Prepared in cooperation with the U.S. Army Corps of Engineers Portland District and Northwest 

Association of Networked Ocean Observing Systems

Observations of Coastal Change and Numerical Modeling 

of Sediment-Transport Pathways at the Mouth of the 

Columbia River and its Adjacent Littoral Cell

Open-File Report 2020–1045

U.S. Department of the Interior

U.S. Geological Survey
Cover. Photograph of North Head Lighthouse, Washington, overlain by tracing of shoreline (black lines) and an 

example of model output (colored lines). Photograph by Andrew Stevens, August 31, 2016.
Observations of Coastal Change and Numerical Modeling 

of Sediment-Transport Pathways at the Mouth of the 

Columbia River and its Adjacent Littoral Cell

By Andrew W. Stevens, Edwin Elias, Stuart Pearson, George M. Kaminsky, Peter R. Ruggiero, 

Heather M. Weiner, and Guy R. Gelfenbaum

Prepared in cooperation with the U.S. Army Corps of Engineers Portland District 

and Northwest Association of Networked Ocean Observing Systems

Open-File Report 2020–1045

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DAVID BERNHARDT, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2020

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Suggested citation:

Stevens, A.W., Elias, E., Pearson, S., Kaminsky, G.M., Ruggiero, P.R., Weiner, H.M., and Gelfenbaum, G.R., 2020, 

Observations of coastal change and numerical modeling of sediment-transport pathways at the mouth of the 

Columbia River and its adjacent littoral cell: U.S. Geological Survey Open-File Report 2020–1045, 82 p., 

https://doi.org//10.3133/ofr20201045.

Associated data for this publication:

Stevens, A.W., Weiner, H.M., Ruggiero, P., Kaminsky, G.M., and Gelfenbaum, G.R., 2019, Beach topography and 

nearshore bathymetry of the Columbia River littoral cell, Washington and Oregon (ver. 2.0, November 2019): U.S. 

Geological Survey data release, https://doi.org//10.5066/P9W15JX8.

ISSN 2331-1258 (online)
iii

Acknowledgments

Funding for this study was provided by the U.S. Army Corps of Engineers (USACE) Portland 

District (in support of the Military Interdepartmental Purchase Request #W66QKZ80758076), 

U.S. Geological Survey (USGS) Coastal and Marine Hazards and Resources Program, and the 

Northwest Association of Networked Ocean Observing Systems (NANOOS).

We thank the large group of coastal scientists, known as the “nearshore all-stars,” that 

participated in the bathymetric and topographic surveys. In particular, we acknowledge the 

efforts of Jeff Wood, Dylan Anderson, Katy Serafin, Nick Cohn, and Paige Hovenga, of Oregon 

State University; Diana McCandless and Amanda Hacking, of Washington State Department of 

Ecology; and Tim Elfers, Cordell Johnson, and Jackson Currie of USGS. 

We thank Lee Faraola of Faraola Brothers Inc., whose mechanical expertise has been essential 

in keeping the USGS personal watercraft operational during the past few years. 

We thank Rod Moritz, James McMillan, and Jarod Norton from the Portland District USACE 

for overall project coordination. Reviews by Nick Cohn and Sean Vitousek greatly improved an 

earlier version of this report.
iv

Contents

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Environmental Setting...................................................................................................................................2

Task 1 – Observations of Coastal Change..................................................................................................4

Methods..................................................................................................................................................6

Field Acquisition...........................................................................................................................6

Bathymetric Data................................................................................................................6

Topographic Data................................................................................................................7

Geodetic Control ................................................................................................................7

Vertical Precision.........................................................................................................................7

Volume Change and Uncertainty Analysis ..............................................................................7

Results ..................................................................................................................................................10

North Beach Subcell.................................................................................................................10

Grayland Plains Subcell............................................................................................................12

Long Beach Subcell ..................................................................................................................17

Clatsop Plains Subcell ..............................................................................................................21

Integrated Net Volume Change ........................................................................................................23

Discussion............................................................................................................................................25

Environmental Forcing .............................................................................................................25

Sediment Supply ........................................................................................................................25

Dredging......................................................................................................................................25

Task 2 – Hydrodynamic and Sediment-Transport Modeling.................................................................26

Model Application...............................................................................................................................27

Delft3D Flow ...............................................................................................................................27

Wave Model................................................................................................................................28

Sediment-Transport Model ......................................................................................................34

Sediment Pathways Interactive Visualization Tool (SPIT)...........................................................34

Background.................................................................................................................................34

Application of SPIT to the Mouth of the Columbia River ....................................................34

Modeling Approach............................................................................................................................36

Results and Discussion......................................................................................................................38

Method 1—Event Time Scales ................................................................................................38

Method 2—Schematized Simulations....................................................................................38

Low-River-Discharge Conditions ...................................................................................42

High-River-Discharge Conditions...................................................................................42

Analysis of Sediment Pathways..............................................................................................43

Concluding Remarks....................................................................................................................................50

Data Availability ...........................................................................................................................................51

References Cited..........................................................................................................................................51

Appendix 1. Coverage Maps, Environmental Conditions, and Water-Column Properties During 

Bathymetric and Topographic Surveys ......................................................................................55

Appendix 2. Wave Heights, Mean Sediment-Transport Fluxes, and Sediment-Transport 

Pathways for Schematized Wave-Climate Simulations...........................................................73
v

Figures

1. Map of Columbia River littoral cell, showing locations of its subcells, major estuary 

entrances, and natural headlands that represent its northern and southern extents, 

respectively, also shown are locations of survey lines, geodetic benchmarks, wave 

buoys, water level gauges, instrumented tripods, and stream gauges...............................2

2. Maps of Columbia River estuary and mouth of Columbia River, showing locations of 

major engineering structures; active dredge-placement sites, North Head study area, 

maintained federal navigation channels, survey lines, geodetic benchmarks, wave 

buoys, water level gauges, instrumented tripods, and stream gauges...............................3

3. Time-series plots of wave heights, cumulative along-shore wave-energy flux, monthly 

mean sea level observed at Westport, Wash., and river discharge of Columbia River 

measured at Bonneville Dam and Willamette River at Salem, Ore......................................5

4. Field equipment used to collect bathymetric and topographic data ...................................6

5. Example analysis of replicate profile to estimate vertical uncertainty in bathymetric 

measurements...............................................................................................................................8

6. Maps showing cumulative net volume changes for entire profiles in 2015, 2016, 

2017, 2018, and 2019....................................................................................................................11

7. Map showing cumulative elevation changes 

along North Beach subcell between 2014 and 2019; also shown are cumulative 

volume changes for beach, nearshore, and entire profiles during same 

time period ...................................................................................................................................11

8. Map showing cumulative elevation changes between 2014 and 2019 for Ocean City 

region within North Beach subcell; example profile showing changes in beach and 

nearshore morphology along survey line 082; time-series plot of volume changes 

calculated for Ocean City region .............................................................................................12

9. Map showing cumulative elevation changes between 2014 and 2019 for Ocean 

Shores region within North Beach subcell; example profile showing changes in 

beach and nearshore morphology along survey line 010; and time-series plot of 

volume changes calculated for Ocean Shores region.........................................................13

10. Map showing cumulative elevation changes along Grayland Plains subcell 

between 2014 and 2019; also shown are cumulative volume changes for beach, 

nearshore, and entire profiles during same time period......................................................14

11. Map showing cumulative elevation changes between 2014 and 2019 for Westport 

region within Grayland Plains subcell; example profile showing changes in beach 

and nearshore morphology along survey line 090; and time-series plot of volume 

changes calculated for Westport region................................................................................15

12. Map showing cumulative elevation changes between 2014 and 2019 for Grayland 

region within Grayland Plains subcell; example profile showing changes in beach 

and nearshore morphology along survey line 035;and time-series plot of volume 

changes calculated for Grayland region ................................................................................16

13. Map showing cumulative elevation changes along Long Beach subcell between 

2014 and 2019; also shown are cumulative volume changes for beach, nearshore, 

and entire profiles during same time period ..........................................................................17

14. Map showing cumulative elevation changes between 2014 and 2019 for Oysterville 

region within Long Beach subcell; example profile showing changes in beach and 

nearshore morphology along survey line 069; and time-series plot of volume 

changes calculated for Oysterville region .............................................................................18
vi

15. Map showing cumulative elevation changes between 2014 and 2019 for Benson 

Beach and North Head regions within Long Beach subcell; example profile s

howing changes in beach and nearshore morphology along survey line 198; and 

time-series plot of volume changes calculated for North Head region............................19

16. Map showing cumulative elevation changes between 2014 and 2019 for Benson 

Beach and North Head regions within Long Beach subcell; example profile showing 

changes in beach and nearshore morphology along survey line 214; and time-series 

plot of volume changes calculated for Benson Beach region............................................20

17. Map showing cumulative elevation changes along Clatsop Plains subcell between 

2014 and 2019; also shown are cumulative volume changes for beach, nearshore, 

and entire profiles during same time period ..........................................................................21

18. Map showing cumulative elevation changes between 2014 and 2019 for South 

Jetty region within Clatsop Plains subcell; example profile showing changes in 

beach and nearshore morphology along survey line 037; and time-series plot of 

volume changes calculated for South Jetty region..............................................................22

19. Map showing cumulative elevation changes between 2014 and 2019 for Camp Rilea 

region within Clatsop Plains subcell; example profile showing changes in beach 

and nearshore morphology along survey line 090; and time-series plot of volume 

changes calculated for Camp Rilea region............................................................................23

20. Integrated cumulative net volume changes in 2015, 2016, 2017, 2018, and 2019 for 

each region having intensive sampling; map shows locations of intensive sampling 

regions within each subcell; and time-series plots show integrated net volume 

changes for regions within North Beach, Grayland Plains, Long Beach, and 

Clatsop Plains subcells..............................................................................................................24

21. Schematic representation of Delft3D modeling system ......................................................26

22. Map showing hydrodynamic and wave model grids used to simulate sediment 

transport in Columbia River estuary and at mouth of Columbia River; also; 

hydrodynamic model grids for Columbia River estuary and mouth of 

Columbia River ............................................................................................................................27

23. Modeled sensitivity of simulated water levels to variations in bed friction .....................29

24. Comparison of measured and modeled current speeds and directions at West 

Tripod Site in 4-day time period during spring tides .............................................................30

25. Comparison of modeled and measured water levels, current speeds, current 

directions, and salinity near seabed at West Tripod Site in same 4-day time period 

during spring tides as in figure 24............................................................................................31

26. Time-series plots of modeled and measured wind speed, wind direction, significant 

wave height, peak wave period, and wave direction between October 18 and 

November 18, 2010......................................................................................................................32

 27. Comparison of modeled and measured wave parameters between October 18 and 

November 18, 2010......................................................................................................................33

28. Maps showing Sediment Pathways Interactive visualization Tool (SPIT) visualizations 

of Lagrangian sediment-transport pathways showing sediment vector fields, 

streamlines representing vector fields, initial positions of sediment sources, and 

sediment pathways derived from SPIT analysis ...................................................................35

29. Flow chart showing modeling approaches applied during this study...............................36

30. Sediment-transport dynamics under varying wave- and tide-forcing conditions ..........39

31. Sediment-transport dynamics under varying wave- and tide-forcing conditions after 

pilot placement of dredged material within North Head study area................................... 40
vii

32. Time-series plots of water levels and significant wave heights, bed-shear stress, 

and sediment-transport flux for 72 days (between September 20 and 

December 1, 2018) after pilot placement of dredged material within 

North Head study area...............................................................................................................41

33. Maps showing annually averaged sediment-transport fluxes that are based on 

schematized model simulations during low fluvial-discharge scenarios; sedimenttransport vectors for simulations forced with tides and fluvial discharge alone and 

with tides, fluvial discharge, and waves.................................................................................44

34. Maps showing annually averaged sediment-transport fluxes that are based on 

schematized model simulations during high fluvial-discharge scenarios; sedimenttransport vectors (black arrows) are provided for simulations forced with tides and 

fluvial discharge alone and with tides, fluvial discharge, and waves ...............................45

35. Maps showing sediment-transport pathways derived from application of Sediment 

Pathways Interactive visualization Tool (SPIT) to schematized model simulations 

using low-river-discharge conditions and constant wave forcing ....................................46

36. Maps showing sediment-transport pathways derived from application of Sediment 

Pathways Interactive visualization Tool (SPIT) to schematized model simulations 

using high-river-discharge conditions and constant wave forcing...................................47

37. Maps showing sediment-transport pathways calculated for various sedimentsource locations and polygons of interest for low-river-discharge scenario; all 

500 sources and 19 wave classes originating from within North Head study area; 

sources and wave classes for pathways that interact with Benson Beach; and 

sources and wave classes for pathways that interact with navigational channel.........48

38. Probabilities of sediment-transport-pathway interactions between each source 

region and Benson Beach during low-river-discharge conditions....................................49

39. Probabilities of sediment-transport-pathway interactions between each source 

region and navigation channel during low-river-discharge conditions............................50

A1. Maps showing locations of bathymetric- and topographic-survey lines, sound-velocity 

measurements derived from Conductivity Temperature Depth casts, and benchmarks 

used for geodetic control from 2014 surveys along Columbia River littoral cell..............55

A2. Time-series plots of water levels, wave heights, wave periods, and wave directions 

during 2014 bathymetric and topographic surveys of Columbia River littoral cell ..........56

A3. Map showing locations of Conductivity Temperature Depth casts collected during 

2014 bathymetric surveys..........................................................................................................57

A4. Maps showing locations of bathymetric- and topographic-survey lines, soundvelocity measurements derived from Conductivity Temperature Depth casts, and 

benchmarks used for geodetic control from 2015 surveys along Columbia 

River littoral cell ..........................................................................................................................58

A5. Time-series plots of water levels, wave heights, wave periods, and wave directions 

during 2015 bathymetric and topographic surveys of Columbia River littoral cell ..........59

A6. Map showing locations of Conductivity Temperature Depth casts collected during 

2015 bathymetric surveys..........................................................................................................60

A7. Maps showing locations of bathymetric- and topographic-survey lines, soundvelocity measurements derived from Conductivity Temperature Depth casts, and 

benchmarks used for geodetic control from 2016 surveys along Columbia 

River littoral cell ..........................................................................................................................61

A8. Time-series plots of water levels, wave heights, wave periods, and wave directions 

during 2016 bathymetric and topographic surveys of Columbia River littoral cell ..........62
viii

A9. Map showing locations of Conductivity Temperature Depth casts collected 

during 2016 bathymetric surveys .............................................................................................63

A10. Maps showing locations of bathymetric- and topographic-survey lines, soundvelocity measurements derived from Conductivity Temperature Depth casts, and 

benchmarks used for geodetic control from 2017 surveys along Columbia 

River littoral cell ..........................................................................................................................64

A11. Time-series plots of water levels, wave heights, wave periods, and wave directions 

during 2017 bathymetric and topographic surveys of Columbia River littoral cell ..........65

A12. Map showing locations of Conductivity Temperature Depth casts collected during 

2017 bathymetric surveys..........................................................................................................66

A13. Maps showing locations of bathymetric- and topographic-survey lines, soundvelocity measurements derived from Conductivity Temperature Depth casts, and 

benchmarks used for geodetic control from 2018 surveys along Columbia 

River littoral cell ..........................................................................................................................67

A14. Time-series plots of water levels, wave heights, wave periods, and wave 

directions during 2018 bathymetric and topographic surveys of Columbia 

River littoral cell ..........................................................................................................................68

A15. Map showing locations of Conductivity Temperature Depth casts collected during 

2018 bathymetric surveys..........................................................................................................69

A16. Maps showing locations of bathymetric- and topographic-survey lines, soundvelocity measurements derived from Conductivity Temperature Depth casts, and 

benchmarks used for geodetic control from 2019 surveys along Columbia 

River littoral cell ..........................................................................................................................70

A17. Time-series plots of water levels, wave heights, wave periods, and wave directions 

during 2019 bathymetric and topographic surveys of Columbia River littoral cell ..........71

A18. Map showing locations of Conductivity Temperature Depth casts collected 

during 2019 bathymetric surveys .............................................................................................72

B1. Maps showing modeled wave parameters for wave classes 1, 2, 3, and 4 

(winter conditions) during low-river-discharge scenarios..................................................73

B2. Maps showing modeled wave parameters for wave classes 5, 6, 7, and 8 

(winter conditions) during low-river-discharge scenarios..................................................74

B3. Maps showing modeled wave parameters for wave classes 9, 10, 11, and 12 

(winter conditions) during low-river-discharge scenarios..................................................75

B4. Maps showing modeled wave parameters for wave classes 13, 14, 15, and 16 

(summer conditions) during low-river-discharge scenarios...............................................76

B5. Maps showing modeled wave parameters for wave classes 17, 18, and 19 

(summer conditions) during low-river-discharge scenarios...............................................77

B6. Maps showing modeled wave parameters for wave classes 1, 2, 3, and 4 

(winter conditions)during high-river-discharge scenarios..................................................78

B7. Maps showing modeled wave parameters for wave classes 5, 6, 7, and 8 

(winter conditions) during high-river-discharge scenarios.................................................79

B8. Maps showing modeled wave parameters for wave classes 9, 10, 11, and 12 

(winter conditions)during high-river-discharge scenarios..................................................80

B9. Maps showing modeled wave parameters for wave classes 13, 14, 15, and 16 

(summer conditions)during high-river-discharge scenarios...............................................81

B10. Maps showing modeled wave parameters for wave classes 17, 18, and 19 

(summer conditions) during high-river-discharge scenarios..............................................82
ix

Tables

1. Bathymetric and topographic surveys, their starting and ending dates and number 

of survey days, the number of profiles collected, and the length of survey lines 

collected during each survey .....................................................................................................4

2. Results of analysis of replicate bathymetric profiles, showing replicate number, 

survey year, subcell, line number, number of boats that surveyed the replicate, 

overlap distance, and 95 percent confidence intervals.........................................................9

3. Integrated cumulative net volume changes for each intensively sampled region 

between 2014 and 2019..............................................................................................................24

4. Error metrics describing sensitivity of simulated water levels to variations in bed 

roughness at four observation stations; for each station and model simulation, 

mean bias, bias-corrected root mean square error, and total root mean square 

error are provided ......................................................................................................................30

5. Specifications of wave classes used in morphological wave-climate 

schematizations, subdivided into winter and summer conditions .....................................37
x

Conversion Factors

U.S. customary units to International System of Units

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

yard (yd) 0.9144 meter (m)

Area

acre 0.4047 hectare (ha)

acre 0.004047 square kilometer (km2)

square foot (ft2) 0.09290 square meter (m2)

square mile (mi2) 259.0 hectare (ha)

Volume

cubic foot (ft3) 0.02832 cubic meter (m3) 

cubic yard (yd3) 0.7646 cubic meter (m3) 

Flow rate

foot per second (ft/s) 0.3048 meter per second (m/s)

cubic foot per second (ft3/s) 0.02832 cubic meter per second (m3/s)

Mass

ounce, avoirdupois (oz) 28.35 gram (g) 

pound, avoirdupois (lb) 0.4536 kilogram (kg) 

Density

pound per cubic foot (lb/ft3) 16.02 kilogram per cubic meter (kg/m3)
xi

International System of Units to U.S. customary units

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

meter (m) 1.094 yard (yd) 

Area

hectare (ha) 2.471 acre

square kilometer (km2) 247.1 acre

square meter (m2) 10.76 square foot (ft2) 

hectare (ha) 0.003861 square mile (mi2) 

Volume

cubic meter (m3) 35.31 cubic foot (ft3)

cubic meter (m3) 1.308 cubic yard (yd3) 

Flow rate

meter per second (m/s) 3.281 foot per second (ft/s) 

cubic meter per second (m3/s) 35.31 cubic foot per second (ft3/s)

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

kilogram (kg) 2.205 pound avoirdupois (lb)

Density

kilogram per cubic meter (kg/m3) 0.06242 pound per cubic foot (lb/ft3) 

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F = (1.8 × °C) + 32.

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C = (°F – 32) / 1.8.

Datum

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD88).

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD83).

