NOAA Technical Memorandum NOS CS 22

VDATUM FOR THE COASTAL WATERS OF 

NORTH/CENTRAL CALIFORNIA, OREGON AND 

WESTERN WASHINGTON: TIDAL DATUMS AND SEA 

SURFACE TOPOGRAPHY 

Silver Spring, Maryland 

October 2010 

noaa National Oceanic and Atmospheric Administration 

U.S. DEPARTMENT OF COMMERCE 

National Ocean Service 

Coast Survey Development Laboratory 
Office of Coast Survey 

National Ocean Service 

National Oceanic and Atmospheric Administration 

U.S. Department of Commerce

The Office of Coast Survey (OCS) is the Nation’s only official chartmaker. As the 

oldest United States scientific organization, dating from 1807, this office has a 

long history. Today it promotes safe navigation by managing the National 

Oceanic and Atmospheric Administration’s (NOAA) nautical chart and 

oceanographic data collection and information programs. 

There are four components of OCS: 

The Coast Survey Development Laboratory develops new and efficient 

techniques to accomplish Coast Survey missions and to produce new and 

improved products and services for the maritime community and other 

coastal users. 

The Marine Chart Division acquires marine navigational data to construct 

and maintain nautical charts, Coast Pilots, and related marine products for 

the United States. 

The Hydrographic Surveys Division directs programs for ship and shorebased hydrographic survey units and conducts general hydrographic 

survey operations. 

The Navigational Services Division is the focal point for Coast Survey 

customer service activities, concentrating predominately on charting 

issues, fast-response hydrographic surveys, and Coast Pilot updates. 
NOAA Technical Memorandum NOS CS 22 

VDATUM FOR THE COASTAL WATERS OF 

NORTH/CENTRAL CALIFORNIA, OREGON AND 

WESTERN WASHINGTON: TIDAL DATUMS AND SEA 

SURFACE TOPOGRAPHY 

Jiangtao Xu and Edward P. Myers 

Office of Coast Survey, Coast Survey Development Laboratory, 

Silver Spring, MD 

Stephen A. White 

 National Geodetic Survey, Silver Spring, MD 

October 2010

noaa National Oceanic and Atmospheric Administration 

U. S. DEPARTMENT National Oceanic and National Ocean Service 

OF COMMERCE Atmospheric Administration David Kennedy 

Gary Locke, Dr. Jane Lubchenco Acting Assistant 

Secretary Under Secretary Administrator 

 

Office of Coast Survey Coast Survey Development Laboratory 

Captain John Lowell, NOAA Mary Erickson 
ii 

NOTICE 

Mention of a commercial company or product does not constitute an 

endorsement by NOAA. Use for publicity or advertising purposes of 

information from this publication concerning proprietary products or 

the tests of such products is not authorized. 
iii 

TABLE OF CONTENTS

LIST OF FIGURES ..................................................................................................................................... iv

LIST OF TABLES ....................................................................................................................................... vi

ABSTRACT ............................................................................................................................................. vii

1. INTRODUCTION .................................................................................................................................... 1

2. DATA DESCRIPTION ............................................................................................................................ 3

2.1. DIGITAL COASTLINE ................................................................................................. 3 

2.2. BATHYMETRIC DATA ................................................................................................ 3 

2.3. WATER LEVEL STATION DATA ................................................................................... 4 

3. TIDAL DATUM SIMULATION ............................................................................................................ 7

3.1. HYDRODYNAMIC MODEL ........................................................................................... 7 

3.2. MODEL GRID ............................................................................................................. 7 

3.3. BATHYMETRY ON MODEL GRID ................................................................................. 8 

4. MODEL RESULTS ANALYSIS AND SENSITIVITY TESTS ......................................................... 13

4.1 SENSITIVITY STUDY .................................................................................................. 13 

4.2 EFFECT OF RIVER FLOW ............................................................................................ 15 

4.3. VERIFICATION OF MODELED TIDAL DATUMS ........................................................... 16 

4.4. CORRECTIONS OF MODELED TIDAL DATUM ERRORS ................................................ 20 

4.5. CONNECTING WITH ADJACENT VDATUM AREAS ..................................................... 22 

5. CREATION AND POPULATION OF THE MARINE GRID ........................................................... 25

5.1. CREATION OF VDATUM MARINE GRID ..................................................................... 25 

5.2. POPULATION OF VDATUM GRID WITH TIDAL DATUMS ............................................. 27 

6. TOPOGRAPHY OF THE SEA SURFACE ........................................................................................ 29

7. COLUMBIA RIVER DATUM TIES TO THE ELLIPSOID ............................................................. 35

8. SUMMARY ............................................................................................................................................. 39

REFERENCES ........................................................................................................................................... 40

ACKNOWLEDGMENTS .......................................................................................................................... 40

APPENDIX A. WATER LEVEL STATIONS ......................................................................................... 43

APPENDIX B. MODELED TIDAL DATUM ERRORS AND CORRECTED TIDAL DATUMS ON 

MARINE GRID ................................................................................................................. 47

APPENDIX C. TSS AT NGS BENCH MARKS AND CO-OPS WATER LEVEL STATIONS ......... 53

APPENDIX D. COLUMBIA RIVER DATUM TO NAVD88 DATA .................................................... 65
iv 

LIST OF FIGURES 

Figure 1. Map of the coastal waters for the VDatum region of interest. The black 

line illustrates the MHW coastline. The green line marks a distance of 25-

nautical miles offshore. Red squares show the locations of the NOAA tide 

stations. ............................................................................................................. 2

Figure 2. (a) ACE bathymetry survey in Columbia River; (b) Dates and locations of 

NOS sounding surveys and (c) distribution of ENC bathymetric data. ............ 4

Figure 3. Unstructured grid for (a) the entire model domain and an enlargement of 

(b) Willapa Bay and the lower Columbia River and (c) San Francisco 

Bay. The blue line represents the model open ocean boundary; the green 

lines represent islands and the brown line is the mainland boundary. .............. 9

Figure 4. The location of stations in Columbia River with CRD to MLLW data from 

CO-OPS. ......................................................................................................... 10

Figure 5. The regression model of CRD to MLLW in Columbia River (a) from 

Astoria to Longview, (b) from Longview to Vancouver and (c) for the 

whole river as a combination of (a) and (b). ................................................... 11

Figure 6. Final model bathymetry relative to Model Zero (MZ). ................................... 12

Figure 7. The bottom friction coefficient calculated by different values for the 

parameters in Equation (2). ............................................................................. 14

Figure 8. Modeled water levels at Vancouver, WA during high- and low- flow (a) 

relative to Model Zero (MZ) (c) relative to mean water level. Observed 

water levels during high- (May, 2008) and low- (Feb., 2008) flows (b) 

relative to NAVD88 and (d) relative to mean water level. (e) MLLW 

differences between simulations of a relatively low river flow and a very 

low river flow in Columbia River (in green) and MLLW relative to 

Columbia River Datum (in magenta) from the CO-OPS. ............................... 16

Figure 9. Model derived tidal datums relative to MSL: (a) MHHW, (b) MHW, (c) 

MLW and (d) MLLW. .................................................................................... 18

Figure 10. A close-up view of modeled MHW relative to MSL in (a) Willapa Bay 

and lower Columbia River and (b) San Francisco Bay. .................................. 19

Figure 11. Modeled versus observed MHHW (red squares), MHW (blue stars), 

MLW (green stars), and MLLW (magenta squares) (all relative to MSL). .... 20

Figure 12. TCARI interpolated model MHW error with (a) default boundary 

conditions and (b) added control stations along the outer boundary so that 

the errors approach zero at the outer boundary. .............................................. 21
v 

Figure 13. (a) Map of Pacific Northwest model domain (black line) and bounding 

polygons of the Juan de Fuca Strait (blue line), Central California 

(magenta line) and Southern California (green line) VDatum areas. (b) A 

close-up view of the overlapping area between PNW and SCA and the 

construction of triangular grid for transitional area. Model domain 

outlined in blue. Bounding polygon for SCA is in green. .............................. 22

Figure 14. An illustration of the domain division. ............................................................ 26

Figure 15. Location of tidal benchmarks and tide stations used to compute the West 

Coast of the Continental United States VDatum TSS grids. .......................... 31

Figure 16. The West Coast of the Continental United States TSS Grid (NAVD88 

realized through GEOID03). .......................................................................... 32

Figure 17. The West Coast of the Continental United States TSS Grid (NAVD88 

realized through GEOID99). ........................................................................... 33

Figure 18. (a) Data availability along the river channel and CRD relative to 

NAVD88 in (b) Columbia River and (c) Willamette River. ........................... 36

Figure 19. The perpendicular transects of the river channel and the color-coded data 

values in feet. The black line shows the shoreline. ......................................... 37

Figure 20. Columbia River Datum relative to NAVD88 in meters. Contour interval is 

0.05 m. ............................................................................................................ 38

Figure B1. Tidal datums on Pacific Northwest VDatum marine grids. (a) MHHW, 

(b) MHW, (c) MLW, (d) MLLW. Color bars are in the unit of meters. ......... 47 

LIST OF TABLES 

Table 1. VDatum marine grid information for the five regions. ....................................... 27

Table A1. NOS Water Level Stations in the Pacific Northwest VDatum region. ............ 43 

Table B1. Tidal datum errors (modeled minus observed in meters and the absolute 

relative error) at the 105 CO-OPS water level stations. ................................... 48 

Table C1. Derived NAVD 88-to-LMSL values for each tidal datum at NGS 

benchmarks from the West Coast of the Continental United States Tidal 

Grids. NAVD88 values realized through GEOID03. ...................................... 53 
vi 

Table C2. Location and elevation information for NOAA tide gauges used to create 

the West Coast of the Continental United States TSS grids. MSL data are 

from CO-OPS and NAVD88 heights were calculated by NGS. ..................... 60

Table D1. Columbia River Datum relative to NAVD88 along the river channel. ............ 65 
vii 

ABSTRACT 

VDatum, NOAA’s vertical datum transformation software tool, allows users to transform 

vertical elevation/depth data between various tidal, orthometric, and ellipsoid-based 3D 

reference systems. An application of VDatum is developed for the coastal waters of 

north/central California, Oregon and western Washington. The region of interest extends 

from Pt. Buchon in California to Cape Flattery, Washington. 

 

The tidal datums fields for this VDatum application were derived from tidal simulations 

using the 2D barotropic version of the finite element model ADCIRC. An unstructured 

triangular grid consisting of 293,009 nodes and 546,190 elements was created for these 

simulations. The model was forced with eight tidal constituents (M2, S2, N2, K2, K1, P1, 

O1 and Q1) and run for 67 days. Water level time series of the last 60 days were saved. 

Various tidal datum fields, including mean lower low water, mean low water, mean high 

water, and mean higher high water, were derived from these time series. Water level 

harmonic analysis was conducted on the model results for the NOAA/NOS standard 37 

tidal constituents. Model results were validated by comparing with observations from 105 

water level stations maintained by the NOAA’s Center for Operational Oceanographic 

Products and Services (CO-OPS). Discrepancies between model results and observational 

datums were attributed to model errors and interpolated over the whole model domain 

using Tidal Constituent And Residual Interpolation, a spatial interpolation tool based on 

solution of Laplace’s equation. These spatially varying error fields were added to the 

original model results to derive corrected tidal datum fields on the unstructured grid. 

These corrected tidal datum fields were then interpolated onto a regularly structured 

marine grid for use as input to the VDatum software. 

The Topography of Sea Surface (TSS), defined as the elevation of NAVD88 relative to 

local mean sea level (LMSL), was developed based on interpolation of bench mark data 

maintained by CO-OPS and the National Geodetic Survey. The NAVD88-to-LMSL 

values were derived either by fitting tidal model results to tidal bench marks leveled in 

NAVD88 or by calculating orthometric-to-tidal datum relationships at NOAA tidal 

gauges. Results by both methodologies were coupled to create the final TSS grids by 

spatial interpolation. 

Key Words: tides, tidal datums, California, Oregon, Washington, VDatum, west coast, 

ADCIRC, bathymetry, coastline, spatial interpolation, marine grid, North American 

Vertical Datum 

 
viii 
1 

1. Introduction 

NOAA’s NOS has developed a software tool called VDatum to transform elevation data 

among approximately 30 vertical datums (Milbert, 2002; Parker, 2002; Parker et al., 

2003; Myers, 2005). Once VDatum has been established for a region, data sets referenced 

to different vertical datums can be integrated through transformations to a common 

vertical datum (Parker, 2002). VDatum allows bathymetric and topographic data to be 

integrated in this manner through its inherent geoidal, ellipsoidal, and tidal relationships. 

Knowledge of the spatial distribution of tidal datums is necessary for developing accurate 

VDatum applications (Milbert and Hess, 2001). Tidal datum fields for VDatum are 

derived from water level observations at presently operating and historical NOAA tide 

stations and from numerical simulations by hydrodynamic models. The observations 

provide accurate tidal datums at the station locations, and the hydrodynamic models are 

an effective way to capture the spatially varying nature of the tidal datums between and 

away from stations. Differences between the model and the data are spatially interpolated 

to create a correction field used to produce a final set of tidal datum fields that match the 

observations. 

This report describes the development of VDatum for an area extending from Cape 

Flattery, Washington to central California. Figure 1 displays a map of the area. In the 

figure, the black line represents the Mean High Water (MHW) coastline and the green 

line denotes the 25-nm offshore demarcation. Tidal datums for VDatum are generally 

developed for water areas between the coastline and the 25-nm offshore limit. 

Creation of VDatum begins with tidal simulations using a hydrodynamic model. Tidal 

datums and harmonic constants of selected tidal constituents were computed from a 60-

day simulated water level time series. Adjustments to model parameters were made based 

on comparisons between the modeled harmonic constituents and tidal datums with 

observational data. Final error corrections to the tidal datums were made using the Tidal 

Constituent and Residual Interpolation (TCARI) software to spatially interpolate modeldata differences. Regularly structured marine grids were created and populated with these 

corrected tidal datums. 

Finally, to be applicable over coastal waters, VDatum requires spatially-varying fields of 

the Topography of Sea Surface (TSS) as well, which refers to the elevation of the North 

American Vertical Datum of 1988 (NAVD88) relative to Local Mean Sea Level (LMSL). 

The NAVD88-to-LMSL field was derived by either fitting tidal model results to tidal 

bench marks leveled in NAVD88 or calculating orthometric-to-tidal datum relationships 

at NOAA tide stations. 

This technical report is organized as follows: After an introduction in Section 1, Section 2 

discusses data needed for driving and validating the hydrodynamic model. Section 3 and 

4 describe the set-up and sensitivity studies of the tide model, respectively. Section 5 

discusses creation of regularly structured marine grid required for the VDatum software 

tool and its population with error-corrected model datums. In Section 6, creation of TSS 
2 

for the area is described. The efforts of establishing a relationship between Columbia 

River Datum (CRD) and NAVD 88 are described in Section 7. Finally, a summary is 

given in Section 8. 

Figure 1. Map of the coastal waters for the VDatum region of interest. The black line 

illustrates the MHW coastline. The green line marks a distance of 25-nautical 

miles offshore. Red squares show the locations of the NOAA tide stations. 

Grays Harbor 

San Francisco Bay 

Columbia River

Monterey Bay

Humboldt Bay

Willapa Bay

Coos Bay 

Tide Stations 
3 

2. Data Description 

To derive spatially varying tidal datum fields for VDatum, a hydrodynamic model was used to 

simulate the tidal dynamics in this region. Coastline and bathymetric data were required to build 

the model grid for the tidal simulation. Observational tidal datums were used to verify the model 

results and to make corrections in the final tidal datum fields. 

2.1. Digital Coastline 

The MHW coastline was used to delineate the land-water boundaries and to guide the building of 

the unstructured grid used in the tide model. High resolution digital shoreline was produced from 

current NOAA Electronic Navigational Chart (ENC) and Raster Navigational Chart data. The 

Coastline (COALNE) and Shoreline Construction (SLCONS) ENC object classes were obtained 

for both the Harbor and Approach scalebands and converted from their native S57 format to 

ESRI shapefiles for use in ArcGIS 9.3. The ENC data were merged and edited against NOAA 

charts to produce a continuous shoreline product representing the most detailed and most current 

information available. The Charts used typically ranged in scale from 1:5,000 to 1:80,000. A 

commercial software package called Surface-Water Modeling System (SMS) was used to read in 

the shapefile and manually connect the shoreline segments together and to correct errors in the 

original digital coastlines. In Figure 1, the black line illustrates this final coastline. 

2.2. Bathymetric Data 

Bathymetric data used in this study were from several sources: NOS soundings, the NOAA 

ENCs, NOAA nautical charts and U.S. Army Corps of Engineers (USACE) navigational channel 

surveys. 

The NOS soundings were from the NOS/OCS hydrographic database maintained at the National 

Geophysical Data Center (NGDC) and include surveys conducted between 1851 and 2004. The 

USACE is responsible for maintaining and dredging the navigational channels. Where available, 

this dataset is usually the most dense and most recent. However, USACE’s bathymetry surveys 

are only conducted for the major ports and harbors. In the studied area, this dataset only covers 

the navigational channels in the Columbia River, Grays Harbor and San Francisco Bay. The 

survey coverage in Columbia River is shown in Figure 2a. Figures 2b and 2c depict the data 

coverage of NOS soundings and the ENC’s bathymetry. 

