Navigability Potential of Washington Rivers and Streams 

Determined with Hydraulic Geometry and a Geographic 

Information System 

Scientific Investigations Report 2009–5122

Prepared in cooperation with the Washington State Department of Natural Resources 

U.S. Department of the Interior

U.S. Geological Survey

Navigability Potential of Washington Rivers and 

Streams Determined with Hydraulic Geometry 

and a Geographic Information System

By Christopher S. Magirl and Theresa D. Olsen

Prepared in cooperation with the 

Washington State Department of Natural Resources

Scientific Investigations Report 2009–5122

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2009

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Suggested citation:

Magirl, C.S., and Olsen, T.D., 2009, Navigability potential of Washington rivers and streams determined with hydraulic 

geometry and a geographic information system: U.S. Geological Survey Scientific Investigations Report 2009–5122, 

22 p.
iii

Figures

Figure 1. Map showing large rivers in the State of Washington represented by the 

NHDPlus dataset ........................................................................... 3

Figure 2. Map showing rivers and streams with a mean annual discharge greater than 

10 cubic feet per second and locations of discharge measurements in the 

State of Washington used in this stud ................................................... 5

Figure 3. Graph showing hydraulic depth, Dh, and mean annual discharge, Q, determined 

from the NHDPlus dataset (MAFLOWU) ................................................ 8

Figure 4. Graph showing top width, Wt, and mean annual discharge, Q, from the NHDPlus 

dataset (MAFLOWU) ........................................................................ 8

Figure 5. Graph showing bottom width, Wb, and mean annual discharge, Q, from the 

NHDPlus dataset (MAFLOWU) ............................................................ 9

Figure 6. Map showing navigability potential of rivers in State of Washington based 

on the regression prediction of hydraulic depth ....................................... 10

Figure 7. Map showing navigability potential of rivers in the State of Washington 

based on the regression prediction of top width ....................................... 11

Figure 8. Map showing navigability potential of rivers in the State of Washington 

based on the regression prediction of bottom width ................................. 12

Figure 9. Map showing navigability potential of rivers in the State of Washington 

based on the NHDPlus slope ............................................................ 13

Contents

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

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

Purpose and Scope ..............................................................................................................................2

Methods...........................................................................................................................................................3

GIS Data Source....................................................................................................................................3

Streamflow-Gaging Station Data .......................................................................................................4

Regression Modeling ...........................................................................................................................4

Calculating Confidence Intervals of Regression Models...............................................................6

Navigability Potential ...........................................................................................................................7

Results .............................................................................................................................................................7

Hydraulic Geometry Relations............................................................................................................7

Maps of Navigability Potential ...........................................................................................................9

Comparison with Known Navigability .............................................................................................12

Bias in Hydraulic Geometry from Selected Locations of Gaging Stations ........................................13

GIS Dataset Artifacts...................................................................................................................................14

Other Potential Error Sources and Caveats ............................................................................................14

Conclusions...................................................................................................................................................15

Acknowledgments.......................................................................................................................................15

References Cited..........................................................................................................................................15

Appendix A. Discharge Measurement Data Used in the Analysis. .................................................17
iv

Conversion Factors and Datum

Conversion Factors

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

mile, nautical (nmi) 1.852 kilometer (km)

yard (yd) 0.9144 meter (m)

Volume

cubic foot (ft3) 0.02832 cubic meter (m3) 

cubic yard (yd3) 0.7646 cubic meter (m3) 

cubic mile (mi3) 4.168 cubic kilometer (km3) 

Flow rate

cubic foot per second (ft3

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

Datum

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

Tables

Table 1. Thresholds of physical river-channel characteristics determined for river flows 

equal to the mean annual discharge that predicts the navigability potential of a 

stream or river reach in the State of Washington ....................................... 2
Navigability Potential of Washington Rivers and Streams 

Determined with Hydraulic Geometry and a Geographic 

Information System

By Christopher S. Magirl and Theresa D. Olsen

Abstract 

Using discharge and channel geometry measurements 

from U.S. Geological Survey streamflow-gaging stations 

and data from a geographic information system, regression 

relations were derived to predict river depth, top width, 

and bottom width as a function of mean annual discharge 

for rivers in the State of Washington. A new technique also 

was proposed to determine bottom width in channels, a 

parameter that has received relatively little attention in the 

geomorphology literature. These regression equations, when 

combined with estimates of mean annual discharge available 

in the National Hydrography Dataset, enabled the prediction 

of hydraulic geometry for any stream or river in the State of 

Washington. 

Predictions of hydraulic geometry can then be compared 

to thresholds established by the Washington State Department 

of Natural Resources to determine navigability potential of 

rivers. Rivers with a mean annual discharge of 1,660 cubic 

feet per second or greater are “probably navigable” and 

rivers with a mean annual discharge of 360 cubic feet per 

second or less are “probably not navigable.” Variance in the 

dataset, however, leads to a relatively wide range of prediction 

intervals. For example, although the predicted hydraulic 

depth at a mean annual discharge of 1,660 cubic feet per 

second is 3.5 feet, 90-percent prediction intervals indicate 

that the actual hydraulic depth may range from 1.8 to 7.0 feet. 

This methodology does not determine navigability—a legal 

concept determined by federal common law—instead, this 

methodology is a tool for predicting channel depth, top width, 

and bottom width for rivers and streams in Washington.

Introduction

The Washington State Constitution (Article XVII, 

Section 1) asserts State 

“ownership to the beds and shores of all navigable 

waters in the state up to and including the line of 

ordinary high tide, in waters where the tide ebbs and 

flows, and up to and including the line of ordinary 

high water with the banks of all navigable rivers and 

lakes.” 

In light of this article of the constitution, the Washington 

State Department of Natural Resources (DNR) needed a 

statewide methodology to assess the navigability potential 

of streams or rivers in the State of Washington. Although 

the question of navigability is ultimately decided by the 

courts, DNR developed thresholds of physical river-channel 

characteristics that predict the navigability potential of 

Washington rivers and streams (table 1). The thresholds in 

table 1 were determined for river flows equal to the mean 

annual discharge. Although other States assert similar 

ownership of navigable streams, DNR has found no other 

States that have thus far established a criterion or methodology 

to assess navigability potential (Michal Rechner, Washington 

State Department of Natural Resources, oral commun., 2008).

In order to determine the navigability potential of a 

stream or river in Washington using the thresholds in table 1, 

a statewide dataset of stream and river metrics was needed. 

Slope and discharge generally are available in geographic 

information system (GIS) datasets for stream segments 

throughout the State, but depth, top width, and bottom width 

are not available. In order to apply the DNR navigability 

thresholds to streams and rivers statewide, a method was 

needed to derive channel depth, top width, and bottom width 

from discharge for any given stream segment.
2 Navigability Potential of Washington Rivers and Streams Determined with Hydraulic Geometry and a GIS

Downstream hydraulic geometry is a channel evaluation 

technique originally developed by Leopold and Maddock 

(1953) that relates width and depth in stream channels to 

discharge. Using U.S. Geological Survey (USGS) streamflowgaging station data collected throughout the United States 

on rivers spanning several orders of magnitude of discharge, 

Leopold and Maddock (1953) found channel depth and width 

(as well as mean velocity and suspended-sediment load) 

correlated exponentially with discharge, Q, in the form

y aQ

y

a

b = ,

where

is the channel variable of interest, and

 and are constants determined by regression. b

(1)

The concept of hydraulic geometry has since become a 

widely applied tool in analyzing the hydrology and channel 

morphology of rivers worldwide (Ferguson, 1986) including 

rivers in the Pacific Northwest (Castro and Jackson, 2001). 

Although commonly applied to the alluvial channels, which 

have a tendency to alter and reshape their geometries (Huang 

and Nanson, 2000; Chew and Ashmore, 2001), exponential 

relations of depth and width to discharge have been found to 

apply to bedrock channels as well (Montgomery and Gran, 

2001). Although the relations hold best for larger rivers and 

have some limitations for smaller, steep-gradient streams 

(Wohl, 2004), the technique of hydraulic geometry does, 

nonetheless, hold true for most rivers and streams.

By applying the principles of hydraulic geometry to 

empirical data from rivers and streams in Washington, a 

statewide relation between discharge and channel metrics can 

be derived. Applied to existing slope and discharge data within 

a GIS framework, these relations provide a methodology for 

deriving channel metrics and an assessment, with the DNR 

thresholds in table 1, of navigability potential for any stream 

or river in the State.

Purpose and Scope

This study, by applying principles of hydraulic geometry 

to statewide discharge and slope data within a GIS, develops a 

methodology to predict the physical characteristics of streams 

and rivers in the State of Washington. Confidence intervals 

of the predictions, based on the variance in the data, also are 

presented. The specific channel characteristics of interest (that 

is, channel depth, top width, bottom width, and channel slope) 

are compared to thresholds established by DNR (table 1) to 

produce a map and dataset of navigability potential for all 

streams and rivers in the State of Washington. These products 

will enable DNR to decide which rivers and streams may have 

navigability potential. The tools and methodology developed 

in this study do not predict or assert navigability. Instead, 

they predict the physical characteristics of a given river reach, 

which, in turn, can indicate the navigability potential of that 

reach.

Table 1. Thresholds of physical river-channel characteristics determined for river 

flows equal to the mean annual discharge that predicts the navigability potential of a 

stream or river reach in the State of Washington.

[Thresholds provided by the Washington State Department of Natural Resources (DNR). 

