear stress) for a set of representative reaches,
and hydrological modeling of reservoir releases. HSC
are developed either through literature review, expert
opinion, site-specific data collection, or experimen-
tation. There are numerous hydrodynamic modeling
options (e.g., River2D, Steffler Blackburn 2002;
MIKE2 from DHI of Denmark; HEC-ResSim, US
Army Corps of Engineers 2007) all of which require
similar types of base data: a bathymetric map of the
river section, water elevations for calibration, and
discharge amounts. In the IFIM framework, each
hydrodynamic modeled pixel-scale habitat variable
is linked to its associated HSC and is scored as to
whether a particular pixel can be considered potential
available habitat. Other variables potentially influ-
encing available habitat, such as temperature (Bovee
et al. 2007), are also frequently linked to HSC. Each
pixel is then scored as available habitat or not avail-
able habitat from these variable scores, for example
as the product of all individual scores. This process
is repeated for each flow of interest. As a final output
of an IFIM habitat analysis, potential available habitat
is totaled for a particular reach. Usually, the amount
of habitat is compared across several alternative flow
release scenarios to enable decision makers to com-
pare habitat availability across various flow scenarios.
Due to the number of models and voluminous amount
of data, the IFIM framework can be facilitated by
incorporating the entire process into a user-friendly,
transparent environmental decision support system
(EDSS).
Environmental decision support systems are com-
puter-based information systems that manipulate, syn-
thesize, transform and present data and information
to support decision making (Díez McIntosh 2009,
Volk et al. 2010). EDSSs have been used to help man-
agers and stakeholders decide among competing op-
tions that involve difficult, complex, and often costly
scenarios (Rizzoli Young 1997, Matthies et al. 2007,
McIntosh et al. 2011). Over the past decade, use of
EDSSs have increased and aided in management of
a variety of riverine taxa including mussels, fish, and
vegetation (Bovee et al. 2007, Schlüter Rüger 2007,
de Kok et al. 2009, Volk et al. 2010). A general EDSS
platform that can be transferable to different areas and
users would be an asset to managers. Such a flexible
platform could reduce costs associated with develop-
ment of EDSSs, reduce timeframes to completion, and
standardize efforts and results. An EDSS that offers
a user-friendly interface and allows users to test the
sensitivity of each EDSS component would add fur-
ther benefit. The IFIM framework, in its basic form,
is an EDSS that enables managers to compare habitat
availability among several operating scenarios. How-
ever, standard output from an IFIM analysis is often
not spatially explicit, overly transparent, user-friendly,
or flexible. Extending the applicability of the IFIM ap-
proach more formally into an EDSS framework would
greatly enhance its functionality.
Here, we developed a user-friendly, transparent,
transferable EDSS platform, called the Riverine Envi-
ronmental Flow Decision Support System (REFDSS)
based on the IFIM framework data needs and the
methodology of Bovee et al. (2007). To complete the
REFDSS, results of each hydrodynamic, hydrologic,
and HSC model were integrated into a graphical user
interface (GUI) that was designed to compare avail-
able habitat among each flow release scenario. This
GUI extends the IFIM framework by allowing the user
to easily modify HSC for sensitivity analyses, upload
additional hydrological models to compare future
flow scenarios of interest, spatially visualize avail-
able habitat through a geographic information system
(GIS) interface, and analyze the results in a variety
of ways and scales. The main objective of this study
was to showcase the various options and tools within
the REFDSS, demonstrating its capacity to synthesize
output and data from several models and enable man-
agers to evaluate competing flow release scenarios on
habitat availability. Secondarily we tested the sensitiv-
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173An integrated Riverine Environmental Flow Decision Support System (REFDSS)
ity of the REFDSS to alterations in the HSC to deter-
mine how robust it is to HSC errors.
Methods
Study area – The Delaware River is located in the mid-Atlantic
region of the USA, flows southward separating the states of
New York, Pennsylvania, New Jersey and Delaware, and drains
a total land area of 33,016 km2
(Fig. 1). It provides water for
nearly 17 million people and to satisfy these needs, three dams
were constructed in the upper reaches in the mid-1900s (Can-
nonsville, Downsville, Neversink Reservoir). We focused our
study on the section of the Delaware River above the USGS
01438500 Montague, NJ, stream gaging station (9,013 km2
drainage), hereafter referred to as the Upper Delaware River
(UPDE). We concentrated our efforts on this section for sev-
eral reasons. First, this portion of the river is currently managed
such that a flow target of 49.6 m3
s–1
is maintained at the stream
gage. Second, this section of the river supports a world class
trout fishery, which is managed with reservoir releases. Third,
Bovee et al. (2007) compiled data on this section of river and in-
corporated it into a preliminary EDSS. This original EDSS was
based on the IFIM framework and evaluated available habitat
at 11 reaches in the UPDE (Fig. 1). Reaches ranged in length
from 0.9 km (Neversink 0 reach, NVR0) to 4.3 km (Main Stem
1 reach, DEL1) and under median flow conditions had a range
in wetted area from 24,661 m2 (NVR0) to 538,765 m2 (DEL1)
with wetted widths that ranged from 29.7 m (NVR0) to 139.8 m
(Main Stem Reach 3, DEL3; Table 1). Bathymetric data, wa-
ter surface elevation, hydrodynamic modeling, HSC, and dis-
charge estimates were all collected in the early 2000s and these
data were synthesized in Microsoft Excel (Bovee et al. 2007).
This EDSS has been frequently used by managers and stake-
holders to evaluate competing flow release scenarios. However,
through workshops and stakeholder meetings, users have com-
piled a list of modifications to this EDSS to enhance its usability
and application. These suggested modifications included: 1) de-
veloping an improved, user-friendly EDSS platform to increase
usability among regional resource managers; 2) extending the
meteorological database to conform to the hydrological period
of record (1929 – 2000, as opposed to 1990 – 2000); 3) automat-
ing data import from the hydrological model to the EDSS; 4)
Fig. 1. Map showing study area with study reaches (●), dam locations (), and key cities (○). Codes for reach locations can be
found in Table 1 and Appendix C. Inset shows Delaware River basin (light gray) in relation to the mid-Atlantic region of the U.S.A.
eschweizerbart_XXX

