The Columbia River estuary and plume:

1

• The Columbia River estuary and plume
• Natural variability, anthropogenic change and
  physical habitat for salmon
• PhD Candidate Michela Burla
• Research Advisor Antonio M. BaptistaCenter for
  Coastal Margin Observation and Prediction, OHSU
• Committee
• Edmundo Casillas, NOAA Fisheries
• Daniel L. Bottom, NOAA Fisheries
• Tawnya Peterson, CMOP, OHSU

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(No Transcript)
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The Columbia River
3,200-10,500 m3s-1 2001 1,800 m3s-1 1996 24,500
m3s-1
1800s
1930s-70s
Late1800s -
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Salmon in the ecology, economy and culture of the
Pacific NW
85 of Oregonians want salmon to be saved 35
part of NW heritage 36 measure of regions
environmental health 15 commodity value (The
Oregonian, Dec 1997)
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Columbia River Basin Salmon
Salmon catch in the Columbia River, 1866-1994
Habitat degradation from mining, logging,
irrigation
Dam development
(Lichatowich, 1999)
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Salmon recovery strategies in the CR
Production view
Population view
Technological fixes and hatchery production
Continuum of marine, estuarine, and riverine
habitats critical to preserve the diversity of
salmon life histories
Paradigm shift
(Lichatowich, 1999 Bottom et al, 2005, 2008
Fresh et al, 2005 NPPC 1997, 1998, 2009)
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CORIE/SATURN A coastal-margin observatory for
the CR estuary-plume-shelf
Observation network
Modeling system
Information management

• Goal to deliver quantifiably reliable
  environmental information, at the right time and
  in the right form to the right users.
• Can complex models that simulate the physical
  environment provide credible and useful answers
  to the decision makers ?
• Opportunity and challenge can high-resolution
  numerical models address the time scales relevant
  to investigate the impact of anthropogenic
  activities in the context of natural variability
  and climate change?

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Research Objectives
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions
Q1a To what extent is the CORIE/SATURN modeling
system capable to reproduce known dynamics of the
CR plume?
Q1b Can multi-year simulation databases of
circulation further our understanding of the
seasonal and inter-annual variability of the
plume in its response to river, ocean and
atmospheric forcings?
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Research Objectives
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions
Q2 Does the CR plume play a role in the survival
of juvenile salmon migrating from the Columbia
River to the ocean? Through what mechanisms? Do
inter-annual variability and climate and ocean
regimes modulate that role?
10
Research Objectives
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions
Q3 Can we use the high-resolution modeling
capabilities of CORIE/SATURN to investigate the
impact of natural variability and anthropogenic
change on physical habitat opportunity for salmon
in the CR estuary?
11
Research Objectives
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions
Q4 How does variability in river, ocean and
atmospheric forcings modify migration paths and
residence times in the CR estuary and plume,
potentially affecting survival success for
outmigrating juvenile salmon?
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Outline
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions
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Part I
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions
Courtesy NOAA
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Known patterns of variability of the CR plume

• Two winter plume patterns in response to wind
  (Hickey et al, 1998)
• - Thicker, northward, coastally attached
• Thin, west to northwestward
• Rapid changes in plume orientation and shape
  resulting from wind reversals (Fiedler and Laurs,
  1990 Hickey et al, 1998)
• Frequent summer bi-directional plume (Garcia
  Berdeal et al, 2002 Hickey et al, 2005)
• Interannual variability associated with
  variability in river discharge and wind forcing
  (Thomas and Weatherbee, 2006)

Classical view
Winter
Summer
Barnes et al, 1972
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A numerical exploration of CR plume variability
Q1a To what extent is the CORIE/SATURN modeling
system capable to reproduce known dynamics of the
CR plume? Q1b Can multi-year simulation
databases of circulation further our
understanding of the seasonal and inter-annual
variability of the plume in its response to
river, ocean and atmospheric forcings?
Analysis of plume variability Evaluation of
model skills
Model-obs and inter-model comparisons
1999-2006 simulation database (SELFE)
Ability to represent known dynamics Suite of
skill scores Conditional distributions of
modeled salinity
Seasonal and monthly climatologiesand anomalies
of surface S Integrative plume metrics EOF
analysis
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Plume variability River forcing