Altitude, as used in this report, refers to distance above the vertical datum.
xii

Abbreviations

ADCP Acoustic Doppler Current Profiler

ADV Acoustic Doppler Velocimeter 

CDIP Coastal Data Information Program

CI Confidence interval

CRE Columbia River estuary

CRLC Columbia River littoral cell

CTD Conductivity Temperature Depth 

ENP Eastern North Pacific Ocean

ENSO El Niño–Southern Oscillation 

GNSS Global navigation satellite system 

GUI Graphical User Interface 

MCR Mouth of the Columbia River 

MLLW Mean lower low water 

MSL Mean sea level 

NAD83 North American Datum of 1983

NAVD88 North American Vertical Datum of 1988

NCAR National Center for Atmospheric Research 

NCEP National Centers for Environmental Protection 

NDBC National Data Buoy Center

NNRP National Centers for Environmental Protection and National Center for 

Atmospheric Research reanalysis project 

NOAA National Oceanic and Atmospheric Administration

ONR Office of Naval Research

PWC Personal watercraft 

RIVET Rivers and Inlets 

RMS Root mean square

RTK Real-time kinematic 

SJS South Jetty Site 

SPIT Sediment Pathways visualization Tool

SWAN Spectral wave model 

SWS Shallow Water Site 

USACE U.S. Army Corps of Engineers

USGS U.S. Geological Survey

UTM Universal Transverse Mercator
Observations of Coastal Change and Numerical Modeling 

of Sediment-Transport Pathways at the Mouth of the 

Columbia River and its Adjacent Littoral Cell

By Andrew W. Stevens,1 Edwin Elias,2 Stuart Pearson,2,3 George M. Kaminsky,4 Peter R. Ruggiero,5

Heather M. Weiner,4 and Guy R. Gelfenbaum1

Abstract

Bathymetric and topographic surveys performed annually 

along the coastlines of northern Oregon and southwestern 

Washington documented changes in beach and nearshore 

morphology between 2014 and 2019. Volume change analysis 

revealed measurable localized erosion and deposition 

throughout the study area, but significant net erosion at the 

regional scale (several kilometers [km]) was limited to Benson 

Beach, Wash., a 3-km-long stretch of coastline immediately 

north of the Columbia River inlet. Despite the placement of 

approximately 6.3 million cubic meters (Mm3) of sand dredged 

from the Columbia River navigational channel at nearshore 

placement sites located nearby, Benson Beach eroded 

2.1±0.8 Mm3 over the 5-year (yr) monitoring time period

(420,000 cubic meters/year [m3/yr]). A hydrodynamic and 

sediment transport model was applied to simulate sedimenttransport fluxes, and a new visualization technique was 

developed to evaluate the linkages between nearshore dredge 

placement sites and adjacent coastlines near the mouth of the 

Columbia River. The model results indicate the dominance of 

wave processes on sediment-transport patterns outside of the 

inlet and suggest that the current configuration of the nearshore 

dredge placement sites can be improved to more efficiently 

enhance the sediment budget of Benson Beach to reduce 

erosion and mitigate associated coastal change hazards.

Introduction

Tidal inlets are an important resource, providing habitat 

for estuarine species and a physical link between land and 

sea. The Columbia River is the largest river on the west coast 

of the United States, and its tidal inlet includes a federally 

managed navigation channel that connects the deep-water 

ports of Vancouver, Wash., and Portland, Ore., to the Pacific 

1

 U.S. Geological Survey.

2

 Deltares.

 3Delft University of Technology. 

4

 Washington State Department of Ecology.

5

 Oregon State University.

Ocean. Sediment historically supplied from the Columbia 

River nourishes beaches and protects infrastructure along 

165 km of coastline, while sedimentation in the navigation 

channel has necessitated costly maintenance dredging. 

Effective regional sediment-management decisions, which 

need to balance the requirements of safe navigation, habitat 

preservation, and beach stability in the Columbia River littoral 

cell (CRLC), require understanding and prediction of the 

spatial and temporal distribution of sediment fluxes, erosion, 

and accumulation. 

Although most of the beaches along the CRLC have 

been prograding (Ruggiero and others, 2016), severe 

localized erosion has prompted a variety of mitigation 

strategies, including nearshore placement of dredged 

material and beach nourishment (for example, Stevens and 

others, 2012). Strategic placement of sand dredged from the 

mouth of the Columbia River (MCR) navigational channel 

could help reduce local sand deficits and shoreline retreat, 

but a detailed understanding of coastal sediment budgets 

and transport processes that is sufficient to select both the 

volumes of sediment needed and appropriate placement 

locations is lacking. This study utilizes a combination of field 

measurements and numerical model experiments to improve 

our understanding of sediment transport pathways and coastal 

sediment budgets in the vicinity of the MCR. 

This report describes two primary research tasks. In 

Task 1, recent changes in coastal sand volume and beach 

morphology are quantified within the CRLC on the basis of 

bathymetric and topographic surveys performed annually 

between 2014 and 2019. Task 2 describes the application 

of a hydrodynamic and sediment transport model of the 

Columbia River estuary (CRE) to help understand the 

processes responsible for sediment dispersal and also 

identify transport pathways between the Columbia River and 

adjacent shorelines. The combination of field measurements 

and numerical modeling aims to inform regional sediment 

management decisions and the adoption of a sustainable 

maintenance strategy. After describing the environmental 

setting, we describe the methodology and discuss the results 

of each task separately. Concluding remarks are provided 

that discuss and synthesize the results from the field surveys 

(Task 1) and numerical modeling (Task 2). 
2 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Environmental Setting

The Columbia River drains an area of approximately 

670,000 square kilometers (km2). Discharge at the river mouth, 

which varies between about 3,000 and 17,000 cubic meters 

per second (m3/s), is characterized by low flow during the late 

summer and fall and high flow during the spring (Sherwood 

and Creager, 1990). The Columbia River historically has 

been the primary source of sediment to approximately 

165 kilometers (km) of shoreline between Point Grenville, 

Wash., and Tillamook Head, Ore. (fig. 1). The CRLC consists 

of four barrier beach plains, or subcells, separated by the 

entrances of Grays Harbor and Willapa Bay, Wash., and the 

Columbia River. The gently sloping, sandy barrier beaches 

and wide surf zones that characterize the CRLC developed and 

began to prograde approximately 6,000 years (yr) ago when the 

rate of relative sea level rise began to decrease (Peterson and 

others, 2010). Prehistoric progradation of the barrier beaches 

was interrupted episodically by large earthquakes that produced 

tsunamis and coseismic subduction (Atwater, 1996).

The Columbia River discharges into the Eastern North 

Pacific Ocean (ENP) at the border of Oregon and Washington. 

The ENP is characterized by an extreme wave climate where 

winter storms regularly generate significant wave heights 

of more than 10 meters (m), and strong seasonal variations 

result in mean average wave heights of approximately 3.8 

and 1.6 m for winter and summer, respectively (Ruggiero and 

others, 2010). Within the inlet, the flow and sediment transport 

fields are modified by a large tidal range, as well as ocean and 

wind waves and estuarine circulation associated with major 

freshwater inputs (Elias and Gelfenbaum, 2009). Ocean tides 

are classified as mixed semidiurnal with a mean tidal range 

of 2.1 m (National Oceanic and Atmospheric Administration 

[NOAA] station 9439040). Towards (and inside of) the MCR 

Figure 1. Map of Columbia River 

littoral cell, showing locations of 

its subcells (from north to south, 

North Beach, Grayland Plains, Long 

Beach, and Clatsop Plains), major 

estuary entrances (CRE, Columbia 

River estuary; GH, Grays Harbor; WB, 

Willapa Bay), and natural headlands 

(PG, Point Grenville; TH, Tillamook 

Head) that represent its northern and 

southern extents, respectively, also 

shown are locations of survey lines, 

geodetic benchmarks, wave buoys, 

water level gauges, instrumented 

tripods, and stream gauges. Black 

box shows area of figure 2. Other 

abbreviations: CDIP, Coastal Data 

Information Program; km, kilometer(s); 

NDBC, National Data Buoy Center; 

NOAA, National Oceanic and 

Atmospheric Administration.
Environmental Setting 3

and CRE, the ocean tides are modified by bed friction on 

the relatively shallow tidal delta and shoals, as well as by 

interaction with fluvial discharges, wind, and wave stresses. 

The MCR is characterized by an approximately 

13-m-deep navigational channel in which the depth and 

location are maintained with regular dredging, training dikes, 

and three major stone jetties (fig. 2). The North and South 

Jetties extend seaward about 3.5 and 10 km, respectively, 

and Jetty A extends southward about 1.5 km. The severe 

wave climate that impacts the MCR has eroded the jetty 

tips about 250 to 500 m in recent years. Located slightly 

inside of the inlet and orthogonal to the channel axis, Jetty 

Figure 2. Maps of 

Columbia River estuary 

(A) and mouth of 

Columbia River (B), 

showing locations of 

major engineering 

structures (JA, Jetty 

A; NJ, North Jetty; 

SJ, South Jetty). Blue 

shading shows active 

dredge-placement sites;

green shading shows 

North Head study area;

red shading shows 

maintained federal 

navigation channels. 

Also shown are locations 

of survey lines, geodetic 

benchmarks, wave 

buoys, water level 

gauges, instrumented 

tripods, and stream 

gauges. Other 

abbreviations: CDIP, 

Coastal Data Information 

Program; DWS, 

Deep Water Site; km, 

kilometer(s); m, meter(s); 

NH, North Head; NOAA, 

National Oceanic 

and Atmospheric 

Administration; USGS, 

U.S. Geological Survey.
4 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

A was constructed during the 1930s to further stabilize the 

shifting channel. The construction of the jetties, however, 

has altered hydrodynamic processes, transport pathways, and 

sediment supplies, resulting in increased progradation rates 

for several decades along much of the CRLC (Kaminsky 

and others, 2010). Although progradation along much of the 

CRLC continues to the present (2020) (Ruggiero and others, 

2016), severe beach erosion has been observed at several 

locations, including Benson Beach, a 3-km stretch of coastline 

immediately adjacent to the north of the MCR (fig. 2). 

Between 2 and 4 Mm3 of sand-sized sediment is dredged 

annually to maintain the entrance to the federal navigation 

channel in the MCR (U.S. Army Corps of Engineers 

[USACE], 2019). The dredged material is placed at one of 

several designated areas located throughout the region (fig.2)

with roughly 30 percent of the dredged sediment placed at 

the Deep Water Site and removed from the active littoral 

system. Most of the sediment that is dredged from the entrance 

channel is placed in either the Shallow Water or South Jetty 

Sites, located in the nearshore in water depths between 

approximately 12 and 22 m. The goal of placement in these 

shallow locations is to increase the coastal sediment supply 

and reduce erosion along shorelines adjacent to the MCR. The 

capacity of the nearshore sites is limited to control mounding, 

minimize impacts to marine resources, and reduce interference 

with other marine activities (for example, fishing). Owing 

to the current constraints to place dredged material within 

existing nearshore sites, a new nearshore dredge-placement 

area offshore of North Head is being studied, and small 

quantities of sediment were placed within the North Head 

study area in 2018 and 2019. 

Task 1 – Observations of Coastal 

Change

In this section, we describe observations of coastal 

change derived from repeated annual field surveys of 

nearshore bathymetry and beach topography between 2014 

and 2019 (table 1). These data are intended to inform regional 

sediment management by quantifying the magnitude and rates 

of change in sand volume and documenting the effectiveness 

of implemented management strategies aimed at reducing 

deficits in local sediment budgets. Although the focus of the 

hydrodynamic and sediment transport modeling described in 

Task 2 is focused on the MCR and its proximal shorelines, 

here we present bathymetric and topographic data collected 

over a larger area that encompasses a significant part of the 

CRLC. The broader spatial coverage provides context for the 

observations of coastal change around the MCR. Of particular 

interest is the comparison of the patterns of erosion and 

deposition around the MCR to the observations around the 

mouth of Grays Harbor, the nearby inlet to the north that also is 

stabilized with jetties and is maintained with regular dredging. 

Bathymetric and topographic data were collected along 

a series of shore-perpendicular transects spaced at 100- to 

1,000-m intervals between Tillamook Head and Point 

Grenville (fig. 1) in the CRLC. The survey-sampling scheme 

described in Ruggiero and others (2005) was designed to 

provide broad spatial coverage throughout a large part of 

the CRLC and intensive sampling along selected regions to 

resolve variability of smaller features. The profiles extend 

from 12- to 15-m water depth to just landward of the primary 

dune crest. The surveys were conducted annually during 

spring tides in the summer months of July, August, and 

September to quantify beach and nearshore morphology at a 

consistent time of year to minimize aliasing in our analysis 

that is due to strong seasonal patterns in wave energy, water 

levels, and fluvial discharge (fig. 3). In order to maximize 

coverage of intertidal areas, nearshore bathymetric data were 

acquired during high tide, and topographic measurements were 

collected during low tide, often resulting in overlap between 

topographic and bathymetric profiles. Each survey required 

between 7 and 10 working days to complete, depending 

on environmental conditions and equipment issues. The 

locations of bathymetric and topographic survey lines and 

environmental conditions during the surveys are provided in 

appendix A (bathymetric and topographic data and associated 

metadata are provided in Stevens and others, 2019).

Table 1. Bathymetric and topographic surveys, their starting and ending dates and number of survey days, the number of profiles 

collected, and the length of survey lines collected during each survey.

[Abbreviations: km, kilometer(s); no., number]

Year Start date End date

No. of survey 

days

No. of profiles Length (km)

Bathymetric

survey

Topographic

survey

Bathymetric

survey

Topographic

survey

2014 July 14, 2014 August 16, 2014 10 217 203 424 248

2015 July 13, 2015 August 11, 2015 7 219 200 425 321

2016 August 15, 2016 September 2, 2016 10 222 202 422 646

2017 August 7, 2017 August 23, 2017 7 219 203 434 455

2018 August 13, 2018 August 31, 2018 10 223 203 425 727

2019 July 29, 2019 August 13, 2019 7 220 201 430 440
Task 1 – Observations of Coastal Change 5

Figure 3. Time-series plots of (A) wave heights (Hs), (B) cumulative along-shore wave-energy flux, 

(C) monthly mean sea level (MSL) observed at Westport, Wash. (National Oceanic and Atmospheric 

Administration [NOAA] station 9441102), and (D) river discharge of Columbia River measured at 

Bonneville Dam (U.S. Army Corps of Engineers [USACE]) and Willamette River at Salem, Ore. (U.S. 

Geological Survey [USGS] station 14191000). Gray vertical lines separate survey years; yellow shading 

shows time of very strong 2015–16 El Niño-Southern Oscillation. Wave heights (A) and cumulative 

energy-flux (B) data were derived primarily from Coastal Data Information Program (CDIP) buoy 179; 

gaps in buoy record were filled with data from National Data Buoy Center (NDBC) buoy 46029. Other 

abbreviations: km, kilometer(s); m, meter(s); s, second; W, watt.
6 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Methods

Field Acquisition

Bathymetric Data

Bathymetric data were collected using personal watercraft 

(PWC) equipped with single-beam sonar systems and global 

navigation satellite system (GNSS) receivers (fig. 4A). The 

sonar systems consisted of an Odom Echotrac CV-100 singlebeam echosounder and a 200-kHz transducer with a 9° beam 

angle. Raw acoustic backscatter returns were digitized by the 

echosounder, using a vertical resolution of 1.25 cm. Depths 

from the echosounders were computed using sound-velocity 

profiles measured using a YSI CastAway Conductivity 

Temperature Depth (CTD) during the survey. Positioning of 

the survey vessels was determined at 5 to 10 Hz, using Trimble 

R7 GNSS receivers operating primarily in real-time kinematic 

(RTK) mode. Output from the GNSS receivers and sonar 

systems were combined in real time on the PWC by a computer 

running HYPACK hydrographic-survey software. Navigation 

information was displayed on a video monitor, allowing PWC 

operators to navigate along survey lines at speeds of 2 to 3 

m/s. The profiles were surveyed from the offshore extent of 

the survey line through the surf zone to a depth as shallow as 

possible near the shoreline, depending on wave conditions. 

Bathymetric data were postprocessed using a custom 

Graphical User Interface (GUI) programmed with the 

computer program MATLAB. Spurious depths were removed, 

and the GUI was used to hand digitize the bottom in areas 

Figure 4. Field equipment used to collect bathymetric and topographic data, including (A) personal watercraft equipped with singlebeam sonar and global navigation satellite system (GNSS) receiver, (B) GNSS receiver, mounted on backpack, being used by surveyor 

collecting topographic profile, (C) all-terrain vehicle equipped with GNSS receiver, and (D) GNSS antenna being set up by surveyor to 

use for geodetic control during surveys. Photographs in A and B by Andrew Stevens; in C and D, by Heather Weiner.
Task 1 – Observations of Coastal Change 7

where the echosounder signal processing failed. This was 

common in the surf zone where turbulence and bubbles in 

the water column added noise to the acoustical signal. After 

the raw depths were adjusted, a running mean with a window 

length of 5 to 20 points (1–6 m long) was applied to smooth 

the bathymetric profiles.

Topographic Data

Topographic profiles were collected by walking along 

survey lines, using GNSS receivers mounted on backpacks 

(fig. 4B). Prior to data collection, vertical distances between 

the GNSS antennas and the ground were measured using a 

tape measure. Each backpack system consisted of a Trimble 

R7, R8, R9, or R10 GNSS receiver. Zephyr Model 2 GNSS 

antennas were used for GNSS systems without integrated 

antennas. Hand-held data collectors were used to log raw data 

and display navigational information, allowing surveyors to 

navigate along survey lines. Profiles were surveyed from the 

landward edge of the study area (either the base of a bluff, an 

engineering structure, or just landward of the primary dune) 

over the beach foreshore, to wading depth on the same series of 

transects as nearshore bathymetric surveys that were conducted 

during the same time period. Additional topographic data were 

collected between survey lines in some areas with an all-terrain 

vehicle (ATV) equipped with a Trimble R8 or R10 GNSS 

receiver (fig. 4C) to constrain the elevations and along-shore 

extents of major morphological features.

Geodetic Control 

Geodetic control for the bathymetric and topographic 

surveys was established using the Washington Coastal 

Geodetic Network, a set of physical benchmarks that have 

published coordinates relative to NAD83. The elevations 

of all the benchmarks in the geodetic network achieve a 

vertical accuracy of 2 cm or better (Daniels and others, 1999). 

A GNSS base station, consisting of a Trimble R7 GNSS 

receiver and Zephyr Geodetic Model 2 antenna, placed on 

one of the benchmarks provided geodetic control for the 

bathymetric and topographic survey platforms (fig. 4D). 

A Pacific Crest ADL Vantage Pro radio modem was used 

to transmit differential corrections from the base station 

to the survey platforms in real time, at 1-Hz intervals. The 

positioning data from the bathymetric platforms were later 

postprocessed using Waypoint Grafnav; these data superseded 

the original positions recorded in real time. The positions 

of the topographic platforms collected in RTK mode were 

retained, and Trimble Business Center software was used to 

apply differential corrections to topographic data collected in 

autonomous mode when VHF communication with the base 

station failed. Orthometric elevations relative to the NAVD88 

vertical datum were computed for all survey platforms, using 

National Geodetic Survey Geoid12b offsets.

Vertical Precision

Precisely quantifying the vertical precision and accuracy 

of bathymetry data is notoriously difficult, as rarely do fixed 

objects on the seabed have known elevations. Although 

previous studies often relied on manufacturer-supplied 

estimates of instrument precisions (for example, Ruggiero and 

others, 2005), the relatively large number of survey vessels 

operating during this study presents an opportunity to develop 

a statistically robust operational estimate of the vertical 

precision of the single-beam bathymetry technique. Here we 

describe analysis of replicate profiles that were surveyed by 

each PWC to establish the vertical precision of the bathymetric 

measurements, and we use the estimated precision to quantify 

uncertainty in volumetric change computed between surveys. 

A replicate profile was typically surveyed by each PWC 

on each day of survey operations. To quantify the vertical 

precision of bathymetric data, the horizontal positions of the 

PWCs were rotated in the cross-profile coordinate system, 

and elevations were binned at 1-m intervals (fig. 5A) along 

the profile. Elevations that had positions more than 5 m from 

the target profile were omitted from further analysis. For the 

retained elevations, the 95 percent confidence interval was 

computed for each 1-m segment containing measurements 

from three or more survey vessels (fig. 5B). The 95th 

percentile of the 95 percent confidence intervals (fig. 5C) was 

selected to represent the precision of the replicate profile. The 

95th percentile was favored over other statistics to reflect the 

conservative nature of this analysis.

During the six surveys performed between 2014 and 

2019, a total of 30 replicate profiles, surveyed by at least 

three separate vessels, were collected and analyzed (table 2). 

The average vertical precision for the replicate profiles varied 

between 4 and 13 cm, with a mean of 8 cm. Variations in the 

average vertical precision between years were small, compared 

to the variability between profiles. No clear dependence of 

the vertical precision on depth was observed in the replicate 

profiles. We, therefore, selected the single value of 8 cm to 

reflect the average vertical uncertainty for all bathymetric data 

collected during this study; this value is consistent with vertical 

uncertainties, which were estimated using the same survey 

equipment, of 7 and 6.7 cm reported by Gelfenbaum and others 

(2015a) and Snyder and others (2016), respectively. 

Volume Change and Uncertainty Analysis

Changes in sediment volume were calculated for each 

profile surveyed along the CRLC in the following manner. 