It is noted that even with the combined datasets from above three sources, there are certain 

nearshore areas and some bays/rivers uncovered. NOAA nautical chart bathymetry, wherever 

they are available, was then manually digitized to compensate for the missing coverage. All 

sources of bathymetric data were used for the best regional coverage. However, they were 

prioritized based on the data quality as follows: USACE dredging/survey data, NOS sounding, 

ENCs and manually digitized nautical charts. 

 
4 

Figure 2. (a) ACE bathymetry survey in Columbia River; (b) Dates and locations of NOS 

sounding surveys and (c) distribution of ENC bathymetric data. 

2.3. Water level station data 

Tidal datums derived from NOAA tide station water level observations were used to verify and 

correct model results. There are a total of 159 stations in the region from central California to 

(b) (c) 

(a)
5 

Washington. However, some stations are located within either small embayments or upper 

reaches of rivers that are not represented in the present model grid (Section 3.2) and some 

stations have no observationally derived tidal datums. These stations were therefore excluded, 

leaving 105 stations used for model validation in this study. The station locations are shown as 

red squares in Figure 1. All tidal datums are relative to the present National Tidal Datum Epoch 

(1983-2001). Table A1 in Appendix A lists the station and tidal datum information used here. 
6 
7 

3. Tidal Datum Simulation 

3.1. Hydrodynamic model 

The ADvanced CIRCulation (ADCIRC) model (Luettich et al., 1992; Westerink et al., 1994) is a 

finite element hydrodynamic model. It was developed to simulate water level and hydrodynamic 

circulation along shelves, coastal ocean and within estuaries and has been applied to model tides 

(Westerink et al., 1993; Luettich et al., 1999; Mukai et al., 2002; Spargo et al., 2004), storm 

surge (Blain et al,, 1998; Westerink et al., 2008; Demirbilek et al., 2008), inundation, and other 

applications. 

The ADCIRC model can be run in either two- or three- dimensional mode. To simulate tides for 

computing tidal datums, the model was run in the two-dimensional barotropic mode with wetting 

and drying. Tidal potential body force of eight major diurnal and semidiurnal constituents (K1, 

O1, P1, Q1, M2, S2, N2 and K2) was included in the model. Water elevations constructed from the 

same eight constituents were also applied at open ocean boundary and were extracted from a 

regional northeast Pacific Ocean tide model (Foreman et al., 2000). No atmospheric forcing was 

used. River flows were not included in the initial model setup and were imposed for Columbia 

River and Sacramento River later due to their significant effects on tides in the corresponding 

systems to improve the model results. Lateral viscosity was set as a constant, 5.0 m s-2, 

throughout the model domain. A 1s time step was used to ensure computational stability. The 

model was run for 67 days with a 7-day ramping using a hyperbolic tangent function. The 6-

minute water level time series were stored for the last 60 days for computing tidal datums and 

harmonic analysis. Sensitivity studies of some parameters and river effects will be discussed in 

sections 4.1 and 4.2. The final model set-up including all model input files are archived along 

with modeled tidal datums output, correction and quality control tests under the VDatum project 

archive. 

 

3.2. Model grid 

ADCIRC model runs utilize unstructured triangular grids. The unstructured mesh with variable 

horizontal resolution allows more accurate representation of complex shoreline and bathymetry. 

The model domain extends from central California to north of the Juan de Fuca Strait and 

adjacent coastal waters, as well as many embayments along the California, Oregon and 

Washington coasts (Figure 1). The SMS software (http://www.aquaveo.com/sms) was used to 

generate the high resolution unstructured model grid (Figure 3), which extends from the MHW 

shoreline to beyond the continental shelf break offshore. Due to the large coverage, the domain 

was divided into six smaller pieces for mesh generation and connected together afterwards. 

Generally speaking, the grid resolution increases from the open ocean to coasts and embayments 

to better represent the complexity in the shorelines and shallow water tidal dynamics. The grid 

sizes range from around 50 m in some riverine systems and embayments to about 32 km along 

the open ocean boundary. The grid resolves major islands/rocks, various rivers and small 

tributaries, as well as embayments and inlets along the coasts. Figures 3(b) and (c) show closeup views of the grid in Willapa Bay and lower Columbia River and San Francisco Bay, 

respectively. 
8 

3.3. Bathymetry on model grid 

The bathymetric datasets described in Section 2.2 were used to specify the model grid 

bathymetry. Bathymetry at each node is specified by the arithmetic mean of data points within 

the node’s surrounding elements. Since element size changes throughout the model domain, the 

searching ranges for bathymetric data points vary from node to node. As the element size is 

smaller in coastal waters and increases towards deep oceans, bathymetry for nodes near the 

coastline were from more locally distributed data points compared to those in deep waters and 

thus were better resolved. 

The bathymetric data were all referenced to Mean Lower Low Water (MLLW) except in the 

Columbia River where a local datum called the Columbia River Datum (CRD) was used. 

Because of the interaction between tides and river flow, the tidal dynamics in a riverine system is 

largely influenced by the river discharge (Parker, 1991). The discharge rate of the Columbia 

River varies greatly seasonally and interannually. Therefore, the tidal range and tidal datum 

fields change accordingly. Generally speaking, CRD is derived from MLLW computed from 

tidal observations during low river-discharge period. Station data from CO-OPS with CRD to 

MLLW survey bench mark ties were used to derive a transformation relationship from CRD to 

MLLW in the Columbia River. The stations are marked in Figure 4. To simplify the problem, the 

stations were divided into two groups based on the river orientation: stations from Astoria to 

Longview (1 to 4) are put in a first group and stations from Longview to Vancouver (4 to 9) in a 

second group. For group one, a second-order polynomial regression model was built using 

longitude as the independent variable; while for group two, latitude was used as the independent 

variable. The two relationships obtained by fitting MLLW relative to CRD data to either 

longitude or latitude are: 

0.63046 57.368414 1305.57 ( 2) (1)

0.701926 174.123538 10798.4474 ( 1)

2

2

MLLW CRD Lat Lon group

MLLW CRD Lon Lon group

     

     

The regression model and data are contrasted in Figure 5 for each group and all stations in the 

River. Equation (1) was used to convert bathymetric data in Columbia River east of Harrington 

Point (123.6667o W, marked in Figure 4) from CRD to MLLW. 
9 

Figure 3. Unstructured grid for (a) the entire model domain and an enlargement of (b) Willapa 

Bay and the lower Columbia River and (c) San Francisco Bay. The blue line represents 

the model open ocean boundary; the green lines represent islands and the brown line is 

the mainland boundary. 

(a) 

(b) 

(c) 

293009 nodes 

546190 elements 

San Francisco Bay 

Columbia River 

Willapa Bay 

Suisan Bay 

San Pablo Bay 
10 

After all bathymetric data are referred to a common vertical datum (MLLW), they were furthered 

transformed to the model datum – the model zero (MZ), a geopotential surface. An initial guess 

of 1m difference between MZ and MLLW was made based on the average MSL relative to 

MLLW at stations within the model domain. After a stable model run was achieved, the model 

bathymetry was furthered adjusted based on the modeled tidal datum fields. This process was 

repeated iteratively until the tidal datums converged. The final model bathymetry is shown in 

Figure 6. Please note that the contour intervals are not of equal values so that the shallow regions 

along the coast and the continental shelf break can be better resolved. 

Figure 4. The location of stations in Columbia River with CRD to MLLW data from CO-OPS. 

Astoria

Longview

Skamokawa

Wauna

Portland

Rocky Point

Multnomah Channel

St. Helens

Vancouver

Harrington Pt
11 

Figure 5. The regression model of CRD to MLLW in Columbia River (a) from Astoria to 

Longview, (b) from Longview to Vancouver and (c) for the whole river as a 

combination of (a) and (b). 
12 

Figure 6. Final model bathymetry relative to Model Zero (MZ). 
13 

4. Model Results Analysis and Sensitivity Tests 

To verify the model results, the simulated water level time series at each grid node and CO-OPS 

water level station were recorded at 6-minute intervals to compute tidal datum fields for MSL, 

MHHW, MHW, MLW, MLLW, Mean Tidal Level (MTL) and Diurnal Tidal Level (DTL). 

MHHW, MHW, MLW and MLLW are then adjusted to be relative to the MSL field. The four 

tidal datum fields are compared against those from the 105 NOAA tide stations. Because MTL 

and DTL were defined as the algebraic averages of MHW/MLW, and MHHW/MLLW, 

respectively, these two fields are only computed using the corrected datum fields (Section 4.4). 

4.1 Sensitivity study 

The initial model setup resulted in consistent instabilities along the Northern boundary (shown as 

a thick grey line in Figure 3). To resolve the problem, uniformly increased horizontal diffusion 

was tested and spatially varying numerical horizontal diffusion was implemented in the model. 

However, the model only ran slightly longer before it blew up. We extended the model domain 

northward to its current coverage shown in Figure 3 in an effort to avoid the problem. However 

the region of the instability now moved to the northeast corner of the open boundary marked by 

the red circle in Figure 3. Runs with significantly increased horizontal diffusivity, increased grid 

resolution in that area, as well as radiation boundary conditions for that portion of the open 

boundary all failed to stabilize the model simulations. Bottom friction coefficients in that area 

were increased to 0.1 so that it acted as a sponge layer to achieve a stable model run. This 

implementation appeared to work well and did not significantly change the interior model results 

of the region of interest. 
14 

Figure 7. The bottom friction coefficient calculated by different values for the parameters in 

Equation (2). 

Further tests were carried out using different bottom friction coefficients. Hybrid nonlinear 

bottom friction was used in the model so that in deep water, the friction coefficient is constant 

and in shallow water the friction coefficient increases as the depths decreases. The friction 

coefficients are calculated by the following formula: 

FFACTOR = FFACTORMIN (1+ (HBREAK H) ) (2) FTHETA (FGAMMA FTHETA) 

Where FFACTORMIN is the minimum friction coefficient which is equivalent to the coefficient 

in deep water (when H>HBREAK), HBREAK is the break depth separating the bottom friction 

schemes, and FGAMMA and FTHETA are two parameters to determine how fast the friction 

coefficient increases in shallow waters. Because the formulation is not very sensitive to the 

choices of FTHETA, it was set to be the recommended value of 10. Figure 7 shows an example 

of the effect of different choices of FFACTORMIN (Fmin), HBREAK (Hbr) and FGAMMA (Fγ) 

on the bottom friction coefficient where the black line represent the base line by setting all values 

as recommended in ADCIRC user’s manual. The effect of FFACTORMIN on model results is 

quite straightforward with higher values giving rise to overall higher bottom friction, which tends 
15 

to damp tidal amplitudes and slow water currents. However, the effects of different values of 

other parameters are more complicated and often lead to compromising model results in different 

regions. Based on the model-data comparison, the parameters represented by the blue dashed line 

in Figure 7 were used in the final model setup. 

4.2 Effect of river flow 

The initial model setup with no river flows showed sizeable errors in the modeled tidal datums 

for the Columbia River and northeastern San Francisco Bay (i.e. Suisan Bay, see Figure 3c) 

when compared with values from the CO-OPS’ tidal datum database. 

River flows interact with tides both linearly and nonlinearly. As a result, tides in the river with 

considerable discharge are often damped and distorted. To examine the river effect on simulated 

tidal datum fields we conducted three experiments: one with high flow discharge from Columbia 

River, one with low river discharge and one with extremely low river discharge. Firstly, we 

observed that the water level time series have a mean elevation that is much higher with high 

flow than with low flow (Figures 8a and 8b). The initial model run with no river flow failed to 

simulate the natural setup of the mean water surface going up the river. With high flow, the 

water surface in the upper reach of the river is further raised up. Figure 8a illustrates modeled 

water level time series at Vancouver, Washington (marked in Figure 4) while Figure 8b shows 

the observed water level during two eight-day periods with contrasting flow conditions: one with 

high flow and one with low flow. Secondly, the tidal ranges in the upper reaches of river are 

heavily damped (Figures 8c and d) due to more energy loss by friction during ebb tides. Thirdly, 

the derived tidal datum fields vary considerably depending on flow condition. As shown in 

Figure 8e, the MLLW difference (green line) from the two low river flow runs differ by up to 

70cm at the stations in the upper reaches of the river and will be even larger closer to the 

Bonneville Dam. Also shown in the plot is the MLLW relative to CRD at those stations from the 

CO-OPS’ database. As mentioned, CRD is a representation of MLLW under low river discharge. 

A similar problem exists in Suisan Bay, California. However, including river flow from the 

Sacramento River alone did not improve the simulated tidal datums significantly. As contrasted 

to the Columbia River where tidal propagation is restricted by the Dam, the tides are still strong 

in Suisan Bay and progress in and out of the delta region beyond the tide model domain. 

Therefore, a radiation boundary condition along with river flow had to be imposed for better 

results. 
16 

Figure 8. Modeled water levels at Vancouver, WA during high- and low- flow (a) relative to 

Model Zero (MZ) (c) relative to mean water level. Observed water levels during high- 

(May, 2008) and low- (Feb., 2008) flows (b) relative to NAVD88 and (d) relative to 

mean water level. (e) MLLW differences between simulations of a relatively low river 

flow and a very low river flow in Columbia River (in green) and MLLW relative to 

Columbia River Datum (in magenta) from the CO-OPS. 

4.3. Verification of modeled tidal datums 

Figures 9a-d display the model derived tidal datum fields for MHHW, MHW, MLW, and 

MLLW, respectively. The four fields exhibit a similar spatial pattern. In the open ocean and 

coastal region, tides are amplified approaching the shallow water from the open ocean and from 

south to north, which is manifested by the increased magnitudes of tidal datums close to the 

(a) (b) 

(c) (d) 

Day 

(e)
17 

shorelines and towards the north. The tidal ranges (defined as MHW – MLW) increase from less 

than 1 m in the south to over 2m in the north. Tides in the riverine and estuarine systems along 

the shore become more complicated due to the interaction with shoreline, bathymetry and river 

flow. Therefore, no uniform trend can be derived and each system needs to be examined 

individually. For example, in Willapa Bay, tides generally get stronger propagating inwards and 

southwards. The MHW increases from about 1m at the entrance to over 1.3m at the south end of 

the Bay (Figure 10a). In San Francisco Bay, tides are amplified traveling south. In the north of 

San Francisco Bay, tides are amplified in San Pablo Bay but are damped in Suisan Bay (Figure 

10b). 

Figure 11 illustrates model-data comparisons for MHHW, MHW, MLW, and MLLW relative to 

MSL. The black line shows the one-to-one correlation. In general, the comparisons exhibit good 

model-data agreement. Over the 105 stations, magnitudes of the absolute model-data differences 

on average are 7.3 cm, 4.5 cm, 6.1 cm, and 8.1 cm for MHHW, MHW, MLW, and MLLW, 

respectively. The root mean squared error for all four tidal datums is 6.8 cm. The 95 percentile of 

errors in the tidal datums is 15.7 cm in absolute error or 16.5% in relative error. Of the four tidal 

datums, the largest discrepancy shows up in MLLW, which probably is related to the difficulty 

in calculating low waters when ponding and drying happen over very shallow waters. The 

model-data differences of each tidal datum at individual stations are listed for all stations in 

Table B1 Appendix B. 
Figure 9: Model derived tidal datums relative to MSL: (a) MHHW, (b) MHW, (c) MLW and (d) MLLW.

(a) (b) (c) (d) 

18
19 

Figure 10. A close-up view of modeled MHW relative to MSL in (a) Willapa Bay and lower 

Columbia River and (b) San Francisco Bay. 

(a) 

(b) 
20 

Figure 11. Modeled versus observed MHHW (red squares), MHW (blue stars), MLW (green 

stars), and MLLW (magenta squares) (all relative to MSL). 

4.4. Corrections of modeled tidal datum errors

The tidal datum results from the model generally agree well with the CO-OPS water level station 

data at most locations. However, they are not expected to match exactly, and at certain stations 

the discrepancy is fairly large. The results presented above are accepted with the understanding 

that i) the model simulates the astronomical tides only, while the station data includes non-tidal 

river flow, ocean circulation and meteorological effects, ii) the bathymetric data coverage around 

some stations are sparse (if any) and/or outdated, and iii) the grid resolution may not be enough 

in some small rivers/embayments. 

To eliminate the model-data difference at the stations and to match existing VDatum project 

across the project boundary, the TCARI program (Hess et al., 1999; Hess, 2002; Hess, 2003) was 

applied to spatially interpolate the error fields. TCARI may be run using either structured or 

unstructured grids. A version of TCARI written in the Python computer language and based on 

use of an unstructured grid (Barry Gallagher, personal comm.) was used in this application. 

To run TCARI, both the observational stations and locations along the domain boundary (see 

section below) are treated equally as control stations. For each tidal datum, both model-data 

differences at the tidal stations and across-boundary discrepancies between current model results 
21 

and existing VDatum results (Southern California VDatum at the south and the Juan de Fuca 

Strait VDatum at the north) were computed and input to TCARI. Artificial stations were added 

along the offshore open ocean boundary with zero model-data difference so that the interpolated 

error fields would taper down towards zero when approaching the open boundaries offshore 

instead of some averaged error value by default. This is more appropriate in this application 

because the model results were validated in the open ocean against some National Data Buoy 

Center bottom pressure DART buoy data (not shown). Figure 12 shows the interpolated error 

field for MHW over the whole domain with default boundary conditions and added control 

stations along the open-ocean boundary. The two fields agree with each other along the shoreline 

where tide station data are available but differ in the open ocean. A choice of different openocean boundary conditions in the TCARI program may be implemented later for similar 

occasions in future applications. 

