A Preliminary SPARROW Model of Suspended Sediment for 

the Conterminous United States 

Open-File Report 2008–1205 

U.S. Department of the Interior 

U.S. Geological Survey 
A Preliminary SPARROW Model of Suspended Sediment 

for the Conterminous United States 

By Gregory E. Schwarz 

National Water-Quality Assessment Program 

Open-File Report 2008–1205 

U.S. Department of the Interior 

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

DIRK KEMPTHORNE, Secretary 

U.S. Geological Survey 

Mark D. Myers, Director 

U.S. Geological Survey, Reston, Virginia: 2008 

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iii 

Contents 

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

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

Sediment Model Data Sources ...................................................................................................................1
 

Preliminary Model Estimation Results .......................................................................................................3
 

Model Simulation...........................................................................................................................................5
 

Model Limitations ..........................................................................................................................................6
 

References Cited............................................................................................................................................6
 

Figures 

1. Location of 1,828 water-quality monitoring stations used in the SPARROW sediment model, in 


relation to the Reach File 1 (RF1) stream network .................................................................2
 

Tables 

1. Preliminary estimation results for the SPARROW suspended sediment model..............................4
 
A Preliminary SPARROW Model of Suspended Sediment 

for the Conterminous United States

By Gregory E. Schwarz

Abstract

This report describes the results of a preliminary Spatially 

Referenced Regression on Watershed attributes (SPARROW) 

model of suspended sediment for the conterminous United 

States. The analysis is based on flux estimates compiled from 

more than 1,800 long-term monitoring stations operated by the 

U.S. Geological Survey (USGS) during the period 1975-2007. 

The SPARROW model is structured on the Reach File 1 (RF1) 

stream network, consisting of approximately 62,000 reach segments. The reach network has been modified to include more 

than 4,000 reservoirs, an important landscape feature affecting the delivery of suspended sediment. The model identifies 

six sources of sediment, including the stream channel and 

five classes of land use: urban, forested, Federal nonforested, 

agricultural and other, noninundated land. The delivery of 

sediment from landform sources to RF1 streams is mediated 

by soil permeability, erodibility, slope, and rainfall; streamflow is found to affect the amount of sediment mobilized from 

the stream channel. The results show agricultural land and 

the stream channel to be major sources of sediment flux. Per 

unit area, Federal nonforested and urban lands are the largest 

landform sediment sources. Reservoirs are identified as major 

sites for sediment attenuation. This report includes a description for how the model results can be used to assess changes 

in instream sediment flux and concentration resulting from 

proposed changes in the regulation of sediment discharge from 

construction sites.

Introduction

This report describes the results of a preliminary Spatially 

Referenced Regression on Watershed attributes (SPARROW) 

model of suspended sediment for the conterminous United 

States.

Sediment Model Data Sources

The spatial framework of the SPARROW sediment model 

is the vector-based 1:500,000-scale River Reach File (RF) 

1 hydrography, originally developed by the U.S. EPA (U.S. 

Environmental Protection Agency, 1996) and subsequently 

enhanced to include areal hydraulic load information for 

selected reservoirs (Ruddy and Hitt, 1990), shoreline reaches, 

and reach catchment areas derived from the U.S. Geological 

Survey (USGS) HYDRO1k Digital Elevation Model (DEM) 

(U.S. Geological Survey, 2006a). The enhanced network 

(Nolan and others, 2002), consisting of 62,776 reach segments, including shoreline reaches, 61,214 delineated reach 

catchments, and 2,171 individual reservoirs, has been used to 

support numerous national SPARROW modeling efforts for 

the conterminous United States (for example, Alexander and 

others, 2000). The RF1 reach network for the current SPARROW sediment model was further enhanced by the inclusion 

of areal hydraulic load information for approximately 2,000 

additional large reservoirs (reservoir storage greater than 500 

acre-feet), identified from the National Inventory of Dams 

(NID) (U.S. Army Corps of Engineers, 2006) and linked to the 

RF1 network according to dam geographic coordinates, river 

name, and drainage area.