testing model sensitivity to current HSC; 5) updating existing
HSC and including additional species of interest; 6) developing
and/or testing a river temperature model; and 7) extending the
aerial coverage of the EDSS (Coon et al. 2012). The REFDSS
presented here (v1.1.2) addresses improvements 1– 5; we also
modified the original EDSS by including additional data col-
lected in 2010 (Maloney et al. 2012).
Flow within the UPDE is managed by operation of the three
dams through a 1954 Supreme Court Decree where decree par-
ties (US states of Delaware, New Jersey, New York, and Penn-
sylvania and New York City) work with the Delaware River
Basin Commission (DRBC) to set management goals. Release
programs have been revised over the years, but since the 1970s
flow management has been aimed at improving ecological
conditions below these dams, originally with an emphasis on a
cold-water fishery. Here, we focus on three of the release pro-
grams: Revision 1 (Rev1), Revision 7 (Rev7) and the Flexible
Flow Management Plan (FFMP). In 1977 an experimental pro-
gram was established to mitigate thermal issues downstream of
reservoirs (e.g. when daily average temperatures reached 72 °F
or 22.2 °C; US Geological Survey 2006). To do so, thermal re-
lease “banks” were used to release a set volume of water from
available reservoir storage. In 1983 this initial program was re-
vised to incorporate a basin-wide drought operating plan and
was deemed Rev1. Over the following years several modifica-
tions were made to Rev1, which ultimately led to Rev7 in 2004.
Rev7 incorporated drought watch and drought warning diver-
sions; a 20,000 cfs-days (~566 cms-days) Habitat Protection
Bank for habitat and thermal protection of the tailwaters below
each reservoir; and flow targets for the West Branch Delaware
River at Hale Eddy, NY, the East Branch Delaware River at
Harvard, NY, and the Neversink River at Bridgeville, NY (US
Geological Survey 2006). The FFMP was originally adopted
on October 1, 2007 and was designed to provide a more natural
flow regime with an enhanced adaptive framework from the
previous operating plans (Delaware Decree Parties 2013). It ad-
dressed competing needs and uses including safe and reliable
water supplies, drought management, flood mitigation, protec-
tion of a cold water fishery, instream habitat needs in the main-
stem river, estuary and bay, and salinity repulsion. The FFMP
replaced the storage bank concept of the earlier operating pro-
grams and instead based its operating program on reservoir
storage levels; the program has no dedicated thermal release
bank and no flow targets for habitat protection at the tailwaters.
Hydrological model
Modeled flow release data were provided by the DRBC using
their Operational Analysis and Simulation System (OASIS)
model, a reservoir operations and flow routing model. The tem-
poral resolution of OASIS is a one day time step. Daily flow
estimates under each of three release programs, Rev1, Rev7, and
FFMP, were uploaded for the time period of 1 October 1928 – 30
September 2000.
Habitat variable data
Modeled habitat variable data were taken from previous stud-
ies. First, we uploaded depth and velocity data from Bovee et al.
(2007), the data that were modeled for the original EDSS. For
this study, bathymetric and water surface elevation (WSE) data
were collected in 2005 at 11 reaches within 4 branches (East
Branch of the Delaware River, West Branch of the Delaware
Table1.Descriptivestatisticsfor11reachesusedinthestudyatalow,median,andhighflow(flowlevelstakenfromBoveeetal.2007).Flowspecificwettedareasweretheareaof
2Dhydrodynamicmodeledpixelswheredepthwasgreaterthan0.Wettedwidthswerecalculatedastheaveragelengthofwettedareaoncrossstreamtransectsplacedperpendicularly
alongeachreachevery100 mlongitudinally.
ReachReachlength
(km)
Lowflow(1 %)Medianflow(50 %)Highflow(99 %)
Flow
(m3
s–1
)
Wettedarea
(m2
)
Wetted
width(m)
Flow
(m3
s–1
)
Wettedarea
(m2
)
Wetted
width(m)
Flow
(m3
s–1
)
Wettedarea
(m2
)
Wetted
width(m)
WestBranchWB02.6 0.4109533 39.8 5.4176167 66.5118.0234868 89.3
WB13.2 1.3196871 60.210.0250287 80.0151.0337579106.9
EastBranchEB02.5 0.7 78700 33.5 1.6 87848 38.2 70.0186795 76.0
EB13.6 1.1152277 43.3 5.6174301 48.5110.5343946 94.7
EB23.6 2.8194847 53.819.8244539 68.7600.3448960125.1
MainStemDEL14.3 9.7494529118.327.0538765128.1360.0877949206.9
DEL23.113.2258602 79.235.2296193 90.7404.0430933133.0
DEL32.914.3374366127.130.0410895139.8490.0548805180.3
NeversinkNVR00.9 0.4 20669 23.9 2.8 24661 29.7 20.2 33811 38.5
NVR12.1 0.8 56505 30.7 3.0 62029 33.1 80.0 98507 54.9
NVR21.2 2.0 42682 34.4 5.5 48766 39.9 81.0 66643 56.3
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River, Neversink River, and mainstem Delaware River) and
used to model each depth and velocity at 15 flow levels (see
Bovee et al. 2007, Fig. 1). We also uploaded modeled habitat
data (depth, velocity, Froude number, shear stress and shear
velocity) from Maloney et al. (2012) who collected bathymetry
and WSE data in the fall of 2010 at the same three reaches in
the mainstem Delaware River branch sampled by Bovee et al.
(2007) (DEL1, DEL2, and DEL3, Fig. 1). Bathymetric data for
both studies were collected using a combination of real-time
kinematic survey-grade GPS equipment for wadeable areas
with adequate GPS coverage; an optical 3-s total station for
locations without adequate GPS coverage; and echosounding
with sonar and Acoustic Doppler Current Profiler equipment in
conjunction with real-time kinematic survey-grade GPS equip-
ment for deep, unwadeable sections. For the 2010 surveys we
used airborne Light Detection and Ranging (LiDAR) to pro-
vide elevation data for areas on banks that were inaccessible
or not sampled effectively with site surveys. Bathymetric data
were taken at a finer spatial scale during the 2010 surveys than
during the 2005 surveys to enable finer scaled accuracy in
habitat variable modeling. Habitat variables were modeled at
approximately 35 reach-specific flow levels for the 2010 data
(see Maloney et al. 2012). Both studies modeled habitat using
River2D, which is a two-dimensional, depth averaged, finite-
element hydrodynamic model (Steffler Blackburn 2002)
that has frequently been used to model hydrological attributes
and fish habitat (Bovee et al. 2007). Data inputs required for
River2D include the bathymetric file, WSE, and discharge at
the input and output boundaries of the reach. Input and output
discharges were either taken directly from rating curves devel-
oped for nearby USGS gages, or estimated via distance-based
averaging of nearby gages (see Bovee et al. 2007, Maloney et
al. 2012). Depth and velocity habitat variables were modeled
for both the 2005 and 2010 periods; Froude number, shear ve-
locity, and shear stress were also modeled for 2010. All habi-
tat variables (depth, velocity, Froude number, shear stress and
shear velocity) were calculated for each reach at a 1 m2 pixel
resolution using the River2D hydrodynamic modeling soft-
ware.
Habitat suitability criteria
Habitat suitability criteria for fish were taken from Bovee et al.
(2007; Table 2) and were developed using the Delphi method
(Zuboy 1981) for the following species: brown trout, Salmo
trutta Linnaeus, 1758 (adult, juvenile, spawning and incuba-
tion); rainbow trout, Oncorhynchus mykiss (Walbaum, 1792)
(adult, juvenile); American shad, Alosa sapidissima (Wilson,
1811) (spawning and juvenile); shallow-slow guilds (includ-
ing bridle shiner, Notropis bifrenatus (Cope, 1867); bluespot-
ted sunfish, Enneacanthus gloriosus (Holbrook, 1855); eastern
mudminnow, Umbra pygmaea (DeKay, 1842); and cutlip min-
now, Exoglossum maxillingua (Lesueur, 1817)); and shallow-
fast guilds (including margined madtom, Notorus insignis
(Richardson, 1836); juvenile fallfish, Semotilus corporalis
(Mitchill, 1817); and American eel, Anguilla rostrata (Lesueur,
1817)). For the dwarf wedgemussel (Alasmidonta heterodon),
HSC were taken from Maloney et al. (2012) where HSC were
developed using both hydrodynamic modeling of field reaches
with known populations and literature surveys (Table 2). These
species were included because they were considered species of
interest by stakeholders. For fish and fish guild metrics, HSC
were available for depth and velocity, whereas HSC for all five
habitat variables were available for the dwarf wedgemussel.
Graphical Users Interface and Results
We developed the GUI application using VB.Net
along with several open-source libraries to handle
the GIS (MapWinGIS), database (SQLite), charting
Table 2. Habitat suitability criteria (HSC) used in the REFDSS and those used for sensitivity analysis. 1
The HSC for fish species
and guilds were taken from Bovee et al. 2007 and for dwarf wedgemussel were taken from Maloney et al. 2012. 2
Includes fry for
both trout and shad species and also a HSC for distance from shore that Bovee et al. 2007 set at 5.0 m, which we adopted here; for
the sensitivity analysis this was set at 5.5 m. 3
HSC also included for Froude number (range 0 – 0.44, 0 – 0.48 for sensitivity analysis),
shear velocity (0 – 0.22, 0 – 0.242 for sensitivity analysis), and shear stress (0 – 47.3, 0 – 52.0 for sensitivity analysis). a
100 m set to
represent no effective upper limit.
Target Organism Life Stage Habitat Suitability Criteria1 Habitat Suitability Criteria –
Sensitivity Analysis
Depth range (m) Velocity range
(m s–1)
Depth range (m) Velocity range
(m s–1)
Brown trout adult 0.3 –100a
0.0 –1.0 0.27–100 0 –1.1
Brown trout juvenile 0.2 – 0.8 0.0 – 0.7 0.18 – 0.88 0 – 0.77
Brown trout spawning 0.2 – 0.6 0.3 – 0.81 0.18 – 0.66 0.27– 0.891
Brown trout incubation 0.2 –1.0 0.15 –1.2 0.18 –1.1 0.135 –1.32
Rainbow trout adult 0.3 –100a 0.0 –1.2 0.27–100 0 –1.32
Rainbow trout juvenile 0.2 –1.0 0.0 – 0.8 0.18 –1.1 0 – 0.88
American shad spawning 0.3 – 3.0 0.2 – 0.7 0.27– 3.3 0.18 – 0.77
American shad juvenile 0.25 –1.6 0.0 – 0.6 0.225 –1.76 0 – 0.66
Shallow-fast guild na 0.05 – 0.3 0.3 –1.2 0.045 – 0.33 0.27–1.32
Shallow-slow guild2
na 0.05 – 0.3 0.0 – 0.3 0.045 – 0.33 0 – 0.33
Dwarf wedgemussel3 na 0.06 –100a 0.02 – 3.3 0.054 –100 0.018 – 3.63
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(Microsoft Charting), and other technical aspects of
the application (DotNetZip) (see Appendix A). The
REFDSS and all base data for the UPDE can be down-
loaded free of charge at www.sciencebase.gov/Dela-
wareREFDSS. The REFDSS is a simulation tool that
in its current version uses habitat data (e.g., depth, ve-
locity, shear stress, shear velocity and Froude number)
from a hydrodynamic model and developed HSC to
determine if a pixel at a particular flow was suitable.
Total habitat for each reach is the total area of calcu-
lated pixels weighted by their habitat suitability score
(weighted useable area, Bovee et al. 1998). Hydrody-
namic models are developed for a discrete, subset of
representative flows.The REFDSS links the discharges
from a hydrologic model (at any temporal resolution
– e.g., daily), to the closest hydrodynamic modelled
flow estimate of available habitat. The REFDSS then
repeats this process for the next date and does so it-
eratively for the selected period of record. At a yearly
and decadal resolution, the REFDSS averages the
daily estimates of available habitat. When evaluating
the amount of habitat at the branch or basin scale, the
REFDSS scales up the weighted habitat from the site
scale, as is traditionally done in an IFIM framework.
Reaches are selected that are representative of a por-
tion of the entire branch and the hydrodynamic models
are run at the reach scale. The proportional area of the
reach relative to the entire basin (or branch) is then
used as a scaling factor to estimate available habitat at
the larger scale. For example, assume a 100 km branch
is comprised of two representative reaches (site A and
site B), both 10 km long. If site A has 50 ha of suit-
able habitat and site B had 60 ha of habitat then they
have 5 ha km–1
and 6 ha km–1
respectively. If site A is
representative of the first 70 km of the branch and site
B of the last 30 km, our final habitat would be 5 ha
km–1 × 70 km +6 ha km–1 × 30 km = 530 ha of habitat.
We also designed the GUI to give users the flex-
ibility to adjust the HSC (Fig. 2, top left panel), to visu-
alize the spatial and temporal changes to each habitat
variable and available habitat throughout the study
reaches (Fig. 2, top center and right panels), to facili-
tate the input of future flow release scenarios, and to
evaluate habitat availability under alternative flow
release scenarios. Allowing adjustments to HSC was
included so users can easily incorporate updated HSC
once they become available as well as to allow users
to test the sensitivity of the REFDSS to the HSC. Us-
ers change the HSC either by simply adjusting the line
on the graph or manually entering values in the lower
table. The REFDSS enables the user to enter the HSC
for each habitat variable (depth, velocity, etc.) as sim-
Fig. 2. Screen capture of the Riverine Environmental Flow Decision Support System (REFDSS) for the Upper Delaware River
system showing habitat suitability criteria interface (brown trout, spawning life stage, upper left panel), spatial representation of
habitat (velocity – upper middle panel, depth – lower middle panel) and composite habitat availability (upper right panel) at site
DEL1for Rev1flow release at1236 ft3 s–1 [35.0 m3 s–1], and hydrograph from1January1997to1July 2000 for site DEL1under Rev1
flow release program (lower panel). Vertical red line in hydrograph highlights flow shown in above habitat maps.
eschweizerbart_XXX

