EFFECTIVENESS OF BMPS IN REDUCING SEDIMENT FROM UNPAVED ROADS

IN THE STILLWATER CREEK, OKLAHOMA WATERSHED1

Donald J. Turton, Michael D. Smolen, and Elaine Stebler2

ABSTRACT: Erosion from rural unpaved roads is thought to be an important source of sediment in sedimentimpaired streams in Oklahoma and other locations. However, no direct measurements of sediment yields from

rural unpaved roads were previously available for Oklahoma. Four rural unpaved road segments in the Stillwater Creek Watershed were instrumented in a paired watershed design to measure sediment yields to streams

before and after the installation of Best Management Practices (BMPs). One segment of each pair remained

under current management to serve as a control. The second segment received BMPs after a 1-year calibration

period. One BMP consisted of widening the ditches, re-shaping ditches and cutslopes, putting a proper crown on

the road surface, and vegetating disturbed areas with grass. The other BMP consisted of creating a proper

crown on the road bed, applying a geo-synthetic fabric to the road bed and surfacing with 127 mm of crusher

run gravel containing 12-15% fines to serve as a binder. Road segment sediment yields for individual storms

varied, depending on factors such as rainfall amount and intensity. During the pre-BMP year, storm sediment

yields ranged from 0 to 4.3 Mg on one pair of segments and from 0 to 2.8 Mg on the other. The storm sediment

yields and annual yields were in the same order of magnitude as sediment yields from unpaved rural or forest

roads reported in other studies. Sediment yields were significantly reduced on both segments by the installation

of BMPs, approximately 80% on one segment pair and 20% on the other. The average sediment yield (across the

four segments) for the pre-BMP year was 138 Mg ⁄ha or 120 Mg ⁄km of road. By extrapolating these average

yields across the 479 km of unpaved roads in the Stillwater Creek Watershed and comparing it to estimated

sediment yields for other land uses obtained from other sources, we conclude that unpaved roads may contribute

up to 35% of the total sediment load to Stillwater Creek.

(KEY TERMS: Best Management Practices; nonpoint source pollution; sediment; erosion; road erosion; unpaved

roads; low-volume roads; best management practice effectiveness.)

Turton, Donald J., Michael D. Smolen, and Elaine Stebler, 2009. Effectiveness of BMPs in Reducing Sediment

From Unpaved Roads in the Stillwater Creek, Oklahoma Watershed. Journal of the American Water Resources

Association (JAWRA) 45(6):1343-1351. DOI: 10.1111 ⁄ j.1752-1688.2009.00367.x

INTRODUCTION

Erosion on unpaved rural roads may be a significant source of stream sediment. Roads usually occupy

a small percentage of a watershed’s area, but have

been reported to contribute a disproportionately large

percentage of a stream’s sediment load. Nagle (2001)

developed a sediment budget for an agricultural

watershed in the Dominican Republic and found that

1

Paper No. JAWRA-08-0186-P of the Journal of the American Water Resources Association (JAWRA). Received October 5, 2008; accepted

July 16, 2009. a 2009 American Water Resources Association. Discussions are open until six months from print publication. 2

Respectively, Associate Professor and Senior Research Specialist (Turton and Stebler), Department of Natural Resource Ecology and

Management, Oklahoma State University, 008 C Ag Hall, Stillwater, Oklahoma 74078; and Professor (Smolen), Department of Biosystems

and Agricultural Engineering, Oklahoma State University, Oklahoma 74078 (E-Mail ⁄ Turton: don.turton@okstate.edu).

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION 1343 JAWRA

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION

Vol. 45, No. 6 AMERICAN WATER RESOURCES ASSOCIATION December 2009
roads accounted for 30% of the total despite occupying a small portion of the watershed. In the grassland

savannah of Kenya, Dunne (1979) determined that

roads and foot paths were responsible for 25-50% of

the total basin sediment yields. Nelson and Booth

(2002) developed a sediment budget for Issaquah

Creek in western Washington. Roads occupied 2.6%

of the watershed area, but contributed 15% of the

total sediment yield. Some states have recognized the

importance of unpaved road erosion and have created

rural roads programs to address the issue (Vermont

Local Roads Program, 1999; Choctawatchee, Pea and

Yellow Rivers Management Authority, 2000; Pennsylvania State University Center for Dirt and Gravel

Roads, 2009). However, only a few studies have actually measured rates of erosion or sediment yields

from rural unpaved roads in the United States (U.S.).