Included in the original RF1 network are reach estimates 

of mean streamflow and mean velocity, the latter being converted to reach time of travel using the RF1 measure of reach 

length. The attributes of mean streamflow and mean velocity 

are used to assess various sediment mobilization and attenuation processes associated with the stream channel. Because 

catchment areas used to derive the original RF1 estimates of 

mean streamflow are not compatible with catchments included 

in the enhanced RF1 network, an alternative measure of mean 

streamflow was used to compute flow-weighted sediment concentration. The alternative measure is based on an interpolation of USGS streamgage estimates from the 1975-2006 water 

years (WYs), with extrapolation of streamflow upstream of 

gages based on runoff estimated at downstream or neighboring stations and apportioned to the land surface according to 

the enhanced RF1 catchments (David Wolock, U.S. Geological Survey, 2008, written commun.). The available period for 

these data is 1 year less than the period for this study, and a 

water year consists of the period October 1st of the previous 

calendar year through September 30th of the enumerated water 

year.

The dependent variable in the SPARROW sediment 

model is given by long-term mean sediment flux. Long-term 
2 A Preliminary SPARROW Model of Suspended Sediment for the Conterminous United States

mean sediment flux is estimated using the maximum likelihood approach developed by Cohn (2005), as implemented in 

the Fluxmaster program (Schwarz and others, 2006). Instream 

sediment concentrations and stream discharge measurements 

over the WY period 1975-2007 have been obtained from the 

National Stream Quality Accounting Network (NASQAN) 

(Alexander and others, 1996; U.S. Geological Survey, 2006b), 

the USGS National Water-Quality Assessment (NAWQA) 

Program (Mueller and Spahr, 2005), and the USGS National 

Water Information System (NWIS) (U.S. Geological Survey, 

2008), a database encompassing USGS water-quality monitoring stations as well as water-quality monitoring activities 

done in cooperation with State governments. Sampling for 

suspended sediment (USGS water-quality parameter 80154) 

is typically done periodically, not daily. Sample data are 

weighted by channel cross-sectional flow geometry (depth, 

width) and correlated with stream discharge at the time of 

sampling. A linear regression model is estimated that relates 

log-transformed instantaneous suspended-sediment concentration to log-transformed mean daily streamflow, which is measured continuously via water-surface height (stage) coupled 

with a previously estimated relation between surface height 

and instantaneous flow. Included in the regression are the sine 

and cosine of decimal time to capture a seasonal signal, and 

a linear time trend to be used for detrending flux. To support 

the detrending of flux, a companion model of daily streamflow 

is estimated for each water-quality station. The streamflow 

model relates the logarithm of daily streamflow to a secondorder harmonic of the sine and cosine of decimal time, and 

a linear time trend term. To account for serial correlation in 

the daily values, the model is estimated using time-series 

methods that assume a 30-day autoregression in the residuals. 

The water-quality and streamflow models are used to simulate daily flux, with both water-quality and streamflow trends 

removed, for all days within the 33-year period WY 1975-

2007 for which a daily streamflow value is available for every 

day in the same WY. Thus, if streamflow is not available for 

any day within a given WY, no simulated water-quality flux is 

computed for any day in that WY. The simulated estimates of 

flux, detrended to the base year 1992, for all complete WYs 

within the 33-year period, are averaged to obtain a detrended 

flux reflecting long-term mean hydrologic conditions. 

The sediment model is estimated using 1,828 monitoring 

stations located on the RF1 stream network (fig. 1). Stations were selected for inclusion in the model if they had at 

least 15 concentration measurements during the period WY 

1975-2007, and the standard error of the flux estimate did not 

exceed 80 percent of the flux estimate. Of the stations included 

in the analysis, 90 percent had streamflow records in excess 

of 5 years, 70 percent had records exceeding 19 years, and 50 

percent had records that exceeded 32 years. Approximately 

700 monitoring stations have been indexed to the RF1 stream 

Figure 1. Location of 1,828 water-quality monitoring stations used in the SPARROW sediment model, in relation to the 