Figure 12. TCARI interpolated model MHW error with (a) default boundary conditions and (b) 

added control stations along the outer boundary so that the errors approach zero at the 

outer boundary. 

The error fields for MHHW, MHW, MLW, and MLLW derived from TCARI were then added to 

the model results to get the final tidal datum elevations for VDatum. These TCARI-corrected 

results match the tide station data at the included stations and seamlessly connect to existing 

adjacent VDatum regions. 

Note that the other two tidal datum fields, the MTL and DTL, were produced in a different way. 

They were derived from the four corrected datums by taking the averages between MHW and 
22 

MLW and between MHHW and MLLW, respectively. This is the accepted procedure for 

determining these datum elevations (Gill and Schultz, 2001). 

Figure 13. (a) Map of Pacific Northwest model domain (black line) and bounding polygons of 

the Juan de Fuca Strait (blue line), Central California (magenta line) and Southern 

California (green line) VDatum areas. (b) A close-up view of the overlapping area 

between PNW and SCA and the construction of triangular grid for transitional area. 

Model domain outlined in blue. Bounding polygon for SCA is in green. 

4.5. Connecting with adjacent VDatum areas 

The present Pacific Northwest (PNW) model domain overlaps with the previously developed 

central California (CCA) (Myers and Hess, 2006), southern California (SCA) (Yang et al., 2009) 

and Juan de Fuca Strait (JFS) VDatum areas (Spargo et al., 2006). Figure 13(a) illustrates the 

coverage of the current model domain with respect to existing VDatum areas. In terms of 

coverage, there is no problem for the current model to connect with JFS in the north. However, 

there is a small triangular area to be filled out in order for the current project to replace the 

existing CCA VDatum and connect directly with SCA Vdatum area. Figure 13(b) shows a closeup view of the problem. Even though the current model domain overlaps with SCA model 

domain, its south boundary is not fully connected with the northern boundary of the bounding 

polygon for SCA. Therefore, a small triangular grid was constructed for the transitional area to 

avoid rebuilding the marine grid for SCA or to extend the current model domain further south. 

The tidal datum fields on this extension grid were populated using TCARI. In the input file for 

TCARI, tidal datums at/close to the northern boundary taken from the PNW model and the 

(a) (b)
23 

southern part which falls in the SCA bounding polygon taken from SCA model, as well as the 

values from a water level station (marked by red square in Figure 13b) were used. 

In reality, tidal datums fields should be matched seamlessly across the boundaries. However, this 

is not necessarily engendered when the three tidal datum products were developed separately 

through different model approaches. Therefore, discrepancies across the boundaries were 

examined and existing VDatum values at the boundaries were treated the same way as 

observations at tidal stations in the TCARI input files (See section 4.4) to have continuous tidal 

datum fields which match exactly at the overlapping boundaries. 
24 
25 

5. Creation and Population of the Marine Grid 

5.1. Creation of VDatum marine grid 

Tidal datums in the VDatum software are defined on regularly structured grid called the VDatum 

marine grid. Each node in the marine grid is designated as either a water node or a land node 

based on the high resolution coastline and the bounding polygon. The water nodes are populated 

with valid tidal datum values and the land nodes are assigned null values. The bounding polygon 

helps to constrain model extrapolation within a certain distance to the modeled domain without 

going to rivers/embayment completely outside of the model domain. 

The FORTRAN programs vgrid.f and vpop.f were used to generate and populate the marine grid, 

respectively. Due to the large size of the domain, a set of five similarly sized marine grids were 

generated to cover the whole region (Figure 14). Cautions were taken in making the division so 

that no rivers or embayments were divided into two regions. 

Marine grid points are equally spaced within each region. The resolution of each marine grid is 

set to be 0.001 degree in both zonal and meridional directions, which is the same resolution as 

the Southern California VDatum marine grid. Details of each marine grid boundary limits and 

grid size information are listed in Table 1. 
26 

Figure 14. An illustration of the domain division. 

R1 

R2 

R3 

R4 

R5 
27 

Table 1. VDatum marine grid information for the five regions. 

VDatum 

Region 

Lat. Lon. Window Horiz. 

Spacing 

(deg) 

Vertical 

Spacing 

(deg) 

No. of 

Horiz. 

Nodes 

No. of 

Vertical 

Nodes 

R1 

R2 

R3 

R4 

R5 

[-126.40 -121.94 45.35 

48.02] 

[-126.47 -123.88 42.69 

45.37] 

[-126.47 -123.88 39.99 

42.71] 

[-126.20 -121.82 37.39 

40.01] 

[-124.81 -120.565 34.89 

37.41] 

0.001 

0.001 

0.001 

0.001 

0.001 

0.001 

0.001 

0.001 

0.001 

0.001 

4461 

2591 

2591 

4381 

4246 

2671 

2681 

2721 

2621 

2521 

5.2. Population of VDatum grid with tidal datums 

Tidal datums on the VDatum marine grid were populated by interpolating TCARI-corrected tidal 

datums (Section 4.4) according to the algorithm of Hess and White (2004). Datums at each 

VDatum marine grid point were computed by averaging or linearly interpolating those values 

within a user-specified searching radius or the closest user-specified number of points. In the 

present case, the interpolation was accomplished using the FORTRAN program vpop12.f. It 

populates marine points differently depending on whether the point is inside/outside of the 

ADCIRC model grid elements. If the point was inside an element, datums were calculated using 

an interpolation of the three nodes of the element; if the point was outside any elements, datums 

were computed using the inverse distance weighting of the closest two node values. For region 

R5, modifications in the code were made to take results from both the PNW grid and the small 

grid for the transitional area. 

Two types of verifications were conducted for the tidal datums populated on the marine grids: 

comparing with observations from the CO-OPS tidal stations and examining the match across its 

boundaries with the existing JFS and SCA VDatum regimes. For each of the four datums 

(MHHW, MHW, MLW, and MLLW), the model-data error is less than 0.1 cm and the 

differences between current and previous VDatum projects are less than 0.5 cm for both 

boundaries. 

The consistency between datum fields across the boundaries of different regions of this VDatum 

project was also evaluated. Because the datum fields on these regions were extracted and 

interpolated from the same model results, they were practically identical across all boundaries. 

For each of MHHW, MHW, MLW, and MLLW, maximum differences are less than 0.01 cm. 

The final tidal datums fields on the marine grids (Figure B1) are shown in Appendix B. 
28 
29 

6. Topography of the Sea Surface 

The Topography of the Sea Surface (TSS) is defined as the elevation of the North American 

Vertical Datum of 1988 (NAVD88) relative to local mean sea level (LMSL). Two 

methodologies were utilized for computing NAVD88-to-LMSL values, and the results were 

coupled for creation of the final TSS grid. This grid represents the local variations between a 

LMSL surface and the NAVD88 geopotential surface over the Pacific Northwest VDatum 

region. A positive value specifies that the NAVD88 reference value is further from the center of 

the Earth than the local mean sea level surface. All data are based on the most recent National 

Tidal Datum Epoch (1983-2001). The location of NOAA tide stations and tidal bench marks 

used are illustrated in Figure 155. 

The two methodologies used for creating the NAVD88-to-MSL values are called the indirect 

method and the direct method. The indirect method consists of deriving a value calibrated by 

fitting tide model results to tidal benchmarks leveled in NAVD88. This process used the four 

tidal datum (MHHW, MHW, MLW, and MLLW) values on the marine grids. At each NGS 

benchmark location, we have TBMnavd88, that is the NAVD88 elevation of the tidal benchmark 

relative to MLLW, and a set of TBMdatum values, which is the tidal datum elevation relative to 

MLLW (i.e., Datum – MLLW) at the tidal benchmark. Also, from the four tidal datum grids, we 

have a set of VDdatum values, which is the difference between the tidal datum and MSL (i.e., 

Datum – MSL). 

For the first step, we compute four residuals. The residual, R, for each datum is defined as: 

Rdatum = TBMnavd88 – TBMdatum + VDdatum 

Note that the VD values are interpolated to the location of the benchmark. The four residuals at 

the benchmark are averaged to produce the mean. Note that this mean is an estimate of the 

quantity NAVD88 – MSL. These NAVD88 – MSL derived estimates for the West Coast of the 

Continental United States region can be found in Table C1 in Appendix C. 

The direct method of obtaining NAVD 88-to-LMSL values includes calculating orthometric-totidal datum relationships at NOAA tide stations where elevation information has been compiled 

as part of the CO-OPS procedures for computing accepted tidal datums and orthometric datum 

relationships at tide stations. This process averages elevation relationships of two or more bench 

marks at each station that have published NAVD88 heights. The tide stations and associated 

elevation information used in the computation of the TSS are presented in Table C2. Data for the 

direct method were supplied by CO-OPS and NGS. 

Next, a continuous surface for the West Coast of the Continental United States was generated 

representing inverse sea-surface topography (Figure 16). The mean residuals at all benchmarks 

are merged with values of the quantity NAVD88 – MSL at NOAA tide stations to produce input 

data for gridding. A mesh covering the entire area of benchmarks and water level stations with a 

spatial resolution similar to that of the tidal marine grids is created. Breaklines are inserted to 

represent the influence of land. A sea surface topography field is generated using the Surfer© 

software’s minimum curvature algorithm to create a surface that honors the data as closely as 
30 

possible. The maximum allowed departure value used was 0.001 meters. To control the amount 

of bowing on the interior and at the edges of the grid, an internal tension of 0.3 and boundary 

tension of 0.5 was utilized. Once the gridded topography field has been generated, null values 

are obtained from the marine tidal grids and are inserted to denote the presence of land. 

Quality control was facilitated through several different pathways. After the initial TSS was 

created through interpolation of data compiled through both methodologies, a set of ‘Delta’ 

values are computed. Delta represents the difference between the observed tidal datum and the 

datum as computed by the gridded fields. If S represents the value of the quantity NAVD88 – 

MSL obtained from the sea surface topography grid, Delta (D) for each tidal datum is computed 

as: 

Ddatum = TBMnavd88 – TBMdatum – VDdatum - S 

The averaged Deltas tabulated for the West Coast of the Continental United States TSS’s are 

consistent and small. This provides confidence that grids are in agreement. If they are not, the 

input data and grids are examined, appropriate changes are made, and a new TSS grid is 

computed from the first step. In response to the limited amount of data available, the data used 

to compile the TSS grids for both the direct and indirect methods were utilized in comparing 

against the TSS grid to generalize internal consistency. The mean delta between NAVD88 

(realized through GEOID03) to MSL relationships for the West Coast of the Continental United 

States region was 0.000009 meters with a standard deviation of 0.001882 meters. 

Data derived from both the indirect and direct methodology are initially relative to NAVD88 

realized through GEIOD03. This data derived from both methods is transformed back through 

GEIOD03 to an ellipsoidal reference and then transformed back utilizing GEIOD99 (Figure 17). 

The mean delta between NAVD88 (realized through GEOID99) to MSL relationships for this 

region was -0.000059 meters with a standard deviation of 0.00188 meters. 
31 

Figure 15. Location of tidal benchmarks and tide stations used to compute the West Coast of the 

Continental United States VDatum TSS grids. 
32 

Figure 16. The West Coast of the Continental United States TSS Grid (NAVD88 realized 

through GEOID03). 
33 

Figure 17. The West Coast of the Continental United States TSS Grid (NAVD88 realized 

through GEOID99). 
34 
35 

7. Columbia River Datum Ties to the Ellipsoid 

In the Columbia River that is upstream of the entrance estuary, a fixed low water datum called 

the Columbia River Datum was established by the USACE in 1911. Because of the interaction 

between river discharge and tides and the great seasonal and interannual variation in the 

discharge rate, the low water elevation in the Columbia River can change considerably. 

Therefore, the river datum zero was set at a point below the average low water, but not as low as 

the lowest record for a long period which resulted from a combination of circumstances that 

seldom occur. The relationships between tidal datums are derived from the tide model. This 

section focuses on establishing the spatial relationship between CRD and NAVD88. 

The CRD relative to NAVD88 data are available from the USACE and are referenced to river 

miles along the river channel and in state plane coordinates (Table D1 in Appendix D). We first 

converted the state plane coordinates to NAD83 to be consistent with the horizontal datum frame 

used throughout this study. Figure 18(a) shows the data coverage in longitude/ latitude, and 

Figures 18(b) and 18(c) illustrate the relationship between CRD and NAVD88 along the river 

channel in the Columbia River and Willamette River, respectively. 

To build the spatial coverage of this relationship, we first extended the data at the centerline of 

the channel along transects perpendicular to the channel (Figure 19). The relationship is assumed 

to remain the same along the transect within the channel but unknown outside. Therefore, the 

transects are not extended all the way to intersect with the shoreline. Instead, the transect only 

extends 0.002 degree (about 150m at this latitude) away from the center line on each side and is 

further sampled at equal spacing of about 30m, which resulted in 5 points on each side. This also 

eliminates the problem of intersecting transects at the river bends which would result in multiple 

values at the same location. The TCARI program was used to interpolate and extrapolate the data 

shown in Figure 19 to the Columbia River portion of the tidal model grid (Figure 20). The points 

along the transects that lie outside the coastline or on an island were not used in the TCARI 

program. As shown in Figures 18 (b) and (c), the CRD to NAVD88 difference increase towards 

the upper reaches of the river. However, the relationship is not a linear one even along the river 

channel, as indicated by the density of the contours (Figure 20). 

USACE contracted a private company, David Evans and Associates, Inc., to work on a model for 

the relationship between CRD and the GRS80 ellipsoid over the survey area. Comparison of the 

results from both approaches will be conducted. The final results and the integration within the 

VDatum transformation tool are subject to further consultation with USACE. 
36 

Figure 18. (a) Data availability along the river channel and CRD relative to NAVD88 in (b) 

Columbia River and (c) Willamette River. 
Figure 19. The perpendicular transects of the river channel and the color-coded data values in feet. The black line shows the shoreline. 

37
Figure 20. Columbia River Datum relative to NAVD88 in meters. Contour interval is 0.05 m.

38
39 

8. Summary 

VDatum tidal datum and TSS fields for the coastal waters extending from central California 

to north of Juan de Fuca Strait were developed in this study. Numerous embayments and 

rivers, such as San Francisco Bay and the Columbia River, were also included in the high 

resolution model grid. Tidal dynamics in the study area were simulated using the twodimensional mode of ADCIRC. Tidal datum fields, including mean lower low water 

(MLLW), mean low water (MLW), mean high water (MHW), and mean higher high water 

(MHHW), were calculated from modeled water level time series. The TCARI program was 

used to generate the interpolated error fields from the model-data discrepancies at the water 

level stations. The errors in the modeled tidal datums were compensated for by subtracting 

the interpolated error fields, and the resulting VDatum values match the CO-OPS database 

closely at the stations. 

VDatum software requires that tidal datum fields be defined on regular grids. Due to the 

large size of the studied area, five VDatum marine grids were built to cover the whole 

domain. Tidal datums defined on the unstructured grid were interpolated onto the regular 

grids to be used as input to the VDatum software tool. 

The TSS field was derived using two methodologies: fitting tidal model results to tidal bench 

marks leveled in NAVD88 or calculating orthometric-to-tidal datum relationships at NOAA 

tide stations. Results from two methods were coupled to create the final TSS grids and were 

incorporated into the VDatum tool. 

A simple approach to establish the relationship between CRD and NAVD88 was developed. 

The results can be incorporated in the VDatum software for data conversion between CRD 

and other vertical datums in the Columbia River. 
40 

ACKNOWLEDGMENTS

Adeline Wong provided us the NOS bathymetric data. Digital coastline was provided by 

Julia Skory. Barry Gallagher modified the python version of TCARI for VDatum use. 

Stephen Gill, Gerald Hovis and Chenglin Gan helped with retrieving updated CO-OPS 

station location. Quality control tests were double checked by Zizang Yang. Jiangtao Xu and 

Edward Myers would also like to thank the ADCIRC group at MMAP, which includes Jesse 

Feyen, Yuji Funakoshi, Kurt Hess and Zizang Yang for discussions and help. 

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43 

APPENDIX A. WATER LEVEL STATIONS 

Table A1. NOS Water Level Stations in the Pacific Northwest VDatum region. 