Abbreviations: <, less than; >, greater than; n/a, not applicable]

Channel 

characteristics

DNR Thresholds

Navigable

Probably not May be depending on 

balance of factors Probably

Mean depth, Dh (feet) Dh < 2 2 < Dh < 3.5 Dh > 3.5

Top width, Wt(feet) Wt

 < 24 24 < Wt < 40 Wt > 40

Bottom width, Wb (feet) Wb < 18 n/a Wb > 18

Gradient or slope, S (feet/foot) S > 0.0047 0.0019 < S < 0.0047 S < 0.0019
Methods 3

Figure 1. Large rivers in the State of Washington represented by the NHDPlus dataset. 

Methods

Development of the methodology to predict channel 

geometry and navigability potential in rivers and streams 

in the State of Washington required assembling a GIS data 

source, collecting channel-geometry data, relating channel 

geometry to the GIS data, and assessing navigability potential.

GIS Data Source

The GIS flowline layer used in the study was the 

1:100,000-scale National Hydrography Dataset (NHD) linked 

to the NHDPlus dataset, a hydrologically conditioned digital 

Oregon Idaho

Washington

Seattle C a s c a d e R a n g e

Queets River

Hoh River

Quinault River

Cowlitz River

Skagit River

White River

Snoqualmie River

Kettle

09-0383_fig01

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47° N

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0 50 100 MILES

0 50 100 KILOMETERS

elevation model (DEM) with 30-m cell-sized resolution (U.S. 

Environmental Protection Agency, 2008). Specifically, the 

Region 17 flowlines, as a shapefile, represented the underlying 

drainage network that served as a surrogate for rivers and 

streams in Washington State (fig. 1). Where available, the 

flowline database contained the river or stream name. The 

specific attributes needed for this study came from the 

NHDPlus FlowlineAttributesFlow database file and included 

the slope (ft/ft) and the mean annual discharge, MAFLOWU 

(ft3/s). The mean annual discharge stored in NHDPlus 

was determined using the unit runoff method, which uses 

catchment area and unit runoff data from regional USGS 

gaging stations to estimate discharge (Research Triangle 

Institute, 2001).
4 Navigability Potential of Washington Rivers and Streams Determined with Hydraulic Geometry and a GIS

Streamflow-Gaging Station Data

The USGS operates more than 200 active streamflowgaging stations in the State of Washington. USGS staff 

periodically measures discharge at each gaging station to 

verify or update the stage-discharge relation. Discharge 

measurements require the collection of depth and watervelocity data at 20 or more locations along a transect 

perpendicular to the flowing water (Rantz and others, 1982). 

Velocity is measured using a current meter (for example, 

a Price AA), an acoustic Doppler velocimeter (ADV), or 

an acoustic Doppler current profiler (ADCP). Water depth 

is measured with either traditional mechanical sounding 

techniques or with the hydroacoustic instrumentation. These 

detailed depth and velocity data are stored at USGS field 

offices and in archives. 

Detailed discharge measurements from gaging stations 

in Washington were collated for this study; the assembled 

data included the calculated discharge, the bathymetric 

profile across the transect, and the top width of the channel 

(appendix A). Owing to the focus of the study to evaluate 

channel characteristics at average discharge, only discharge 

measurements within ±10 percent of the mean annual 

discharge were evaluated. Although assembled discharge 

measurements spanned five orders of magnitude (from about 

1 to 100,000 ft3/s)—representing a reasonable sampling of 

all gaging stations in the State—most measurements were 

from streams with mean annual discharge between 100 and 

10,000 ft3/s; the discharge range thought to bound the DNR 

navigability thresholds. Inspection of the assembled data 

identified anomalies at some gaging stations. Six discharge 

measurements were discarded because they were located on 

small catchments (less than 4 mi2) in an urbanized setting. 

These particular data appeared to be outliers relative to the 

larger dataset, probably as a result of engineering or channel 

alterations to these smaller streams. Another five discharge 

measurements were discarded because they were on streams 

dominated by seepage from a nearby reservoir. All assembled 

discharge measurements had been collected in the last 8 years. 

From the discharge measurements, the hydraulic depth, 

Dh, at the cross section was calculated as the cross-sectional 

wetted area, A, divided by the top width, Wt (Chow, 1959):

D A

W h

t

= . (2)

Hydraulic depth is essentially equivalent to the mean depth 

of the channel. The value of top width of the channel was 

taken directly from the discharge measurement and the crosssectional area was calculated from the measured bathymetric 

profile. 

Determining bottom width, Wb, was more complicated. 

Although calculating bottom width for a trapezoidal channel 

is relatively straight forward, calculating the bottom width of 

cross sections with irregular shapes can be ambiguous. For 

example, on a triangular cross section, bottom width could be 

determined as the width at one-half the maximum depth or 

as the width just upstream of the deepest part of the channel. 

Each choice, however, can introduce bias or artifacts that 

make geomorphic comparisons between disparate channels 

problematic. One approach considered for this study was to 

determine the bottom width at depths of 2.0 and 3.5 ft, the 

thresholds for hydraulic depth listed in table 1. However, 

channels with small to moderate discharge are often less 

than 2.0 or 3.5 ft deep and would thus have an indeterminate 

bottom width. Plotting these threshold-derived bottom widths 

against discharge also resulted in a non-linear relation with 

data truncation at small discharges. Because the focus of this 

study was to assess the navigability potential of a river or 

stream, we elected to calculate bottom width as the channel 

width at the hydraulic depth of the cross section. With this 

approach, a bottom-width value was determined for every 

cross section regardless of shape. The bottom width calculated 

in this manner correlated well with discharge using an 

exponential function, consistent with the methodology of 

hydraulic geometry (Leopold and Maddock, 1953). More 

importantly, this approach is independent of the navigability 

thresholds of table 1; therefore, thresholds can be changed or 

updated without affecting the regression model for the present 

study.

Regression Modeling

Using the selection criteria listed above, a total 

of 264 discharge measurements (representing channel 

measurements at 137 individual gaging stations) were 

assembled and analyzed for the study (fig. 2). As many 

as three replicate measurements were collected for each 

gaging station: 57 stations had one replicate, 33 stations had 

two replicates, and 47 stations had three replicates. Each 

discharge measurement represented an independent sampling 

of a particular gaging station with unique hydraulic and 

morphologic conditions—these conditions could differ greatly 

from year to year. Replicates of the same gaging station do 

not give a true parametric sampling of the entire dataset. The 

replicates, however, were distributed randomly throughout 

the dataset and did not bias the overall trends in the data 

(Tim Cohn, U.S. Geological Survey, oral commun., 2009). 

We chose to include replicates to increase the data available 

for the analysis rather than limit the analysis to fewer data. 

Although this approach does not bias the resulting regression 

model, it does result in overly optimistic confidence intervals 

(see section, “Calculating Confidence Intervals of Regression 

Models”). 
Methods 5

Figure 2. Rivers and streams with a mean annual discharge greater than 10 cubic feet per second and locations of discharge 

measurements in the State of Washington used in this study. 

Consistent with the distribution of the gaging-station 

network in the State of Washington, 193 of the discharge 

measurements were collected west of the crest of the Cascade 

Range (Cascades) and 71 measurements were collected east 

of the crest. An evaluation of the regression relations showed 

no appreciable difference between data collected from the 

eastern and western sides of the Cascades. The depth and 

width of a river channel is a function of the discharge at that 

point in the river. Although discharge per unit area on the 

western side of the Cascade is different than the eastern side 

of the Cascades, the mean annual discharge of a given stream 

represents the integrated climatic influences of precipitation, 

catchment hydrology, and runoff. Therefore, when comparing 

channel shape to mean annual discharge (as opposed to 

drainage area, precipitation, or runoff), the regression relations 

are the same for the eastern and western sides of the State. 

Although precipitation patterns, catchment hydrology, and 

runoff may be different, a river with a mean annual discharge 

of 1,000 ft3/s in the eastern side of the State will have similar 

channel geometry as a river with a mean annual discharge of 

1,000 ft3/s in the western side of the State—the morphologic 

response of the channel depends on the discharge in the river, 

not the drainage area or the depth of precipitation.

NHDPlus streams

USGS streamflow-gaging station

 With one replicate

 With two replicates

 With three replicates

EXPLANATION

09-0383_fig02

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0 50 100 MILES

0 50 100 KILOMETERS
6 Navigability Potential of Washington Rivers and Streams Determined with Hydraulic Geometry and a GIS

Hydraulic data from the gaging stations were spatially 

linked to the NHDPlus flowline network, thus relating 

hydraulic depth, top width, and bottom width to the NHDPlus 

estimate of mean annual discharge (MAFLOWU) and slope. 

Simple linear regression models, or ordinary least squares 

(Helsel and Hirsch, 1992), of the log-log transformations 

of Dh and MAFLOWU, Wt and MAFLOWU, and Wb and 

MAFLOWU were calculated. Those regression equations 

were then transformed back into real coordinate space giving 

equations relating Dh, Wt, and Wb to MAFLOWU in an 

exponential form (eq. 1).

Calculating Confidence Intervals of 

Regression Models

To evaluate the variance of the three regression 

models using ordinary least squares, 90-percent confidence 

intervals were calculated for each relation. Complete details 

for calculating confidence intervals are available in most 

statistics books (for example, Helsel and Hirsch, 1992); a brief 

overview of the techniques used for this study is presented 

here.

