# Sediment Production from Unpaved Oil Well Access

Road s in the Allegheny National Forest

Prepared for : 

# United States Department of Energy National Energy Technology Laboratory Through 

# URS Corporation Joel Siegel ; URS Corporation 626 Cochrans Mill Road Pittsburgh, Pa, 15236

and : 

# USDA Northern Research Station Susan Stout; Northern Research Station 335 National Forge Road, P.O. Box 267

Irvine, PA 16329



### By



# Steven M . Bloser Dr. Barry E. Scheetz

Center for Dirt and Gravel Road Studies

The Pennsylvania State University University Park, PA 16802

FINAL REPORT March 26 , 2012

### ii STUDY NOTE
This study was fun ded and completed in two phases:

Phase one was completed in 2010 and consisted of 14 test conducted on “as is” roads in the Allegheny National Forest to provide a baseline and range of sediment productions. This was funded through the US Department of Energy’s National Energy Technology Laboratory. (Agreement 2010

- SC

- RES

- 30033026, 400.4.650.920.003)

Phase two was completed in 2011 and consisted on 4 tests conducted on newly placed aggregate on roads in the Allegheny National Forest to provide a comparison of sediment production compared to the findings in phase one. This was funded through the USDA Northern R esearch Station. (Agreement 11

- CS

- 11242302

- 066 )
Description and results of both phases are included in this paper.

### iii ACKNOWLEDGEMENTS
This study was made possible by the United States Department of Energy through the National Energy Technology Laboratory (Agreement 2010

- SC

- RES

- 30033026, 400.4.650.920.003) and through the United States Department of Agriculture, Northern Research Station (Agreement 11

- CS

- 11242302

- 066 )
The authors would like to extend their thanks to several people and organizations that have contributed to this study : Thanks to Tim Ziegler, Field Operations Specialist at the Center for Dirt and Gravel Road Studies at Penn State, for help with RainMaker design, construction, and field testing. Other support staff of the Center at Penn State including : Dave Shearer, Kathy Moir, Dave Creamer, Ken Corradini, Danielle Lombardi, and Adam Rado have played varying roles in the development and implementation of this study . Two former Center employees, Megan Walsh and Jennifer Eismeier, deserve recognition for their ideas and effort s in the development of the original RainMaker apparatus and sampling procedure. Special thanks to everyone at the Allegheny Nation al Forest, especially Charles Keeports and Dan Salm, for their cooperative efforts in planning the study, and for providing field assistance with road testing

. Thanks also to Jim Letko, of Letko’s Dam Water Hauling, and Tom Tobin of Aquarius Water Hauling
, for their patience and willingness to deliver water on short notice to some very remote locations.

Steven Bloser 216 Larson Transportation Institute University Park, PA 16802 814

- 865

- 6967 smb201@psu.edu

Dr. Barry E Scheetz 214 Larson Transportation Institute University Park, PA 16802 814

- 863

- 5956 se6@psu.edu

### iv 

## Abstract

T he Center for Dirt and Gravel Road Studies at Penn State University has been working to reduce sediment pollution generated by unpaved roads in Pennsylvan ia for over a decade. Runoff from unpaved roads is a large source of sediment pollution in many forested watersheds. The Allegheny Nation Forest, located in Northwest ern Pennsylvania, has over 1, 695 miles of unpaved access roads that serve the shallow oil wells i n the Forest ( USDA

- FS unpublished
, 20 10 a ) . The purpose of this study was to quantify sediment generation rates from these oil access roads in the Allegheny National Forest. In addition, the objective of phase II of the study was to determine differences in sediment production after new aggregate had been placed on 4 of the sites. The experimental approach taken in this study was to use a rainfall simulation device to create a repeatable rain fall event and collect sediment load data

. The rainfall simulator was used to collect sediment in road runoff on 14 sites, each of which was 100’ in length. The simulated rainfall event was 0.61” in 30 minutes which has a return interval of slightly less than 2 months. The 14 sites tested showed sediment productions ranging from 3.2 to 60 pounds of sediment for each 30 minute simulated rain event. The average sediment run off from the sites was 24.7 pounds, which equates to a sediment production rate of 1, 300 pounds per mile for each 3 0 minute simulated rain event. Extrapolation of these results indicates that a single storm of similar intensity and duration to the design storm could be expected to produce over 1,100 tons of sediment from the oil access roads in the Allegheny National Forest. An estimated 385 tons of that sediment can be expected to enter directly into nearby streams during each storm. The study also iden tified a significant ‘first flush’ effect on the road segments studied. Additionally, road segments that received more traffic have been more compacted and exhibit higher structural strengths. Without traffic stress, the best indicators of sediment produ ction from the roads tested were road slope combined with road width. If the road is stressed by traffic, then sediment production becomes less dependent on road width and slope, and more dependent on road strength as measured by the California Bearing Ra tio. Finally it was observed that sediment generation would be greatly reduced from roads with very low usage by establishing vegetative cover on the road surface. After initial testing, 4 of the 14 sites were surface with new aggregate material. Two sit es were surface with local “pit run” material as is standard procedure. Two of the sites were surfaced with Driving Surface Aggregate. The 4 sites were then tested a year later to determine sediment production. All four sites showd reductions in sedimen t production (39% and 65% for pit

- run, 67% and 65% for DSA). The two pit

- run sits averaged ten times as much sediment production as the DSA sites (26.1 lbs versus 2.5 pounds).

