N inputs Atmospheric N2

DON

 NH4

+

N03

-

DON

 NH4

+

N03

-

Import from

upstream

Groundwater dissolved organic nitrogen, nitrate, ammonium 

N2

NO2-

N2

 NH4+

NO3

-

NO2

-

 NH4

+

NO3

-

Export to

downstream

Dead

organic

matter and

microbes

Benthic

algae and

microbes

Cyanobacteria

Mineralization

Assimilation

Assimilation

Assimilation

N fixation

Excretion

Sediment subsurface

Denitrification

Nitrification

Stream water

U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2015–5074

Version 1.1, February 2016

Prepared in cooperation with the Washington State Department of Ecology

Nutrient Attenuation in Rivers and Streams, 

Puget Sound Basin, Washington

Nutrient Attenuation in Rivers and Streams, 

Puget Sound Basin, Washington

By Rich W. Sheibley, Christopher P. Konrad, and Robert W. Black

Prepared in cooperation with the Washington State Department of Ecology

Scientific Investigations Report 2015–5074

Version 1.1, February 2016

U.S. Department of the Interior

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

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia

First release: 2015

Revised: February 2016 (ver. 1.1)

For more information on the USGS—the Federal source for science about the Earth, its natural and living 

resources, natural hazards, and the environment—visit http://www.usgs.gov or call 1–888–ASK–USGS.

For an overview of USGS information products, including maps, imagery, and publications, 

visit http://www.usgs.gov/pubprod/.

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials 

as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:

Sheibley, R.W., Konrad, C.P., and Black, R.W., 2015, Nutrient attenuation in rivers and streams, Puget Sound Basin, 

Washington (ver. 1.1, February 2016): U.S. Geological Survey Scientific Investigations Report 2015–5074, 67 p., http://

dx.doi.org/10.3133/sir20155074.

ISSN 2328-0328 (online)
iii

Contents

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

Introduction.....................................................................................................................................................2

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

Study Area.......................................................................................................................................................2

Nutrient Cycling in Streams and Rivers .....................................................................................................4

Sources and Cycles of Nitrogen ........................................................................................................4

Sources and Cycles of Phosphorus...................................................................................................7

Factors Related to Nutrient Attenuation in Streams and Rivers............................................................8

Physical Factors....................................................................................................................................8

Chemical Factors ................................................................................................................................10

Biological Factors...............................................................................................................................10

Watershed Related Factors ..............................................................................................................10

Methods for Evaluating Nutrient Attenuation in Rivers and Streams.................................................11

Field-Based Methods of Instream Nutrient Attenuation..............................................................11

Watershed-Scale Models of Instream Nutrient Attenuation......................................................14

Analysis of Relative Nutrient Attenuation in Puget Sound Basin .......................................................14

Watershed Scale Attenuation of Rivers and Streams in Puget Sound Basin ..........................14

 RivR-N Attenuation Model ......................................................................................................18

vf Attenuation Model .................................................................................................................22

Comparison of Relative Nitrate Attenuation Models...........................................................29

Development of a Framework for Ranking Stream Reach Attenuation.....................................29

Temporal Effects of Nutrient Attenuation.......................................................................................33

Future Work ..................................................................................................................................................46

Management of Instream Nutrient Attenuation .....................................................................................47

Summary and Conclusions.........................................................................................................................48

References Cited..........................................................................................................................................49

Appendix A. Relationship Between Mean Annual Discharge and Drainage Area for 

Puget Sound Rivers and Streams................................................................................................57

Appendix B. Maps Showing Individual Scores for the Four Primary Factors Related to Nitrate 

and Orthophosphate Attenuation in Rivers and Streams in the Puget Sound Basin..........61
iv

Figures

1. Map showing study location and associated hydrologic network, Puget Sound

Basin, Washington........................................................................................................................3

2. Map showing simplified land cover, Puget Sound Basin, Washington, 2006.....................5

3. Diagram showing example of the nitrogen (N) cycle in streams and rivers ......................6

4. Diagram showing example of the phosphorus (P) cycle in streams ...................................8

5. Graph showing example of how to determine the uptake length (Sw) for a stream

reach from a short-term nutrient addition experiment.........................................................13

6. Graph showing mean annual discharge and drainage area for 147 U.S. Geological

Survey streamgages with at least 5 years of record, western Washington, 1981–2010 19

7. Map showing relative instream nitrogen attenuation expressed in percentage of

nitrate inputs removed per kilometer of stream length using the RivR-N model for

Puget Sound Basin, Washington .............................................................................................20

8. Boxplot and histogram of relative instream attenuation calculated using the

RivR-N model expressed as the percentage of nitrate removed per kilometer of

stream length, Puget Sound Basin, Washington...................................................................21

9. Graphs showing relation between total and dissolved nutrient concentrations for

total nitrogen and nitrate and total phosphorus and orthophosphate for data

compiled from the U.S. Geological Survey National Water Information System,

Puget Sound Basin, Washington..............................................................................................24

10. Map showing relative instream attenuation expressed as the percentage of

nitrate inputs removed per kilometer of stream length based on the vf model,

Puget Sound Basin, Washington..............................................................................................25

11. Boxplot and histogram showing relative instream attenuation based on the

fraction of nitrate removed per kilometer of stream length using the vf model,

Puget Sound Basin, Washington..............................................................................................26

12. Map showing relative orthophosphate attenuation represented by the

percentage of orthophosphate inputs removed per kilometer of stream length

based on the vf model, Puget Sound Basin, Washington ....................................................27

13. Boxplot and histogram showing calculated relative instream attenuation based

on the fraction of orthophosphate removed per kilometer of stream length using

the vf model, Puget Sound Basin, Washington......................................................................28

14. Map showing differences of relative nitrate attenuation of reaches in the

hydrologic network between the vf and RivR-N models for nitrate, Puget Sound

Basin, Washington......................................................................................................................30

15. Map showing total nitrate attenuation scores in streams and rivers, Puget Sound

Basin, Washington......................................................................................................................32

16. Map showing total orthophosphate attenuation scores in streams and rivers,

Puget Sound Basin, Washington..............................................................................................34

17. Boxplots showing relation between relative nutrient attenuation and reach

scores for the RivR-N model, vf nitrogen model, and vf orthophosphate model,

Puget Sound Basin, Washington..............................................................................................35
v

Figures

18. Graphs showing relation between relative nitrate attenuation and nitrate

concentration for representative high- and low-flow conditions at North Fork

Skokomish River, Thornton Creek, and Nooksack River at Ferndale, Washington .........38

19. Graphs showing relation between relative orthophosphate attenuation and

orthophosphate concentration for representative high- and low-flow conditions

at North Fork Skokomish, Thornton Creek, and Nooksack River at Ferndale,

Washington..................................................................................................................................39

20. Graphs showing relative nitrate attenuation and nitrate concentration for the

range in nutrient concentrations for typical low- and high-flow conditions, North

Fork Skokomish River, Thornton Creek, and Nooksack River near Ferndale,

Washington..................................................................................................................................40

21. Graphs showing relative orthophosphate attenuation and orthophosphate

concentration for the range in nutrient concentrations for typical low- and

high-flow conditions, North Fork Skokomish River, Thornton Creek, and Nooksack

River near Ferndale, Washington.............................................................................................41

22. Graphs showing monthly variation of relative nitrate attenuation using the vf

model given by equation 6 for the North Fork Skokomish River, Thornton Creek,

and Nooksack River at Ferndale, Washington ......................................................................44

23. Graphs showing monthly variation of relative orthophosphate attenuation using

the vf model given by equation 6 for the North Fork Skokomish River, Thornton

Creek, and Nooksack River at Ferndale, Washington..........................................................45

Tables

1. Summary of physical, chemical, biological, and watershed factors associated

with nutrient attenuation in streams and rivers ....................................................................12

2. Summary of modeling approaches to describe instream nutrient attenuation for

watershed-scale models from review of scientific literature.............................................15

3. Summary statistics of modeled concentrations, vf values, and reach-level relative

attenuation from the RivR-N model and vf models expressed as a percentage

of nutrient input attenuated per kilometer of stream length, Puget Sound Basin,

Washington..................................................................................................................................21

4. Primary factors related to nutrient attenuation and criteria corresponding to a

score of 1 for a given river segment........................................................................................31

5. Nutrient data for three study sites compared to nutrient data for Puget Sound

Basin, Washington......................................................................................................................37

6. Representative high- and low-flow conditions at the three case study sites to

estimate nutrient attenuation, Puget Sound Basin, Washington .......................................37

7. Discharge and stream width measures by month for the North Fork Skokomish

River, Thornton Creek, and Nooksack River, Washington. .................................................42

8. Nitrate and orthophosphorus data by month for the North Fork Skokomish River,

Thornton Creek, and Nooksack River at Ferndale, Washington. .......................................43
vi

Conversion Factors

Inch/Pound to International System of Units

Multiply By To obtain

Length

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

square foot (ft2) 0.09290 square meter (m2)

square mile (mi2) 2.590 square kilometer (km2) 

Volume

gallon (gal) 3.785 liter (L) 

gallon (gal) 0.003785 cubic meter (m3) 

cubic foot (ft3) 0.02832 cubic meter (m3) 

Flow rate

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

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

International System of Units to Inch/Pound

Multiply By To obtain

Length

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

Area

square meter (m2) 10.76 square foot (ft2) 

square kilometer (km2) 0.3861 square mile (mi2)

Volume

cubic meter (m3) 264.2 gallon (gal) 

liter (L) 61.02 cubic inch (in3) 

cubic meter (m3) 35.31 cubic foot (ft3)

Flow rate

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

cubic meter per second per meter 

[(m3/s)/m]

35.31 cubic foot per second per meter 

[(ft3/s)/m]

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

millimeter per minute (mm/min) 0.03937 inch per minute (in/min) 

Mass

kilogram (kg) 2.205 pound avoirdupois (lb)

Density

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

meter squared per year (m2/yr) 10.76 foot squared per yr (ft2/yr) 

Hydraulic gradient

meter per kilometer (m/km) 5.27983 foot per mile (ft/mi) 
vii

Datums

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

(NAVD 88).

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

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

Supplemental Information

Concentrations of chemical constituents in water are given in either milligrams per liter (mg/L) 

or micrograms per liter (μg/L)

Abbreviations

DIN dissolved inorganic nitrogen

DOC dissolved organic carbon

DON dissolved organic nitrogen

D/T displacement ratio

FBOM fine benthic organic matter

HL hydraulic load

N nitrogen

N2 nitrogen gas

NH4

+ ammonium

NHD National Hydrography Dataset

NO2

− nitrite

NO3

−

nitrate

NWIS National Water Information System

P phosphorus

PAH polycyclic aromatic hydrocarbon

PNW Pacific Northwest

PO 4

−3 orthophosphate

Q/w specific discharge

Sw uptake length

TN total nitrogen

TP total phosphorus

U uptake rate

USGS U.S. Geological Survey

vf uptake velocity

w:d width to depth ratio

Nutrient Attenuation in Rivers and Streams, 

Puget Sound Basin, Washington

By Rich W. Sheibley, Christopher P. Konrad, and Robert W. Black 

Abstract

Nutrients such as nitrogen and phosphorus are important 

for aquatic ecosystem health. Excessive amounts of nutrients, 

however, can make aquatic ecosystems harmful for biota 

because enhanced growth and decay cycles of aquatic algae can 

reduce dissolved oxygen in the water. In Puget Sound marine 

waters, low dissolved oxygen concentrations are observed in 

a number of marine nearshore areas, and nutrients have been 

identified as a major stressor to the local ecosystem. Delivery 

of nutrients from major rivers in the Puget Sound Basin to the 

marine environment can be large. Therefore, it is important 

to identify factors related to how nutrients are retained 

(attenuated) within streams and rivers in the Puget Sound 

Basin. Physical, chemical, and biological factors related to 

nutrient attenuation were identified through a review of related 

scientific literature. 

Numerous empirical modeling approaches for estimating 

nutrient attenuation in streams and rivers also were compiled, 

and a subset of these models was applied to the Puget 

Sound Basin. In particular, models based on the physical 

characteristics of a river reach (RivR-N model) and on the 

physical and biological features of a river reach (vf model) 

were used and compared for the 17 major rivers draining to 

the Puget Sound. Data on the relative amount of instream 

attenuation (the fraction of nutrient input removed per 

kilometer of stream reach) showed some common and general 

themes. Firstly, headwater reaches throughout the Puget Sound 

Basin tend to be better than the main stems of the major rivers 

at attenuating nitrate (NO3

−) and orthophosphorus (ortho-P). 

Secondly, rivers are more efficient at attenuating NO3

− than 

ortho-P, probably because of the close relation between 

phosphorus and suspended sediment, which was not captured 

fully in the models. Thirdly, when comparing the RivR-N and 

vf models for NO3

−, physical characteristics of the channel may 

be more effective predictors of relative NO3

− attenuation for 

main stem reaches, whereas biological factors may be more 

effective predictors in headwater reaches. These results are 

explained in terms of four primary factors of attenuation: 

sinuosity, channel slope, specific discharge, and uptake velocity 

(vf) of the reach. 

A simple scoring procedure based on these four factors 

showed that reaches where attenuation scores were high had 

higher relative attenuation of nutrients from the RivR-N and 

vf models. This attenuation “scorecard” can be used to quickly 

assess the potential for a given reach to attenuate nutrients. 

Seasonal relative attenuation at three case studies was greater 

in summer months (July through September) and much lower 

and almost constant from January through June. An analysis of 

relative attenuation across a range of nutrient concentrations 

showed that, at some point, relative instream attenuation 

is minimized. For NO3

−, relative attenuation reached a 

minimum value greater than 3 milligrams of nitrogen per liter 

(mg N/L) during low flow and 1 mg N/L during high flow. For 

orthophosphate, minimum relative attenuation was observed 

at about 0.1 milligram of phosphorus per liter (mg P/L) for 

both low- and high-flow conditions. Generally, the temporal 

dynamics of nutrient attenuation are dependent on the 

travel time through a given reach, the proportion of flow 

in contact with the sediment, and the amount of biological 

activity. Improved understanding of nutrient attenuation in 

Puget Sound Basin will benefit from the compilation of more 

detailed data for specific discharge, channel slope, and channel 

sinuosity in Puget Sound streams and rivers. Additionally, field 

studies examining upstream-downstream changes in nutrient 

load and field-based measurements of vf are needed. 

From a management perspective, preservation and 

improvement of instream nutrient attenuation should focus 

on increasing the travel time through a reach and contact time 

of water sediment (reactive) surfaces and lowering nutrient 

concentrations (and loads) to avoid saturation of instream 

attenuation and increase attenuation efficiency. These goals 

can be reached by maintaining and restoring channel-flood 

plain connectivity, maintaining and restoring healthy riparian 

zones along streams, managing point and nonpoint nutrient 

loads to streams and rivers, and restoring channel features 

that promote attenuation such as the addition of woody debris 

and maintaining pool-riffle morphologies. Many of these 

management approaches are already being undertaken during 

projects aimed to restore quality salmon habitat. Therefore, 

there is a dual benefit to these projects that also may lead to 

enhanced potential for nitrogen and phosphorus attenuation.
2 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

Introduction

Nutrients such as nitrogen (N) and phosphorus (P) are 

key components for all living things because they are the 

building blocks of proteins, enzymes, amino acids, and other 

organic compounds. In aquatic systems, certain amounts of 

nutrients are needed to sustain healthy ecosystems; however, 

excessive amounts of nutrients in these systems can cause the 

degradation of streams, rivers, lakes, and estuaries (Dubrovsky 

and others, 2010; Roberts and others, 2014). Nutrients, 

particularly N, have been identified as major stressors to 

the Puget Sound ecosystem. In marine waters, excess N can 

cause algal blooms that eventually die off and, through the 

decomposition process, drive dissolved oxygen to levels 

too low to support aquatic life. In fresh waters, N and (or) 

P can increase plant and algal biomass, which can also lead 

to low levels of dissolved oxygen. These coupled processes 

(increased biomass production and subsequent decay and 

oxygen depletion), called eutrophication, are a widespread 

environmental problem that is observed in many parts of 

the world. Low dissolved-oxygen concentrations have been 

observed in numerous locations in Puget Sound (Roberts and 

others, 2014), and riverine inputs of N to Puget Sound marine 

waters can be significant (Mohamedali and others, 2011), 

especially in south and central Puget Sound. Therefore, it is 

important to understand factors related to stream and river 

nutrient attenuation so that managers can preserve features 

of streams and rivers that will help reduce nutrient loads to 

marine waters of Puget Sound. Nutrient attenuation, also 

referred to as nutrient retention, is a generic term that refers 

to the loss of nutrient load from the stream or river as it moves 

downstream. This loss can be temporary, as when nutrients 

cycling within a stream reach and are taken up and released 

multiple times as they move downstream, or the loss of 

nutrient can be permanent. Throughout this report, the terms 

attenuation and retention are used interchangeably. 

It has been long recognized that rivers and streams are 

not just pipes that move solutes downstream to recipient 

water bodies (Bencala, 1983). Instead, rivers and streams 

transform and attenuate nutrient loads through a combination 

of physical and biological processes as they move downstream. 

Point source management of nutrients can be expensive, and 

nonpoint source management can be challenging given the 

distributed nature of the sources. Understanding what factors 

contribute to high or low attenuation and where attenuation 

is likely to occur can provide an additional nonpoint source 

management tool. Nonpoint source management could 

broaden from reducing sources to enhancing and preserving 

factors associated with attenuation in the watershed, flood 

plain, and river network. This is important because reducing 

nonpoint sources may not result in lower levels of nutrients in 

river networks if attenuation characteristics are lost.

Purpose and Scope

The purpose of this report is to identify what factors are 

responsible for attenuating nutrients in freshwater systems 

and where these processes are expected to occur in order to 

better understand and manage for the delivery of nutrients 

from Puget Sound watersheds to nearshore marine ecosystems. 

Recent analyses of ambient monitoring data for rivers draining 

into Puget Sound (Mohamedali and others, 2011) suggest that 

summer N loads generated in Puget Sound watersheds are 

significantly attenuated before reaching Puget Sound. If so, 

then watershed and instream processes have a major mitigating 

effect that has not been quantified at the Puget Sound scale to 

date. Additionally, most pollution-reduction approaches do 

not account for instream attenuation when establishing load 

reduction targets. A review of the available scientific literature 

identified important factors related to nutrient attenuation 

in rivers and streams, and modeling approaches that can be 

used to estimate attenuation in river reaches and watershed 

river networks. The literature review presented in this report is 

meant to be an overview of the state of the science relevant to 

Puget Sound systems; however, it is not intended to serve as a 

detailed review for each factor related to nutrient attenuation. 

Nutrient attenuation in rivers and streams is complex and is 

controlled by numerous factors, some of which are fields of 

science on their own. From the literature review, attenuation 

models were used to identify areas of Puget Sound where 

high and low nutrient attenuation would be expected across 

different spatiotemporal scales. The focus of this report is on 

instream nutrient attenuation and not watershed (terrestrial) 

attenuation of nutrients, though it is well known that both 

terrestrial and instream attenuation are important for reducing 

total nutrient inputs to a watershed. This report was done in 

cooperation with the Washington State Department of Ecology 

(Ecology) and supports the Toxics and Nutrients Reduction 

Strategy developed by Ecology (Washington State Department 

of Ecology, 2013a) to implement a National Estuary Program 

grant for Puget Sound toxics and nutrients.

Study Area

The Puget Sound Basin encompasses the 13,700-mi2

area that drains to Puget Sound and adjacent marine waters. 

Included in the basin are all or part of 13 western Washington 

counties, as well as the headwaters of the Skagit River and 

part of the Nooksack River in British Columbia, Canada. 

Streams and rivers drain three physiographic provinces—the 

Olympic Mountains in the west, the Cascade Range in the 

east, and the Puget Lowlands in the center of the basin (fig. 1). 
Study Area 3

San 

Juan

Islands

Strait of Juan de Fuca

Puget Sound

BRITISH COLUMBIA, CANADA

OLYMPIC

MOUNTAINS CASCADE RANGE

Admiralty

Inlet

Cape

Flattery

PACIFIC

OCEAN

Skagit R

Green R

Puyallup R

Cedar R

Deschutes R

Nisqually R

Duckabush R

Samish R

Dungeness R

Elwha R

Hamma

Hamma R

Nooksack R

Dosewalips R

Snohomish R

Stillaguamish R

Duwamish R

Skokomish R

Big

Quilcene R

Commencement

Bay

Elliott

Bay

124° 123° 122° 121°

49°

48°

47°

0 10 20 30 40 50 MILES

0 10 20 30 40 50 KILOMETERS

Base from U.S. Geological Survey digital data, 1:100,000

Transverse Mercator projection: NAD 1983 UTM Zone 10N

WASHINGTON STATE

tac15-0989_fig01

WASHINGTON STATE

Figure

Location

EXPLANATION

Puget Sound Basin

YAKIMA

KING

LEWIS

CHELAN

CLALLAM

SKAGIT

KITTITAS

PIERCE

WHATCOM

JEFFERSON

SNOHOMISH

SKAMANIA

PACIFIC

MASON

COWLITZ

GRAYS HARBOR

KITSAP

THURSTON

ISLAND

SAN JUAN

WAHKIAKUM

OKANOGAN

Figure 1. Study location and associated hydrologic network, Puget Sound Basin, Washington.
4 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

Nearly 4 million people, about 70 percent of Washington State’s 

population, live in the Puget Sound Basin. Urban growth 

is rapid; by 2020, the population is expected to increase by 

1.1 million people, with most growth in urban and suburban 

areas. Urban and agricultural lands, which cover about 9 and 

6 percent of the basin, respectively, are concentrated in the 

lowlands. Forestry dominates land use in the basin and is 

concentrated in the foothills and mountains (fig. 2).

Forestry, agriculture, and urban development have 

affected the quality of freshwater in the Puget Sound Basin. 

The quality of groundwater in the upper watersheds probably 

differs little from natural conditions (Ebbert and others, 

2000) but, because of development, many streams in the 

Puget Lowlands have undergone changes in structure and 

function, with a trend toward simplification of stream channels 

(channelization, disconnection from flood plains) and loss of 

aquatic plants and organism habitat (Black and Silkey, 1998; 

Collins and Montgomery, 2002; Collins and others, 2002; 

Collins and others, 2012).