Rates of unpaved road erosion vary greatly

depending on soils, climate, road design, traffic,

topography, and other factors. Welsh et al. (2006)

measured erosion rates from 20 unpaved road segments in the Upper South Platte River Basin of

Colorado over a 5-year period. The mean annual

sediment production ranged from 4 to 67 Mg ⁄ha,

varying mainly because of differences in summer

rainfall. Ramos-Scharro ́n and MacDonald (2007) measured a sediment yield of 194 Mg ⁄km ⁄ year from an

unpaved rural road segment during a 1-year study in

the U.S. Virgin Islands. Concentrations of sediment

in runoff from unpaved roads tend to be very high.

In a study of unpaved road erosion in Guanella

Pass, Colorado, Stevens (2000) measured sediment

concentrations ranging from 34 to 38,800 mg ⁄l, with

a median of 1,510 mg ⁄l. Ziegler et al. (2000) measured sediment concentrations of 100,000 mg ⁄l and

greater in runoff from unpaved roads in rural areas

of Thailand.

Forest roads are similar to many unpaved rural

roads in that they are constructed from native materials and are typically unpaved. Sugden and Woods

(2007) measured annual sediment yields ranging

from 0 to 96.9 Mg ⁄ha from 20 forest road plots in

western Montana. Fransen, et al. (2001) measured

sediment yields of 30-380 Mg ⁄km ⁄ year from established roads and rates ranging from 266 to

7,600 Mg ⁄km⁄ year from newly constructed roads at

various locations across New Zealand. Reid and Dunne (1984) measured erosion rates ranging from 3.4 to

36 Mg ⁄km⁄ year and as high as 440 Mg ⁄km⁄ year on

heavily used forest roads in western Washington. In

the Ouachita Mountains of southeastern Oklahoma

and central Arkansas, sediment yields ranging from

18 to 172 Mg ⁄ha ⁄ year (19-114 Mg ⁄km⁄ year) have

been reported for forest road segments of various

ages and slopes (Miller et al., 1985; Vowell, 1985;

Turton and Vowell, 2000).

There are approximately 117,000 km of unpaved

county roads in Oklahoma. Approximately 81% are

classified as gravel roads and the remaining 19% are

classified as graded or unimproved roads (Association

of County Commissioners of Oklahoma, August 4,

2008, personal communication). In many cases, counties are required to maintain roads along section lines

to provide access to agricultural land even when traffic volume is very low. Many of these roads are poorly

designed and are poorly maintained due to restricted

county budgets. Miller (2001) surveyed changes in

road cross-sections to estimate erosion following the

installation of road improvements on rural unpaved

roads in southern Oklahoma, but did not quantify

sediment yields.

The objectives of this study were to measure sediment yields from typical low-volume unpaved road

segments in north-central Oklahoma and determine

the reduction in sediment yields following the installation of Best Management Practices (BMPs).

METHODOLOGY

Study Sites

Two pairs of unpaved road segments in the Stillwater Creek, Oklahoma Watershed were chosen for

runoff and sediment yield measurements as affected

by the installation of road BMPs. Stillwater Creek is

a tributary of the Cimarron River and has a drainage

area of 715 km2

. The watershed is located approximately 70 km north of Oklahoma City and 96 km

west of Tulsa. The road sites were not chosen randomly, but in consultation with the Payne County,

Oklahoma Commissioners, who were cooperators in

the demonstration aspects of the project. The road

segments on the sites represent two typical design

flaws and maintenance issues found in most of the

low-traffic volume unpaved roads in the watershed.

Site 1 (19th Street 0.5 km west of Vasser Rd.) consisted of two consecutive road segments on opposite

sides of a common ridge. The road segments were

named 1B (received BMPs) and 1C (control). The

road was composed of native soil over shale ⁄ sandstone bedrock. Site 1 was chosen because like many

nongraveled roads in the region, it had a narrow

right-of-way, was incised below the surrounding land,

lacked bar ditches to provide road bed drainage, was

poorly crowned, and was susceptible to deep rutting

when the surface was wet. As a result the road was

re-graded frequently.