### v 

## TABLE OF CONTENTS

List of Figures............................................................................................. vi List of Tables.............................................................................................. vii

CHAPTER 1: Introduction

............................................................................. 1 1.1 Background............................................................

......... ............ 1 1.2 Site Selection......................................................

..... ................ 2

CHAPTER 2: Rainfall Simulator

......................... ... ......................................... 5 2.1 RainMaker Design Specifications

.............................. .......... ............. 5 2.2 RainMaker Calibration.............................................

.......... ............. 6 2.3 RainMaker ‘Return Period’ Equivalence........................

.......... ........... 8
CHAPTER 3: Methodology

........................................................................... 9 3.1 Study Setup and Timeline ........................................................... 9 3.2 RainMaker Testing Procedure......................................................... 9 3.3 RainMaker Summary.................................................................... 1 1

CHAPTER 4: Results

.................................................................................. 12 4 .1 Results of “ existing condition ” Road Testing on 14 sites

.................. .... . 1 2 4

. 2 Results of “after aggregate” Road Testing on 4 sites

... ... ..................... 1 6

CHAPTER 5: Discussion

............................................................................. 1 9 5.1 Effect of Traffic During Testing........................................................ 20 5.2 Influencing Fa ctors........................................................................ 20 5.2.1 Road Slope and Sediment.................................................. 2 1 5.2.2 Road Width and Sediment................................................. 2 1 5.2.3 Road Use and Sediment................................................... 2 2 5.2.4 Road Strength and Sediment ............................................. 2 3 5.2.5 Road Composition and Sediment........................................ 2 4 5.3 Multi

- variable Analysis

.............. ..................................................... 25 5.4 Sediment Production After Aggregate Placement

... ... .................. ...... . 2 6

CHAPTER 6: Conclusions

............................................................................ 2 9 Future Resear c h................................................................................ 33

REFERENCES

...... ... ................................................................................... 35

APPENDECES:
Appendix A: RainMaker flo w and sedimen t data for all sites....................... 36

### vi 

## LIST OF FIGURES

Figure 1.1: Example of the effect of road runoff on aquatic ecosystems. This image, taken in

the Allegheny National Forest adjacent to site “C” in this study, shows road runoff entering Grunder Run at a crossing. (photo courtesy ANF) 1

Figure 1.2: Aerial view of Grunder (right) and Hedgehog (left) watersheds. Notice amount of oil

wells and access roads in Grunder watershed. (map courtesy ANF) 2
Figure 1.3: Locations of the 14 road sites used in this study (green stars, labeled with letters).

The town of Warren and the Allegheny River can be seen in the upper right. (map courtesy ANF) 4

Figure 2.1: RainMaker being run on road Segment “R” as part of this study. 5 Figure 2.2: A water truck fills two1,250 gallon collapsible bladders with water for the RainMaker. 5 Figure 2.3: Rainfall collection jars were used to measure and calibrate the rainfall simulator. 7 Figure 2.4: One of the petri dishes used to capture and suspend raindrops in order to measure

t heir size

. 7
Figure 2.5: Eight individual raindrops are being tracked in this still frame from the high speed

video used to determine raindrop velocity

. 7

Figure 2. 6 : ‘Return Period’ estimate for a 0.64 inch 30

- minute rainfall is slightly under two

months (0.16 years). (Aron et al. 1986) 8
Figure 3.1: An example of a RainMaker sampling point with the RainMaker in the background

. 9 Figure 3.2: A sediment sample is taken at a sample point on site “N ”. 10 Figure 3.3: An oil well sits idle as the RainMaker runs on site “R” in the background. 1 1 Figure 5.1: Average sediment concentration in samples over time for all 14 sites. T=0 when

runoff reaches the sample point

. 1 9
Figure 5.2: Runoff samples from site A are arranged by time, with T=1 on the right, through

T=30 on the left. 1 9
Figure 5.3 : Sediment results from individual runs of the rainfall simulator. All roads were

subject to 20 vehicle passes before run 2 and again before run 3. 20
Figure 5.4: Road slope in relation to average sediment production. (Site A omitted because of

grass cov

er) 21
Figure 5.5: Road slope in relation to sediment production from RUN 1 only. (Site A omitted

because of grass cover ) 18
Figure 5.6: Road width, with and without berm, in relation to average sediment production.

(Site A omitted because of grass cover and indeterminate width ) 22
Figure 5.7: Road width, with and without berm, in relation to RUN 1 sediment production. (Site

A omitted because of grass cover and indeterminate width ) 22
Figure 5.8: Road use, or traffic volume, in relation to average sediment production

. 22 Figure 5.9: The dynamic cone penetrometer pictured here is used to measure road surface

strength

. 2 3
Figure 5.10: Road strength, expressed as California Bearing Ratio, in relation to average

sediment production. (Site A omitted because of grass cover. No data for Site B & C ) 2 3
Figure 5.11: The relationship of strength, expressed as California Bearing Ratio, to the percent

of sediment increase from Run 1 to Run 3. ( No data for Site B & C) 2 4
Figure 5.12: The relationship of strength, expressed as California Bearing Ratio, to the traffi c

volume level. ( No data for Site B & C) 2 4
Figure 5.13: The relationship of the percent sand, silt, and clay in road surface samples to

average sediment production. ( Site A omitted because of grass cover ) 2 4
Figure 5.14: Road “slope+width ” factor, in relation to average sediment production for each run.