Heavy industry generally is located on the shores 

of the urban bays and along the lower reaches of their 

influent tributaries, such as Commencement Bay and the 

Puyallup River in Tacoma and Elliott Bay and the Duwamish 

Waterway in Seattle. High density commercial and residential 

development occurs primarily within and adjacent to the 

major cities. This trend has resulted in increasing urban sprawl 

in the central Puget Sound Basin, and urban land-use activities 

have had a significant effect on the quality of streams in the 

Puget Sound Basin (May and others, 1997; Staubitz and others, 

1997; Morley and Karr, 2002; McBride and Booth, 2005; 

Herrera Environmental Consultants, Inc., 2011). Water-quality 

concerns related to urbanization include providing adequate 

sewage treatment and disposal, transporting contaminants 

to streams by storm runoff, and preserving stream corridors. 

It is not uncommon, particularly during high flow events, 

for measurable concentrations of herbicides, pesticides, 

fungicides, industrial chemicals, metals, polycyclic aromatic 

hydrocarbon (PAHs), and (or) elevated nutrients to be in the 

highly urbanized Puget Sound lowland rivers and streams 

(Ebbert and others, 2000; Herrera Environmental Consultants, 

Inc., 2011; Conn and Black, 2014).

More than half of the agricultural acreage in the basin 

is located in Whatcom, Skagit, and Snohomish Counties. 

Agricultural land use consists of about 60 percent cropland 

and 40 percent pasture. Livestock produce a large amount of 

manure that is applied as fertilizer to cropland, sometimes in 

excess amounts, resulting in the runoff of N and P to surface 

water and the leaching of nitrate to groundwater. Runoff 

from agricultural areas also carries sediment, pesticides, and 

bacteria to streams (Staubitz and others, 1997; Ebbert and 

others, 2000).

Sources of contaminants to Puget Sound lowland streams 

and the lower reaches of large rivers are largely nonpoint 

because most major point sources discharge directly to 

Puget Sound (Ebbert and others, 2000). The concentration 

of anthropogenic chemicals in the water of the lower reaches 

of large Puget Sound rivers are often lower than that in small 

streams originating in the Puget Lowlands because much of 

the flow is derived from the forested and alpine headwaters. 

However, during high flows events, particularly during late 

summer and early autumn, concentrations of nutrients and 

other anthropogenically generated chemicals can increase 

(Ebbert and others, 2000; Conn and Black, 2014).

Nutrient Cycling in Streams and Rivers

During transport downstream, N and P undergo complex 

cycles, which can be thought of as nutrient spirals that are 

constantly transforming nutrients as water moves from the 

headwaters to receiving water bodies. To understand the factors 

that lead to nutrient attenuation in streams and rivers, it is 

important to first understand the sources and cycles of N and P 

that take place in fluvial systems.

Sources and Cycles of Nitrogen

In freshwater systems, N occurs in many forms, 

including dissolved and particulate fractions. Dissolved 

inorganic nitrogen (DIN) is made up of nitrate (NO3

−), 

ammonium (NH4

+ ), and nitrite (NO2

− ); dissolved organic 

nitrogen (DON) is made up of complex organic compounds 

such as amino acids; and particulate N occurs in organic form 

as microbes and detritus (leaf litter and other decaying organic 

matter). It is the dissolved inorganic forms (NO3

− and NH4

+

) 

that contribute the most to water quality problems related to 

eutrophication and hypoxia (Rabalais and others, 1996) because 

aquatic plants, algae, fungi, and bacteria assimilate, or take up, 

N primarily as NH4

+ and NO3

− (Duff and Triska, 2000). 

Sources of N to streams include atmospheric deposition, 

N fixation, and terrestrial inputs carried from runoff and 

groundwater flow to the stream, and are comprised of natural 

and anthropogenic sources. As a result, the amount and form 

of N source to a stream is highly dependent on local land use 

(Allan and Castillo, 2007; Dubrovsky and others, 2010) as the 

contribution of natural and anthropogenic sources also 

varies across land use. Atmospheric deposition consists of 

precipitation (wet deposition) and dry fallout (dry deposition) 

and is mainly in the form of NH4

+ and NO3

−. Nitrogen fixation 

is the conversion of relatively inert nitrogen gas (N2) into more 

biologically available forms and is mainly a natural biological 

(bacterial fixation through cyanobacteria) and chemical (the 

high energy from lightning strikes can result in fixation) 

process. However, with the increase in synthetic fertilizer 

production, the burning of fossil fuels, and the cultivation of 

N-fixing crops such as soybeans, anthropogenic N-fixation now 

greatly exceeds natural fixation (Vitousek and others, 1997). 
Nutrient Cycling in Streams and Rivers 5

San 

Juan

Islands

Strait of Juan de Fuca

Puget Sound

BRITISH COLUMBIA, CANADA

OLYMPIC

MOUNTAINS CASCADE RANGE

WASHINGTON STATE

Admiralty

Inlet

Cape

Flattery

PACIFIC

OCEAN

Skagit R

Green R

Puyallup R

Cedar R

Deschutes R

Nisqually R

Duckabush R

Samish R

Dungeness R

Elwha R

Hamma

Hamma R

Nooksack R

Dosewalips R

Snohomish R

Stillaguamish R

Duwamish R

Skokomish R

Big

Quilcene R

124° 123° 122° 121°

49°

48°

47°

0 10 20 30 40 50 MILES

0 10 20 30 40 50 KILOMETERS

Base from U.S. Geological Survey digital data, 1:100,000

Transverse Mercator projection: NAD 1983 UTM Zone 10N

tac15-0989_fig02

EXPLANATION

Simplified 2006 

National Land Cover

Urban

Forest

Agriculture

Other

YAKIMA

KING

LEWIS

CHELAN

CLALLAM

SKAGIT

KITTITAS

PIERCE

WHATCOM

JEFFERSON

SNOHOMISH

SKAMANIA

PACIFIC

MASON

COWLITZ

GRAYS HARBOR

KITSAP

THURSTON

ISLAND

SAN JUAN

WAHKIAKUM

OKANOGAN

Figure 2. Simplified land cover, Puget Sound Basin, Washington, 2006. From Fry and others (2011).
6 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

Terrestrial inputs can be in dissolved forms from runoff and 

groundwater pathways and in particulate forms such as litter 

fall (Roberts and Bilby, 2009). Direct inputs to the stream 

of N from precipitation and through fall (water that drips 

from vegetation) are less important (Duff and Triska, 2000) 

in most cases but can be significant at the beginning of a rain 

event (Allan and Castillo, 2007). Atmospheric deposition to 

the watershed, however, can be a large source of N that can 

make its way into streams through groundwater flow (Shibata 

and others, 2001). Generally, because the main reservoir of 

N in the environment is the atmosphere, rock weathering as 

a source of N is assumed negligible, although in some cases 

it can be important (Holloway and others, 1998). The main 

anthropogenic inputs of N to streams include agricultural 

and urban fertilizers in runoff, atmospheric deposition from 

industrial fertilizer production and fossil fuel burning, and 

wastewater from direct (treatment plants) and indirect (septic 

systems) sources. In Puget Sound, sources of N to streams 

are primarily from point sources, livestock manure, runoff 

from forest and developed land uses, and N-fixing alder trees 

(Bechtold and others, 2003; Brett and others, 2005a; Herrera 

Environmental Consultants, Inc., 2011; Steinberg and others, 

2011; Wise and Johnson, 2011).

The N cycle in streams and rivers is complex, with most 

reactions being microbially mediated (fig. 3). Generally, 

reactions are either used to obtain N for structural synthesis 

(assimilatory uptake) or for energy in microbial reactions 

(dissimilatory uptake). Atmospheric N2, the most abundant 

form of N globally, is soluble in water and therefore 

can exchange to and from the water column in streams. 

In streams and rivers, dissolved N2 can be converted into 

oxidized forms (NH4

+ and NO3

−) by N-fixing bacteria 

(cyanobacteria), through N fixation (fig. 3), and incorporated 

into cells. The oxidized N not used by the N-fixers is released 

N inputs Atmospheric N2

DON

 NH4

+

N03

-

DON

 NH4

+

N03

-

Import from

upstream

Groundwater dissolved organic nitrogen, nitrate, ammonium 

N2

NO2-

N2

 NH4+

NO3

-

NO2

-

 NH4

+

NO3

-

Export to

downstream

Dead

organic

matter and

microbes

Benthic

algae and

microbes

Cyanobacteria

Mineralization

Assimilation

Assimilation

Assimilation

N fixation

Excretion

Sediment subsurface

Denitrification

Nitrification

Stream water

Figure 3. Nitrogen (N) cycle in streams and rivers (adapted from Allan and Castillo, 2007). DON, dissolved organic nitrogen; 

NO3

−

, nitrate; NH4

+, ammonium; NO2

−, nitrite; N2

, nitrogen gas. 
Nutrient Cycling in Streams and Rivers 7

(excreted). Although N-fixation is important in some streams 

(Grimm and Petrone, 1997; Kunza and Hall, 2014), most N 

inputs into a stream come from riparian vegetation (litter fall), 

overland flow, and groundwater flow. 

Both NH4

+ and NO3

− are easily assimilated by benthic 

algae, aquatic plants, and microbes associated with decaying 

organic matter. Generally, NH4

+ is more energetically favorable 

and is taken up more readily than NO3

−. Breakdown of organic 

matter represents the opposite process, where organic N 

is mineralized to NH4

+ . Besides direct assimilation of N by 

plants and microbes, there are two important energy-yielding 

microbial reactions that are common in streams and rivers, 

nitrification and denitrification. Nitrification is a microbial 

process that converts NH4

+ to NO3

− and is favored under more 

aerobic conditions (fig. 3). Denitrification converts NO3

− to N2

and denitrifying bacteria can thrive under both low and high 

oxygen conditions; however, they use NO3

− only for energy 

production when oxygen is low (fig. 3). Denitrification is one 

of the most important N cycling processes because the end 

product, N2, is inert to most living things and can be released 

into the atmosphere, representing a true loss of N from stream 

and river ecosystems. Although not as common as nitrification 

and denitrification, the process of dissimilatory NO3

− reduction 

to ammonium (DNRA) can also take place. Under certain 

conditions, NH4

+ can actively exchange (sorb and desorb) 

with cation sites within the sediment matrix representing a 

temporary loss or storage of N. As shown in figure 3, most 

N cycling takes place within streambed sediments, and uptake 

directly from the water column is believed to be a small 

amount of total uptake; however, some studies have shown 

that, in large rivers, uptake from the water column can be 

important (Tank and others, 2008).

Sources and Cycles of Phosphorus

Phosphorus can be present in stream water as 

orthophosphate (PO 4

−3 ) dissolved in water and attached 

to inorganic particles in suspension, as dissolved organic 

molecules, and as particulate organic forms from bacteria 

and detritus. Generally, P exists in greater proportions in 

particulate forms compared to dissolved forms; therefore, 

landscape features such as soil type, geology, terrestrial 

vegetation, topography, land use, along with human sources 

control the amount and form of P in streams and rivers 

(Hendricks and White, 2000). Most P in soils and surrounding 

geology is insoluble; however, as these materials erode and 

become weathered, there is a potential for this P to enter 

streams and become more readily available. This is because 

PO 4

−3 easily adsorbs to charged particles, especially clays, 

which are transported to streams in runoff. The decomposition 

of litter from terrestrial systems further adds to the dissolved 

and particulate forms of inorganic P from runoff and 

groundwater discharge (Roberts and Bilby, 2009). 

Atmospheric deposition of P is lower than deposition 

of N (Allan and Castillo, 2007); however, similar to N, local 

land use has a big effect on the P loading to streams and rivers 

(Brett and others, 2005a, 2005b; Herrera Environmental 

Consultants, Inc., 2007, 2011). Anthropogenic sources of 

P to streams and rivers are from point source wastewater 

discharges, and non-point sources from fertilizer and manure 

applications, and failing septic systems (Brett and others, 

2005a; Withers and Jarvie, 2008). These nonpoint sources can 

enter streams and rivers by runoff and groundwater flowpaths. 

Wastewater sources can have a big influence on river water 

quality and primary productivity because a large fraction of 

these inputs is as PO 4

−3

, which is taken up easily and efficiently 

by stream biota. Similarly, runoff can include a larger fraction 

of dissolved P, but also carries particulate forms as soil and 

sediment are mobilized during runoff events. In Puget Sound, 

direct wastewater discharges of P are not important (Ebbert 

and others, 2000; Brett and others 2005a); however, non-point 

source inputs of P to streams from urban and agricultural land 

uses (Brett and others, 2005a, 2005b; Herrera Environmental 

Consultants, Inc., 2007, 2011) and geologic material (Wise and 

Johnson, 2011) are significant.

Phosphorus cycling in streams is complex (fig. 4) and 

influenced by physical, chemical, and biological processes. 

The main biological processes include the assimilation of 

dissolved inorganic P into cells of phytoplankton, macrophytes, 

and benthic algae; transfer of this organic P through the food 

chain to invertebrates and fish, and then released again by 

excretion and remineralization during decomposition (fig. 4). 

Algae and microbes in biofilms obtain most of their P from 

the water column, whereas rooted plants will acquire their P 

from sediments and sediment pore waters. Physical-chemical 

processes such as sorption and desorption and complexation 

also influence the amount of available P in streams and rivers. 

Sorption and desorption are dependent on the capacity of 

sediments to retain P and can influence local diffusional 

gradients at the sediment-water interface. Complexation, or 

bonding, of P to metal oxides and hydroxides under aerobic 

conditions can release P when conditions become more 

anaerobic. This process can result in the temporary storage of 

P at sediment surfaces, which becomes available later when 

sediments are buried and soluble P is released into pore waters. 

The physical attributes of a channel, such as slope and presence 

of pools and riffles create areas for sediment transport and 

deposition, which temporarily store and release particulate P 

as it moves downstream (Reddy and others, 1999).
8 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

tac15-0989_fig04

P inputs

Import from

upstream

Groundwater dissolved organic phosphorus, orthophosphate

Export to

downstream

Sediment subsurface

Stream water

Particulate P

Orthophosphate

Sorption

Uptake of P

P release

Sediment

resuspension

Phytoplankton

Aquatic plants Fish

Benthic algae and

microbes

Sediment

deposition

Diffusion of P

across sedimentwater interface

Mineralization of organic

matter

Figure 4. Example of the phosphorus (P) cycle in streams (adapted from Allan and Castillo, 2007). 

Factors Related to Nutrient Attenuation 

in Streams and Rivers

The N and P cycles in streams are dictated by a complex 

suite of physical, chemical, and biological processes that make 

these cycles dynamic in space and time. Flow in streams and 

rivers is dominated by movement in the downstream direction; 

therefore, advection of dissolved and particulate forms of 

N and P results in a constant interaction of nutrients with 

surface and subsurface features of these environments. The 

factors related to nutrient attenuation in streams and rivers are 

numerous and vary in scale from the watershed, to the reach 

level, to individual channel features. Furthermore, factors of 

nutrient attenuation are intricately connected where biological 

factors can be influenced by physical factors, biological factors 

can be influenced by chemical factors, and physical factors can 

be influenced by biological factors. This report summarizes the 

important physical, chemical, and biologic factors related to 

nutrient attenuation. Additionally, although the focus of this 

report is on the important instream factors related to nutrient 

attenuation, important watershed factors related to nutrient 

delivery to streams and rivers are briefly summarized. 

Physical Factors

Physical factors of nutrient attenuation are factors of a 

stream or river reach related to the hydrologic and geomorphic 

characteristics of the channel. The main overarching theme 

in the scientific literature is that increasing the time nutrient 

molecules spend within a given river reach enhances the ability 

of that reach to retain or attenuate these nutrients. Streamflow, 

water velocity, and channel geometry (width and depth) are 

interrelated and contribute to travel time of a stream or river 

reach. In the simplest form, the slower the surface water 

velocity, the longer the travel time. Because streamflow is 

defined as the velocity of the water times the cross-sectional 
Factors Related to Nutrient Attenuation in Streams and Rivers 9

area of the channel (width times the depth), changes in any 

of these parameters will result in changes to the average reach 

travel time. Several studies have shown that small streams 

(1st and 2nd order) are more efficient at nutrient retention 

than large streams (4th order and greater), particularly when 

looking at the watershed scale (Alexander and others, 2000; 

Bernot and Dodds, 2005; Ensign and Doyle, 2006; Wollheim 

and others, 2006; Mulholland and others, 2008; Roberts and 

others, 2008). Generally, there are more stream miles of small 

streams in river networks than in larger order streams and 

these small streams have lower flows and greater surface areas 

per unit flow than large streams that have high velocities and 

are more channelized. The width to depth ratio of a reach also 

is important because it is related to how much of the flow is 

in contact with the stream bottom, which is an active area for 

nutrient processing.

Channel-flood plain connectivity is an important physical 

feature of stream and river reaches related to attenuation in 

a given watershed. The more connected a channel is with its 

flood plain, the more opportunity there is for high streamflows 

to access the flood plain with its shallow topography resulting 

in slower velocities and increased travel times. The interaction 

of a stream channel with its flood plain has been shown to 

retain water, sediment, and nutrients (Jansson and others, 

1994). The main pathway for N loss is through denitrification 

(Mitsch and others, 2000; Saunders and Kalff, 2001; Sheibley 

and others, 2006), whereas the main pathway for P loss is 

sedimentation (Behrendt and Opitz, 1999; Olde Venterink and 

others, 2003). The nutrient retention capacity of a flood plain 

depends on many factors such as soil properties, availability 

of labile organic carbon (Davidsson and Ståhl, 2000), 

water temperature (Pinay and others, 2007), soil moisture 

(Olde Venterink and others, 2003), flow velocities, and 

water retention times (Tockner and others, 1999). All these 

properties are tied to the frequency and duration (and extent) 

of flooding within a given flood plain unit when relating to 

how much nutrient attenuation can take place (Natho and 

Venohr, 2014). Flood plains can be important for nutrient 

retention over an annual time scale because increased flows 

during storms can carry a significant amount of the annual 

load of nutrients in many watersheds (Ahearn and others, 

2004; Macrae and others, 2007). Channel confinement, the 

ratio of the flood plain width to the channel width (Knighton, 

1998), is commonly used to evaluate channel-flood plain 

connectivity. When the channel confinement is greater than 

three the channel is considered unconfined and there is a 

potential for substantial exchange of water between channel 

and flood plain, which can lead to increased retention of 

organic matter (Bellmore and Baxter, 2013).

In addition to channel-flood plain exchange of water, 

streams and rivers continuously exchange water between 

the main channel and subsurface sediment, surrounding 

riparian areas, and underlying groundwater (Boano and 

others, 2014). The exchange of water in the vertical and lateral 

directions with slower moving water beneath and along 

the stream slows the bulk flow of dissolved and suspended 

materials (termed transient storage) that can increase the 

contact time with reactive surfaces (Jones and Mulholland, 

2000). Transient storage can occur as surface storage in the 

main channel of rivers and streams as a result of pools, side 

channels, back waters, and eddies, or as a result of hyporheic 

exchange. Hyporheic exchange, also called hyporheic transient 

storage, is the transport of surface water through subsurface 

flowpaths below and lateral to the main channel that returns 

to surface water; this exchange may or may not also interact 

with the shallow groundwater system (Bencala and Walters, 

1983; Triska and others, 1989; Harvey and others, 1996). 

Therefore, the total amount of transient storage in a given 

reach is made up of both surface and hyporheic components. 

Transient storage zones have been shown to greatly affect N 

and P cycling because they extend residence times within 

the reach and increase exposure of surface water to areas of 

biologically active sediment communities (bacteria, plants, 

algae) (Mulholland and others, 1997; Duff and Triska, 

2000; Hendricks and White, 2000; Briggs and others, 2009). 

Although the correlation between increases in transient storage 

and increases in nutrient retention is not universal (Ensign 

and Doyle, 2006), generally, features of a stream or river that 

enhance transient storage, in particular hyporheic storage, will 

likely result in increased nutrient attenuation.

Over the last few decades, there has been a great deal 

of research associated with understanding the physical and 

geomorphic controls of hyporheic exchange (see Boano and 

others [2014] for a recent review). Generally, there is a greater 

potential for hyporheic exchange in a stream or river that 

contains heterogeneous habitat elements at both large scales 

(for example, pool-riffle sequences and secondary channels) 

and small scales (heterogeneous substrate, debris dams, and 

in-channel vegetation). Hyporheic exchange in streams has 

been shown to increase in the presence of large woody debris 

(Valett and others, 2002), in-stream vegetation (Harvey and 

others, 2003), channel meanders (Boano and others, 2006), 

and pool-riffle sequences (Gooseff and others, 2006; Tonina 

and Buffington, 2007). In addition to these large channel 

features, sandbars and sand dunes (Thibodeaux and Boyle, 

1987; Holmes and others 1994; Elliot and Brooks, 1997; Tonina 

and Buffington, 2011; Hester and others, 2013; Stonedahl and 

others, 2013), and coarse substrate such as cobbles (Vaux, 

1968) have been shown to promote hyporheic exchange. 

A growing body of literature shows that restoration of 

in-stream features such as constructed riffles, steps, debris 

dams, and weirs can promote N processing (Shibata and 

others, 2004; Ensign and Doyle, 2005; Kasahara and Hill, 

2006a, 2006b). Physical characteristics of stream and 

river reaches such as channel slope and sinuosity, channel 

roughness, and substrate size have been determined to be 

important factors that contribute to hyporheic exchange and in 

turn, nutrient retention (Gooseff and others, 2007; Baker and 

others, 2012). 
10 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

Urbanization in the Puget Lowlands has resulted in 

changes to stream channels and their associated hydrologic 

characteristics throughout the region. The increase in amount 

of impervious surfaces can lead to quick movement of 

stormwater to streams and rivers, increase the flashiness of 

a stream, and increase the peak discharge of storms (Booth 

and others, 2002; Konrad and others, 2005). Flood control 

practices in urban streams can result in the removal of 

important channel features such as woody debris. Channel 

straightening (Booth and others, 2002) can result in a loss of 

habitat complexity. As a result, urbanization results in higher 

stream water velocities, less dispersion, and shorter travel 

times (Roberts and Bilby, 2009) compared to forested streams 

as well as the loss of important channel features that promote 

hyporheic exchange. Little information exists for characterizing 

important physical factors for nutrient attenuation directly in 

Puget Lowland streams. However, several habitat monitoring 

programs likely gather relevant data, which have not been 

summarized or widely distributed. 