Site 2 (32nd Street just west of Country Club Rd.)

consisted of two consecutive road segments that

TURTON, SMOLEN, AND STEBLER

JAWRA 1344 JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
drain to the same stream. The road segments were

named 2B (received BMPs) and 2C (control). Site 2

was approximately 13 km east and 1.5 km south of

Site 1. The road was originally constructed from

native soil with gravel in a narrow track down the

center of the road surface. Site 2 was chosen

because like many roads in the area, it lacked a sufficient crown to allow the road bed to drain, and

although the right of way was wide enough, the

ditch capacities were too small to handle flows without eroding the ditch and the road bed. This road

also required frequent re-grading to re-shape the

ditches and remove small ruts from the part of the

road not covered by gravel.

Mean annual precipitation for Payne County

where the two sites were located is 942 mm (1971-

2000). Mean monthly precipitation is highest in

May (145 mm) and June (109 mm) and lowest in

January (31 mm) and February (41 mm) (Oklahoma

Climatological Survey, 2008). The majority of the

annual precipitation is produced by a few large

intense thunderstorms.

Measurements

The study was designed as a paired watershed

study, where one road segment of each pair remained

under existing conditions and maintenance (1C and

2C) to serve as a control, and the neighboring segment was treated with road BMPs (1B and 2B).

Maintenance was not carried out on a regular schedule. The road surfaces were re-graded to eliminate

ruts after major rain events. Ditches were pulled on

an ‘‘as-needed’’ basis determined by the grader operator. Sediment yield, rainfall, and discharge data were

collected for 1 year before BMPs were installed and

1 year after the BMPs were installed. The watershed

of each segment included approximately half of the

road surface (from the crown to the bar ditch), the

bar ditch and the associated cutslope (Figure 1).

The upslope divides were defined by the hillcrest of

the road.

Road segment lengths, slopes, and areas were

determined using standard land surveying techniques

and submeter resolution GPS. Soil textures were

determined by taking samples from random locations

on the road segment surface. A composite sample

from each segment was sifted through a 2 mm sieve

to remove rock and analyzed for texture by settling

tube analysis (Gee and Bauder, 1986).

Each site contained a siphoning tipping bucket

rain gage, a plastic rain can to serve as a backup,

and two sediment collection stations. Each station

was equipped with a sediment collection trough, a

0.46 m H-Flume, and a pumping sampler to sample

suspended load not captured in the trough (Figure 2).

The sediment collection stations were connected to

the bar ditches and located at the end of each road

segment close to where runoff entered a stream or

other natural outlet.

The troughs were constructed of treated plywood

and were approximately 2.4 m long, 0.6 m deep, and

0.4 m wide. Seven plastic baskets lined with landscape fabric to trap coarse sediment were placed

inside the troughs. After each storm, the baskets containing sediment were individually weighed in the

field. Subsamples of sediment were pulled from each

basket, oven dried, and the moisture content determined. The moisture content was used to determine

the dry weight of sediment in each basket. Sediment

FIGURE 2. Sediment Measuring System at Road Segment 2C. The

same equipment was installed at each of the road segments. However, only one recording rain gage was installed at each site.

FIGURE 1. Road Segment Boundaries and Areas for Road Segment 2B. Boundaries for all of the road segments were defined by

the road crown, bar ditch, and cutslope boundaries.

EFFECTIVENESS OF BMPS IN REDUCING SEDIMENT FROM UNPAVED ROADS IN THE STILLWATER CREEK, OKLAHOMA WATERSHED

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION 1345 JAWRA
collected in the trough baskets was called bulk

sediment.

Water stage in the flumes was measured by pressure transducers installed in the stilling wells. The

transducers were capable of measuring stage to the

nearest 3 mm. Measurements of stage and precipitation were collected by data loggers every 5 minutes.

The data loggers also triggered the pumping samplers,

based on the following criteria. If the stage rose above

21 mm, a sample was taken. When the stage was

above the minimum, samples were taken every 5

minutes if the stage rose or fell 15 mm during that

interval, or every 30 minutes if the stage remained

constant. This allowed samples to be taken throughout

a storm to account for changes in flow and sediment

concentration while conserving available bottles. The

sampler intakes were located in the wall of the flume

near the flume outlet where velocity, and hence, mixing are greatest. The quantity of sediment that left the

system at flow rates below the 21 mm minimum stage

was assumed (and later confirmed by our measurements) to be negligible when compared to the sediment

yields when flows were higher. Additional details

about the equipment used in this project are available

in Turton et al. (2006).