Reach File 1 (RF1) stream network.
Preliminary Model Estimation Results 3

network as part of previous studies (Alexander and others, 

2000). The remaining monitoring stations were linked to RF1 

reaches via their association with USGS streamgages, which 

are linked to the National Hydrography Dataset (NHD) reach 

network (Stewart and others, 2006). The location of these 

streamgages was transferred from NHD to RF1 using information on streamgage latitude and longitude (based on the NHD 

location), stream name, and reported drainage area. If multiple 

stations were present for the same RF1 reach, the alternative 

stations were first ranked in terms of drainage area, number 

of days predictions were made, the number of water-quality 

observations used in estimation, the coefficient of variation of 

the flux estimate, and whether the water-quality and streamflow records were sufficient to support detrending of flux to 

the base year. (To be detrended, the water-quality and streamflow records must span at least 3 years and, if extended no 

more than 15 percent in duration, must include the detrending 

date June 30, 1992.) The station with the lowest sum of these 

ranks was selected for inclusion in the model. 

Most of the source variables for the SPARROW sediment 

model are expressed as extensive measures of land use. Data 

on land cover and land use have been developed from the 2001 

USGS National Land Cover Data (NLCD) Set Retrofit Change 

Product [Multi-resolution Land Characteristics (MRLC), 

2001], derived from Landsat Thematic Mapper/Embedded Trace Macrocells (TM/ETM) remotely sensed imagery 

at 30-meter resolution and classified according to the eight 

Anderson Level I categories. These data were transformed to 

1-square kilometer (km2

) cells within a Lambert map projection as consistent with HYDRO1k for use within SPARROW. 

The 1-km2 cells are then resolved to catchments associated 

with specific RF1 reaches. For model estimation, land use was 

assigned the 1992 values of the 2001 NLCD Retrofit Change 

Product; the 2001 values of the Retrofit Change Product were 

used to simulate water-quality conditions for 2001. 

Federal nonforested (range and barren) land was included 

in the model separately from private land. Federal land extent, 

taken from the Federal Land coverage of the National Atlas 

(U.S. Geological Survey, 2003) and transformed to 1-km2 cells 

in Lambert projection, was apportioned into Federal range 

and Federal barren land using the 1-km2

 transformation of 

the 1992 NLCD Change Product for Anderson Level I range 

and barren land classes (see above). For model simulation of 

2001 conditions, Federal range and barren land were similarly 

estimated using the land-use estimates from the 2001 NLCD 

Retrofit Change Product.

Variables governing the estimated delivery of contaminants from the land to RF1 streams include soil erodibility 

[the revised universal soil loss equation (RUSLE) K factor], 

soil permeability (inches/hour; depth integrated), mean slope 

(percent), and precipitation (RUSLE R factor). Slope, soil 

erodibility, and permeability were obtained from the State Soil 

Survey Geographic (STATSGO) database (U.S. Department of 

Agriculture, 1994), converted to a 1-km2

 grid in the Lambert 

projection, and averaged over RF1 catchments. The RUSLE 

rainfall factor was derived by interpolating a digitized national 

map of rainfall factor isoline contours (Wischmeier and Smith, 

1978), creating a continuous 1-km2 grid surface in the Lambert 

projection. The grid coverage was subsequently averaged over 

individual RF1 catchments. 

Preliminary Model Estimation Results

The nonlinear, least-squares estimation results of a preliminary version of the SPARROW suspended sediment model 

are given in table 1. The preliminary model includes six source 

terms, five of which are measured by area of specific land 

use (urban, forested, Federal nonforested, agricultural, and 

other land, expressed in km2), and an additional source given 

by the length of the stream channel. The Federal land class 

consists only of Federal range and barren land; it excludes 

Federal forested land, which is incorporated in the forested 

land class. Agricultural land includes cropland, pasture land, 

and orchards. Other land consists of non-Federal range and 

barren land. Among all the land classes, only wetlands and 

land covered by water, ice, or snow are excluded as a potential 

source. The source described as “streambed” relates to stream 

channels as a direct source of sediment, and is measured in 

terms of stream length (expressed in meters). 