Given a population of x-y data, where xi is the ith 

observation of the explanatory (or independent) variable and 

yi is ith observation of the response (or dependent) variable, a 

linear equation

0 1 ˆ , i y b b x = + (3)

exists that minimizes the cumulative error between the 

estimate, yˆ, and the response variable, yi. In equation (3), b0

and b1 are constants adjusted to minimize the estimate error. 

The error estimate, more appropriately termed the error sum of 

squares (SSE), is given by

( )2

1

ˆ ,

n

i

i

SSE y y

=

= − ∑ (4)

where n is the sample size of the dataset. In determining the 

ordinary least squares, a number of variance parameters are 

computed that are used to estimate the confidence intervals. 

Specifically, these parameters are the sums of the squares of 

x (SSX),

SS x x X i

i

n

= − ( ) =

∑ 2

1

 , (5)

the sums of the squares of y (SSY),

SS y y Y i

i

n

= − ( ) =

∑ 2

1

 , (6)

and the sums of the x-y cross products (SXY),

S x x y y XY i i

i

n

= − ( )( ) −

=

∑

1

 , (7)

where x and y are the means of the explanatory and response 

variables, respectively. Using equations (6) and (7), the 

standard error of the regression, s, can be determined with

s

SS b S

n

Y XY = ( ) −

( ) −

1

2 . (8)

Similarly, the coefficient of determination of the regression 

can be calculated with

R SSE

SSY

2 = −1 , (9)

which is the fraction of variance explained by the regression.

The confidence interval, CI for the conditional mean of y

at any value of x (represented by x0) is then determined with 

the following:

( )2

1 0 ˆ ,

X

x x

CI y t s n SS

− = ± • + (10)

where t is from the students’ t-distribution having n-2 degrees 

of freedom with the probability of exceedance of α/2 (Helsel 

and Hirsch, 1992). In this study, we calculated 90-percent 

confidence intervals, thus α = 0.90 and t = 1.65. Equation (10) 

gives an estimate of the uncertainty with which the regression 

relation (eq. 3) represents the mean value of y at a given 

value of x0. Thus, given a value of x0, there is a 90-percent 

confidence that the actual mean of y is within the confidence 

intervals given by equation (10). But equation (10) does not 

give the uncertainty of the regression model to predict an 

individual value of y (as opposed to the mean values of y). To 

estimate the prediction interval, PIα, or the uncertainty of the 

regression equation (3) to predict an individual value of y, the 

follow equation is used (Helsel and Hirsch, 1992):

( )2

1 0 ˆ 1 ,

X

x x PI y t s n SS

− = ± • + + (11)

For the present study, using the determined regression models, 

there is a 90-percent confidence that the real value of y is 

within the limits defined in equation (11).

In analyzing the regression equations of Dh, Wt

, and 

Wb versus MAFLOWU using equations (3)-(11), a number 

of assumptions about the dataset are made (Helsel and 

Hirsch, 1992): (1) y is linearly related to x (in this case, 
Results 7

under a log-log transformation), (2) data used to fit the 

models are representative of the data of interest, (3) variance 

of the residuals is constant, (4) residuals are independent, 

and (5) residuals are normally distributed. Each of these 

assumptions generally are met for the data analysis in this 

study with the possible exception of assumption (2) (see 

section, “Results”).

Navigability Potential

Combining the regression relations of hydraulic depth, 

top width, and bottom width versus discharge with the 

discharge and slope available in the NHDPlus dataset, maps 

of the navigability potential of streams and rivers in the State 

of Washington were constructed. Using the regression models, 

four statewide maps were generated showing the navigability 

potential of Washington rivers and streams based on the four 

channel characteristics. 

Results

The collected channel-geometry data, combined with the 

GIS dataset, enabled the generation of regression relations 

between channel geometry and discharge as well as the 

construction of maps showing the navigability potential of 

Washington State rivers and streams.

Hydraulic Geometry Relations

The hydraulic depth data from the 264 discharge 

measurements plotted as a function of mean annual discharge 

from the NHDPlus dataset is shown in figure 3. The regression 

equation between hydraulic depth and mean annual discharge 

is:

D Q h = 0 23 0 37 . . , (12)

where Q is the mean annual discharge from the NHDPlus 

dataset (MAFLOWU). The coefficient of determination of 

the regression was R2 = 0.67. The 90-percent confidence and 

prediction intervals also are shown in the figure; 

the equation describing the 90-percent prediction intervals is 

log . log .

. . log .

.

PI Q

Q

Dh ( ) = −

± + ( − )

0 369 0 646

0 297 1 004

2 813

127 87

2

 , (13)

Using equation (12) and comparing the results to the 

thresholds listed in table 1, the predicted hydraulic depth is 

3.5 ft for a discharge of 1,664 ft3/s. Similarly, the predicted 

hydraulic depth is 2.0 ft for a discharge of 366 ft3/s. By these 

measures, a river segment with a mean annual discharge, 

given by NHDPlus, greater than 1,660 ft3/s would have a 

tendency toward being navigable although a stream or river 

less than 370 ft3/s would probably not be navigable. The 

variance in the dataset, however, precludes precise predictions. 

For example, although a river with a mean annual discharge 

of 1,664 ft3/s would have a predicted hydraulic depth of 3.5 ft, 

the 90-percent prediction intervals at that discharge indicated 

that the hydraulic depth could range from 1.8 to 7.0 ft.

The top width data plotted as a function of mean annual 

discharge is shown in figure 4. The regression equation 

between top width and mean annual discharge was 

W Q t = 4 85 0 45 . . . (14)

The coefficient of determination of the regression was 

R2 = 0.82. The equation describing the prediction intervals is

log . log .

. . log .

.

PI Q

Q

Wt ( ) = +

± + ( − )

0 450 0 686

0 247 1 004

2 813

127 87

2

 . (15)

According to the regression equation, the predicted 

top width is 40 ft for a discharge of 109 ft3/s and 24 ft for a 

discharge of 35 ft3/s. In contrast to hydraulic depth, which 

required a large discharge to meet the navigability threshold, 

the navigability for the top width of a channel is achieved 

at a modest discharge. The variance in the top width dataset 

also has a wide range: A river with a mean annual discharge 

of 109 ft3/s would have a prediction top width range (at 

90-percent confidence) of 23 to 71 ft.

The bottom width data plotted as a function of mean 

annual discharge (fig. 5) where the regression equation 

between hydraulic depth and mean annual discharge is

W Q b = 2 14 0 46 . . . (16)

The coefficient of determination of the regression was R2 = 

0.75. The equation describing the 90-percent prediction 

intervals is 

log . log .

. . log .

.

PI Q

Q

Wb ( ) = +

± + ( − )

0 460 0 330

0 303 1 004

2 813

127 87

2

 . (17)

According to the regression equation, the predicted 

bottom width is 18 ft for a discharge of 102 ft3/s. The trends 

in hydraulic geometry of bottom width mirror the trends in 

top width, with similar discharge values dictating navigability 

thresholds. The variance in the bottom width dataset shows a 

river with a mean annual discharge of 102 ft3/s would have a 

predicted bottom width range (at 90-percent confidence) from 

9 to 36 ft.
8 Navigability Potential of Washington Rivers and Streams Determined with Hydraulic Geometry and a GIS

Figure 4. Top width, Wt, and mean annual discharge, Q, from the NHDPlus dataset (MAFLOWU). Navigability 

thresholds are shown in table 1.

Figure 3. Hydraulic depth, Dh, and mean annual discharge, Q, determined from the NHDPlus dataset 

(MAFLOWU).Navigability thresholds are shown in table 1.

tac09-0383_fig03

0.1

1

10

100

1 10 100 1,000 10,000 100,000 1,000,000

HYDRAULIC DEPTH, IN FEET

MEAN ANNUAL DISCHARGE FROM THE NHDPlus DATASET, IN CUBIC FEET PER SECOND

Regression model

90-percent confidence intervals, mean response

90-percent prediction intervals, individual estimates of Dh

Hydraulic depth data

Dh = 0.23 Q 0.37

R 2 = 0.67

n = 264

Probably navigable

Maybe navigable

Probably not navigable

3.5 ft

2.0 ft

1

10

100

1,000

10,000

1 10 100 1,000 10,000 100,000 1,000,000

MEAN ANNUAL DISCHARGE FROM THE NHDPlus DATASET, IN CUBIC FEET PER SECOND

TOP WIDTH, IN FEET

Regression model

90-percent confidence intervals, mean response

90-percent prediction intervals, individual estimates of Wt

Hydraulic depth data

Wt = 4.85 Q 0.45

R 2 = 0.82

n = 264

Probably navigable

Maybe navigable

Probably not navigable

40 ft

24 ft
Results 9

Maps of Navigability Potential

Using the regression equations relating hydraulic 

depth, top width, and bottom width to MAFLOWU, all 

stream segments in the State of Washington in the NHDPlus 

dataset can be classified by their navigability potential per 

the thresholds in table 1. The navigability potential of all 

streams and rivers in Washington State based on the relation 

of hydraulic depth and MAFLOWU is shown in figure 6. To 

simplify the figure, only water courses with a MAFLOWU 

greater than 10 ft3/s are displayed. In all, the maps display 

21,798 individual stream segments; the length of individual 

stream segments varied but averaged 1.1 mi. Small streams 

and mountain rivers typically are classified “probably not 

navigable” and the larger rivers away from mountain fronts 

tend to be classified “probably navigable.”