• Seasonal
• Sustained peaks during the spring snowmelt
  freshet
• More episodic peaks generated by winter storms
• Flows decreasing through the summer into the fall
• Interannual
• Intensity of winter storms and timing and
  intensity of the freshet (though reduced by flow
  regulation)
• Highest flows of winter and spring 1999, followed
  by 2000
• 2001 drought

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Plume variability wind forcing

• Seasonal
• Winter downwelling -favorable winds to the north
• Summer upwelling- favorable winds to the south
• Stronger wind stress during winter storms
• Interannual
• Intensity of winter storms and timing of spring
  transition
• E.g. strongly enhanced downwelling of Feb 1999
• Weak northward winds and reversals of Feb 2003
• Upwelling winds of Feb 2005 and 2006
• Late spring transition of 2000 and 2005

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Plume variabilityseasonal climatologies
Winter
Summer
Climatologies of the surface S, generated from
our 8-year simulations, are consistent with the
known prevailing seasonal patterns
DB14
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Plume variabilitymonthly climatologies and
anomalies
DB14
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Plume variability plume metrics
Multi-year simulations of the 3D salinity field
Area of the surface plume
Integrating over space
Plume volume
Salinity cutoff 28 psu
Plume average depth
model output_at_ 15 min intervals
Plume location (centroid)
1999
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Plume variability volume

• Delayed response to increases in CR discharge
• Largest volumes formed following the freshet
  season of 1999 and 2000, with seasonally larger
  volumes characterizing, in most years, the stormy
  winter season and the spring.
• 30-psu plume varied, in average-flow years,
  within a range comparable to the 20-110 km3
  estimated in Hickey et al (1998)

DB14
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Plume variability average depth
2002 Plume average depth (m)
Wind (ms-1)
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
The ratio of plume volume to its surface area
(average depth) in the simulations captures the
prompt response of the plume to wind reversals
DB14
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Plume variability depth and orientation

• Time series of plume depth at the northward inner
  shelf location consistent with the two basic
  winter structures observed in (Hickey et al,
  1998)
• Agreement with observed shallow summertime plumes
  and deeper wintertime plumes
• Summer plume consistently present at ogi01 in
  1999 (high discharge and consistent southward
  winds)
• Occasional appearances at ogi01 if low flows and
  frequent wind reversals
• Bi-directionality observed by Hickey et al.
  (2005) for the CR summer plume may apply at times
  to the winter plume as well.
• Episodic winter plume reversals confirmed in
  CORIE/SATURN observations

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Plume variability EOF analysis
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Plume variability EOF analysis - winter
Our analysis Winter months Nov-March of all
years 1999-2006 Hickey et al, 1998 EOF analysis
of 1 m salinity survey data, October 25-November
28, 1990 EOF1 57 CR plume when separated from
the coast and oriented northward of the mouth
EOF2 18 CR plume to the north but hugging the
coast.
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Plume variability EOF analysis - winter
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Plume variability EOF analysis - summer
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Evaluation of model skills methods

• Duplicative realizations of circulation database
• DB14 SELFE (upwind )
• DB11 ELCIRC (ELM)
• DB13 SELFE (ELM)
• Skill scores
• RMSE
• Brier skill score
• 1-MSE/MSEref
• Correlation skill score, ?MO
• (Unconditional) model bias
• MB(E(M)-E(O))/ sO
• Normalized standard deviation for the model
  predictions, sM/sO
• Distributions of modeled salinity conditional on
  the value of the observed salinity

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Evaluation of model skills scores

• RMSE is in most cases substantially reduced in
  DB14, except at deeper stations (at 5 and 20 m
  depth at the three RISE buoys)
• MB is consistently negative for DB11, and
  markedly larger, in absolute value, than the bias
  in DB14 (except at deeper stations) ? excessive
  freshness in ELCIRC simulations
• Larger biases at depth in DB14 are due to the use
  of terrain-following coordinates
• Despite the clear overall superiority of SELFE in
  DB14, ?MO reveals instances where DB14
  simulations perform worse than DB11 in
  reproducing variability in observed salinity
• DB11 variability in modeled salinity is
  generally distinctively higher than the
  variability in observed salinity (sMgtsO)DB14
  sOgtsM
• Consistently higher Brier skill scores for DB14
  than for DB13 improvement in adopting an upwind
  method in place of ELM to solve the transport
  equation

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Evaluation of model skillsconditional
distributions
DB14 (SELFE)
DB11 (ELCIRC)
Percentiles
10th and 90th
25th and 75th
50th (median)
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Part I Summary of findings
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions

• Correctly reproduced known patterns of
  variability.
• Interannual variability around climatological
  seasonal conditions in agreement with the results
  of TW (2006).
• Integrative metrics proved valuable in capturing
  the evolution of the CR plume in its response to
  variability in river and wind forcing.
• Differential influence of the CR plume on the
  Washington shelf across the years with potential
  implications on productivity.
• 8-year EOF analysis confirmed the two basic
  winter structures observed in 1990-91 (Hickey et
  al, 1998), indicating generality of the result.
• First two EOF modes clearly related to the two
  key forcing mechanisms of seasonal and
  inter-annual variability of the CR plume

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Part I Summary of findings
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions

• Prevalent bi-directionality of summer plume
  regardless of interannual variability.
• Short-term bi-directional plumes, previously
  observed or modeled only in summer, can
  occasionally develop also in winter as a result
  of episodically strong upwelling-favorable winds.
  
• Confirmed overall superiority of SELFE in the
  multi-year DB14 simulations (small RMSE and bias)
  and excessive freshness of DB11 simulations
  (ELCIRC) .
• DB14, to an extent, achieved better performance
  in terms of RMSE even when exhibiting weaker
  correlation with the observations by producing
  results that are conservatively less variable
  than the corresponding observations
• No one score is adequate by itself to fully
  evaluate the skill of a model

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High quality of CORIE/SATURN simulations provides
a rationale for using integrative metrics of CR
plume structure to investigate the ecological
implications of plume dynamics
Q2 Does the CR plume play a role in the survival
of juvenile salmon migrating from the Columbia
River to the ocean? Through what mechanisms? Do
inter-annual variability and climate and ocean
regimes modulate that role?
Photo courtesy E. Keeley
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Part II
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions
Photo courtesy E. Keeley
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Ocean environments in Pacific salmon survival

• Both freshwater and ocean environments contribute
  substantially to egg-to-adult salmon mortality
• For the ocean phase of salmon life history, most
  mortality occurs within the first few weeks or
  months of ocean residence
• Effort in the last decade into understanding the
  relationship between Pacific salmon production
  and climate variability patterns, such as ENSO
  and PDO
• Local marine environments (ocean-shelf upwelling,
  river plumes) may play as large a role in the
  early marine survival of salmon as the regime
  shifts operating at broader, regional scales

A role for the Columbia River plume?
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Does the CR plume influence salmon survival?What
we know

• Higher abundance of juvenile salmon in the
  coastal region off the CR associated with the
  low-salinity plume waters and frontal zones
  compared to the surrounding ocean waters (De
  Robertis et al, 2005)
• Juvenile salmon do not seem to take advantage of
  increased zooplankton biomasses at plume fronts,
  possibly due to their transience or small scale
  (Morgan et al, 2005)
• Local conditions in the environments that connect
  the river migration corridor to the ocean more
  likely determine rapid change in survival during
  a migration season than conditions farther away
  (ocean feeding areas of the gulf of Alaska or
  Bering Sea) (Scheuerell et al, 2009)
• Survival of outmigrating juvenile salmon varies
  at time scales consistent with changes in the CR
  plume

How does intraseasonal variability in salmon
survival relate to variability in the physical
plume environment simulated by CORIE/SATURN?
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Smolt-to-adult return rates (SARs)
PIT tagging
Barging
Migration
Through the estuary
2-4 Years at sea
Upstream migration to spawn
Adult detection
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The correlation analysis
The CR plumea fast-changing hydrodynamic feature

• Correlation analysis between daily values of SARs
  and plume metrics.
• Since we could only roughly estimate time of
  ocean entry, we explored the cross-correlations
  at different time lags.
• Analysis performed using anomalies from the
  4-year climatologies
• Non-parametric method to account for
  autocorrelation in testing significance of
  cross-correlations

May 1999
DB14
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Steelhead
Poor large-scale ocean conditions
Favorable large-scale ocean conditions
DB14
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Chinook
Poor large-scale ocean conditions
Favorable large-scale ocean conditions
DB14
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Strengths and uncertainties

• Our results were robust to the high inter-annual
  variability in local ocean (plume) conditions,
  till the regime shift in the large-scale ocean
  conditions occurred.