Bathymetric and topographic data collected along each profile 

were rotated into the cross-profile coordinate system defined 

by the end points of the planned profile. Survey points that 

had positions more than 20 m from the target profile were 

removed, and the elevations of the remaining points were 
8 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure 5. Example analysis of replicate profile to estimate vertical uncertainty in 

bathymetric measurements. A, Elevation profile from separate vessels that surveyed 

replicate. B, Deviations from mean and 95 percent confidence intervals (CI) for each 1-m 

segment along profile. C, Histogram (purple bars) and cumulative distribution (red line) of 

95 percent confidence intervals along profile. Results from analysis of all replicates are 

provided in table 2. Other abbreviation: m, meter(s).
Task 1 – Observations of Coastal Change 9

Table 2. Results of analysis of replicate bathymetric profiles, showing replicate number, survey year, subcell, line number, number 

of boats that surveyed the replicate, overlap distance, and 95 percent confidence intervals (summarized as the 50th percentile, 90th 

percentile, and 95th percentile values).

[Subcells: CP, Clatsop Plains; GP, Grayland Plains; LB, Long Beach; NB, North Beach. Other abbreviations: m, meter(s); N, replicate; no., number]

Replicate Year Subcell Line no. N Overlap 

distance (m)

95% confidence intervals (m)

50th 

percentile

90th 

percentile

95th

percentile

1 2014 GP 42 4 1,588 0.04 0.06 0.07

2 2014 LB 60 3 666 0.04 0.07 0.08

3 2014 LB 190 3 881 0.05 0.12 0.14

4 2014 NB 25 4 1,402 0.04 0.07 0.08

5 2014 NB 74 4 1,841 0.03 0.05 0.06

6 2015 CP 101 4 1,654 0.03 0.06 0.07

7 2015 GP 34 3 343 0.04 0.08 0.09

8 2015 LB 60 4 1,794 0.03 0.05 0.06

9 2015 LB 175 4 514 0.03 0.07 0.08

10 2015 NB 25 4 1,573 0.03 0.06 0.07

11 2015 NB 79 4 2,259 0.04 0.07 0.09

12 2016 CP 88 4 1,691 0.05 0.09 0.11

13 2016 CP 101 3 1,697 0.05 0.08 0.09

14 2016 GP 44 4 1,472 0.02 0.04 0.05

15 2016 LB 160 3 691 0.04 0.08 0.10

16 2016 NB 25 5 1,060 0.02 0.04 0.04

17 2016 NB 79 4 1,700 0.04 0.07 0.08

18 2017 CP 101 4 1,500 0.03 0.05 0.06

19 2017 GP 48 4 1,406 0.03 0.04 0.05

20 2017 LB 150 5 1,784 0.03 0.06 0.07

21 2017 LB 216 4 1,442 0.03 0.05 0.06

22 2017 NB 25 4 1,258 0.02 0.03 0.04

23 2017 NB 99 4 1,845 0.03 0.04 0.05

24 2018 CP 48 4 1,834 0.04 0.09 0.11

25 2018 GP 48 3 815 0.03 0.05 0.06

26 2018 GP 48 3 555 0.04 0.06 0.07

27 2018 LB 60 4 1,340 0.03 0.06 0.08

28 2018 LB 145 4 1,232 0.05 0.10 0.12

29 2018 NB 25 3 1,117 0.04 0.07 0.08

30 2018 NB 79 4 2,201 0.04 0.07 0.08

Average 0.03 0.06 0.08

Minimum 0.02 0.03 0.04

Maximum 0.05 0.12 0.14
10 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

binned at 1-m intervals. Small gaps along relatively smooth 

sections in the profiles were filled with linear interpolation. 

Changes in sediment volume between surveys were computed 

by summing the differences in elevation along each 1-m-long 

segment along the profile. No change-detection threshold 

was applied to remove volume changes that were less than 

the estimated uncertainty, as the application of detection 

thresholds can lead to erroneous interpretations of volume 

change (Anderson, 2019).

Volume changes were calculated separately for depth 

zones both above and below 0 m NAVD88, hereafter referred 

to as “beach” and “nearshore” areas, respectively. As defined 

here, the beach region roughly includes intertidal and subaerial 

elevations because the 0-m NAVD88 contour is 0.25 m above 

mean lower low water (MLLW) level at Toke Point, Wash., tide 

gauge (NOAA station 9440910) and 0.07 m below MLLW for 

the Astoria, Ore., tide gauge (NOAA station 9439040). Volume 

changes along each intensively sampled region where survey 

lines were spaced no more than 200 m apart were computed 

by multiplying the profile-averaged volume changes by the 

distance between the profiles and summing these volumes for 

all the profiles acquired within the region. 

Uncertainty in volume change was assessed on the basis 

of the vertical precision of the bathymetry measurements, 

derived from analysis of repeat lines. Here, we assume 

that vertical precision is equivalent to vertical accuracy 

between surveys. Previously published studies (for example, 

Gelfenbaum and others, 2015a) have used this assumption 

to generate uncertainty estimates for volume-change 

calculations using similar survey methodology. The total 

vertical uncertainty was calculated by assuming the error 

between surveys are independent and by summing the average 

precision of each bathymetric survey (8 cm) in quadrature 

(for example Taylor, 1997) to yield a total uncertainty 

between surveys of ±11 cm. The profile-averaged uncertainty 

in volume change is computed by multiplying the vertical 

uncertainty by the total distance of the survey profile. This is 

a very conservative approach because all of the uncertainty is 

treated as systematic error (bias). Future work will focus on 

separately quantifying the systematic and spatially correlated 

random components of error (as explained in Anderson, 

2019) to reduce the uncertainty in the volume-change 

estimates. Although topographic-elevation measurements 

using our methodology have less vertical uncertainty than the 

bathymetric data owing to the relatively simple survey system 

and geometry, we do not distinguish between the bathymetric 

and topographic parts of the profile, and we use the estimated 

precision of the bathymetric data to characterize vertical 

uncertainty for the entire profile. 

Results

A total of 2,560 km of nearshore bathymetric-survey 

lines and 2,837 km of topographic-survey lines were collected 

during the six surveys performed between 2014 and 2019 

(table 1). Results of the volume-change analysis, which 

revealed measurable net erosion and deposition in each of 

the subcells surveyed, are presented as follows. First, we 

describe the large-scale along-shore patterns of net erosion and 

accretion that were computed for each profile collected along 

the CRLC. Next, we analyze the net elevation change and 

examine the variability in sediment-volume change across the 

beach and nearshore depth zones for each subcell. We provide 

example profiles within each region and subcell to examine the 

morphological changes associated with observed net erosion 

and accumulation. Finally, we integrate the volume changes for 

each region that was surveyed more intensively (with profiles 

spaced at 100–200-m intervals) to identify large-scale, regional, 

net volume changes and temporal dynamics along the CRLC.

The largest net changes in sand volume integrated over 

all of the profiles were observed in proximity to the two 

maintained inlets of Grays Harbor and the Columbia River 

(fig. 6). At both locations, net erosion was observed north of 

the inlet, and net accumulation was observed to the south. 

Net volume change outside of these two locations, which was 

generally small, was characterized by deposition along the 

Long Beach and Clatsop Plains subcells and erosion along the 

southern Grayland Plains subcell. These patterns are described 

in detail for each subcell below. 

North Beach Subcell

Cumulative net changes in elevation and volume between 

2014 and 2019 were spatially variable throughout the North 

Beach subcell (fig. 7). The beaches (that is, parts of the profile 

above 0 m) along Ocean City, Wash. (northern North Beach 

subcell), and central North Beach accumulated sediment, 

whereas no consistent accretional trends at the south end of 

the North Beach subcell were observed. Measurable erosion 

in the nearshore area was observed along parts of Ocean 

Shores between 2016 and 2017, but the trend was reversed 

in subsequent years, and net changes in nearshore sediment 

volume were negligible. 

Geomorphic and volumetric changes in the Ocean City 

region were relatively uniform along the coast, as shown in 

figures 7 and 8. A combined topographic and bathymetric 

profile is representative of the temporal beach and nearshore 

dynamics throughout the about 3.5 km stretch of coast (fig.8)

Volume changes in the nearshore area of Ocean City were 

largely driven by changes in nearshore sandbar size and 

position. A broad zone of sediment that accumulated between 

2014 and 2019 (fig. 8A) may represent the movement and 

decay of a sandbar that migrated from the inner surf zone 

offshore during this time period (for example, Cohn and 

Ruggiero, 2016). This hypothesis is supported by the presence 

of a prominent outer bar at about –4 m depth in 2017 (fig. 8B) 

that is not present in later survey years. Conversely, a lowering 

of more than 1 m of the bed surface over this timeframe near 

the –2 m depth is related to the presence of a bar trough in 

the 2019 survey that was not present in the 2014 survey. The 

beaches along Ocean City also gained volume measurably 

(that is, the volume change is greater than our estimated 
Task 1 – Observations of Coastal Change 11

Figure 6. Maps 

showing cumulative 

net volume changes 

(colored dots) for entire 

profiles in 2015 (A), 2016

(B), 2017 (C), 2018 (D), 

and 2019 (E). Darker 

gray shading indicated 

profiles that had volume 

changes less than 

estimated uncertainty. 

Other abbreviations: 

km, kilometer(s); m, 

meter(s).

Figure 7. Map 

showing cumulative 

elevation changes 

(A) along North Beach 

subcell between 

2014 and 2019. Also 

shown are cumulative 

volume changes for 

beach (B), nearshore

(C), and entire profiles 

(D) during same time 

period. Abbreviations: 

km, kilometer(s); m, 

meter(s).
12 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure 8. A, Map showing cumulative elevation changes between 2014 and 2019 for Ocean City region within North Beach subcell

(see fig. 7 for location); depth contours (5-m interval between –10 and 0 m) based on 2014 survey. B, Example profile showing changes 

in beach and nearshore morphology along survey line 082 (location shown in A). C, Time-series plot of volume changes calculated for 

Ocean City region; net volume changes are provided for beach and nearshore depth zones, as well as net volume changes integrated 

over entire region. Abbreviations: km, kilometer(s); m, meter(s); Mm3, million cubic meter(s).

uncertainty) across a broad range of elevations, from the lower 

intertidal zone (near 0 m) to near the dune at 5-m elevation. 

Despite the complicated pattern of net volume change 

in the Ocean Shores region, some notable patterns of erosion 

and deposition were observed (fig. 9). The shape of the outer 

shore face between –10 and –5 m depth increased in concavity 

owing to erosion offshore at depths of between –10 and –7 m, 

as observed in example profile 010. Net erosion at this location 

occurred between 2014 and 2017, and deepening of the trough 

of a nearshore bar was responsible for a large amount of the 

volume loss (fig. 9B). The erosional trend in Ocean Shores 

ended in 2017, and sediment accumulated between 2017 and 

2019, both of which resulting in no significant change for this 

region during the entire study period. Beach dynamics were 

quite complicated in the Ocean Shores region, as some profiles 

(for example, line 010) experienced measurable erosion and 

about 10 m of landward movement of the dune face. 

Grayland Plains Subcell

Spatially consistent patterns of erosion and deposition 

were observed along the Grayland Plains subcell (fig. 10). In 

the Westport region, sediment accumulation in the nearshore 

was spatially pervasive, and the magnitude of the gains were 

large. The largest amount of accumulation observed throughout 

the CRLC during the monitoring period was observed in 

the Westport region, at the north end of the Grayland Plains 

subcell where cumulative profile integrated net volume change 

between 2014 and 2019 exceeded 1,000 m3/m for several 

profiles (fig. 10D). Despite the strong accumulation pattern 

in the nearshore and beach at the north end of Westport, the 

beach in the southern part of Westport eroded. In the Grayland 

region, at the south end of the Grayland Plains subcell, a large 

cross-shore exchange signal in volume change was observed 

whereby the beaches gained volume and the nearshore lost 
Task 1 – Observations of Coastal Change 13

Figure 9. A, Map showing cumulative elevation changes between 2014 and 2019 for Ocean Shores region within 

North Beach subcell (see fig. 7 for location); depth contours (5-m interval between –10 and 0 m) based on 2014 

survey. B,Example profile showing changes in beach and nearshore morphology along survey line 010 (location 

shown in A). C, Time-series plot of volume changes calculated for Ocean Shores region; net volume changes are 

provided for beach and nearshore depth zones, as well as net volume changes integrated over entire region. 

Abbreviations: km, kilometer(s); m, meter(s); Mm3, million cubic meter(s).
14 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure 10. Map showing cumulative elevation changes (A) along Grayland Plains subcell between 2014 and 2019;

gray-filled box shows nearshore dredge-placement area offshore of Westport. Also shown are cumulative volume 

changes for beach (B), nearshore (C), and entire profiles (D) during same time period. Abbreviations: km, kilometer(s); 

m, meter(s).

volume. The net result was a measurable erosion signal along 

parts of the Grayland region, the cumulative profile integrated 

net erosion being as high as 450 m3/m.

Most of the net volume gain in the Westport region of 

the Grayland Plains subcell is due to accumulation across 

the lower shoreface (fig. 11). Elevation change in excess of 

1 m was observed across a broad depth zone between the 

end of the profile (at –10 m depth) to approximately –5 m 

depth. Accumulation in the lower shoreface appears to be 

enhanced onshore of the nearshore dredge-placement site, and 

unusual dynamics at the end of the profiles seem to capture 

areas of active dredge placement. The rate of sediment 

accumulation in the nearshore was steady between 2014 and 

2017, after which no further net volume gain, or potentially 

a net volume loss (within the measurement uncertainty), 

was observed. The observed beach erosion at the south end 

of Westport occurred in the upper beach and dunes where 

cumulative elevation change in excess of –3 m was observed. 

The dune crest retreated approximately 20 m landward, and 

its height reduced by approximately 1 m. Despite volume 

losses to the dune, nearly no net volume changes to the 

beach compartment occurred within Westport during the 

measurement period (fig.11C

Throughout the Grayland region within the Grayland 

Plains subcell, rotation of the shoreface was observed around 

a pinch point at approximately –5 m depth (fig. 12). The 

shoreface rotation, which has been relatively consistent 

throughout the monitoring period, has led to increased 

concavity and volume loss on the lower shoreface. Meanwhile, 

between the shoreline and dune toe across the wide beaches 

of Grayland region, a broad area of accumulation was 

observed. The average elevation of the beach increased by 

approximately 1 m, and the location of the 3-m elevation 

contour prograded seaward about 40 m, resulting in net beach 

volume gain that about matched the loss in the nearshore. The 

combined effect of nearshore erosion and beach accumulation 

resulted in minimal cumulative net volume losses during the 

study period integrated across Grayland region.
Task 1 – Observations of Coastal Change 15

Figure 11. A, Map showing cumulative elevation changes between 2014 and 2019 for Westport region within Grayland 

Plains subcell (see fig. 10 for location); depth contours (5-m interval between –10 and 0 m) based on 2014 survey. Gray-filled 

box shows nearshore dredge-placement area. B, Example profile showing changes in beach and nearshore morphology 

along survey line 090 (location shown in A). C, Time-series plot of volume changes calculated for Westport region; net volume 

changes are provided for beach and nearshore depth zones, as well as net volume changes integrated over entire region. 

Abbreviations: km, kilometer(s); m, meter(s); Mm3, million cubic meter(s).
16 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure 12. A, Map showing cumulative elevation changes between 2014 and 2019 for Grayland region within Grayland 

Plains subcell (see fig. 10 for location); depth contours (5-m interval between –10 and 0 m) based on 2014 survey. B, 

Example profile showing changes in beach and nearshore morphology along survey line 035 (location shown in A). C, 

Time-series plot of volume changes calculated for Grayland region; net volume changes are provided for beach and 

nearshore depth zones, as well as net volume changes integrated over entire region. Abbreviations: km, kilometer(s); m, 

meter(s); Mm3, million cubic meter(s).
Task 1 – Observations of Coastal Change 17

Long Beach Subcell

The most severe erosion throughout the study area was 

observed along the southern part of the Long Beach subcell 

(fig. 13) at Benson Beach. Beach erosion peaked in 2017 in 

the area between the Columbia River North Jetty and North 

Head. The extreme beach erosion was also accompanied by 

erosion in the nearshore, with profile-averaged net volume 

losses within Benson Beach as high as 1,600 m3/m during the 

5-year study period. However, at the southernmost part of 

Benson Beach (immediately adjacent to the Columbia River 

mouth where the survey profiles intersect the North Jetty), 

accumulation in the nearshore resulted in net accretion. North 

of Benson Beach, the beaches of the Long Beach peninsula 

accumulated sediment measurably, whereas volume changes 

in the nearshore were minimal. 

Figure 13. Map showing cumulative elevation changes (A) along Long Beach subcell between 2014 and 2019; gray-filled 

boxes show nearshore dredge-placement areas offshore of Benson Beach and North Head. Also shown are cumulative 

volume changes for beach (B), nearshore (C), and entire profiles (D) during same time period. Abbreviations: km, 

kilometer(s); m, meter(s).
18 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

A broad zone of small but measurable erosion was 

observed throughout the outer part of the nearshore zone in 

the Oysterville region (fig. 14), at the north end of the Long 

Beach subcell. Changes in the size and position of sandbars 

in the inner nearshore at depths between –5 and –1 m resulted 

a complicated pattern of erosion and deposition. Cumulative 

net volume change in the nearshore did not generally exceed 

the measurement uncertainty over the monitoring time period. 

Accumulation was observed on the beaches of the Oysterville 

region, with positive elevation changes occurring on the 

beach foreshore between 3- and 7-m elevations. Although 

little measurable elevation change occurred above 7 m and the 

position of the primary dune crest was stable, the 3-m elevation 

contour prograded seaward an average of about 25 m.

Closely spaced topographic and bathymetric profiles 

were collected on both sides of North Head, including for the 

Figure 14. A, Map showing cumulative elevation changes between 2014 and 2019 for Oysterville region within Long 

Beach subcell (see fig. 13 for location); depth contours (5-m interval between –10 and 0 m) based on 2014 survey. 

B, Example profile showing changes in beach and nearshore morphology along survey line 069 (location shown in A). 

C, Time-series plot of volume changes calculated for Oysterville region; net volume changes are provided for beach and 

nearshore depth zones, as well as net volume changes integrated over entire region. Abbreviations: km, kilometer(s); m, 

meter(s); Mm3, million cubic meter(s).
Task 1 – Observations of Coastal Change 19

erosional region of Benson Beach. North of North Head, the 

dynamics of a pronounced outer bar drove observed changes 

in elevation and sand volume in the nearshore (fig.15)

Alternating erosion and deposition across the nearshore 

reflected interannual variations in the position of the outer 

bar crest and trough. Measurable net accumulation in the 

nearshore peaked in 2017, after which erosion occurred, 

and no significant net change in nearshore sand volume 

could be detected by 2019. After 2016, the beaches north of 

North Head began to gain volume, and net deposition was 

significant (111,000±35,000) by 2019.

Central Benson Beach, south of North Head at the south 

end of the Long Beach peninsula, experienced net erosion 

across the entire shoreface (fig. 16). Measurable erosion 

Figure 15. A, Map showing cumulative elevation changes between 2014 and 2019 for Benson Beach and North Head 

regions within Long Beach subcell (see fig. 13 for location); depth contours (5-m interval between –10 and 0 m) based 

on 2014 survey. Black line outlines profiles used to calculate net volume changes in North Head region. Gray-filled 

boxes show North Head study area (northwest corner) and Columbia River Shallow Water Site (southwest corner) 

dredge-placement areas. B, Example profile showing changes in beach and nearshore morphology along survey line 

198 (location shown in A). C, Time-series plot of volume changes calculated for North Head region; net volume changes 

are provided for beach and nearshore depth zones, as well as net volume changes integrated over entire region. 

Abbreviations: km, kilometer(s); m, meter(s); Mm3, million cubic meter(s).
20 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

extended from the seaward extents of many of the profiles and 

continued across the shoreface to the beach, where the crest of 

the dune retreated landward roughly 50 m, and the elevation of 

the dune crest lowered more than 1 m between 2014 and 2019. 

Accumulation on the beach alleviated some erosion in recent 

years, although net volume loss on the beach was ubiquitous 

throughout the Benson Beach region during the monitoring 

period. At the southernmost extent of Benson Beach, an area of 

net accumulation was observed in the nearshore from the seaward extent of the profile to a depth of about –5 m. The area of 

nearshore accumulation is immediately adjacent to the Columbia River Shallow Water Site, an active dredge-placement area. 

Figure 16. A, Map showing cumulative elevation changes between 2014 and 2019 for Benson Beach and North Head 

regions within Long Beach subcell (see fig. 13 for location); depth contours (5-m interval between –10 and 0 m) based on 

2014 survey. Black line outlines profiles used to calculate net volume changes in Benson Beach region. Gray-filled boxes 

show North Head study area (northwest corner) and Columbia River Shallow Water Site (southwest corner) dredgeplacement areas. B, Example profile showing changes in beach and nearshore morphology along survey line 214 (location 

shown in A). C, Time-series plot of volume changes calculated for Benson Beach region; net volume changes are provided 

for beach and nearshore depth zones, as well as net volume changes integrated over entire region. Abbreviations: km, 

kilometer(s); m, meter(s); Mm3, million cubic meter(s).
Task 1 – Observations of Coastal Change 21

Clatsop Plains Subcell

Very little net erosion was observed along the Clatsop 

Plains subcell. Only one profile (out of the 48 surveyed 

and analyzed) in the Clatsop Plains subcell experienced 

cumulative net erosion above the measurement uncertainty 

between 2014 and 2019. At South Jetty, a large quantity 

of sediment deposited in the beach and nearshore (fig. 17). 