Similar maps were constructed showing navigability 

potential based on top width (fig. 7) and bottom width (fig. 8). 

In both cases, river segments classified as probably navigable 

are widespread, extending high into mountains along most 

rivers and tributaries. 

The maps show that, when considering all three 

hydraulic-geometry variables of interest, hydraulic depth is 

the limiting factor governing navigability potential for most 

rivers. Typically, if a river has a mean annual discharge to 

make it deep enough to meet the required navigability depth, 

then the river also usually is wide enough to be considered 

navigable. Streamflow-gaging station data indicate that 71 data 

points demonstrate adequate depths for navigation (> 3.5 ft). 

Of the 71 data points, 100 percent had top and bottom widths 

greater than the thresholds for navigability (40 and 18 ft, 

respectively). Of the 83 gaging-station data points with 

hydraulics depths between 2.0 and 3.5 ft, 98 percent had top 

widths greater than the navigability threshold and 95 percent 

had bottom widths greater than the navigability threshold.

The navigability potential map based on slope is 

ambiguous (fig. 9). The variability of river slope, as reported 

by the NHDPlus dataset, results in a navigability potential 

map with stream segments that alternate between “probably 

navigable” and “probably not navigable.” Moreover, there 

appears to be poor correlation between navigability potential 

based on slope reported by the NHDPlus dataset and 

navigability potential based on hydraulic depth or width. For 

example, the Hoh and Queets Rivers display navigability 

potential ranging from “probably navigable” to “navigability 

depends on balance of factors” throughout the lower reach, 

though both rivers probably are navigable. Many small 

streams with low gradient that appear to be potentially 

navigable (fig. 9), based on NHDPlus slope, are too shallow 

or narrow to support navigation. In general, slope as reported 

by the NHDPlus data appears to be an inconsistent indicator of 

navigability potential.

Figure 5. Bottom width, Wb, and mean annual discharge, Q, from the NHDPlus dataset (MAFLOWU). Navigability 

thresholds are shown in table 1.

tac09-0383_fig05

1

10

100

1,000

1 10 100 1,000 10,000 100,000 1,000,000

BOTTOM WIDTH AT HYDRAULIC DEPTH, IN FEET

MEAN ANNUAL DISCHARGE FROM THE NHDPlus DATASET, IN CUBIC FEET PER SECOND

Regression model

90-percent confidence intervals, mean response

90-percent prediction intervals, individual estimates of Wb

Hydraulic depth data

Wb = 2.14 Q 0.46

R 2 = 0.75

n = 264

Probably navigable

Probably not navigable

18 ft
10 Navigability Potential of Washington Rivers and Streams Determined with Hydraulic Geometry and a GIS

Figure 6. Navigability potential of rivers in State of Washington based on the regression prediction of hydraulic depth. 

Based on the four maps generated in this study and the 

regression relations, hydraulic depth is the limiting factor 

deciding navigability potential. If the channel of interest 

meets the navigability threshold for hydraulic depth, the 

same channel quite likely meets the navigability criteria for 

EXPLANATION

 Hydraulic depth (Dh), in feet

< 2 probably not navigable

2.0 < 3.5 may be navigable depending on balance of factors

> 3.5 probably navigable

0383_fig06

124° W 123° W 122° W 121° W 120° W 119° W 118° W 117° W

49° N

48° N

47° N

46° N

0 50 100 MILES

0 50 100 KILOMETERS

top width and bottom width. Classification based on channel 

slope from the NHDPlus dataset generally is ambiguous and 

probably should not be used as a primary decision criterion for 

determining navigability potential.
Results 11

Figure 7. Navigability potential of rivers in the State of Washington based on the regression prediction of top width. 

EXPLANATION

Top width (Wt ), in feet

< 24 probably not navigable

24 < 40 may be navigable depending on balance of factors>

> 40 probably navigable

09-0383_fig07

124° W 123° W 122° W 121° W 120° W 119° W 118° W 117° W

49° N

48° N

47° N

46° N

0 50 100 MILES

0 50 100 KILOMETERS
12 Navigability Potential of Washington Rivers and Streams Determined with Hydraulic Geometry and a GIS

Comparison with Known Navigability

A few prominent rivers in the State of Washington have 

been either examined by the courts as to their navigability or 

have been classified by the DNR as being definitely navigable, 

probably navigable, or probably not navigable (Washington 

State Department of Natural Resources, 2004). Navigability 

potential, based on hydraulic depth, is in generally good 

agreement with the DNR provisional map. For example, the 

DNR map and the maps from this study show the Quinault, 

Queets, and Hoh Rivers as being navigable from the Pacific 

Ocean to near the boundary with Olympic National Park. The 

maps also agree along other major rivers including the Skagit, 

Snoqualmie, and Cowlitz Rivers. There were, however, some 

notable disagreements between the two maps. For example, 

although this study indicated the lower White River as being 

“probably navigable,” the DNR map lists the White River 

from Pacific, Washington, to the confluence with the Puyallup 

River as being “probably not navigable.” Based on a court 

case concerning a small section of the Kettle River in the 

State of Washington, DNR also assumed the entire river to 

be “probably not navigable,” yet figure 6 classified most of 

the Kettle River as “probably navigable.” Court evaluation of 

navigability in Washington considers many factors in addition 

to channel morphology. Thus, the navigability maps generated 

in this study can aid in assessing navigability potential; 

however, many factors ultimately dictate the legal threshold of 

navigability.

EXPLANATION

Bottom width (Wb), in feet

< 18 probably not navigable

> 18 probably navigable

0383_fig08

124° W 123° W 122° W 121° W 120° W 119° W 118° W 117° W

49° N

48° N

47° N

46° N

0 50 100 MILES

0 50 100 KILOMETERS

Figure 8. Navigability potential of rivers in the State of Washington based on the regression prediction of bottom width. 
Bias in Hydraulic Geometry from Selected Locations of Gaging Stations 13

EXPLANATION

Slope (S), in feet per foot

<0.0019 probably navigable

 0.0019 < 0.0047 may be navigable depending on balance of factors

>0.0047 probably not navigable

09-0383_fig09

124° W 123° W 122° W 121° W 120° W 119° W 118° W 117° W

49° N

48° N

47° N

46° N

0 50 100 MILES

0 50 100 KILOMETERS

Figure 9. Navigability potential of rivers in the State of Washington based on the NHDPlus slope. 

Bias in Hydraulic Geometry from 

Selected Locations of Gaging Stations 

An assumption is made in the linear-regression analysis 

of this study that the channel characteristics at streamflowgaging stations are representative of the entire river segment, 

but locations of streamflow-gaging stations are not selected 

randomly along rivers, rather the locations of gaging stations 

are selected on the basis of hydraulic conditions beneficial to 

discharge measurement. The location of gaging stations tend 

not to be situated on braided or distributary-channel systems; 

there is a bias in the selected locations of gaging stations 

toward straight reaches of single-channeled rivers with stable 

channel geometry producing stable stage-discharge relations.

When the hydraulic conditions at a streamflow-gaging 

station are controlled by a downstream boulder or cobble 

bar (typical of pool-riffle morphologies), the gaging station 

is considered to be influenced by section control. When 

the hydraulic conditions at a streamflow-gaging station are 

controlled by the roughness of the channel itself (typical of 

prismatic, alluvial channels), the gaging station is considered 

to be influenced by channel control. In developing the 

techniques of hydraulic geometry, Leopold and Maddock 

(1953) were aware that locations of gaging stations may not 

adequately represent averaged channel geometry. Leopold 

and Maddock (1953) attempted to choose data from gaging 

stations predominantly from channel-control sites. 
14 Navigability Potential of Washington Rivers and Streams Determined with Hydraulic Geometry and a GIS

In the present study, we made no attempt to differentiate 

between section control and channel control, nor did we 

preferentially select from channel-control gaging stations; 

the data in this study represent both control types. Thus, the 

methodology developed in the study is potentially biased due 

to the selection of locations for gaging stations. The potential 

bias would result in cross sections that are deeper than an 

average sampling taken at a random location along the river 

reach of interest. Moreover, section control tends to be most 

prevalent in smaller streams and mountain rivers, whereas 

channel control tends to dominate larger, alluvial rivers. The 

bias will be larger on rivers with smaller discharge, with the 

result that some of the smaller rivers could be classified as 

potentially navigable even though the average hydraulic depth 

throughout the river reach, incorporating the full pool-riffle 

sequence, might not actually meet the navigability threshold of 

table 1.

GIS Dataset Artifacts

The NHDPlus dataset is known to contain 

misrepresentations typical of hydrologic GIS databases. For 

example, the dataset has difficulties tracking the drainage 

network through lakes, sloughs, and estuaries; the NHDPlus 

flowline works best when representing rivers that are spatially 

well defined. In addition, the dataset has difficulties with 

distributary channels. Larger rivers often bifurcate into 

multiple channels that span the width of the floodplain. In 

these reaches, NHDPlus will show unique stream segments 

for individual channels, but estimates of mean annual 

discharge are assigned to only one of the channels. This 

results in a digital representation in which one channel is 

overloaded with discharge even though the other channels are 

underrepresented. In most cases, this representation does not 

affect classification outcomes as the overall discharge in the 

river follows the same general course, often reconnecting into 

a single channel downstream. Most secondary channels, where 

present, also are not visible at the final map scale. 