Suspended sediment concentrations were determined by evaporation of a weighed sample (Guy,

1969). Samples were shaken and the entire contents

were poured into preweighed aluminum tins. The

evaporation method was chosen because preliminary

grab samples of road ditch water indicated that

sediment concentrations would be too high to make

filtering practicable. Sediment concentrations were

calculated in parts per million (ppm) and converted

directly to mg ⁄l. When sediment concentrations were

very high (above 16,000 ppm) a correction factor

(Guy, 1969) was applied to account for the volume of

the sample that was occupied by the sediment

particles.

The suspended sediment yield of each storm was

calculated by multiplying together the discharge of

each time interval, the interval time and the suspended sediment concentration associated with the

interval. Interval suspended sediment loads were

summed to obtain the total storm suspended load.

The total yield for each storm was equal to the sum

of the suspended sediment yield and the dry weight

of the bulk sediment.

Road Best Management Practices

Oklahoma does not currently have a generally

accepted BMP manual for unpaved rural roads. We

used erosion control and road construction practices

recommended by the Local Technology Assistance

Program (LTAP) located in the Center for Local Government Technology at Oklahoma State University.

The LTAP roads program provides training to county

road crews in the proper design, construction, and

maintenance of roads. The BMPs used were tailored

to fit the conditions at each site.

Because the roadway at Site 1 was incised 2-3 m

below the surrounding land, properly sloping the cutbanks and widening the ditches would have required

extensive excavation and extending the construction

beyond the narrow right-of-way (10 m either side of

center). Considering the limited budget and capabilities of the county road crew, more cost-effective techniques that would also disturb the least amount of

otherwise stable soil were employed. The existing

road bed was graded to achieve a 13-19 mm per

meter crown, and nonwoven geo-synthetic fabric

(3.66 m wide, 141.7 g) was installed. The fabric was

covered with 127 mm of crusher run limestone (3 ⁄ 4

minus) containing approximately 12-15% fines. Three

quarters minus is rock that has been crushed such

that it passes through a 19 mm (3 ⁄ 4 inches) sieve.

The limestone crusher run compacts to a dense, uniform roadbed material and the geo-synthetic fabric

acts as a separator between it and the soil. These

practices, however, did not increase the capacity of

the bar ditches.

The major problem at Site 2 was poor drainage

because of an inadequate road crown and unstable

ditches. The BMPs consisted of creating a 13-19 mm

per meter crown on the road surface and trapezoidal

ditches with a 1:4 fore slope, 1.2-1.8 m flat bottom,

and 1:3 back slope. Vegetation was removed from the

right-of-way as necessary to allow for the re-grading.

To re-establish vegetation as quickly as possible, the

disturbed area of the right-of-way was seeded with

native Bermuda grass (Cynodon dactylon) and covered with a biodegradable mesh⁄ straw erosion control

mat. The same type of crusher run limestone used on

Site 1 was spread to a thickness of 51 mm over the

surface of the road.

RESULTS

Road segment lengths ranged from 0.16 to

0.26 km. Mean segment slope ranged from 6.6 to

8.3% (Table 1). Road segment slope profiles were typically S-shaped, flat at the top and bottom and steep

in the middle. The steep sections were 11% on three

segments and 15% on another. Due to the distance

between them (13 km), the two sites had different

storm and annual precipitation totals (Table 2). The

precipitation on Site 1 in the pre- and post-BMP

TURTON, SMOLEN, AND STEBLER

JAWRA 1346 JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
years was approximately 25% below the mean annual

amount. Precipitation on Site 2 for both the pre- and

post-BMP years was about 4% below the mean

annual amount (Table 2). Individual storm rainfalls

for storms that produced measurable flow on both

road segments at either site ranged from 3 to

116 mm. Average storm rainfall intensities over both

sites ranged from <1 to 31 mm ⁄hour and maximum

30-minute intensities ranged from 2 to 108 mm ⁄hour.

Frequency–depth–duration analysis based on Hershfield (1961) showed a 2-year 6-hour and a 10-year

1-hour storm occurred at Site 2 and 5-year 6-hour,

5-year 12-hour and 10-year 30-minute storms

occurred at Site 1. One other large event was equivalent to the 2-year 1-hour storm. The remaining

events on both sites were less than the 1-year storm

for all durations between 30 minutes and 24 hours.