ple yes/no, or as curves. Here, for the UPDE, we used
the simple yes/no option assigning a pixel a score of 0
if the modeled habitat variable is not within the suitable
criteria range and a1if it is contained within this range.
We used this flexibility to test the sensitivity of the
REFDSS to HSC by adding10 % of the upper criteria to
the upper limits and subtracting 10 % of the lower cri-
teria from the lower limits of the HSC, except in cases
where the lower limit equaled 0 or upper limit equaled
100; in such cases they were kept constant (Table 2).
Species and life histories are easily changed using
a pull-down menu. Potential habitat suitability is cal-
culated using pre-defined equations; here we simply
multiply the pixel score for depth (0 or 1) by the pixel
score for velocity (0 or 1), but this weighting is easily
modified by the user. In this case it will be the total area
of pixels that had HSC values of 1 in all habitat vari-
ables. Calculations were based on the water year for
this region (1 October – 30 September). Moreover, for
the UPDE REFDSS, potential habitat was only calcu-
lated for each species/life stage during a hydroperiod
of importance (1 October – 30 November for spawn-
ing brown trout, 1December –15 April for incubat-
ing brown trout, 16 April – 30 June for emergence of
young of year fish (juveniles) brown and rainbow trout
and spawning American shad, and 1 July – 30 Septem-
ber for summer growing seasons (adults) for brown
and rainbow trout and juvenile American shad; see
Bovee et al. 2007). Habitat was calculated over the
entire water year for shallow-fast guild, shallow-slow
guild, and the dwarf wedgemussel. We also followed
Bovee et al. (2007) and used the average of the lower
25 % of habitat values in the time series to account for
populations likely being limited by the most restrictive
periods and to lessen the influence of large values in
calculations. For example, if the time series contained
100 days of estimated habitat, we averaged the lower
25 of these habitat values. Users have the ability to
change this calculation within the REFDSS. Spatial
representation of each habitat variable, and the calcu-
lated habitat suitability (Fig. 2, top middle and right
panels), and a time-series of the hydrological model
(Fig. 2, bottom panel) also are provided. Users can ad-
just the flow level in the upper panels by clicking on a
point in the hydrograph or by selecting a specific flow
from a dropdown menu accessed by right clicking on
the map. Each habitat variable also can be visualized
for multiple reaches, release scenarios, or flow levels
simultaneously; Figure 3 shows an example for depth
at the lowest hydrodynamic modeled flow for each
reach in the East Branch.
The calculated potential available habitat outputs
can be displayed in a number of formats including
individual maps, summaries of daily, yearly, or total
area, and tabular summaries of the output. Here we
used potentially available habitat from Rev1 as a base-
line amount to compare changes in available habitat
under the Rev7 and FFMP scenarios. If this habitat
increased by 10 % or more it is highlighted as hashed
green in resultant figures; if available habitat decreased
by 10 % or more results are highlighted in hashed red.
These output views are designed to allow easy access
to the specific data of interest. For example, estimation
of available habitat can be summarized for the entire
basin, (Appendix B), for individual branches within
the basin (Fig. 4), or by reaches within a branch (Ap-
Fig. 3. Screen capture of the Riverine Environmental Flow Decision Support System (REFDSS) for the Upper Delaware River
system showing study location with three focal reaches for the East Branch of the Delaware River (EB0 left panel, EB1 middle
panel, EB2 right panel) and spatial representation of the two-dimensional hydrodynamic modeled depth habitat under the Rev1
flow release program for the three study sites at the lowest modeled flow (EB0 –7 ft3 s–1 [0.2 m3 s–1], EB1– 38 ft3 s–1 [1.1 m3 s–1],
EB2 – 99 ft3 s–1 [2.8 m3 s–1]).
eschweizerbart_XXX