One notable exception is the Skagit River. In the estuary 

delta, the Skagit River bifurcates into two large channels that 

independently empty into Puget Sound about 5 mi from each 

other. At moderate discharge, the northern channel carries 

about 60 percent of the total discharge and the southern 

channel carries about 40 percent, yet NHDPlus reports that 

all discharge follows the southern channel. NHDPlus shows 

the northern channel as a small regional flowline with little 

discharge. Therefore, both channels of the Skagit River are 

large and widely used for navigation in and out of Puget 

Sound; however, the final navigation maps published in this 

study show the northern channel as “probably not navigable,” 

an obvious error. Other errors or artifacts may be present in 

maps from this study, and all data should be verified with field 

observations or checked with independent data. 

Data from NHDPlus were used ‘as is’ (U.S. 

Environmental Protection Agency, 2008), without corrections 

or improvements. Thus, the final navigability potential maps 

are as good as the accuracy of the underlying NHDPlus 

dataset.

Other Potential Error Sources and 

Caveats

As discussed in the section, “Methods,” multiple replicate 

data from some streamflow-gaging stations, although not 

biasing the regression, may result in confidence and prediction 

intervals that are narrower than if one replicate was used. To 

evaluate the effect of multiple replicates on the prediction 

interval, the dataset used in the linear regression of hydraulic 

depth to discharge was recalculated using only the first 

replicate from each gaging station (n = 137). The resulting 

90-percent prediction intervals at a discharge of 1,660 ft3/s, 

using just single replicates, ranged from 1.8 to 7.2 ft, or a 

total range of 5.4 ft—the comparable range of the 90-percent 

prediction interval at 1,660 ft3/s using all 264 data points was 

5.2 ft. Therefore, using all replicates (n = 264) in the analysis 

appeared to narrow the prediction intervals by about 4 percent.

The concepts of hydraulic geometry used in this study 

largely were derived from river data from self-forming alluvial 

rivers and streams. Many channels, however, actively are 

engineered in a way that restricts a channel’s natural trends. 

For example, bank stabilization or channel straightening 

often results in a river that is deeper and narrower than 

would otherwise occur. Similarly, channel maintenance 

(for example, dredging) often results in a channel that is 

deeper and narrower than it would be in a natural setting. 

Data used to develop the hydraulic geometry relations in 

this study were not segregated by degree of anthropogenic 

modification—this information generally was not available, 

would require much effort to obtain, and was beyond the 

scope of this investigation—but it is reasonable to say 

that a wide range in the degree of engineered alteration is 

represented by the channels included in the overall dataset. 

Considering these influences, the predictive equations in this 

study probably underpredict the hydraulic depth of a highly 

engineered channel and overpredict the hydraulic depth of a 

largely natural channel. Similarly, the equations probably also 

would overpredict the width of an engineered channel and 

underpredict the width of a natural channel.

Because depth was determined to be the limiting 

parameter of navigability potential, it is possible that for 

many channels on the threshold of navigability, the results 

from this study may indicate an average depth at or less than 

the navigability threshold when the actual depth, owing to 

anthropogenic effects, could be deeper. Again, a case-by-case 

investigation of the watercourse of interest is needed to fully 

assess the navigability potential.
References Cited 15

Flow regulation and diversions from upstream dams also 

may affect the applicability of the methodology of this study. 

In some Washington rivers, large diversions for agricultural or 

municipal use can significantly lower the effective discharge 

in the channel. However, the mean annual discharge reported 

by NHDPlus is based on watershed and climatic parameters 

and generally does not consider flow regulation. Therefore, the 

NHDPlus discharge reported for more heavily used rivers may 

tend to overestimate the discharge in the channel. Again, caseby-case investigations of individual watercourses are needed 

to fully assess navigability potential.

Conclusions

Combining statewide discharge data and a GIS dataset 

with empirical techniques of hydraulic geometry, we 

developed a quantitative method for predicting the physical 

channel characteristics of any stream or river in the State of 

Washington. Using 264 discharge measurements at 137 U.S. 

Geological Survey streamflow-gaging stations distributed 

throughout the State, combined with the predicted mean 

annual discharge available in the NHDPlus dataset, allowed 

the prediction of hydraulic geometry with the following 

regression equations:

D Q

W Q

W Q

h

t

b

=

=

=

0 23

4 85

2 14

0 37

0 45

0 46

.

.

.

.

.

.

 ,

 ,

 ,

where Q is the mean annual discharge from the NHDPlus 

dataset (MAFLOWU). Bottom width was defined as the 

channel width in the cross section at the hydraulic depth. 

Because the value of Q from the NHDPlus dataset integrates 

precipitation, drainage area, and runoff, the regression 

equations above are applicable statewide, that is, to regions 

east and west of the Cascade Range.

Comparing the regression relations developed in this 

study with the navigability thresholds provided by DNR, 

rivers with a mean annual discharge of 1,660 cubic feet 

per second or greater tend to be “probably navigable” and 

rivers with a discharge of 360 cubic feet per second or 

less are “probably not navigable.” Variance in the dataset, 

however, leads to relatively wide prediction intervals in the 

regressions. For example, although the predicted hydraulic 

depth at 1,660 cubic feet per second is 3.5 feet, the 90-percent 

prediction intervals indicate that the actual hydraulic depth in 

any given river could range from 1.8 to 7.0 feet. 

Again, using Washington State Department of Natural 

Resources navigability thresholds, the predicted top width is 

40 feet for a discharge of 109 cubic feet per second, and the 

predicted top width is 24 feet for a discharge of 35 cubic feet 

per second; navigability based on only the channel top width is 

achieved with modest discharge. Similarly, the bottom-width 

data showed that the predicted bottom width is 18 feet for a 

discharge of 102 cubic feet per second. 

Of the three channel parameters analyzed in this study, 

hydraulic depth appeared to be the limiting parameter for 

defining navigability potential. Reach slope, as taken directly 

from the NHDPlus dataset, appeared to be a poor and 

inconsistent predictor of navigability potential.

There are a few caveats associated with the results of this 

study. First, the U.S. Geological Survey locates many of its 

streamflow-gaging stations just upstream of local hydraulic 

controls, which could result in predicted hydraulic depths 

greater than actual average stream depth. This bias would 

be most prevalent for smaller, mountainous rivers. Second, 

the NHDPlus dataset is known to contain some errors. No 

attempt was made in this study to correct these artifacts—

the NHDPlus data were used ‘as is’. Finally, anthropogenic 

impacts on rivers and streams that alter channel geometry 

were not explicitly analyzed for this study. Instead, all rivers, 

whether free flowing or highly modified, were analyzed 

together as one population. As a general rule, highly affected 

rivers would tend to be deeper and narrower than their freeflowing counterparts.

Acknowledgments

Michal Rechner and Tim Strickler from the Washington 

State Department of Natural Resources provided technical 

support for the study. Sonja Lin (USGS) collected and collated 

gaging-station data from field offices throughout the State of 

Washington with the help of several field-office personnel. 

Morgan Keys (USGS) processed and cleaned the GIS 

database. Tim Cohn (USGS) provided valuable expertise and 

insight into the statistical analysis of this study. Peter Griffiths 

and Justin Ferris (both USGS) provided valuable reviews of 

the study report.

References Cited

Castro, J.M., and Jackson, P.L., 2001, Bankfull discharge 

recurrence intervals and regional hydraulic geometry 

relationships: Patterns in the Pacific Northwest, USA: 

Journal of the American Water Resources Association, v. 37, 

no. 5, p. 1249-1262.

Chew, L.C., and Ashmore, P.E., 2001, Channel adjustment 

and a test of rational regime theory in a proglacial braided 

stream: Geomorphology, v. 37, no. 1-2, p. 43-63.

Chow, V.T., 1959, Open channel hydraulics: New York, 

McGraw Hill, 680 p.
16 Navigability Potential of Washington Rivers and Streams Determined with Hydraulic Geometry and a GIS

Ferguson, R.I., 1986, Hydraulics and hydraulic geometry: 

Progress in Physical Geography, v. 10, p. 1-31.

Helsel, D.R., and Hirsch, R.M., 1992, Statistical Methods in 

Water Resources: New York, Elsevier, 522 p.

Huang, H.Q., and Nanson, G.C., 2000, Hydraulic geometry 

and maximum flow efficiency as products of the principle of 

least action: Earth Surface Processes and Landforms, v. 25, 

no. 1, p. 1-16.

Leopold, L.B., and Maddock, T.J., 1953, The Hydraulic 

Geometry of Stream Channels and Some Physiographic 

Implications: U.S. Geological Survey Professional 

Paper 252, 57 p.

Montgomery, D.R., and Gran, K.B., 2001, Downstream 

variation in the width of bedrock channels: Water Resources 

Research, v. 37, no. 6, p. 1841-1846.

Rantz, S.E., and others, 1982, Measurement and computation 

of streamflow: Volume 1, Measurement of stage and 

discharge: U.S. Geological Survey Water-Supply 

Paper 2175, 284 p.

Research Triangle Institute, 2001, The National Water 

Pollution Control Assessment Model (NWPCAM) Version 

2 Draft Report: Prepared for the U.S. Environmental 

Protection Agency, Research Triangle Park, NC. 

U.S. Environmental Protection Agency, 2008, NHDPlus User 

Guide: http://www.horizon-systems.com/nhdplus, 111 p.

Washington State Department of Natural Resources, 2004, 

Navigability assessment of Washington lakes and rivers, 

provisional, Washington: State Department of Natural 

Resources Map, 1 plate.