No. Station ID Latitude Longitude Station Name 

1 9412553 35.641700  ‐121.188000 SAN SIMEON

2 9413450 36.605000  ‐121.888000 MONTEREY, MONTEREY HARBOR

3 9413616 36.801700  ‐121.790000 MOSS LANDING,OCEAN PIER

4 9413623 36.810000  ‐121.785000 ELKHORN SLOUGH, ENTRANCE BRIDGE

5 9413631 36.818300  ‐121.747000 ELKHORN SLOUGH AT ELKHORN

6 9414290 37.806700  ‐122.465000 SAN FRANCISCO, SAN FRANCISCO BAY

7 9414317 37.790000  ‐122.387000 PIER 22 1/2, SAN FRANCISCO

8 9414358 37.730000  ‐122.357000 HUNTERS POINT, S.F. BAY

9 9414392 37.665000  ‐122.377000 OYSTER POINT MARINA, SAN FRANCISCO BAY

10 9414458 37.580000  ‐122.253000 SAN MATEO BRIDGE, WEST SIDE

11 9414509 37.506700  ‐122.115000 DUMBARTON BRIDGE, SAN FRANCISCO BAY

12 9414519 37.493300  ‐122.042000 MOWRY SLOUGH, SAN FRANCISCO BAY

13 9414523 37.506700  ‐122.210000 REDWOOD CITY, WHARF 5, S. F. BAY

14 9414575 37.465000  ‐122.023000 COYOTE CREEK, ALVISO SLOUGH

15 9414632 37.595000  ‐122.145000 ALAMEDA CREEK, SAN FRANCISCO BAY

16 9414688 37.695000  ‐122.192000 SAN LEANDRO MARINA, SAN FRANCISCO BAY

17 9414711 37.731700  ‐122.208000 OAKLAND AIRPORT, SAN FRANCISCO BAY

18 9414746 37.771700  ‐122.235000 OAKLAND/ALAMEDA PARK ST. BRIDGE

19 9414750 37.771667  ‐122.298333 ALAMEDA, SAN FRANCISCO BAY

20 9414764 37.795000  ‐122.282000 OAKLAND INNER HARBOR, SAN FRANCISCO BAY

21 9414767 37.793300  ‐122.315000 ALAMEDA NAS, NAVY FUEL PIER

22 9414777 37.805000  ‐122.338000 OAKLAND MIDDLE HARBOR, PIER 40

23 9414782 37.810000  ‐122.360000 YERBA BUENA ISLAND, SAN FRANCISCO BAY

24 9414806 37.846700  ‐122.477000 SAUSALITO, SAN FRANCISCO BAY

25 9414816 37.865000  ‐122.307000 BERKELEY,S.F.BAY

26 9414818 37.863300  ‐122.420000 ANGEL ISLAND, EAST GARRISON, S.F. BAY

27 9414819 37.865000  ‐122.493000 SAUSALITO, COE DOCK, S.F. BAY

28 9414837 37.891700  ‐122.443000 POINT CHAUNCEY, RICHARDSON BAY

29 9414849 37.910000  ‐122.358000 RICHMOND INNER HARBOR, SAN FRANCISCO BAY

30 9414863 37.928300  ‐122.400000 RICHMOND, CHEVRON OIL PIER

31 9414873 37.945000  ‐122.475000 POINT SAN QUENTIN, SAN FRANCISCO BAY

32 9414874 37.943300  ‐122.513000 CORTE MADERA CREEK

33 9414881 37.958300  ‐122.425000 POINT ORIENT

34 9414958 37.910000  ‐122.682000 BOLINAS, BOLINAS LAGOON

35 9415009 37.993300  ‐122.447000 POINT SAN PEDRO, SAN FRANCISCO BAY

36 9415020 37.996100  ‐122.976700 POINT REYES, DRAKES BAY

37 9415052 38.015000  ‐122.503000 GALLINAS, GALLINAS CREEK

38 9415056 38.015000  ‐122.363000 POINT PINOLE, SAN PABLO BAY
44 

39 9415074 38.023300  ‐122.292000 HERCULES WHARF

40 9415096 38.036700  ‐121.880000 PITTSBURG, NEW YORK SLOUGH, SUISUN BAY

41 9415111 38.043300  ‐122.130000 BENICIA, CARQUINEZ STRAIT

42 9415112 38.043300  ‐121.918000 MALLARD ISLAND, SUISUN BAY

43 9415144 38.056700  ‐122.038000 PORT CHICAGO, SUISUN BAY

44 9415218 38.070000  ‐122.250000 MARE IS.NAVAL SHIPYARD,CARQUINEZ STRAIT

45 9415228 38.113300  ‐122.868000 INVERNESS, TOMALES BAY

46 9415252 38.111700  ‐122.498000 PETALUMA RIVER ENTRANCE

47 9415265 38.128300  ‐122.073000 SUISUN SLOUGH ENTRANCE

48 9415320 38.146700  ‐122.883000 REYNOLDS, TOMALES BAY

49 9415379 38.180000  ‐122.045000 JOICE ISLAND, SUISUN SLOUGH

50 9415415 38.191700  ‐122.312000 EDGERLEY ISLAND, NAPA RIVER

51 9415423 38.198300  ‐122.547000 LAKEVILLE, PETALUMA RIVER

52 9415477 38.231700  ‐122.968000 SAND POINT, TOMALES BAY

53 9416841 38.913300  ‐123.708000 ARENA COVE, PACIFIC OCEAN

54 9418686 40.686700  ‐124.222000 HOOKTON SLOUGH,HUMBOLDT BAY

55 9418723 40.723300  ‐124.222000 FIELDS LANDING, HUMBOLDT BAY

56 9418739 40.739000  ‐124.213200 RED BLUFF, HUMBOLDT BAY

57 9418767 40.766700  ‐124.217000 NORTH SPIT, HUMBOLDT BAY

58 9418778 40.778300  ‐124.197000 BUCKSPORT, HUMBOLDT BAY

59 9418799 40.798300  ‐124.120000 FRESHWATER SLOUGH, HUMBOLDT BAY

60 9418801 40.806700  ‐124.167000 EUREKA, HUMBOLDT BAY

61 9418802 40.806700  ‐124.142000 EUREKA SLOUGH, HUMBOLDT BAY

62 9418817 40.818000  ‐124.180000 SAMOA, HUMBOLDT BAY

63 9418865 40.865000  ‐124.148000 MAD RIVER SLOUGH, ARCATA BAY

64 9419059 41.056700  ‐124.147000 TRINIDAD HARBOR

65 9419750 41.745000  ‐124.183000 CRESCENT CITY, PACIFIC OCEAN

66 9431647 42.738970  ‐124.498278 PORT ORFORD, PACIFIC OCEAN

67 9432373 43.120000  ‐124.413000 BANDON, COQUILLE RIVER

68 9432771 43.341700  ‐124.367000 CAPE ARAGO LIGHTHOUSE

69 9432780 43.345000  ‐124.322000 CHARLESTON, COOS BAY

70 9432796 43.351700  ‐124.192000 ISTHMUS SLOUGH, COOS BAY

71 9432879 43.376700  ‐124.297000 SITKA DOCK, COOS BAY

72 9432895 43.410000  ‐124.218000 NORTH BEND, COOS BAY

73 9434938 44.413300  ‐123.990000 DRIFT CREEK, ALSEA RIVER

74 9435308 44.593300  ‐124.008000 WEISER POINT, YAQUINA RIVER

75 9435380 44.625000  ‐124.043000 SOUTH BEACH, YAQUINA RIVER

76 9435385 44.626700  ‐124.055000 YAQUINA USCG STA, NEWPORT

77 9435827 44.810000  ‐124.058000 DEPOE BAY

78 9437262 45.430000  ‐123.945000 NETARTS, NETARTS BAY

79 9437540 45.554530  ‐123.918944 GARIBALDI

80 9438125 45.811700  ‐122.827000 MULTNOMAH CHANNEL, COLUMBIA RIVER

81 9439008 46.206700  ‐123.950000 FORT STEVENS
45 

82 9439011 46.201700  ‐123.945000 HAMMOND NMFS PIER

83 9439026 46.171700  ‐123.842000 ASTORIA, YOUNGS BAY

84 9439040 46.207310  ‐123.768306 ASTORIA, TONGUE POINT, COLUMBIA RIVER

85 9439069 46.186700  ‐123.588000 KNAPPA

86 9439099 46.160000  ‐123.405000 WAUNA, COLUMBIA RIVER

87 9439135 46.181700  ‐123.180000 BEAVER

88 9439189 45.696700  ‐122.868000 ROCKY POINT, MULTNOMAH CHANNEL

89 9439201 45.865000  ‐122.797000 ST. HELENS, COLUMBIA RIVER

90 9440083 45.631700  ‐122.697000 VANCOUVER, COLUMBIA RIVER

91 9440422 46.108300  ‐122.957000 LONGVIEW, COLUMBIA RIVER

92 9440569 46.266700  ‐123.452000 SKAMOKAWA, COLUMBIA RIVER

93 9440571 46.265000  ‐123.653000 ALTOONA, COLUMBIA RIVER

94 9440572 46.268300  ‐124.037000 JETTY A, COLUMBIA RIVER

95 9440574 46.273300  ‐124.072000 NORTH JETTY

96 9440575 46.268300  ‐123.827000 KNAPPTON

97 9440691 46.430000  ‐123.903000 NASELLE RIVER SWING BRIDGE

98 9440747 46.501700  ‐124.023000 NAHCOTTA, WILLAPA BAY

99 9440846 46.623300  ‐123.945000 BAY CENTER, PALIX RIVER, WILLAPA BAY

100 9440875 46.663300  ‐123.798000 SOUTH BEND

101 9440910 46.707470  ‐123.966917 TOKE POINT, WILLAPA BAY

102 9441102 46.904310  ‐124.105083 WESTPORT

103 9441156 46.950000  ‐124.128000 POINT BROWN

104 9441187 46.968300  ‐123.853000 ABERDEEN, GRAYS HARBOR

105 9442396 47.913300  ‐124.637000 LA PUSH, QUILLAYUTE RIVER
46 
APPENDIX B. Modeled Tidal Datum Errors and Corrected TIDAL DATUMS ON MARINE GRID 

Figure B1. Tidal datums on Pacific Northwest VDatum marine grids. (a) MHHW, (b) MHW, (c) MLW, (d) MLLW. Color bars are in 

the unit of meters.

Longitude Longitude Longitude Longitude

(a) MHHW (b) MHW (c) MLW (d) MLLW

47
48 

Table B1. Tidal datum errors (modeled minus observed in meters and the absolute relative 

error) at the 105 CO-OPS water level stations. 