The Revised Universal Soil Loss Equation (RUSLE) rainfall energy-intensity factor (R-factor) was

calculated for each storm and totaled for each year

(Dissmeyer and Foster, 1984). Annual R-factors for

the pre-BMP year were below the annual mean on

Site 1 ()35%) and above the annual mean on Site 2

(36%). The annual R-factors were 56 and 187% above

the mean on Site 1 and Site 2, respectively, for the

post-BMP year (Table 2). Most of the rainfall energy

was delivered by the larger events mentioned above.

Storm sediment yields were linearly regressed with

total storm rainfall, maximum 5- and 30-minute

intensities and storm R-factor for each segment and

year. As rainfall amounts, intensities, and energy

increased, sediment yields increased. The rainfall

parameters explained from as little as 11% to as much

as 78% of the variation in sediment yields. Flowweighted mean sediment concentrations for each

storm across both sites ranged from 223 to

108,000 mg ⁄l and were in the same orders of magnitude (103 to 105 mg ⁄l) as reported in road runoff studies by Stevens (2000) and Ziegler et al. (2000). The

pre-BMP year sediment yields from the four road segments ranged from 6 to 20 Mg (Table 3). The sediment yield from one large storm (68 mm) near the

end of the first year was not measured on road segment 2B because construction on the BMPs was under

way when the rain occurred. We estimated the sediment yield for that storm using the pre-BMP relationship between segments 2C and 2B. This allowed

comparison of annualized sediment yield between

sites without sacrificing measurements on the other

three segments. The estimated value was not used in

the Analysis of variance (ANOVA) and Analysis of

covariance (ANCOVA) analysis. Post-BMP annual

sediment yields from the two control segments were

6.1 and 24.8 Mg. Post-BMP annual sediment yields

from the two BMP-treated segments were 11.5 and

5.7 Mg, respectively (Table 3). Sediment yields from

the two BMP-treated segments were considerably

lower in the post-BMP year despite the fact that rainfall energy was greater than in the pre-BMP year.

Sediment yields from all segments in the pre-BMP

year and from the control segments in the post-BMP

TABLE 2. Measured Rainfall and Calculated Rainfall

Erosivity (R-factors) and Deviations From Annual Means.

Period

Measured

Annual

Precipitation

(mm)

Precipitation

Percent

Deviation

From Mean

Calculated

Annual

Rainfall

Erosivity

MJ

(mm ⁄ ha ⁄ hour)

Erosivity

Percent

Deviation

From Mean

Before BMPs

Site 1 722 )24 2,018 )35

Site 2 908 )4 4,250 +36

After BMPs

Site 1 700 )26 4,860 +56

Site 2 908 )4 8,940 +187

Note: Rainfall is based on the period 1971-2000, Oklahoma Climatological Survey, 2008.

TABLE 1. Physical Characteristics of the Four Unpaved

Road Segments Used in the Study.

Segment 1C 1B 2B 2C

Length (m) 158 203 215 264

Mean slope (%) 8.3 7.8 6.6 6.7

Highest slope (%) 15.3 10.6 11.0 10.6

Road area (ha) 0.055 0.074 0.192 0.109

Drainage area (ha) 0.119 0.157 0.243 (0.294) 0.200

Soil texture Clay

loam

Sandy

clay loam

Loamy

sand

Sandy

loam

Note: The road area includes the road surface, ditch, and cut banks

on which erosion occurred. The drainage area includes the road

area plus surrounding well-vegetated land that drained into the

ditches. Value in parenthesis represents the drainage area after

the installation of BMPs.

TABLE 3. Annual Sediment Yields and Totals

for the Four Road Segments.

Road Segment

Year 1, Pre-BMPs Year 2, Post-BMPs

Mg Mg ⁄ ha Mg ⁄ km Mg Mg ⁄ ha Mg ⁄ km

1C 6.0 109 76 6.1 111 77

1B 20.1 272 198 11.5 155 113

2C 11.2 103 85 24.8 227 188

2B 13.1* 68 122 5.7 30 53

Station totals 50.0 - - 48.1 - -

Area-weighted

means

- 138 120 - 112 114

Note: Area-specific yields are based on the road area (Table 1).

*Includes an estimate of 5.5 Mg for the storm of May 14, 2005. The

value was estimated from the pre-BMP regression relationship

developed between the two Site 2 road segments.