Wohl, E., 2004, Limits of downstream hydraulic geometry: 

Geology, v. 32, no. 10, p. 897-900.
Appendix A 17

Gaging 

station No. Official name Replicate

Measurement 

date

(mm-dd-yy)

Measured 

discharge 

(ft3/s)

Hydraulic 

depth 

(ft)

Top 

width 

(ft)

Bottom 

width 

(ft)

MAFLOWU 

(ft3/s)

Slope 

(ft/ft)

12010000 Naselle River near Naselle A 04-23-01 403 3.34 70 29 272 0.0039

B 12-23-02 450 1.49 95 50 272 0.0039

C 01-25-05 412 1.67 85 39 272 0.0039

12013500 Willapa River near Willapa A 05-04-01 621 5.07 69 38 669 0.0001

B 01-17-07 606 5.09 82 49 669 0.0001

12024000 South Fork Newaukum River near Onalaska A 04-08-02 194 1.22 65 16 161 0.0055

B 02-23-06 217 1.51 65 32 161 0.0055

C 01-19-07 203 1.77 61 29 161 0.0055

12025700 Skookumchuck River near Vail A 04-21-06 191 1.72 61 17 148 0.0165

B 01-18-07 201 1.58 62 25 148 0.0165

12026150 Skookumchuck River below Bloody Run Creek, 

near Centralia

A 03-08-04 276 1.65 80 32 225 0.0019

B 02-22-06 248 2.22 74 30 225 0.0019

C 04-18-08 265 1.85 68 43 225 0.0019

12026400 Skookumchuck River near Bucoda A 03-08-04 360 2.28 75 24 380 0.0014

B 12-14-04 354 2.43 74 14 380 0.0014

C 02-01-05 359 2.15 74 29 380 0.0014

12027500 Chehalis River near Grand Mound A 02-28-06 2,920 10.36 247 151 3,280 0.0009

12031000 Chehalis River at Porter A 01-17-03 4,430 14.09 259 62 4,570 0.0000

12035000 Satsop River near Satsop A 04-07-08 1,990 5.35 177 76 1,970 0.0026

12035002 Chehalis River near Satsop A 03-21-06 6,330 8.49 290 186 7,750 0.0003

12035400 Wynoochee River near Grisdale A 05-17-02 484 2.88 113 60 306 0.0117

B 02-06-03 470 2.83 112 77 306 0.0117

12036000 Wynoochee River above Save Creek, near Aberdeen A 12-03-04 820 2.13 166 98 542 0.0036

12037400 Wynoochee River above Black Creek, near 

Montesano

A 05-18-01 1,150 3.07 132 67 1,140 0.0022

B 05-25-05 1,210 2.98 132 84 1,140 0.0022

12040500 Queets River near Clearwater A 06-11-08 4,140 4.36 372 197 4,700 0.0000

12041200 Hoh River at U.S. Highway 101, near Forks A 07-25-07 2,680 2.56 246 116 2,360 0.0019

B 01-17-08 2,730 2.71 243 58 2,360 0.0019

C 06-11-08 2,600 2.73 242 73 2,360 0.0019

12043000 Calawah River near Forks A 10-04-07 977 3.23 124 75 1,230 0.0035

12043300 Hoko River near Sekiu A 10-04-07 405 2.52 82 41 468 0.0035

12044900 Elwha River above Lake Mills, near Port Angeles A 06-01-05 1,280 2.47 154 36 845 0.0001

B 05-04-06 1,270 3.13 150 86 845 0.0001

C 06-27-07 1,500 2.62 150 66 845 0.0001

12045500 Elwha River at McDonald Bridge, near Port Angeles A 07-06-06 1,570 8.16 91 66 1,140 0.0035

B 12-19-07 1,360 8.68 90 45 1,140 0.0035

C 05-07-08 1,460 8.87 91 47 1,140 0.0035

12048000 Dungeness River near Sequim A 12-03-01 385 1.91 81 25 669 0.0098

B 07-22-02 403 1.66 90 60 669 0.0098

12054000 Duckabush River near Brinnon A 12-09-04 383 3.84 44 27 435 0.0186

B 05-11-05 453 1.83 77 34 435 0.0186

C 06-02-05 394 1.88 68 34 435 0.0186

12056500 North Fork Skokomish River below Staircase 

Rapids, near Hoodsport

A 04-08-05 547 1.64 139 72 505 0.0040

12058800 North Fork Skokomish River below Lower 

Cushman Dam, near Potlatch

A 10-01-07 57.6 1.39 37 18 834 0.0128

B 12-11-07 56.5 1.49 39 20 834 0.0128

Appendix A. Discharge Measurement Data Used in the Analysis.

[Measured discharge, hydraulic depth, top width, and bottom width were collected from U.S. Geological Survey streamflow-gaging stations in the State of 

Washington; MAFLOWU and Slope where collected for the given reach from the NHDPlus dataset. Abbreviations: ft3/s, cubic foot per second; ft, foot; 

MAFLOWU, mean annual discharge; ft/ft, foot per foot]
18 Navigability Potential of Washington Rivers and Streams Determined with Hydraulic Geometry and a GIS

Gaging 

station No. Official name Replicate

Measurement 

date

(mm-dd-yy)

Measured 

discharge 

(ft3/s)

Hydraulic 

depth 

(ft)

Top 

width 

(ft)

Bottom 

width 

(ft)

MAFLOWU 

(ft3/s)

Slope 

(ft/ft)

12059500 North Fork Skokomish River near Potlatch A 01-30-07 125 1.07 65 42 917 0.0021

B 04-12-07 119 0.98 70 33 917 0.0021

C 03-05-08 108 0.93 58 39 917 0.0021

12060500 South Fork Skokomish River near Union A 04-22-02 700 1.69 213 106 700 0.0076

B 02-14-06 677 1.78 170 65 700 0.0076

C 03-28-06 754 1.68 172 62 700 0.0076

12061500 Skokomish River near Potlatch A 03-28-06 1,170 2.69 175 93 1,900 0.0014

12069550 Big Beef Creek near Seabeck A 02-04-08 37.0 0.67 29 17 69.2 0.0106

12076800 Goldsborough Creek above 7th Street Bridge,

 at Shelton

A 04-16-07 158 1.52 43 16 283 0.0044

12079000 Deschutes River near Rainier A 10-22-03 244 2.39 67 42 398 0.0031

B 01-23-07 262 2.26 70 40 398 0.0031

C 04-15-08 267 2.24 71 38 398 0.0031

12080010 Deschutes River at E Street Bridge, at Tumwater A 04-01-02 411 2.54 86 57 681 0.0067

12082500 Nisqually River near National A 04-30-07 701 1.43 110 47 616 0.0109

12083000 Mineral Creek near Mineral A 06-04-02 337 1.36 95 40 333 0.0056

B 02-23-04 360 1.73 89 22 333 0.0056

C 02-27-06 395 2.24 95 55 333 0.0056

12086500 Nisqually River at La Grande A 02-07-07 1,310 3.88 153 54 1,287 0.0087

12087000 Mashel River near La Grande A 05-28-02 211 1.60 84 32 387 0.0094

B 03-08-06 230 1.63 82 49 387 0.0094

C 05-30-08 199 1.30 100 29 387 0.0094

12090500 Clover Creek near TiIllicum A 04-11-08 37.6 1.63 26 15 453 0.0042

12091500 Chambers Creek below Leach Creek, near 

Steilacoom

A 02-25-03 114 1.04 37 17 718 0.0059

B 05-01-03 107 1.06 38 12 718 0.0059

12092000 Puyallup River near Electron A 04-18-02 572 1.68 107 48 481 0.0137

B 06-10-02 503 1.62 107 23 481 0.0137

C 02-05-03 528 1.56 109 39 481 0.0137

12093500 Puyallup River near Orting A 01-20-04 701 2.55 77 55 895 0.0083

12094000 Carbon River near Fairfax A 03-09-07 414 1.85 64 12 373 0.0229

12095000 South Prairie Creek at South Prairie A 12-08-06 219 2.10 55 34 484 0.0046

12097500 Greenwater River at Greenwater A 05-19-03 203 1.49 51 24 351 0.0082

B 04-26-07 203 1.36 70 41 351 0.0082

12098500 White River near Buckley A 06-20-01 1,450 2.12 130 58 2,080 0.0162

B 05-06-03 1,440 1.89 132 54 2,080 0.0162

12099600 Boise Creek at Buckley A 12-01-06 35.2 0.90 25 15 86.5 0.0162

B 04-01-08 32.4 0.84 23 10 86.5 0.0162

12100496 White River near Auburn A 08-20-07 836 2.08 80 41 2,480 0.0042

12101500 Puyallup River at Puyallup A 06-28-04 3,080 4.77 214 98 4,900 0.0006

B 05-01-06 3,650 5.01 220 106 4,900 0.0006

C 06-15-07 3,350 4.60 221 109 4,900 0.0006

12102075 Clarks Creek at Tacoma Road, near Puyallup A 10-30-06 56.5 2.61 17 10 118 0.0022

B 04-25-08 58.1 3.48 19 11 118 0.0022

12105900 Green River below Howard A. Hanson Reservoir A 04-23-01 968 3.87 91 50 1,480 0.0112

B 12-05-06 991 3.73 93 53 1,480 0.0112

12106700 Green River at Purification Plant, near Palmer A 10-19-01 871 3.24 108 41 1,540 0.0072

B 04-30-03 862 3.28 110 73 1,540 0.0072

C 12-21-04 919 3.20 110 76 1,540 0.0072

12113000 Green River near Auburn A 02-11-04 1,450 4.43 115 70 2,640 0.0012

B 05-01-07 1,260 5.71 140 84 2,640 0.0012

C 04-08-08 1,290 5.57 139 90 2,640 0.0012

12115000 Cedar River near Cedar Falls A 11-29-01 231 1.85 85 41 318 0.0023

12116500 Cedar River at Cedar Falls A 01-28-02 317 1.75 91 49 636 0.0263

C 11-29-07 315 1.72 90 48 636 0.0263

12117500 Cedar River near Landsburg A 02-23-06 666 2.96 95 66 942 0.0046

B 02-14-07 622 2.85 94 63 942 0.0046

12117600 Cedar River below Diversion, near Landsburg A 02-24-06 551 3.00 88 61 945 0.0063

B 02-14-07 551 3.53 89 54 945 0.0063

Appendix A. Discharge Measurement Data Used in the Analysis.—Continued

[Measured discharge, hydraulic depth, top width, and bottom width were collected from U.S. Geological Survey streamflow-gaging stations in the State of 