Fig. 4. Screen capture of the Riverine Environmental Flow Decision Support System (REFDSS) for the Upper Delaware River sys-
tem showing total amount of available habitat (temporal range 1 October 1928 to 30 September 2000) for adult brown trout under
the three alternative flow release scenarios (Rev1, Rev7, FFMP). The four branches are indicated by color in each chart, Delaware
main stem in blue, Delaware West Branch in green, Delaware East Branch in pink, and the Neversink in orange. Bars highlighted in
hashed green indicate a habitat increase of at least 10 % relative to the baseline scenario of Rev1. Available habitat values presented
are the average of the lower 25 % of value in the time series for a hydroperiod of importance (see Methods).
Fig. 5. Screen capture of the Riverine Environmental Flow Decision Support System (REFDSS) for the Upper Delaware River sys-
tem comparing the total amount of available habitat for adult brown trout for three alternative flow release scenarios (Rev1, Rev7,
FFMP) during the 1980s (left panel) and 1990s (right panel) for the West Branch. Hashed red highlighted (Rev7, 1980s) section
indicates a loss of habitat of 10 % or more from the baseline provided by Rev1. Hashed green highlight (FFMP, 1990s) indicates a
gain of 10 % or more habitat from the baseline provided by Rev1. Available habitat values presented are the average of the lower
25 % of value in the time series for a hydroperiod of importance (see Methods).
eschweizerbart_XXX