EFFECTIVENESS OF BMPS IN REDUCING SEDIMENT FROM UNPAVED ROADS IN THE STILLWATER CREEK, OKLAHOMA WATERSHED

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION 1347 JAWRA
year were in the same orders of magnitude reported

for unpaved rural or forest road runoff (Miller et al.,

1985; Vowell, 1985; Turton and Vowell, 2000; Fransen

et al., 2001; Ramos-Scharro ́n and MacDonald, 2007).

Road segment sediment yields were calculated for

all storms that produced measurable runoff from both

paired segments. Thirty-three pre-BMP and 20 postBMP storms produced measurable runoff on Site 1,

while 31 pre-BMP and 22 post-BMP storms produced

measurable runoff on Site 2. Individual storm sediment yields varied, depending on factors such as

rainfall amount and intensity. Several small storms

generated low sediment yields of <10 kg at both sites.

The largest single storm sediment yield recorded at

either site (Site 2; 5,702 kg) was generated by a 10-

year 1-hour storm. The three largest storms recorded

on Site 1 and Site 2 during the pre- and post-BMP

years generated between 40 and 72% of the total

yearly sediment yields.

The relationship between pairs of BMP-treated

and control road segments was analyzed storm by

storm using a procedure described by the USEPA

(1993) and applied by Claussen et al. (1996). Singlestorm sediment yields were found to be log-normally

distributed (Kolmogorov–Smirnoff test). An F-test

showed that the length of the calibration period was

sufficient to detect a 10% change in sediment yield

(p < 0.01). Linear regression was applied to the logtransformed data to determine the relationships

between road segments in the pre- and post-BMP

years (Figures 3 and 4). ANOVA was used to test the

significance of the regressions. The regressions for

both sites and the pre- and post-BMP years were significant (F-test) at p < 0.001. ANCOVA analysis was

used to detect changes in slopes and intercepts

between the pre- and post-BMP years. On Site 1 the

post-BMP slope (1.36) was significantly (p < 0.05)

greater than the pre-BMP slope (0.788), but the postBMP intercept ()1.01) was significantly (p < 0.005)

less than the pre-BMP intercept (0.97). On Site 2 the

post-BMP slope (1.24) was not significantly (p < 0.05)

different than the pre-BMP slope (1.07), but the postBMP intercept ()1.48) was significantly (p < 0.005)

less than pre-BMP intercept ()0.17).

To estimate the change in sediment yields at each

site due to the installation of BMPs, we applied postBMP sediment yields from the control segments to

the pre-BMP regression equations to estimate the

sediment yields that would have occurred had the

BMPs not been installed. The differences between

measured and predicted values were calculated and

summed (Figure 5). The measured and predicted

FIGURE 3. Storm Sediment Yield Regressions

for the Pre- (calibration) and Post-BMP (treatment)

Periods for Site 1 Road Segments.

FIGURE 5. Road Segment Storm Sediment Yields of Road

Segments Predicted by the Measured Minus the Calibration

Equation Values During the Post-BMP Year for Sites 1 and 2.

Negative values represent a reduction in sediment yield as a result

of BMP installation. Storms are graphed in order of occurrence.

FIGURE 4. Storm Sediment Yield Regressions

for the Pre- (calibration) and Post-BMP (treatment)

Periods for Site 2 Road Segments.

TURTON, SMOLEN, AND STEBLER

JAWRA 1348 JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
sediment yields for the post-BMP year at Site 1 were

11.5 and 14.4 Mg, respectively (20% reduction) and

5.7 and 29 Mg, respectively (80% reduction) at Site 2.

DISCUSSION

Best Management Practices Effectiveness

The ANOVA ⁄ANCOVA analysis demonstrated

overall reductions in sediment yields of 20 and 80%

for Sites 1 and 2, respectively. However, on Site 1,

this reduction was not consistent across storm sizes

(Figure 3). The slope of the post-BMP regression was

significantly greater than the pre-BMP slope, but the

post-BMP regression intercept was significantly lower

than the pre-BMP intercept. This indicates that as

storms became larger, the BMPs became less effective. This result may be explained by short-comings of

the BMP installation and the magnitude of the first

few storms that occurred immediately after construction. Four of the first five storms that occurred in the

first month following BMP installation produced

sediment yields greater than the yields predicted from

the pre-BMP regression equation (Figure 5). Two of

these storms produced large rainfalls (30 and 36 mm)

with high maximum 30-min intensities (28 and

42 mm ⁄hour, respectively). At that time some of the

crusher run gravel was still loose and unconsolidated,

especially along the sides of the road and in the bar

ditches. This material was easily moved by runoff produced by the two large storms. Surface runoff cut new

ditches down to bedrock then expanded laterally into

the cutslope and road bed. Subsequent storms used

the newly cut channels, but did not expand further.