• SARs are a metric that encompasses several stages
  in the life history of the fish and multiple
  years conditions that steelhead encounter in the
  plume at the time of ocean entry can explain only
  part of their overall survival (16-40 of its
  variability) .
• Small numbers of returning adults upon which the
  SARs were based made their estimate fairly
  imprecise, but we believe that the trends of
  within-season variability are correctly captured .

• Alternative interpretations (e.g. local
  upwelling, which may affect salmon survival
  through bottom-up forcing of the marine food web)
  do not explain the differential response of the
  two species.

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Part II Summary of findings
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions

• Lagged cross-correlations suggested that
  steelhead benefited from the plume environment at
  a narrow window of time around their ocean entry.
  
• Contribution of plume conditions to the overall
  variability in steelhead survival became modest
  when large-scale ocean conditions turned
  unfavorable.
• Daily variability of the plume did not affect
  survival of Chinook salmon.
• Differential response between the two species is
  consistent with observed and previously reported
  behavioral characteristics
• H Steelhead mainly use the plume to move quickly
  away from coastal predation and for a more direct
  migration to ocean habitats.

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Succeeded in using the high-quality CORIE/SATURN
simulations of plume dynamics to develop a
biological hypothesis
Q3 Can we use the high-resolution modeling
capabilities of CORIE/SATURN to investigate the
impact of natural variability and anthropogenic
change on physical habitat opportunity for salmon
in the CR estuary?
Courtesy J. Burke
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Part III
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions
Courtesy J. Burke
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Physical Habitat Opportunity
Habitat Opportunity
availability of habitat that, based upon physical
factors, physiological constraints, and
ecological interactions, salmon can access and
which salmon can benefit from occupying (Bottom
et al, 2005).
Estuarine PHO metrics
Hours of PHO per week _at_ each grid point

• Water depth10cm ? d ? 2m
• Water velocityv ? 30cm/s
• Salinity0 ? s ? 5 psu
• Temperature0 ? T ? 19 oC

Sub-yearling ocean-type salmon
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Physical Habitat Opportunity
Habitat Opportunity
availability of habitat that, based upon physical
factors, physiological constraints, and
ecological interactions, salmon can access and
which salmon can benefit from occupying (Bottom
et al, 2005).
Estuarine PHO metrics
PHO accumulated per week over a specified region
(hoursm2)

• Water depth10cm ? d ? 2m
• Water velocityv ? 30cm/s
• Salinity0 ? s ? 5 psu
• Temperature0 ? T ? 19 oC

Averaged PHO within the inundated area
(hours/week)
Habitat opportunity
Sub-yearling ocean-type salmon
River flow (m3 s-1)
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Estuarine regions
Mouth
Middle estuary
Tidal freshwater
Peripheral bays
Baker
Grays
Youngs
Cathlamet
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Interannual variability and anthropogenic change
Interannual variability
Time series of weekly PHO climatologies and
anomalies
1999-2006 simulation database
Catalogue of anomaly maps
Anthropogenic change
Scenario 1 Predevelopment (1880) bathymetry and
flow Scenario 2 Modern dikes in predevelopment
scenario Scenario 3 Predevelopment flow over
modern bathymetry Scenario 4 Modern (2004) flow
over predevelopment bathymetry Scenario
5 Modern flow over modern bathymetry
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Water depth in the modern lower estuary

• Influence of tides dominates variability in
  shallow water (and low-velocity) habitats in the
  modern CR lower estuary
• Differential response to neap and spring tides
  across lower estuary

DB14
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Water depth in the tidal freshwater region

• Only more extreme flows have an appreciable, but
  still modest, impacton PHO in the modern
  bathymetry
• Strong historical freshets brought considerable
  gain in shallow water habitats through access to
  the floodplain in the predevelopment bathymetry

DB17
DB14
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Velocity in the tidal freshwater region

• In the modern bathymetry, the moderate gain in
  shallow water habitat, as Q?, tends to be
  canceled out by PHO loss due to velocity
  constraints
• In the predevelopment bathymetry, loss in PHO due
  to increasing velocities stopped for flows
  higher than 15,000 m3s-1 (inundated floodplain)

DB17
DB14
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Influence of temperature on PHO

• Continuous improvements in the quality of the
  CORIE/SATURN simulations DB17 skill in
  representing temperature changes in the middle
  estuary has been transformative.
• Simulations confirmed that, by mid-July (and
  through September), habitat is scarcely available
  for salmon to rear in the middle estuary because
  of excessively warm temperatures.