Farther south in the Camp Rilea region, deposition was 

observed on the beach, whereas changes in the nearshore were 

within the measurement uncertainty. The net result was no net 

measurable change in sediment volume along the southern part 

of the Clatsop Plains subcell. 

Most of the observed net volume change in the South 

Jetty region was due to a relatively thin (<0.5 m) layer of 

sediment accumulation that spread throughout the nearshore 

Figure 17. Map showing cumulative elevation changes (A) along Clatsop Plains subcell between 2014 and 2019; gray-filled box 

shows nearshore dredge-placement area offshore of South Jetty. Also shown are cumulative volume changes for beach (B), 

nearshore (C), and entire profiles (D) during same time period. Abbreviations: km, kilometer(s); m, meter(s).
22 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

(fig. 18). Unlike the pattern observed in the Wesport region, 

sediment accumulation does not appear to be enhanced 

onshore of the South Jetty nearshore dredge-placement area. 

Some erosion was observed along the South Jetty, as well as 

in a narrow band along the inner nearshore zone at depths 

of between –5 and –2 m. The beaches also gained sediment 

volume in the South Jetty region, especially to the north, in 

close proximity to the base of South Jetty. 

Bar dynamics in the Camp Rilea region of the Clatsop 

Plains subcell resulted in a complicated pattern of alternating 

erosion and deposition in the nearshore zone (fig. 19). A 

prominent outer bar was present in 2014 and again in 2019, 

Figure 18. A, Map showing cumulative elevation changes between 2014 and 2019 for South Jetty region within Clatsop 

Plains subcell (see fig. 17 for location); depth contours (5-m interval between –10 and 0 m) based on 2014 survey. Grayfilled box shows nearshore dredge-placement area. B, Example profile showing changes in beach and nearshore 

morphology along survey line 037 (location shown in A). C, Time-series plot of volume changes calculated for South Jetty 

region; net volume changes are provided for beach and nearshore depth zones, as well as net volume changes integrated 

over entire region. Abbreviations: km, kilometer(s); m, meter(s); Mm3, million cubic meter(s).
Task 1 – Observations of Coastal Change 23

Figure 19. A, Map showing cumulative elevation changes between 2014 and 2019 for Camp Rilea region within 

Clatsop Plains subcell (see fig. 17 for location); depth contours (5-m interval between –10 and 0 m) based on 2014 

survey. B, Example profile showing changes in beach and nearshore morphology along survey line 090 (location 

shown in A). C, Time-series plot of volume changes calculated for Camp Rilea region; net volume changes are 

provided for beach and nearshore depth zones, as well as net volume changes integrated over entire region. 

Abbreviations: km, kilometer(s); m, meter(s); Mm3, million cubic meter(s).

although the position of the bar was slightly offset between 

these years. The changes in the positions and morphology of 

the bars in the Camp Rilea region did not lead to significant 

net volume change in the nearshore. Net accumulation 

observed along the beaches was primarily caused by seaward 

progradation of the dune. The position of the dune crest 

migrated seaward approximately 10 m during the study period, 

and the height of the dune crest increased by more than 1 m. 

Integrated Net Volume Change

Significant net volume change was observed at the 

regional scale (across several kilometers) for some regions 

within the CRLC (fig. 20; table 3). The largest regional 

changes were in the vicinity of the two maintained inlets of 

Grays Harbor and the mouth of the Columbia River. A total 

of 2.2±0.7 Mm3 of sediment accumulated within the Westport 

region on the south side of Grays Harbor inlet between 2014 

and 2019 (440,000 m3/yr). Similarly, on the south side of the 

Columbia River inlet, 1.8±1.0 Mm3 of sediment accumulation was observed (360,000 m3

/yr) within the South Jetty 

region. Erosion was observed on the north side of both of 

the maintained inlets, although net volume change in Ocean 

Shores (on the north side of Grays Harbor) was not above the 

uncertainty threshold (–0.5±1.0 Mm3). Throughout the entire 

CRLC survey area, the only significant regional erosion pattern was observed at Benson Beach (on the north side of the 

Columbia River) (fig. 20). A total of 2.1±0.8 Mm3 of sediment 

eroded from the Benson Beach region between 2014 and 2019 

(420,000 m3/yr). Farther from the inlets, no significant changes 

in regional sand volume were observed over the study period, 

although the trends are largely consistent over time. The trends 

may become significant during future monitoring or if our 

conservative approach to quantifying uncertainty is refined 

(for example, distinguishing between systematic and random 

errors in the datasets).
24 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure 20. Integrated cumulative net volume changes in 2015, 2016, 2017, 2018, and 2019 for each region having intensive 

sampling (see table 3 for data). Map (A) shows locations of intensive sampling regions within each subcell. Time-series 

plots show integrated net volume changes for regions within North Beach (B), Grayland Plains (C), Long Beach (D), and 

Clatsop Plains (E) subcells. Colors of rectangles in A correspond to colors of dots in plots in B–E. Abbreviations: km, 

kilometer(s); Mm3, million cubic meter(s).

Table 3. Integrated cumulative net volume changes for each intensively sampled region between 2014 and 2019.

[Estimated uncertainty is in integrated net volume change values; yellow cells indicate erosion (that is, volume changes values are greater than uncertainty 

values); blue cells indicate deposition (that is, volume changes values are less than uncertainty values). Subcells: CP, Clatsop Plains; GP, Grayland Plains; 

LB, Long Beach; NB, North Beach. Other abbreviations: ha, hectare(s); Mm3, million cubic meters; N, number of profiles within each region. See fig. 20 for 

locations of each region and plots of values]

Subcell Region Surface area 

of region (ha) N Uncertainty(±Mm3)

Integrated net volume change (Mm3)

2015 2016 2017 2018 2019

NB Ocean City 0.40 21 1.19 0.43 0.63 0.61 0.65 0.86

NB Ocean Shores 0.38 20 0.95 –0.61 –0.40 –1.10 –0.78 –0.47

GP Westport 0.32 17 0.69 0.69 1.80 2.66 2.41 2.16

GP Grayland 0.36 17 0.87 0.03 –0.33 –0.31 –0.54 –0.67

LB Oysterville 0.40 20 1.07 0.13 0.40 0.07 –0.11 –0.32

LB North Head 0.19 11 0.37 0.12 0.45 0.46 0.03 –0.06

LB Benson Beach 0.37 24 0.75 –0.91 –1.40 –1.59 –1.72 –2.06

CP South Jetty 0.40 21 0.95 0.62 0.71 1.56 2.18 1.82

CP Camp Rilea 0.40 21 0.97 0.16 0.32 0.20 0.43 0.40
Task 1 – Observations of Coastal Change 25

Discussion

Environmental Forcing 

The Eastern North Pacific Ocean is well known for strong 

seasonal variations in environmental forcing caused by largescale fluctuations in the positions of high- and low-pressure 

systems over the Eastern Pacific Ocean and North American 

continent (Mass, 2008). In the winter, the position of the East 

Pacific Low shifts to the south, resulting in increased storm 

frequency and magnitude. Strong southerly winds during 

winter storms produce large waves and downwelling that is 

partly responsible for elevating mean water levels along the 

coast during the winter months (Jay and others, 2015). Rainfall 

associated with winter storms leads to higher river discharge 

and increased sediment flux from many smaller streams 

along the coast, although dams along the Columbia River 

have dramatically altered its natural hydrologic cycle. These 

seasonal variations in meteorological and oceanographic 

processes result in a predictable sediment exchange between 

the beach and nearshore (for example, Ruggiero and others, 

2005). Less well understood are the effects of interannual 

changes in environmental conditions on beach and nearshore 

morphodynamics and sediment volume change. In this 

section, we examine the observed sediment volume change 

in relation to interannual variations in environmental forcing 

conditions (for example, fig. 3) to better understand the factors 

responsible for erosion and deposition along the coast.

The El Niño–Southern Oscillation (ENSO) is a primary 

factor responsible for large scale, interannual changes 

in sea-level pressure and atmospheric forcing across the 

equatorial Pacific. The monitoring period that encompasses 

this study included the 2015–16 ENSO event, one of the 

strongest in recorded history (Barnard and others, 2017). 

During the winter of the 2015–16 ENSO, wave energy was 

approximately 50 percent greater than average, and mean 

water levels were elevated by more than 10 cm, resulting in 

widespread, enhanced seasonal erosion of beaches throughout 

the Pacific basin, including the CRLC (Barnard and others, 

2017). However, our annual observations, which we collect 

during the summer, did not show that enhanced beach erosion 

occurred during the 2015–16 ENSO event (fig. 20). Instead, 

many of the beaches gained volume between the 2015 and 

2016 surveys, suggesting that the sediment that eroded from 

beaches in the winter of 2015–16 during the erosive ENSO 

conditions remained in the littoral system and that the beaches 

had recovered before our survey in the summer of 2016. 

Furthermore, large-scale beach rotations (that is, oscillations 

in beach volume between the north and south ends of embayed 

beaches) commonly have been observed elsewhere during 

strong ENSO events (for example, Ranasinghe and others, 

2004). Typical ENSO winters in the Pacific Northwest are 

characterized by larger, more northward directed waveenergy flux (Barnard and others, 2015) that result in gradients 

in longshore transport, causing erosion at the south end of 

the beach and accumulation at the north end (for example, 

Anderson and others, 2018). However, the 2015–16 ENSO 

was peculiar in that the direction of wave-energy flux was 

similar to the 20-yr mean in the Pacific Northwest (Barnard 

and others, 2017). The lack of a wave direction anomaly 

is consistent with our observations of beach and nearshore 

volume change that show no strong evidence for large-scale 

beach rotation after the 2015–16 ENSO winter.

Sediment Supply

Interannual variations in the supply of fluvial sediment 

may be an important factor that contributed to the erosion of 

Benson Beach, the only region in the study area that had net 

sediment erosion above the uncertainty threshold (fig. 20). 

Although the construction of dams on the Columbia River has 

drastically altered its natural hydrologic cycle and reduced 

sediment supply to the coast (Sherwood and others, 1990), 

model simulations presented in Task 2 suggest the system 

is capable of exporting sand-sized sediment during high 

discharge conditions. The rate of erosion at Benson Beach was 

highest between 2014 and 2016, a time period that coincides 

with drought conditions that affected much of the western 

United States. Although the drought in the Columbia River 

drainage basin was not as severe as that in California to the 

south, anomalously high temperatures throughout the western 

states led to record low snow pack (Mote and others, 2016), 

reduced river discharge in the lower Columbia River (fig. 3), 

and presumably lower sediment flux from the Columbia River 

to the coast. Owing to its proximity to the Columbia River 

mouth and connectivity to the fluvial source (see results from 

Task 2), Benson Beach would likely be most directly impacted 

by short-term changes in fluvial sediment delivery from the 

Columbia River.

Dredging

Although natural variations in wave forcing and 

fluvial sediment delivery may contribute to the observed 

net accretion at the south sides of Grays Harbor and the 

Columbia River, the presence of dredge-placement areas in 

both of these regions suggests that increasing the sediment 

supply by placing dredged material in the nearshore is an 

effective approach for regional sediment management. The 

effects of dredge placement are particularly apparent in 

the Westport region where net accumulation was enhanced 

directly onshore of the dredge-placement site (fig. 11). Both 

nearshore dredge-placement areas in proximity to the Westport 

and South Jetty regions are located offshore of our survey 

lines (with some minor overlap; see figs. 11, 18), suggesting 

that waves and tides effectively disperse sediment onshore 

from the placement areas into the nearshore zone (and into 

our survey area). Repeat surveys performed by the USACE 

between 2009 and 2017 have suggested that 70 percent of the 

2.5 Mm3 of sediment placed within the nearshore placement 
26 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

site at Westport was dispersed away from the placement area 

(David Michalsen, 2019, USACE, written commun.), thereby 

enhancing the coastal sediment budget by as much as 215,000 

m3/yr. Assuming similar volumes of sediment placed during 

the time period of this study, dredging can account for about 

50 percent of the net accumulation (440,000 m3/yr) that was 

observed in the Westport region. The connection between the 

enhanced sediment budget from nearshore dredge placements 

and the volume changes along intertidal and subaerial 

elevations is less clear, particularly at Westport where the 

southern part of the beach has continued to erode (fig. 11). 

More research is needed to identify the physical processes 

and time scales associated with transport between nearshore 

placement sites and adjacent beaches. There may be a lag time 

of several years between the time of sediment accumulation 

in the nearshore and that of shoreline progradation, as was 

observed for the massive increase in sediment supply to the 

coast following dam removals on the Elwha River (Warrick 

and others, 2019). 

The placement of dredged material likely contributed 

to the observed net accumulation on the south side of the 

Columbia River in the South Jetty region (1.8±1.0 Mm3) 

between 2014 and 2019. Approximately 1.2 Mm3 of sediment 

was placed within the nearby South Jetty Site (SJS) dredgeplacement area over the same time period (USACE, 2019). 

Note that, owing to the timing between the nearshore surveys 

and dredge placements, the total volume of dredged material 

placed within the SJS was calculated using annual totals 

between 2014 and 2018. Repeat bathymetric surveys of the 

SJS by the USACE suggest that only a small percentage 

of the sediment placed within the SJS remained within the 

site boundaries (13 percent between 2012 and 2018). The 

sediment placed within the SJS likely was dispersed landward, 

enhancing the coastal sediment supply. This analysis suggests 

that about 1 Mm3 of the 1.8±1.0 Mm3 observed within the 

South Jetty region can be directly attributed to the beneficial 

use of sand dredged from the MCR. 

In contrast to the accumulation observed on the south 

sides of Grays Harbor and Columbia River inlets, severe 

erosion was observed between 2014 and 2019 at Benson 

Beach on the north side of the Columbia River (fig. 16). 

During the same time period, approximately 6.3 Mm3 of 

sediment was placed within nearshore sites on the north side of 

the Columbia River navigation channel during the monitoring 

period (USACE, 2019). Most (82 percent) of this sediment 

was placed within the Shallow Water Site (SWS) to enhance 

the coastal sediment budget north of the inlet. The SWS is 

much more dispersive than the SJS, with less than 2 percent 

of the approximately 33 Mm3 of sediment placed within the 

SWS between 1997 and 2018 being retained (USACE, 2019). 

Despite the placement of large quantities of dredged material 

within the SWS and the efficient dispersal away from the 

placement area, nearby Benson Beach eroded 2.1±0.8 Mm3

between 2014 and 2019. The enhanced sediment supply from 

dredge placement has not been sufficient to reverse the trend 

of erosion in that region. Our results suggest that additional 

nourishment is needed to mitigate the 420,000 m3/yr deficit 

in sediment supply to the Benson Beach region and reverse 

the steady erosional trend. The persistent erosion—even with 

enhanced sediment supply—highlights the need for efficient 

delivery of sediment from the nearshore dredge-placement 

sites to the eroding beach and nearshore areas. In Task 2 of 

this study, we present results of a hydrodynamic and sedimenttransport model that was constructed to identify sedimenttransport pathways in the vicinity of the MCR, to identify the 

most advantageous locations for nearshore nourishment.

Task 2 – Hydrodynamic and SedimentTransport Modeling

In this section, we describe the application of a coupled 

Delft3D-SWAN hydrodynamic, wave, and sediment-transport 

model (fig. 21) to quantify the sediment linkages between 

the MCR and adjacent open coasts of the Long Beach 

peninsula and Clatsop Plains. Hydrodynamic and sedimenttransport modeling at the MCR is challenging owing to the 

interaction of strong tidal currents and highly variable density 

stratification, as well as the importance of waves and wavecurrent interaction, of tidal asymmetry and related mean 

flow in the system, and of wetting and drying of large tidal 

flats and wetlands in the lower estuary. Previous research 

has demonstrated that process-based models applied to 

the Columbia River system are able to accurately simulate 

important processes such as density stratification (for example, 

Figure 21. Schematic 

representation of Delft3D 

modeling system.
Task 2 – Hydrodynamic and Sediment-Transport Modeling 27

Karna and others, 2015) and wave-current interaction (Elias 

and others, 2012; Akan and others, 2017). For this study, the 

hydrodynamic-model application was adapted from Elias and 

others (2012). The model grid and boundary conditions were 

modified and the sediment-transport module was activated to 

simulate hydrodynamics and sediment transport. Additional 

analyses were performed on the calculated sediment-transport 

fields using the Sediment Pathway Interactive visualization 

Tool (SPIT) developed as part of this study to visualize 

sediment-transport pathways and to identify the linkages 

between the MCR, nearshore dredge-placement sites, the 

North Head study area, and adjacent coastlines. 

The next sections describe the implementation of the 

Delft3D modeling system and SPIT postprocessing analysis. 

Additional information on the Delft3D modeling system, 

including testing and validation of the Delft3D Online 

Morphology system, was reported in Lesser and others (2004). 

Van Rijn (2007a, b, c) provided explicit descriptions of the 

sediment transport formulations. 

Model Application

Delft3D Flow 

The hydrodynamic- and sediment-transport-model 

domain consisted of a structured, orthogonal, curvilinear, 

43,356-cell grid that covered the ocean, estuary, and river 

domain (fig. 22). The ocean domain had a maximum grid-size 

of 2 km2 along its seaward boundaries. The grid resolution 

between North Head and the MCR was variable (15 to 100 

m) in the along-shore direction and 50 m in the cross-shore 

direction. Ten equally spaced vertical sigma layers were used 

to simulate 3D effects within the model domain. The grid was 

aligned with coastal engineering structures, including the three 

primary jetties, as well as several training dikes in the vicinity 

of Baker Bay, Wash. Flow through the structures was limited 

in the model by using thin dams (no transmission) or dry 

points. The spatial extent of the grid extends from the MCR 

roughly 150 and 100 km to the north and south, respectively. 

Figure 22. A, Map showing hydrodynamic (red lines) and wave (blue lines) model grids used to simulate sediment transport in 

Columbia River estuary and at mouth of Columbia River; also shown are detailed hydrodynamic model grids for Columbia River 

estuary (B), and mouth of Columbia River (C) (grid resolutions in B and C were reduced by factor of three for display). Abbreviations: 

CDIP, Coastal Data Information Program; km, kilometer(s); NOAA, National Oceanic and Atmospheric Administration.
28 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

This large domain was needed to prevent instabilities at the 

ocean boundaries during high-discharge conditions. The 

hydrodynamic and sediment-transport model was run with a 

computational time step of 6 seconds (s).

The model bathymetry is derived from recent datasets, 

including the swath bathymetry collected by the U.S. 

Geological Survey (USGS) in 2013 (Gelfenbaum and others, 

2015b). Additional bathymetric data used in the model include 

swath bathymetry collected by NOAA between 2007 and 2009 

(available at https://maps.ngdc.noaa.gov/viewers/bathymetry/) 

and unpublished single-beam bathymetry collected in 2004 

and 2012 by USACE. A previously published digital elevation 

model of the lower Columbia River (Lower Columbia Estuary 

Partnership, 2010) was used for the tidal river between the 

Astoria Bridge and the fluvial boundary. A regional digital 

terrain model (Love and others, 2012) was used in areas where 

more recent datasets were not available. The source bathymetric 

data were converted to a common horizontal datum (NAD83) 

and to the land-based North American Vertical Datum of 1988 

(NAVD88), then it was projected into the Cartesian UTM Zone 10 

coordinate system (meters). Deep areas associated with the Astoria 

submarine canyon were removed from the model bathymetry to 

improve stability along the oceanic boundaries.

Oceanic boundaries of the MCR model were forced 

using astronomic tidal constituents derived from the TPXO 

7.2 global tide model (Egbert and Erofeeva, 2002). A vertical 

offset of 1.15 m (positive values are up) derived from NOAA 

VDatum (version 3.2; Xu and others, 2010) was applied at the 

oceanic boundary to account for the difference between local 

mean sea level and NAVD88. Water levels in the MCR and 

estuary are influenced by coastal processes such as regional 

upwelling and downwelling events that induce variations 

at subtidal frequencies (for example, Jay and others, 2015) 

and propagate upriver (MacMahan, 2016). Oceanic subtidal 

variations were imposed at the oceanic open boundary as a 

time-varying correction to the astronomic tides. 

The subtidal time-series was derived from observations 

of water levels at NOAA stations 9440910 (Toke Point, 

Wash.) and 9437540 (Garibaldi, Ore.). Water-level timeseries from the two stations were low-pass-filtered using a 

66-hour (hr) cutoff to remove fluctuations at tidal frequencies. 