pendix B). In this example, available habitat for brown
trout adults was highest in the Delaware main stem
(Delaware); the Rev7 scenario increased predicted po-
tential adult brown trout habitat by 10 % or more at the
Neversink branch, and the FFMP increased available
habitat for the West Branch and Neversink (Fig. 4).
Available habitat can also be calculated for a specific
time period comparison. Here we compared potential
available habitat for brown trout adults in the 1980s
versus the 1990s for the West Branch (Fig. 5). For the
entire West Branch, during the 1980s the FFMP had
similar predicted potential adult brown trout habitat to
Rev1, while during the 1990s FFMP had 11.4 % more
available habitat. Rev7had15.5 % less predicted avail-
able habitat in the 1980s than Rev1 and similar levels
of predicted habitat for the 1990s (Fig. 5). Available
habitat can also be examined by reach or on a daily
time step (Appendix B).
The underlying data from any of the chart outputs
can also be displayed in tabular form. We used this
feature to compare potential available habitat between
Rev1 versus Rev7 and Rev1 versus FFMP, defining a
difference of at least ± 10 % as a measurable change.
Here we present detailed results for all species and
life stages for three individual reaches (EB0, EB1, and
EB2) within the East Branch and for the entire East
Branch using the 2005 data (all 3 reaches combined,
Table 3). For the entire East Branch, Rev7 increased
available habitat for 6 species/life stage combinations
(brown trout spawning, incubating and adult; adult
rainbow trout; American shad spawning, shallow-fast
guild) and FFMP increased available habitat for 4 spe-
cies/life stage combinations (brown trout spawning
and incubating; American shad spawning; shallow-
fast guild, Table 3). At the reach scale, results varied.
At reach EB0, Rev7 increased brown trout incubating
and shallow-fast guild available habitat, but decreased
habitat for brown trout spawning, juvenile rainbow
trout and shall-slow guilds. At reach EB0, the FFMP
increased potentially available habitat for all tested
species except the shallow-slow guild where habitat
decreased (Table 3). At reach EB1, Rev7 increased
available habitat for spawning, incubating, and adult
brown trout and adult rainbow trout; FFMP increased
potential habitat for the same species/life stage com-
binations that increased under Rev7, but showed de-
creased habitat for shallow-fast guild. At reach EB2,
Rev7 increased brown trout spawning and adult
available habitat as well as habitat for rainbow trout
adults and American shad spawning; FFMP showed
increased potential habitat only for American shad
spawning (Table 3).
Estimated potential available habitat for all scales
(basin, branch, and reach) is located in Appendix
C. Briefly, across all scales, potentially available habi-
tat increased under both Rev7 and FFMP more often
than it decreased (50 versus 4 species/life stage com-
binations for Rev7; 62 versus 4 for the FFMP, Appen-
dix C). For the entire basin, potential available habi-
tat under both the Rev7 and FFMP release scenarios
increased for 3 of the 10 species/life stage combina-
tions. Over the entire main stem and in each main stem
reach, both Rev7 and FFMP showed no increase in po-
tentially available habitat except for incubating brown
trout when using the 2010 data and FFMP (at DEL1).
Under the FFMP, the entire West Branch, and the WB0
and WB1 reaches showed increased potential habitat
for all species and life stages except for shallow-slow
guild species in the entire West Branch and at reach
WB1. At the reach scale, FFMP for reaches WB0 and
WB1 increased potential available habitat for 15 spe-
cies/life stage combinations, whereas Rev7 showed
increases in habitat for only 8 species/life stage com-
binations. The Neversink branch showed increased
available habitat under both the Rev7 and FFMP re-
lease scenarios (19 and 20 species/life stage combina-
tions, respectively, Appendix C).
Sensitivity analyses showed that, although total
weighted potential available habitat estimates changed
with the adjusted HSC, the overall patterns in gained
or lost habitat showed only a few changes for the East
Branch (Table 3). Rev7 showed the same patterns
in altered available habitat compared to the original
HSC estimates for all scales except at the entire East
Branch scale where no increase in adult brown or
American shad spawning habitat was observed; for
reach EB0 where the analyses now indicated a loss of
adult brown trout and adult rainbow trout habitat and
no loss of habitat for the shallow-fast guild; and at
reach EB2 where analyses now showed no increase in
habitat for American shad spawning (Table 3). During
the sensitivity analysis, the FFMP scenario showed
the same gains in available habitat for the species and
life stages as with the original HSC for the entire East
Branch. At reach EB0, sensitivity analyses showed
FFMP had similar increases in potential habitat for the
same species and life stages compared to the origi-
nal HSC, except during this analysis no loss in habi-
tat was detected for the shallow-slow guild. Sensitiv-
ity analysis with FFMP at the EB1 and EB2 reaches
showed the same trends observed using the original
HSCs (Table 3). Results from the sensitivity analysis
for all other scales and species/life stages are located
in Appendix C.
eschweizerbart_XXX