Chemical Factors

Chemical factors related to nutrient attenuation include 

the amount of nutrients present, the amount of oxygen present, 

and for some N cycle processes, the amount of organic carbon 

present. Multiple field and laboratory based studies have 

determined that the rate of nutrient uptake is a function of the 

nutrient concentration (Dodds and others, 2002; Inwood and 

others, 2005; Bernot and others, 2006; Mulholland and others, 

2008) and the more nutrients that are present, the greater the 

potential for attenuation. However, this relation is not linear, 

and a leveling off, or saturation, of retention is typically found 

at high nutrient concentrations (Dodds and others, 2002). 

Although the rates of nutrient attenuation may increase in high 

nutrient loaded systems, the proportion of the stream or river 

load retained decreases as concentrations increase, reducing 

the efficiency of overall attenuation (Inwood and others, 2005; 

Mulholland and others, 2008; Alexander and others, 2009). 

Many of the processes in the N and P cycles are controlled by 

the amount of oxygen in surface water and hyporheic waters 

(figs. 3 and 4). For example, denitrification, which represents 

a true loss of inorganic N from the system, needs anaerobic 

conditions in the sediment to take place. For denitrification, 

organic carbon also is required as an energy source for 

denitrifying bacteria. Therefore, low oxygen conditions in 

the sediment, often related to anaerobic microsites (Sheibley 

and others, 2003a), the amount of dissolved organic carbon 

(DOC), and presence of fine benthic organic matter (FBOM) 

are important factors related to N retention (Mulholland and 

others, 2000; Meyer and others, 2005; Inwood and others, 

2007; Harvey and others, 2013). Thus, as the overall percentage 

of fines in a given stream reach increases, N attenuation also 

is expected to increase. Likewise, the sorption/desorption 

of P is highly dependent on the redox conditions present in 

the sediment.

Biological Factors

Biological processes of N attenuation in streams 

and rivers includes both microbial and algal/plant uptake 

processes. Biological uptake for P is greatest through plant/

algal uptake processes; therefore, factors that result in 

increases in plant and algal biomass will be important for 

nutrient attenuation. Firstly, because algae and plants are 

primary producers, they need sunlight and as the amount of 

sunlight increases, the gross primary production (GPP) in 

streams increases (Mulholland and others, 2001). Secondly, 

studies have shown that nutrient attenuation is greater during 

daylight (Fellows and others, 2006; Mulholland and others, 

2006) and N and P retention is correlated with gross primary 

production (GPP) and community respiration (CR) of streams 

(Mulholland and others, 2001; Hall and Tank, 2003; Meyer and 

others, 2005; Roberts and Mulholland, 2007).

Plant and algal communities also have an indirect effect 

on nutrient attenuation. The presence of large algal mats and 

aquatic plants changes the hydraulic characteristics of the 

stream by increasing dispersion coefficients and transient 

storage, and enhancing nutrient uptake (Mulholland and 

others, 1994; Sand-Jensen and Mebus, 1996; White and 

Hendricks, 2000). These biological features increase travel 

times through a reach and can trap sediment over time, which 

provides a source of organic matter for microbial processing 

of N and alters stream bed topography to promote increased 

hyporheic exchange (White and Hendricks, 2000; Duff and 

others, 2002).

Biological processes are also influenced by temperature, 

which has been shown to influence stream nutrient 

concentrations of N and P (Hendricks and White, 1995; 

Sheibley and others, 2003a; Triska and others, 2006). 

Warm temperatures are related to the amount of sunlight 

and increases in microbial uptake kinetics, thus higher 

temperatures tend to correlate with high rates of N and P 

retention across many studies (Martin and others, 2001; 

Sheibley and others, 2003b; Simon and others, 2005; Hanafi 

and others, 2006; Mulholland and others 2006; Triska and 

others, 2007). 

Watershed Related Factors

Although the focus of this report is on instream factors 

related to nutrient attenuation, several factors of a stream’s 

watershed control the amount of nutrients delivered to streams 

and rivers and subsequently the amount of instream nutrient 

attenuation. For example, watershed size correlates with 

the amount of N delivered to rivers and streams (Saunders 

and Kalff, 2001) because a large watershed receives greater 

amounts of N, which can potentially reach streams and 

rivers. Other watershed factors include human population, 

development (agriculture and urbanization), and the amount 

of impervious surfaces in a watershed, all of which are related 
Methods for Evaluating Nutrient Attenuation in Rivers and Streams 11

to watershed land use. Streams and rivers in developed areas 

of Puget Sound are enriched with nutrients relative to those 

in undeveloped areas (Ebbert and others, 2000; Herrera 

Environmental Consultants, Inc., 2007, 2011). Recent data 

collected throughout the nation have shown that the highest 

average concentrations of total N are in small streams draining 

agricultural areas (Dubrovsky and others, 2010). Similar trends 

were observed in the Puget Sound Basin where urban and 

agricultural land use in the basin is positively correlated to 

instream dissolved inorganic nitrogen (DIN) concentrations 

(Roberts and others, 2014). Fertilizers used in agricultural 

and urban areas, manure associated with dairy farms, and 

atmospheric deposition are sources of N in Puget Sound Basin 

rivers (Embrey and Inkpen, 1998). Average concentrations of 

total P that exceed the goal of 0.1 mg/L to prevent excessive 

plant growth (U.S. Environmental Protection Agency, 1986) 

have been detected in streams and rivers in all land-use 

areas of Puget Sound Basin except undeveloped land (Ebbert 

and others, 2000). Unlike total N, concentrations of total 

P in streams and rivers in the Puget Sound Basin do not 

correlate with watershed application rates and atmospheric 

deposition of P in drainage basins (Inkpen and Embrey, 1998). 

Phosphorus attaches to soil particles and usually remains close 

to application areas unless it is transported to rivers by soil 

erosion. Because erosion transports P to streams, yields of total 

P correlate with yields of suspended sediment. The presence of 

riparian zones along stream corridors can influence nutrient 

delivery to streams (Naiman and Décamps, 1997) and the 

importance of riparian zones for reducing terrestrial loads 

of nutrients as they move through surface and subsurface 

flowpaths to streams and rivers has been demonstrated (see 

Ranalli and Macalady, 2010 for a recent review). 

Numerous physical, chemical, biological, and watershed 

factors related to nutrient attenuation in streams and rivers 

are shown in table 1. Any of these factors can work together 

in a real world system; however, little is known about the 

importance of a single factor, or interaction of factors, 

on reach-scale nutrient attenuation. Some studies have 

attempted to combine multiple factors and related ecosystem 

processes that directly and indirectly influence reach scale 

nutrient attenuation (Hall and others, 2009; Mulholland and 

others, 2009).

Methods for Evaluating Nutrient 

Attenuation in Rivers and Streams

There are several methods for estimating attenuation in 

streams and rivers at both the stream reach and watershed 

scales. At the stream-reach scale, field-based methods typically 

are used to directly or indirectly measure attenuation rates. 

These field-based methods were developed for and have 

been largely applied to small streams; however, recent studies 

have tried to adapt small-stream field methods to large rivers 

(Dodds and others, 2008; Tank and others, 2008) with some 

success. At the watershed-scale, empirical relations measured 

at the reach-scale are incorporated into river network models. 

Estimating stream and river attenuation in the field at the 

reach-scale provides local, site-specific information about 

nutrient attenuation that is useful on its own as well as 

information that can be used to develop model parameters 

that are optimized for a given study area. Field methods can 

be labor intensive, which limits the number of sites where 

direct estimates can be made. Despite this challenge, when 

using a watershed-scale model of nutrient attenuation, having 

local data to feed into the models is always preferred to using 

literature-based data. Approaches to modeling watershed-scale 

attenuation vary in the extent to which they incorporate 

empirical reach-scale measurements, the complexity in which 

they represent stream and watershed hydrology, and the scale 

at which they predict attenuation (that is, small watershed to 

regional/continental).

Field-Based Methods of Instream 

Nutrient Attenuation

Generally, there are three approaches to estimating 

reach-scale attenuation in the field: (1) reach scale nutrient 

mass balances; (2) field or laboratory experiments that estimate 

nutrient uptake of individual processes, which can then be 

scaled up to a study reach; and (3) short-term tracer and 

nutrient additions. Mass balance studies measure all nutrient 

inputs and outputs of a given stream reach to estimate the 

amount of attenuation by calculating the difference between 

inputs and outputs. Mass balance studies sometimes ignore 

groundwater nutrient inputs and focus only on longitudinal 

change in surface water nutrient load; however, even when 

surface water nutrient loads are the same between upstream 

and downstream locations, retention may be taking place if 

groundwater input loads are taken into account (Duff and 

others, 2008; Sheibley and others, 2014).

Measuring fine-scale nutrient uptake rates using field 

or laboratory based experiments involve the calculation of 

a nutrient uptake rate per unit area of streambed, which is 

multiplied by the total surface area of the stream reach to 

estimate the total amount of reach-scale attenuation. This can 

be done in numerous ways, but the most common methods 

use benthic flux chambers (Davis and Minshall, 1999; Fellows 

and others, 2006), the use of sediment-water flask studies in 

the laboratory (Duff and Triska, 1990; Garcia-Ruiz and others, 

1998; Kemp and Dodds, 2002; Inwood and others, 2007), or 

sediment cores in the field or laboratory (Sheibley and others, 

2003a; Strauss and others, 2004; Fellows and others, 2006). 
12 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

Table 1. Summary of physical, chemical, biological, and watershed factors associated with nutrient attenuation in streams and rivers.

Factor Parameter Effect

Physical factors

Substrate size/type Sand and gravel (percent) Increase hyporheic exchange potential.

Travel time Discharge High flows reduce travel time through the reach.

Stream velocity High velocity reduces travel time through the reach.

Channel geometry Specific discharge (Q/w) Low values indicate a greater proportion of flow in contact with stream bottom.

Width to depth ratio (w:d) Larger values indicate a greater proportion of flow in contact with stream 

bottom.

Flood plain connectivity Channel confinement Increases overall downstream travel time.

Slows down velocity of water; increases surface area available for nutrient 

attenuation.

Transient storage

Surface storage Backwaters/eddies These features contribute to increases in travel time in the reach, but play a less 

Side channels important role in attenuation compared to hyporheic exchange.

Pools

Hyporheic exchange

Riffle pool sequences Channel slope Changes in slope promote subsurface flow.

Sand dunes and sand bars Channel roughness Changes in pressure differentials promote subsurface flow.

Large woody debris These features promote subsurface flow below and around these structures.

Boulders

Chemical factors

Nutrient concentration Nitrate (NO3), phosphate (PO4) 

concentration

High nutrient concentrations result in high rates of attenuation, but the 

efficiency of retention decreases. 

Uptake velocity (vf) The uptake velocity is a measure of uptake efficiency and levels off at high 

concentrations.

Increase nitrogen attenuation through denitrification.

Redox condition Dissolved-oxygen 

concentration (DO)

Low DO favors denitrification and nitrogen loss.

DO concentration is related to sorption/desorption of phosphorus in sediment.

Presence of organic matter Percent fines (fine benthic organic 

matter)

Biological factors

Presence of algae and plants Sunlight Open canopies result in greater primary productivity and more nutrient 

uptake.

Algal and plant alteration 

of hydraulics

Decreased velocities These indirect processes take place in the presence of macrophyte beds, which 

can lead to greater attenuation of nutrient.

Deposition of organic matter

Formation of hummocks

Uptake rate kinetics Temperature Warmer temperatures tend to result in higher rates of nutrient uptake.

Watershed related factors

Watershed characteristics Watershed area

Population

Urban and agriculture (percent)

Impervious surface (percent)

All of these factors contribute to increases in nutrient loading to rivers and 

streams, thereby reducing attenuation efficiency in a given reach.

Riparian buffers In the presence of intact riparian buffers, nutrient delivery to the reach is 

decreased.
Methods for Evaluating Nutrient Attenuation in Rivers and Streams 13

One of the most common approaches for estimating 

nutrient attenuation in the field, particularly since the 1990s, 

is using short-term nutrient and stream tracer additions. 

This procedure involves injecting a concentrated solution of 

nutrient and conservative tracer into the upstream end of a 

reach and then measuring nutrient and tracer concentrations 

longitudinally at multiple downstream locations along the 

reach when the stream reaches equilibrium. The reach is 

determined to be in equilibrium when the concentration 

of the conservative tracer has reached a plateau at the most 

downstream location of the reach. A conservative tracer is 

a chemical that will not undergo significant transformation 

by biological activity, whereas the nutrient concentration 

will change as it moves downstream through the reach 

(non-conservative) as a result of various uptake processes. 

Data from these injection experiments are used to estimate 

travel time and changes in flow along a reach by analyzing the 

behavior of the conservative tracer. The change in nutrient 

concentration relative to the tracer also can be used to estimate 

the amount of attenuation in the reach based on the nutrient 

spiraling concept (Webster and Patten, 1979; Newbold and 

others, 1981). These experiments calculate attenuation through 

the use of three nutrient spiraling metrics: the uptake length 

(Sw), uptake rate (U), and uptake velocity (vf) (details on 

performing a nutrient addition experiment are presented in 

Stream Solute Workshop [1990]). The Sw is the mean stream 

distance traveled by a nutrient atom before it is removed 

from the water column, U is the mass of nutrient removed 

from the water column per unit area of stream bottom per 

unit time, and vf, the uptake velocity, is analogous to a mass 

transfer coefficient and describes how efficient a given reach 

is at attenuating nutrients. The three metrics are related to one 

another by the following equations (Newbold and others, 1981; 

Stream Solute Workshop, 1990):

Sw = QC/(Uw) (1)

U = vfC (2)

vf = Q/(Sww) (3)

where 

C is surface-water nutrient concentration,

w is stream width, and

Q is discharge.

These metrics are typically determined for reaches ranging 

from less than 100 to several thousand meters long with the 

assumption that the values hold for longer reaches if the 

experimental reach incorporates the typical characteristics 

(width, depth, flow, sediment type) of the longer reach. The 

uptake length can be determined graphically by plotting 

the ratio of nutrient to tracer concentration compared with 

downstream distance; the slope of this line is -1/Sw (fig. 5). 

Distance downstream of injection point

Ln (nutrient/tracer)

Slope = -1/Sw

Figure 5. Example of how to determine the uptake length (Sw) for a stream reach from a 

short-term nutrient addition experiment. The natural log (ln) of the ratio of nutrient to tracer 

concentration in the stream is plotted over distance downstream of the injection point.
14 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

Once Sw is calculated, U and vf are determined from stream 

width, discharge, and nutrient concentration using the 

equations 1–3. 

The nutrient spiraling approach is described in detail 

because it is common to incorporate these metrics into 

model estimates of watershed-scale instream attenuation. The 

spiraling approach is limited by the assumptions that uptake 

follows first order kinetics and that dispersion and transient 

storage within the reach are negligible. Another limitation of 

the spiraling approach is that it does not measure true ambient 

or background rates of nutrient uptake because it involves an 

artificial addition of nutrients to the system. Because nutrient 

uptake is a function of nutrient concentration (see Dodds and 

others, 2002), nutrient additions result in an estimate of net 

uptake and do not reflect gross uptake of the stream or river. 

However, different approaches to analyzing data from a typical 

nutrient injection experiment (Payn and others, 2005; Earl 

and others, 2007; Covino and others, 2010) or the use of stable 

isotopes of N (Webster and others, 2003; Mulholland and 

others, 2008) and P (Mulholland and others, 1990) can result 

in better estimates of ambient rates of attenuation.

Watershed-Scale Models of Instream 

Nutrient Attenuation

Watershed-scale approaches to estimating nutrient 

attenuation use empirical models that are based on expressions 

derived from field-collected data directly or indirectly from 

a model parameterization process. These models provide 

expressions for reach level attenuation that are based on 

correlations between measured attenuation data and channel 

or watershed characteristics; estimates based on summarized 

scientific literature; or estimates derived from expressions 

that describe changes in nutrient concentrations in reaches 

as water moves downstream. Watershed-scale models are 

independent in space so an attenuation expression can be 

used across study areas but will vary in complexity based on 

the representation of watershed hydrology and the amount of 

data needed to parameterize the model. For example, models 

for nutrient attenuation can range from simple expressions 

based on only physical features of a stream channel (Seitzinger 

and others, 2002) to complex watershed models that simulate 

flow and water quality using detailed water quality sampling 

in the study area of interest in order to calibrate and fit model 

parameters used to describe attenuation (Smith and others, 

1997; Arheimer and Brandt, 1998; Jung and Deng, 2011). A 

brief summary of empirical models of nutrient attenuation 

is provided in table 2. There is a wide range of complexity 

represented in these models; however, a common feature of 

all these models is that the residence time of water within a 

given reach is used as a key factor influencing the amount of 

attenuation that takes place within a reach.

Analysis of Relative Nutrient 

Attenuation in Puget Sound Basin 

Analysis of relative nutrient retention in the Puget Sound 

Basin was done at multiple scales to better understand the 

most important factors related to attenuation in the region. 

The Puget Sound region lacks a comprehensive assessment 

of nutrient spiraling metrics (vf, Sw, U) or other field-based 

estimates of nutrient attenuation (nutrient-tracer injections, 

mass balances, measurement of sediment uptake rates). 

Although SPARROW (a watershed-scale spatially explicit 

regression model that can estimate instream attenuation) 

has been used to assess the Puget Sound region as part of 

a larger application to the Pacific Northwest (PNW) (Wise 

and Johnson, 2013), the model has not been optimized for 

Puget Sound conditions. Therefore, as an initial analysis of 

nutrient attenuation patterns in the Puget Sound Basin, the 

potential N and P removal across Puget Sound stream reaches 

was estimated using two empirical attenuation models; a 

framework was developed to identify and score stream reaches 

with potentially high attenuation capacity; and temporal 

drivers of N and P attenuation were analyzed in specific Puget 

Sound stream reaches. This assessment uses only information 

that can be expressed as mapped characteristics to explain the 

relative attenuation of nutrients in Puget Sound rivers and 

streams based on best available information. Maps of these 

factors will help identify areas within the system where relative 

attenuation is high or low throughout the region. The relative 

attenuation of a stream or river reach will be considered 

attenuation on a per kilometer basis for comparative purposes 

in this report. 

Watershed Scale Attenuation of Rivers and 

Streams in Puget Sound Basin

At the watershed scale, two empirical attenuation models 

were used to estimate average relative annual attenuation in 

the Puget Sound Basin for the networks of the 17 major rivers 

draining to Puget Sound (fig. 1). The river nitrogen (RivR-N) 

model (Seitzinger and others, 2002), which is based on only 

physical (hydrological) characteristics and the vf model, which 

incorporates physical, chemical, and biological factors, were 

used (Doyle, 2005; Wollheim and others, 2006).
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 15

Table 2. Summary of modeling approaches to describe instream nutrient attenuation for watershed-scale models from review of scientific literature.

Attenuation expression Nutrient

Parameter categories

Description References Physical Chemical Biological

R Sn z T Sn

where

Sn f N

O

= ( )

+ ( )

= 

 



−

/ /

/ 3

Nitrate

X

X

X This method uses physical characteristics of the stream

and information on nutrient concentration anddenitrification rates. Initially developed for lakes, butapplicable for any unstratified water body. WhereR is instream attenuation defined as the percentage ofnutrient input removed, z is mean depth, T isresidence time, Sn is mass transfer coefficient, f is themeasured denitrification rate and NO−

3

 

 is the nitrate concentration.

Kelly and others (1987);Howarth and others (1996)

y Q = ( )− ( ) 10 1 00 0 39 . log x/Q . / Total nitrogen 

(TN)

X

X Based on previous work showing that instream

attenuation (y) increases with loading rates (x), a regression was developed for discharge (Q)normalized data form lakes, wetlands, andrivers. Mass balance data (outputs – inputs) fromthe literature were used. y = nitrogen attenuation ingrams per square meters per year and x is nitrogen load in grams per square meters per year. 

Saunders and Klaff (2001) 

R D

T

= ( )− 88 45 0 3677 . / . Nitrate

X A regression model, the RivR-N model, was used to

simulate the proportion of nitrate removed from streams and reservoirs based on published nitrateremoval data. Data were compiled and quantified from mass balances (upstream-downstream loads) ordenitrification studies in sediment cores. R = nutrientattenuation as proportion of nitrate inputs removed; D = mean depth in meters; T = time of travel in years. T was calculated by taking reach length divided by thevelocity. D was calculated from mean annual discharge (Q) as D = 26.12Q-0.3966 (Leopold and Maddock, 1953).

Seitzinger and others (2002)
16 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington Attenuation expression Nutrient Parameter categories Description References Physical Chemical Biological R LVf uh Vf

HL = −

−( ) − −( ) 1 1 exp / ; exp / Nitrogen or phosphorus

X

X

X Retention of nutrient as a part of incoming load 

(R) based on an analysis of the hydrologic variability onnutrient spiralling. Beginning with assumptions ofnutrient sprialing, first order exponential decay alongreach and low influence of dispersion and transientstorage, this expression for R, takes into accountthe hydrological and biological characteristics ofthe reach. vf = uptake velocity for nitrogen or

phosphorus; L = reach length; u = mean velocity; h = mean depth; HL is the hydraulic load defined as Q/wL = h/T = uh/L, where Q is discharge, w is width and T is residence time. 

Doyle (2005); Wollheim and others (2006); Mulholland and others (2008); Helton and others (2010); Stewart and others (2011); Aguilera and others (2013)

k T k T 1 2 = −( )

−( ) exp D δ α

α ; 2 = exp 1 Nitrogen or phosphorus

X

X

X The SPARROW model is a hybrid statistical and

mechanistic model for estimating the movement of massthrough the landscape under long-term, steady stateconditions. A calibrated model provides estimates of theannual load and annual yield (load per unit area) for theconstituent of interest, for example TN and total

phosphorus (TP), for every reach in the modeled surface-water network. The instream decay (k1) is a function of δ, the decay coefficient (fitted with the model), and T is the travel time in the reach. In later uses, the expression given by k2 and was used where α1 and α2 are coefficients fitted by the model, D is the reach depth.