The low-pass-filtered values from both stations were highly 

correlated, and an average for the two stations was applied 

to the oceanic model boundaries. The landward boundary 

was forced with a time-series of river discharge measured at 

30-minute (min) intervals at USGS gauge 14246900 (http://

waterdata.usgs.gov/usa/nwis/uv?site_no=14246900), located 

at the Beaver Army Terminal near Quincy, Ore. The oceanic 

and fluvial boundaries were prescribed constant salinity 

values of 33 and 0 practical salinity units (psu), respectively. 

The effects of temperature variations on circulation were 

neglected in the present model application. 

Accurate modeling of tidal propagation is essential 

to simulate water-level dynamics in the MCR and its 

surroundings. Tidal propagation into inlets such as the 

Columbia River is modified by bed friction, topographic 

funneling, and opposing river flow. Whereas river flow and 

topographic variability are well represented in the model by 

recent high-resolution inputs, bottom roughness is poorly 

constrained. Bottom roughness was schematized using the 

Manning formulation, which relates bed friction to water 

depth, and it was prescribed during the calibration process 

(described below). Simulated water levels were compared 

against time-series measurements of observed water levels 

during high river-discharge conditions from four locations 

throughout the study area for the time period between May 10, 

2013, and June 16, 2013. The sensitivity of tidal propagation 

to bottom roughness was examined for a range of spatially 

uniform Manning roughness coefficients between 0.0202 

and 0.0234 in a series of five otherwise identical simulations 

(fig.23). We found that a Manning roughness coefficien

of 0.0218 best represented mean water levels and variance 

throughout the domain. The final calibrated model accurately 

simulated water levels at each of the four observation stations, 

with a total RMS value less than 12 cm and an average value 

of 10 cm (table 4).

Using the calibrated model, predictions of currents and 

salinity were compared against time-series measurements at the 

West Tripod Site as part of the Office of Naval Research (ONR) 

sponsored Rivers and Inlets (RIVET) II field experiment 

that was focused on hydrodynamics processes at the MCR. 

Stevens and others (2017) provided data and associated 

metadata that describes the collection and processing of timeseries oceanographic data during the experiment. Qualitative 

comparisons of the current speeds and directions throughout 

the water column sampled with an Acoustic Doppler Current 

Profiler (ADCP) show reasonable agreement with the modeled 

currents at the West Tripod Site during spring tides (fig. 24). 

Additional comparisons between model predictions and field 

data were performed near the seabed at the West Tripod Site, 

where measurements of currents were acquired at 0.6 m above 

the bottom using an Acoustic Doppler Velocimeter (ADV) 

and also measurements of salinity were made at 1.8 m above 

the bottom using a Conductivity Temperature Depth (CTD) 

probe. Peak current speeds near the seafloor of more than 2 

m/s, which were observed during ebb tides, were captured 

accurately in model simulations. The direction of near-bed 

currents was generally well represented by the model (fig. 25). 

A larger discrepancy between model and data was observed 

during the part of the tidal cycle that corresponds to the daily 

falling tide (between lower high water and higher low water). 

During this tidal phase, modeled current speeds are too high; 

currents are directed offshore for too long, and salinity remains 

high relative to the observations. 

Wave Model

The spectral wave model SWAN (version 40.72ABCDE) 

was applied in stationary, third-generation mode to propagate 

waves from the continental shelf to the coastline. SWAN 

simulates the evolution of wave action density using the 

action balance equation (Booij and others, 1999). The wave 
Task 2 – Hydrodynamic and Sediment-Transport Modeling 29

Figure 23. Modeled sensitivity of simulated 

water levels to variations in bed friction. A, Map 

showing center of main tidal channel (black 

line) and locations of observation stations (red 

dots) used for model calibration; black numbers 

along line correspond to river kilometers (rkm) 

in B and C. B, Comparison of modeled and 

measured mean water levels during 1.5-month 

simulation for various values of bed friction; 

colored lines indicate Manning roughness 

coefficients used in model. C, Comparison of 

modeled and measured water level variance 

during same 1.5-month simulation as in B. Other 

abbreviations: CDIP, Coastal Data Information 

Program; km, kilometer(s); m, meter(s); n, 

coefficient; NOAA, National Oceanic and 

Atmospheric Administration.

model takes into account propagation in geographical space, 

depth- and current-induced refraction, and shifting of the 

intrinsic frequency owing to variations in mean current 

and depth, as well as generation (by wind) and dissipation 

(by breaking) of waves. Waves were simulated on a grid 

that covered part of the flow grid (see fig. 22) to improve 

computational efficiency of the coupled model. The seaward 

open boundary approximately intersects the location of 

Coastal Data Information Program (CDIP) buoy 179. The 2D, 

spatially uniform, time-varying energy spectra derived from 

measurements at CDIP buoy 179 were used to force the wave 

model. Interaction between the wave model and flow model 

in the Delft3D modeling system involves a two-way coupling 

of a nonstationary hydrodynamic calculation, in combination 

with regular stationary-wave simulations. SWAN was 

activated every 30 min during the hydrodynamic simulation, 

and, using the water levels and depth-averaged currents passed 

from the flow model, performed a stationary wave simulation.

Wave-parameter settings were based on those reported in 

Elias and others (2012), who performed extensive calibration 

of the SWAN wave model in the MCR. The best agreement 

between modeled and observed wave conditions was found 

using the default JONSWAP bottom-friction value for swell 

propagation of 0.038 m2 and dissipation by whitecapping 

using the Westhuysen (2007) formulation; 37 frequency bins 

between 0.03 and 1 Hz were used, along with 72 directional 

bins that covered 360°. Convergence criteria were set to 99 

percent of cells and a maximum of 50 iterations to obtain full 

convergence for all wave cases.

The influence of different wind-input forcings on 

modeled wave parameters was assessed as part of the SWAN 

model calibration. Three wind-input cases were examined, 

including (1) no wind, (2) time- and space-varying wind, 

based on the National Centers for Environmental Protection 

(NCEP) and National Center for Atmospheric Research 

(NCAR) reanalysis project (NNRP) (Kalnay and others, 
30 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Table 4. Error metrics describing sensitivity of simulated water levels to variations in bed roughness at four observation stations; for

each station and model simulation, mean bias, bias-corrected root mean square error, and total root mean square error are provided.

[Definitions of error metrics from Joliff and others (2009). See figure 23 for locations of tide stations. Abbreviations: cm, centimeter(s); RMS, root mean square]

Error metric Manning roughness 

coefficient

Total error (cm)

Astoria Skamakawa Wauna Beaver

Mean bias

0.0202 0.07 0.04 0.08 0.12

0.0210 0.06 0.01 0.05 0.07

0.0218 0.06 0.00 0.03 0.04

0.0226 0.05 –0.02 0.00 –0.01

0.0234 0.04 –0.04 –0.03 –0.05

Bias-corrected 

RMS error

0.0202 –0.10 –0.09 –0.10 –0.14

0.0210 –0.09 0.08 0.09 –0.11

0.0218 0.09 0.09 0.11 –0.09

0.0226 0.09 0.10 0.13 0.09

0.0234 0.10 0.12 0.15 0.11

Total RMS error

0.0202 0.12 0.10 0.13 0.19

0.0210 0.11 0.08 0.11 0.13

0.0218 0.11 0.09 0.11 0.10

0.0226 0.11 0.10 0.13 0.09

0.0234 0.11 0.12 0.15 0.12

Figure 24. Comparison 

of measured (“data”) 

and modeled current 

speeds and directions 

at West Tripod Site (see 

fig. 2 for location), in 

4-day time period during 

spring tides. Speeds and 

directions measured 

between 2.9 meters 

above bottom (mab) and 

water surface, using 

Acoustic Doppler Current 

Profiler (ADCP). A, Water 

levels, as measured 

throughout entire Rivers 

and Inlets (RIVET) II field 

experiment; gray shading 

corresponds to time 

period depicted in B–E. 

B, Measured current 

speeds. C, Measured 

current directions. 

D, Modeled current 

speeds. E, Modeled 

current directions. 

Other abbreviations: m, 

meter(s); s, second.
Task 2 – Hydrodynamic and Sediment-Transport Modeling 31

Figure 25. Comparison of modeled and measured (“data”) water levels (A), current 

speeds (B), current directions (C), and salinity (D) near seabed at West Tripod Site (see fig. 

2 for location), in same 4-day time period during spring tides as in figure 24. Abbreviations: 

m, meter(s); psu, practical salinity unit(s); s, second.
32 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

1996) and 12-km spatial resolution, and (3) time-varying 

but spatially uniform wind derived from measurements at 

National Data Buoy Center (NDBC) buoy 46029. The time 

period of October 18 to November 18, 2010, was selected 

for the sensitivity tests, on the basis of the relatively large 

wave-forcing conditions and availability of continuous wind 

data. The NNRP–modeled time-and-space-varying wind fields 

showed good agreement with wind measurements collected at 

NDBC buoy 46029 (fig. 26). Bulk wave parameters for three 

SWAN wind scenarios were compared to wave observations 

collected at CDIP wave buoy 162, located just offshore, 

and to the south, of the MCR (fig. 22). The model scenario 

that used time-and-space-varying wind fields improved 

the predictions of wave heights, reducing the bias by 20 

cm compared to simulation without wind input (fig. 27). 

Differences in wave heights between the uniform-wind and 

the time-and-space-varying-wind scenarios were nominal. 

Other wave parameters (peak period, wave direction) were 

less sensitive to wind input. All three wind-model setups 

underestimate the energetic conditions observed on October 

25, 2010, when the significant wave height at CDIP wave 

buoy 162 exceeded 9 m. Additional sensitivity tests to 

Figure 26. Time-series plots of 

modeled and measured (“Obs.”) 

wind speed (A), wind direction

(B), significant wave height (Hsig) 

(C), peak wave period (Tpeak) (D), 

and wave direction (E) between 

October 18 and November 

18, 2010. Model predictions 

from National Centers for 

Environmental Protection and 

National Center for Atmospheric 

Research reanalysis project 

(NNRP) shown in A and B were 

used force wave model for timeand-space-varying wind-input 

scenario. Comparisons between 

modeled and measured wave 

parameters in C–E show three 

wind-input scenarios: no wind, 

time-and-space-varying wind 

(“Space-varying”), and timevarying but spatially uniform 

wind (“Uniform”). Other 

abbreviations: deg, degree(s); m, 

meter(s); s, second(s).
Task 2 – Hydrodynamic and Sediment-Transport Modeling 33

Figure 27. Comparison of modeled and measured wave parameters between October 18 and 

November 18, 2010. Scatter plots show three wave parameters: A, significant wave height (Hsig); C, 

peak wave period (Tpeak); E, wave direction. Modeled wave parameters in scatter plots show three 

wind-input scenarios: no wind, time-and-space-varying wind (“Space-varying”), and time-varying but 

spatially uniform wind (“Uniform”). Target diagrams (B, D, F) (for example, Joliff and others, 2009) are 

provided for each scatter plot. Other abbreviations: deg, degree(s); m, meter(s); RMSD’, bias corrected 

root mean square deviation; s, second(s).
34 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

model input parameters that dissipate wave energy, such as 

whitecapping, depth-induced breaking, and bottom friction, 

are needed to resolve the observed underestimation of wave 

heights during extreme wave events.

Sediment-Transport Model

The online morphology addition to Delft3D was used 

to simulate sediment transports in the flow domain at each

computational time step (Lesser and others, 2004). The 

TRANSPOR2004 transport equations, which were used 

to model the movement of noncohesive sand fractions, 

are implemented in the Delft3D flow solver. The Delft3D

implementation of this formulation follows the principle 

description of Van Rijn (2007a, b, c), which separates the 

sediment transport into suspended and bed-load components. 

Suspended-sediment transport, which is computed by the 

advection-diffusion equation, includes the effect on fluid

density of sediment in suspension. Bed-load transports 

represent the transport of sand particles in the wave boundary 

layer in close contact with the bed surface, and they include 

an estimate of the effect of wave orbital-velocity asymmetry. 

The bed was schematized as a single sediment fraction, using 

a median diameter (d50) of 200 micrometers (μm) with 

unlimited supply. Holding the bed level constant in the model 

(to prevent feedback between the flow and changing bed

level) was done to isolate the role of the changing flow on the

sediment-transport patterns that result from the interaction 

with the observed morphologic features.

Sediment Pathways Interactive Visualization 

Tool (SPIT)

Background

The Sediment Pathways Interactive visualization Tool 

(SPIT) was developed to visualize, identify, and analyze the 

pathways along which sand-sized sediment was transported 

during the coupled hydrodynamic- and sediment-transportmodel simulations. The SPIT model computes the Lagrangian 

pathways that idealized particles travel as they pass through 

a changing vector field. SPIT was adapted from the mDrift 

particle-tracking model described in Storlazzi and others 

(2017) to simulate transport of sediment rather than coral 

larvae. Existing approaches to sediment-particle tracking (for 

example, Deltares, 2016) use velocity fields coupled with 

simple formulas to govern sediment entrainment and settling 

thresholds that are based on critical shear stresses. This often 

greatly simplifies the processes of sediment transport, as key 

behaviors such as particle settling may be neglected.

The main difference between SPIT and existing particletracking methodologies (for example, MacDonald and others, 

2006; Soulsby and others, 2011) is that SPIT uses sedimenttransport vector fields derived from a transport formula that 

has been developed and rigorously tested for noncohesive 

(sandy) sediment transport (Van Rijn, 2007a, b, c) and 

computed at each computational time step in Delft3D. Mass 

fluxes of sediment calculated in a Delft3D simulation were 

converted to an equivalent volume flux by dividing by the bulk 

density of the sediment (Equation 1):

 , (1)

where

Sm is mass flux;

Sv is volume flux; and

ρb is bulk density.

The resulting flux is equivalent to that of sand volume per unit 

width of a given grid cell face or transect, passing that point 

per second (fig. 28). The volumetric flux is converted into an 

effective velocity for transporting particles by dividing by a 

length scale (Equation 2): 

, (2)

where

utr is effective velocity; and

htr is length scale.

For a realistic approximation of particle motion, the 

length scale should be related to a representative height in 

the water column over which material is transported and 

varies depending on the mode of transport. In the case that 

we are interested in, the maximum potential motion along 

a pathway for a particle in space, the time scale may be of 

secondary interest. In that case, for visualization purposes, this 

length scale factor can be adjusted to increase rate of particle 

motion because sediment-transport rates often are very small 

in magnitude. The length-scale factor can only be adjusted 

until the critical value where particle trajectories begin to 

diverge with changes in length scale; this critical value can be 

determined through sensitivity testing.

Application of SPIT to the Mouth of the Columbia 

River 

To assess the sediment pathways at the MCR, we 

simulated particle trajectories from 500 initial locations (or 

sources) throughout the model domain. The initial source 

locations were determined using k-means cluster analysis 

(Davis, 2002) that was based on a weighted combination 

of XY-coordinates and depth below mean sea level. This 

methodology resulted in a set of sources that was distributed 

throughout the model domain but provided finer detail in areas 

that had greater bathymetric complexity (fig. 28). The total 

number of sources was chosen to deliver sufficient resolution in 

the areas of interest while also being computationally feasible. 

Sv = sm

ρb

=

kg

m⋅s

⎡

⎣

⎢ ⎤

⎦

⎥

kg

m3

⎡

⎣

⎢ ⎤

⎦

⎥

= m3

m⋅s

⎡

⎣

⎢ ⎤

⎦

⎥ = m2

s

⎡

⎣

⎢ ⎤

⎦

⎥

utr = sv

htr

=

m2

s

⎡

⎣

⎢ ⎤

⎦

⎥

⎡

⎣m⎤⎦

= m

s

⎡

⎣

⎢ ⎤

⎦

⎥
Task 2 – Hydrodynamic and Sediment-Transport Modeling 35

Figure 28. Maps showing Sediment Pathways Interactive visualization Tool (SPIT) visualizations of Lagrangian 

sediment-transport pathways showing (A) sediment vector fields (blue arrows), (B) streamlines representing 

vector fields (blue lines), (C) initial positions of sediment sources (white dots), and (D) sediment pathways 

(colored lines) derived from SPIT analysis. Lengths of vectors in A are scaled to length of blue arrow (1.3x10–3

m3/s/m) in upper left corner. Black dots in D indicate initial position (same as white dots in C) of sediment source; 

color of sediment pathway indicates relative mobility of source). Here, we define relative mobility as relative 

distance each source particle travels during simulation. Black boxes show locations of dredge-placement sites. 

Other abbreviations: km, kilometer(s); m, meter(s); s, second.
36 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

To capture temporal variations in sediment transport (for 

example, over the course of a tidal cycle), the 10-min mean 

total (bed load plus suspended load) sediment transport was 

calculated from the cumulative mean total transport from 

Delft3D simulations. One particle was released at each source 

location in the initial timestep. Although particle-tracking 

models are often highly sensitive to the choice of initial 

timestep (for example, consider the release of a particle at the 

ebb versus flood stages of a tidal cycle), the effective particle 

velocities (utr) in this case were sufficiently small such that the 

precise release time did not affect their ultimate trajectories. 

Numerical accuracy was maintained using a 4th-order 

Runge-Kutta scheme and a computational timestep of 60 s. 

Particle positions were stored every hour to enable the tracking 

of particle positions over tidal time scales. A transport height 

scale (htr,) value of 0.1 m was chosen to increase the rate of 

particle motion in a given timestep. Note that this htr value 

basically converts the sediment-transport flux into a velocity 

that is 10 times the size of the flux. To account for the random 

motion of particles, a normally distributed perturbation with 

zero mean and a standard deviation of 0.1 was applied. This 

corresponds to a random motion equal to 10 percent of the 

particle’s travel distance in a given timestep.

Modeling Approach

The modeling approach for this study involved two 

sets of model simulations, performed using the calibrated 

and validated MCR model (fig. 29). The first simulations 

(Method 1) were forced with time series of observed waves, 

wind, and discharge conditions over relatively short timeframes 

(1–2 months) to characterize detailed hydrodynamics and 

sediment transport at the event time scale. The results from 

these simulations provide synoptic, realistic estimates of 

wave heights, currents, and sediment transports that have high 

spatial and temporal resolution over the entire inlet domain. 

Analysis of these data can provide valuable information 

on governing flow and sediment-transport patterns in the 

areas that do not contain observation stations. Varying the 

forcing conditions and analyzing the response of the sediment 

Figure 29. Flow chart showing modeling approaches (Methods 1 and 2) applied during this study (MCR, Columbia River mouth).
Task 2 – Hydrodynamic and Sediment-Transport Modeling 37

transports in these model simulations allows for identification 

of the dominant processes responsible for sediment movement 

(for example, Elias and Gelfenbaum, 2009). 

Two time periods were selected to analyze sediment 

transports using Method 1. The first time period—between 

October 18 to November 18, 2010—was selected because 

it contained relatively large waves that had maximum wave 

heights of more than 9 m. The second time period—between 

September 20 and December 1, 2018—coincided with the pilot 

placement of dredged material at the North Head study area. 

A second set of simulations (Method 2) was constructed 

to determine the annual exchange of sediment between the 

MCR, ebb-tidal delta, and adjacent coastal areas. Annually 

averaged predictions of the sediment budget require 

simulations that characterize the complete range of forcing 

conditions to create representative sediment-transport patterns. 

Such simulations are computationally unfeasible given the 

spatial extent of the model and the resolution required in the 

areas of interest. Therefore, input-reduction techniques (for 

example, Vriend and others, 1993; Lesser, 2009) were used to 

make such simulations feasible (fig. 29, Method 2). 

Morphodynamic schematizations of boundary conditions 

were derived for wave, tidal, and fluvial forcing to reduce the 

number of conditions needed to represent annual sedimenttransport patterns and magnitudes. Lesser (2009) provided a 

comprehensive description of input-schematization techniques 

for the neighboring Willapa Bay inlet and demonstrated that 

schematized model inputs can be used for medium-term 

(3–5 yr) morphodynamic predictions. The wave-climate 

schematization described in Lesser (2009) was based on a 5-yr 

timeframe (1998–2003) in which the winter and summer seasons 

are grouped separately (table 5). A total of 19 wave classes 

were chosen to represent the morphological impact of all wave 

conditions that occur during the year. Winter-season waves are 

grouped into 12 discrete classes of wave heights and directions 

and their associated probabilities of occurrence; summerseason waves are grouped into seven such classes. Willapa Bay 

and Columbia River are exposed to a similar wave climate from 

the northeastern Pacific Ocean; therefore, we utilized the same 

wave climate schematization as described in Lesser (2009).

The objective of tidal-input schematization using a 

morphological tide is to replace the complex time-series of 

tidal water-level and current fluctuations occurring in nature 

with a simplified tide (or tides) (Lesser, 2009). Gelfenbaum 

and others (2017) described the construction of morphological 

tides for the Columbia River. To investigate the influence of 

Table 5. Specifications of wave classes used in morphological wave-climate schematizations, subdivided into winter and 

summer conditions.