Table3.Amountofweightedaveragepotentialavailablehabitat(hectares)estimatedfromtheREFDSSusingthe2005bathymetrydatafortheEastBranchoftheDelawareRiver.
EastBranchscaleofanalysisistheweightedaverageamountofpotentialhabitatacrossthreeindividualreaches(EB0,EB1,EB2);scalesincluding“reach”indicateamountofpotential
habitatwithineachoftheindividualreaches.Valueshighlightedinlightgrayandboldfaceindicatepotentialhabitatincreased10 %ormoreoverhabitatestimatedundertheRev1flow
releasescenario.Valueshighlightedindarkgrayanditalicizedindicatepotentialhabitatdecreased10 %ormorefromhabitatestimatedunderflowreleasescenarioRev1.Available
habitatvaluespresentedaretheaverageofthelower25 %ofvalueinthetimeseriesforahydroperiodofimportance(seemethods).WeightedaveragevaluesfortheentireUPDEare
locatedinAppendixC.
OriginalHabitatSuitabilityCriteria SensitivityHabitatSuitabilityCriteria
FlowScenario%Changevs.
Rev1
FlowScenario%Changevs.
Rev1
ScaleofAnalysisSpecies/LifeStagesRev1Rev7FFMP Rev7FFMP Rev1Rev7FFMP Rev7FFMP
EastBranchBrowntroutspawning 14.9 20.7 17.13915 22.2 30.7 25.63816
Browntroutincubation 64.7 72.6 79.21222 81.3 91.1 98.91222
Browntroutjuvenile 80.2 80.0 87.309 98.0 97.5106.2–18
Browntroutadult147.3161.4160.1109158.2173.0173.199
Rainbowtroutjuvenile111.2109.8119.4–17132.8131.6141.8–17
Rainbowtroutadult148.1162.6161.0109158.9174.2173.9109
Americanshadspawning 41.0 45.1 47.41016 52.6 57.1 59.6813
Americanshadjuvenile 84.6 91.1 87.784 91.7 98.9 95.784
Shallow-fastguild 4.3 4.8 5.21322 6.4 7.2 7.71220
Shallow-slowguild 27.0 26.1 26.0– 3– 4 30.9 30.1 30.0– 3– 3
EastBranchreach0Browntroutspawning 0.9 0.7 2.4– 23179 1.4 1.2 3.8–13176
(EB0)Browntroutincubation 0.1 1.8 7.5257411214 0.1 2.7 9.518376644
Browntroutjuvenile 16.0 15.3 20.4– 527 19.1 18.0 23.8– 625
Browntroutadult 19.5 17.8 22.4– 915 21.9 19.7 25.8–1018
Rainbowtroutjuvenile 19.3 17.2 23.3–1121 22.2 19.9 26.5–1019
Rainbowtroutadult 19.5 17.8 22.4– 915 21.9 19.7 25.8–1018
Shallow-fastguild 0.7 1.1 1.965190 0.9 1.5 2.661182
Shallow-slowguild 9.6 8.6 8.6–11–11 10.9 10.0 10.0– 8– 8
EastBranchreach1Browntroutspawning 4.0 6.9 4.67315 5.4 9.6 6.37715
Browntroutjuvenile 30.2 30.5 31.715 35.9 36.1 37.705
Browntroutadult 43.4 49.7 47.71410 46.4 52.6 51.01310
Rainbowtroutjuvenile 39.6 39.8 41.615 45.0 45.4 47.015
Rainbowtroutadult 43.4 49.8 47.81510 46.4 52.7 51.11410
Shallow-fastguild 1.5 1.6 1.26–15 2.3 2.4 1.95–14
Shallow-slowguild 8.1 8.1 8.010 9.3 9.4 9.210
eschweizerbart_XXX

Discussion
Rivers are experiencing increased demand from human
needs that competes with the ecological flow needs of
resident species. To sustain these competing needs,
managers require decision tools that simultaneously
evaluate alternative flow scenarios and their effects on
instream habitat. The REFDSS presented here, while
based on the IFIM framework, was also developed
to be spatially explicit, user-friendly, and flexible, al-
lowing users to easily modify input information as it
becomes available. Here, we tested its applicability in
the UPDE by comparing the effects of three alterna-
tive flow release scenarios on habitat availability for
several key species. Results indicated that of the three
flow scenarios examined, the FFMP had the highest
amount of potentially available habitat for most spe-
cies and life stages (see Appendix C). Our sensitivity
analysis indicated that the REFDSS was generally in-
sensitive to minor changes in the HSC, suggesting that
HSC modifications of ≤ 10 % will not affect inferences
on the relative performance of the flow release sce-
narios.
The FFMP was designed to provide a more natural
flow regime to the Delaware River. Under this sce-
nario, potential available habitat increased for many
species and life stages when compared to release sce-
nario Rev1. Similarly, Rev7 provided increased habi-
tat over Rev1; however there were fewer increases
in habitat for several species/life stage combinations
compared to FFMP, and there were some habitat losses
at reach EB0 under Rev7. For some reaches the com-
peting release scenarios provided drastically different
estimates of potentially available habitat. For example,
under the FFMP, incubating brown trout habitat in-
creased from 0.1 to 7.5 ha at reach EB0. If the available
habitat estimated from the REFDSS under the FFMP
is a reflection of actual habitat, then there is a clear
advantage of using this flow scenario for this species
and life stage. However, caution is warranted when in-
terpreting the output because results of the REFDSS
are modeled estimates of potentially available habitat;
field validation is necessary to determine how well the
REFDSS output reflects actual available habitat. In ad-
dition, the current REFDSS is based solely on velocity
and depth preference, ignoring other important envi-
ronmental (e.g., substrate, temperature, water quality)
and ecological (e.g., species interactions) variables
that constrain habitat use (Boavida et al. 2013, Wer-
ner et al. 1983). Incorporating HSC and the necessary
modeled base layers for these additional factors would
undoubtedly improve the model’s habitat predictabil-
EastBranchreach2Browntroutspawning 10.1 13.2 10.2311 15.4 19.8 15.6291
Browntroutjuvenile 33.9 34.3 35.214 43.0 43.4 44.714
Browntroutadult 84.4 93.9 90.0117 89.9100.7 96.3127
Rainbowtroutjuvenile 52.3 52.8 54.514 65.7 66.3 68.314
Rainbowtroutadult 85.1 95.1 90.8127 90.6101.8 97.1127
Americanshadspawning 41.0 45.1 47.41016 52.6 57.1 59.6813
Americanshadjuvenile 84.6 91.1 87.784 91.7 98.9 95.784
Shallow-fastguild 2.1 2.2 2.02– 4 3.2 3.3 3.12– 3
Shallow-slowguild 9.4 9.4 9.4 00 10.7 10.7 10.7 00
Numberspecies/lifestageswith 10 %increase:16161316
Numberspecies/lifestageswith 10 %decrease:3241
eschweizerbart_XXX