The transport of sediment from the land surface to RF1 

rivers is mediated by a land-to-water delivery factor that is 

expressed as a function (see Equation 1.28 in Schwarz and 

others, 2006) of logarithm-transformed values of soil permeability, soil erodibility (USLE K factor), land-surface slope, and 

the USLE rainfall factor. The streambed source is mediated 

by the logarithm of streamflow, distinguished by streamflows 

above and below 500 cubic feet per second (ft3

/s). Although 

the mediation of the streambed source by streamflow is not 

a land process, the manner in which the process is specified in SPARROW is mathematically equivalent to treating 

streamflow as a land-to-water variable affecting the streambed 

source, and for this reason streamflow is listed as a land-towater variable in table 1. To facilitate interpretation of the 

source coefficients, the delivery variables are all expressed as 

deviations from their mean value.

Streamflow was used as the mediating factor affecting 

the mobilization of sediment from the stream channel. There 

are two principal physical factors affecting the mobilization 

of sediment from the streambed: the energy of the stream, 

represented by stream velocity; and the availability of channel 

material, which is proportional to the area of the streambed per 

unit of channel length. Direct measurements of channel velocity, width, and depth (the determinants of streambed area per 

unit channel length) are not available for most reaches in the 

RF1 network. Streamflow was deemed to be a viable surrogate 

for these variables because it is highly correlated with them 

(Schwarz and others, 2006) (in fact, the estimate of velocity 

included with the RF1 network is derived from streamflow), 

and because estimates of streamflow exist for all reaches. 
4 A Preliminary SPARROW Model of Suspended Sediment for the Conterminous United States

The model specifies two instream sediment-attenuation 

processes: attenuation in streams (see Equation 1.30 in 

Schwarz and others, 2006), distinguished by three streamflow 

classes (less than 500 ft3/s, 500-1,000 ft3/s, and greater than 

1,000 ft3/s); and reservoir attenuation, specified as a function 

of areal hydraulic load (see Equation 1.34 in Schwarz and 

others, 2006). The three streamflow classes used to distinguish instream decay are characteristic of the streamflow at 

the 1,828 monitoring stations: 1,040 stations have streamflow 

less than 500 ft3/s, and 539 stations have streamflow exceeding 

1,000 ft3/s. Attenuation in reservoirs is specified to be a function of the ratio of the reservoir settling velocity, the estimated 

mean rate at which sediment moves vertically in water, to areal 

hydraulic load (the ratio of streamflow to reservoir surface 

area), which represents the velocity a particle at the surface of 

the stream would need to travel in order to reach the bottom of 

the reservoir within the average period that the streamflow is 

impounded in the reservoir.

The estimation results given in table 1 characteristically 

reflect the large uncertainty associated with sediment modeling. The model root mean squared error (RMSE) is 1.4, implying that predicted sediment flux or concentration in any given 

reach has an error of approximately 140 percent (Schwarz 

and others, 2006). This compares with the much smaller 0.3 

RMSE obtained with total nitrogen models (Alexander and 

others, 2008). Despite this uncertainty, many of the model 

coefficients are statistically significant. With the exception of 

forested land, all of the source variables are highly statistically 

significant. The largest intrinsic sediment yield is associated 

with Federal range and barren land; urban land has the second 

highest intrinsic yield. Stream channels are also a statistically 

significant source of sediment.

Land-to-water delivery for land sources is strongly 

mediated by the four delivery variables—soil permeability, 

soil erodibility, slope, and rainfall. As would be expected and 

with the exception of soil permeability, the presence of higher 

levels of these factors results in greater sediment delivery to 

streams. Conversely, permeable soils reduce the delivery of 

sediment, presumably because more of the water runoff infiltrates into the ground leaving less overland flow to transport 

Table 1. Preliminary estimation results for the SPARROW suspended sediment model.