Smith and others (1997);Alexander and others (2000); Alexander and others (2007) 

PHI par2 C T V i 10 = ( )( )( )( ) Nitrogen

X

X

X The hydrologic model (HBV) uses daily precipitation

and monthly evaporation data to simulate water flow inthe river network. The watershed model is calibratedto a time series for outlet discharge. Instreamattenuation (PHI) is a function of par2, a fittedparameter, which is site specific, Ci is the inorganic nitrogen concentration, T10 is average of the last 10 day air temperature, and V water volume in storage. 

Arheimer and Brandt (1998)

Table 2. Summary of modeling approaches to describe instream nutrient attenuation for watershed-scale models from review of scientific literature.—Continued
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 17

Attenuation expression Nutrient

Parameter categories

Description References Physical Chemical Biological

R K Ab

Q T = × × ( ) 100 0293 . / Nitrogen

X

X

X HYDRA is a riverine flow and transport model, and

authors assumed NO−

3 removal was primarily though

denitrification and associated with the sediments. For each grid cell of the model defined R, thefraction of nitrogen removed where T is the watertemperature, K is a rate parameter (m/sec) fitted withthe model; Ab is the river bed area (m2), Cn is NO−

3

concentration (kg/m3). 

Donner and others (2004)

R / xl 1000slope+1 qx2

= ( ) ( ) 1 Nitrogen

X The POLFLOW model, a GIS-based model that 

simulates water flow, nutrient transport, and attenuation at a 1×1 km2 GIS pixel scale. The expression for R, the fraction of nitrogen removed in each pixel is based on ×1 and ×2, which are fitted model parameters, slope is the topographic slope of each cell, and q is average water flow for each pixel. 

Darracq and Destouni (2005)

k T

w

= ( )

− 0 14 0 28 . ln . Nitrogen

X This modeling approach estimated nitrogen retention

in streams and rivers using a longitudinal transportmodel with storage and variable residence time (VART),and incorporating a first-order reaction term. Monthly mean discharge and water-quality data and watershed modeling using the hydrologic simulation program Fortran (HSPF) model to parameterize the model. The instream nutrient loss (k) of the model is a function of Tw, the monthly mean water temperature and based on site-specific correlations.

Jung and Deng (2011)

Table 2. Summary of modeling approaches to describe instream nutrient attenuation for watershed-scale models from review of scientific literature.—Continued
18 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

 RivR-N Attenuation Model

The RivR-N model (Seitzinger and others, 2002) is 

a predictive model relating the physical and hydraulic 

properties of rivers and lakes to the proportion of N input 

that is removed by the water body. Published data on N 

removal from river reaches from the 1970s through 1990s 

were compiled that ranged from first order headwater rivers 

to the mouths of major rivers in the United States, Europe, 

New Zealand, and Canada. Land use in the watersheds 

included agricultural, urban, forested, and mixed uses. 

The proportion of N removal was quantified from mass 

balances (changes between upstream-downstream loads) or 

denitrification studies in sediment cores. Of the mass balance 

studies used, most were based on mass balance of NO3

−

, or 

in cases of mass balances on total N, loss of total N in each 

study was likely from denitrification. As a result, the RivR-N 

model primarily represents annual rates of NO3

−

 removal (by 

denitrification) across various rivers as the original study was 

focused on watershed N losses (Seitzinger and others, 2002). 

The relations between removal and river order, river discharge, 

watershed land use, total N-loading to the watershed, surface 

water residence time, and the water displacement ratio were 

examined. The best model, derived from 33 studies, was based 

on the ratio of depth to time of travel and given by: 

R = 88.45(D/T)-0.3677 (4)

where

R is nitrate removal as a fraction of total reach 

inputs, 

D is the average reach depth in meters, and

T is time of travel in the reach in years. 

The time of travel is typically calculated by taking the reach 

length (L) divided by the mean velocity (u) of the reach. 

The displacement ratio (D/T) represents the height of water 

column annually displaced from the water body (Seitzinger 

and others, 2002). This model provides a measure of the extent 

to which nutrients are in contact with the benthic sediments 

and a measure of variations in water contact time that result 

from changes in channel size (velocity and depth). Although 

the model was not developed with data from the PNW, and 

did not include rivers that are glacially influenced, the model 

has been successfully used to describe patterns of instream 

attenuation across 16 watersheds in the eastern United States 

(Seitzinger and others, 2002). Because the model describes a 

relation between N (as NO3

−) removal from a wide variety of 

studies, it was applied to the Puget Sound lowlands for this 

first-level analysis because estimates of channel characteristics 

in equation 4 were available. 

The RivR-N model was applied to a hydrologic network 

consisting of 535 valley segments (Konrad, 2015) that are 

based on the Puget Sound Watershed Characterization 

(Washington Department of Ecology, 2013b) (fig. 1). This 

river network is based on the high-resolution (1:24,000) flow 

lines from the National Hydrography Dataset (NHD) for 

Washington (U.S. Geological Survey, 2013). Flow lines for 

the 17 major rivers flowing into Puget Sound were clipped, 

and any segments draining less than 50 km2 were removed. 

Therefore, analysis of relative attenuation presented in this 

report do not include the smallest headwater streams for these 

17 major river basins.

The D/T in equation 4 is also referred to as the hydraulic 

load (HL) (Wollheim and others, 2006) and can be defined 

in terms of streamflow and the surface area of the streambed 

by D/T = Du/L = Q/wL, where w is the reach width and 

Q (= wDu) is the streamflow of the reach, and u is the mean 

velocity and L is the reach length. Therefore, the RivR-N model 

requires reach-scale estimates of Q/wL to estimate attenuation 

within stream and river reaches the Puget Sound Basin. Mean 

annual discharge for each of the 535 river segments was 

determined from an area-discharge relation derived from 

historical streamflow data for western Washington collected 

by U.S. Geological Survey (USGS). Streamflow data were 

downloaded from the USGS National Water Information 

System (NWIS) database (http://waterdata.usgs.gov/wa/nwis/

nwis) and mean annual discharge was calculated at all sites 

with at least 5 years of daily streamflow measurements for the 

1981–2010 period (current National Oceanic and Atmospheric 

Association climate normal period). The drainage area for 

these streamgages was also compiled from NWIS site files 

and an area-based regression for mean annual streamflow 

based on 147 USGS streamgages in western Washington with 

drainage areas greater than 10 square kilometers was created 

(fig. 6; appendix A). Drainage areas for the river segments 

in the hydrologic model are provided in Konrad (2015); the 

equation in figure 6 was used to estimate mean annual flow in 

all 535 river segments.

Width in meters was derived using regression equation 

5, which describes the hydraulic geometry for rivers in 

Washington State (Magirl and Olsen, 2009): 

w = 4.85 * Qmean0.48/3.281 (5)

where 

w is mean annual width in meters, 

Qmean is an estimate of the mean annual flow in 

cubic feet per second, and 

3.281 is a conversion factor to convert width from 

feet to meters. 
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 19

tac15-0989_fig06

y = 0.0247x1.1091

R2 = 0.8608 

0.1 

1 

10 

100 

1,000 

1 10 100 1,000 10,000 

Mean annual discharge, in cubic meters per second 

Drainage area, in square kilometers 

Figure 6. Mean annual discharge and drainage area for 147 U.S. 

Geological Survey streamgages with at least 5 years of record, 

western Washington, 1981–2010.

Equation 5 is based on data from USGS streamgages that 

are located on areas of river reaches where channels are well 

defined; therefore, for unconfined reaches, or braided channels 

with complex geomorphologies these width estimates will 

underestimate the actual channel widths. As a result, NO3

−

attenuation (R) will be underestimated for these reaches 

as well. Lastly, a standardized reach length (L) of 1,000 meters 

was selected to calculate a reach normalized HL. Because a 

standardized reach length was used, all attenuation values 

calculated for Puget Sound in this report are referred to as 

“relative attenuation.” This approach was selected to normalize 

attenuation across all reaches so that areas with low and high 

attenuation potential could be highlighted. In order to display 

attenuation data more clearly on a map, the relative instream 

NO3

−

 attenuation values for each reach are shown spatially 

by applying these values to their incremental contributing 

drainage area and do not represent attenuation within the 

watershed (fig. 7).

Generally, the reaches with the highest relative 

attenuation (>4 percent of NO3

−

 inputs attenuated per 

kilometer) were few (only 8 of the 535 river segments) and 

located in a handful of headwater reaches scattered throughout 

the Puget Sound Basin. Most reaches showed moderate levels 

of attenuation (ranging from 2 to 4 percent of NO3

−

 inputs 

attenuated per kilometer). The lowest relative attenuation was 

in the main stems of the largest of the 17 major rivers ranging 

from the Nooksack River in the north to the Nisqually River 

in the south (< 2 percent of N inputs attenuated per kilometer; 

fig. 7). The channels with the lowest relative attenuation tended 

to be wide and deep, which resulted in a lower displacement 

ratio and lower attenuation. Low relative attenuation was 

calculated throughout the entire main stem of the Skagit 

River from Canada to where it enters Puget Sound (fig. 7). 

For each of the major river basins, the RivR-N model shows 

higher relative attenuation in smaller headwater reaches than 

in their respective main stem reaches. These results do not 

necessarily mean that attenuation is not important in the main 

stems, but rather the RivR-N model shows that main stems are 

not as efficient at attenuating NO3

−

 as the smaller headwater 

reaches are.

Overall, the fraction of NO3

−

 inputs attenuated per 

kilometer of stream length using the RivR-N model ranged 

from 1.3 to 4.6 percent with an overall mean of 2.7 percent 

(table 3). The distribution of RivR-N attenuation showed only a 

few reaches with NO3

−

 inputs attenuated per kilometer greater 

than 4 percent (fig. 8), and a majority of the data was centered 

around the mean.
20 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

tac15-0989_fig07

EXPLANATION

Nitrate input removed 

per kilometer, in percent

< 2 

2 – 3 

3 – 4 

> 4

Puget Sound Basin

KING

LEWIS

YAKIMA

CLALLAM

CHELAN

SKAGIT

PIERCE

WHATCOM

KITTITAS

JEFFERSON

SNOHOMISH

PACIFIC

MASON

GRAYS HARBOR

COWLITZ

KITSAP

OKANOGAN

ISLAND

THURSTON

SKAMANIA

SAN JUAN

WAHKIAKUM

125° 124° 123° 122° 121°

49°

48°

47°

0 12.5 25 50 MILES

0 12.5 25 50 KILOMETERS

Base from U.S. Geological Survey digital data, 1:100,000

Transverse Mercator projection: NAD 1983 UTM Zone 10N

Puget Sound

Admiralty

Inlet

Skagit R

Green R

Puyallup R

Cedar R

Deschutes R

Nisqually R

Duckabush R

Samish R

Dungeness R

Elwha R

Hamma

Hamma R

Nooksack R

Dosewalips R

Snohomish R

Stillaguamish R

Duwamish R

Skokomish R

Big

Quilcene R

Commencement

Bay

Elliott

Bay

Figure 7. Relative instream nitrogen attenuation expressed in percentage of nitrate inputs removed per kilometer of stream length 

using the RivR-N model for Puget Sound Basin, Washington. The instream attenuation values for each reach are shown spatially 

by applying these values to their incremental contributing drainage area and do not represent watershed attenuation. Gray areas

represent areas of the Puget Sound lowlands that do not include a major river.
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 21

1.0 1.4 1.8 2.2 2.6 3.0 3.4 3.8 4.2 4.6 5.0

Nitrate removed per kilometer based on RivR-N model, in percent Nitrate removed per kilometer based on RivR-N model, in percent

0.00

0.04

0.08

0.12

Frequency of detection

x

x

o

1

2

4

10

20

517

517 number of values 

EXPLANATION 

Schematic boxplot

x

x

o

o

upper adjacent

75th percentile

median

25th percentile

lower adjacent

lower outside

lower detached

upper detached

upper outside

RivR-N

Figure 8. Relative instream attenuation calculated using the RivR-N model expressed as the percentage of 

nitrate removed per kilometer of stream length, Puget Sound Basin, Washington.

Table 3. Summary statistics of modeled concentrations, vf values, and reach-level relative attenuation from the RivR-N 

model and vf models expressed as a percentage of nutrient input attenuated per kilometer of stream length, Puget Sound 

Basin, Washington.

[Relative attenuation is defined as the percentage of nutrient inputs removed per kilometer of stream reach. Abbreviations: mg/L, milligram per 

liter; mm/min, millimeter per minute]

Nitrate

(mg/L)

Phosphate

(mg/L)

Nitrate vf

(mm/min)

Phosphate vf

(mm/min)

Attenuation model (percent)

RivR-N vf Nitrate vf Phosphate

Minimum 0.0 0.0 0.02 0.15 1.3 0.03 0.23

Maximum 7.1 1.5 2.2 0.50 4.6 32 8.5

Mean 0.25 0.02 0.99 0.41 2.7 4.8 2.0

Median 0.11 0.01 0.93 0.41 2.7 4.0 1.8

Sample N1 11,213 11,223 492 489 517 492 489

1

Nitrate and orthophosphate concentration data were calculated from the output from the PNW SPARROW model clipped to the Puget 

Sound Basin. The data for proportion of nutrient attenuation and vf are based on the 535 reaches of the aggregated hydrologic model. 
22 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

vf Attenuation Model

The second watershed attenuation model used was the vf

model. This model was first developed as a generic expression 

for describing the effects of hydrologic variability on nutrient 

attenuation measured from nutrient spiraling metrics (Doyle, 

2005) and has been used by several researchers for describing 

attenuation in watersheds throughout the United States and 

Spain (Wollheim and others, 2006; Mulholland and others, 

2008; Helton and others, 2011; Aguilera and others, 2013). The 

vf model defines attenuation (the same as the RivR-N model) 

as the amount of nutrients removed as a fraction of total reach 

inputs (R) by:

R = 1 – exp(-vf/HL) (6)

where

HL is the hydraulic load and 

vf is the nutrient uptake velocity. 

The uptake velocity is equivalent to a mass transfer coefficient 

and represents how efficient a given reach is at taking up 

(retaining) nutrients. As vf increases, the capacity of a stream to 

retain nutrients also increases. Furthermore, vf is independent 

of river size in benthic dominated systems (Wollheim and 

others, 2006) making it an ideal biological parameter for 

estimating nutrient attenuation. As a result, the vf model 

incorporates biological factors of nutrient attenuation through 

vf and the hydrologic condition of the stream channel through 

HL. The vf model was derived beginning with two assumptions 

about nutrient spiraling: attenuation follows first order 

exponential decay along a reach, and nutrient transport is 

minimally influenced by dispersion and transient storage and 

is a generic expression that can be applied to any watershed.

The vf model for attenuation was applied to the same 

hydrologic network described for the RivR-N model above and 

HL was calculated the same way. To parameterize the vf model 

fully, segment-scale estimates of vf are needed for each nutrient 

being studied. To date (2015), there are no known estimates of 

vf for streams and rivers in the Puget Sound Basin. However, 

Mulholland and others (2008) calculated NO3

−

 uptake 

across 72 streams in the United States and showed that vf for 

denitrification was a function of stream NO3

−

 concentration 

(range was 0.001 to 21.2 milligrams of nitrogen per liter 

[mg N/L]). The general expression relating vf to nutrient 

concentration (Helton and others, 2011) is:

vf = aCb (7)

where 

C is nutrient concentration (either NO3

−

 or

 (PO 4

−3

), and

a and b are fitted by plotting vf values calculated 

from field experiments to surface water 

concentrations during the time of each 

field experiment and these coefficients are 

dependent on study area. 

The expression given by equation 7 allows for “biologic 

saturation” of nutrient attenuation at high concentration 

values, which has been shown to occur in various small stream 

types (pool/riffle, channelized reaches, reference, agricultural, 

and urban land uses) (Dodds and others, 2002; Mulholland 

and others, 2008).

Aguilera and others (2013) derived equations for vf for 

NO3

−

 and PO 4

−3

 based on a review of the scientific literature. In 

that study, the authors compiled data for measured vf values 

and concentrations for NO3

−

 and PO 4

−3

from a wide variety of 

small streams across the United States located in reference, 

agricultural, and urban watersheds, and focused on studies that 

used stable isotopes or mass balances in order to focus on net 

retention of nutrients. Aguilera and others (2013) purposely 

omitted short-term nutrient addition studies because they tend 

to focus on gross attenuation, not net attenuation. Their review 

of the scientific literature included more than 100 studies of 

NO3

−

 retention (concentration range from 0.001 to greater 

than 10 mg N/L) and more than 60 studies of PO 4

−3

 retention 

(concentration range from 0.001 to greater than 10 milligrams 

of phosphorus per liter [mg P/L]) to derive the following 

relations between vf and nutrient concentration:

vf

N = 0.41[NO3-

]-0.39 (8)

vf

P

 = 0.25[PO4

-

]-0.11 (9)

where 

vf is in units of millimeters per minute and 

concentration in units of milligrams per 

liter. 

No data from Puget Sound streams were included in the 

formulation of equations 8 and 9; however, several sites in 

western Oregon that ranged from pristine forested reaches 

to highly urbanized reaches were included. Because the 

range in concentrations represented in equations 8 and 9 

encompasses the values of nutrients measured in Puget Sound 

(Embrey and Inkpen, 1998; Ebbert and other, 2000), we 

determined that for this first level analysis they are applicable 

to Puget Sound streams as well. Some differences from these 

equations and Puget Sound sites are expected in larger rivers 

where interactions between groundwater and surface water 

might be minimal. Equations 8 and 9 were used to estimate 

segment-scale vf values for each reach in the Puget Sound 

hydrologic network through a multistep process. 

Using the results from a recently published total N (TN) 

and total P (TP) SPARROW model for the PNW, specific 

results for mean annual TN and TP loads were extracted 

from Wise and Johnson (2013) output files (Daniel Wise, 

U.S. Geological Survey, written commun., 2014) for the 

535 river segments of the Puget Sound hydrologic network. 

SPARROW is a watershed statistical model that uses 

comprehensive input datasets for water quality, watershed 

characteristics, and total watershed (terrestrial) nutrient 
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 23

inputs to simulate instream nutrient loads for each segment 

of a model river network (Smith and others, 1997). For the 

PNW SPARROW model, the river network was defined using 

the NHD (Horizon Systems Corporation, 2012) and the 

mean annual discharge and reach-scale TN or TP load from 

SPARROW output was compiled for the 535 segments in the 

river network. These mean annual TN and TP loads then 

were converted into mean annual TN and TP concentrations 

by dividing the loads by the mean annual discharge from the 

NHD for each modeled reach. The discharge values given by 

the NHD are long-term mean annual flow estimates adjusted 

to long-term (1971–2000) mean annual discharge values 

measured at USGS streamgages. Therefore, the discharge 

values represent the average values between 1971 and 2000 

(Horizon Systems Corporation, 2012). The NHD discharge 

values were selected instead of discharge values from the areaflow regression used previously (fig. 6) because the NHD data 

were used to model the nutrient load and the same discharge 

values were needed to convert from load to concentration for 

consistency with how these data were produced. Reach-scale 

estimates of TN and TP concentrations were converted to 

NO3

−

 and PO 4

−3

 concentrations using simple linear regressions 

between TN and NO3

−

 and TP and PO 4

−3

 concentrations 

from historical water-quality data for Puget Sound available 

from the USGS NWIS database. The regression equations 

were developed with the intercept set at zero. A statistically 

significant relation between TN and NO3

−

 from the USGS 

NWIS database was developed for 197 measurements for 

streams in the Puget Sound Basin between 2003 and 2011. 

Those observations with values less than the detection 

limit of 0.01 mg N/L were not used in the analysis. The N 

analysis resulted in the following model: NO3

−

, mg/L = 0.76 

(total N, mg/L) (R2 = 0.96; p<0.0001) (fig. 9A). A relation 

between TP and ortho-P was also developed using data from 

the NWIS database. The P model used 322 observations 

and, like the N model, data less than the detection limits 

(typically 0.01 mg P/L) were excluded. Sites in the database 

that were tidally influenced or that were dramatically altered 

hydraulically (that is, diversion canals, outlets from dams) 

were eliminated from the analysis because of the way these 

systems influence sediment and therefore sediment bound  P. 

The P analysis resulted in the following model: PO 4

−3

, 

mg/L = 0.40 (total P, mg/L) (R2 = 0.76; p<0.0001) (fig. 9B). 

The P analysis did exhibit heteroscedasticity (fig. 9B), and 

although this can result in a biased estimate of the standard 

error for a coefficient, it does not result in a biased estimate of 

the coefficient itself. This limitation was viewed as acceptable 

for the exploratory and hypothetical analysis done for this 

study. After these reach-level estimates of mean annual NO3

−

and PO 4

−3

concentrations were calculated, equations 8 and 9 

were used to calculate the respective vf value and the relative 

attenuation value (equation 6) for each reach in the Puget 

Sound hydrologic network.

Summary statistics of the modeled nutrient 

concentrations from SPARROW used to calculate NO3

−

 and 

PO 4

−3

 vf values are given in table 3 and are within the range 

of observed values for Puget Sound (Embrey and Inkpen, 

1998). This indicates that the method for estimating instream 

concentrations of NO3

−

 and PO 4

−3

 is producing reasonable 

concentration data. Values of vf calculated for NO3

−

 ranged 

from 0.02 to 2.2 mm/min and for PO 4

−3

 0.15 to 0.50 mm/min 

(table 3); both ranges were within the ranges found in the 

literature, but tended to be on the lower end of those ranges 

(Ensign and Doyle, 2006; Aguilera and others, 2013).

It should be noted that the coefficients used to describe 

attenuation in the PNW SPARROW model were not significant 

explanatory variables of nutrient load (Wise and Johnson, 

2013). These results should not be used to assume attenuation 

is not occurring in Puget Sound streams and rivers. Rather, 

it is possible that the available input data or the expression 

used to characterize attenuation in the SPARROW model 

were temporally, spatially, or conceptually inadequate to 

characterize this process. Additionally, the SPARROW model 

is not optimized for Puget Sound, but rather the entire 

PNW, so although attenuation was not significant across 

this entire region, it still may be a factor within the smaller 

Puget Sound region.