ity. Nevertheless, habitat estimates from the current
REFDSS provided a valuable comparison of potential
available habitat based on reservoir management prac-
tices, which directly affect depth and flow velocity.
The REFDSS synthesizes output data from multi-
ple models and therefore is sensitive to the limitations
from each individual model. For example, measure-
ment errors (e.g., operator and location errors) and
modeling errors (e.g., spatial averaging and model
formulation errors) from hydrodynamic models could
affect habitat calculations in the REFDSS (Waddle
2010, Boavida et al. 2013). Additionally, HSC and
the resulting available habitat calculations have been
simplified into a binomial distinction between “suit-
able” and “unsuitable”; more complex HSC should be
evaluated in the future. The HSC assessed here for fish
are based on expert opinion and should be validated,
either through literature support or field studies. Pro-
vided the current HSC are meaningful, our sensitivity
analysis indicates that the inferences from the UPDE
are robust to slight alterations to the HSC. While this
is true, the effects on available habitat to each individ-
ual species and life stages varied under different flow
release scenarios; managers and stakeholders may be
forced to weigh losses in habitat for an individual spe-
cies to maximize gains in overall habitat.
A valid criticism of EDSS development is lack of
utility of these tools to users and stakeholders. McI-
ntosh et al. (2011) suggested involving EDSS users
throughout the development process. During devel-
opment of the REFDSS, we involved managers and
stakeholders through a series of workshops, meetings,
and webinars. We addressed several of the most im-
portant user improvement suggestions (see ‘Meth-
ods’). The Bovee et al. (2007) EDSS was updated to a
more user-friendly open source platform. We also ex-
tended the time coverage to include1929 – 2000, added
the ability to easily upload hydrological model output
to the platform, and tested the model’s sensitivity to
the current HSC. Regarding the 5th
suggested im-
provement (updating HSC), we uploaded finer scaled
bathymetric data for 3 of the 11 sites and estimated po-
tentially available habitat for the US Federally endan-
gered dwarf wedgemussel using criteria from Maloney
et al. (2012). Future research will focus on developing
a persistent habitat suitability metric for this and other
sedentary species. On-going and future research also
is being conducted to confirm the adequacy of the ex-
isting HSC and additional species of interest may be
added pending data availability and user input.
For this version of the REFDSS (v1.1.2) we did
not directly address the improvements on the tempera-
ture model or aerial extension; however, a temperature
model is being developed (Cole et al. 2014) for pos-
sible later incorporation into the REFDSS. Extending
the aerial coverage is both technically and computa-
tionally complicated. One requirement of the IFIM
is the need for detailed bathymetry data, which can
be both timely and costly to sample at large scales.
Recent advances in remote sensing, such as Bathy-
metric LiDAR, may lessen this burden. We are cur-
rently examining the feasibility of using such data to
facilitate this process. However, the size of data files
generated from this technique has not been tested in
the current VB.net platform. We also plan to test the
transferability of the REFDSS to other systems. Pro-
vided the required data are available (e.g., 2D hydro-
dynamic model output of habitat, HSC, hydrological
model) and appropriately formatted, uploading into
the shell version should be relatively easy. Inclusion of
other parameters such as catchment land use, dispersal
ability or species distribution models for each species
(Jähnig et al. 2012, Kuemmerlen et al. 2014, Domisch
et al. 2015 (this issue), Sondermann et al. 2015 (this is-
sue)) and other methods on habitat assessment (sensu
Kiesel et al. 2015 (this issue)) might further improve
performance of the REFDSS, especially in other
drainages where these factors might play a stronger
role. Finally, inferences from the REFDSS might be
improved by inclusion of an optimization algorithm
(e.g., Andreu et al. 1996, Shim et al. 2002).
In conclusion, we have developed a tool to com-
pare the effects of flow management scenarios on hab-
itat availability for key aquatic species in a region with
competing flow needs. However, instream flow needs
for aquatic species are just one small piece of the wa-
ter budget puzzle in the UPDE and worldwide. The
ideal tool will integrate the findings generated from
this REFDSS with human water demands (current and
predicted future demands), along with predicted envi-
ronmental variability (climate change, etc.) and water
availability. Once developed, such a tool will enable
managers to simultaneously evaluate release scenarios
while considering all facets of the water budget and
facilitate more informed decision making.
Acknowledgements
We thank many users, in particular James Serio, Erik Silldorff,
Hernan Quinodoz, and Peter Kolesar, for feedback and im-
provements to the original EDSS. Hernan Quinodoz also pro-
vided OASIS output for the REFDSS. We also thank Athena
Clark (USGS), Mathias Kuemmerlen, and two anonymous
reviewers whose comments greatly improved this manuscript.
Support for this project was provided by the U.S. Department
of the Interior’s WaterSMART (Sustain and Manage America’s
eschweizerbart_XXX

Resources for Tomorrow) program and the U.S. Geological
Survey’s National Water Census. Use of trade, product, or firm
names does not imply endorsement by the U.S. Government.
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eschweizerbart_XXX

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phi technique. – North American Journal of Fisheries Man-
agement 1: 55 – 59.
eschweizerbart_XXX

Appendix A. Credit for Open-Source Components used.
The development of the Delaware REFDSS would not have been possible without the use of several open-source and free projects
that contributed tremendously. GIS map display is provided by the MapWinGIS ActiveX Control Project which is part of the Map-
Window GIS Open Source Project (http://www.mapwindow.org/). The user configurable docking windows are from the DockPanel
suite available at http://dockpanelsuite.sourceforge.net/. The database backend uses SQLite with the dot.net bindings. (http://www.
sqlite.org/about.html). Unzipping functionality uses the DotNetZip Library (http://dotnetzip.codeplex.com/). Charting functional-
ity was built using the Microsoft Charting Library.
Appendix B. Screen capture of the Riverine Environmental Flow Decision Support System (REFDSS) for the Upper Delaware
River system showing total amount of available habitat (temporal range1October1928 to 30 September 2000) for adult brown trout
under the three alternative flow release scenarios (Rev1, Rev7, FFMP) at three scales: reach (upper left panel, three reaches in the
East Branch), branch (upper middle panel) and basin wide (upper right panel). The lower panel provides an example hydrograph
with available habitat for adult brown trout at DEL1 for all three flow release scenarios; habitat data are displayed on a daily resolu-
tion and only for the 1 July to 30 September period. Bars highlighted in hashed green indicate an increase in available habitat by at
least 10 % relative to the baseline scenario of Rev1.
eschweizerbart_XXX

AppendixC. Amountoftotalweightedpotentialavailablehabitat(hectares)estimatedfromtheRiverineEnvironmentalFlowDecisionSupportSystem(REFDSS)fortheUpperDelaware
Riversystemusingthe2005and2010bathymetricfilesforallscales(basin,branch,andreach).Forthereachscale,acronymsinparenthesessignifyreachcodesthatcorrespondtoFig. 1.NA
indicatesspecieswasnotlocatedinreachoranalysiswasnotconductedforthatyear(dwarfwedgemusselin2005).Cellshighlightedinlightgreysignifyagainof10 %ormoreofhabitatover
theRev1scenario,thoseindarkgreyindicatealossof10 %ormoreofhabitat.Availablehabitatvaluespresentedaretheaverageofthelower25 %ofvalueinthetimeseriesforahydroperiod
ofimportance(seeMethods).
OriginalHabitatSuitabilityCriteria SensitivityAnalysis–ExtendedHSCby10 %