[Kg/km2/yr = kilograms per square kilometer per year; kg/m/yr = kilograms per meter per year; ft3/s = cubic feet per second; and m/yr = meters per 

year]

Parameter Units Estimate Standard Error p-value

Source Coefficients

Urban land kg/km2

/yr 47,130 9,925 0.000

Forested land kg/km2

/yr 634 898 0.480

Federal non-forested land kg/km2

/yr 64,344 12,411 0.000

Agricultural land kg/km2

/yr 18,047 3,623 0.000

Other land kg/km2

/yr 11,343 3,186 0.000

Streambed (reach length) kg/m/yr 28.80 6.40 0.000

Land-to-Water Delivery Factors

Slope – 0.804 0.087 0.000

Soil permeability – -0.778 0.094 0.000

R-factor – 0.821 0.081 0.000

K-factor – 1.292 0.279 0.000

Flow [< 500 ft3

/s] (Reach) – 0.154 0.100 0.125

Flow [> 500 ft3

/s] (Reach) – 0.721 0.354 0.042

Stream Attenuation Factors

Travel time (Q < 500 ft3

/s) day-1 -0.007 0.016 0.673

Travel time (500 < Q < 1,000 ft3

/s) day-1 -0.233 0.057 0.000

Travel time (Q > 1,000 ft3

/s) day-1 0.009 0.047 0.854

Reservoir settling velocity m/yr 36.49 5.552 0.000

Number of Observations 1,828

Root mean squared error (RMSE) 1.414

R-square 0.711
Model Simulation 5

sediment. Greater streamflow causes an increase in the amount 

of sediment generated from stream channels, with the largest 

effect associated with streams having flows greater than 500 

ft3/s. 

Reservoir retention is statistically significant and indicates sediment settles at a mean velocity of 36 meters per 

year (m/yr), comparable to estimates of reservoir attenuation 

obtained for phosphorus (Alexander and others, 2008). The 

preliminary model indicates medium-sized streams (flow 

500-1,000 ft3/s) have a statistically significant negative rate 

of instream attenuation, indicating that medium streams are a 

source of sediment, in addition to the stream-channel source 

identified above. Unlike the streambed source of sediment (see 

above), which is dictated by channel length and, thus, explicitly tied to a physical entity, the implied “source” of sediment 

arising from a negative rate of instream attenuation represents 

a proportional “enhancement” of sediment already suspended 

in the stream (see Equation 1.30 in Schwarz and others, 2006). 

Because this proportional enhancement of sediment is not 

associated with a physical source, it is inconsistent with mass 

balance and represents an anomalous finding of the model that 

is not yet explainable. Instream attenuation in small and large 

streams is not significantly statistically different from zero. 

Thus, the preliminary model does not find evidence for sediment loss in streams.

Model Simulation

The estimated SPARROW suspended sediment model for 

base WY 1992 can be used to simulate water-quality conditions for 2001, with and without U.S. EPA proposed changes 

in the regulation of construction activity. The simulation of 

suspended sediment flux for WY 2001, without changes in 

regulation, is obtained using the model prediction equation, 

described as Equation 1.120 in Schwarz and others (2006), 

with all land use-related source variables set to 2001 values 

according to the 2001 NLCD Retrofit Change Product. Flowweighted average sediment concentration is estimated by 

dividing simulated flux estimates by mean streamflow over the 

period WY 1975-2006, obtained from USGS streamgages and 

interpolated to RF1 reaches (Wolock, U.S. Geological Survey, 

2008, written commun.). Although the SPARROW model 

does not explicitly include a source term for construction, such 

loading is implicitly accounted for in the urban land component of the model. Therefore, the 2001 precompliance loading 

from construction (that is, the “base-case” scenario loading) is 

incorporated in the 2001 loading attributed to urban land that 

is obtained by evaluating the urban land variable in the SPARROW model using the 2001 NLCD Change Product value.

The absence of an explicit term for construction loading 

in the SPARROW model necessitates the development of an 

indirect method for assessing changes in sediment loading 

arising from different construction industry regulation scenarios. Suspended sediment loading under alternative regulation 

scenarios has been estimated by U.S. EPA using a variation 

of the Universal Soil Loss Equation (USLE). The USLE 

method determines the amount of soil that is mobilized and 

delivered, under a proposed regulation scenario, to the edge 

of a construction site. To evaluate the impact that changes in 

these loadings have on RF1 stream-sediment flux and flowweighted concentration, it is first necessary to assess the rate 

at which “edge of site” loads are subsequently delivered to 

RF1 streams. To do this, we use the estimated rate of delivery 

from agricultural land, a source that is explicitly included in 

the model, and that can be factored into a mobilization, “edge 

of site” delivery component and a stream-delivery component. 