Model bias
Hours
week
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Influence of salinity intrusion on PHOin the
middle estuary

• Salt may penetrate deeper in the modern CR
  system, at times limiting habitat opportunity in
  Cathlamet Bay and off Grays Bay also at higher
  flows
• Modest estimated loss in PHO due to deeper salt
  intrusion into the modern middle estuary
• Order of magnitude not dissimilar from the loss
  determined by extreme low flows within the
  natural variability of the modern system

DB17
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Part III Summary of findings
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions

• Strategies aimed at re-establishing some
  connectivity between the river and its floodplain
  through modification of both flow and bathymetry
  are necessary to restore access to shallow and
  low-velocity rearing habitats in the upper
  estuary
• Modest estimated loss due to deeper salt
  intrusion in the modern middle estuary
• How salinity intrusion is changing relative to
  historical conditions needs to be a focus of
  further investigation
• Confirmed rearing habitat scarcely available in
  the middle estuary because of excessively warm T
  by mid-July through September
• Spatial connectivity among pockets of habitat
  opportunity needs to be investigated

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Future work
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions
Q4 How does variability in river, ocean and
atmospheric forcings modify migration paths and
residence times in the CR estuary and plume,
potentially affecting survival success for
outmigrating juvenile salmon?
56
Differential response of estuarine regions

• Preliminary results from ELCIRC simulations
  (DB11)
• Shallow environments and well-connected channels
  exhibit a differential response to changes in
  river discharge, both seasonally and
  interannually
• Shallow regions are areas of longer retention

DB11
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RTs in the estuary-plume continuum

• While RTs in the estuary are clearly influenced
  by river flow regimes, dominant processes
  affecting RTs in the domain extending over the
  plume region are wind-driven, and not necessarily
  linked to the presence of the plume

DB11
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Contributions
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions

• Demonstrated the quality of CORIE/SATURN
  simulations in reproducing known dynamics of the
  CR plume
• Improved our understanding of CR plume
  variability, in particular by showing
• that results of a bimodal winter plume and
  prevalence of a bidirectional plume in summer can
  be generalized regardless of interannual
  variability
• episodic winter plume bidirectionality
• Evaluated skill of the simulations providing
  feedback to the model developers

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Contributions
Introduction Research Objectives I. Seasonal and
interannual variability of the CR plume II. The
CR plume and salmon survival III. Salmon habitat
opportunity in the CR estuary IV. Future work
residence times in the CR estuary V. Conclusions

• Demonstrated how high-resolution numerical models
  like SELFE and ELCIRC, in the context of CMOs,
  can be successfully used to
• Formulate hypotheses for the mechanisms that link
  performance of biological species to their
  physical environment
• Address the temporal scales that are relevant to
  investigate natural variability and anthropogenic
  change
• Inform salmon recovery strategies in the CR basin
• - Combination of flow and bathymetry
  modifications are necessary to restore access to
  shallow and low-velocity rearing habitats in the
  upper estuary

60
Acknowledgments

• My committee
• Joseph Zhang
• Charles Seaton, Paul Turner, Ethan VanMatre,
  Michael Wilkin
• John Williams, Charles Si Simenstand, Doug
  Marsh
• Sergey Frolov
• Barbara Hickey, Ed Dever, Jen Burke, Mark
  Scheuerell
• Sandra Oster
• Nate Hyde, Aaron Racicot
• OGI staff Amy, Nancy, Alison

• The PDX Aliens
• Peter
• My family
• Bonnie Gibbs
• Funding support for this research
• NOAA Fisheries
• National Science Foundation

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The end
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Back-up slides
63
Plume variability location (centroid)
N-S relative to the CR mouth
Distance from shore
Coastal Upwelling Index
Columbia River discharge
DB14
64
Accounting for the autocorrelation in the data

• The shape of the ACF and PACF suggested that
  simple AR1 models were not adequate to describe
  the plume metrics time series in our study.
• We could not assume that frequencies lower than
  the daily sampling frequency (removed by removing
  autocorrelation) were unimportant.
• Size of SAR dataset and non-stationarity of plume
  series potential shortcomings of adjusting
  hypothesis testing procedure

Non-parametric test
Empirical distribution for rCRIT generated
resampling in the frequency domain
Phase-randomized
2000 surrogates
Plume time series
IFT
DFT
Surrogates preserve the original autocorrelation
structure