Bathymetry
date
FlowScenario PercentChange
vs.Rev1
vs.Rev1
ScaleofAnalysisSpecies/LifeStageRev1Rev7FFMP Rev7FFMP Rev1Rev7FFMP Rev7FFMP
BasinwideBrowntroutspawning200593.60125.41107.843415134.34177.45155.613216
Browntroutincubation2005287.54337.52358.151725359.37416.92440.781623
Browntroutjuvenile2005340.08344.35364.6817419.71425.22450.3417
Rainbowtroutjuvenile2005470.17478.45506.2928559.74570.65601.1327
Americanshadspawning2005191.03198.23208.2949239.41247.12258.5838
Americanshadjuvenile2005375.25383.08380.4021415.45423.42422.2722
Shallow-fastguild200528.6933.9734.24181941.7449.1949.701819
Shallow-slowguild200591.1991.0690.220–1105.74105.89104.880–1
Dwarfwedgemussels2005NANANANANANANANANANA
DelawaremainstemBrowntroutspawning200548.0748.0846.010– 468.4268.3465.970– 4
Rainbowtroutadult2005342.77341.04347.09–11364.45362.98368.9601
Shallow-fastguild20055.465.495.371– 28.408.468.281– 2
Shallow-slowguild200524.0824.1324.220127.8727.9328.0401
Delawaremainstemreach1Browntroutspawning200517.6817.8116.811– 525.7025.8824.741– 4
(DEL1)Browntroutincubation200554.3657.4758.986965.9769.7271.3068
eschweizerbart_XXX

Shallow-fastguild20052.822.822.780–14.064.084.010–1
Delawaremainstemreach3Browntroutspawning200517.9017.7417.11–1– 425.2024.8824.26–1– 4
Browntroutadult2005105.53104.39106.34–11113.78112.69114.57–11
Rainbowtroutadult2005107.67106.37108.44–11115.22114.05115.95–11
Shallow-fastguild20051.501.501.470– 22.232.242.190–1
WestBranchBrowntroutspawning200515.6526.9225.31726223.4738.1337.196258
Americanshadspawning2005NANANANANANANANANANA
Americanshadjuvenile2005NANANANANANANANANANA
WestBranchreach0Browntroutspawning20050.180.471.681678530.330.832.65152706
(WB0)Browntroutincubation20050.070.752.6596536590.141.053.466292312
Browntroutadult20054.324.296.81–1585.335.158.33– 356
Rainbowtroutadult20054.364.296.84– 2575.365.158.35– 456
eschweizerbart_XXX


Bathymetry
date
vs.Rev1
vs.Rev1
WestBranchreach1Browntroutspawning200515.4726.4523.63715323.1437.3034.546149
(WB1)Browntroutincubation200540.1255.8962.41395650.0968.8775.313750
EastBranchBrowntroutspawning200514.9420.7417.15391522.1830.6625.653816
Browntroutjuvenile200580.2180.0287.330998.0397.53106.17–18
Shallow-slowguild200527.0426.1125.97– 3– 430.9330.1229.97– 3– 3
EastBranchreach0Browntroutspawning20050.860.662.38– 231791.381.193.80–13176
(EB0)Browntroutincubation20050.071.787.522574112140.142.729.4718376644
Browntroutjuvenile200516.0215.2920.40– 52719.0517.9923.79– 625
Browntroutadult200519.5417.7522.42– 91521.9119.6525.79–1018
Rainbowtroutadult200519.5417.7622.43– 91521.9119.6525.79–1018
Shallow-slowguild20059.598.578.56–11–1110.9510.0210.03– 8– 8
AppendixC.(continued)
eschweizerbart_XXX

EastBranchreach1Browntroutspawning20053.966.854.5773155.459.656.277715
EastBranchreach2Browntroutspawning200510.1213.2310.1931115.3619.8215.58291
NeversinkBrowntroutspawning200514.9529.6719.36982920.2740.3226.819932
Shallow-slowguild200526.3325.6525.02– 3– 530.7830.0129.19– 3– 5
NeversinkReach0Browntroutspawning20050.791.932.481452141.253.194.01154220
(NVR0)Browntroutincubation20052.885.339.09852154.006.7311.4268186
Rainbowtroutjuvenile200521.5021.4623.6001023.7323.5825.95–19
Shallow-slowguild20056.005.225.28–13–127.046.146.19–13–12
eschweizerbart_XXX


Bathymetry
date
vs.Rev1
vs.Rev1
Shallow-slowguild20057.147.196.781– 58.518.578.051– 5
Shallow-slowguild200513.1913.2512.960– 215.2315.3014.950– 2
2010DATA
DelawaremainstemBrowntroutspawning201025.6425.8824.571– 438.7939.1637.291– 4
Dwarfwedgemussels2010427.54430.24432.5511450.60452.33453.8201
AppendixC.(continued)
eschweizerbart_XXX

Americanshadspawning*201053.9154.6557.751764.9865.7269.0316
Americanshadjuvenile*2010123.73123.86124.3901133.85133.88134.6801
Dwarfwedgemussels2010154.27154.54155.21 01 160.75160.96161.52 00
Numberspecies/LifeStagesshowinga10 %orincrease:50624861
Numberspecies/LifeStagesshowinga10 %ordecrease:4452
*AmericanshadspawningandjuvenilewerenotincludedattheNVR2reachinthisversion(asinBoveeetal.2007).
eschweizerbart_XXX

Appendix D. List of acronyms used in manuscript.
Acronym Explanation Acronym Explanation
DEL1 Delaware River mainstream sampling reach #1 HSC Habitat Suitability Criteria
DEL2 Delaware River mainstream sampling reach #2 IFIM Instream Flow Incremental Methodology
DEL3 Delaware River mainstream sampling reach #3 LiDAR Light Detection And Ranging
DRBC Delaware River Basin Commission REFDSS Riverine Environmental Flow Decision Support System
EB0 East Branch Delaware River sampling reach #0 Rev1 Revision 1
EB1 East Branch Delaware River sampling reach #1 Rev7 Revision 7
EB2 East Branch Delaware River sampling reach #2 UPDE Upper Delaware River
EDSS Environmental Decision Support System USGS United States Geological Survey
FFMP Flexible Flow Management Plan WB0 West Branch Delaware River sampling reach #0
GIS Geographic Information System WB1 West Branch Delaware River sampling reach #1
GPS Global Positioning System WSE Water Surface Elevation
GUI Graphical User Interface
eschweizerbart_XXX

REFDSS_FundApplLimnolManuscript

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