[Schematization from Lesser (2009). Abbreviations: deg, degree(s); m, meter(s); s, second(s)]

Wave class Significant wave 

height (m)

Peak wave 

period (s)

Wave direction 

(deg) Wind speed (m/s) Wind direction (deg) Probability (%)

Winter conditions

1 1.00 10.2 279 4.2 196 5.0

2 2.28 8.6 216 8.2 176 2.0

3 2.29 10.0 241 6.0 176 2.0

4 2.16 11.4 262 4.9 156 4.5

5 2.16 13.0 278 3.6 155 9.9

6 2.06 11.4 294 2.5 195 10.4

7 3.88 10.1 224 10.3 201 3.0

8 3.87 12.2 257 7.5 205 3.5

9 3.79 13.9 278 5.5 199 4.5

10 3.71 13.4 291 5.8 201 2.5

11 5.76 12.9 241 12.0 207 1.0

12 5.9 15.1 281 8.7 216 1.0

Summer conditions

13 0.7 9.8 271 2.94 343 3.0

14 1.67 8.4 221 5.8 198 2.5

15 1.58 9.9 259 2.88 284 6.0

16 1.64 10.4 281 3.66 329 14.1

17 1.53 8.6 300 5.02 334 16.6

18 3.5 10.7 241 8.56 190 3.5

19 3.38 13.2 284 4.06 267 5.0
38 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

river discharge on morphological tide selection, Gelfenbaum 

and others (2017) selected two time periods representing highand low-discharge conditions when extensive field campaigns 

were performed. Average discharge during the 2005 USACE 

Mega-transect experiment (Elias and others, 2012) was 

4,000 m3/s and, during the 2013 ONR RIVET II experiment 

(Stevens and others, 2017), was 8,000 m3/s. For each time 

period, a Delft3D model simulation forced by tides on the 

open-ocean boundary, and the measured discharge at the 

Beaver Army Terminal was performed over an approximately 

6-week timeframe. All other parameter settings and boundary 

conditions between the high- and low-discharge scenarios. The 

results of a spatially explicit correlation analysis showed that a 

single representative tide can be selected to accurately model 

sediment transport over a full spring-neap cycle during both 

low and high river flow. However, no clear correspondence 

in the characteristics of the two selected tides (for example, 

asymmetry, phasing in the spring-neap) was observed. We 

therefore simulated both the high- and low-discharge scenarios 

and associated morphological tides identified by Gelfenbaum 

and others (2017) and investigated the sediment transports and 

pathways separately. 

A total of 38 simulations were performed to calculate the 

average annual sediment fluxes for high- and low-discharge 

scenarios. For each discharge scenario (2) and wave class (19) 

in the wave schematization, a 50-hr simulation was performed. 

The transports from each wave class were scaled by their 

probability of occurrence (table 5) and summed to yield the 

average annual sediment flux. Additional scenarios that have 

no wave forcing and no salinity variations were also simulated 

to investigate sediment-transport potential from tides alone 

and the influence of density stratification on sediment 

transport. Sediment-transport pathways from each simulation 

were computed over a time period of 365 days using SPIT and 

total-transport vector fields saved at 10-min intervals. Output 

from the 50-hr Delft3D simulations were looped cyclically 

over the 365-day duration of the SPIT timeframe.

Results and Discussion

Method 1—Event Time Scales

Variations in wave conditions and tidal forcing during 

the time period of October 18 to November 18, 2010, resulted 

in complex spatial patterns and magnitudes of sediment 

transport in the MCR, its ebb-tidal delta, and along its adjacent 

shorelines (fig. 30). Note that this time period was used to 

validate the model predictions of wave parameters as shown 

in figures 26 and 27. Large waves from the west-southwest 

(fig.30A) resulted in onshore and northward transport o

sand-sized sediment at locations north of the inlet, including 

the North Head study area. At the same time, strong ebbtidal currents within the inlet, combined with enhanced shear 

stress from waves, produced a large flux of sediment from 

the MCR to the ebb-tidal delta. Neap tides and lower wave 

energy originating from the southwest resulted in northward 

transport along the beaches north and south of the inlet but 

little transport within the MCR (fig. 30B). Despite relatively 

weak tidal forcing, larger waves from the west were capable 

of causing sediment export from the inlet during ebb tide 

(fig. 30C). Transport directions reverse from offshore to 

onshore within the Shallow Water Site dredge-placement area. 

Waves approaching the inlet from the west refract around 

the complex bathymetry of the ebb-tidal delta, resulting in 

northward sediment flux along Benson Beach and the Long 

Beach peninsula. Smaller waves from the northwest move 

sediment southward along the beaches, but relatively weak 

tidal forcing is insufficient to transport much sediment within 

the inlet (fig. 30D). The results of this simulation suggest 

that waves are the dominant process at the North Head study 

area, and they influence sediment transports in the MCR by 

increasing bed-shear stresses and enhancing sediment export 

onto the ebb-tidal delta. 

Approximately 40,000 m3 of sand dredged from the 

MCR was placed within the North Head study area during a 

pilot program between September 19 and 21, 2018 (USACE, 

2019). The dredged sand was placed in the southern part of 

the study area along a northwest-southeast-oriented transect in 

water depths between about 10 and 15 m (fig. 31). The linear 

feature created by the placement was about 75 m wide and 

about 60 cm tall. A simulation was performed to characterize 

the conditions and evaluate the transport of sand-sized 

sediment for 72 days after the pilot placement. Transport 

fluxes during this time period were generally low relative to 

the highly energetic conditions examined in 2010. The model 

simulation suggests that tidal currents alone were not capable 

of resuspending and transporting sand-sized sediment placed 

during the pilot program. Offshore wave heights did not 

exceed 4 m for more than a month after the pilot placement, 

and little sediment mobility and transport occurred during 

this time (fig. 32) relative to the 2010 time period. Wave 

energy increased in late October 2018, enhancing bed-shear 

stresses and causing sediment to be mobilized throughout 

the pilot-placement area, according to the model simulations. 

Additional wave events in November 2018 resuspended 

sediment at both the shallower (southeastern) and deeper 

(northwestern) extents (fig. 32) of the pilot-placement transect. 

During these transport events, sediment fluxes were 3 to 10 

times higher at the shallower (southeastern) end of the pilot 

placement compared to the deeper (northwestern) end.

Method 2—Schematized Simulations

In this section, we present an analysis of the governing 

processes that dominate the patterns and relative magnitudes 

of sediment transport during an average year at the lower parts 

of the CRE and MCR, as well as their adjacent shorelines. 

This analysis is based on the schematized model simulations 

for years that had low (2005) and high (2013) river discharge. 

In addition to the simulations that use full forcing conditions 
Task 2 – Hydrodynamic and Sediment-Transport Modeling 39

Figure 30. Sediment-transport dynamics under varying wave- and tide-forcing conditions. A–D, Maps showing modeled wave heights 

(Hs) and sediment-transport vectors (black arrows) at selected times (see E) between October 18 and November 18, 2010. Red arrows 

in upper left corner denote incident wave direction at offshore location. Lengths of vectors are scaled to length (5x10–3 m3/s/m) of 

black arrow in upper right corner of A. Gray-filled boxes show locations of dredge-placement sites. E, Time-series plot of significant 

wave heights (black lines) and water levels (blue lines) throughout model simulation; red lines show times of maps in A–D. Other 

abbreviations: km, kilometer(s); m, meter(s); s, second.
40 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure 31. Sediment-transport dynamics under varying wave- and tide-forcing conditions after pilot placement of dredged material 

within North Head study area. A–D, Maps showing modeled wave heights (Hs) and sediment-transport vectors (black arrows) at selected 

times (see E) between September 20 and December 1, 2018. Thick black line shows approximate location of pilot placement; white dots 

mark deeper (northwest [NW]) and shallower (southeast [SE]) ends. Red arrows in upper left corner denote incident wave direction at 

offshore location. Lengths of vectors are scaled to length (5x10–3 m3/s/m) of black arrow in upper right corner of A. Gray-filled boxes show 

locations of dredge-placement sites. E, Time-series plot of significant wave heights (black lines) and water levels (blue lines) throughout 

model simulation; red lines show times of maps in A–D. Other abbreviations: km, kilometer(s); m, meter(s); s, second.
Task 2 – Hydrodynamic and Sediment-Transport Modeling 41

Figure 32. Time-series plots of (A) water levels (blue lines) and significant wave heights (Hs; black lines), (B) 

bed-shear stress (τb), and (C) sediment-transport flux for 72 days (between September 20 and December 1, 2018) 

after pilot placement of dredged material within North Head study area. Time-series plot in A depicts same offshore 

location and conditions as in figure 31 (see fig. 31E); time-series plots in B and C show model output at same two 

locations (shallower northwest [NW] and deeper southeast [SE] ends of pilot placement) shown in figs. 31A–D. Other 

abbreviations: m, meter(s); Pa, pascal(s); s, second.
42 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

(for example, tides, waves, river discharge), simulations 

also were performed with no waves and with no fresh-water 

discharge. These simulations allowed us to understand 

how the different forcing mechanisms (waves, tides, river 

flow, and baroclinic circulation) affect sediment transport 

at the study site. However, we caution that the calculated 

magnitudes of sediment transport presented in this analysis 

cannot be directly related to observed erosion and deposition 

volumes, owing to the assumptions used in the modeling 

(for example, single grain size, unlimited sand supply, 

no morphodynamic feedback). The results from selected 

simulations are described below; in addition, maps showing 

wave heights, mean total-sediment-transport values, and 

visualizations of sediment-transport pathways for all 

simulations are provided in appendix B.

Low-River-Discharge Conditions

Figure 33 summarizes the sediment-transport fluxes 

averaged over a year during low-flow conditions for 

simulations forced with tides alone (left panels [figs. 33A, 

C]) and including wave forcing (right panels [figs. 33B, D]). 

The year-averaged transport rates are calculated from the 

19 individual wave simulations and are scaled with their 

probabilities of occurrence (see table 5). Tides only introduce 

a small (1,960 m3/tide) net sediment export from the Columbia 

River to the Pacific Ocean. Transport rates decrease in the 

MCR (between the jetties), suggesting that transports from 

tide-averaged circulation contribute to sediment accumulation 

in this area. The patterns of tide-averaged circulation are 

related, in part, to the effect of density stratification, as well 

as to the presence of the deep channel at the MCR. The 

model predictions of sediment accumulation in the MCR are 

consistent with the extensive dredging efforts that are needed 

to maintain the navigation channel. Net sediment-transport 

rates from tides alone are negligible outside of the inlet, north 

and south of the jetties. Tidal transports alone are, therefore, 

unlikely to transport sand-sized sediment in the North Head 

study area.

Sediment-transport rates at the MCR and along its 

adjacent coastlines increased when wave forcing was imposed 

during the model simulations (figs. 33B, D). Although the 

sediment export from the estuary remained unchanged 

(2,500 m3/tide), the inclusion of waves induced a reversal 

(relative to the tide-only scenario) in the sediment exchange 

at the MCR (3,730 m3/tide). The reversal can likely be 

explained by waves breaking on the ebb-tidal delta. Waves 

enhanced shear stresses and sediment resuspension, increasing 

the amount of sediment that is available for advection by 

tidal currents. This process is more important on the shallow 

ebb-tidal delta, where flood currents dominate and transport 

is directed towards the MCR. Wave-enhanced resuspension 

is limited in the deeper areas inside the MCR, where ebb 

currents are dominant. This introduces a larger asymmetry in 

ebb- and flood-tidal transports, changing the near-balanced 

transports to landward-directed transports. Convergence of 

the transports landward of the deepest part of the navigation 

channel indicates that waves enhance sediment accumulation 

in this part of the channel. 

Over an average year of wave conditions, littoral 

processes in surf zones along the shorelines adjacent to the 

MCR disperse sediment northward and southward, away from 

the inlet (figs. 33B, D). On the north side of the inlet, 

model simulations indicate net northward-directed alongshore transport. The magnitude of the northward transport 

increases between the North Jetty and North Head, whereas 

farther north, the magnitude of net along-shore transports 

decreases, and it is negligible along this part of the Long 

Beach peninsula. South of the inlet, net along-shore transport 

is relatively weak and is directed southward. The gradients 

in along-shore transport are related to wave-sheltering and 

wave-refraction by the ebb-tidal delta and by the North and 

South Jetties. As a result of the convergences and divergences 

in along-shore transports, a large net northward-directed 

sediment flux along Benson Beach is predicted that exceeds 

the net landward-directed transports. This observation is 

consistent with the observed erosion of Benson Beach. 

Conversely, the model predicts a convergence of sediment 

transport and accumulation north of North Head. The model 

does not predict strong gradients in along-shore transport 

south of the inlet over an average year. 

High-River-Discharge Conditions

Overall, the tide- and annual wave-averaged transport 

patterns during high-discharge conditions (fig. 34) are similar 

to the low-flow conditions described above. Net sediment 

delivery to the MCR from the estuary increases during highflow conditions (figs. 34A, C). In both the high- and low-flow 

cases, residual tide-averaged transport exports sediment from 

the mouth of the river to the ebb-tidal delta offshore. However, 

during low-flow conditions, most of this material deposits 

in front of the MCR, whereas, during high-flow conditions, 

approximately 20 percent of the sediment bypasses the river 

mouth towards the north. During high-flow conditions, 

transports to the north of the jetties are still small, but these 

transports are larger compared to those during the low-flow 

conditions. High river discharge alters estuarine circulation 

and residual tidal currents, resulting in a seaward shift in the 

area where sediment accumulation is predicted. During high 

river discharge, we can still observe a decrease in transport 

rates towards Jetty A, but a reversal in transport direction 

seaward of Jetty A does not occur. Wave-driven littoraltransport patterns outside the inlet are largely unchanged 

between high- and low-flow conditions. 

On the ebb-tidal delta (represented by the transect adjacent 

to the North Jetty), a relatively large (3,160 m3/tide) net 

landward-directed sediment transport occurs, which indicates 

an active sediment transport from the ebb-tidal delta towards 

Benson Beach. At this location, large waves dissipate on 

the shallow ebb-tidal delta, enhancihng bed-shear stresses 

and generating wave-driven currents that transport sediment 
Task 2 – Hydrodynamic and Sediment-Transport Modeling 43

landward. Transport rates here exceed the landward transport 

rates that occur to the north. At the North Head study area, 

landward transport rates are about 80 percent smaller. 

Analysis of Sediment Pathways

Sediment-transport vectors provide valuable information 

on the processes that contribute to sediment dynamics and 

the relative magnitudes of potential transport of sand-sized 

sediment at the MCR. Through the analysis of the sedimenttransport pathways described below, we aim to understand the 

connectivity and linkages between the lower estuary, ebb-tidal 

delta, and shorelines adjacent to the MCR under variable wave, 

tide, and discharge conditions. As noted above (see Methods 

section), sediment-transport pathways were identified with 

SPIT to provide a Lagrangian visualization of the transportvector fields. Note that the computations performed with SPIT 

are not tracer simulations, as the rate of sediment movement 

is not calibrated to represent the actual particle velocity. 

The length of the pathway can, therefore, only be used 

qualitatively, and it must be interpreted as relative sediment 

mobility between source locations. Longer pathways indicate 

higher sediment mobility compared to shorter pathways. 

The sediment pathways for the 19 individual wave 

conditions were calculated similarly for both high- and lowriver-discharge conditions, and examples of such sedimenttransport pathways for four wave conditions are shown in 

figures 35 and 36, respectively. During low-wave conditions, 

the dominant sediment movement occurred in the estuary and 

mouth (fig. 35A), and sediment pathways were predominantly 

directed offshore through the navigation channel and MCR. 

Some pathways along the northern part of the channel indicated 

landward transport during low-discharge conditions. Sediment 

mobility in the estuary increased during high-flow conditions, 

and all transport pathways directed offshore (fig. 36A).

Enhanced shear stress owing to waves generally 

increased the length of the pathways observed along the coasts 

under both high- and low-discharge scenarios. For moderate 

wave energy directed from the southwest and a significant 

wave height of 3.5 m and peak period of 10.7 s, northwarddirected pathways were observed along narrow surf zones 

both north and south of the inlet (figs. 35B, 36B). The relative 

mobility of sediment transported in the surf zone was much 

higher for sources on the north side of the inlet relative to that 

of the south. In addition, sediment sources originating within 

the MCR and ebb-tidal delta on the north side of the navigation channel, including several originating within the Shallow 

Water Site dredge-placement area, were directed to the north 

and ultimately were incorporated into the surf-zone pathways, 

suggesting that a direct connection between MCR sediment 

and beaches to the north exists under these wave conditions. 

On the other hand, sediment-transport pathways that originate 

from sources to the south of the navigation channel within the 

MCR either terminated along the South Jetty or were directed 

onshore towards Clatsop Spit, suggesting that no connection 

exists between the MCR and adjacent beaches to the south 

under these conditions. 

Southward-directed littoral transport was observed for 

wave energy from the northwest, a wave height of 3.71 m, 

and a peak wave period of 13.4 s (figs. 35C, 36C). Under 

low-discharge conditions, sediment-transport pathways from 

sources that originate in shallow areas north of the inlet, 

including the North Head study area, were directed onshore 

and incorporated into the surf zone. However, higher discharge 

conditions resulted in more complicated pathways north of 

the inlet, and some pathways originating within the North 

Head study area were directed offshore. The North Jetty 

clearly separates the inlet from shallow sources to the north 

by interrupting southward-directed littoral-transport pathways, 

under both high- and low-discharge conditions. Although 

most pathways that originate from within the inlet were 

directed offshore and terminated on the ebb-tidal-delta front, 

the moderate northwestward-directed wave energy resulted in 

some connectivity between the MCR and adjacent beaches. For 

instance, sediment-transport pathways that originate from sources 

within the MCR on the south side of the navigation channel were 

directed offshore and southward and were incorporated into the 

littoral transport along Clatsop Plains beaches. 

Large waves from the southwest resulted in high 

sediment mobility and northward-directed transport pathways 

along a large part of the ebb-tidal delta, including the North 

Head study area and Shallow Water Site dredge-placement 

areas (figs. 35D, 36D). Surprisingly, dispersal pathways in 

both northward and southward directions were enhanced 

with high wave energy from the southwest. Whereas the 

sources that originate on the north side of the inlet followed 

the dominant wave direction, pathways that originate within 

the inlet and on the south side of the ebb-tidal delta took 

a circuitous route, and they were somewhat sensitive to 

discharge conditions along paths that ultimately were mostly 

directed to the south. Although the sediment mobility was 

relatively low, offshore-directed pathways were observed for 

sources that had relatively deep initial locations. 

A total of 19,000 source pathways were computed with 

SPIT, using 19 wave classes, two discharge scenarios, and 500 

sediment sources per simulation. Interpretation and synthesis 

of the raw results were challenging owing to the density of 

the sediment-transport pathways and the number of scenarios 

examined (fig. 37A). Results were simplified by examining 

sediment-source regions within several polygons of interest, 

including the North Head study area, Benson Beach, and the 

maintained navigational channel. The pathways for high- and 

low-discharge scenarios were generally similar, and so only 

the results from the low-discharge scenarios are described here. 

Sediment-transport pathways from sources that originate from 

within the North Head study area were directed onshore and 

northward for wave classes from western and southwestern 

directions (fig. 37B). Waves from the northwest resulted in 

limited southward-directed pathways from sources within the 

North Head study area towards Benson Beach. No pathways 
44 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure 33. Maps showing annually averaged sediment-transport fluxes that are based on schematized model simulations during low 

(4,000 m3/s) fluvial-discharge scenarios. Sediment-transport vectors (black arrows) are provided for simulations forced (A) with tides 

and fluvial discharge alone and (B) with tides, fluvial discharge, and waves; lengths of vectors are scaled to length (1.0x10–4 m3/s/m) of 

black arrow in upper right corner of A. Transect-averaged sediment fluxes (white-filled arrows) are shown for simulations forced (C) 

with tides and fluvial discharge alone and (D) with tides, fluvial discharge, and waves; white boxes show locations of transects; numeric 

values next to arrows in C and D represent transect-averaged sediment-transport fluxes, in thousands of m3 per tide. Black boxes show 

locations of dredge-placement sites. Other abbreviations: km, kilometer(s); m, meter(s); s, second.
Task 2 – Hydrodynamic and Sediment-Transport Modeling 45

Figure 34. Maps showing annually averaged sediment-transport fluxes that are based on schematized model simulations during high 

(8,000 m3/s) fluvial-discharge scenarios. Sediment-transport vectors (black arrows) are provided for simulations forced (A) with tides 

and fluvial discharge alone and (B) with tides, fluvial discharge, and waves; lengths of vectors are scaled to length (1.0x10–4 m3/s/m) of 

black arrow in upper right corner of A. Transect-averaged sediment fluxes (white-filled arrows) are shown for simulations forced (C) 

with tides and fluvial discharge alone and (D) with tides, fluvial discharge, and waves; white boxes show locations of transects; numeric 

values next to arrows in C and D represent transect-averaged sediment-transport fluxes, in thousands of m3 per tide. Black boxes show 

locations of dredge-placement sites. Other abbreviations: km, kilometer(s); m, meter(s); s, second.
46 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure 35. Maps showing sediment-transport pathways (colored lines) derived from application of Sediment Pathways 

Interactive visualization Tool (SPIT) to schematized model simulations using low-river-discharge conditions and constant wave 

forcing. Maps A–D show wave classes 13, 18, 10, and 11, respectively (see table 5 for specifications of wave classes). Black dots 

indicate initial positions of sediment sources; colors of sediment pathways indicate relative mobility of sources. Red arrows in 

upper left corners denote incident wave directions at offshore locations modeled in scenario. Abbreviation: km, kilometer(s).
Task 2 – Hydrodynamic and Sediment-Transport Modeling 47

Figure 36. Maps showing sediment-transport pathways (colored lines) derived from application of 

Sediment Pathways Interactive visualization Tool (SPIT) to schematized model simulations using highriver-discharge conditions and constant wave forcing. Maps A–D show wave classes 13, 18, 10, and 11, 

respectively (see table 5 for specifications of wave classes). Black dots indicate initial positions of sediment 

sources; colors of sediment pathways indicate relative mobility of sources. Red arrows in upper left corners 

denote incident wave directions at offshore locations modeled in scenario. Abbreviation: km, kilometer(s).
48 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

that originate from within the North Head study area interact 

with the inlet, regardless of wave direction, suggesting that 

dredged material placed within the North Head study area is 

unlikely to contribute to shoaling in the navigational channel. 