The method described below isolates the stream-delivery component from the overall rate of delivery from agricultural land 

and applies this component to the change in construction loading to determine the change in loading to RF1 streams. Thus, 

the approach assumes that the delivery of sediment from the 

edge of a site to an RF1 stream is the same for both construction and agriculture activities; the mobilization and delivery 

of sediment to the edge of the site between these activities 

is allowed to differ. Given that urban areas, as compared to 

agricultural areas, generally exhibit higher rates of runoff, with 

compressed runoff duration periods for a given precipitation 

event, the assumption probably leads to an underestimate in 

the change in stream-sediment flux from proposed regulation 

of the construction industry. It would not be necessary to make 

this assumption if the analysis was based instead on a factorization of urban land delivery; however, as is indicated below, 

the information necessary to do this is not available.

The amount of sediment mobilized from agricultural 

land, delivered to the edge of field, and subsequently transported to an RF1 stream, is estimated in SPARROW as the 

product of the agricultural land-source coefficient and the 

associated land-to-water delivery factor. This quantity, denoted 

KAG and expressed in units of yield as kilograms per square 

kilometer per year (kg/km2/yr), is conceptually divided into 

two components: a component representing the amount of 

sediment mobilized from agricultural land and delivered to the 

edge of site, denoted KEOS-AG, and a component representing 

the fraction of this material that is subsequently delivered to an 

RF1 stream, denoted KRF1. If ∆LEOS(S) represents the change in 

construction sediment loading to the edge of site, as estimated 

by U.S. EPA using the USLE method, and ∆LRF1(S) represents 

the change in sediment loading to RF1 streams associated with 

construction regulation scenario S, then the two loadings are 

related according to

( ) ( ) (1) EOS ( )

RF1 RF1 EOS AG

EOS-AG

S

S S

L

L KL K

K

∆

∆ = ⋅∆ =

Given estimates of the regulation-induced change in 

sediment delivered to each RF1 reach, instream processes 

associated with attenuation in channels and reservoirs, as 

described by the SPARROW model estimates, can be applied 

to estimate changes in sediment flux and concentration for 

all RF1 reaches. Additionally, because SPARROW imposes 
6 A Preliminary SPARROW Model of Suspended Sediment for the Conterminous United States

mass balance, the reservoir attenuation process can be used to 

assess changes in the amount of sediment retained in each of 

the approximately 4,000 reservoirs linked directly to the RF1 

network. 

To implement the method described by Equation 1, it 

is necessary to have estimates of KAG, the delivery factor 

for agricultural land, and KEOS-AG, the amount of soil erosion 

mobilized from agricultural land and delivered to the edge of 

site. KAG is reach specific and is estimated in SPARROW as 

a function of the land-to-water delivery factors for agriculture (see Equation 1.28 in Schwarz and others, 2006) and the 

empirically estimated values of the agricultural land-source 

and land-to-water delivery coefficients. The value for KEOS-AG

is obtained using information on soil erosion included in the 

1992 National Resources Inventory (NRI) (U.S. Department 

of Agriculture, 1994), which reports county estimates of soil 

erosion rates for cropland, pasture, and orchards—the land 

classes encompassed by the class labeled “agricultural land” in 

the NLCD Retrofit Change Product. (KRF1 is based on agricultural land because erosion rates for urban land are not reported 

by the NRI.) The USLE-based county erosion rates for each 

of the three land classes were weighted according to the share 

of county land in the respective class (as reported in the 1992 

NRI) and then averaged. If there was no county estimate for 

cropland erosion, an average erosion rate for that county was 

not computed. The county average erosion rate was apportioned to RF1 catchments according to a 1-km2

 grid of agricultural land area derived from the 1992 NLCD Retrofit Change 

Product. For 6,329 catchments where an NRI erosion rate was 

not available, the erosion rate was estimated by determining 

an agricultural land weighted average of all available erosion 

rates for catchments in the same 8-digit hydrologic cataloging 

unit. Lack of an 8-digit cataloging unit average necessitated 

using a 6-digit cataloging unit average for 713 catchments, and 

the remaining 54 catchments were estimated using a 4-digit 

cataloging unit average.