(Site A omitted because of grass cover) Figure 5.15: Summary of sediment reductions found between existing road surfaces and new

aggregate Figure 5.16: Visual comparison of the four sites in exiting condition during testing in 2010 and

with new aggregate during testing in 2011. Average sediment production for three runs is included on each photo. Figure 5.17: Summary of average sediment production by ro ad type. All figures are in pounds

of sediment produced per mile of road. Note the differing number of each type of sites that was available for use in obtaining average. 2 5

26

27

28

### vii

Figure 6.1: Testing on site “E”. 2 9 Figure 6.2: This image, taken in the Grunder watershed in late March after a natural rain event,

illustrates the effect of poor road material, excessive moisture, and vehicle traffic on sediment generation. (photo courtesy ANF) 30

### viii 

## LIST OF TABLES

Table 2.1: Results of repeatability testing for the RainMaker. 22 rainfall collection jars

were randomly placed on the roadway and subjecte d to three runs of the RainMaker. 6

Table 4.1: Summary of sediment results, in increasing order, along with site

characteristics. Table 4.2: Summary of sediment results from existing roads and after placement of new

aggregate. 1 6

18

Table 5.1: Composition of road surface samples. Samples are in order of increasing sediment

production

. 2 4

## CHAPTER 1: INTROUDCTION

1.1 Background
The Commonwealth of Pennsylvania has recognized that a significant contributor of
sediment pollution to Pennsylvania streams is runoff from publicly maintained dirt and gravel
roads ( Figure 1.1 ) . In response to a statewide assessment of pollution sites on public unpaved roads, the Commonwealth estab lished the Dirt and Gr avel Road Maintenance Program [ Program ] in 1997 within the State Conservation Commission [SCC] . The Program provides a

non
- lapsing funding source with an objective of identifying the polluting sources and implementing solutions . The Center for Dirt and G ravel Road Studies [ Center ] was established
with in the Larson Transportation Institute on the University Park Campus of The Pennsylvania State University in 2000 to support the Conservation Commission ’s Program. The Center
identifies and refines E nvironmentally S ensitive road Maintenance P ractices [ESMPs] to reduce sediment pollution , teach es these practices to municipal road crews , and coordinates a technical outreach and assistance program for townships in the Commonwealth.
The C enter has conducted more than 14 0 two

- day training session s which have been attended by over 5,0 00 state and township personnel. In the thirteen yea r s that the DGRP has been in operation, over 2,0 0 0 individual road projects have been completed which mitigat e sediment pollution to streams of the Commonwealth. A

m ore detailed description of the P rogram and its accomplishments to date can be found at www.dirtandgravelroads.org

. In 2008, the Center completed a study funded by
the Chesapeake Bay Commission [CBC] with the objective of quantifying sediment production values from unpaved roads. The CBC study implemented several ESMPs in order to quantify sediment after sediment reduction practices had been implemented on the roads.
T he CBC study employed an artificial rainfall simulator to provide a consistent and repeatable rain event on different sections of roadway. The procedures and methodologies developed in the 2008 CBC study were the basis for the current NETL study describe d in this report. A summary and full report on the Center’s previous CBC study is available on the Center’s website Figure 1.1: Examp le of the effect of road runoff on aquatic ecosystems. This image, taken in the Allegheny National Forest adjacent to site “C” in this study, shows road runoff entering Grunder Run at a crossing. (photo courtesy ANF)

### 2

at www.dirtandgravelroads.org under “research”.
The objective of Phase I of this study was to quantify sediment production rates for various unpaved roads created and maintained by the oil industry within the Allegheny National Forest. Another component of the study was to quantify sediment reductions after the placement of road aggregates, how ever, this component of the study has yet to be completed

. The objective of Phase II of the study was to compare sediment productions after new aggregates had been placed on 4 of the sites.

1.2 Site Selection The Center worked in cooperation with representatives from the Allegheny National Forest [ANF] to determine site selection criteria. ANF representatives also assisted in finding and evaluating many of the field sites that were used in this study. The Cent er worked cooperatively with ANF personnel throughout the study to make joint decisions on which sites to
include.
Because of other sediment

- related studies that were underway with Clarion University and the US Geological Survey (USGS) , it was determined that the watersheds of Grunder Run and Hedgehog Run, located just south of Warren, PA, would be the ideal location for this study. The two adjacent watersheds are very similar in size, slope, and cover. The major
difference in the two watersheds was the amount of oil well development
, with Grunder being heavily developed, and Hedgehog being relatively
undisturbed (Figure 1.2)

. The comparative study between these two watersheds that is being conducted by Clarion University may provide further insights to sediment effects to aquatic
habitat on a watershed scale, but are not part of this study or report. In 2010, t he USGS began sampling suspended sediment and streamflow to analyze sediment concentrations for
the two basins during storm e vents. Figure 1. 2 : Aerial view of Grunder (right) and Hedgehog (left) watersheds. Notice amount of oil wells and access roads in Grunder waters hed. (map courtesy ANF)

### 3 The major phase of oil and gas development began in Grunder Run watershed in the early 1980’s. By 1990
, most of the 455 wells in this watershed were completed (US DA