After the fifth storm, the measured sediment yield

was always less than that predicted by the pre-BMP

relationship (what would have occurred had the

BMPs not been installed). The reduction in sediment

yield was 50% for storms 6-21 (measured yield minus

predicted by pre-BMP relationship divided by the predicted). This indicates that once the site stabilized following construction and the ditches did not expand

further, the sediment yields decreased. Because the

post-BMP regression developed in the ANOVA ⁄

ANCOVA procedure uses all the data, it may actually

be underestimating the reduction in sediment yield

over the long run. However, we cannot rule out that

future storms larger than those measured in the short

post-BMP period would not cause additional lateral

cutting into the road bed and cutslope and higher

than predicted sediment yield.

The bar ditches on Site 1 were not re-constructed

with sufficient capacity because the road was incised

approximately 3 m below the surrounding land. Some

of the incision may have been created when the road

was originally built, but most is likely the result of erosion and improper road grading through time. There is

no practical way of breaking up the drainage in ditches

and routing sediment away from streams on incised

roads. The installation of ditches with the proper

width and stable shape would have required extensive

excavation and disturbance of road banks that were

already stabilized with vegetation. The amount of

excavation would have been too expensive for county

road budgets and would also have extended the road

prism beyond the legal right-of-way into private land.

Some other cost-effective method to stabilize ditches

for unpaved roads in narrow cuts is needed.

The crusher run gravel was effective in reducing

erosion and sediment yield from the road surface at

both sites. We observed no rutting in the road surface

following rains for at least two years after the gravel

was installed. As a result, the road surface required

no re-grading during the period. The installation of

the geo-synthetic fabric and gravel not only created a

better road surface for traffic, it reduced road surface

erosion and has saved the county maintenance costs.

The road on Site 2 was not deeply incised and cutslopes were relatively small. There was sufficient

space to construct the bar ditches with sufficient

capacity and stable side slopes. The slope of the postBMP regression was not significantly different than

the pre-BMP slope, but the post-BMP regression

intercept was significantly lower then the pre-BMP

intercept. As a result, the measured storm sediment

yields were consistently less than those estimated by

the pre-BMP relationship throughout the post-BMP

period for all storm amounts and intensities (Figure 5). Sediment yields were relatively high during

the three large storms that occurred in the month following construction and installation of BMPs. The

largest and most intense storm (84 mm; maximum

30 minutes intensity 108 mm ⁄hour) recorded on Site

2 during the entire 2-year study occurred about

2 weeks after construction. At that time, the grass

was not well established. We observed rill erosion in

the ditch in the steepest part (11% slope) of the road

segment after this large event. After the sixth storm

(about one month), and the grass had grown and the

site stabilized from construction, the reduction in sediment yield was 87% (measured yield minus yield

predicted by the pre-BMP relationship).

Importance of Unpaved Road Sediment Yields to the

Stillwater Creek Sediment Budget

Bar ditches carrying road runoff from unpaved

rural roads in Oklahoma typically drain directly into

EFFECTIVENESS OF BMPS IN REDUCING SEDIMENT FROM UNPAVED ROADS IN THE STILLWATER CREEK, OKLAHOMA WATERSHED

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION 1349 JAWRA
streams, because the right-of-ways are limiting (10 m

on either side of the road center) and many roads are

deeply incised. The deep incision prevents installation

of drainage relief structures such as wing ditches or

cross drain culverts that reduce velocity and sediment transport capacity. In a related component of

this study, roads, ditches, stream crossings, and outlets for all unpaved road segments in the Lake Carl

Blackwell subbasin of Stillwater Creek were mapped

using submeter resolution GPS and GIS (Turton and

Stebler, 2006 unpublished data). The analysis showed

that 80% of the total unpaved road area drained

directly into streams. The remaining 20% drained

into vegetated swales or riparian land a short distance from streams.