Results from the vf model of attenuation for NO3

−

 had 

some features similar to the RivR-N model for NO3

−

, but also 

exhibited some differences (figs. 7 and 10). For NO3

−, the 

highest relative attenuation per kilometer of stream length 

(>4 percent of nitrate inputs attenuated) was in the headwaters 

of almost all the major rivers. The main stems and mouths 

of most major rivers consistently showed the least amount of 

relative attenuation (< 2 percent of NO3

− inputs attenuated, 

fig. 10) throughout the Puget Sound Basin. The major rivers of 

the Olympic Peninsula in the western Puget Sound Basin, also 

show higher relative attenuation throughout their watersheds 

than basins draining the Cascade Range in the eastern 

Puget Sound Basin. Watersheds on the Olympic Peninsula 

tend to have lower nutrient concentrations, lower mean annual 

discharge, and wider shallow channels than more populous 

basins that tend to have higher nutrient loads and channel 

simplifications from developed land uses. The relative NO3

−

attenuation per kilometer ranged from 0.03 to 31.8 percent 

with a median of 2.7 percent, and the distribution showed 

that the maximum relative attenuation value was an anomaly 

(fig. 11). Without this one high value, the range of relative NO3

−

attenuation ranged from 0.03 to 15.5 percent of inputs to the 

reach per kilometer. 

For PO 4

−3

, the patterns of relative attenuation 

per kilometer of stream length are similar to patterns 

for NO3

−

. Relative attenuation tended to be high in 

headwater reaches and low in the main stem and mouths 

of the major rivers (fig. 12). Only a few reaches (15 of 489) 

show relative attenuation greater than 4 percent per kilometer 

of stream reach. Reaches having the lowest relative attenuation 

are (< 2 percent of inputs removed per kilometer) much 

more pervasive for PO 4

−3

 than for NO3

−

. This might be an 

artifact of the vf model for PO 4

−3

, which is based on a biologic 

removal of P and might not fully incorporate P attenuation 

related to sedimentation of P bound to suspended sediment. 
24 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

tac15-0989_fig09ab

R2 = 0.96; p<0.0001 

2.5

2.0

1.5

1.0

0.5

0.0

Nitrate , in milligrams per liter

0.0 0.5 1.0 1.5 2.0 2.5 3.0

Total nitrogen, in milligrams per liter

0.005 0.030 0.055 0.080 0.105 0.130 0.155 0.180

Total phosphorus, in milligrams per liter

0.00

0.02

0.04

0.06

Orthophosphate, in milligrams per liter

A

B

R2 = 0.76; p<0.0001

Figure 9. Relation between total and dissolved nutrient concentrations for (A) total nitrogen 

and nitrate and (B) total phosphorus and orthophosphate for data compiled from the U.S. 

Geological Survey National Water Information System, Puget Sound Basin, Washington.
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 25

tac15-0989_fig010

EXPLANATION

Nitrate input removed per

kilometer, in percent

Not applicable

< 2

2 – 3

3 – 4

> 4

Puget Sound Basin

KING

LEWIS

YAKIMA

CLALLAM

CHELAN

SKAGIT

PIERCE

WHATCOM

KITTITAS

JEFFERSON

SNOHOMISH

PACIFIC

MASON

GRAYS HARBOR

COWLITZ

KITSAP

OKANOGAN

ISLAND

THURSTON

SKAMANIA

SAN JUAN

WAHKIAKUM

125° 124° 123° 122° 121°

49°

48°

47°

0 12.5 25 50 MILES

0 12.5 25 50 KILOMETERS

Base from U.S. Geological Survey digital data, 1:100,000

Transverse Mercator projection: NAD 1983 UTM Zone 10N

Puget Sound

Admiralty

Inlet

Skagit R

Green R

Puyallup R

Cedar R

Deschutes R

Nisqually R

Duckabush R

Samish R

Dungeness R

Elwha R

Hamma

Hamma R

Nooksack R

Dosewalips R

Snohomish R

Stillaguamish R

Duwamish R

Skokomish R

Big

Quilcene R

Commencement

Bay

Elliott

Bay

BRITISH COLUMBIA, CANADA

WASHINGTON STATE

Figure 10. Relative instream attenuation expressed as the percentage of nitrate inputs removed per kilometer of stream length 

based on the vf model, Puget Sound Basin, Washington. The relative instream attenuation values for each reach are shown 

spatially by applying these values to their incremental contributing drainage area and do not represent watershed attenuation. 

Gray areas represent areas of the Puget Sound lowlands that do not include a major river. White areas are reaches where a nitrate 

concentration could not be calculated.
26 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

tac15-0989_fig11

0 4 8 12 16 20 24 28 32

0

0.05

0.10

0.15

Frequency of detection

Nitrate removed per kilometer based on vf model, in percent Nitrate removed per kilometer based on vf model, in percent

x

0.5

5

50 492

492 number of values 

EXPLANATION 

Schematic boxplot

x

x

o

o

upper adjacent

75th percentile

median

25th percentile

lower adjacent

lower outside

lower detached

upper detached

upper outside

NO3.Vf.Atten

Figure 11. Relative instream attenuation based on the fraction of nitrate removed per kilometer of stream 

length using the vf model, Puget Sound Basin, Washington.
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 27

tac15-0989_fig12

Orthophosphate inputs removed 

per kilometer, in percent

Not applicable

< 2

2 – 3

3 – 4

> 4

Puget Sound Basin

EXPLANATION

KING

LEWIS

YAKIMA

CLALLAM

CHELAN

SKAGIT

PIERCE

WHATCOM

KITTITAS

JEFFERSON

SNOHOMISH

PACIFIC

MASON

GRAYS HARBOR

COWLITZ

KITSAP

OKANOGAN

ISLAND

THURSTON

SKAMANIA

SAN JUAN

WAHKIAKUM

125° 124° 123° 122° 121°

49°

48°

47°

0 12.5 25 50 MILES

0 12.5 25 50 KILOMETERS

Base from U.S. Geological Survey digital data, 1:100,000

Transverse Mercator projection: NAD 1983 UTM Zone 10N

Puget Sound

Admiralty

Inlet

Skagit R

Green R

Puyallup R

Cedar R

Deschutes R

Nisqually R

Duckabush R

Samish R

Dungeness R

Elwha R

Hamma

Hamma R

Nooksack R

Dosewalips R

Snohomish R

Stillaguamish R

Duwamish R

Skokomish R

Big

Quilcene R

Commencement

Bay

Elliott

Bay

BRITISH COLUMBIA, CANADA

WASHINGTON STATE

Figure 12. Relative orthophosphate attenuation represented by the percentage of orthophosphate inputs removed per kilometer 

of stream length based on the vf model, Puget Sound Basin, Washington. The instream orthophosphate attenuation values for each 

reach are shown spatially by applying these values to their incremental contributing drainage area and do not represent watershed 

attenuation. Gray areas represent areas of the Puget Sound lowlands that do not include a major river. White areas (values not 

applicable) are reaches where an orthophosphate concentration could be calculated.
28 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

0.00

0.05

0.10

0.15

Frequency of detection

Orthophosphate removed per kilometer based on vf model, in percent

Orthophosphate removed per kilometer based 

on vf model, in percent

0 1 2 3 4 5 6 7 8 9 10

x

x

o

x

0.1

1

10

100

489 489 number of values 

EXPLANATION 

Schematic boxplot

x

x

o

upper adjacent

75th percentile

median

25th percentile

lower adjacent

lower outside

upper detached

upper outside

PO4.Vf.Atten

Figure 13. Calculated relative instream attenuation based on the fraction of orthophosphate removed per 

kilometer of stream length using the vf model, Puget Sound Basin, Washington.

Additionally, the range of vf values calculated for PO 4

−3

(0.15 to 0.50 mm/min; table 3) is small and is on the low end 

of the range in values summarized elsewhere (Ensign and 

Doyle, 2006; Aguilera and others, 2013) where vf for PO 4

−3

can be greater than 6 mm/min. The distribution of the PO 4

−3

attenuation was skewed toward the low end with a few high 

values, but most reaches showed less than 3 percent of inputs 

attenuated per kilometer (fig. 13).

Note that the attenuation categories presented in figures 7, 

10, and 12 were selected in order to be consistent across these 

figures and to facilitate comparisons between the two models 

and nutrient species (NO3

− and PO 4

−3

) being considered. 

The main reason for these analyses is to examine patterns of 

relative attenuation across the Puget Sound Basin and not to 

focus on the absolute values of reach-scale relative attenuation. 

These categories capture the range of data adequately; however, 

for relative NO3

− attenuation from the vf

 model, numerous 

reaches are greater than 4 percent of inputs attenuated per 

kilometer (fig. 11) and should be noted. Furthermore, it 

is important to note that the values presented represent 

reach-level attenuation per kilometer and not the cumulative 

attenuation of the entire river basin, which would be greater.
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 29

Comparison of Relative Nitrate 

Attenuation Models

Two approaches were used for estimating relative NO3

−

attenuation for the Puget Sound Basin: the RivR-N and vf

models. Both of these models estimate NO3

−

 loss from similar 

processes, namely denitrification, and a comparison of the 

output for these two models is provided in figure 14. Positive 

values in figure 14 indicate that more attenuation is being 

predicted by the NO3

−

 vf model and this comparison shows that 

in almost all cases, relative NO3

−

 attenuation is greater when 

using the vf model. These differences are highest in headwater 

reaches for all the major river basins. However, in many of 

the lower main stem reaches, relative NO3

−

 attenuation from 

RivR-N model is greater, as indicated by the negative values. 

The RivR-N model is based solely on physical (hydrological) 

characteristics of a given stream or river reach, whereas the 

vf model incorporates not only physical but also biological 

characteristics of attenuation. If error from these two 

approaches is assumed to be similar, the differences between 

these two models may indicate areas where hydrologic and 

biologic factors are most important. For example, in headwater 

reaches, the vf model predicts much higher relative attenuation 

compared to main stems of rivers indicating that biological 

factors in these small channels may be more important 

(Ensign and Doyle, 2006). In contrast, in lower gradient, large 

channels of the main stem reaches, hydrologic (physical) 

factors may play a larger role on instream attenuation of NO3

−

(Tank and others, 2008). However, comparing these two 

models is not without limitations because the assumptions 

and error associated with each model are likely different. 

This comparison does begin to indicate where physical and 

biological factors may be important, however, and warrants 

further investigation.

Development of a Framework for Ranking 

Stream Reach Attenuation

Although the RivR-N and vf models worked well for 

identifying locations in the Puget Sound Basin, where relative 

attenuation is high or low, specific data were lacking for some 

of the parameters. For example, no site-specific values of vf

were available for Puget Sound stream reaches and generalized 

empirical relations (from other studies) were used to estimate 

vf. Estimating other hydraulic parameters at the segment 

scale currently is the only way to calculate HL for all reaches. 

Because of these limitations, a stream and river attenuation 

rating tool, or scorecard, was developed based on four primary 

factors of attenuation that can be used to quickly assess the 

potential for NO3

−

 or PO 4

−3

 attenuation in a given reach.

Generally, nutrient removal in aquatic systems is a 

function of (1) the amount of biogeochemical activity, (2) the 

proportion of nutrient mass exposed to biogeochemically 

active surfaces, and (3) the duration of exposure between 

nutrients and these active surfaces. These three conditions can 

be represented by measurable parameters in stream and river 

reaches. Firstly, the value of vf is a function of the strength of 

biogeochemical activity of a reach, it is minimally influenced 

by hydrology, and a robust metric to compare uptake efficiency 

across sites (Davis and Minshall, 1999). Secondly, the 

proportion of flow, and therefore proportion of nutrient load, 

in contact with the streambed is related to specific discharge 

(Q/w) or the width to depth ratio (w:d) of the channel and is 

shown to be related to NO3

−

 retention (Lautz and Siegel, 2007; 

Hall and others, 2009; Hensley and others, 2014; Sheibley 

and others, 2014). Lastly, the duration of exposure of flow to 

biologically active surfaces can be related to travel time and 

degree of transient storage in the reach, which is related to 

features such as reach slope and sinuosity (Gooseff and others, 

2007; Boano and others, 2014). Therefore, four primary factors 

of nutrient attenuation are proposed: vf, specific discharge 

(Q/w), channel slope, and channel sinuosity. These factors 

can be used to score Puget Sound reaches into five categories 

to illustrate the combined potential effect of these factors on 

instream nutrient attenuation. Based on professional judgment 

and data summarized from the literature, each of these factors 

was given a value (a breakpoint) to split the data into two bins, 

one for low attenuation potential and one for high attenuation 

potential. Using a score of 0 for the low bin and 1 for the high 

bin for each of these four factors, each reach in the hydrologic 

network was given a cumulative score that would range from 

0 (least potential for attenuation) to 4 (highest potential 

for attenuation).

To rank reaches based on the amount of biological 

activity, vf data from a recent study that complied data from 

hundreds of nutrient spiraling studies for first through fifth 

order streams (Ensign and Doyle, 2006) were used as a guide. 

Small streams (first and second order) tend to have higher 

attenuation than large streams (fourth and fifth order) and are 

associated with median values of vf for NO3

−

 and PO 4

−3

 that 

are typically greater than 1.0 and 2.0 mm/min, respectively 

(Ensign and Doyle, 2006). Therefore, the breakpoints for vf

were assigned these values (table 4).

Discharge per unit channel width (Q/w), or specific 

discharge, indicates the contact area between water 

transporting nutrients and the river bed. Rivers with high 

width-to-depth ratios have low streamflow per unit area 

and allow more contact between streamflow and the river 

bed. Previous studies have shown that as Q/w decreases, 

nutrient attenuation increases (Hall and others, 2002; Lautz 

and Siegel, 2007; Hall and others, 2009; Hensley and others, 

2014); however, there is not a clear threshold for Q/w from 

these studies where attenuation transitions from low to high. 

Therefore, to divide the reaches into approximately equal bins, 

the mean value of Q/w (0.5 cubic meter per second per meter 

([m3/s]/m) was used as the breakpoint for the 535 reaches in 

the Puget Sound hydrologic network (table 4).
30 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

tac15-0989_fig14

Nitrate inputs removed per 

kilometer, in percent

Not applicable

< 0 

0 – 1 

1 – 2 

> 2 

Puget Sound Basin

EXPLANATION

KING

LEWIS

YAKIMA

CLALLAM

CHELAN

SKAGIT

PIERCE

WHATCOM

KITTITAS

JEFFERSON

SNOHOMISH

PACIFIC

MASON

GRAYS HARBOR

COWLITZ

KITSAP

OKANOGAN

ISLAND

THURSTON

SKAMANIA

SAN JUAN

WAHKIAKUM

125° 124° 123° 122° 121°

49°

48°

47°

0 12.5 25 50 MILES

0 12.5 25 50 KILOMETERS

Base from U.S. Geological Survey digital data, 1:100,000

Transverse Mercator projection: NAD 1983 UTM Zone 10N

Puget Sound

Admiralty

Inlet

Skagit R

Green R

Puyallup R

Cedar R

Deschutes R

Nisqually R

Duckabush R

Samish R

Dungeness R

Elwha R

Hamma

Hamma R

Nooksack R

Dosewalips R

Snohomish R

Stillaguamish R

Duwamish R

Skokomish R

Big

Quilcene R

Commencement

Bay

Elliott

Bay

BRITISH COLUMBIA, CANADA

WASHINGTON STATE

Figure 14. Differences of relative nitrate attenuation of reaches in the hydrologic network between the vf and RivR-N models for 

nitrate, Puget Sound Basin, Washington. Positive values indicate greater attenuation from the vf model.
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 31

Table 4. Primary factors related to nutrient attenuation and criteria corresponding to a score of 1 for a given river segment.

[Abbreviations: (m3/s)/m, cubic meter per second per meter; m/m, meter per meter; mm/min, millimeter per minute; >, greater than; <, less than]

Specific 

discharge

[(m3/s)/m]

Sinuosity

(m/m)

Slope

(m/m)

Uptake velocity

(mm/min)

Nitrogen Phosphorus Nitrogen Phosphorus

Criteria <0.5 >1.2 >0.005 <0.005 >1.0 >2.0

Number or river segments scoring 

a value of 1

249 334 361 174 213 0

The water-surface gradient, or channel slope, indicates 

the energy available to force hyporheic flow and to transport 

sediment. In this case, NO3

− attenuation is likely to be higher 

in high gradient rivers (all other factors equal), whereas PO 4

−3

retention is likely to be higher in low gradient rivers through 

increased sedimentation of sediment-bound P. A threshold 

gradient of 0.005 was used to differentiate between low and 

high gradient river segments across the Puget Sound Basin 

based on studies by Beechie and others (2006); therefore, 0.005 

was used as the breakpoint for scoring the reaches (table 4).

Sinuosity, which is the ratio of the path length to straight 

line length of river segment, indicates longer travel times 

through a segment, pool-riffle morphology, and presence 

of point bars. Hyporheic flow is associated with pool-riffle 

morphology and point bars and is caused by changes in 

localized vertical hydraulic gradients. A sinuosity of 1.2 

generally is used to distinguish sinuous channels from straight 

channels (Knighton, 1998); therefore, 1.2 was used as the 

breakpoint for this factor in the analysis (table 4).

Values for vf, NO3

−

, and PO 4

−3

 for each river segment were 

the same data used for the vf model (see section vf attenuation 

model). The Q/w for each reach was calculated from the mean 

annual discharge for each reach used in the RivR-N and vf

models (derived from fig. 6) and GIS-based measurements of 

average channel width (w) that were based on high-resolution 

elevation data (Konrad, 2015). Average channel width from 

Konrad (2015) was used instead of estimating width using 

equation 5 (Magirl and Olsen, 2009) because the former 

represented more accurate representation of field conditions. 

However, the widths from Konrad (2015) were not available 

for approximately 200 of the 535 river segments, which limited 

the ability to score this factor across all reaches of the river 

network. Despite this limitation, it was determined that using 

fewer but more-accurate data was warranted and strengthened 

the scoring analysis. Data for channel slope (water-surface 

gradient) and sinuosity for the 535 reaches of the river network 

were derived as part of a geospatial assessment of flood 

plains along major rivers in the Puget Sound Basin (Konrad, 

2015). Surface-water gradient was used as a proxy for channel 

slope and was calculated by the change in surface-water 

elevation extrapolated from the National Elevation Dataset 

(U.S. Geological Survey, 2012) from the top and bottom of 

each river segment (Konrad, 2015). Sinuosity was calculated 

by measuring the length of each river segment divided by the 

straight-line distance between the endpoints of the segment 

(Konrad, 2015).

For NO3

−

 attenuation, 328 of the 535 reaches (fig. 15) 

could be scored, and 207 reaches lacked at least one of the 

four factors needed to fully score the reach. Only a handful 

of reaches (25 of 328) scored the highest value of four, 

indicating the greatest attenuation potential. These reaches 

were in locations similar to reaches with high calculated 

relative attenuation from the RivR-N and vf models, namely, in 

headwater reaches of the major river basins. Reaches scoring 

a four indicate that biological activity likely is high (vf for 

NO3

−

 greater than 1.0 mm/min), have steep gradients, sinuous 

channels, and a high proportion of surface water in contact 

with streambed sediments. Most reaches scored in the middle 

with 213 reaches scoring either a two or three, indicating a 

moderate potential for NO3

−

 attenuation. Only 19 reaches 

scored a zero and were usually located on areas of the main 

stems of larger rivers, which indicated that the primary factors 

needed for attenuation were not sufficient. This does not 

necessarily mean that no attenuation is occurring in these 

reaches, but the potential for attenuation is low.
32 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

tac15-0989_fig15

Total nitrate attenuation score

Not applicable

0

1

2

3

4

Puget Sound Basin

EXPLANATION

KING

LEWIS

YAKIMA

CLALLAM

CHELAN

SKAGIT

PIERCE

WHATCOM

KITTITAS

JEFFERSON

SNOHOMISH

PACIFIC

MASON

GRAYS HARBOR

COWLITZ

KITSAP

OKANOGAN

ISLAND

THURSTON

SKAMANIA

SAN JUAN

WAHKIAKUM

125° 124° 123° 122° 121°

49°

48°

47°

0 12.5 25 50 MILES

0 12.5 25 50 KILOMETERS

Base from U.S. Geological Survey digital data, 1:100,000

Transverse Mercator projection: NAD 1983 UTM Zone 10N

Puget Sound

Admiralty

Inlet

Skagit R

Green R

Puyallup R

Cedar R

Deschutes R

Nisqually R

Duckabush R

Samish R

Dungeness R

Elwha R

Hamma

Hamma R

Nooksack R

Dosewalips R

Snohomish R

Stillaguamish R

Duwamish R

Skokomish R

Big

Quilcene R

Commencement

Bay

Elliott

Bay

BRITISH COLUMBIA, CANADA

WASHINGTON STATE

Figure 15. Total nitrate attenuation scores in streams and rivers, Puget Sound Basin, Washington.
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 33

For PO 4

−3

 attenuation, 327 of the 535 reaches could be 

scored with 208 reaches missing data for at least one of the 

four factors (fig. 16). The most interesting result for the PO 4

−3

scoring was that no reach scored a total of four because none 

of the reaches had a PO 4

−3

 vf value greater than the breakpoint 

of 2.0 mm/min. This may indicate that reaches in the Puget 

Sound Basin are not efficient at biological P removal relative 

to data summarized in the literature. However, the accuracy 

of the method used to calculate vf for PO 4

−3

 is uncertain. Of 

the 327 reaches, 55 reaches scored a three, and were spread 

throughout the major river basins (fig. 16). There tended to 

be more high scores for PO 4

−3

 compared to NO3

−

 in main stem 

reaches, likely a result of lower slopes and increased potential 

for sedimentation. A total of 261 of the 328 reaches scored 

a one or two, which indicates that this scoring procedure 

ranks many reaches in the Puget Sound Basin low for 

potential PO 4

−3

 attenuation. This does not necessarily mean 

PO 4

−3

 potential in Puget Sound rivers is not important, but 

might indicate that a different set of factors would describe 

potential PO 4

−3

 attenuation better if there were limitations in 

scoring vf for PO 4

−3

 from the inconsistent variance structure 

(heteroscedasticity) in the regression equation used to 

calculate PO 4

−3

 from TP (fig. 9B). The distribution of scores in 

the Puget Sound Basin for each attenuation factor individually 

is provided in appendix B. 