A primary objective of the placement of dredged material 

in the nearshore is to supplement the sediment budget and 

mitigate erosion of beaches and associated coastal change 

hazards in proximity to the inlet. According to baseline 

monitoring of beach nearshore morphology as described 

in Task 1, Benson Beach eroded approximately 2.1 Mm3 

(420,000 m3/yr) between 2014 and 2019 (table 3). Analysis 

of sediment-transport pathways was performed to identify 

source regions that can supply sediment to Benson Beach. 

Sources that have pathways that intersect Benson Beach were 

Figure 37. Maps showing sediment-transport pathways (colored lines) calculated for various sediment-source locations (white dots) 

and polygons of interest for low-river-discharge scenario. A, All 500 sources and 19 wave classes. B, Sources from all wave classes

originating from within North Head study area. C, Sources and wave classes for pathways that interact with Benson Beach. D, Sources 

and wave classes for pathways that interact with navigational channel. Black dots indicate initial positions of sediment sources; colors 

of sediment pathways indicate direction from which waves were directed. Abbreviations: deg, degree(s); km, kilometer(s).
Task 2 – Hydrodynamic and Sediment-Transport Modeling 49

located on the north side of the MCR, as well as throughout 

the northern ebb-tidal delta, including both the Shallow Water 

Site dredge-placement area and the North Head study area 

(fig. 37C). However, only wave conditions from the northwest 

produced sediment-transport pathways between the North 

Head study area and Benson Beach, suggesting that limited 

connectivity between the two exists. On the other hand, 

sediment-transport pathways from sources that originate within 

the Shallow Water Site, as well as from the ebb-tidal delta 

between the Shallow Water Site and North Head study area, 

intersected Benson Beach under a variety of wave conditions. 

The total probability, or percent of time, that sedimenttransport pathways from each source location interacted with 

Benson Beach (fig. 38) suggests that areas along the ebb-tidal 

delta between the inlet and North Head study area are more 

often connected to Benson Beach. The total probability of 

interaction for each source was calculated by summing the 

number of wave classes that have pathways that intersect 

Benson Beach multiplied by the wave class probability of 

occurrence (table 5). This analysis suggests that placement of 

dredged material in the region between the Shallow Water Site 

and North Head study area would more directly and efficiently 

enhance the sediment budget of Benson Beach. 

Some sediment transport pathways from source regions 

originating along the ebb delta, including those within the 

Shallow Water Site dredge placement area, interacted with the 

Figure 38. Probabilities (colored dots) of sediment-transport-pathway interactions between each source 

region and Benson Beach during low-river-discharge conditions. Gray dots indicate sediment-source 

locations with that have zero probability of occurrence. Abbreviation: km, kilometer(s).
50 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

navigation channel (fig. 37D). This suggests the possibility that 

dredged sediment placed in these regions may be transported 

back into the navigation channel. However, the total probability 

that sediment transport pathways between sources located 

within the Shallow Water Site and other locations on the ebb 

delta was generally low (fig. 39). As noted above, none of the 

pathways with sources originating within the North Head study 

area interacted with the navigation channel under any of the 

wave conditions that were simulated.

Concluding Remarks

A total of 2,560 km of nearshore bathymetric survey 

lines and 2,837 km of topographic survey lines were collected 

during the six surveys performed between 2014 and 2019. 

Throughout the entire CRLC survey area, the only significant 

regional erosion pattern was observed at Benson Beach, on 

the north side of the Columbia River. Despite the placement 

of approximately 6.3 Mm3 of sand dredged from the Columbia 

Figure 39. Probabilities 

(colored dots) of sedimenttransport-pathway 

interactions between 

each source region and 

navigation channel during 

low-river-discharge 

conditions. Gray dots 

indicate sediment-source 

locations that have zero 

probability of occurrence. 

Abbreviation: km, 

kilometer(s).
References Cited 51

River navigational channel at nearshore dredge-placement 

sites located nearby, Benson Beach eroded 2.1±0.8 Mm3 

(420,000 m3/yr) during the monitoring time period. The 

dredged material placed within the Shallow Water Site 

likely contributed to accumulation that was observed in 

the nearshore at the south end of the Benson Beach region. 

However, our results suggest that additional nourishment 

is needed to mitigate the 420,000 m3/yr deficit in sediment 

supply to the Benson Beach region and reverse the steady 

erosional trend of the nearshore and beach. 

The persistent erosion—despite the enhanced sediment 

supply—observed at Benson Beach highlights the need for 

efficient delivery of sediment from the nearshore dredgeplacement sites to the eroding beach and nearshore areas. In 

this study, an innovative, new numerical modeling method was 

developed to simulate sediment-transport fluxes and evaluate 

the linkages between nearshore dredge-placement areas and 

adjacent coastlines. The core of this model consisted of a 

coupled Delft3D-SWAN hydrodynamic, wave, and sedimenttransport model that was validated with extensive field 

measurements. Sediment-transport pathways were visualized 

and linkages were quantified using the Sediment Pathway 

Interactive visualization Tool (SPIT). 

Model results indicate the dominant importance of wave 

processes on sediment-transport patterns outside of the inlet 

and also that the North Head study area is not well situated 

to efficiently enhance the sediment budget of Benson Beach 

as currently configured. Sediment-transport pathways from 

sources that originate within the North Head study area were 

primarily directed onshore and northward, suggesting that 

sediment placed within the North Head study area will bypass 

Benson Beach and be transported toward the Long Beach 

peninsula. Sediment-transport pathways that originate from 

the northeastern part of the Shallow Water Site interacted 

with Benson Beach during a wider range of wave conditions, 

and yet these sediment-source locations also interacted with 

the navigation channel. Our analysis suggests that the region 

along the ebb-tidal delta between the Shallow Water Site and 

North Head study area would be best situated to enhance the 

sediment budget of Benson Beach without a high probability 

of sediment placed in this area being transported back into the 

navigation channel.

Data Availability

Data files— including all of the bathymetric and 

topographic data and associated metadata described in this 

report—are provided in Stevens and others (2019). In addition, 

Stevens and others (2017) provided data files and associated 

metadata that describe the collection and processing of timeseries oceanographic data used to validate the hydrodynamic 

model applied in this study.

References Cited

Akan, C., Moghimi, S., Ozkan-Haller, H.T., Osborne, J., 

and Kurapov, A., 2017, On the dynamics of the Mouth of 

the Columbia River—Results from a three-dimensional 

fully coupled wave-current interaction model: Journal of 

Geophysical Research Oceans, v. 122, p. 5218–5236.

Anderson, D., Ruggiero, P., Antolínez, J.A.A., Méndez, F.J., 

and Allan, J., 2018, A climate index optimized for longshore 

sediment transport reveals interannual and multidecadal 

littoral cell rotations: Journal of Geophysical Research - 

Earth Surface, v. 123, p. 1958–1981.

Anderson, S.W., 2019, Uncertainty in quantitative analyses 

of topographic change—Error propagation and the role of 

thresholding: Earth Surface Processes and Landforms, v. 44, 

p. 1015–1033.

Atwater, B.F., 1996, Coastal evidence for great earthquakes 

in western Washington, in Rogers, A.M., Walsh, T.J., 

Kockelman, W.J., and Priest, G.R., eds., Assessing 

earthquake hazards and reducing risk in the Pacific 

Northwest, volume 1: U.S. Geological Survey Professional 

Paper 1560, v. 1, p. 77–90, https://doi.org/10.3133/pp1560_

vol1.

Barnard, P.L., Hoover, D., Hubbard, D.M., Snyder, A., Ludka, 

B.C., Allan, J., Kaminsky, G.M., Ruggiero, P., Gallien, 

T.W., Gabel, L., McCandless, D., Weiner, H.M., Cohn, 

N., Anderson, D.L., and Serafin, K.A., 2017, Extreme 

oceanographic forcing and coastal response due to the 2015-

2016 El Niño: Nature Communications, v. 8, p. 1–8. 

Barnard, P.L., Short, A.D., Harley, M.D., Splinter, K.D., 

Vitousek, S., Turner, I.L., Allen, J., Banno, M., Bryan, 

K.R., Doria, A., Hansen, J.E., Kato, S., Kuriyama, Y., 

Randal-Goodwin, E., Ruggiero, P., Walker, I.J., and 

Heathfield, D.K., 2015, Coastal vulnerability across the 

Pacific dominated by El Nino/Southern Oscillation: Nature 

Geoscience, v. 8, p. 801–807.

Booij, N., Ris, R.C., and Holthuijsen, L.H., 1999, A thirdgeneration wave model for coastal regions, Part I—Model 

description and validation: Journal of Geophysical 

Research, v. 104, p. 7649–7666.

Cohn, N., and Ruggiero, P.R., 2016, The influence of seasonal 

to interannual nearshore profile variability on extreme water 

levels—Modeling wave runup on dissipative beaches: 

Coastal Engineering, v. 115, p. 79–92.

Daniels, R.C., Ruggiero, P., and Weber, L.E., 1999, Washington 

coastal geodetic control network— Report and station index: 

Washington Department of Ecology, Coastal Monitoring & 

Analysis Program, Publication #99–103, 268 p.
52 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Davis, J.C., 2002, Statistics and data analysis in geology (3d 

ed.): New York, Wiley & Sons, 638 p.

Deltares, 2016, D-Waq PART User Manual—Simulation of 

mid-field water quality and oil spills, using particle tracking: 

Delft, The Netherlands, Deltares Technical Report, 144 p.

Egbert, G.D., and Erofeeva, S.Y., 2002, Efficient inverse 

modeling of barotropic ocean tides: Journal of Atmospheric 

and Oceanic Technology, v. 19, p. 183–204.

Elias, E., and Gelfenbaum, G., 2009, Modeling processes 

controlling sediment transport at the mouth of the Columbia 

River: Proceedings of Coastal Dynamics 2009, Paper No. 

68, https://doi.org/10.1142/9789814282475_0070.

Elias, E.P.L., Gelfenbaum, G., and Westhuysen, van der A.J., 

2012, Validation of a coupled wave-flow model in a highenergy setting—The mouth of the Columbia River: Journal 

of Geophysical Research, v. 117, p. C09011.

Gelfenbaum, G., Elias, E., and Stevens, A.W., 2017, 

Investigation of input reduction techniques for 

morphodynamic modeling of complex inlets with baroclinic 

forcing: Proceedings of Coastal Dynamics 2017, Paper No. 

260, 13 p.

Gelfenbaum, G., Stevens, A.W., Miller, I., Warrick, J.A., 

Ogston, A.S., and Eidam, E., 2015a, Large-scale dam 

removal on the Elwha River, Washington, USA—Coastal 

geomorphic change: Geomorphology, v. 246, p. 649–668.

Gelfenbaum, G.R., Finlayson, D.P., Dartnell, P., Carlson, E., 

and Stevens, A.W., 2015b, Bathymetry and backscatter 

from 2013 interferometric swath bathymetry systems survey 

of Columbia River Mouth, Oregon and Washington: U.S. 

Geological Survey data release, https://doi.org/10.5066/

F7T72FHB.

Jay, D.A., Leffler, K.L., Diefenderfer, H.L., and Borde, A.B., 

2015, Tidal-fluvial and estuarine processes in the lower 

Columbia River—I. Along-channel water level variation, 

Pacific Ocean to Bonneville Dam: Estuaries and Coasts, v. 

38, p. 415–433.

Joliff, J.K., Kindle, J.C., Shulman, I., Penta, B., Friedrichs, 

M.A.M., Helber, R., and Arnone, R.A., 2009, Summary 

diagrams for coupled hydrodynamic-ecosystem model skill 

assessment: Journal of Marine Systems, v. 76, p. 64–82.

Kalnay, E., Kanmitsu, M., Kistler, R., Collins, W., Deaven, 

D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, 

J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgens, W., 

Janowiak, J., Mo, K.C., Ropelewski, C., Wang, J., Leetmaa, 

A., Reynolds, R., Jenne, R., and Joseph, D., 1996, The 

NCEP/NCAR 40-Year reanalysis project: Bulletin of the 

American Meteorological Society, v. 77, p. 437–471.

Kaminsky, G.M., Ruggiero, P., Buijsman, M.C., McCandless, 

D., and Gelfenbaum, G., 2010, Historical evolution of the 

Columbia River littoral cell: Marine Geology, v. 273, p. 

96–126.

Karna, T., Baptista, A.M., Lopez, J.E., Turner, P.J., McNeil, C., 

and Sanford, T.B., 2015, Numerical modeling of circulation 

in high-energy estuaries—A Columbia River estuary 

benchmark: Ocean Modeling, v. 88, p. 54–71.

Lesser, G.R., 2009, An approach to medium term coastal 

morphological modelling: Delft, Netherlands, Delft 

Technical University, Ph.D. Dissertation, 239 p.

Lesser, G.R., Roelvink, J.A., van Kester, T.M., and Stelling, 

G.S., 2004, Development and validation of a threedimensional morphological model: Coastal Engineering, v. 

51, p. 883–915.

Love, M.R., Friday, D.Z., Grothe, P.R., Carignan, K.S., 

Eakins, B.W., and Taylor, L.A., 2012, Digital elevation 

model of Astoria, Oregon—Procedures, data sources 

and analysis: National Oceanic and Atmospheric 

Administration, National Geophysical Data Center, 30 p.

Lower Columbia Estuary Partnership, 2010, Lower Columbia 

River digital terrain model: Lower Columbia Estuary 

Partnership website, https://www.estuarypartnership.org/

lower-columbia-digital-terrain-model.

MacDonald, N.J., Davies, M.H., Zundel, A.K., Howlett, J.D., 

Demirbilek, Z., Gailani, J.Z., Lackey, T.C., and Smith, 

J., 2006, PTM—Particle tracking model, Report 1—

Model theory, implementation, and example applications: 

U.S. Army Corps of Engineers Engineer Research and 

Development Center Technical Report ERDC/CHL TR-06-

20, 169 p.

MacMahan, J., 2016, Observations of oceanic-forced subtidal 

elevations in a convergent estuary: Estuarine, Coastal and 

Shelf Science, v. 181, p. 319–324.

Mass, C., 2008, The weather of the Pacific Northwest: Seattle, 

University of Washington Press, 280 p.

Mote, P.W., Rupp, D.E., Li, S., Sharp, D.J., Otto, F., Uhe, 

P.F., Xiao, M., Lettenmaier, D.P., Cullen, H., and Allen, 

M.R., 2016, Perspectives on the causes of exceptionally low 

2015 snowpack in the western United States: Geophysical 

Research Letters, v. 43, p. 10,980–10,988.

Peterson, C.D., Vanderburgh, S., Roberts, M.C., Jol, H.M., 

Phipps, J., and Twichell, D.C., 2010, Composition, age, 

and depositional rates of shoreface deposits under barriers 

and beach plains of the Columbia River littoral cell, USA: 

Marine Geology, v. 273, p. 62–82.

Ranasinghe, R., McLoughlin, R., Short, A., and Symonds, G., 

2004, The Southern Oscillation Index, wave climate, and 

beach rotation: Marine Geology, v. 204, p. 273–287.

Ruggiero, P., Kaminsky, G.M., Gelfenbaum, G., and Cohn, N., 

2016, Morphodynamics of prograding beaches—A synthesis 

of seasonal- to century-scale observations of the Columbia 

River littoral cell: Marine Geology, v. 376, p. 51–68.
References Cited 53

Ruggiero, P., Kaminsky, G.M., Gelfenbaum, G., and Voigt, 

B., 2005, Seasonal to interannual morphodynamics along 

a high-energy dissipative littoral cell: Journal of Coastal 

Research, v. 21, p. 553–578. 

Ruggiero, P., Komar, P.D., and Allan, J.C., 2010, Increasing 

wave heights and extreme value projections—The wave 

climate of the U.S. Pacific Northwest: Coastal Engineering, 

v. 57, p. 539–552.

Sherwood, C.R., and Creager, J.S., 1990, Sedimentary geology 

of the Columbia River estuary: Progress in Oceanography, 

v. 25, p. 15–79.

Sherwood, C.R., Jay, D.A., Harvey, R.B., Hamilton, P., and 

Simenstad, C.A., 1990, Historical changes in the Columbia 

River Estuary: Progress in Oceanography, v. 25, p. 299–352.

Snyder, A.G., Lacy, J.R., Stevens, A.W., and Carlson, E.M., 

2016, Bathymetric survey and digital elevation model 

of Little Holland Tract, Sacramento-San Joaquin Delta, 

California: U.S. Geological Survey Open-File Report 

2016‒1093, 14 p., https://doi.org/10.3133/ofr20161093.

Soulsby, R.L., Mead, C.T., Wild, B.R., and Wood, M.J., 2011, 

Lagrangian model for simulating the dispersal of sandsized particles in coastal waters: Journal of Waterway, Port, 

Coastal and Ocean Engineering, v. 137, no. 3, p. 123–131.

Stevens, A.W., Gelfenbaum, G., MacMahan, J., Reniers, 

A.J.H.M., Elias, E.P., Sherwood, C.R., and Carlson, E.M., 

2017, Oceanographic measurements and hydrodynamic 

modeling of the mouth of the Columbia River, Oregon and 

Washington, 2013: U.S. Geological Survey data release, 

https://doi.org/10.5066/F7NG4NS1.

Stevens, A.W., Gelfenbaum, G., Ruggiero, P., and 

Kaminsky, G.M, 2012, Southwest Washington littoral 

drift restoration—Beach and nearshore morphological 

monitoring: U.S. Geological Survey Open-File Report 

2012–1175, 67 p., https://pubs.usgs.gov/of/2012/1175/.

Stevens, A.W., Weiner, H.M., Ruggiero, P., Kaminsky, G.M., 

and Gelfenbaum G.R., 2019, Beach topography and 

nearshore bathymetry of the Columbia River littoral cell, 

Washington and Oregon (ver. 2.0, November 2019): U.S. 

Geological Survey data release, https://doi.org/10.5066/

P9W15JX8.

Storlazzi, C.D., van Ormondt, M., Chen, Y-L., and Elias, 

E.P.L., 2017, Modeling fine-scale coral larval dispersal 

and interisland connectivity to help designate mutuallysupporting coral reef Marine Protected Areas—Insights from 

Maui Nui, Hawaii: Frontiers in Marine Science, v. 4, p. 1–14. 

Taylor, J.R., 1997, An introduction to error analysis (2d ed.): 

Sausalito, Calif., University Science Books. 

U.S. Army Corps of Engineers (USACE), 2019, Management 

of open water dredged material placement/disposal sites, 

Mouth of the Columbia River, OR and WA: 2019 Annual 

Use Plan, 97 p.

Vriend, de H.J., Capobianco, M., Chesher, T., de Swart, H.E., 

Latteux, B., and Stive, M.J.F., 1993, Approaches to longterm modelling of coastal morphology—A review: Coastal 

Engineering, v. 21, p. 225–269.

Van Rijn, L.C., 2007a, Unified view of sediment transport by 

currents and waves—I. Initiation of motion, bed roughness, 

and bed-load transport: Journal of Hydraulic Engineering, v. 

133, p. 19.

Van Rijn, L.C., 2007b, Unified view of sediment transport by 

currents and waves—II. Suspended transport: Journal of 

Hydraulic Engineering, v. 133, p. 22.

Van Rijn, L.C., 2007c, Unified view of sediment transport by 

currents and waves—III. Graded beds: Journal of Hydraulic 

Engineering, v. 133, p. 15.

Warrick, J.A., Stevens, A.W., Miller, I.M., Harrison, S.R., 

and Gelfenbaum, G., 2019, World’s largest dam removal 

reverses coastal erosion: Scientific Reports, v. 9, no. 13968, 

12 p., https://doi.org/10.1038/s41598-019-50387-7.