Model Limitations 

The preliminary SPARROW model for suspended sediment described above has certain limitations, some of which 

are inherent to the methodology and some the result of the 

particular model application. An example of the former is the 

restriction of the analysis to the description of long-term mean 

water-quality conditions. As explained in Schwarz and others 

(2006), this restriction is a consequence of imposing mass 

balance on the predictions. One of the benefits of the mass 

balance methodology is that it facilitates the interpretation of 

model coefficients, and enables the comparison of coefficient 

estimates to estimates obtained by other studies in the literature; however, the restriction to mean water-quality conditions 

precludes an analysis of the frequency with which conditions 

of extreme sediment transport occur. 

A second example of a methodology-imposed limitation concerns the use of the statistical method to estimate 

model coefficients. The statistical method provides considerable insight into the evaluation of model fit and the empirical 

relevance of individual model processes. It also enables the 

estimation of prediction uncertainty. However, reasonable 

precision in the statistical estimation of model coefficients 

is generally possible only if the number of specified model 

parameters is limited to those associated with sources and 

delivery processes that have the greatest influence on water 

quality. The resulting model is parsimonious, but may be 

overly simplistic in terms of the range of processes affecting 

sediment transport. 

The RF1 reach network is fairly coarse, and its use in the 

present application limits the ability to predict water-quality 

conditions in smaller streams. The median headwater catchment area in RF1 is 88 km2

, implying water-quality conditions 

in streams with smaller catchments are unresolved. Additionally, the smallest monitored catchment in the SPARROW sediment model is 13 km2

, with only five percent of the monitored 

catchments less than 100 km2. A SPARROW analysis structured on a denser reach network, such as the National Hydrography Dataset, would relax the reach network limitation, but 

the large number of reaches associated with this network 

would make it difficult to conduct a national analysis. 

The large error obtained in the present analysis implies 

the prediction of sediment flux or concentration in any given 

reach segment is imprecise. Although this error compromises 

the ability to describe water-quality conditions in any given 

reach, it does not preclude using the model to characterize 

water quality in a large grouping of reaches. As long as the 

error across reaches is sufficiently independent, the assessment 

of mean water quality in a group of reaches becomes more 

precise as the size of the group increases. 

With the exception of reservoirs, the preliminary model 

does not find evidence of sediment attenuation in streams. The 

result implies that sediment transport in streams is not in a 

steady state. Additional investigation is necessary to determine 

if this result is real, or if there are additional reach attributes, 

currently absent from the model, that identify a subset of 

reaches where sediment attenuation takes place. 

References Cited 

Alexander, R.B., Slack, J.R., Ludtke, A.S., Fitzgerald, K.K., 

Schertz, T.L., Briel, L.I., and Buttleman, K.P., 1996, Data 

from selected U.S. Geological Survey National Stream 

Water-Quality Networks (WQN): U.S. Geological Survey Digital Data Series DDS–37, available online at 

http://pubs.usgs.gov/dds/wqn96cd/. (Accessed January 30, 

2008.)
References Cited 7

Alexander R.B., Smith, R.A., and Schwarz, G.E., 2000, Effect 

of stream channel size on the delivery of nitrogen to the 

Gulf of Mexico: Nature, v. 403, no. 6771, p. 758–761.

Alexander, R.B., Smith, R.A., Schwarz, G.E., Boyer, E.W., 

Nolan, J.V., and Brakebill, J.W., 2008, Differences in phosphorus and nitrogen delivery to the Gulf of Mexico from the 

Mississippi River Basin: Environmental Science & Technology, v. 42, issue 3, p. 822–830.

Cohn, T.A., 2005, Estimating contaminant loads in rivers—An 

application of adjusted maximum likelihood to type 1 

censored data: Water Resources Research 41:W07003, 

doi:10.1029/2004WR003833.

Mueller, D.K., and Spahr, N.E., 2005, Water-quality, streamflow, and ancillary sata for nutrients in streams and 

rivers across the Nation, 1992–2001: U.S. Geological 

Survey Digital Data Series DDS–152, available online at 

http://pubs.usgs.gov/ds/2005/152/. (Accessed 1/30/2008.)

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