No. Station ID MHHW MHW MLW MLLW 

1 9412553 0.065

8.52%

0.043

7.95%

‐0.050

9.63%

‐0.014

1.64%

2 9413450 0.065

8.44%

0.050

9.05%

‐0.050

9.51%

‐0.024

2.74%

3 9413616 0.071

9.43%

0.056

10.28%

‐0.062

12.07%

‐0.053

6.31%

4 9413623 0.057

7.44%

0.039

6.91%

‐0.069

13.42%

‐0.050

6.00%

5 9413631 0.078

10.36%

0.062

11.53%

‐0.051

9.59%

‐0.031

3.55%

6 9414290 0.060

7.18%

0.021

3.29%

‐0.048

7.97%

‐0.038

4.01%

7 9414317 0.059

6.47%

0.022

3.02%

‐0.045

6.93%

‐0.037

3.67%

8 9414358 0.037

3.73%

‐0.010

1.21%

‐0.016

2.22%

0.003

0.27%

9 9414392 0.024

2.33%

‐0.020

2.39%

‐0.007

0.85%

0.013

1.11%

10 9414458 0.031

2.85%

‐0.015

1.65%

0.017

1.93%

0.045

3.61%

11 9414509 0.040

3.33%

‐0.004

0.36%

0.040

3.93%

0.057

4.09%

12 9414519 0.050

4.11%

0.007

0.67%

0.094

8.83%

0.165

11.61%

13 9414523 0.026

2.27%

‐0.020

2.08%

0.039

3.98%

0.064

4.74%

14 9414575 0.042

3.39%

‐0.008

0.79%

0.097

8.64%

0.168

11.19%

15 9414632 0.127

12.70%

0.076

9.39%

0.027

3.33%

‐0.053

5.90%

16 9414688 0.030

2.76%

‐0.016

1.79%

0.000

0.04%

0.027

2.27%

17 9414711 0.036

3.72%

‐0.008

0.96%

‐0.012

1.62%

0.008

0.71%

18 9414746 0.022

2.25%

‐0.021

2.72%

‐0.039

5.69%

‐0.027

2.66%

19 9414750 0.040

4.19%

‐0.006

0.74%

‐0.035

5.01%

‐0.018

1.68%

20 9414764 0.040

4.27%

‐0.007

0.91%

‐0.031

4.53%

‐0.016

1.54%

21 9414767 0.037

4.06%

‐0.006

0.82%

‐0.034

4.96%

‐0.016

1.55%
49 

22 9414777 0.054

6.05%

0.004

0.50%

‐0.045

6.82%

‐0.038

3.85%

23 9414782 0.054

6.07%

0.011

1.53%

‐0.034

5.03%

‐0.025

2.52%

24 9414806 0.064

7.95%

0.023

3.67%

‐0.058

9.84%

‐0.040

4.26%

25 9414816 0.066

7.65%

0.026

3.88%

‐0.047

7.18%

‐0.032

3.19%

26 9414818 0.065

7.88%

0.023

3.59%

‐0.043

6.88%

‐0.027

2.81%

27 9414819 0.074

9.17%

0.031

5.05%

‐0.060

9.94%

‐0.046

4.92%

28 9414837 0.070

8.56%

0.028

4.43%

‐0.060

10.05%

‐0.054

5.84%

29 9414849 0.059

6.91%

0.021

3.19%

‐0.038

5.86%

‐0.023

2.35%

30 9414863 0.055

6.43%

0.014

2.04%

‐0.035

5.42%

‐0.020

2.01%

31 9414873 0.068

8.29%

0.028

4.36%

‐0.048

7.82%

‐0.042

4.51%

32 9414874 0.047

5.67%

0.003

0.55%

0.044

7.07%

0.160

16.89%

33 9414881 0.060

7.06%

0.020

3.05%

‐0.034

5.33%

‐0.019

1.97%

34 9414958 0.207

32.12%

0.159

35.00%

‐0.080

17.56%

‐0.103

15.40%

35 9415009 0.067

7.88%

0.028

4.25%

‐0.051

8.28%

‐0.043

4.56%

36 9415020 0.064

7.87%

0.043

7.05%

‐0.042

7.26%

‐0.011

1.12%

37 9415052 0.069

8.18%

0.033

5.03%

‐0.022

3.42%

‐0.004

0.44%

38 9415056 0.084

9.80%

0.050

7.45%

‐0.039

5.98%

‐0.027

2.78%

39 9415074 0.055

6.31%

0.019

2.79%

‐0.013

1.90%

‐0.001

0.15%

40 9415096 0.061

9.63%

0.082

17.31%

‐0.040

8.34%

0.019

2.79%

41 9415111 0.100

13.21%

0.078

13.12%

‐0.050

8.32%

‐0.018

2.10%

42 9415112 0.077

12.11%

0.090

18.59%

‐0.047

9.45%

0.008

1.20%

43 9415144 0.115

16.05%

0.098

17.46%

‐0.071

12.80%

‐0.043

5.49%

44 9415218 0.072

8.80%

0.040

6.09%

‐0.019

2.94%

0.008

0.84%
50 

45 9415228 0.125

15.05%

0.126

20.83%

‐0.081

14.04%

‐0.069

7.76%

46 9415252 0.072

8.32%

0.029

4.13%

0.004

0.60%

0.045

4.45%

47 9415265 0.129

17.88%

0.110

19.42%

‐0.064

11.10%

‐0.035

4.42%

48 9415320 0.134

16.54%

0.131

22.28%

‐0.104

19.00%

‐0.118

14.03%

49 9415379 0.134

17.71%

0.114

18.78%

‐0.061

10.13%

‐0.027

3.26%

50 9415415 0.063

7.17%

0.037

5.26%

‐0.025

3.45%

‐0.030

3.02%

51 9415423 0.093

10.51%

0.051

7.11%

0.014

1.83%

0.022

2.14%

52 9415477 0.121

15.75%

0.112

20.33%

‐0.094

18.65%

‐0.106

13.22%

53 9416841 0.060

7.19%

0.044

7.05%

‐0.038

6.25%

‐0.031

3.26%

54 9418686 0.065

6.76%

0.048

6.50%

‐0.000

0.04%

0.011

0.93%

55 9418723 0.090

9.54%

0.063

8.63%

‐0.033

4.59%

‐0.001

0.08%

56 9418739 0.084

8.89%

0.061

8.39%

‐0.020

2.69%

‐0.008

0.74%

57 9418767 0.055

5.70%

0.029

3.87%

0.031

4.16%

0.074

6.51%

58 9418778 0.046

4.65%

0.025

3.28%

0.054

7.15%

0.110

9.59%

59 9418799 0.047

4.44%

0.017

2.09%

0.052

6.73%

0.099

8.87%

60 9418801 0.104

10.62%

0.058

7.47%

0.074

9.23%

0.152

12.78%

61 9418802 0.051

4.94%

0.026

3.14%

0.075

9.17%

0.153

12.64%

62 9418817 0.055

5.38%

0.028

3.54%

0.092

11.15%

0.177

14.49%

63 9418865 0.069

6.67%

0.040

5.00%

0.127

14.37%

0.220

17.01%

64 9419059 0.082

8.58%

0.055

7.40%

‐0.040

5.46%

‐0.058

5.26%

65 9419750 0.103

10.65%

0.062

8.06%

‐0.051

6.79%

‐0.072

6.37%

66 9431647 0.089

8.71%

0.063

7.82%

‐0.054

6.94%

‐0.036

2.99%

67 9432373 0.087

8.59%

0.055

6.91%

‐0.034

4.35%

‐0.034

2.96%
51 

68 9432771 0.027

2.33%

‐0.015

1.60%

‐0.046

5.44%

‐0.106

8.99%

69 9432780 0.084

7.74%

0.016

1.77%

0.003

0.35%

0.011

0.92%

70 9432796 0.123

10.52%

0.051

5.25%

0.252

23.33%

0.421

28.25%

71 9432879 0.080

7.44%

0.009

1.03%

0.046

5.26%

0.083

6.52%

72 9432895 0.126

11.03%

0.047

4.97%

0.162

15.90%

0.256

18.00%

73 9434938 0.013

1.24%

0.007

0.88%

‐0.133

19.07%

‐0.253

28.08%

74 9435308 0.091

7.63%

0.036

3.62%

‐0.058

5.92%

‐0.081

5.86%

75 9435380 0.098

8.31%

0.050

5.16%

‐0.060

6.45%

‐0.061

4.52%

76 9435385 0.132

11.57%

0.056

5.84%

‐0.055

5.91%

‐0.054

3.97%

77 9435827 0.083

7.15%

0.037

3.87%

‐0.029

3.15%

‐0.022

1.61%

78 9437262 0.268

27.41%

0.241

32.31%

‐0.070

8.85%

‐0.036

3.27%

79 9437540 0.021

1.84%

‐0.050

5.50%

0.141

14.98%

0.248

18.45%

80 9438125 0.078

14.71%

0.028

7.48%

‐0.042

11.73%

‐0.024

5.49%

81 9439008 0.034

2.77%

‐0.021

2.09%

0.031

3.15%

0.060

4.30%

82 9439011 0.075

6.30%

0.014

1.46%

0.001

0.14%

0.028

2.10%

83 9439026 0.011

0.88%

‐0.045

4.30%

0.075

7.16%

0.119

8.39%

84 9439040 ‐0.007

0.53%

‐0.065

6.21%

0.094

9.19%

0.156

11.37%

85 9439069 0.011

0.89%

‐0.042

4.17%

0.100

9.76%

0.157

11.80%

86 9439099 ‐0.016

1.48%

‐0.075

8.18%

0.069

8.27%

0.110

10.54%

87 9439135 0.038

4.08%

‐0.025

3.26%

‐0.012

1.80%

‐0.003

0.35%

88 9439189 ‐0.022

3.77%

‐0.050

12.17%

‐0.003

0.73%

0.030

6.89%

89 9439201 0.065

11.97%

0.011

2.72%

‐0.026

6.79%

‐0.005

1.10%

90 9440083 ‐0.028

4.77%

‐0.053

13.11%

0.006

1.72%

0.043

10.22%
52 

91 9440422 0.055

7.12%

‐0.017

2.78%

‐0.031

5.94%

‐0.016

2.53%

92 9440569 ‐0.011

0.93%

‐0.068

7.09%

0.079

8.66%

0.130

11.23%

93 9440571 0.015

1.25%

‐0.041

4.19%

0.087

8.87%

0.144

11.23%

94 9440572 0.090

7.57%

0.046

4.76%

‐0.017

1.80%

0.017

1.22%

95 9440574 0.162

14.55%

0.093

10.25%

‐0.109

12.52%

‐0.138

11.11%

96 9440575 ‐0.017

1.33%

‐0.070

6.70%

0.094

9.18%

0.142

10.17%

97 9440691 0.114

7.77%

0.055

4.51%

0.171

12.60%

0.270

14.97%

98 9440747 0.084

5.86%

0.025

2.07%

0.194

14.59%

0.274

15.45%

99 9440846 0.076

5.97%

0.023

2.19%

0.035

3.15%

0.087

5.72%

100 9440875 0.052

3.90%

0.002

0.21%

0.061

5.02%

0.105

6.34%

101 9440910 0.098

7.74%

0.053

5.12%

0.013

1.30%

0.071

4.88%

102 9441102 0.048

3.71%

‐0.004

0.41%

0.062

5.91%

0.102

6.95%

103 9441156 0.025

1.90%

‐0.025

2.29%

0.140

12.25%

0.228

14.26%

104 9441187 0.077

5.57%

0.014

1.19%

0.098

7.82%

0.150

8.76%

105 9442396 0.074

6.06%

0.034

3.37%

‐0.005

0.46%

0.057

3.98%
53 

APPENDIX C. TSS at NGS Bench Marks and CO-OPS Water Level Stations 

Table C1. Derived NAVD 88-to-LMSL values for each tidal datum at NGS benchmarks from 

the West Coast of the Continental United States Tidal Grids. NAVD88 values realized through 

GEOID03. 

Benchmark Latitude Longitude 

From 

MLL

W 

(m) 

From 

MLW 

(m) 

From 

MHW 

(m) 

From 

MHH

W 

(m) 

Avera

ge 

(m) 

Std. 

Dev. 

(m) 

FV0898 35.17083  ‐120.75500  ‐0.829 ‐0.829 ‐0.829 ‐0.828 ‐0.829 0.001

FV1994 35.17111  ‐120.75583  ‐0.829 ‐0.829 ‐0.829 ‐0.828 ‐0.829 0.001

FV1077 35.17194  ‐120.75527  ‐0.832 ‐0.832 ‐0.832 ‐0.831 ‐0.832 0.001

FV1993 35.17194  ‐120.75583  ‐0.832 ‐0.832 ‐0.832 ‐0.831 ‐0.832 0.001

FV1078 35.17222  ‐120.75527  ‐0.832 ‐0.832 ‐0.832 ‐0.831 ‐0.832 0.001

FV1992 35.17222  ‐120.75583  ‐0.829 ‐0.829 ‐0.829 ‐0.828 ‐0.829 0.001

FV1991 35.17333  ‐120.75500  ‐0.832 ‐0.832 ‐0.832 ‐0.831 ‐0.832 0.001

FV1079 35.17500  ‐120.75444  ‐0.829 ‐0.829 ‐0.829 ‐0.828 ‐0.829 0.001

FV1124 35.64277  ‐121.19027  ‐0.909 ‐0.910 ‐0.905 ‐0.904 ‐0.907 0.003

FV1125 35.64277  ‐121.19138  ‐0.910 ‐0.912 ‐0.904 ‐0.903 ‐0.907 0.005

FV1121 35.64305  ‐121.18666  ‐0.910 ‐0.911 ‐0.910 ‐0.909 ‐0.910 0.001

FV1123 35.64305  ‐121.19000  ‐0.909 ‐0.910 ‐0.905 ‐0.904 ‐0.907 0.003

FV0986 35.64416  ‐121.18777  ‐0.911 ‐0.912 ‐0.910 ‐0.908 ‐0.910 0.002

FV1119 35.64416  ‐121.18555  ‐0.907 ‐0.908 ‐0.907 ‐0.906 ‐0.907 0.001

FV1120 35.64444  ‐121.18583  ‐0.907 ‐0.908 ‐0.907 ‐0.906 ‐0.907 0.001

GU3221 36.59777  ‐121.89000  ‐0.908 ‐0.907 ‐0.907 ‐0.907 ‐0.907 0.001

GU3220 36.60027  ‐121.88916  ‐0.905 ‐0.904 ‐0.904 ‐0.904 ‐0.904 0.001

GU4116 36.60138  ‐121.89166  ‐0.908 ‐0.908 ‐0.906 ‐0.906 ‐0.907 0.001

GU3229 36.60166  ‐121.88861  ‐0.905 ‐0.904 ‐0.904 ‐0.904 ‐0.904 0.001

GU4117 36.60194  ‐121.88861  ‐0.905 ‐0.904 ‐0.904 ‐0.904 ‐0.904 0.001

GU2088 36.60305  ‐121.89166  ‐0.902 ‐0.902 ‐0.900 ‐0.900 ‐0.901 0.001

GU2090 36.60361  ‐121.89194  ‐0.902 ‐0.902 ‐0.900 ‐0.900 ‐0.901 0.001

GU3218 36.60361  ‐121.89250  ‐0.905 ‐0.905 ‐0.903 ‐0.903 ‐0.904 0.001

GU3219 36.60638  ‐121.89277  ‐0.911 ‐0.911 ‐0.909 ‐0.909 ‐0.910 0.001

GU3224 36.60750  ‐121.89333  ‐0.905 ‐0.905 ‐0.903 ‐0.903 ‐0.904 0.001

GU3204 36.81416  ‐121.74388  ‐0.867 ‐0.868 ‐0.866 ‐0.866 ‐0.867 0.001

GU3203 36.81472  ‐121.74305  ‐0.846 ‐0.847 ‐0.845 ‐0.845 ‐0.846 0.001

HT2357 37.59305  ‐122.13944  ‐1.135 ‐1.134 ‐1.134 ‐1.134 ‐1.134 0.001

HT2358 37.59305  ‐122.14027  ‐1.137 ‐1.135 ‐1.134 ‐1.134 ‐1.135 0.002

HT2360 37.59333  ‐122.14222  ‐1.137 ‐1.135 ‐1.135 ‐1.135 ‐1.135 0.001

HT2361 37.59333  ‐122.14305  ‐1.134 ‐1.132 ‐1.132 ‐1.132 ‐1.132 0.001

HT2362 37.59361  ‐122.14500  ‐1.137 ‐1.133 ‐1.132 ‐1.132 ‐1.133 0.002

HT0279 37.72916  ‐122.20777  ‐1.014 ‐1.013 ‐1.015 ‐1.014 ‐1.014 0.001

HT0277 37.73055  ‐122.20888  ‐1.017 ‐1.016 ‐1.018 ‐1.017 ‐1.017 0.001

HT0027 37.77055  ‐122.23638  ‐0.980 ‐0.981 ‐0.979 ‐0.979 ‐0.980 0.001

HT0025 37.77111  ‐122.23583  ‐0.980 ‐0.981 ‐0.979 ‐0.979 ‐0.980 0.001
54 

Benchmark Latitude Longitude 

From 

MLL

W 

(m) 

From 

MLW 

(m) 

From 

MHW 

(m) 

From 

MHH

W 

(m) 

Avera

ge 

(m) 

Std. 

Dev. 

(m) 

HT3551 37.77194  ‐122.29750  ‐0.981 ‐0.980 ‐0.978 ‐0.981 ‐0.980 0.001

HT0024 37.77277  ‐122.23444  ‐0.980 ‐0.981 ‐0.979 ‐0.979 ‐0.980 0.001

HT3550 37.77416  ‐122.29944  ‐1.010 ‐1.010 ‐1.014 ‐1.018 ‐1.013 0.004

HT0890 37.77527  ‐122.29833  ‐0.986 ‐0.986 ‐0.990 ‐0.994 ‐0.989 0.004

HT0888 37.77833  ‐122.29694  ‐0.998 ‐0.998 ‐1.002 ‐1.006 ‐1.001 0.004

HT0882 37.78000  ‐122.29722  ‐0.986 ‐0.986 ‐0.990 ‐0.994 ‐0.989 0.004

HT3554 37.78361  ‐122.29611  ‐0.983 ‐0.983 ‐0.987 ‐0.991 ‐0.986 0.004

HT0884 37.78444  ‐122.29611  ‐0.980 ‐0.980 ‐0.984 ‐0.988 ‐0.983 0.004

HT0758 37.78805  ‐122.38916  ‐0.994 ‐0.994 ‐0.988 ‐0.990 ‐0.991 0.003

HT0787 37.78805  ‐122.38722  ‐0.990 ‐0.989 ‐0.980 ‐0.982 ‐0.985 0.005

HT0788 37.78805  ‐122.38722  ‐0.993 ‐0.992 ‐0.983 ‐0.985 ‐0.988 0.005

HT0759 37.79027  ‐122.38750  ‐0.984 ‐0.984 ‐0.984 ‐0.985 ‐0.984 0.001

HT0654 37.79555  ‐122.27861  ‐0.984 ‐0.984 ‐0.983 ‐0.982 ‐0.983 0.001

HT0655 37.79666  ‐122.27888  ‐0.984 ‐0.984 ‐0.983 ‐0.982 ‐0.983 0.001

HT3538 37.80333  ‐122.46555  ‐0.979 ‐0.980 ‐0.977 ‐0.977 ‐0.979 0.002

HT0705 37.80361  ‐122.46611  ‐0.973 ‐0.974 ‐0.971 ‐0.971 ‐0.972 0.001

HT0701 37.80472  ‐122.46583  ‐0.973 ‐0.974 ‐0.971 ‐0.971 ‐0.972 0.001

HT0702 37.80500  ‐122.46611  ‐0.976 ‐0.977 ‐0.974 ‐0.974 ‐0.975 0.001

AE5209 37.80555  ‐122.46555  ‐0.976 ‐0.977 ‐0.974 ‐0.974 ‐0.975 0.001

AH7158 37.80666  ‐122.33111  ‐0.993 ‐0.990 ‐0.986 ‐0.987 ‐0.989 0.003

HT0697 37.80833  ‐122.46972  ‐0.960 ‐0.961 ‐0.975 ‐0.975 ‐0.968 0.009

HT0700 37.80861  ‐122.46972  ‐0.959 ‐0.960 ‐0.976 ‐0.976 ‐0.968 0.009

HT2255 37.80861  ‐122.47000  ‐0.959 ‐0.960 ‐0.976 ‐0.977 ‐0.968 0.010

HT0698 37.80861  ‐122.46972  ‐0.959 ‐0.960 ‐0.976 ‐0.976 ‐0.968 0.009

AH7160 37.80888  ‐122.32944  ‐0.993 ‐0.991 ‐0.986 ‐0.987 ‐0.989 0.003

AH7161 37.80888  ‐122.32722  ‐0.993 ‐0.988 ‐1.000 ‐0.999 ‐0.995 0.006

AH7162 37.80888  ‐122.32833  ‐0.993 ‐0.991 ‐0.986 ‐0.987 ‐0.989 0.003

AH7163 37.80888  ‐122.32833  ‐0.993 ‐0.991 ‐0.986 ‐0.987 ‐0.989 0.003

HT0696 37.80888  ‐122.47027  ‐0.957 ‐0.959 ‐0.977 ‐0.978 ‐0.968 0.011

HT2253 37.80888  ‐122.47055  ‐0.957 ‐0.958 ‐0.978 ‐0.978 ‐0.968 0.012

HT3537 37.84888  ‐122.47722  ‐0.992 ‐0.991 ‐0.987 ‐0.987 ‐0.989 0.003

HT1073 37.85250  ‐122.47777  ‐0.990 ‐0.991 ‐0.982 ‐0.982 ‐0.986 0.005

HT1074 37.85611  ‐122.47861  ‐0.992 ‐0.993 ‐0.980 ‐0.979 ‐0.986 0.008

HT1070 37.85916  ‐122.48416  ‐0.999 ‐0.998 ‐0.996 ‐0.996 ‐0.997 0.001

HT3536 37.86055  ‐122.48638  ‐0.993 ‐0.992 ‐0.991 ‐0.990 ‐0.992 0.001

HT3535 37.86138  ‐122.48833  ‐1.000 ‐0.999 ‐0.997 ‐0.997 ‐0.998 0.001

HT1066 37.86277  ‐122.49166  ‐0.990 ‐0.990 ‐0.990 ‐0.990 ‐0.990 0.000

HT1067 37.86333  ‐122.49222  ‐0.999 ‐0.999 ‐1.000 ‐1.000 ‐0.999 0.000

HT3508 37.99472  ‐122.97583  ‐0.929 ‐0.933 ‐0.937 ‐0.938 ‐0.934 0.004

HT3510 37.99472  ‐122.97500  ‐0.931 ‐0.936 ‐0.940 ‐0.942 ‐0.937 0.005

HT3509 37.99527  ‐122.97611  ‐0.937 ‐0.936 ‐0.937 ‐0.938 ‐0.937 0.001

HT1838 37.99555  ‐122.97638  ‐0.937 ‐0.936 ‐0.937 ‐0.938 ‐0.937 0.001
55 

Benchmark Latitude Longitude 

From 

MLL

W 

(m) 

From 

MLW 

(m) 

From 

MHW 

(m) 

From 

MHH

W 

(m) 

Avera

ge 

(m) 

Std. 

Dev. 