Washington; MAFLOWU and Slope where collected for the given reach from the NHDPlus dataset. Abbreviations: ft3/s, cubic foot per second; ft, foot; 

MAFLOWU, mean annual discharge; ft/ft, foot per foot]
Appendix A 19

Gaging 

station No. Official name Replicate

Measurement 

date

(mm-dd-yy)

Measured 

discharge 

(ft3/s)

Hydraulic 

depth 

(ft)

Top 

width 

(ft)

Bottom 

width 

(ft)

MAFLOWU 

(ft3/s)

Slope 

(ft/ft)

12119000 Cedar River at Renton A 03-10-04 668 2.03 88 53 1,290 0.0020

B 02-24-06 687 2.18 89 64 1,290 0.0020

12121600 Issaquah Creek near mouth, near Issaquah A 02-06-08 132 1.33 35 24 385 0.0032

B 04-21-08 131 1.31 34 13 385 0.0032

C 06-09-08 133 1.35 34 19 385 0.0032

12137800 Sultan River below Diversion Dam, near Sultan A 05-24-05 203 1.73 51 22 545 0.0129

B 03-29-07 183 1.70 49 29 545 0.0129

C 05-02-07 182 1.69 51 31 545 0.0129

12138160 Sultan River below powerplant, near Sultan A 06-27-02 758 3.27 107 59 672 0.0092

B 06--06 683 3.18 109 68 672 0.0092

12141300 Middle Fork Snoqualmie River near Tanner A 06-19-06 1,310 4.59 125 69 1,130 0.0128

B 02-22-07 1,120 4.52 124 36 1,130 0.0128

C 10-01-07 1,160 4.60 121 34 1,130 0.0128

12142000 North Fork Snoqualmie River near Snoqualmie Falls A 10-11-07 530 4.04 80 39 468 0.0104

12143400 South Fork Snoqualmie River above Alice Creek, 

near Garcia

A 05-23-05 279 1.67 87 25 303 0.0024

B 04-12-06 319 1.74 87 28 303 0.0024

C 06-25-07 270 1.82 69 43 303 0.0024

12143600 South Fork Snoqualmie River at Edgewick A 04-12-06 432 1.69 125 63 454 0.0025

12144000 South Fork Snoqualmie River at North Bend A 04-13-06 558. 2.13 98 46 581 0.0026

B 06-19-06 552 2.17 95 47 581 0.0026

C 05-07-07 556 1.87 97 54 581 0.0026

12144500 Snoqualmie River near Snoqualmie A 04-16-08 2,530 8.50 212 140 2,700 0.0631

12147500 North Fork Tolt River near Carnation A 12-09-03 363 5.17 54 32 265 0.0386

B 03-01-06 328 5.54 56 34 265 0.0386

C 03-03-07 334 5.78 54 32 265 0.0386

12148500 Tolt River near Carnation A 05-05-03 552 3.27 77 44 564 0.0103

B 06-10-04 578 3.45 73 43 564 0.0103

C 03-02-06 516 2.65 95 50 564 0.0103

12150800 Snohomish River near Monroe A 06-28-06 10,000 7.53 489 175 10,900 0.0002

12155300 Pilchuck River near Snohomish A 04-24-01 462 2.01 78 47 864 0.0021

B 02-06-03 484 2.22 77 44 864 0.0021

C 11-30-05 470 2.05 77 51 864 0.0021

12167000 North Fork Stillaguamish River near Arlington A 04-12-06 1,890 5.67 130 71 1,860 0.0008

B 05-04-07 2,030 5.59 148 86 1,860 0.0008

12175500 Thunder Creek near Newhalem A 04-30-07 626 1.85 89 56 538 0.0143

12178000 Skagit River at Newhalem A 12-07-07 4,580 6.80 160 125 6,120 0.0085

12178100 Newhalem Creek near Newhalem A 04-27-06 171 1.60 44 20 147 0.0610

B 11-19-07 189 1.69 43 18 147 0.0610

12179900 Bacon Creek below Oakes Creek, near Marblemount A 11-19-07 388 1.53 94 36 268 0.0101

12181000 Skagit River at Marblemount A 12-07-05 5,660 3.95 296 144 7,210 0.0019

B 05-08-07 6,280 3.97 331 143 7,210 0.0019

C 10-03-07 6,220 3.86 335 149 7,210 0.0019

12200500 Skagit River near Mount Vernon A 01-04-06 17,500 9.88 600 257 17,900 0.0003

B 05-08-07 16,700 9.08 597 263 17,900 0.0003

C 02-12-08 17,500 9.67 587 180 17,900 0.0003

12201500 Samish River near Burlington A 04-17-08 234 1.87 57 21 422 0.0027

12201960 Brannian Creek at South Bay Drive, near 

Wickersham

A 06-09-08 10.3 0.50 14 9 2.12 0.1113

12202300 Olsen Creek near Bellingham A 01-02-08 10.5 0.59 13 8 22.6 0.0425

12205000 North Fork Nooksack River below Cascade Creek, 

near Glacier

A 07-22-04 827 2.24 83 34 661 0.0093

B 10-13-05 760 2.12 77 35 661 0.0093

C 07-31-06 734 3.07 63 38 661 0.0093

12206900 Racehorse Creek at North Fork Road, near Kendall A 10-13-05 54.3 0.97 46 18 66.8 0.0633

B 06-08-06 60.6 1.00 46 24 66.8 0.0633

C 02-07-07 61.6 1.08 46 21 66.8 0.0633

12207750 Warm Creek near Welcome A 03-31-04 28.9 0.97 16 9 27.4 0.1213

B 05-05-05 26.4 0.85 16 7 27.4 0.1213

C 06-22-06 27.4 0.86 17 3 27.4 0.1213

Appendix A. Discharge Measurement Data Used in the Analysis.—Continued

[Measured discharge, hydraulic depth, top width, and bottom width were collected from U.S. Geological Survey streamflow-gaging stations in the State of 

Washington; MAFLOWU and Slope where collected for the given reach from the NHDPlus dataset. Abbreviations: ft3/s, cubic foot per second; ft, foot; 

MAFLOWU, mean annual discharge; ft/ft, foot per foot]
20 Navigability Potential of Washington Rivers and Streams Determined with Hydraulic Geometry and a GIS

Gaging 

station No. Official name Replicate

Measurement 

date

(mm-dd-yy)

Measured 

discharge 

(ft3/s)

Hydraulic 

depth 

(ft)

Top 

width 

(ft)

Bottom 

width 

(ft)

MAFLOWU 

(ft3/s)

Slope 

(ft/ft)