Many similarities were noted in the patterns of NO3

−

 and 

PO 4

−3

 attenuation when comparing the reach scores (figs. 15

and 16) to the results from the RivR-N and two vf models 

(figs. 7, 10, and 12). The relative attenuation values calculated 

using the RivR-N and vf models were compared to the scores 

generated from the ranking approach. The comparison 

indicated that the scoring procedure accurately identified 

reaches with high and low attenuation potential (fig. 17). For 

the RivR-N and NO3

−

 vf models, median relative attenuation 

increased as reach scores increased and this relation is 

stronger for the vf model (fig. 17B) than the RivR-N model 

(fig. 17A). However, for PO 4

−3

, the relation between the relative 

attenuation and reach score was not as obvious (fig. 17C), 

indicating that the scoring procedure is not as effective for 

PO 4

−3

, or that other factors are more important for describing 

PO 4

−3

 attenuation that were not included in the ranking.

Temporal Effects of Nutrient Attenuation

The analysis of relative nutrient attenuation was 

focused on using average annual discharges and nutrient 

concentrations for the hydrologic network. However, 

hydrologic conditions and nutrient concentrations can change 

dramatically during the year which, in turn, will influence 

the amount of nutrient attenuation. Therefore, to evaluate the 

temporal variability of changes in flow and concentration on 

relative nutrient attenuation, the vf model was examined in 

more detail for three case studies using sites with long-term 

USGS water-quality data in the Puget Sound Basin. An 

intermediate sized, high-gradient reference stream (North 

Fork Skokomish), a small sized, low-gradient urban stream 

(Thornton Creek), and large sized, low-gradient river in the 

north Puget lowlands (Nooksack River) were selected. These 

three sites were selected to span a range of both hydrologic 

(discharge, channel width) and nutrient (concentration) 

characteristics.

The North Fork Skokomish River site is in the Olympic 

National Park. It is a high-gradient, forested site with a range of 

substrate sizes, but generally is dominated by cobble and small 

boulders. The North Fork Skokomish River drains an area of 

57.2 mi2 and is located entirely within the Olympic National 

Park. The high-flow period is typically from October through 

January. The transition period, from February through July, 

is a time of generally lower streamflows than in winter and 

diminishing flows during summer. The low-flow period 

is from August through September. Mean daily discharge, 

based on 89 years of record, are 673 ft3/s with a maximum of 

9,980 ft3/s in 1956 and a minimum of 37 ft3/s in 1937. Based 

on previous studies, the highest concentrations of TN, TP, and 

suspended sediment tended to occur during the high-flow 

period (Embrey and Frans, 2003). Median NO3

−

 concentrations 

from 1996 to 2014 were 0.05 μg/L and ranged from less than 

the detection limit of 0.05 μg/L to 0.17 μg/L. Orthophosphate 

concentrations from 1996 to 2014 often were less than the 

detection limit of 0.01 μg/L and ranged to 0.06 μg/L with a 

median of <0.01 μg/L (Ebbert and others, 2000; Embrey and 

Frans, 2003).

The Thornton Creek site is in a subbasin of the Lake 

Washington drainage and entirely within the Puget Sound 

lowlands physiographic province. Population density in the 

basin is high, on the order of 600–1,000 people per square 

mile, an example of a fully developed urban basin. It is largely 

residential, but includes large shopping malls and commercial 

development and an interstate freeway that bisects the basin. 

The creek drains an area of 12.1 mi2. Its substrate is dominated 

by silts and sands with some gravels. Mean annual discharge 

is about 9.6 ft3/s from 1996 to 2013. Low flows occur in the 

summer and high flows occur during late autumn through 

spring, with periodic storm-related high flows. Historical 

water-quality sampling of this site has detected elevated 

concentrations of numerous chemicals. Nitrate concentration 

ranged from 0.42 to 1.70 mg/L with a median of 1.3 mg/L 

from 1996 to 2011. During this same period, the median 

concentration of PO 4

−3

 was 0.03 mg/L and ranged from less 

than the detection limit of 0.01 mg/L to 0.3 mg/L (Ebbert and 

others, 2000; Embrey and Frans, 2003). 
34 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

tac15-0989_fig16

Total orthophosphate 

attenuation score

Not applicable

0

1

2

3

Puget Sound Basin

EXPLANATION

KING

LEWIS

YAKIMA

CLALLAM

CHELAN

SKAGIT

PIERCE

WHATCOM

KITTITAS

JEFFERSON

SNOHOMISH

PACIFIC

MASON

GRAYS HARBOR

COWLITZ

KITSAP

OKANOGAN

ISLAND

THURSTON

SKAMANIA

SAN JUAN

WAHKIAKUM

125° 124° 123° 122° 121°

49°

48°

47°

0 12.5 25 50 MILES

0 12.5 25 50 KILOMETERS

Base from U.S. Geological Survey digital data, 1:100,000

Transverse Mercator projection: NAD 1983 UTM Zone 10N

Puget Sound

Admiralty

Inlet

Skagit R

Green R

Puyallup R

Cedar R

Deschutes R

Nisqually R

Duckabush R

Samish R

Dungeness R

Elwha R

Hamma

Hamma R

Nooksack R

Dosewalips R

Snohomish R

Stillaguamish R

Duwamish R

Skokomish R

Big

Quilcene R

Commencement

Bay

Elliott

Bay

BRITISH COLUMBIA, CANADA

WASHINGTON STATE

Figure 16. Total orthophosphate attenuation scores in streams and rivers, Puget Sound Basin, Washington.
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 35

tac15-0989_fig17ab

x

x

x

x

x

x

x

x

x

x

x

o

o

o

o

x

x

x

x

x

o

x

x

x

x x

x

x

19 71 100 113 25

Relative nitrate attenuation as a percentage of inputs per kilometer Relative nitrate attenuation from vf N model, as a percentage of inputs per kilometer

0 1 2 3 4

5

4

3

2

1

14

24

10

8

6

4

2

0

19 71 100 113 25

A

B

Relative vf attenuation score, nitrate

25 number of values 

EXPLANATION 

Schematic boxplot

x

x

o

o

upper adjacent

75th percentile

median

25th percentile

lower adjacent

lower outside

lower detached

upper detached

upper outside

Figure 17. Relation between relative nutrient attenuation and reach scores 

for the (A) RivR-N model, (B) vf nitrogen model, and (C) vf orthophosphate 

model, Puget Sound Basin, Washington.
36 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

tac15-0989_fig17c

x

x

x

x

x

x

o

8

6

4

2

0

11 101 160 55

Relative orthophosphate attenuation, as a percentage of inputs removed per kilometer

0 1 2 3

Relative vf attenuation score, orthophosphate

C

55 number of values 

EXPLANATION 

Schematic boxplot

x

x

o

o

upper adjacent

75th percentile

median

25th percentile

lower adjacent

lower outside

lower detached

upper detached

upper outside

The Nooksack River site at Ferndale drains an area of 

about 790 mi2 of a watershed dominated by forest practices 

in the headwaters (about 70 percent of the watershed) and 

agriculture and urbanization in the downstream portion of 

the watershed near the site. The river substrate is dominated 

by fines and gravels. Average daily discharges at the site based 

on USGS streamgage data (12213100) are 4,140 ft3/s, but 

have exceeded 20,000 ft3/s and have been as low as 593 ft3/s 

during the period of record (1986–2014). The dry season 

is generally during late summer; the highest flows typically 

occur in the spring, but can increase rapidly during storm 

events. Low-nutrient water from the mountain headwaters 

has an important influence on the water chemistry of the 

main stem Nooksack River and contributes to the dilution of 

high nutrient inputs to this river from urban and agricultural 

land uses in the watershed (fig. 2). At times, however, large 

volumes of runoff can result in high flows with large amounts 

of sediment and occasionally high concentrations of TP. 

Figure 17.—Continued

Historical samples collected at this site (from 1995 to 1998) 

have NO3

−

 concentrations ranging from 0.13 mg/L to a 

maximum of 0.92 mg/L, with a median of 0.35 mg/L (Ebbert 

and others, 2000; Embrey and Frans, 2003). Orthophosphate 

concentration ranged from less than the detection limit of 

0.01 mg/L to a maximum of 0.06 mg/L and a median of 

<0.01 mg/L during the same period. A summary of nutrient 

concentrations at these sites compared to the range reported 

for Puget Sound is presented in table 5.

Measured hydrologic parameters were downloaded from 

NWIS for a representative low- and high-flow condition at 

each site since 2000 (table 6) and used to calculate HL (Q/wL). 

Discharge, stream width, average depth, and cross sectional 

area are measured and reported whenever a manual discharge 

measurement is made and the average velocity was calculated 

by taking discharge divided by the cross sectional area. 
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 37

Table 5. Nutrient data for three study sites compared to nutrient data for Puget Sound Basin, Washington.

[Concentrations are in milligram per liter. –, not calculated; <, less than]

Site name Site No.

Nitrate Orthophosphate

Minimum Maximum Median Minimum Maximum Median

North Fork Skokomish River 12056500 <0.05 0.17 0.05 <0.01 0.06 <0.01

Thornton Creek 12128000 0.42 1.7 1.3 <0.01 0.3 0.03

Nooksack River at Ferndale 12213100 0.13 0.92 0.35 <0.01 0.06 0.01

Puget Sound Basin1 <0.05 7 – <0.01 1 –

1 From data summarized in Ebbert and others (2000) and Embrey and Frans (2003).

Table 6. Representative high- and low-flow conditions at the three case study sites to estimate nutrient attenuation, 

Puget Sound Basin, Washington.

[Abbreviations: ft3/s, cubic foot per second; ft2, foot squared;, ft, foot; ft/s, foot per second]

Site name Date Flow

category

Discharge

(ft3/s)

Cross

sectional 

area

(ft2)

Width

(ft)

Depth

(ft)

Uptake

rate

(ft/s)

North Fork Skokomish River 08-28-13 Low 140 88 136 0.6 0.9

11-14-01 High 2,450 466 107 4.4 4.6

Thornton Creek 07-19-11 Low 4 3 7 0.5 1.3

11-15-01 High 28 17 14 1.2 1.7

Nooksack River at Ferndale 10-29-13 Low 1,140 1,020 198 5.2 1.1

01-14-14 High 10,900 2,810 236 11.9 3.9

A standardized reach length (L) of 1,000 m was used to 

calculate HL in order to compute relative attenuation across 

these sites because measurements were made at a single 

locations within a much longer (and undefined) reach. 

Therefore, this analysis is consistent with the approach used 

previously when using the RivR-N and vf models. Values 

of vf for use in equation 6 were based on the concentration 

relations in equations 8 and 9 using the range of nutrient 

concentrations at each site and for the range in the Puget 

Sound Basin (table 5). For NO3

−

 and PO 4

−3

, relative attenuation 

was always higher during low-flow conditions compared to 

high-flow conditions even when concentrations were high 

(figs. 18 and 19). For NO3

−

, the slope of the relative attenuation 

curves approach zero at about 3 mg N/L indicating that at 

concentrations greater than 3 mg N/L, uptake in the reaches 

may be saturated and relative attenuation approaches a 

minimum (fig. 18). During high flow, relative NO3

−

 attenuation 

is minimal and the saturation point of attenuation is about 1 

mg N/L (fig. 18), much lower than during low-flow conditions. 

For PO 4

−3

, saturation of relative attenuation for both high- and 

low-flow conditions was similar and starts at about 0.1 mg P/L 

(fig. 19).

When relative retention is plotted for only the parts of 

each curve represented by the measured range in nutrient 

concentrations at each site, some interesting features are 

observed (figs. 20 and 21). The North Fork Skokomish 

relative NO3

−

 attenuation begins high and decreases rapidly 

as concentration increases for both the low and high flow 

conditions (fig. 20). The Nooksack relative NO3

−

 retention is 

fairly constant over the range of observed concentrations and 

always low for the low-and high-flow conditions. Thornton 

Creek shows small but not dramatic changes in relative 

retention over the range of observed concentrations. During 

low flow, relative NO3

−

 attenuation in Thornton Creek is 

in the middle of the other two sites, but shows the highest 

relative attenuation during high flow, probably because the 

difference in hydrologic conditions between low and high-flow 

conditions at this site are smaller than the other two sites 

(table 6). For relative PO 4

−3

 attenuation, North Fork Skokomish 

River and Thornton Creek were similar during low flow, but 

during high flow, relative attenuation was greater at Thornton 

Creek and the North Fork Skokomish River was negligible 

and similar to the Nooksack River. Relative PO 4

−3

 attenuation 

in the Nooksack River was always small and never exceeded 

1 percent of inputs attenuated per kilometer (fig. 21).
38 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

tac15-0989_fig18abc

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

4.0 

4.5 

0 1 2 3 4 5 6 7 8

Low flow

High flow 

EXPLANATION

Nitrate input removed per kilometer, in percent

Nitrate concentration, in milligrams of nitrite per liter

A

B

C

140 cubic feet per second

2,450 cubic feet per second

4.4 cubic feet per second

28 cubic feet per second

1,700 cubic feet per second

7,800 cubic feet per second

Figure 18. Relation between relative nitrate attenuation and nitrate 

concentration for representative high- and low-flow conditions at (A) North 

Fork Skokomish River, (B) Thornton Creek, and (C) Nooksack River at Ferndale, 

Washington. The nitrate concentration range on the x-axis represents the overall 

range detected in the Puget Sound Basin (Ebbert and others, 2000; Embrey and 

Frans, 2003).
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 39

Figure 19. Relation between relative orthophosphate attenuation and 

orthophosphate concentration for representative high- and low-flow conditions 

at (A) North Fork Skokomish, (B) Thornton Creek, and (C) Nooksack River at 

Ferndale, Washington. The orthophosphate concentration range on the x-axis 

represents the overall range detected in the Puget Sound Basin (Ebbert and 

others, 2000; Embrey and Frans, 2003).

tac15-0989_fig19abc

Low flow

High flow 

EXPLANATION

0 

2 

4 

6 

8 

10 

12 

14 

140 cubic feet per second

2,450 cubic feet per second

4.4 cubic feet per second

28 cubic feet per second

1,700 cubic feet per second

7,800 cubic feet per second

0 

2 

4 

6 

8 

10 

12 

14 

0.0 

0.2 

0.4 

0.6 

0.8 

1.0 

1.2 

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Orthophosphate concentration, in milligrams of phosphate per liter

Orthophosphate inputs removed per kilometer, in percent

A

B

C
40 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

tac15-0989_fig20ab

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

4.0 

4.5 

5.0 

0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0

Nitrate concentration, in milligrams of nitrite per liter

A

B

Nitrate inputs removed per kilometer, in percent

North Fork 

Skokomish River

Thornton Creek

Nooksack River

EXPLANATION

Figure 20. Relative nitrate attenuation and nitrate concentration for the range 

in nutrient concentrations for typical (A) low- and (B) high-flow conditions, 

North Fork Skokomish River, Thornton Creek, and Nooksack River near Ferndale, 

Washington.
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 41

tac15-0989_fig21ab

North Fork 

Skokomish River

Thornton Creek

Nooksack River

EXPLANATION

0 

2 

4 

6 

8 

10 

12 

14 

0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

4.0 

0 0.02 0.04 0.06 0.08 0.10 0.12

Orthophosphate inputs removed per kilometer, in percent

Orthophosphate concentration, in milligrams of phosphate per liter

A

B

Figure 21. Relative orthophosphate attenuation and orthophosphate 

concentration for the range in nutrient concentrations for typical (A) low- and (B) 

high-flow conditions, North Fork Skokomish River, Thornton Creek, and Nooksack 

River near Ferndale, Washington.
42 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

Seasonality of relative attenuation at these three sites 

was determined from field measured data downloaded from 

NWIS for discharge, stream width, and concentrations of 

NO3

−

 and PO 4

−3

 (tables 7 and 8), and summarized monthly to 

identify when attenuation is greatest during the course of a 

year. Because attenuation calculated by the vf model (equation 

6) varies with nutrient concentration and HL (Q/wL), monthly 

variability of relative attenuation was examined by (1) holding 

concentration constant at the monthly median value and using 

a the monthly range of hydrologic conditions and (2) holding 

Table 7. Discharge and stream width measures by month for the North Fork Skokomish River, Thornton Creek, and Nooksack River, 

Washington. 

[North Fork Skokomish, 178 observations from 1986 to 2014; Thornton Creek, 158 observations from 1996 to 2013; and Nooksack River, 177 observations from 

1987 to 2014. Abbreviations: ft, foot; ft3/s, cubic foot per second]

Site name Month

Discharge (ft3/s) Width (ft)

Minimum Maximum Median Mean Minimum Maximum Median Mean

North Fork Skokomish River Jan. 114 9,660 596 913 65 168 108 114

Feb. 133 3,500 446 576 64 179 105 103

Mar. 165 7,300 414 606 76 136 110 109

Apr. 172 3,940 461 543 56 165 118 115

May 231 2,760 585 665 56 140 125 107

June 169 2,380 502 574 62 176 107 109

July 84 2,460 253 341 78 128 100 102

Aug. 48 1,840 120 165 70 136 87 94

Sept. 40 2,870 82 139 70 112 78 83

Oct. 38 7,620 194 420 56 129 83 92

Nov. 39 5,440 555 900 81 140 111 111

Dec. 119 13,100 510 840 59 172 106 113

Thornton Creek Jan. 5.1 81.0 14.0 15.8 6.5 16.1 13.7 12.2

Feb. 4.4 42.0 10.0 12.1 7.0 17.4 12.7 12.3

Mar. 4.6 68.0 10.0 12.7 6.3 16.2 10.0 10.9

Apr. 4.3 55.0 8.3 10.2 6.9 17.5 10.0 11.0

May 3.5 45.0 6.8 8.2 5.9 16.4 12.0 11.4

June 0.8 38.0 5.1 6.2 6.4 18.0 7.9 10.5

July 2.2 24.0 3.9 4.6 5.2 15.3 9.4 9.9

Aug. 0.6 33.0 3.5 4.1 6.1 17.4 10.6 11.2

Sept. 0.4 39.0 4.2 5.5 7.4 16.7 11.7 11.6

Oct. 2.8 116.0 5.8 8.6 6.3 21.0 11.9 12.0

Nov. 3.8 104.0 9.5 13.5 7.0 21.5 14.3 13.7

Dec. 3.1 190.0 12.0 15.1 8.0 24.0 13.3 14.2

Nooksack River Jan. 1,570 47,500 4,230 5,557 203 395 236 256

Feb. 1,180 27,500 3,090 3,763 199 223 212 211

Mar. 1,170 33,700 3,195 4,123 206 256 218 223

Apr. 1,720 15,700 3,515 4,001 193 236 215 214

May 2,200 15,300 4,540 4,991 212 230 218 220

June 2,120 17,700 4,675 4,944 194 300 214 217

July 1,650 15,300 3,035 3,538 200 226 213 214

Aug. 852 10,700 1,810 2,080 190 308 205 208

Sept. 672 13,800 1,310 1,769 197 353 211 242

Oct. 565 32,300 2,030 3,080 180 293 212 215

Nov. 575 42,100 4,195 5,570 210 397 239 262

Dec. 1,200 32,300 3,790 4,830 200 279 217 220

hydrologic conditions constant at the monthly median value 

and using the monthly range of concentrations. This approach 

was used to examine the variability in monthly relative 

attenuation from all parameters. However, the variability of 

relative attenuation from hydrologic parameters was always 

greater than the variability from changes in monthly nutrient 

concentration. Therefore, only seasonal relative attenuation 

data based on the monthly range of hydrologic conditions at 

each site are presented.
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 43

Table 8. Nitrate and orthophosphorus data by month for the North Fork Skokomish River, Thornton Creek, and Nooksack River at 

Ferndale, Washington. 

[North Fork Skokomish, 87 observations from 1996 to 2014; Thornton Creek, 164 observations from 1996 to 2011; and Nooksack River, 41 observations from 

1995 to 1998. Abbreviatons: mg/L, milligram per liter]

Site name Month

Nitrate (mg/L) Orthophosphate (mg/L)

Minimum Maximum Median Mean Minimum Maximum Median Mean

North Fork Skokomish River Jan. 0.024 0.090 0.030 0.040 0.009 0.061 0.022 0.026

Feb. 0.025 0.147 0.034 0.068 0.006 0.034 0.016 0.020

Mar. 0.025 0.030 0.025 0.027 0.006 0.031 0.016 0.019

Apr. 0.021 0.100 0.030 0.046 0.006 0.028 0.016 0.014

May 0.025 0.058 0.030 0.035 0.006 0.055 0.016 0.020

June 0.005 0.087 0.030 0.033 0.006 0.031 0.016 0.020

July 0.023 0.070 0.030 0.033 0.009 0.037 0.023 0.021

Aug. 0.019 0.054 0.030 0.034 0.006 0.031 0.011 0.013

Sept. 0.025 0.090 0.032 0.042 0.009 0.031 0.022 0.021

Oct. 0.025 0.090 0.080 0.062 0.006 0.016 0.016 0.012

Nov. 0.025 0.168 0.050 0.056 0.009 0.061 0.016 0.024

Dec. 0.020 0.043 0.025 0.027 0.006 0.031 0.017 0.020

Thornton Creek Jan. 0.477 1.720 1.320 1.299 0.049 0.144 0.071 0.079

Feb. 0.680 1.660 1.350 1.254 0.061 0.129 0.071 0.078

Mar. 0.417 1.590 1.095 1.021 0.031 0.184 0.067 0.076

Apr. 0.480 1.300 0.969 0.940 0.031 0.156 0.061 0.071

May 0.553 1.400 1.110 1.069 0.016 0.304 0.086 0.096

June 0.656 1.480 1.095 1.054 0.040 0.166 0.097 0.105

July 0.727 1.380 1.070 1.059 0.046 0.193 0.149 0.144

Aug. 0.816 1.300 0.961 1.010 0.046 0.190 0.147 0.132

Sept. 0.570 1.410 0.928 0.975 0.069 0.190 0.137 0.129

Oct. 0.630 1.400 1.130 1.073 0.086 0.236 0.123 0.129

Nov. 0.620 1.450 1.005 1.010 0.046 0.156 0.094 0.098

Dec. 0.430 1.580 1.220 1.167 0.055 0.153 0.079 0.085

Nooksack River Jan. 0.350 0.841 0.558 0.577 0.016 0.061 0.040 0.039

Feb. 0.510 0.920 0.573 0.668 0.016 0.055 0.031 0.034

Mar. 0.230 0.750 0.712 0.601 0.016 0.049 0.023 0.028

Apr. 0.270 0.540 0.469 0.437 0.016 0.031 0.016 0.019

May 0.139 0.450 0.278 0.286 0.016 0.016 0.016 0.016

June 0.183 0.250 0.217 0.217 0.016 0.031 0.023 0.023

July 0.142 0.229 0.170 0.178 0.016 0.031 0.023 0.023

Aug. 0.128 0.200 0.164 0.164 0.016 0.061 0.038 0.038

Sept. 0.230 0.370 0.275 0.292 0.016 0.061 0.016 0.031

Oct. 0.207 0.375 0.210 0.264 0.016 0.016 0.016 0.016

Nov. 0.257 0.560 0.260 0.369 0.016 0.034 0.031 0.029

Dec. 0.570 0.920 0.604 0.698 0.016 0.061 0.016 0.031

For both NO3

−

 and PO 4

−3

, relative attenuation was greatest 

in July through September and was lowest and relatively 

constant from January through June (figs. 22 and 23). 