- FS unpublished, 2010) . In the last few years, some new wells and roads have been developed. In Hedgehog watershed, there are 27 recorded oil and gas wells, but only 7 are known to be active (US DA

- FS unpublished, 2010). All of the 14 sites in Grunder and Hedgehog watersheds are on
roads that have existed for at least 2 0 years. The roads in Grunder Run development receive use mainly from light trucks and all

- terrain vehicles to operate and maintain the oil and gas
well s

. Some roads serve as main access routes to the majority of the oil and gas wells and tank
batteries.
The 14 sites tested in this study were chosen to cover a wide variety of road slopes, widths, surface materials, and use levels. Two of this Study’s 14 road sites were located in the Hedgehog Watershed and 11 sites were in the Grunder watershed. One site is located in the adjoining Sill Run watershed, on Forest Road 362. It was the intent of this study not only to give an overall sediment production average for the 14 roads, but to begin to determine which physical fact ors of the roads may be responsible for the highest sediment loads. Physical description and details of each site are included in the results section

. The second part of this study looked at sediment production after the placement of pit

run aggregate and Driving Surface Aggregate. Pit

- run is a term used to describe a locally derived material that is mined from “unofficial borrow pits”. Historically, t t has been widely used on most of the access roads in this study in the past. Compared with commercially supplied aggregate, locally excavated pit

- run is less expensive. Since pit

- run is taken directly from the ground at various locations without processing, it is also highly variable in its composition and quality. Driving Surface Aggregate is a specially designed aggregate specification designed to achieve maximum compacted density to resist traffic and erosion. The DSA used in this study was limestone based, although limestone is not required. The experimental approach taken in this study was to collect sediment load s on a section of road long enough to be representative of the roadway during a simulated rain even.
To ensure an accurate comparison of each road segment , a device was constructed that would
deliver water to the test site in a unifo r m manner. The details of the “ RainMaker ” , its performance characteristics
, and testing protocol follow.

### 4 Figure 1.3 : Locations of the 14 road sites used in this study (green stars, labeled with letters). The town of Warren and the Allegheny River can be seen in the upper right. (map courtesy ANF)

### 5



## CHAPTER 2: Rainfall Simulator

The Center originally designed the first

- generation rainfall simulator, or “ RainMaker ”
, for

use under a previous study funded by the Chesapeake Bay Commission, and described earlier in this report. The RainMaker is ideally suited to sediment monitoring because of the convenience and repeatability that cannot be achieved by sampling natural events

. As part of this NETL study, the Center redesigned the RainMaker in order to improve road coverage, repeatability, dr op size, and drop velocity to produce a mo re repeatable rainfall event that is more representative of natural rain fall . The “second

- generation” RainMaker used in this study is
described below. The RainMaker is designed to simulate a rain event on a 100’ length of road. It delivers approximately 1.2 inches of rainfall per hour in a highly controlled and repeatable
event (Figure 2.1)

.

2.1 RainMaker Design S pecifications

- water source : delivered to site and stored for use in collapsa ble bladders (figure 2.2 )

.

- pump : 3”
, 5hp Honda water pump

.

- body : 100’ x 11⁄2” PVC pipe (in 10’ sections)

.

- risers : 11 PVC risers at 10’ intervals, e ach 1⁄2” in diameter and 10’ tall. A “T” extends 2.5
feet in both directions laterally towards the adjacent risers in order to pos ition a nozzle every 5 feet along the sample road section.

- nozzles : One 180 o nozzle every 5 feet along road ( Rainbird ® MPR Rotary N ozzles)

.

Figure 2.1 : RainMaker being run on road Segment “R” as part of this study. Figure 2.2 : A water truck fills two 1,250 gallon collapsible bladders with water on site “T”.

### 6 Table 2 .1: Results of repeatability testing for the RainMaker

. 22 rainfall collection jars were randomly placed on the roadway and subjected to three runs of the RainMaker

. - p ressure : 30 psi measured on gauge at the terminal end of RainMaker

.

- rainfall rate : measured average of 0.6 2 inches in 30 minutes (1. 23 inches per hour)

.

2 .2 RainMaker Calibration The primary purpose of the RainMaker is to create a highly repeatable rainfall event. The repeatability of the setup was verified by collecting and measuring rainfall for three separate
events on a flat paved surface (Figure 2.3)

. Rainfall intensities from the repea tability testing can
be found in Table 2 .1 . The average rainfall intensity over the entire road was 1. 23 inches per hour. The variability between rainfall collection jars within a single run of the RainMaker approximates the “evenness” of precipitation over the road. The stand ard deviation between collection jars was 0.37, or 30 % of the mean intensity. This indicates that although the average intensity of r ainfall is 1.23 in/hr, most rainfall rates can be expected to vary between 0.86 and
1.60 in/hr for any point on the road.