Westhuysen, van der A.J., 2007, Advances in the spectral 

modeling of wind waves in the nearshore: Delft, 

Netherlands, Delft University of Technology, Ph.D. 

dissertation, 209 p.

Xu, J., Myers, E., and White, S., 2010, VDatum for the coastal 

waters of North/Central California, Oregon and Western 

Washington—Tidal datums and sea surface topography: 

National Oceanic and Atmospheric Administration 

Technical Memorandum NOS CS 22, 68 p.

Appendix 1. Coverage Maps, Environmental Conditions, and Water-Column Properties 55

Appendix 1. Coverage Maps, Environmental Conditions, and Water-Column 

Properties During Bathymetric and Topographic Surveys

In this appendix, we provide maps that show survey lines, time-series plots that show tide heights and wave conditions 

during data acquisition, and water-column properties derived from Conductivity Temperature Depth (CTD) casts collected 

during bathymetric and topographic surveys performed along the Columbia River littoral cell (CRLC) between 2014 and 2019. 

Figure A1. Maps showing locations of bathymetric- and topographic-survey lines (blue and red lines, respectively), sound-velocity 

measurements derived from Conductivity Temperature Depth casts, and benchmarks used for geodetic control from 2014 surveys 

along Columbia River littoral cell; left and right panels show data coverage for northern and southern parts of study area, respectively. 

Abbreviations: CR, Columbia River; GH, Grays Harbor; km, kilometer(s).
56 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure A2. Time-series plots of (A) water levels, (B) wave heights, (C) wave periods, and (D) wave 

directions during 2014 bathymetric and topographic surveys of Columbia River littoral cell; green and purple 

shading shows timing of bathymetric- and topographic-data collections, respectively. Abbreviations: CDIP, 

Coastal Data Information Program; km, kilometer(s); m, meter(s); MLLW, mean lower low water; NOAA, 

National Oceanic and Atmospheric Administration; s, second(s); °T, degree(s) true north.
Appendix 1. Coverage Maps, Environmental Conditions, and Water-Column Properties 57

Figure A3. A, Map showing locations (colored dots) of Conductivity Temperature Depth casts collected during 2014 

bathymetric surveys; numbers represent depth-averaged sound velocities. Depth profiles of water-column properties were 

measured during each cast, including (B) temperature, (C) salinity, and (D) sound velocity. Abbreviations: deg C, degrees 

Celsius; km, kilometer(s); m, meter(s); psu, practical salinity unit(s); s, second.
58 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure A4. Maps showing locations of bathymetric- and topographic-survey 

lines (blue and red lines, respectively), sound-velocity measurements derived from 

Conductivity Temperature Depth casts, and benchmarks used for geodetic control 

from 2015 surveys along Columbia River littoral cell; left and right panels show data 

coverage for northern and southern parts of study area, respectively. Abbreviations: 

CR, Columbia River; GH, Grays Harbor; km, kilometer(s).
Appendix 1. Coverage Maps, Environmental Conditions, and Water-Column Properties 59

Figure A5. Time-series plots of (A) water levels, (B) wave heights, (C) wave periods, and (D) wave 

directions during 2015 bathymetric and topographic surveys of Columbia River littoral cell; green 

and purple shading shows timing of bathymetric- and topographic-data collections, respectively. 

Abbreviations: CDIP, Coastal Data Information Program; km, kilometer(s); m, meter(s); MLLW, mean 

lower low water; NOAA, National Oceanic and Atmospheric Administration; s, second(s); °T, degree(s) 

true north.
60 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure A6. A, Map showing locations (colored dots) of Conductivity Temperature Depth casts collected during 2015 

bathymetric surveys; numbers represent depth-averaged sound velocities. Depth profiles of water-column properties were 

measured during each cast, including (B) temperature, (C) salinity, and (D) sound velocity. Abbreviations: deg C, degrees Celsius; 

km, kilometer(s); m, meter(s); psu, practical salinity unit(s); s, second.
Appendix 1. Coverage Maps, Environmental Conditions, and Water-Column Properties 61

Figure A7. Maps showing locations of bathymetric- and topographic-survey lines (blue and red 

lines, respectively), sound-velocity measurements derived from Conductivity Temperature Depth 

casts, and benchmarks used for geodetic control from 2016 surveys along Columbia River littoral 

cell; left and right panels show data coverage for northern and southern parts of study area, 

respectively. Abbreviations: CR, Columbia River; GH, Grays Harbor; km, kilometer(s).
62 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure A8. Time-series plots of (A) water levels, (B) wave heights, (C) wave periods, and (D) wave 

directions during 2016 bathymetric and topographic surveys of Columbia River littoral cell; green 

and purple shading shows timing of bathymetric and topographic-data collections, respectively. 

Abbreviations: CDIP, Coastal Data Information Program; km, kilometer(s); m, meter(s); MLLW, mean 

lower low water; NOAA, National Oceanic and Atmospheric Administration; s, second(s); °T, degree(s) 

true north.
Appendix 1. Coverage Maps, Environmental Conditions, and Water-Column Properties 63

Figure A9. A, Map showing locations (colored dots) of Conductivity Temperature Depth casts collected during 2016 

bathymetric surveys; numbers represent depth-averaged sound velocities. Depth profiles of water-column properties were 

measured during each cast, including (B) temperature, (C) salinity, and (D) sound velocity. Abbreviations: deg C, degrees 

Celsius; km, kilometer(s); m, meter(s); psu, practical salinity unit(s); s, second.
64 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure A10. Maps showing locations of bathymetric- and topographic-survey lines (blue and 

red lines, respectively), sound-velocity measurements derived from Conductivity Temperature 

Depth casts, and benchmarks used for geodetic control from 2017 surveys along Columbia 

River littoral cell; left and right panels show data coverage for northern and southern parts 

of study area, respectively. Abbreviations: CR, Columbia River; GH, Grays Harbor; km, 

kilometer(s).
Appendix 1. Coverage Maps, Environmental Conditions, and Water-Column Properties 65

Figure A11. Time-series plots of (A) water levels, (B) wave heights, (C) wave periods, and (D) wave 

directions during 2017 bathymetric and topographic surveys of Columbia River littoral cell; green 

and purple shading shows timing of bathymetric- and topographic-data collections, respectively. 

Abbreviations: CDIP, Coastal Data Information Program; km, kilometer(s); m, meter(s); MLLW, mean 

lower low water; NOAA, National Oceanic and Atmospheric Administration; s, second(s); °T, degree(s) 

true north.
66 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure A12. A, Map showing locations (colored dots) of Conductivity Temperature Depth casts collected during 2017 bathymetric 

surveys; numbers represent depth-averaged sound velocities. Depth profiles of water-column properties were measured during 

each cast, including (B) temperature, (C) salinity, and (D) sound velocity. Abbreviations: deg C, degrees Celsius; km, kilometer(s); m, 

meter(s); psu, practical salinity unit(s); s, second.
Appendix 1. Coverage Maps, Environmental Conditions, and Water-Column Properties 67

Figure A13. Maps showing locations of bathymetric- and topographic-survey lines (blue and 

red lines, respectively), sound-velocity measurements derived from Conductivity Temperature 

Depth casts, and benchmarks used for geodetic control from 2018 surveys along Columbia River 

littoral cell; left and right panels show data coverage for northern and southern parts of study 

area, respectively. Abbreviations: CR, Columbia River; GH, Grays Harbor; km, kilometer(s).
68 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure A14. Time-series plots of (A) water levels, (B) wave heights, (C) wave periods, and (D) wave 

directions during 2018 bathymetric and topographic surveys of Columbia River littoral cell; green 

and purple shading shows timing of bathymetric and topographic-data collections, respectively. 

Abbreviations: CDIP, Coastal Data Information Program; km, kilometer(s); m, meter(s); MLLW, mean 

lower low water; NOAA, National Oceanic and Atmospheric Administration; s, second(s); °T, degree(s) 

true north.
Appendix 1. Coverage Maps, Environmental Conditions, and Water-Column Properties 69

Figure A15. A, Map showing locations (colored dots) of Conductivity Temperature Depth casts collected during 2018 bathymetric 

surveys; numbers represent depth-averaged sound velocities. Depth profiles of water-column properties were measured during 

each cast, including (B) temperature, (C) salinity, and (D) sound velocity. Abbreviations: deg C, degrees Celsius; km, kilometer(s); m, 

meter(s); psu, practical salinity unit(s); s, second.
70 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure A16. Maps showing locations of bathymetric- and topographic-survey lines (blue and 

red lines, respectively), sound-velocity measurements derived from Conductivity Temperature 

Depth casts, and benchmarks used for geodetic control from 2019 surveys along Columbia River 

littoral cell; left and right panels show data coverage for northern and southern parts of study 

area, respectively. Abbreviations: CR, Columbia River; GH, Grays Harbor; km, kilometer(s).
Appendix 1. Coverage Maps, Environmental Conditions, and Water-Column Properties 71

Figure A17. Time-series plots of (A) water levels, (B) wave heights, (C) wave periods, and (D) wave 

directions during 2019 bathymetric and topographic surveys of Columbia River littoral cell; green 

and purple shading shows timing of bathymetric- and topographic-data collections, respectively. 

Abbreviations: CDIP, Coastal Data Information Program; km, kilometer(s); m, meter(s); MLLW, mean 

lower low water; NOAA, National Oceanic and Atmospheric Administration; s, second(s); °T, degree(s) 

true north.
72 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure A18. A, Map showing locations (colored dots) of Conductivity Temperature Depth casts collected during 2019 

bathymetric surveys; numbers represent depth-averaged sound velocities. Depth profiles of water-column properties were 

measured during each cast, including (B) temperature, (C) salinity, and (D) sound velocity. Abbreviations: deg C, degrees Celsius; 

km, kilometer(s); m, meter(s); psu, practical salinity unit(s); s, second.
Appendix 2. Wave Heights, Mean Sediment-Transport Fluxes, and Sediment-Transport Pathways 73

Appendix 2. Wave Heights, Mean Sediment-Transport Fluxes, and SedimentTransport Pathways for Schematized Wave-Climate Simulations

In this appendix, we provide maps that show simulated wave heights, mean sediment-transport fluxes, and visualizations of 

sediment-transport pathways for 19 wave classes in schematized wave climates and for both high- and low-discharge scenarios 

(see table 5 for wave-parameter specifications and probabilities of occurrence for all wave classes).

Figure B1. Maps showing 

modeled wave parameters for wave 

classes 1 (A–C), 2 (D–F), 3 (G–I), and 

4 (J–L) during low-river-discharge 

scenarios (wave classes 1–4 depict 

winter conditions; see table 5 for 

wave parameters and probabilities 

of occurrence for each wave class). 

Black boxes show locations of 

dredge-placement sites. A, D, G, 

J (left panels), significant wave 

heights; arrows show significant 

wave height magnitude and peak 

wave direction. B, E, H, K (middle 

panels), mean total sediment 

transport; arrows show magnitude 

and direction of mean total 

sediment transport (lengths are 

scaled to length [5x10–3 m3/s/m] of 

black arrow in upper right corner of 

B). C, F, I, L (right panels), sedimenttransport pathways (colored lines); 

black dots indicate initial positions 

of modeled sediment sources; 

colors of sediment pathways 

indicate relative mobility of sources. 

Abbreviations: km, kilometer(s); m, 

meter(s); s, second. 
74 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure B2. Maps showing 

modeled wave parameters for 

wave classes 5 (A–C), 6 (D–F), 

7 (G–I), and 8 (J–L) during 

low-river-discharge scenarios

(wave classes 5–8 depict winter 

conditions; see table 5 for wave 

parameters and probabilities 

of occurrence for each wave 

class). Black boxes show 

locations of dredge-placement 

sites. A, D, G, J (left panels), 

significant wave heights; 

arrows show significant wave 

height magnitude and peak 

wave direction. B, E, H, K

(middle panels), mean total 

sediment transport; arrows 

show magnitude and direction 

of mean total sediment 

transport (lengths are scaled 

to length [5x10–3 m3/s/m] of 

black arrow in upper right 

corner of B). C, F, I, L (right 

panels), sediment-transport 

pathways (colored lines); black 

dots indicate initial positions 

of modeled sediment sources; 

colors of sediment pathways 

indicate relative mobility of 

sources. Abbreviations: km, 

kilometer(s); m, meter(s); s, 

second. 
Appendix 2. Wave Heights, Mean Sediment-Transport Fluxes, and Sediment-Transport Pathways 75

Figure B3. Maps showing 

modeled wave parameters 

for wave classes 9 (A–C), 

10 (D–F), 11 (G–I), and 12

(J–L) during low-riverdischarge scenarios (wave 

classes 9–12 depict winter 

conditions; see table 5 

for wave parameters and 

probabilities of occurrence 

for each wave class). Black 

boxes show locations of 

dredge-placement sites. 

A, D, G, J (left panels), 

significant wave heights; 

arrows show significant 

wave height magnitude and 

peak wave direction. B, E, 

H, K (middle panels), mean 

total sediment transport; 

arrows show magnitude 

and direction of mean total 

sediment transport (lengths 

are scaled to length [5x10–3

m3/s/m] of black arrow in 

upper right corner of B). C, F, 

I, L (right panels), sedimenttransport pathways (colored 

lines); black dots indicate 

initial positions of modeled 

sediment sources; colors 

of sediment pathways 

indicate relative mobility of 

sources. Abbreviations: km, 

kilometer(s); m, meter(s); s, 

second. 
76 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure B4. Maps showing 

modeled wave parameters for 

wave classes 13 (A–C), 14 (D–F), 

15 (G–I), and 16 (J–L) during 

low-river-discharge scenarios

(wave classes 13–16 depict 

summer conditions; see table 

5 for wave parameters and 

probabilities of occurrence for 

each wave class). Black boxes 

show locations of dredgeplacement sites. A, D, G, J

(left panels), significant wave 

heights; arrows show significant 

wave height magnitude and 

peak wave direction. B, E, H, 

K (middle panels), mean total 

sediment transport; arrows 

show magnitude and direction 

of mean total sediment transport 

(lengths are scaled to length 

[5x10–3 m3/s/m] of black arrow 

in upper right corner of B). C, 

F, I, L (right panels), sedimenttransport pathways (colored 

lines); black dots indicate 

initial positions of modeled 

sediment sources; colors of 

sediment pathways indicate 

relative mobility of sources. 

Abbreviations: km, kilometer(s); 

m, meter(s); s, second. 
Appendix 2. Wave Heights, Mean Sediment-Transport Fluxes, and Sediment-Transport Pathways 77

Figure B5. Maps showing modeled wave parameters for wave classes 17 (A–C), 18 (D–F), and 19 (G–I)

during low-river-discharge scenarios (wave classes 17–19 depict summer conditions; see table 5 for wave 

parameters and probabilities of occurrence for each wave class). Black boxes show locations of dredgeplacement sites. A, D, G (left panels), significant wave heights; arrows show significant wave height 

magnitude and peak wave direction. B, E, H (middle panels), mean total sediment transport; arrows show 

magnitude and direction of mean total sediment transport (lengths are scaled to length [5x10–3 m3/s/m] of 

black arrow in upper right corner of B). C, F, I (right panels), sediment-transport pathways (colored lines); 

black dots indicate initial positions of modeled sediment sources; colors of sediment pathways indicate 

relative mobility of sources. Abbreviations: km, kilometer(s); m, meter(s); s, second. 
78 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure B6. Maps showing 

modeled wave parameters for 

wave classes 1 (A–C), 2 (D–F), 

3 (G–I), and 4 (J–L) during 

high-river-discharge scenarios

(wave classes 1–4 depict winter 

conditions; see table 5 for wave 

parameters and probabilities of 

occurrence for each wave class). 

Black boxes show locations of 

dredge-placement sites. A, D, G, 

J (left panels), significant wave 

heights; arrows show significant 

wave height magnitude and 

peak wave direction. B, E, H, 

K (middle panels), mean total 

sediment transport; arrows 

show magnitude and direction 

of mean total sediment transport 

(lengths are scaled to length 

[5x10–3 m3/s/m] of black arrow in 

upper right corner of B). C, F, I, L

(right panels), sediment-transport 

pathways (colored lines); black 

dots indicate initial positions 

of modeled sediment sources; 

colors of sediment pathways 

indicate relative mobility of 

sources. Abbreviations: km, 

kilometer(s); m, meter(s); s, 

second. 
Appendix 2. Wave Heights, Mean Sediment-Transport Fluxes, and Sediment-Transport Pathways 79

Figure B7. Maps 

showing modeled wave 

parameters for wave 

classes 5 (A–C), 6 (D–F), 

7 (G–I), and 8 (J–L) during 

high-river-discharge 

scenarios (wave classes 

5–8 depict winter 

conditions; see table 5 

for wave parameters 

and probabilities of 

occurrence for each 

wave class). Black 

boxes show locations of 

dredge-placement sites. 

A, D, G, J (left panels), 

significant wave heights; 

arrows show significant 

wave height magnitude 

and peak wave direction. 

B, E, H, K (middle panels), 

mean total sediment 

transport; arrows show 

magnitude and direction 

of mean total sediment 

transport (lengths are 

scaled to length [5x10–3

m3/s/m] of black arrow in 

upper right corner of B). 

C, F, I, L (right panels), 

sediment-transport 

pathways (colored lines); 

black dots indicate initial 

positions of modeled 

sediment sources; colors 

of sediment pathways 

indicate relative mobility 

of sources. Abbreviations: 

km, kilometer(s); m, 

meter(s); s, second. 
80 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure B8. Maps showing 

modeled wave parameters for 

wave classes 9 (A–C), 10 (D–F), 

11 (G–I), and 12 )(J–L) during 

high-river-discharge scenarios

(wave classes 9–12 depict 

winter conditions; see table 

5 for wave parameters and 

probabilities of occurrence 

for each wave class). Black 

boxes show locations of 

dredge-placement sites. A, D, 

G, J (left panels), significant 

wave heights; arrows show 

significant wave height 

magnitude and peak wave 

direction. B, E, H, K (middle 

panels), mean total sediment 

transport; arrows show 

magnitude and direction of 

mean total sediment transport 

(lengths are scaled to length 

[5x10–3 m3/s/m] of black 

arrow in upper right corner 

of B). C, F, I, L (right panels), 

sediment-transport pathways 

(colored lines); black dots 

indicate initial positions of 

modeled sediment sources; 

colors of sediment pathways 

indicate relative mobility of 

sources. Abbreviations: km, 

kilometer(s); m, meter(s); s, 

second. 
Appendix 2. Wave Heights, Mean Sediment-Transport Fluxes, and Sediment-Transport Pathways 81

Figure B9. Maps showing 

modeled wave parameters for 

wave classes 13 (A–C), 14 (D–F), 15

(G–I), and 16 (J–L) during highriver-discharge scenarios (wave 

classes 13–16 depict summer 

conditions; see table 5 for wave 

parameters and probabilities of 

occurrence for each wave class). 

Black boxes show locations of 

dredge-placement sites. A, D, G, 

J (left panels), significant wave 

heights; arrows show significant 

wave height magnitude and 

peak wave direction. B, E, H, 

K (middle panels), mean total 

sediment transport; arrows 

show magnitude and direction 

of mean total sediment transport 

(lengths are scaled to length 

[5x10–3 m3/s/m] of black arrow in 

upper right corner of B). C, F, I, L

(right panels), sediment-transport 

pathways (colored lines); black 

dots indicate initial positions of 

modeled sediment sources; colors 

of sediment pathways indicate 

relative mobility of sources. 

Abbreviations: km, kilometer(s); m, 

meter(s); s, second. 
82 Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River

Figure B10. Maps showing modeled wave parameters for wave classes 17 (A–C), 18 (D–F), and 19 (G–I) during 

high-river-discharge scenarios (wave classes 17–19 depict summer conditions; see table 5 for wave parameters 

and probabilities of occurrence for each wave class). Black boxes show locations of dredge-placement sites. 

A, D, G (left panels), significant wave heights; arrows show significant wave height magnitude and peak wave 

direction. B, E, H (middle panels), mean total sediment transport; arrows show magnitude and direction of 

mean total sediment transport (lengths are scaled to length [5x10–3 m3/s/m] of black arrow in upper right corner 

of B). C, F, I (right panels), sediment-transport pathways (colored lines); black dots indicate initial positions of 

modeled sediment sources; colors of sediment pathways indicate relative mobility of sources. Abbreviations: km, 

kilometer(s); m, meter(s); s, second. 
Menlo Park Publishing Service Center, California

Manuscript approved for publication May 1, 2020 

Edited by Taryn A. Lindquist

Layout and design by Kimber Petersen
Stevens and others—Coastal Change and Sediment-Transport Pathways at Mouth of Columbia River—Open-File Report 2020–1045

ISSN 2331-1258 (online)

https://doi.org/10.3133/ofr20201045