Variability in monthly relative attenuation is also the greatest in 

July through September. Peaks in relative nutrient attenuation 

at all three sites correspond to times when monthly mean 

flows are the lowest and monthly mean nutrient concentration 

declines (tables 7 and 8). The combination of lower flows and 

nutrient concentrations leads to longer travel times within the 

reach, more contact time of surface water with the streambed 

(from lower Q/w), and more efficient relative attenuation 

(via lower concentration and higher vf). The summer peak 

in relative nutrient attenuation is greatest for the North Fork 

Skokomish site likely because the change to lower flows are the 

most pronounced for this site.
44 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

tac15-0989_fig22abc

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

0 

10 

20 

30 

40 

50 

60 

70 

80 

90 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

4.0 

4.5 

5.0 

Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec.

Relative nitrate attenuation, as a percent of inputs removed per kilometer

A

B

C

EXPLANATION 

Maximum value

Minimum value

Median value

Figure 22. Monthly variation of relative nitrate attenuation using the 

vf model given by equation 6 for the (A) North Fork Skokomish River, (B) 

Thornton Creek, and (C) Nooksack River at Ferndale, Washington. Data 

points represent median monthly relative attenuation and bars represent 

the minimum and maximum values based on variation in monthly stream 

discharge and width.
Analysis of Relative Nutrient Attenuation in Puget Sound Basin 45

tac15-0989_fig23abc

0 

2 

4 

6 

8 

10 

12 

14 

16 

0 

10 

20 

30 

40 

50 

60 

70 

0 

0.5 

1.0 

1.5 

2.0 

2.5 

Relative orthophosphate attenuation, as percent of inputs removed per kilometer

Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec.

A

B

C

EXPLANATION 

Maximum value

Minimum value

Median value

Figure 23. Monthly variation of relative orthophosphate attenuation using 

the vf model given by equation 6 for the (A) North Fork Skokomish River, 

(B) Thornton Creek, and (C) Nooksack River at Ferndale, Washington. Data 

points represent median monthly relative attenuation and bars represent 

the minimum and maximum values based on variation in monthly stream 

discharge and width.
46 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

Across all months, relative attenuation is about an order 

of magnitude lower in the Nooksack River than in the other 

two sites, having the highest nutrient concentrations, greatest 

discharge, and largest values for Q/w. Relative nutrient 

attenuation at the North Fork Skokomish River and Thornton 

Creek are comparable throughout the year despite being 

different types of streams (high gradient headwater stream 

compared with low gradient urban stream, respectively). 

The monthly mean nutrient concentrations from North Fork 

Skokomish River were much lower than from Thornton Creek 

(table 8); however, monthly mean discharge at Thornton Creek 

was much lower than at North Fork Skokomish River (table 7). 

The similarity in relative attenuation at these two sites shows 

how the physical (hydrologic) and biological conditions in 

streams and rivers are important, and the interaction of these 

factors can improve attenuation potential even in highly 

developed watersheds.

Future Work

There are several ways forward for improving 

understanding of nutrient attenuation in Puget Sound stream 

and rivers. Firstly, a simple procedure was developed to score 

the relative nutrient attenuation potential of a given stream or 

river reach for NO3

−

 and PO 4

−3

based on four factors (vf, channel 

slope, channel sinuosity, and specific discharge [Q/w]). The 

scoring procedure showed that for two different attenuation 

models, higher scores represent higher relative attenuation 

values. Therefore, compilation of more detailed spatial 

data sets for these factors will allow for a better broad-scale 

assessment of attenuation potential in the Puget Sound Basin. 

Much of this data likely are already being collected as part of 

other programs by Washington State Department of Ecology 

and other local and federal agencies, but these data need to be 

assembled. Particularly, channel slope, sinuosity, and Q/w, or 

a subset of these data are likely collected during stream habitat 

assessments and estimates of channel slope and sinuosity 

can be determined from high-resolution GIS coverages. 

Seasonal changes in these factors also could be collected 

and summarized and used to further understand and assess 

temporal changes in attenuation.

One other parameter that could help managers 

understand nutrient attenuation dynamics in the region is 

the amount of fine benthic organic matter contained within 

streams and rivers. It has been shown that the amount of 

fine benthic organic matter is important for NO3

−

 removal 

(Mulholland and others, 2000; Meyer and others, 2005; Inwood 

and others, 2007; Harvey and others, 2013); however, detailed 

spatial data on this parameter (percent fines) for Puget Sound 

streams and rivers are not currently available. For this reason, 

this parameter was not included in the scoring procedure even 

though is it an important factor. If this data were spatially 

available, scoring for orthophosphorus attenuation may be 

improved because this parameter indicates the extent of 

sediment deposition, and thus deposition of sediment bound 

P. These data, if collected during instream habitat assessments, 

could help explain controls on instream nutrient attenuation in 

the future.

A large data gap exists for Puget Sound Basin streams and 

rivers. Information on vf is not currently available for Puget 

Sound. Estimates of vf based on a literature-based correlation 

between nutrient concentration and vf from other studies 

were used for this report; however, the procedure used to 

estimate nutrient concentration was based on modeled data 

and involved a complicated procedure to calculate reach-scale 

concentrations. A first step in developing a Puget Sound 

Basin dataset for vf would involve compiling mean annual 

and (or) monthly nutrient concentrations for monitoring 

locations to calculate vf using equations 8 and 9. Other efforts 

to develop a vf dataset for Puget Sound include conducting 

field experiments to measure vf directly across a range of 

nutrient concentrations and stream types in order to derive 

a specific correlation between concentration and vf for the 

Puget Sound Basin. These data are best collected using stream 

nutrient injections, but this approach is better for use on 

small to medium sized reaches and can be labor-intensive. 

For large main stem reaches, if groundwater and hyporheic 

exchange loads are assumed negligible, calculating 

upstream-downstream loads also can be used to estimate vf.

No studies could be found that directly measured nutrient 

attenuation in streams and rivers in the Puget Sound Basin. 

Existing ambient monitoring networks do not typically include 

multiple stations along a river reach; however, longitudinal 

sampling of rivers and streams can provide detailed 

information on spatial and temporal attenuation. Additionally, 

longitudinal data may be collected under other programs (for 

example, during total maximum daily load assessments) and 

could be compiled in order to begin estimating attenuation at 

specific locations around Puget Sound. Beyond conducting 

detailed field assessments of instream attenuation, the PNW 

SPARROW model (Wise and Johnson, 2013) could be 

recalibrated for the Puget Sound Basin and used to determine 

nutrient attenuation dynamics in the region. In addition to 

redefining the PNW SPARROW model for the Puget Sound 

Basin, the expression used to describe instream attenuation 

can be updated to use the vf model as was done in Aguilera and 

others (2013). The current PNW SPARROW model uses an 

expression to describe instream loss based on physical factors 

only and as shown in this report, attenuation is related to 

physical and biological metrics.

Emerging techniques using continuous NO3

−

 monitors 

may allow for detailed analysis of longitudinal estimates of 

attenuation or time-series estimates of attenuation at a fixed 

groundwater-streamgage station. For example, Hensley and 

others (2014) used continuous NO3

−

 monitors that recorded 
Management of Instream Nutrient Attenuation 47

data as they were dragged behind a small watercraft to produce 

detailed longitudinal profiles for NO3

−

. From these data, 

sections of the NO3

−

 curve were used to calculate attenuation 

metrics (Sw, U, and vf) in great spatial detail. Continuous NO3

−

monitors also can be coupled with a new generation of USGS 

groundwater-streamgages to infer real-time NO3

−

 attenuation 

at fixed stations. This technique combines the instrumentation 

of existing streamgages with real-time groundwater-level data 

from an adjacent shallow well to provide detailed information 

on surface water-groundwater interactions (Eddy-Miller 

and others, 2012). The data on groundwater-surface water 

interactions can be coupled with the continuous NO3

−

 data 

(collected in a stream) and continuous or discrete NO3

−

 data 

collected from the shallow well to estimate nutrient transport 

though the stream bottom (Barlow and Coupe, 2012).

Overall, through compiling new and old data in 

Puget Sound Basin streams and rivers for various channel 

characteristics (Q/w, slope, sinuosity, substrate size) and other 

chemical and biological factors (nutrient concentrations 

and vf data) and integrating the collection of new data with 

an appreciation for the types of data needed to characterize 

attenuation, a better understanding of the spatial and 

temporal dynamics of instream nutrient attenuation can be 

achieved. Little is known about the incremental effect that 

the physical, chemical, and biological factors presented in 

this report have on overall nutrient attenuation, and future 

research is needed to understand the synergistic effects of 

how multiple attenuation factors influence stream and river 

nutrient removal.

Management of Instream 

Nutrient Attenuation

Based on the information presented in this report, several 

actions are available for managing instream nutrient loads 

and attenuation of nutrient loads in stream and rivers of the 

Puget Sound Basin. Firstly, it is important to preserve areas 

that currently indicate high potential for instream nutrient 

attenuation, namely the small streams in headwaters of river 

basins. Secondly, work to improve reaches that are currently 

degraded and show a low potential for nutrient attenuation. 

These areas include smaller reaches in developed areas and 

larger main stem reaches. It is not feasible to make large main 

stem reaches into small headwater reaches, but restoration 

techniques can be used to try and mimic small stream features 

in larger reaches.

Generally, preservation and improvement of instream 

nutrient attenuation should focus on two factors: (1) increasing 

the travel time through a reach and contact time of water 

sediment (reactive) surfaces and (2) lowering nutrient 

concentrations (and loads) to avoid saturation of instream 

attenuation and increase attenuation efficiency. Increasing the 

travel time and contact time with sediment surface in a reach 

can be achieved by maintaining or reestablishing channel-flood 

plain connectivity and instream channel complexity features 

that promote groundwater-surface water exchange (woody 

debris dams, riffle-pool morphology, side channels, and 

meandering reaches). Maintaining and restoring channel-flood 

plain connectivity will help disperse floods, increasing overall 

travel times through the reach and reducing the proportion of 

flow that remains in the main channel, thus lowering Q/w. In 

turn, restoration of flood plain connectivity can be achieved by 

increasing levy setbacks or removing channelization features 

entirely. Restoration projects that include addition of woody 

debris, constructed step-pools maintaining heterogeneous 

substrate, aquatic planting, and creating sinuosity in previously 

channelized reaches will increase the potential for hyporheic 

exchange and the contact time for biological uptake of 

nutrients and lead to greater nutrient uptake (Shibata and 

others 2004; Kasahara and Hill 2006a, 2006b).

To address the second factor, management of point 

and non-point sources of nutrients and maintaining or 

re-establishing riparian vegetation along reaches will work 

to lower nutrient concentrations and instream loads. Intact 

riparian zones have been shown to greatly reduce nutrient 

delivery to streams and rivers through uptake in soils and 

vegetation from overland and groundwater flowpaths to the 

stream reach (Naiman and Décamps, 1997). River-flood plain 

connectivity also has the benefit of increasing potential for 

nutrient attenuation when floodwater is dispersed to areas that 

are optimal for the removal of nutrients thus reducing nutrient 

burden for downstream reaches (Sheibley and others, 2006).

Land use affects both the hydrology and biology of 

streams and rivers through modification of flow regimes from 

urbanization and increased nutrient delivery from urban 

and agricultural practices. Although urban and suburban 

development is inevitable, effects from altered flow regimes 

(higher leak flows, flashier hydrographs) and higher nutrient 

loads may be mitigated by preserving riparian zones along 

streams and the implementation of low impact development 

practices.

Key management goals that can be used to maintain and 

improve instream attenuation include:

1. Preserve areas where relative nutrient attenuation is 

high, namely small headwater reaches by maintaining 

important channel features (woody debris, instream 

vegetation, step-pool morphology, channel sinuosity) 

and preserve intact riparian zones.

2. Restore channels where relative attenuation is low, 

large main stem reaches, and smaller reaches with high 

nutrient inputs.
48 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

Specific actions that can be utilized to reach these goals 

include:

1. Restore instream habitat through addition of woody 

debris, heterogeneous substrate (gravel and cobbles), and 

constructed step-pools.

2. Restore and maintain channel-flood plain connectivity 

through increased levy setback or levy removal.

3. Restore and maintain healthy riparian zones along 

streams.

4. Reduce point and non-point source nutrient loads.

5. Where development cannot be avoided, mitigate 

potential degradation of channels by retaining intact 

riparian zones and through implementation of low 

impact development.

As these management actions are undertaken, an 

appreciation of the data needs and modeling tools presented 

can be used to quantify the nutrient attenuation success of 

these efforts. Many of these management approaches are 

already being undertaken during projects aimed to restore 

quality salmon habitat throughout the Puget Sound Basin. 

Therefore, there is a dual benefit to these projects that also may 

lead to enhanced potential for N and P attenuation.

Summary and Conclusions

A review of the scientific literature identified several 

physical, chemical, and biological factors that influence 

nutrient retention in streams and rivers. A number of models 

were identified that can be used to estimate reach scale 

attenuation. Attenuation is dependent on both physical and 

biological factors, and the importance of these factors changes 

with location in the watershed. For example, attenuation is 

generally high in headwater reaches compared to main stem 

reaches likely because of a combination of long travel times 

and low nutrient concentrations, and more biological activity. 

In contrast, main stem reaches tend to have lower attenuation 

potential because they have shorter travel times because these 

channels are larger, water moves faster than in headwater 

reaches, and therefore have less contact with bed sediments. 

Relative to headwater reaches, main stem reaches generally 

tend to have higher nutrient concentrations resulting from 

adjacent developed land uses and more human activities. Main 

stem reaches also have been shown to have low biological 

diversity due to other water-quality issues, and biomonitoring 

of these lowland reaches shows that many of them are 

degraded. Attenuation of orthophosphate (PO 4

−3 ) is much 

lower than nitrate (NO3

−

) across Puget Sound Basin streams 

and rivers. Because relative attenuation in the larger main stem 

reaches is lower does not mean attenuation is not important, 

rather these larger reaches have a lower potential for nutrient 

removal than smaller headwater reaches. 

Two models of relative NO3

−

 attenuation based on physical 

factors (RivR-N) and physical and biological factors (vf model) 

were compared to identify where these factors are more 

important in the Puget Sound Basin. In headwater reaches, the 

vf model simulates much higher relative attenuation indicating 

that biological factors in these small channels may be more 

important. In contrast, in lower gradient, large channels of the 

main stem reaches, the RivR-N model simulates greater relative 

attenuation indicating that hydrologic (physical) factors may 

play a bigger role on instream attenuation of NO3

−

. Comparing 

these two models is not without its limitations because the 

assumptions and error associated with each model are likely 

different. However, this comparison does begin to indicate 

where physical and biological factors may be important and 

warrants further investigation. 

Some limitations of the two models (RivR-N and vf

model) used for the analysis in this report that should be 

mentioned. Both the attenuation models were applied to a 

refined stream and river network that did not include the 

smallest watersheds (greater than 50 square kilometers); 

therefore, the results do not include the smaller headwater 

reaches. This approach was used because there was accurate 

and detailed data on channel characteristics (widths, slopes, 

and sinuosity) for the refined river network; therefore, 

attenuation could be described accurately on a spatial basis 

at this resolution. For the RivR-N model, the expression used 

to estimate instream attenuation was based on field studies 

outside the Puget Sound region and does not include attention 

data from the scientific literature from the last decade. Despite 

this, the model did use the best available information at that 

time and data used to derive equation 4 included a wide variety 

of stream and river types. Our application of the RivR-N 

model relied on estimates of reach width based on correlation 

between mean annual discharge and width (equation 5) at 

locations of USGS streamgages. Because streamgages are 

in areas with stable, straight channels the attenuation is 

expected to be underestimated at unconfined reaches using 

this approach. For the vf model, the addition of a biological 

factor (vf) results in additional limitations and assumptions in 

our approach. Modeled concentration data were relied on for 

total nitrogen (TN) and total phosphorus (TP), correlations 

between total and dissolved nitrogen and phosphorus, and 

expressions for vf in terms of concentration (equation 7 and 8) 

in order to parameterize this model. Although the approach 

used for estimating reach-scale vf is acceptable and uses the 

available data, the vf model would be more accurate with real 

Puget Sound Basin data for vf. The vf model assumes that 

dispersion and transient storage in the reach is negligible. This 

may be true in some reaches, but these assumptions would 

not be universally met throughout the Puget Sound Basin. 
References Cited 49

The vf model for PO 4

−3

 attenuation may underestimate total 

attenuation because it is based mainly on the biological uptake 

of phosphorus and does not describe loss by sedimentation 

well. This may be one reason that the scoring procedure did 

not work as well for PO 4

−3

 attenuation. Despite the limitation of 

these models, for the initial analysis of attenuation in the Puget 

Sound Basin where the focus was on general patterns, these 

two models described similar patterns of instream nutrient 

attenuation that are consistent with current understanding of 

the factors that influence attenuation in streams and rivers.

Four primary factors were identified that accurately 

describe the patterns observed from the RivR-N and vf models; 

the uptake velocity (vf), channel sinuosity, channel slope, and 

specific discharge (Q/w). These factors incorporate the strength 

of biological activity of a reach, the duration of time that water 

spends in a reach, and the amount of contact between surface 

water and the streambed. Criteria derived in this report allows 

for a scoring of a stream or river reach in order to identify the 

degree of potential attenuation. However, without detailed 

reach-specific data, and the Puget Sound Basin as a whole, 

this approach should be considered a preliminary, first level 

analysis. A first step for future investigations is to compile 

detailed datasets for these four factors and improve the scoring 

procedure presented in this report.

Temporal variability of relative attenuation was 

examined in detail at three case study locations by varying 

flow and nutrient concentrations. Results indicate that 

relative attenuation may reach a minimum when NO3

−

concentrations approach about 3 milligrams nitrogen per 

liter (mg N/L) during low-flow conditions and at about 

1 mg N/L during high-flow conditions. For PO 4

−3 , relative 

attenuation is minimized at much lower concentrations (about 

0.1 milligram phosphorus per liter [mg P/L]) for low- and 

high-flow conditions. These results indicate the need to 

keep instream concentrations low in order to avoid reaching 

minimum attenuation, which will lead to increased transport 

of nutrients to downstream reaches. This can be done through 

the reduction of both point and nonpoint sources of nutrients 

to stream and rivers, particularly in larger main stem reaches 

where relative attenuation is less. Preliminary seasonal 

analysis at three case study sites showed that attenuation is 

highest in summer months and lowest in winter and spring. 

Summer months typically correspond to lower flows and 

higher biological activity. Variability in physical factors 

(discharge and channel width) resulted in greater monthly 

variability in attenuation than did changes in monthly nutrient 

concentrations. The analysis of seasonal relative attenuation 

also showed that the headwater reaches of the North Fork 

Skokomish River and highly urban Thornton Creek have 

comparable levels of relative attention throughout the year. 

The similarity in relative attenuation at these two sites shows 

how both the physical (hydrologic) and biological conditions 

in streams and rivers are important and the interaction of 

these factors can improve attenuation potential even in highly 

developed watersheds.

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Association, v. 47, no. 5, p. 1–26, doi:10.1111/j.1752-

1688.2011.00580.x.

Wise, D.R., and Johnson, H.M., 2013, Application of the 

SPARROW model to assess surface-water nutrient 

conditions and sources in the United States Pacific 

Northwest: U.S. Geological Survey Scientific Investigations 

Report 2013–5103, 32 p.

Withers, P.J.A., and Jarvie, H.P., 2008, Delivery and cycling 

of phosphorus in rivers—A review: Science of the Total 

Environment, v. 400, p. 379–395.

Wollheim, W.M., Vörösmarty, C.J., Peterson, B.J., Seitzinger, 

S.P., and Hopkinson, C.S., 2006, Relationship between river 

size and nutrient removal: Geophysical Research Letters, 

v. 33, L06410, doi:10.1029/2006GL025845.
Appendix A 57

Appendix A. Relationship Between Mean Annual Discharge and Drainage Area 

for Puget Sound Rivers and Streams

Table A1. Summary of flow data used in figure 6 for calculating mean annual discharge at the 535 rivers segments of the hydrologic 

network in this report.