### 7 Consistency between separate
RainMaker runs is of a greater importance to this study than evenness of coverage over the road. The primary advantage of the rainfall simulator is that it provides the same
storm event every time it is run. Analysis of the data presented in T able
2 .1 indicates that the standard
deviation betwe en runs of the
RainMaker is 0.11 or 9 % of the mean intensity. This means that most point s on the road can be expected to vary by
less than 9 % between separate runs of
the RainMaker

. A paired

- t test was als o run on the data presented in T able 2 .1 to test the statistical significance of the repeatability of the separate runs . T he results of the paired

- t test
indicated with a 95% confidence that there were no significant differences in rainfall intensity
between the three runs. In summary, the RainMaker does a satisfactory job of providing an evenly distributed rain event ( SD of 30% of mean within run ), and an excellent job of providing repeatability by providing the same rainfall intensity at the same points on successive runs (SD
of 9% of mean between runs). In order to better characterize the simulated storm event, testing was done to determine the size of the raindrops produced by the RainMaker

. Fifteen covered petri dishes with a mixture of STP motor oil treatment and mineral oil [REF 2001] were p laced ra ndomly through
the rain fall area (Figure 2.4) . Each dish was individually uncovered for approximately one Figure 2.3 : Rainfall collection jars were used to measure and calibrate the rainfall simulator.

Figure 2.5 : Eight individual raindrops are being tracked in this still frame from the high speed video used to determine raindrop velocity. Figure 2.4 : One of the petri dishes used to capture and suspend raindrops in order to measure their size.

### 8

second; enough to allow rain drops to impact the oil mixture. The hydropho b ic characteristics of the fluid mixture suspended the individual rain drops in the mixture from which they could be photographed. The numbers and size of the individual rain drops in each of the fifteen petri dishes was measured with a custom written program in MatLab. The av erage size of the rain drops measured was 0.84 mm

. Although it is on the smaller end, 0.84mm is within the normal size distribution of what most sources consider a moderate rainfall (Rogers, 1979).
In further efforts to better characterize the simulated ra infall, the velocity of individual raindrops was measured as well. Individual rain drops were videotaped with a Fastcam Ultima
1024 high speed video camera at 5000 frames per second to provide slow

- motion images from which the speed of the rain drops coul d be measured. “Photron Motion Tools Analysis
Software” was then used to determine the velocities of the individual drops. The drops averaged 11.5 miles per hour

. Figure 2. 5 is one of the photographic image s of the drop
movement that was used in the cal culations. This velocity matches expected raindrop velocities for a moderate rainstorm of 9 to 16 miles per hour (Rogers, 1979).

2. 3 RainMaker ‘Return Period’ Equivalence
The “ RainMaker ” simulate s a 1. 23 inches per hour rainfall on a 100’ length of road. The magnitude of the simulated rainfall was chosen to represent a ‘modest’ but not an extraordinary
event for the region. The applied r ate of 0.62 inches per one half

- hour for th is region of
N orth western Pennsylvania is equivalent to approximately a 1.9 month rain event (return period
= 0.1 6 years)

. The return period for 0.62 inches of rainfall in 30 minutes was extracted from Aron et al. [1986] and extrapolated from the data presented in Figure 2. 6

.

Figure 2.6 : ‘Return Period’ estimate for a 0.62 inch 30

- minute r ainfall is slightly under two month s (0.16 years)

. (Aron et al. 1986)

0.16 yrs

### 9



## CHAPTER 3 : Methodology

3.1 Study Setup and Timeline Working with the Allegheny National Forest (ANF) in the Spring of 2010 , the Center identified approximately 25 potential test sections of roadway 100 feet in length where the
rainfall sim ulator could be applied

. The initial study planned to incorporate 18 sections of roadway. In cooperation with the ANF, the Center narrowed down the site list to 14 sites that
would be tested “as is” to quantify sediment production from “typical” oil well access roads. Four of these sites had been previously identified by the ANF as locations where new surface aggregates would be placed. For the remaining four rainfall simulator tests, it was decided that “after” test s should
be run on the four sections of roadway that would receive new aggregate (two with pit

- run and two with Driving Surface Aggregate)

. The Center completed construction and calibration of

two RainMaker d evices in the Spring and early S ummer of 2010. The first road site to be tested, site K, was completed on June 18 th

, 2010. Working around summer rainstorms, the Center completed the remaining 13 “as is” test sections with the help of ANF personnel throughout the summer. All testing was done in accordance with the RainMaker testing
pr ocedure described below . The last road segment, site T, was completed on August 19 th

, 2010. The Center took all sediment samples back to the Water Lab at Penn State Institute for Energy and the Environment for analysis of total suspended solids. Photogra phs, detailed measurements, and road surface samples were also taken from each site to help in later analysis of sediment production. In the Spring of 2011, f our of the sites received placement of a new aggregate surface (sites B & F with “pit

- run aggrega te,” and sites G & C with Driving Surface Aggregate). The RainMaker was run on these sites in the fall of 2011 in order to obtain sediment production figures for the new aggregates.

3.2 RainMaker Testing Procedure

 General Considerations

o RainMaker was run after at least 2 days of dry weather to avoid saturated conditions.

o A 100

- ft stretch of road was evaluated for each test site

. Figure 3.1 : A n example of a RainMaker sampling point with the RainMaker in the background.

### 10 o Each test section of road was subjected to three 30

- minute runs of the RainMaker

.

o Nozzles were checked before each run, and a ny clogged or malfunctioning nozzles were replaced.

 Step

- by

- step procedure

o Set up RainMaker on test section . Insure the collapsible water bladders have a flat place to lay uphill of the test section.

o Insure sample points are ready for collection. This procedure was site

- specific, but
included activates such as digging sampling points (see Figure 3.1 ), installing sheeting to make sampling easier, and insuring no runoff bypasses sampling point.

o Flush any trenches or channels that were dug for the collection system, and test the sampling setup using a garden hose from the terminal end of the RainMaker

.