(m) 

HT1839 37.99555  ‐122.97638  ‐0.940 ‐0.939 ‐0.940 ‐0.941 ‐0.940 0.001

HT3507 37.99583  ‐122.97666  ‐0.934 ‐0.933 ‐0.934 ‐0.935 ‐0.934 0.001

HT3503 37.99611  ‐122.97805  ‐0.937 ‐0.936 ‐0.937 ‐0.938 ‐0.937 0.001

HT3505 37.99611  ‐122.97777  ‐0.937 ‐0.936 ‐0.937 ‐0.938 ‐0.937 0.001

HT3506 37.99611  ‐122.97722  ‐0.937 ‐0.936 ‐0.937 ‐0.938 ‐0.937 0.001

HT3504 37.99638  ‐122.97861  ‐0.937 ‐0.936 ‐0.937 ‐0.938 ‐0.937 0.001

JT9538 38.07416  ‐122.25277  ‐1.072 ‐1.075 ‐1.098 ‐1.097 ‐1.085 0.014

JT0318 38.07611  ‐122.24805  ‐1.071 ‐1.075 ‐1.095 ‐1.093 ‐1.083 0.012

JT9537 38.07611  ‐122.24833  ‐1.074 ‐1.078 ‐1.098 ‐1.096 ‐1.086 0.012

JT9387 38.91055  ‐123.70083  ‐0.927 ‐0.927 ‐0.926 ‐0.925 ‐0.926 0.001

JT9388 38.91194  ‐123.70305  ‐0.924 ‐0.924 ‐0.923 ‐0.922 ‐0.923 0.001

JT9393 38.91277  ‐123.70944  ‐0.920 ‐0.920 ‐0.921 ‐0.920 ‐0.920 0.001

JT9392 38.91305  ‐123.70944  ‐0.923 ‐0.923 ‐0.924 ‐0.923 ‐0.923 0.001

JT9390 38.91472  ‐123.70722  ‐0.926 ‐0.926 ‐0.927 ‐0.926 ‐0.926 0.001

JT9391 38.91500  ‐123.70861  ‐0.923 ‐0.923 ‐0.924 ‐0.923 ‐0.923 0.001

LV0656 40.72583  ‐124.21944  ‐0.938 ‐0.942 ‐0.938 ‐0.936 ‐0.939 0.002

LV0264 40.73666  ‐124.20777  ‐0.930 ‐0.950 ‐0.942 ‐0.937 ‐0.940 0.008

LV0264 40.73666  ‐124.20777  ‐0.948 ‐0.947 ‐0.948 ‐0.946 ‐0.947 0.001

LV0652 40.73722  ‐124.21027  ‐0.952 ‐0.951 ‐0.952 ‐0.950 ‐0.951 0.001

LV0653 40.73861  ‐124.21166  ‐0.955 ‐0.951 ‐0.946 ‐0.944 ‐0.949 0.005

LV0266 40.74472  ‐124.19555  ‐1.001 ‐0.977 ‐0.938 ‐0.937 ‐0.963 0.031

LV0636 40.76638  ‐124.21750  ‐1.025 ‐1.025 ‐1.027 ‐1.027 ‐1.026 0.001

LV0360 40.76666  ‐124.21666  ‐1.028 ‐1.028 ‐1.029 ‐1.029 ‐1.028 0.001

LV0361 40.76666  ‐124.21694  ‐1.028 ‐1.028 ‐1.029 ‐1.029 ‐1.028 0.001

LV0637 40.76666  ‐124.21694  ‐1.025 ‐1.025 ‐1.026 ‐1.026 ‐1.025 0.001

LV0359 40.76694  ‐124.21638  ‐1.031 ‐1.031 ‐1.032 ‐1.031 ‐1.031 0.000

LV0634 40.76694  ‐124.21750  ‐1.025 ‐1.025 ‐1.027 ‐1.027 ‐1.026 0.001

LV0630 40.76805  ‐124.21750  ‐1.022 ‐1.021 ‐1.021 ‐1.021 ‐1.021 0.000

LV0632 40.76833  ‐124.21638  ‐1.020 ‐1.020 ‐1.020 ‐1.019 ‐1.020 0.001

LV0631 40.76861  ‐124.21694  ‐1.020 ‐1.020 ‐1.020 ‐1.019 ‐1.020 0.001

LV0647 40.77722  ‐124.19250  ‐0.963 ‐0.962 ‐0.968 ‐0.970 ‐0.966 0.004

LV0642 40.79500  ‐124.12500  ‐0.978 ‐0.978 ‐0.976 ‐0.976 ‐0.977 0.001

LV0643 40.79527  ‐124.12000  ‐0.972 ‐0.972 ‐0.970 ‐0.969 ‐0.971 0.001

LV0289 40.80444  ‐124.12500  ‐0.953 ‐0.970 ‐0.977 ‐0.979 ‐0.970 0.012

LV0287 40.80500  ‐124.14055  ‐0.971 ‐0.972 ‐0.973 ‐0.971 ‐0.972 0.001

LV0639 40.80694  ‐124.14222  ‐0.973 ‐0.972 ‐0.974 ‐0.973 ‐0.973 0.001

LV0640 40.80694  ‐124.14166  ‐0.976 ‐0.975 ‐0.977 ‐0.975 ‐0.976 0.001

LV0352 40.81805  ‐124.17972  ‐1.050 ‐1.051 ‐1.050 ‐1.049 ‐1.050 0.001

LV0351 40.82222  ‐124.17527  ‐1.058 ‐1.060 ‐1.054 ‐1.055 ‐1.056 0.003

LV0350 40.82861  ‐124.17138  ‐1.071 ‐1.072 ‐1.048 ‐1.050 ‐1.060 0.013

LV0344 40.86444  ‐124.15194  ‐0.990 ‐0.991 ‐0.991 ‐0.990 ‐0.990 0.001

LV0346 40.86527  ‐124.14888  ‐0.990 ‐0.991 ‐0.991 ‐0.990 ‐0.991 0.001
56 

Benchmark Latitude Longitude 

From 

MLL

W 

(m) 

From 

MLW 

(m) 

From 

MHW 

(m) 

From 

MHH

W 

(m) 

Avera

ge 

(m) 

Std. 

Dev. 

(m) 

LV0599 41.05611  ‐124.14861  ‐1.022 ‐1.023 ‐1.020 ‐1.020 ‐1.021 0.002

LV0598 41.05638  ‐124.14861  ‐1.022 ‐1.023 ‐1.020 ‐1.020 ‐1.021 0.001

LV0600 41.05638  ‐124.14805  ‐1.022 ‐1.022 ‐1.021 ‐1.020 ‐1.021 0.001

LV0601 41.05638  ‐124.14777  ‐1.022 ‐1.022 ‐1.021 ‐1.021 ‐1.021 0.001

LV0602 41.05638  ‐124.14750  ‐1.019 ‐1.019 ‐1.018 ‐1.018 ‐1.018 0.001

LV0603 41.05694  ‐124.14694  ‐1.021 ‐1.022 ‐1.021 ‐1.021 ‐1.021 0.001

LV0604 41.05722  ‐124.14638  ‐1.021 ‐1.022 ‐1.021 ‐1.021 ‐1.021 0.001

LV0597 41.05833  ‐124.14750  ‐1.021 ‐1.022 ‐1.021 ‐1.021 ‐1.021 0.001

LV0110 41.74611  ‐124.18250  ‐1.014 ‐1.015 ‐1.013 ‐1.013 ‐1.014 0.001

LV0565 41.74638  ‐124.18055  ‐1.017 ‐1.015 ‐1.007 ‐1.004 ‐1.011 0.006

LV0566 41.74638  ‐124.18000  ‐1.026 ‐1.022 ‐1.005 ‐1.000 ‐1.013 0.013

LV0101 41.74777  ‐124.18333  ‐1.016 ‐1.016 ‐1.012 ‐1.011 ‐1.014 0.003

LV0563 41.74805  ‐124.18027  ‐1.014 ‐1.015 ‐1.013 ‐1.013 ‐1.014 0.001

LV0562 41.75027  ‐124.18055  ‐1.018 ‐1.017 ‐1.010 ‐1.008 ‐1.014 0.005

LV0561 41.75138  ‐124.18250  ‐1.024 ‐1.022 ‐1.012 ‐1.009 ‐1.017 0.007

OA0789 42.73888  ‐124.49861  ‐1.047 ‐1.047 ‐1.046 ‐1.048 ‐1.047 0.001

OA0787 42.73916  ‐124.49888  ‐1.050 ‐1.050 ‐1.049 ‐1.051 ‐1.050 0.001

OA0788 42.73916  ‐124.49861  ‐1.050 ‐1.050 ‐1.049 ‐1.051 ‐1.050 0.001

OA0790 42.73916  ‐124.49805  ‐1.047 ‐1.047 ‐1.046 ‐1.048 ‐1.047 0.001

OA0786 42.73944  ‐124.49916  ‐1.047 ‐1.047 ‐1.046 ‐1.048 ‐1.047 0.001

OA0785 42.74000  ‐124.49944  ‐1.047 ‐1.048 ‐1.045 ‐1.047 ‐1.047 0.001

OA0075 42.74111  ‐124.49722  ‐1.050 ‐1.050 ‐1.049 ‐1.051 ‐1.050 0.001

OA0783 42.74194  ‐124.49777  ‐1.047 ‐1.047 ‐1.046 ‐1.048 ‐1.047 0.001

OA0427 43.11805  ‐124.41388  ‐1.117 ‐1.117 ‐1.116 ‐1.116 ‐1.117 0.001

OA0428 43.11916  ‐124.41055  ‐1.107 ‐1.108 ‐1.105 ‐1.105 ‐1.106 0.001

OA0426 43.12055  ‐124.41638  ‐1.119 ‐1.117 ‐1.109 ‐1.108 ‐1.113 0.006

OA0644 43.34361  ‐124.32416  ‐1.091 ‐1.092 ‐1.093 ‐1.092 ‐1.092 0.001

OA0645 43.34388  ‐124.32305  ‐1.089 ‐1.089 ‐1.088 ‐1.086 ‐1.088 0.001

OA0651 43.34444  ‐124.32638  ‐1.095 ‐1.097 ‐1.098 ‐1.096 ‐1.097 0.001

OA0649 43.34472  ‐124.32305  ‐1.101 ‐1.101 ‐1.101 ‐1.100 ‐1.101 0.001

OA0650 43.34472  ‐124.32444  ‐1.096 ‐1.096 ‐1.097 ‐1.095 ‐1.096 0.001

OA0652 43.34666  ‐124.32777  ‐1.095 ‐1.095 ‐1.095 ‐1.094 ‐1.095 0.001

OA0653 43.34750  ‐124.32805  ‐1.088 ‐1.089 ‐1.089 ‐1.087 ‐1.088 0.001

OA0635 43.37277  ‐124.29027  ‐1.099 ‐1.098 ‐1.092 ‐1.093 ‐1.095 0.004

OA0639 43.37277  ‐124.29305  ‐1.097 ‐1.095 ‐1.094 ‐1.095 ‐1.095 0.001

OA0636 43.37305  ‐124.29166  ‐1.100 ‐1.098 ‐1.095 ‐1.096 ‐1.097 0.002

OA0638 43.37305  ‐124.29333  ‐1.091 ‐1.089 ‐1.087 ‐1.088 ‐1.089 0.001

OA0637 43.37333  ‐124.29250  ‐1.098 ‐1.096 ‐1.094 ‐1.094 ‐1.095 0.002

OA0499 43.40527  ‐124.22055  ‐1.126 ‐1.132 ‐1.131 ‐1.131 ‐1.130 0.003

OA0626 43.40527  ‐124.22083  ‐1.126 ‐1.132 ‐1.131 ‐1.131 ‐1.130 0.003

OA0654 43.40777  ‐124.22000  ‐1.123 ‐1.128 ‐1.130 ‐1.131 ‐1.128 0.004

OA0655 43.40833  ‐124.22055  ‐1.129 ‐1.134 ‐1.136 ‐1.136 ‐1.134 0.003
57 

Benchmark Latitude Longitude 

From 

MLL

W 

(m) 

From 

MLW 

(m) 

From 

MHW 

(m) 

From 

MHH

W 

(m) 

Avera

ge 

(m) 

Std. 

Dev. 

(m) 

OA0656 43.40833  ‐124.22027  ‐1.126 ‐1.131 ‐1.133 ‐1.133 ‐1.131 0.003

QE1613 44.62277  ‐124.04638  ‐1.159 ‐1.160 ‐1.160 ‐1.167 ‐1.162 0.004

QE1616 44.62333  ‐124.04527  ‐1.145 ‐1.145 ‐1.145 ‐1.151 ‐1.146 0.003

QE1615 44.62361  ‐124.04277  ‐1.135 ‐1.135 ‐1.134 ‐1.136 ‐1.135 0.001

QE1210 44.62527  ‐124.05777  ‐1.102 ‐1.102 ‐1.104 ‐1.100 ‐1.102 0.002

QE1114 44.62555  ‐124.04388  ‐1.129 ‐1.129 ‐1.129 ‐1.132 ‐1.130 0.002

QE1425 44.80777  ‐124.05777  ‐1.151 ‐1.151 ‐1.151 ‐1.152 ‐1.151 0.001

QE1424 44.80861  ‐124.05805  ‐1.154 ‐1.154 ‐1.154 ‐1.155 ‐1.154 0.001

QE1423 44.80888  ‐124.05805  ‐1.151 ‐1.151 ‐1.151 ‐1.152 ‐1.151 0.001

QE1165 44.80944  ‐124.05777  ‐1.154 ‐1.154 ‐1.154 ‐1.155 ‐1.154 0.001

QE1426 44.80972  ‐124.05888  ‐1.154 ‐1.154 ‐1.154 ‐1.155 ‐1.154 0.001

QE1421 44.81000  ‐124.06055  ‐1.154 ‐1.154 ‐1.154 ‐1.155 ‐1.154 0.001

QE1164 44.81000  ‐124.06083  ‐1.151 ‐1.151 ‐1.151 ‐1.152 ‐1.151 0.001

QE1418 44.81000  ‐124.06083  ‐1.151 ‐1.151 ‐1.151 ‐1.152 ‐1.151 0.001

QE1419 44.81027  ‐124.06055  ‐1.151 ‐1.151 ‐1.151 ‐1.152 ‐1.151 0.001

QE1420 44.81027  ‐124.05805  ‐1.154 ‐1.154 ‐1.154 ‐1.155 ‐1.154 0.001

QE1422 44.81055  ‐124.05833  ‐1.154 ‐1.154 ‐1.154 ‐1.155 ‐1.154 0.001

RD1243 45.56083  ‐123.90777  ‐1.216 ‐1.236 ‐1.252 ‐1.251 ‐1.239 0.017

SC1026 46.17111  ‐123.83611  ‐1.371 ‐1.372 ‐1.371 ‐1.371 ‐1.371 0.001

SC0509 46.17138  ‐123.84250  ‐1.378 ‐1.379 ‐1.380 ‐1.380 ‐1.380 0.001

SC1025 46.17305  ‐123.84277  ‐1.374 ‐1.375 ‐1.378 ‐1.378 ‐1.376 0.002

SC1024 46.17333  ‐123.84277  ‐1.374 ‐1.375 ‐1.378 ‐1.378 ‐1.376 0.002

SC0447 46.18611  ‐123.58694  ‐1.546 ‐1.545 ‐1.545 ‐1.545 ‐1.545 0.001

AC5404 46.19972  ‐123.94666  ‐1.360 ‐1.359 ‐1.358 ‐1.359 ‐1.359 0.001

AC5403 46.20000  ‐123.94638  ‐1.359 ‐1.358 ‐1.358 ‐1.359 ‐1.359 0.001

AC5405 46.20083  ‐123.94944  ‐1.379 ‐1.375 ‐1.336 ‐1.334 ‐1.356 0.024

SC1048 46.20277  ‐123.76555  ‐1.428 ‐1.442 ‐1.449 ‐1.447 ‐1.441 0.010

SC1050 46.20527  ‐123.76555  ‐1.432 ‐1.439 ‐1.441 ‐1.440 ‐1.438 0.004

AC5406 46.20583  ‐123.95138  ‐1.397 ‐1.390 ‐1.314 ‐1.310 ‐1.352 0.047

SC1051 46.20611  ‐123.76472  ‐1.425 ‐1.438 ‐1.445 ‐1.444 ‐1.438 0.009

SC0586 46.20638  ‐123.95333  ‐1.314 ‐1.314 ‐1.331 ‐1.330 ‐1.322 0.010

SC0478 46.20694  ‐123.76472  ‐1.433 ‐1.439 ‐1.440 ‐1.439 ‐1.438 0.003

SC0583 46.20694  ‐123.96083  ‐1.339 ‐1.333 ‐1.356 ‐1.354 ‐1.345 0.011

SC0480 46.20750  ‐123.76500  ‐1.441 ‐1.442 ‐1.440 ‐1.440 ‐1.440 0.001

SC1053 46.20750  ‐123.76472  ‐1.431 ‐1.435 ‐1.436 ‐1.436 ‐1.434 0.003

SC1055 46.20750  ‐123.76555  ‐1.441 ‐1.442 ‐1.440 ‐1.440 ‐1.440 0.001

SC0479 46.20777  ‐123.76500  ‐1.443 ‐1.444 ‐1.442 ‐1.442 ‐1.443 0.001

SC1054 46.20777  ‐123.76472  ‐1.424 ‐1.429 ‐1.430 ‐1.430 ‐1.428 0.003

SC0534 46.26638  ‐123.65500  ‐1.368 ‐1.367 ‐1.367 ‐1.369 ‐1.367 0.001

SD0300 46.27222  ‐124.07000  ‐1.170 ‐1.171 ‐1.169 ‐1.171 ‐1.170 0.001

SD0302 46.27222  ‐124.07000  ‐1.167 ‐1.168 ‐1.166 ‐1.168 ‐1.167 0.001

SD0299 46.27305  ‐124.07250  ‐1.170 ‐1.170 ‐1.165 ‐1.167 ‐1.168 0.003
58 

Benchmark Latitude Longitude 

From 

MLL

W 

(m) 

From 

MLW 

(m) 

From 

MHW 

(m) 

From 

MHH

W 

(m) 

Avera

ge 

(m) 

Std. 

Dev. 