[Abbreviations: km2, square kilometer; m3/s, cubic meter per second]

Site No. Site name

Drainage 

area

(km2)

Years of 

record

Water year Mean annual 

discharge

(m3/s) Start End

12200500 Skagit River near Mount Vernon 7,918 30 1981 2010 462.3

12194000 Skagit River near Concrete 7,010 30 1981 2010 418.8

12035002 Chehalis River near Satsop 4,508 6 2003 2008 175.5

12150800 Snohomish River near Monroe 3,935 30 1981 2010 263.8

12181000 Skagit River at Marblemount 3,535 30 1981 2010 171.4

12031000 Chehalis River at Porter 3,313 30 1981 2010 112.6

12179000 Skagit River above Alma Creek near Marblemount 3,261 15 1981 1995 142.0

12178000 Skagit River at Newhalem 3,008 30 1981 2010 123.1

12101500 Puyallup River at Puyallup 2,427 30 1981 2010 90.79

12027500 Chehalis River near Grand Mound 2,291 30 1981 2010 78.70

12213100 Nooksack River at Ferndale 2,012 29 1981 2010 108.8

12189500 Sauk River near Sauk 1,828 30 1981 2010 121.4

12149000 Snoqualmie River near Carnation 1,544 30 1981 2010 100.2

12210700 Nooksack River at North Cedarville 1,508 5 2006 2010 108.3

12210500 Nooksack River at Deming 1,495 25 1981 2005 94.38

12134500 Skykomish River near Gold Bar 1,370 30 1981 2010 111.6

12089500 Nisqually River at Mckenna 1,324 30 1981 2010 34.50

12100496 White River near Auburn 1,216 18 1988 2009 25.87

12040500 Queets River near Clearwater 1,139 30 1981 2010 128.5

12100000 White River at Buckley 1,093 22 1981 2003 16.48

12099200 White River above Boise Creek at Buckley 1,052 7 2004 2010 35.44

12098500 White River near Buckley 1,027 23 1981 2003 39.75

12113000 Green River near Auburn 1,021 30 1981 2010 36.75

12097850 White River below Clearwater River near Buckley 960 15 1983 2010 36.44

12144500 Snoqualmie River near Snoqualmie 960 30 1981 2010 73.26

12035000 Satsop River near Satsop 765.0 30 1981 2010 59.03

12193500 Baker River at Concrete 760.0 28 1981 2008 74.24

12086500 Nisqually River at La Grande 747.5 30 1981 2010 40.71

12045500 Elwha River at McDonald Bridge near Port Angeles 688.6 30 1981 2010 42.76

12039500 Quinault River at Quinault Lake 675.8 30 1981 2010 83.06

12167000 North Fork Stillaguamish River near Arlington 670.7 30 1981 2010 54.08

12041200 Hoh River at U.S. Highway 101 near Forks 647.7 30 1981 2010 72.49

12106700 Green River at Purification Plant near Palmer 591.4 30 1981 2010 25.46

12061500 Skokomish River near Potlatch 581.1 29 1981 2009 35.28

12105900 Green River below Howard A. Hanson Dam 565.8 30 1981 2010 26.89

12017000 North River near Raymond 560.6 5 1996 2000 32.48

12044900 Elwha River above Lake Mills near Port Angeles 506.9 9 1995 2010 37.08

12119000 Cedar River at Renton 471.0 30 1981 2010 17.78

12093500 Puyallup River near Orting 440.3 30 1981 2010 20.60

12080010 Deschutes River at E St. Bridge at Tumwater 414.7 20 1991 2010 11.10

12125200 Sammamish River near Woodinville 407.0 25 1981 2005 8.327

12048000 Dungeness River near Sequim 399.4 30 1981 2010 11.00

12025000 Newaukum River near Chehalis 396.8 29 1981 2010 14.33

12037400 Wynoochee River above Black Creek near Montesano 396.8 29 1981 2010 35.72

12141300 Middle Fork Snoqualmie River near Tanner 394.2 29 1981 2010 34.04
58 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

Site No. Site name

Drainage 

area

(km2)

Years of 

record

Water year Mean annual 

discharge

(m3/s) Start End

12186000 Sauk River above Whitechuck River near Darrington 389.1 30 1981 2010 30.88

12082500 Nisqually River near National 340.5 30 1981 2010 21.59

12039005 Humptulips River below Highway 101 near Humptulips 337.9 8 2003 2010 39.48

12013500 Willapa River near Willapa 332.8 30 1981 2010 17.89

12043000 Calawah River near Forks 330.2 26 1985 2010 29.52

12155300 Pilchuck River near Snohomish 325.1 18 1993 2010 13.04

12117600 Cedar River below Diversion near Landsburg 317.4 18 1993 2010 14.63

12117500 Cedar River near Landsburg 309.8 30 1981 2010 18.52

12059500 North Fork Skokomish River near Potlatch 299.5 30 1981 2010 3.944

12020000 Chehalis River near Doty 289.3 30 1981 2010 16.30

12026400 Skookumchuck River near Bucoda 286.7 30 1981 2010 9.782

12175500 Thunder Creek near Newhalem 268.8 30 1981 2010 17.62

12205000 North Fork Nooksack River below Cascade Creek near 

Glacier

268.8 30 1981 2010 23.12

12091500 Chambers Creek below Leach Creek near Steilacoom 266.2 13 1998 2010 2.858

12209000 South Fork Nooksack River near Wickersham 263.7 13 1996 2008 19.27

12058800 North Fork Skokomish River below lower Cushman Dam 

near Potlatch

261.1 20 1989 2008 1.789

12104500 Green River near Lester 246.3 11 1981 1993 9.362

12138160 Sultan River below Powerplant near Sultan 241.2 27 1984 2010 20.93

12092000 Puyallup River near Electron 237.6 30 1981 2010 14.79

12079000 Deschutes River near Rainier 229.9 23 1981 2010 6.786

12201500 Samish River near Burlington 224.8 14 1997 2010 7.043

12116500 Cedar River at Cedar Falls 215.6 30 1981 2010 8.706

12116400 Cedar River at Powerplant at Cedar Falls 214.8 5 2006 2010 3.222

12144000 South Fork Snoqualmie River at North Bend 209.2 26 1985 2010 15.16

12148500 Tolt River near Carnation 208.4 30 1981 2010 15.12

12087000 Mashel River near La Grande 206.6 19 1992 2010 6.009

12095000 South Prairie Creek at South Prairie 203.5 23 1988 2010 6.244

12094000 Carbon River near Fairfax 202.0 19 1992 2010 12.07

12137800 Sultan River below Diversion Dam near Sultan 197.4 27 1984 2010 5.698

12060500 South Fork Skokomish River near Union 195.3 19 1981 2010 21.18

12083000 Mineral Creek near Mineral 192.5 21 1981 2006 10.30

12036000 Wynoochee River above Save Creek near Aberdeen 189.7 30 1981 2010 24.25

12039300 North Fork Quinault River near Amanda Park 189.7 6 1981 1986 25.38

12090500 Clover Creek near Tillicum 188.9 18 1991 2010 1.047

12097500 Greenwater River at Greenwater 188.2 17 1994 2010 5.146

12208000 Middle Fork Nooksack River near Deming 187.6 18 1993 2010 14.50

12112600 Big Soos Creek above Hatchery near Auburn 170.8 30 1981 2010 3.447

12054000 Duckabush River near Brinnon 170.2 30 1981 2010 11.86

12026150 Skookumchuck River below Bloody Run Creek 

near Centralia

168.7 29 1981 2010 7.456

12143600 South Fork Snoqualmie River at Edgewick 168.7 27 1984 2010 12.17

12142000 North Fork Snoqualmie River near Snoqualmie Falls 163.8 29 1981 2010 14.29

12056500 North Fork Skokomish River below Staircase Rapids 

near Hoodsport

146.4 30 1981 2010 14.91

12121600 Issaquah Creek near mouth near Issaquah 144.9 30 1981 2010 3.476

12076800 Goldsborough Creek above 7th Street at Shelton 140.5 6 2005 2010 4.314

12010000 Naselle River near Naselle 140.3 30 1981 2010 11.75

12043300 Hoko River near Sekiu 131.1 15 1996 2010 8.837

Table A1. Summary of flow data used in figure 6 for calculating mean annual discharge at the 535 rivers segments of the hydrologic 

network in this report.—Continued

[Abbreviations: km2, square kilometer; m3/s, cubic meter per second]
Appendix A 59

Site No. Site name

Drainage 

area

(km2)

Years of 

record

Water year Mean annual 

discharge

(m3/s) Start End

12179900 Bacon Creek below Oakes Creek near Marblemount 127.2 12 1999 2010 12.33

12052210 Big Quilcene River below Diversion near Quilcene 126.5 16 1995 2010 4.056

12143400 South Fork Snoqualmie River above Alice Creek 

near Garcia

106.5 29 1981 2010 8.234

12035400 Wynoochee River near Grisdale 105.7 30 1981 2010 14.57

12115000 Cedar River near Cedar Falls 104.2 30 1981 2010 6.824

12025700 Skookumchuck River near Vail 102.4 30 1981 2010 5.658

12147500 North Fork Tolt River near Carnation 102.1 30 1981 2010 9.750

12212050 Fishtrap Creek at Front Street at Lynden 96.77 12 1999 2010 1.994

12190710 Swift Creek near Concrete 93.06 8 1983 1990 11.76

12088000 Ohop Creek near Eatonville 88.32 17 1994 2010 1.785

12043163 Sooes River below Miller Creek near Ozette 81.92 6 1981 1986 6.271

12145500 Raging River near Fall City 78.34 30 1981 2010 3.510

12148300 South Fork Tolt River below regulating basin 

near Carnation

75.78 28 1983 2010 4.024

12108500 Newaukum Creek near Black Diamond 70.14 30 1981 2010 1.558

12178100 Newhalem Creek near Newhalem 68.86 30 1981 2010 4.989

12114500 Cedar River below Bear Creek near Cedar Falls 65.02 30 1981 2010 4.362

12127100 Swamp Creek at Kenmore 59.14 9 1981 1989 1.001

12209490 Skookum Creek above Diversion near Wickersham 58.88 12 1999 2010 3.994

12192700 Thunder Creek near Concrete 57.34 12 1983 1994 3.745

12148000 South Fork Tolt River near Carnation 50.43 30 1981 2010 2.722

12207850 Clearwater Creek near Welcome 47.36 10 1999 2010 3.328

12120600 Issaquah Creek near Hobart 45.06 23 1987 2010 1.326

12117000 Taylor Creek near Selleck 44.03 30 1981 2010 2.587

12105710 North Fork Green River near Lemolo 42.75 7 1981 1987 2.253

12103380 Green River above Twin Camp Creek near Lester 42.24 7 1993 1999 1.667

12099600 Boise Creek at Buckley 39.42 29 1981 2010 0.920

12158040 Tulalip Creek near Tulalip 39.42 9 2002 2010 0.349

12122500 Bear Creek near Redmond 35.58 8 1981 1996 0.615

12069550 Big Beef Creek near Seabeck 35.33 15 1981 2010 0.899

12115500 Rex River near Cedar Falls 34.30 30 1981 2010 2.698

12102075 Clarks Creek at Tacoma Road near Puyallup 33.28 13 1996 2008 1.626

12118500 Rock Creek near Maple Valley 32.26 8 2002 2010 0.381

12036400 Schafer Creek near Grisdale 30.98 10 1987 1996 2.143

12120000 Mercer Creek near Bellevue 30.72 30 1981 2010 0.640

12137290 South Fork Sultan River near Sultan 29.70 19 1992 2010 3.50

12118400 Rock Creek at Highway 516 near Ravensdale 28.67 9 2002 2010 0.313

12190718 Park Creek at Upper Bridge near Concrete 26.88 8 1983 1990 3.45

12206900 Racehorse Creek at North Fork Road near Kendall 26.88 12 1999 2010 1.66

12035450 Big Creek near Grisdale 24.50 16 1981 1996 3.15

12158010 Tulalip Creek above East Branch near Tulalip 24.17 9 2002 2010 0.199

12117820 Walsh Lake Ditch near Landsburg 24.12 5 1986 1990 0.320

12210900 Anderson Creek at Smith Road near Goshen 22.94 12 1999 2010 0.585

12113346 Springbrook Creek at Orillia 21.60 17 1994 2010 0.284

12157250 Mission Creek near Tulalip 20.28 9 2002 2010 0.151

12091100 Flett Creek at Tacoma 18.76 19 1981 2010 0.426

12120500 Juanita Creek near Kirkland 17.13 9 1981 1989 0.345

12091300 Leach Creek near Steilacoom 16.79 17 1981 2004 0.368

12073500 Huge Creek near Wauna 16.56 30 1981 2010 0.302

Table A1. Summary of flow data used in figure 6 for calculating mean annual discharge at the 535 rivers segments of the hydrologic 

network in this report—Continued

[Abbreviations: km2, square kilometer; m3/s, cubic meter per second]
60 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

Site No. Site name

Drainage 

area

(km2)

Years of 

record

Water year Mean annual 

discharge

(m3/s) Start End

12090400 North Fork Clover Creek near Parkland 16.00 15 1992 2010 0.221

12113349 Mill Creek near mouth at Orillia 14.41 16 1995 2010 0.418

12147600 South Fork Tolt River near Index 13.67 30 1981 2010 1.547

12117700 Rock Creek above Walsh Lake Ditch near Landsburg 12.57 5 1986 1990 0.484

12091200 Leach Creek near Fircrest 12.11 27 1981 2010 0.164

12115700 Boulder Creek near Cedar Falls 11.88 26 1984 2010 0.687

12091180 Leach Creek at Holding Pond at Fircrest 11.75 5 1981 1985 0.141

12207750 Warm Creek near Welcome 10.57 11 1999 2009 0.777

Table A1. Summary of flow data used in figure 6 for calculating mean annual discharge at the 535 rivers segments of the hydrologic 

network in this report.—Continued

[Abbreviations: km2, square kilometer; m3/s, cubic meter per second]
Appendix B 61

Appendix B. Maps Showing Individual Scores for the Four Primary Factors 

Related to Nitrate and Orthophosphate Attenuation in Rivers and Streams in the 

Puget Sound Basin
62 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

tac15-0989_figB1

Specific discharge (Q/w) scores

Not applicable

0

1

Puget Sound Basin

EXPLANATION

KING

LEWIS

YAKIMA

CLALLAM

CHELAN

SKAGIT

PIERCE

WHATCOM

KITTITAS

JEFFERSON

SNOHOMISH

PACIFIC

MASON

GRAYS HARBOR

COWLITZ

KITSAP

OKANOGAN

ISLAND

THURSTON

SKAMANIA

SAN JUAN

WAHKIAKUM

125° 124° 123° 122° 121°

49°

48°

47°

0 12.5 25 50 MILES

0 12.5 25 50 KILOMETERS

Base from U.S. Geological Survey digital data, 1:100,000

Transverse Mercator projection: NAD 1983 UTM Zone 10N

Puget Sound

Admiralty

Inlet

Skagit R

Green R

Puyallup R

Cedar R

Deschutes R

Nisqually R

Duckabush R

Samish R

Dungeness R

Elwha R

Hamma

Hamma R

Nooksack R

Dosewalips R

Snohomish R

Stillaguamish R

Duwamish R

Skokomish R

Big

Quilcene R

Commencement

Bay

Elliott

Bay

BRITISH COLUMBIA, CANADA

WASHINGTON STATE

Figure B1. Specific discharge scores, Puget Sound Basin, Washington.
Appendix B 63

tac15-0989_figB2

Sinuosity score

Not applicable

0

1

Puget Sound Basin

EXPLANATION

KING

LEWIS

YAKIMA

CLALLAM

CHELAN

SKAGIT

PIERCE

WHATCOM

KITTITAS

JEFFERSON

SNOHOMISH

PACIFIC

MASON

GRAYS HARBOR

COWLITZ

KITSAP

OKANOGAN

ISLAND

THURSTON

SKAMANIA

SAN JUAN

WAHKIAKUM

125° 124° 123° 122° 121°

49°

48°

47°

0 12.5 25 50 MILES

0 12.5 25 50 KILOMETERS

Base from U.S. Geological Survey digital data, 1:100,000

Transverse Mercator projection: NAD 1983 UTM Zone 10N

Puget Sound

Admiralty

Inlet

Skagit R

Green R

Puyallup R

Cedar R

Deschutes R

Nisqually R

Duckabush R

Samish R

Dungeness R

Elwha R

Hamma

Hamma R

Nooksack R

Dosewalips R

Snohomish R

Stillaguamish R

Duwamish R

Skokomish R

Big

Quilcene R

Commencement

Bay

Elliott

Bay

BRITISH COLUMBIA, CANADA

WASHINGTON STATE

Figure B2. Sinuosity score, Puget Sound Basin, Washington.
64 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

tac15-0989_figB3

Slope score for nitrate

Not applicable

0

1

Puget Sound Basin

EXPLANATION

KING

LEWIS

YAKIMA

CLALLAM

CHELAN

SKAGIT

PIERCE

WHATCOM

KITTITAS

JEFFERSON

SNOHOMISH

PACIFIC

MASON

GRAYS HARBOR

COWLITZ

KITSAP

OKANOGAN

ISLAND

THURSTON

SKAMANIA

SAN JUAN

WAHKIAKUM

125° 124° 123° 122° 121°

49°

48°

47°

0 12.5 25 50 MILES

0 12.5 25 50 KILOMETERS

Base from U.S. Geological Survey digital data, 1:100,000

Transverse Mercator projection: NAD 1983 UTM Zone 10N

Puget Sound

Admiralty

Inlet

Skagit R

Green R

Puyallup R

Cedar R

Deschutes R

Nisqually R

Duckabush R

Samish R

Dungeness R

Elwha R

Hamma

Hamma R

Nooksack R

Dosewalips R

Snohomish R

Stillaguamish R

Duwamish R

Skokomish R

Big

Quilcene R

Commencement

Bay

Elliott

Bay

BRITISH COLUMBIA, CANADA

WASHINGTON STATE

Figure B3. Slope score for nitrate, Puget Sound Basin, Washington.
Appendix B 65

tac15-0989_figB4

Slope score for orthophosphate

Not applicable

0

1

Puget Sound Basin

EXPLANATION

KING

LEWIS

YAKIMA

CLALLAM

CHELAN

SKAGIT

PIERCE

WHATCOM

KITTITAS

JEFFERSON

SNOHOMISH

PACIFIC

MASON

GRAYS HARBOR

COWLITZ

KITSAP

OKANOGAN

ISLAND

THURSTON

SKAMANIA

SAN JUAN

WAHKIAKUM

125° 124° 123° 122° 121°

49°

48°

47°

0 12.5 25 50 MILES

0 12.5 25 50 KILOMETERS

Base from U.S. Geological Survey digital data, 1:100,000

Transverse Mercator projection: NAD 1983 UTM Zone 10N

Puget Sound

Admiralty

Inlet

Skagit R

Green R

Puyallup R

Cedar R

Deschutes R

Nisqually R

Duckabush R

Samish R

Dungeness R

Elwha R

Hamma

Hamma R

Nooksack R

Dosewalips R

Snohomish R

Stillaguamish R

Duwamish R

Skokomish R

Big

Quilcene R

Commencement

Bay

Elliott

Bay

BRITISH COLUMBIA, CANADA

WASHINGTON STATE

Figure B4. Slope score for orthophosphate, Puget Sound Basin, Washington.
66 Nutrient Attenuation in Rivers and Streams, Puget Sound Basin, Washington

tac15-0989_figB5

vf model score for nitrate

Not applicable

0

1

Puget Sound Basin

EXPLANATION

KING

LEWIS

YAKIMA

CLALLAM

CHELAN

SKAGIT

PIERCE

WHATCOM

KITTITAS

JEFFERSON

SNOHOMISH

PACIFIC

MASON

GRAYS HARBOR

COWLITZ

KITSAP

OKANOGAN

ISLAND

THURSTON

SKAMANIA

SAN JUAN

WAHKIAKUM

125° 124° 123° 122° 121°

49°

48°

47°

0 12.5 25 50 MILES

0 12.5 25 50 KILOMETERS

Base from U.S. Geological Survey digital data, 1:100,000

Transverse Mercator projection: NAD 1983 UTM Zone 10N

Puget Sound

Admiralty

Inlet

Skagit R

Green R

Puyallup R

Cedar R

Deschutes R

Nisqually R

Duckabush R

Samish R

Dungeness R

Elwha R

Hamma

Hamma R

Nooksack R

Dosewalips R

Snohomish R

Stillaguamish R

Duwamish R

Skokomish R

Big

Quilcene R

Commencement

Bay

Elliott

Bay

BRITISH COLUMBIA, CANADA

WASHINGTON STATE

Figure B5. Vf model score for nitrate, Puget Sound Basin, Washington.
Appendix B 67

tac15-0989_figB6

vf model score for orthophosphate

Not applicable

0

Puget Sound Basin

EXPLANATION

KING

LEWIS

YAKIMA

CLALLAM

CHELAN

SKAGIT

PIERCE

WHATCOM

KITTITAS

JEFFERSON

SNOHOMISH

PACIFIC

MASON

GRAYS HARBOR

COWLITZ

KITSAP

OKANOGAN

ISLAND

THURSTON

SKAMANIA

SAN JUAN

WAHKIAKUM

125° 124° 123° 122° 121°

49°

48°

47°

0 12.5 25 50 MILES

0 12.5 25 50 KILOMETERS

Base from U.S. Geological Survey digital data, 1:100,000

Transverse Mercator projection: NAD 1983 UTM Zone 10N

Puget Sound

Admiralty

Inlet

Skagit R

Green R

Puyallup R

Cedar R

Deschutes R

Nisqually R

Duckabush R

Samish R

Dungeness R

Elwha R

Hamma

Hamma R

Nooksack R

Dosewalips R

Snohomish R

Stillaguamish R

Duwamish R

Skokomish R

Big

Quilcene R

Commencement

Bay

Elliott

Bay

BRITISH COLUMBIA, CANADA

WASHINGTON STATE

Figure B6. Vf model score for orthophosphate, Puget Sound Basin, Washington.

Publishing support provided by the U.S. Geological Survey

Science Publishing Network, Tacoma Publishing Service Center

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

 Director, Washington Water Science Center

U.S. Geological Survey

934 Broadway, Suite 300

Tacoma, Washington 98402 

http://wa.water.usgs.gov
Sheibley and others—Nutrient Attentuation in Rivers and Streams, Puget Sound Basin, Washington—Scientific Investigations Report 2015–5074, ver. 1.1

ISSN 2328-0328 (online)

http://dx.doi.org/10.3133/sir20155074