 RainMaker Run 1

o Pump was turned on and adjusted to 30psi at the gauge on the terminal end of the
Rain Maker . The pump ran for a total of 30 minutes in each run

.

o Sampling :

 During each run of the RainMaker runoff flow rate and sediment samples were captured at regular intervals to determine the amount of sediment leaving each
site (Figure 3.2)

.

 Sediment : Runoff samples were taken at regular intervals and returned to the Water Lab at Penn State for Total Suspended Solids analysis. A total of six samples were collected at each sample point for each run of the RainMaker

. W i t h Time=0 (T=0) set when the wet ting front reached the sample point, sediment samples were collected at one (T=1), five (5), ten (10), fifteen (15), twenty (20), and thirty (30) minutes after runoff reached the sample point

.

 Flow : Flow rate was determined by timing the amount of time it took to fill a
container of known volume. The runoff flow was measured at T=1, T=5 and at
five minute intervals until T= 60 or until runoff stopped.

o After running for 30 minutes , the pump was turned off. Because of the delay in water reaching the sample point, the pump was typically shut off around T=25 in the sample
timeline.
Figure 3.2 : A sediment sample is taken at a sample point on site “N”.

### 11

 Drying Time 1

o After the pump was turned off, the road was allowed to dry for a period of one hour

.

o Approximately 30 minutes into the 60 minute drying cycle, a light truck was driven a total of 20 passes over the entire test section. This was done to simulate traffic and
further stress the road surface before the next RainMaker run.

 RainMaker Run 2

o Afte r the 60 minute drying time, the pump was turned back on for 30 minutes at 30psi. The sampling procedure outlined in “ RainMaker R un 1” above was repeated.

 Drying Time 2

o Another 60 minute drying cycle with 20 light truck passes was completed.

 RainMaker Run 3

o After the 60 minute drying time, the pump was turned back on for 30 minutes at 30psi. The sampling procedure outlined in “ RainMaker R un 1” above was repeated.

3.3 RainMaker Summary By collecting sediment samples and measuring flow volumes at each sample point at regular time intervals , total sediment loading can be calculated for each site . Each time the
RainMaker is run, it is run for three 30

- minute sample periods as described in the “ RainMaker procedure” above. The flow rates and sediment conc entrations for these three runs are then combined to obtain the average sediment production for each section of road.

Figure 3.3 : An oil well sits idle as the RainMaker runs on site “R” in the background.

### 12



## CHAPTER 4: Results

4.1 Results of “existing condition ” Road Testing on 14 sites Sediment loads from each site were determined by combining the Total Suspended
Solids (TSS) concentration found in the water samples with the know flow volumes for each
simulated rainfall event. The RainMaker was run three times on each site, with 20 light truck passes before runs 2 and 3

. All sediment figures are in pounds per 30 minute event unless
otherwise noted. Sediment production rates (3 run average) ranged from 3.2 pounds to 60.1 pounds for the segm ents in this study. Site A, with the least amount of sediment, was a grass covered road where only the wheel tracks contained exposed soil. Site B, with the most amount of sediment, was a high traffic USFS road that was steep with runoff flowing in chann els on the
road surface

. The sediment results for individual site s , along with pertinent site information and photos
are listed below. A summary of the site data and results can be found in Table 3.1. Sites are
described in order of increasing sediment production (3 run average) :



## Site A : 3.2 pounds of sediment (1.0 lbs, 2.1 lbs, 6.4 lbs in successive runs) Tested : 8/18/2010 Slope : 14.7% Width : 13’ Traffic : Very Low CBR ( strength ) : 31 Material : Loam: 43% sand, 31% silt, 26% clay Site Notes : Grass covered road . AASHTO #1 stone exposed in wheeltracks. Minimal use gated road. Ditche s also heavily grassed. Running vehicle over road between tests mad e a lot of difference , both visually and in sediment data. Most runoff came down wheel tracks.



## Site T : 7.4 pounds of sediment (7.1 lbs, 7.0 lbs, 8.0 lbs in successive runs) Tested : 8/19/2010 Slope : 3.3% Width : 12’ (16’ with berm) Traffic : High CBR ( strength ) : 141 Material : Sandy Loam: 75% sand, 14% silt, 11% clay Site Notes : Flattest road tested. Surface largely sand. A few large stones on top. This is a USFS Road with a relatively higher traffic count. Road surface was hard

- packed. Traffic passes between tests had little effect, visually or in sediment data. Runoff was on road and in ditches.

### 13



## Site S : 7.9 pounds of sediment (4.2 lbs, 10.1 lbs, 9.4 lbs in successive runs) Tested : 7/27/2010 Slope : 7.6% Width : 11’ (11’ with berm) Material : Sandy Clayey Loam: 52% sand, 24% silt, 24% clay Traffic : Med CBR ( strength ) : 91 Site Notes : Surface was a mixture of large stone with dirt and some exposed bedrock. Fabric was under surface and exposed in some locations. Ditches were non

- existent and all runoff came down channels cut into road surface.