12208000 Middle Fork Nooksack River near Deming A 06-21-01 524 2.39 81 54 428 0.0243

12209000 South Fork Nooksack River near Wickersham A 05-19-04 783 2.07 121 62 606 0.0009

12209490 Skookum Creek above Diversion, near Wickersham A 02-08-07 140 2.02 48 14 135 0.0595

B 05-16-07 140 1.68 48 25 135 0.0595

C 06-04-07 144 1.66 48 31 135 0.0595

12210900 Anderson Creek at Smith Road, near Goshen A 12-09-03 21.8 0.60 20 5 81.3 0.0095

B 06-06-06 20.3 0.74 18 8 81.3 0.0095

C 04-30-08 19.9 0.65 22 8 81.3 0.0095

12213100 Nooksack River at Ferndale A 04-17-06 3,500 6.37 214 76 4,500 0.0004

B 12-10-07 3,460 7.87 217 77 4,500 0.0004

C 02-13-08 3,990 6.98 218 77 4,500 0.0004

12396500 Pend Oreille River below Box Canyon, near Ione A 06-26-01 24,900 14.74 430 236 31,500 0.0132

B 10-04-04 26,600 14.04 423 236 31,500 0.0132

12397100 Outlet Creek near Metaline Falls A 11-30-05 79.5 0.97 41 28 66.5 0.0200

12399500 Columbia River at International boundary A 05-05-04 95,600 18.82 728 453 90,900 0.0267

B 09-28-05 94,500 18.78 724 445 90,900 0.0267

C 04-12-07 109,000 19.98 734 452 90,900 0.0267

12409000 Colville River at Kettle Falls A 02-27-03 302 1.69 51 29 337 0.0111

B 04-14-04 300 1.47 48 16 337 0.0111

C 12-05-07 326 2.34 58 29 337 0.0111

12419500 Spokane River above Liberty Bridge, near Otis 

Orchards

A 03-06-07 6,400 6.81 290 175 6,890 0.0019

12420500 Spokane River at Greenacres A 6-01-05 4,830 10.16 215 124 6,890 0.0019

12422500 Spokane River at Spokane A 03-06-07 6,820 13.18 287 161 6,960 0.0045

12424000 Hangman Creek at Spokane A 04-07-03 235 2.73 62 20 201 0.0043

12431000 Little Spokane River at Dartford A 06-18-08 307 3.30 48 32 166 0.0034

12431500 Little Spokane River near Dartford A 05-17-06 598 4.10 75 30 176 0.0010

B 03-02-07 607 4.03 75 35 176 0.0010

C 06-18-08 578 3.81 74 35 176 0.0010

12433542 Blue Creek above Midnite Mine drainage, near 

Wellpinit

A 06-01-06 1.22 0.31 5 3 4.19 0.0409

B 03-06-07 1.16 0.36 5 3 4.19 0.0409

12439500 Okanogan River at Oroville A 02-09-00 654 1.87 144 87 4,6700 0.0005

B 04-12-00 668 2.05 146 83 4,700 0.0005

C 01-05-05 711 2.06 154 38 4,700 0.0005

12445000 Okanogan River near Tonasket A 04-11-00 3,040 6.76 173 97 11,000 0.0009

12447200 Okanogan River at Malott A 06-02-05 3,210 7.72 211 140 11,600 0.0003

12447383 Methow River above Goat Creek, near Mazama A 07-10-03 461 1.20 160 80 576 0.0048

B 03-31-04 468 1.84 122 53 576 0.0048

12447390 Andrews Creek near Mazama A 07-13-06 28.6 1.38 17 9 29.9 0.0360

12448000 Chechuw River at Winthrop A 06-07-01 354 1.84 63 14 771 0.0080

B 07-14-06 373 1.51 76 25 771 0.0080

12448500 Methow River at Winthrop A 04-05-00 1,270 2.66 177 47 1,540 0.0028

B 04-07-04 1,170 2.21 174 60 1,540 0.0028

C 01-26-05 1,090 2.34 167 54 1,540 0.0028

12448998 Twisp River near Twisp A 06-22-05 245 1.15 71 25 335 0.0079

B 04-20-06 235 1.18 69 27 335 0.0079

C 07-14-06 251 1.16 72 15 335 0.0079

12449500 Methow River at Twisp A 06-14-05 1,440 2.94 138 66 1,940 0.0031

B 07-13-06 1,460 2.72 143 64 1,940 0.0031

12449950 Methow River near Pateros A 04-04-00 1,490 3.31 150 91 2,390 0.0065

B 03-31-04 1,530 3.44 149 99 2,390 0.0065

C 01-27-05 1,470 3.40 143 84 2,390 0.0065

12451000 Stehekin River at Stehekin A 04-19-07 1,510 5.30 146 55 1,310 0.0023

12452800 Entiat River near Ardenvoir A 06-21-05 369 2.97 61 32. 514 0.0019

12452890 Mad River at Ardenvoir A 03-30-06 85.3 0.84 40 18 233 0.0182

12456500 Chiwawa River near Plain A 04-06-00 537 2.16 75 26 674 0.0083

B 06-22-05 561 2.13 72 24 674 0.0083

Appendix A. Discharge Measurement Data Used in the Analysis.—Continued

[Measured discharge, hydraulic depth, top width, and bottom width were collected from U.S. Geological Survey streamflow-gaging stations in the State of 

Washington; MAFLOWU and Slope where collected for the given reach from the NHDPlus dataset. Abbreviations: ft3/s, cubic foot per second; ft, foot; 

MAFLOWU, mean annual discharge; ft/ft, foot per foot]
Appendix A 21

Gaging 

station No. Official name Replicate

Measurement 

date

(mm-dd-yy)

Measured 

discharge 

(ft3/s)

Hydraulic 

depth 

(ft)

Top 

width 

(ft)

Bottom 

width 

(ft)

MAFLOWU 

(ft3/s)

Slope 

(ft/ft)

12458000 Icicle Creek above Snow Creek, near Leavenworth A 04-15-00 638 3.60 82 42 776 0.0406

B 04-11-02 590 3.56 84 39 776 0.0406

12467000 Crab Creek near Moses Lake A 08-30-07 69.3 1.80 74 45 116 0.0014

B 10-02-07 61.5 1.74 74 44 116 0.0014

12472600 Crab Creek near Beverly A 04-08-07 203 1.82 65 32 579 0.0014

B 08-13-07 198 2.19 63 46 579 0.0014

12472800 Columbia River below Priest Rapids Dam A 03-15-07 97,000 24.55 1,140 813 129,000 0.0006

12484500 Yakima River at Umantum A 04-04-06 2,420 3.89 203 109 3,600 0.0019

B 06-20-07 2,460 3.87 202 106 3,600 0.0019

12502500 Ahtanum Creek at Union Gap A 04-20-07 82.6 1.97 25 13 238 0.0035

12508990 Yakima River at Mabton A 03-03-06 3,020 8.50 318 181 8,280 0.0002

B 06-28-06 3,200 8.11 306 169 8,280 0.0002

13334450 Asotin Creek below confluence, near Asotin A 12-11-07 48.3 0.80 26 11 35.9 0.0187

B 07-07-08 48.8 0.88 27 11 35.9 0.0187

13335050 Asotin Creek at Asotin A 02-14-08 87.7 1.35 26 18 76.6 0.0088

13344500 Tucannon River near Starbuck A 05-23-07 164 1.39 39 23 147 0.0069

13348000 South Fork Palouse River at Pullman A 04-03-07 38.9 1.42 21 15 30.5 0.0046

13351000 Palouse River at Hooper A 04-19-04 544 6.15 101 64 673 0.0030

14013000 Mill Creek near Walla Walla A 12-21-06 93.2 0.97 40 20 80.6 0.0161

B 04-12-07 97 0.97 39 14 80.6 0.0161

C 04-09-08 100 0.98 39 17 80.6 0.0161

14015000 Mill Creek at Walla Walla A 04-27-06 73.7 0.97 65 27 130 0.0129

B 12-21-06 81.6 1.00 66 49 130 0.0129

C 04-11-07 77.2 0.96 65 27 130 0.0129

14111400 Klickitat River below Summit Creek, near 

Glenwood

A 01-24-07 1,260 2.37 126 58 879 0.0058

14113000 Klickitat River near Pitt A 01-24-07 1,640 3.07 173 115 1,320 0.0050

14216500 Muddy River below Clear Creek, near Cougar A 02-01-05 848 3.12 81 34 674 0.0087

B 04-04-06 931 2.85 81 41 674 0.0087

C 04-25-07 788 2.64 81 38 674 0.0087

14219000 Canyon Creek near Amboy A 12-01-06 416 1.84 68 25 323 0.0204

B 02-22-08 432 2.06 68 40 323 0.0204

14219800 Speelyai Creek near Cougar A 04-12-06 91.2 1.23 37 16. 65.0 0.0189

B 11-30-06 100 1.10 43 26 65.0 0.0189

C 04-10-07 101 1.09 43 27 65.0 0.0189

14222500 East Fork Lewis River near Heisson A 05-18-00 676 3.62 98 33 623 0.0079

B 05-25-05 742 3.60 101 52 623 0.0079

C 04-13-06 664 3.59 102 73 623 0.0079

14226500 Cowlitz River at Packwood A 06-25-07 1,500 3.20 169 56 986 0.0036

14231900 Cispus River above Yellowjacket Creek, near 

Randle

A 12-04-01 984 3.47 111 56 821 0.0051

B 05-20-03 984 3.17 116 56 821 0.0051

14236200 Tilton River above Bear Canyon Creek, near 

Cinebar

A 02-23-04 805 2.49 106 50 585 0.0049

14240525 North Fork Toutle River below sediment retention 

structure near Kid Valley

A 11-05-06 731 1.96 114 5 609 0.0061

14241500 South Fork Toutle River at Toutle A 03-28-06 610 2.07 135 45 492 0.0036

B 12-04-06 570 1.42 132 44 492 0.0036

14242580 Toutle River at Tower Road, near Silver Lake A 03-06-06 2,040 3.91 159 59 2,070 0.0029

B 05-25-06 1,910 3.63 157 57 2,070 0.0029

C 12-04-06 2,040 3.45 159 57 2,070 0.0029

14243000 Cowlitz River at Castle Rock A 02-01-07 9,470 8.60 307 150 8,555 0.0009

B 03-07-08 8,810 8.44 307 133 8,555 0.0009

Appendix A. Discharge Measurement Data Used in the Analysis.—Continued

[Measured discharge, hydraulic depth, top width, and bottom width were collected from U.S. Geological Survey streamflow-gaging stations in the State of 

Washington; MAFLOWU and Slope where collected for the given reach from the NHDPlus dataset. Abbreviations: ft3/s, cubic foot per second; ft, foot; 

MAFLOWU, mean annual discharge; ft/ft, foot per foot]
22 Navigability Potential of Washington Rivers and Streams Determined with Hydraulic Geometry and a GIS

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For more information concerning the research in this report, contact the 

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2 Report Title

Magirl and Olsen— Navigability Potential of Washington Rivers and Streams Determined with Hydraulic Geometry and a GIS —Scientific Investigations Report 2009–5122