(m) 

SD0298 46.27361  ‐124.06972  ‐1.174 ‐1.174 ‐1.167 ‐1.169 ‐1.171 0.004

SD0297 46.27694  ‐124.06500  ‐1.204 ‐1.193 ‐1.157 ‐1.154 ‐1.177 0.025

SC1021 46.42805  ‐123.90388  ‐1.229 ‐1.229 ‐1.230 ‐1.229 ‐1.229 0.001

SC2839 46.43361  ‐123.90055  ‐0.489 ‐0.490 ‐0.489 ‐0.488 ‐0.489 0.001

SC2840 46.43361  ‐123.90055  ‐0.489 ‐0.490 ‐0.489 ‐0.488 ‐0.489 0.001

SC2841 46.43361  ‐123.90055  ‐0.492 ‐0.493 ‐0.492 ‐0.491 ‐0.492 0.001

SC0953 46.66277  ‐123.79722  ‐1.228 ‐1.227 ‐1.229 ‐1.229 ‐1.228 0.001

SC0954 46.66305  ‐123.79722  ‐1.216 ‐1.215 ‐1.216 ‐1.217 ‐1.216 0.001

SC0956 46.66305  ‐123.79833  ‐1.224 ‐1.223 ‐1.226 ‐1.227 ‐1.225 0.002

SC0955 46.66333  ‐123.79805  ‐1.210 ‐1.209 ‐1.211 ‐1.211 ‐1.210 0.001

SC0957 46.66333  ‐123.79888  ‐1.236 ‐1.235 ‐1.238 ‐1.239 ‐1.237 0.002

SC0916 46.70472  ‐123.97027  ‐1.216 ‐1.213 ‐1.197 ‐1.198 ‐1.206 0.010

SC0917 46.70472  ‐123.96805  ‐1.219 ‐1.218 ‐1.203 ‐1.205 ‐1.211 0.008

SC0795 46.96833  ‐123.85305  ‐1.208 ‐1.207 ‐1.207 ‐1.209 ‐1.208 0.001

SD0157 47.90861  ‐124.63638  ‐1.200 ‐1.187 ‐1.170 ‐1.168 ‐1.181 0.015

SD0158 47.90861  ‐124.63638  ‐1.194 ‐1.181 ‐1.164 ‐1.162 ‐1.175 0.015

SY0868 47.05000  ‐122.90138  ‐1.302 ‐1.305 ‐1.306 ‐1.305 ‐1.304 0.002

SY0865 47.05166  ‐122.90250  ‐1.311 ‐1.314 ‐1.315 ‐1.314 ‐1.313 0.002

SY0866 47.05194  ‐122.90388  ‐1.314 ‐1.317 ‐1.318 ‐1.317 ‐1.316 0.002

SY0535 47.25888  ‐122.41916  ‐1.320 ‐1.320 ‐1.294 ‐1.293 ‐1.307 0.016

SY0536 47.26416  ‐122.41194  ‐1.360 ‐1.357 ‐1.331 ‐1.333 ‐1.345 0.016

SY0536 47.26416  ‐122.41194  ‐1.324 ‐1.324 ‐1.298 ‐1.297 ‐1.311 0.015

SY1272 47.35694  ‐123.10305  ‐1.252 ‐1.252 ‐1.255 ‐1.253 ‐1.253 0.002

SY1274 47.35694  ‐123.10083  ‐1.259 ‐1.259 ‐1.260 ‐1.258 ‐1.259 0.001

SY1271 47.35722  ‐123.10305  ‐1.255 ‐1.255 ‐1.258 ‐1.256 ‐1.256 0.002

SY0805 47.38361  ‐122.82527  ‐1.294 ‐1.295 ‐1.295 ‐1.294 ‐1.295 0.001

SY0804 47.38444  ‐122.82750  ‐1.233 ‐1.234 ‐1.234 ‐1.233 ‐1.234 0.001

SY0920 47.56305  ‐122.62527  ‐1.306 ‐1.307 ‐1.306 ‐1.306 ‐1.306 0.001

SY5718 47.56305  ‐122.62416  ‐1.321 ‐1.322 ‐1.321 ‐1.321 ‐1.321 0.001

SY0270 47.57444  ‐122.36277  ‐1.299 ‐1.299 ‐1.300 ‐1.299 ‐1.299 0.001

SY0271 47.57833  ‐122.36277  ‐1.299 ‐1.299 ‐1.300 ‐1.299 ‐1.299 0.001

SY0272 47.58194  ‐122.36277  ‐1.299 ‐1.299 ‐1.300 ‐1.299 ‐1.299 0.001

SY0273 47.58416  ‐122.36250  ‐1.299 ‐1.299 ‐1.300 ‐1.299 ‐1.299 0.001

SY0283 47.60194  ‐122.33388  ‐1.310 ‐1.312 ‐1.309 ‐1.311 ‐1.311 0.001

SY0286 47.60305  ‐122.33444  ‐1.310 ‐1.312 ‐1.309 ‐1.311 ‐1.311 0.001

SY0290 47.60388  ‐122.33750  ‐1.310 ‐1.312 ‐1.309 ‐1.311 ‐1.311 0.001

SY0289 47.60444  ‐122.33500  ‐1.310 ‐1.312 ‐1.309 ‐1.311 ‐1.311 0.001

SY0959 47.74666  ‐122.72638  ‐1.253 ‐1.254 ‐1.253 ‐1.253 ‐1.253 0.001

SY1164 47.76138  ‐122.85000  ‐1.253 ‐1.254 ‐1.252 ‐1.253 ‐1.253 0.001

SY1162 47.76194  ‐122.85000  ‐1.253 ‐1.254 ‐1.252 ‐1.253 ‐1.253 0.001

SY0225 47.93916  ‐122.35666  ‐1.351 ‐1.351 ‐1.352 ‐1.352 ‐1.352 0.001

SY0227 47.93916  ‐122.35666  ‐1.360 ‐1.360 ‐1.361 ‐1.361 ‐1.361 0.001
59 

Benchmark Latitude Longitude 

From 

MLL

W 

(m) 

From 

MLW 

(m) 

From 

MHW 

(m) 

From 

MHH

W 

(m) 

Avera

ge 

(m) 

Std. 

Dev. 

(m) 

TR2726 48.11138  ‐122.76166  ‐1.198 ‐1.191 ‐1.194 ‐1.190 ‐1.193 0.004

TR0559 48.11583  ‐122.75194  ‐1.195 ‐1.190 ‐1.198 ‐1.196 ‐1.195 0.003

TR0791 48.11972  ‐123.43416  ‐1.159 ‐1.122 ‐1.186 ‐1.167 ‐1.159 0.027

TR0790 48.12333  ‐123.44472  ‐1.163 ‐1.154 ‐1.168 ‐1.164 ‐1.162 0.006

TR0789 48.12722  ‐123.45777  ‐1.165 ‐1.150 ‐1.175 ‐1.167 ‐1.165 0.011

TR0782 48.14000  ‐123.40194  ‐1.178 ‐1.216 ‐1.169 ‐1.198 ‐1.190 0.021

TR0783 48.14000  ‐123.40138  ‐1.178 ‐1.216 ‐1.169 ‐1.198 ‐1.190 0.021

TR0784 48.14055  ‐123.40888  ‐1.178 ‐1.221 ‐1.172 ‐1.205 ‐1.194 0.023

TR0785 48.14055  ‐123.40972  ‐1.177 ‐1.221 ‐1.172 ‐1.206 ‐1.194 0.024

TR0779 48.14055  ‐123.40250  ‐1.181 ‐1.220 ‐1.173 ‐1.203 ‐1.194 0.022

TR0911 48.16138  ‐123.72722  ‐1.152 ‐1.153 ‐1.162 ‐1.161 ‐1.157 0.005

TS0095 48.26055  ‐124.29861  ‐1.096 ‐1.100 ‐1.124 ‐1.112 ‐1.108 0.013

TS0099 48.26194  ‐124.30000  ‐1.098 ‐1.100 ‐1.123 ‐1.111 ‐1.108 0.012

TS0098 48.26361  ‐124.29944  ‐1.101 ‐1.102 ‐1.121 ‐1.109 ‐1.108 0.010

TS0101 48.26416  ‐124.29972  ‐1.101 ‐1.103 ‐1.121 ‐1.109 ‐1.108 0.009

TR0438 48.28444  ‐122.62166  ‐1.387 ‐1.389 ‐1.399 ‐1.400 ‐1.394 0.007

TR0440 48.28472  ‐122.61916  ‐1.394 ‐1.396 ‐1.404 ‐1.405 ‐1.400 0.006

TS0156 48.36555  ‐124.61666  ‐1.057 ‐1.047 ‐1.079 ‐1.071 ‐1.063 0.014

TS0161 48.36555  ‐124.62083  ‐1.058 ‐1.052 ‐1.070 ‐1.066 ‐1.061 0.008

AF8871 48.36583  ‐124.61722  ‐1.057 ‐1.049 ‐1.075 ‐1.068 ‐1.062 0.011

TS0154 48.36638  ‐124.61138  ‐1.058 ‐1.046 ‐1.080 ‐1.071 ‐1.064 0.015

TS0152 48.36694  ‐124.60416  ‐1.063 ‐1.052 ‐1.080 ‐1.072 ‐1.067 0.012

TS0340 48.36694  ‐124.61944  ‐1.058 ‐1.052 ‐1.070 ‐1.065 ‐1.061 0.008

TS0340 48.36694  ‐124.61944  ‐1.058 ‐1.052 ‐1.070 ‐1.065 ‐1.061 0.008

TS0150 48.36694  ‐124.60416  ‐1.063 ‐1.052 ‐1.080 ‐1.072 ‐1.067 0.012

AF8872 48.36805  ‐124.62388  ‐1.058 ‐1.054 ‐1.067 ‐1.064 ‐1.061 0.006

AF8873 48.36805  ‐124.62666  ‐1.058 ‐1.055 ‐1.064 ‐1.063 ‐1.060 0.004

TS0171 48.36833  ‐124.62305  ‐1.058 ‐1.054 ‐1.067 ‐1.064 ‐1.061 0.006

TR0236 48.39305  ‐122.49444  ‐1.351 ‐1.354 ‐1.362 ‐1.365 ‐1.358 0.006

TR0033 48.75055  ‐122.48138  ‐1.371 ‐1.363 ‐1.373 ‐1.370 ‐1.369 0.004

TR0031 48.75222  ‐122.48277  ‐1.368 ‐1.358 ‐1.371 ‐1.368 ‐1.366 0.006

TR0029 48.75333  ‐122.48472  ‐1.363 ‐1.352 ‐1.365 ‐1.362 ‐1.361 0.006

TR0628 48.99277  ‐122.76277  ‐1.353 ‐1.352 ‐1.367 ‐1.369 ‐1.360 0.009

TR0630 48.99277  ‐122.76305  ‐1.356 ‐1.355 ‐1.370 ‐1.372 ‐1.363 0.009

TR0632 48.99722  ‐122.75222  ‐1.357 ‐1.353 ‐1.393 ‐1.395 ‐1.375 0.023

TR0633 48.99722  ‐122.75222  ‐1.366 ‐1.362 ‐1.402 ‐1.404 ‐1.384 0.023

DC1339 32.57888  ‐117.13138  ‐0.763 ‐0.763 ‐0.763 ‐0.763 ‐0.763 0.000

DC1340 32.57972  ‐117.13111  ‐0.763 ‐0.763 ‐0.763 ‐0.763 ‐0.763 0.000

DC0888 32.71388  ‐117.17333  ‐0.760 ‐0.764 ‐0.765 ‐0.761 ‐0.763 0.002

DC1322 32.71555  ‐117.17250  ‐0.755 ‐0.768 ‐0.773 ‐0.771 ‐0.767 0.008

DC1313 32.86527  ‐117.25333  ‐0.772 ‐0.772 ‐0.777 ‐0.777 ‐0.774 0.003

DC1312 32.86583  ‐117.25305  ‐0.775 ‐0.775 ‐0.780 ‐0.780 ‐0.777 0.003
60 

Benchmark Latitude Longitude 

From 

MLL

W 

(m) 

From 

MLW 

(m) 

From 

MHW 

(m) 

From 

MHH

W 

(m) 

Avera

ge 

(m) 

Std. 

Dev. 

(m) 

DC0986 32.86611  ‐117.25277  ‐0.774 ‐0.775 ‐0.780 ‐0.780 ‐0.777 0.003

DC1308 32.86611  ‐117.25305  ‐0.771 ‐0.772 ‐0.777 ‐0.777 ‐0.774 0.003

DC0990 32.86638  ‐117.25305  ‐0.771 ‐0.772 ‐0.777 ‐0.777 ‐0.774 0.003

DC1310 32.86638  ‐117.25250  ‐0.768 ‐0.769 ‐0.774 ‐0.774 ‐0.771 0.003

DX1969 33.60250  ‐117.88388  ‐0.790 ‐0.791 ‐0.790 ‐0.791 ‐0.790 0.001

DX3663 33.60250  ‐117.88333  ‐0.790 ‐0.791 ‐0.790 ‐0.791 ‐0.790 0.001

DX1968 33.60277  ‐117.88333  ‐0.790 ‐0.791 ‐0.790 ‐0.790 ‐0.790 0.001

DX3420 33.60305  ‐117.88222  ‐0.787 ‐0.788 ‐0.787 ‐0.787 ‐0.787 0.001

DX1967 33.60333  ‐117.88277  ‐0.790 ‐0.791 ‐0.790 ‐0.790 ‐0.790 0.001

DX1970 33.60361  ‐117.88416  ‐0.790 ‐0.791 ‐0.789 ‐0.790 ‐0.790 0.001

DY2509 33.70722  ‐118.27388  ‐0.787 ‐0.788 ‐0.786 ‐0.786 ‐0.787 0.001

DY2508 33.70777  ‐118.27500  ‐0.781 ‐0.782 ‐0.780 ‐0.780 ‐0.781 0.001

DY2507 33.70805  ‐118.27638  ‐0.778 ‐0.779 ‐0.777 ‐0.777 ‐0.778 0.001

DY2506 33.70861  ‐118.27722  ‐0.785 ‐0.787 ‐0.787 ‐0.787 ‐0.787 0.001

DY2505 33.70916  ‐118.27944  ‐0.775 ‐0.778 ‐0.785 ‐0.785 ‐0.781 0.005

DY1100 33.70944  ‐118.28277  ‐0.772 ‐0.776 ‐0.788 ‐0.787 ‐0.781 0.008

DY1099 33.71000  ‐118.28333  ‐0.790 ‐0.791 ‐0.789 ‐0.789 ‐0.790 0.001

DY1083 33.71972  ‐118.27166  ‐0.796 ‐0.797 ‐0.797 ‐0.797 ‐0.797 0.000

DY2515 33.72000  ‐118.27138  ‐0.796 ‐0.797 ‐0.797 ‐0.797 ‐0.797 0.000

DY1080 33.72055  ‐118.27138  ‐0.799 ‐0.800 ‐0.800 ‐0.800 ‐0.800 0.000

DY2514 33.72250  ‐118.27250  ‐0.799 ‐0.799 ‐0.800 ‐0.800 ‐0.800 0.000

DY2513 33.72472  ‐118.27333  ‐0.799 ‐0.799 ‐0.800 ‐0.800 ‐0.800 0.001

DY1085 33.72527  ‐118.27611  ‐0.796 ‐0.797 ‐0.798 ‐0.798 ‐0.797 0.001

DY9300 33.72666  ‐118.27138  ‐0.802 ‐0.801 ‐0.803 ‐0.803 ‐0.802 0.001

DY2512 33.72694  ‐118.27361  ‐0.796 ‐0.795 ‐0.797 ‐0.797 ‐0.796 0.001

EW1586 34.01027  ‐118.49555  ‐0.787 ‐0.784 ‐0.793 ‐0.787 ‐0.788 0.004

EW6485 34.34750  ‐119.44361  ‐0.834 ‐0.835 ‐0.833 ‐0.835 ‐0.834 0.001

EW6484 34.34777  ‐119.44388  ‐0.834 ‐0.835 ‐0.833 ‐0.835 ‐0.834 0.001

EW6804 34.35555  ‐119.44083  ‐0.824 ‐0.825 ‐0.823 ‐0.825 ‐0.824 0.001

EW6807 34.35555  ‐119.44000  ‐0.797 ‐0.798 ‐0.796 ‐0.798 ‐0.797 0.001

EW6481 34.35583  ‐119.44138  ‐0.821 ‐0.822 ‐0.820 ‐0.822 ‐0.821 0.001

EW6480 34.35611  ‐119.44138  ‐0.803 ‐0.804 ‐0.802 ‐0.804 ‐0.803 0.001

EW6488 34.35666  ‐119.43861  ‐0.827 ‐0.828 ‐0.826 ‐0.828 ‐0.827 0.001

EW6801 34.35666  ‐119.44083  ‐0.812 ‐0.813 ‐0.811 ‐0.813 ‐0.812 0.001

EW7026 34.41000  ‐119.69055  ‐0.823 ‐0.822 ‐0.824 ‐0.823 ‐0.823 0.001

EW3742 34.41250  ‐119.68750  ‐0.824 ‐0.823 ‐0.823 ‐0.823 ‐0.823 0.001

EW6796 34.41388  ‐119.68583  ‐0.827 ‐0.826 ‐0.826 ‐0.826 ‐0.826 0.000

EW3748 34.41472  ‐119.68472  ‐0.824 ‐0.823 ‐0.823 ‐0.823 ‐0.823 0.001

Table C2. Location and elevation information for NOAA tide gauges used to create the West 

Coast of the Continental United States TSS grids. MSL data are from CO-OPS and NAVD88 

heights were calculated by NGS. 
61 

Station ID Latitude 

(deg) 

Longitude 

(deg) 

MSL 

(m) 

NAVD88 

[GEOID03]

(m) 

NAVD88 

[GEOID99]

(m)

TSS 

[GEOID03] 

(m) 

TSS 

[GEOID99]

(m) 