## Site R : 11.1 pounds of sediment (9.3 lbs, 9.8 lbs, 1 4.3 lbs in successive runs) Tested : 7/27/2010 Slope : 9.0% Width : 11.5’ (11.5’ with berm) Traffic : Low CBR ( strength ) : 99 Material : Loam: 47% sand, 29% silt, 24% clay Site Notes : Ditches were cutoff from surface, and all runoff came down wheel tracks. Surface was hard packed with large rocks on surface. Fabric was under surface and exposed in some locations. Traffic had little visual effect.



## Site K : 12.7 pounds of sediment (7.9 lbs, 15.4 lbs, 14 .9 lbs in successive runs) Tested : 6/18/2010 Slope : 4.4% Width : 12’ (13’ with berm) Traffic : Med CBR ( strength ) : 67 Material : Sandy Loam: 57% sand, 27% silt, 16% clay Site Notes : Road had 10

- 20% ballast rock on surface. Ditches were cutoff from surface, and all runoff came down wheel tracks. Traffic passes mad e a difference , both visually and in sediment data. Runoff ran on road surface and in ditch.



## Site G : 13.0 pounds of sediment (15.1 lbs, 14.0 lbs, 10.9 lbs in successive runs) Teste d : 7/2/2010 Slope : 16.2% Width : 12.5’ (12.5’ with berm) Traffic : High CBR ( strength ) : 126 Material : Loam: 41% sand, 38% silt, 21% clay Site Notes : Very hard packed surface with some rock. High traffic road. Ditches were non

- existent and all runoff came down channels cut into road surface. Traffic passes made little difference visually. One of few sites to have less sediment in successive runs.

### 14



## Site I : 14.7 pounds of sediment (14 lbs, 16.5 lbs, 13.7 lbs in successive runs) Tested : 8/17/2010 Slope : 20.5% Width : 13’ (17’ with berm) Traffic : Low CBR ( strength ) : 81 Material : Loam: 43% sand, 33% silt, 24% clay Site Notes : Steepest road tested. A lot of rocks present on road surface. Most runoff ran down wheel tracks, with some running in ditch. Traffic passes made little difference visually or in sediment data.



## Site C : 14.9 pounds of sediment (11.9 lbs, 14.6 lbs, 1 8.0 lbs in successive runs) Tested : 7/8/2010 Slope : 7.2% Width : 10’ (14’ with berm) Traffic : Low CBR ( strength ) : unknown Material : Loam: 45% sand, 30% silt, 25% clay Site Notes : Runoff ran in wheel track and ditch. Lower use road with little rock on surface. Traffic passes made a difference visually and in sediment data.



## Site L : 28.4 pounds of sediment (12 lbs, 35.7 lbs, 37.5 lbs in successive runs) Tested : 6/31/2010 Slope : 13.8% Width : 12’ (15’ with berm) Traffic : Low CBR ( strength ) : 71 Material : Loam: 51% sand, 31% silt, 18% clay Site Notes : In

- sloped road with runoff flowing in ditch. Relatively low use road with soft surface. Water and traffic has large effect on surface, both visually and in sediment data. Surface became muddy and s lippery, making walking or driving difficult.



## Site N : 29.7 pounds of sediment (14.3 lbs, 40.5 lbs, 34.4 lbs in successive runs) Tested : 8/18/2010 Slope : 5.6% Width : 13’ (15’ with berm) Traffic : High CBR ( strength ) : 103 Material : Loam: 49% sand, 31% silt, 20% clay Site Notes : High use “trunk” road. Very few stones on surface. Water and traffic has large effect on surface, both visually and in sediment data. Ditches were cut off and water ran down wheel tracks.

### 15



## Site E : 35.9 pounds of sediment (7.8 lbs, 36.9 lbs, 62.8 lbs in successive runs) Tested : 6/30/2010 Slope : 9.2% Width : 13’ (13’ with berm) Traffic : Low CBR ( strength ) : 65 Material : Loam: 73% sand, 14% silt, 13% clay Site Notes : Road was mostly sand with some small stones. Very deep ruts ( 6”) in road surface carried all runoff. Traffic had large effect on road, visually and in sediment data.



## Site F : 42.7 pounds of sediment (47.1 lbs, 42.2 lbs, 38.8 lbs in successive runs) Tested : 7/2/2010 Slope : 13.3% Width : 15’ (15’ with berm) Traffic : High CBR ( strength ) : 133 Material : Loam: 46% sand, 33% silt, 21% clay Site Notes : Higher traffic road with hard packed surface with few rocks. No ditches, water runs in wheel tracks. Traffic had very little visual effect. One of few sites to have less sediment in successive runs. This site had the highest “run 1” sediment before traffic.



## Site M : 43.1 pounds of sediment (23.6 lbs, 50.5 lbs, 55.2* lbs in successive runs) Tested : 6/31/2010 Slope : 19.2% Width : 10’ (15’ with berm) Traffic : Low CBR ( strength ) : 76 Material : Loam: 47% sand, 33% silt, 20% clay Site Notes : Very steep road. Low traffic volume and soft surface. All runoff ran down wheeltracks. Traffic had large effect, visually and in sediment data. * Run 3 was not completed due to water truck problems. Data extrapolated based on other sites average increase from run 2

.