The water quality impacts of these high concentrations of sediment and high sediment yields from

unpaved road runoff may be significant, depending

on the magnitude of the flow in the stream when the

road runoff is produced. When streamflow is high,

road sediment may be diluted, but when streamflow

is low or the stream is relatively small, high sediment concentrations will occur downstream of road

ditch outlets. This condition is common in summer

storms in Oklahoma when runoff may be produced

from unpaved roads, but the surrounding land produces none. During such conditions, road sediments

are added to streams, and the high concentrations

and quantities of sediment may have a deleterious

effect on residual pools and other habitat used as

refuges by aquatic life during low flow periods.

Regardless of the magnitude of streamflow, the high

sediment yields from roads may be a large part of

the total load of sediment delivered to streams and

lakes.

There are 479 km of unpaved roads in the Stillwater

Creek Watershed that occupy about 1.3% of the watershed’s area (Storm et al., 2003). Direct measurement of

sediment load to Stillwater Creek from unpaved road

erosion is unavailable, but Storm et al. (2003) developed an estimate of the sediment budget using the Soil

and Water Analysis Tool (SWAT) to estimate upland

erosion and the Water Erosion Prediction Project

(WEPP) model to estimate road erosion. They estimated erosion from all sources to be 118,000 Mg ⁄ year

and unpaved roads to be 12,700 Mg ⁄ year, or 10.7% of

the total average annual load.

The average sediment yield across the four road

segments in the pre-BMP year was 120 Mg ⁄km

(Table 3). If we make a coarse extrapolation of this

yield across the entire 479 km of unpaved roads in

the Stillwater Creek Watershed, we would estimate

that unpaved roads produced as much as 57,500 Mg

of sediment during the pre-BMP year. If approximately 80%, or 45,600 Mg, were delivered directly to

the streams in Stillwater Creek, it would raise the

estimated erosion from all sources to 162,800 Mg,

with sediment yields from roads accounting for

about 35%. This is an alarming rate considering

that roads only occupy 1.3% of the watershed area.

This estimate is consistent with several other studies that have also shown that unpaved roads occupying small portions (2-8%) of watersheds can account

for 25-73% of a watershed’s annual sediment budget

(Dunne, 1979; Dunne and Dietrich, 1982; Nagle,

2001).

SUMMARY AND CONCLUSIONS

Our study has shown that unpaved rural roads in

the Stillwater Creek, Oklahoma Watershed yield

large quantities of sediment delivered directly to

streams. During 1 year of the 2-year study, the average sediment yield across four typical road segments

was 138 Mg ⁄ha or 120 Mg ⁄km. Using these average

sediment yields, the total unpaved road distance in

the watershed and estimates of sediment yields from

other sources obtained by watershed modeling, we

estimated that unpaved road erosion and sediment

delivery may account for up to 35% of the sediment

load delivered to Stillwater Creek.

We demonstrated that sediment yields from

unpaved roads can be reduced as much as 80% by

installing appropriate BMPs, even on a limited budget. Particularly effective were providing a stable surface with geotextile fabric and gravel, a proper crown

for drainage of the roadway, and stable channels to

remove water without eroding the road bed or the

cutslopes. This work suggests that where roads are

deeply incised and a proper bar ditch and stable

drainage cannot be provided, surface BMPs may

become less effective as storm size increases. Reductions in road sediment yield and runoff may be especially effective in improving rural stream water

quality because sediment from roads is added directly

to streams where its impacts are the greatest.

ACKNOWLEDGMENTS

The authors thank USEPA Region 6, the Oklahoma Conservation Commission, the Oklahoma Agricultural Experiment Station,

and the Oklahoma Cooperative Extension Service for funding this

work through sec. 319 of the Clean Water Act. The Payne County,

Oklahoma Commissioners provided manpower and supplies for

the BMP installation and Doug Wright and Mike Hinkston at the

Local Technology Assistance Program in the Oklahoma State University Center for Local Government Technology provided design

and consultation. We also thank graduate research assistants

Cory Peranich, Leah Thomas, Andy Lyons, and Phillip Busteed

TURTON, SMOLEN, AND STEBLER

JAWRA 1350 JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
for their help in the field and the staff of the Oklahoma State

University Kiamichi Forestry Research Station for their help in

building and installing the field equipment. We also thank two

reviewers who made excellent suggestions that have improved

this manuscript.

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EFFECTIVENESS OF BMPS IN REDUCING SEDIMENT FROM UNPAVED ROADS IN THE STILLWATER CREEK, OKLAHOMA WATERSHED

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