9410120 32.57830 ‐117.13500 1.695 0.930 0.946  ‐0.765  ‐0.749

9410170 32.71419 ‐117.17358 2.052 1.287 1.271  ‐0.765  ‐0.781

9410230 32.86670 ‐117.25800 2.163 1.389 1.353  ‐0.774  ‐0.811

9410580 33.60330 ‐117.88300 1.861 1.071 1.103  ‐0.790  ‐0.758

9410650 33.70670 ‐118.27300 11.029 10.244 10.233  ‐0.785  ‐0.796

9410660 33.72000 ‐118.27200 2.028 1.229 1.213  ‐0.799  ‐0.815

9410840 34.00830 ‐118.50000 1.594 0.802 0.802  ‐0.792  ‐0.792

9411270 34.34830 ‐119.44300 2.178 1.347 1.346  ‐0.831  ‐0.832

9411340 34.40830 ‐119.68500 1.824 1.003 1.017  ‐0.821  ‐0.807

9412110 35.17670 ‐120.76000 2.149 1.320 1.287  ‐0.829  ‐0.863

9412553 35.64170 ‐121.18800 1.523 0.615 0.542  ‐0.908  ‐0.981

9413450 36.60500 ‐121.88800 1.893 0.988 0.979  ‐0.905  ‐0.914

9413631 36.81830 ‐121.74700 2.662 1.788 1.793  ‐0.874  ‐0.869

9413663 36.85667 ‐121.75500 6.383 5.485 5.492  ‐0.898  ‐0.891

9414290 37.80670 ‐122.46500 2.773 1.804 1.736  ‐0.969  ‐1.036

9414317 37.79000 ‐122.38700 2.057 1.068 1.001  ‐0.989  ‐1.056

9414392 37.66500 ‐122.37700 1.711 0.730 0.691  ‐0.981  ‐1.020

9414458 37.58000 ‐122.25300 5.737 4.746 4.733  ‐0.991  ‐1.004

9414575 37.46500 ‐122.02300 1.388 0.123 0.136  ‐1.265  ‐1.252

9414632 37.59500 ‐122.14500 1.488 0.351 0.344  ‐1.137  ‐1.144

9414688 37.69500 ‐122.19200 2.634 1.627 1.596  ‐1.007  ‐1.038

9414711 37.73170 ‐122.20800 1.620 0.606 0.564  ‐1.014  ‐1.056

9414746 37.77170 ‐122.23500 1.542 0.561 0.507  ‐0.981  ‐1.035

9414750 37.77167 ‐122.29833 2.067 1.086 1.027  ‐0.981  ‐1.040

9414764 37.79500 ‐122.28200 2.369 1.385 1.321  ‐0.984  ‐1.048

9414782 37.81000 ‐122.36000 3.817 2.782 2.711  ‐1.035  ‐1.106

9414806 37.84670 ‐122.47700 1.890 0.903 0.831  ‐0.987  ‐1.059

9414816 37.86500 ‐122.30700 2.488 1.448 1.368  ‐1.040  ‐1.120

9414819 37.86500 ‐122.49300 4.247 3.251 3.179  ‐0.996  ‐1.068

9414837 37.89170 ‐122.44300 4.921 3.906 3.826  ‐1.015  ‐1.095

9414849 37.91000 ‐122.35800 16.048 15.060 14.973  ‐0.988  ‐1.075

9414863 37.92830 ‐122.40000 4.520 3.530 3.444  ‐0.990  ‐1.076

9414873 37.94500 ‐122.47500 3.411 2.423 2.345  ‐0.988  ‐1.066

9414881 37.95830 ‐122.42500 3.213 2.220 2.135  ‐0.993  ‐1.078

9414958 37.91000 ‐122.68200 1.437 0.328 0.303  ‐1.109  ‐1.134

9415020 37.99610 ‐122.97670 2.152 1.214 1.328  ‐0.938  ‐0.824

9415111 38.04330 ‐122.13000 9.621 8.560 8.454  ‐1.061  ‐1.167

9415112 38.04330 ‐121.91800 1.687 0.568 0.461  ‐1.119  ‐1.226

9415193 38.08670 ‐121.68500 3.998 2.639 2.526  ‐1.359  ‐1.472

9415218 38.07000 ‐122.25000 1.864 0.784 0.680  ‐1.080  ‐1.184

9415228 38.11330 ‐122.86800 2.980 2.037 2.128  ‐0.943  ‐0.852

9415252 38.11170 ‐122.49800 1.990 0.932 0.873  ‐1.058  ‐1.117

9415477 38.23170 ‐122.96800 4.843 3.514 3.661  ‐1.329  ‐1.182
62 

Station ID Latitude 

(deg) 

Longitude 

(deg) 

MSL 

(m) 

NAVD88 

[GEOID03]

(m) 

NAVD88 

[GEOID99]

(m)

TSS 

[GEOID03] 

(m) 

TSS 

[GEOID99]

(m) 

9416841 38.91330 ‐123.70800 9.786 8.863 8.872  ‐0.923  ‐0.914

9418686 40.68670 ‐124.22200 1.879 0.923 0.798  ‐0.956  ‐1.081

9418723 40.72330 ‐124.22200 1.635 0.694 0.569  ‐0.941  ‐1.066

9418739 40.74000 ‐124.21200 2.170 1.221 1.100  ‐0.949  ‐1.070

9418767 40.76670 ‐124.21700 5.562 4.537 4.416  ‐1.025  ‐1.146

9418799 40.79830 ‐124.12000 1.350 0.377 0.290  ‐0.973  ‐1.060

9418801 40.80670 ‐124.16700 5.175 4.233 4.133  ‐0.942  ‐1.043

9418802 40.80670 ‐124.14200 2.017 1.041 0.948  ‐0.976  ‐1.069

9418817 40.82670 ‐124.18000 1.811 0.756 0.655  ‐1.055  ‐1.157

9418865 40.86500 ‐124.14800 1.816 0.826 0.741  ‐0.990  ‐1.075

9419059 41.05670 ‐124.14700 2.617 1.594 1.559  ‐1.023  ‐1.058

9419750 41.74500 ‐124.18300 2.254 1.240 1.342  ‐1.014  ‐0.912

9431647 42.73897 ‐124.49828 8.224 7.176 7.127  ‐1.048  ‐1.097

9432373 43.12000 ‐124.41300 0.968  ‐0.144  ‐0.215  ‐1.112  ‐1.183

9432780 43.34500 ‐124.32200 2.390 1.298 1.236  ‐1.092  ‐1.154

9432879 43.37670 ‐124.29700 2.140 1.045 0.982  ‐1.095  ‐1.158

9432895 43.41000 ‐124.21800 4.155 3.026 2.961  ‐1.129  ‐1.194

9435362 44.61670 ‐123.93700 2.051 0.866 0.907  ‐1.185  ‐1.144

9435380 44.62500 ‐124.04300 2.806 1.673 1.702  ‐1.133  ‐1.104

9435385 44.62670 ‐124.05500 2.785 1.679 1.707  ‐1.106  ‐1.079

9435827 44.81000 ‐124.05800 2.382 1.229 1.237  ‐1.153  ‐1.145

9439008 46.20670 ‐123.95000 3.902 2.571 2.539  ‐1.331  ‐1.363

9439011 46.20170 ‐123.94500 2.137 0.783 0.749  ‐1.354  ‐1.388

9439026 46.17170 ‐123.84200 1.969 0.595 0.551  ‐1.374  ‐1.418

9439040 46.20731 ‐123.76831 2.054 0.615 0.587  ‐1.439  ‐1.468

9439069 46.18670 ‐123.58800 2.199 0.654 0.629  ‐1.545  ‐1.570

9439201 45.86500 ‐122.79700 1.047  ‐1.281  ‐1.347  ‐2.328  ‐2.394

9440422 46.10830 ‐122.95700 1.382  ‐0.745  ‐0.797  ‐2.127  ‐2.179

9440569 46.26670 ‐123.45200 1.269  ‐0.286  ‐0.274  ‐1.555  ‐1.543

9440571 46.26500 ‐123.65300 2.311 0.941 0.943  ‐1.370  ‐1.368

9440574 46.27330 ‐124.07200 2.356 1.187 1.181  ‐1.169  ‐1.175

9440691 46.43000 ‐123.90300 2.514 2.020 2.067  ‐0.494  ‐0.447

9440747 46.50170 ‐124.02300 1.993 0.904 0.957  ‐1.089  ‐1.036

9440875 46.66330 ‐123.79800 3.046 1.821 1.888  ‐1.225  ‐1.158

9440910 46.70747 ‐123.96692 2.836 1.627 1.676  ‐1.209  ‐1.161

9441102 46.90431 ‐124.10508 2.386 1.215 1.205  ‐1.171  ‐1.181

9441187 46.96830 ‐123.85300 3.854 2.646 2.642  ‐1.208  ‐1.212

9442396 47.91330 ‐124.63700 2.943 1.773 1.767  ‐1.170  ‐1.176

9443090 48.36667 ‐124.61167 1.925 0.866 0.949  ‐1.059  ‐0.977

9443361 48.26330 ‐124.29700 6.326 5.233 5.284  ‐1.093  ‐1.042

9444090 48.12500 ‐123.44000 10.534 9.369 9.438  ‐1.165  ‐1.097

9444122 48.14000 ‐123.41300 2.519 1.334 1.402  ‐1.185  ‐1.118

9445133 47.74830 ‐122.72700 2.809 1.559 1.601  ‐1.250  ‐1.208
63 

Station ID Latitude 

(deg) 

Longitude 

(deg) 

MSL 

(m) 

NAVD88 

[GEOID03]

(m) 

NAVD88 

[GEOID99]

(m)

TSS 

[GEOID03] 

(m) 

TSS 

[GEOID99]

(m) 

9445246 47.76170 ‐122.85000 2.660 1.407 1.467  ‐1.253  ‐1.193

9445478 47.35830 ‐123.09800 2.616 1.359 1.387  ‐1.257  ‐1.229

9445958 47.56170 ‐122.62300 2.719 1.408 1.413  ‐1.311  ‐1.306

9446281 47.38330 ‐122.82300 3.547 2.240 2.245  ‐1.307  ‐1.302

9446484 47.26667 ‐122.41333 2.268 0.932 0.879  ‐1.336  ‐1.389

9446545 47.25500 ‐122.43200 2.239 0.937 0.886  ‐1.302  ‐1.353

9446969 47.06000 ‐122.90300 2.281 0.962 0.980  ‐1.319  ‐1.301

9447110 47.58500 ‐122.36200 3.600 2.299 2.271  ‐1.301  ‐1.330

9447130 47.60264 ‐122.33931 4.443 3.134 3.105  ‐1.309  ‐1.338

9447427 47.81330 ‐122.38300 2.886 1.564 1.552  ‐1.322  ‐1.334

9447659 47.98000 ‐122.22300 1.896 0.540 0.508  ‐1.356  ‐1.388

9447729 48.04000 ‐122.16800 0.000 0.739 0.708 0.739 0.708

9447952 48.28670 ‐122.61700 2.687 1.290 1.279  ‐1.397  ‐1.408

9448576 48.40000 ‐122.54800 3.017 1.686 1.664  ‐1.331  ‐1.353

9448657 48.44500 ‐122.55500 2.667 1.320 1.296  ‐1.347  ‐1.371

9449211 48.74500 ‐122.49500 6.398 5.035 4.980  ‐1.363  ‐1.418

9449679 48.99170 ‐122.76500 2.238 0.878 0.763  ‐1.360  ‐1.476
64 
65 

APPENDIX D. Columbia River Datum to NAVD88 Data

Table D1. Columbia River Datum relative to NAVD88 along the river channel. 

River Mile Northing Easting CRD Relative to 

NAVD88 (feet) 

Columbia River 

 

23 958799.9 7399110 -0.45 

24 960371.5 7404198 -0.50 

25 960654.8 7409387 -0.57 

26 959901 7414658 -0.65 

27 959147.4 7419930 -0.74 

28 958990.8 7425258 -0.81 

29 959380.9 7430605 -0.87 

30 960791.2 7435722 -0.89 

31 962718.5 7440685 -0.92 

32 963946.3 7445778 -0.92 

33 962925.2 7450907 -0.92 

34 959469.3 7454810 -0.97 

35 955224.7 7458025 -1.01 

36 950862 7460962 -1.09 

37 945599.3 7461774 -1.16 

38 940365.2 7461371 -1.25 

39 935145.5 7460331 -1.35 

40 929959.4 7460340 -1.42 

41 925811.5 7463671 -1.46 

42 921720.7 7467080 -1.50 

43 918149.6 7470831 -1.51 

44 916632.6 7475935 -1.47 

45 915261.1 7481073 -1.46 

46 915023.9 7486388 -1.47 

47 915206 7491699 -1.51 

48 916327.2 7496902 -1.58 

49 917769.6 7501980 -1.63 

50 920738.9 7506400 -1.69 

51 923668.1 7510760 -1.76 

52 925872.1 7515687 -1.86 

53 928046.7 7520547 -1.97 

54 930221.3 7525408 -2.07 

55 930634.9 7530568 -2.18 

56 929840.1 7535833 -2.31 

57 927594.3 7540443 -2.40 

58 924170.7 7544522 -2.49 

59 920747.2 7548601 -2.55 

60 918359.1 7553303 -2.58 

61 915164.6 7557505 -2.62 

62 912026.7 7561757 -2.65 

63 909667.9 7566507 -2.68 
66 

64 905678.1 7570034 -2.75 

65 901688.2 7573561 -2.82 

66 898537.8 7577780 -2.86 

67 895954.4 7582349 -2.98 

68 893531.1 7587006 -3.15 

69 890926 7591546 -3.28 

70 887041 7595017 -3.39 

71 882242.5 7597070 -3.45 

72 877046.5 7597671 -3.48 

73 871810.7 7597921 -3.5 

74 867642.9 7601046 -3.53 

75 863470 7604126 -3.54 

76 858397.9 7605481 -3.58 

77 853325.8 7606836 -3.66 

78 849280 7610128 -3.74 

79 845310.8 7613564 -3.79 

80 840484.4 7615446 -3.82 

81 835253.6 7615712 -3.89 

82 830103.5 7614864 -3.98 

83 824957 7614585 -4.06 

84 819776.2 7615435 -4.11 

85 815098.8 7617779 -4.14 

86 810362.6 7620001 -4.15 

87 805157.6 7620059 -4.13 

88 800130 7618782 -4.16 

89 795244.7 7616878 -4.2 

90 790058.1 7616883 -4.22 

91 785332.3 7619084 -4.24 

92 780817.6 7621763 -4.27 

93 776158.8 7624107 -4.3 

94 771031.1 7625016 -4.32 

95 765781.5 7625077 -4.35 

96 760589.2 7624693 -4.34 

97 755527.5 7623300 -4.39 

98 750465.6 7621907 -4.46 

99 745383.6 7620642 -4.54 

100 740186.9 7621053 -4.62 

101 735171.7 7622606 -4.71 

102 731229.7 7625774 -4.86 

103 728874.9 7630376 -4.95 

104 726957.7 7635253 -5.06 

105 724026.8 7639571 -5.15 

106 720998.5 7643665 -5.24 

107 718630.6 7648384 -5.36 

108 716296.6 7653121 -5.48 

109 714597.9 7658103 -5.61 

110 713201.5 7663200 -5.73 

111 712305.1 7668392 -5.83 

112 711732.5 7673604 -5.93 

113 709847.3 7678514 -6.04 
67 

114 707614.5 7683266 -6.16 

115 705740.3 7688119 -6.28 

116 704635.6 7693250 -6.36 

117 702223.6 7697915 -6.42 

118 698923.8 7701996 -6.49 

119 698130.3 7706983 -6.55 

120 699285.2 7712109 -6.61 

121 700859 7717099 -6.94 

122 701072.6 7722197 -7.07 

123 699340.1 7727130 -7.19 

124 695015.2 7729768 -7.33 

125 692081.3 7733660 -7.46 

126 690850.4 7738769 -7.61 

127 689701.6 7743869 -7.76 

128 689418.5 7749000 -7.92 

129 690948.8 7754053 -8.06 

130 692964.6 7758927 -8.23 

131 695319.6 7763640 -8.42 

132 698199 7767913 -8.61 

133 701029.4 7772218 -8.68 

134 702027.9 7777381 -8.72 

135 703083.1 7782535 -8.75 

136 702360.1 7787729 -8.8 

137 703377.7 7792839 -8.99 

138 706154.9 7797319 -9.01 

139 708916.5 7801804 -9.04 

140 711726 7806287 -9.11 

141 713390.9 7811263 -9.17 

142 714254.6 7816455 -9.22 

143 716082.8 7821361 -9.69 

144 718681.2 7825923 -10.77 

145 722429.9 7829584 -11.78 

 

Willamette River 

0 733440.9 7623141 -4.77 

1 728956.3 7620692 -4.9 

2 725511.4 7616856 -5.02 

3 720543.6 7616073 -5.14 

4 715476.1 7617214 -5.12 

5 710842.7 7619555 -5.15 

6 706910.3 7622929 -5.17 

7 703980.8 7627188 -5.19 

8 700363.4 7630936 -5.21 

9 696891.3 7634786 -5.22 

10 693970.6 7639053 -5.22 

11 690141.8 7642576 -5.25 

12 686281.7 7645978 -5.26 

13 681547.5 7645656 -5.34 

14 676226.4 7646980 -5.43 

15 671208.6 7645643 -5.5 
68 

16 665920.5 7646473 -5.58 

17 660862.9 7647052 -5.59 

18 656145 7649460 -5.65 

19 652711.7 7650040 -5.73 

20 648439.3 7648919 -5.81 

21 643312.6 7647928 -5.89 

22 640007.5 7651965 -5.96 

23 636503.6 7655755 -6.02 

24 631406.1 7657199 -6.09 

25 628249.1 7660897 -6.15 

26 624351.6 7660199 -6.23