## Site B : 60.1 pounds of sediment (31.7 lbs, 67.0 lbs, 81.7 lbs in successive runs) Tested : 7/8/2010 Slope : 12.7% Width : 11’ (16’ with berm) Traffic : Med CBR ( strength ) : unknown Material : Loam: 48% sand, 32% silt, 20% clay Site Notes : Surface was a mixture of soil and rock. Ditches were cut off. Water ran down channels in road surface. Traffic passes made noticeable difference, visually an in sediment data. This site h ad the highest total average sediment (60.1 lbs), and the highest single run sediment (81.7 lbs for run 3).

### 16 The sediment results for the 14 sites that were tested in this study are shown in Table
4.1
, along with most of the physical information about each site. All sediment figures are in pounds per 30 minute event
, and are based on the average of three RainMaker runs unless
otherwise noted

. When results from the 14 100’ test sections are averaged, it shows that typical 100’ section of oil access roads in the Allegheny National Forest can be expected to lose almost 25 pounds of sediment in a single 30 minute storm event with a ~2 month retur n cycle. It should be noted, and will be discussed in detail later, that the rainfall simulator results represent a conservative estimate of sediment loss. Sediment loss from a similar sized actual rain event would be higher because of compounding effects form upslope road drainage and off site drainage, instead of a limited 100’ rainfall on the road only

.

4.2 Results of “after aggregate” Road Testing on 4 sites (Phase II) New aggregate was placed on 4 of the sites in early 2011 (site s B & F with “pit

- run aggregate,” and sites G & C with Driving Surface Aggregate). RainMaker testing, using the same procedures as previously described , was completed on these four sites in the Fall of
2011. Table 4.1 : Summary of sediment results, in increasing order, along with site characteristics.

### 17



## Site B : New Pit

- Run Existing Road: 60.1 lbs (31.7
, 67.0
, 81.7) 

### New Pit

- Run Surface : 36.8 lbs (20.2, 41.4, 48.9) 

### Sediment Reduction: 39% Slope : 12.7% Width : 11’ (16’ with berm) Site Notes : This site had the highest overall sediment production in “existing road” testing. Although sediment pr oduction was less on the new pit

- run surface, the 36.8 lbs of sediment found was still higher than 11 of the 14 original “existing condition” tests. Traffic created a significant increase in sediment production for both the existing road and new surface.



## Site F : New Pit

- Run Existing Road: 42.7 lbs (47.1
, 42.2
, 38.8 ) 

### New Pit

- Run Surface : 15.4 lbs (23.3, 13, 9.8) 

### Sediment Reduction: 64 % Slope : 13.3% Width : 15’ (15’ with berm) Site Notes : This is one of the higher traffic roads in the study. It is also one of the few sites that showed a decrease in sediment production after traffic in successive runs, indicating that traffic did not have an effect on sediment production.



## Site G : New Driving Surface Aggregate Existing Road: 13.0 ( 15.1 lbs, 14.0 lbs, 10.9 ) 

### New DSA : 4.2 lbs ( 6.3, 2.9, 3.5 ) 

### Sediment Reduction: 67 % Slope : 16.2% Width : 12.5’ (12.5’ with berm) Site Notes : This site is located only ~300 feet from site F and also sees significant traffic. Also like site F, traffic did not increase sediment production. The 4.2 lbs found here was significantly lower than all of the “existing road” tests (other than grassed road).



## Site C : New Driving Surface Aggregate Existing Road: 14.9 ( 11.9 lbs, 14.6 lbs, 18.0) 

### New DSA : 0.8 lbs (1.5, 0.5, 0.4) 

### Sediment Reduction: 95 % Slope : 7.2% Width : 10’ (14’ with berm) Site Notes : This site showed the lowest sediment production by far of any site in the study, including the grassed road. This site also had a decrease in sediment production after traffic between the runs.

### 18 Table 4.2 summarizes the sediment production from the existing roads and newly place aggr egate for site B, F, G, and C. While all sites
showed a reduction in sediment compared to their “existing road” tests
, the two pit

- run sites produced ten times
as much sediment as the two DSA sites (26.1 lbs and 2.5 lbs respectively) Table 4.2 : Summary of sediment results from existing roads and after placement of new aggregate.

### 19



## CHAPTER 5: Discussion

The average sediment production found in the 42 individual rainfall simulation tests on these 14 sites was 24.7 pounds per 30 minute event. This equates to a sediment production rate of 1,304 pounds per mile of road for a single 30 minute 0.6 2 ” rain event. Given that the Grunder Run watershed alone has approximately 52 miles of unpaved roads, it can be extrapolated that a single watershed

- wide storm event similar to our design storm will cause a
loss of nearly 34 tons of road sediment in the watershed (USDA

- FS unpublished, 2010)

. It is important to note when extrapolating
, that these figures represent sediment loss from the road, not necessarily into a stream. Some roads higher in the watershed may not be hydrologically connected directly t o the stream system. Unfortunately, many of the roads and
ditches in the watershed serve as direct extensions of the stream channel. Based upon an inventory and assessment of 16,500 miles of unpaved roads throughout Pennsylvania, 35% of unpaved roads sta tewide are typically directly connected to streams. Applying this ratio to the Grunder watershed would yield an estimate of 12 tons of road sediment entering directly into Grunder Run in a single storm of similar intensity and duration to the RainMaker. In addition to the total sediment load described above, the rainfall simulator testing also showed a significant “first flush” of sediment on the tested roads. The “First Flush” concept

states that the majority of sediment pollution is generated at the be ginning of the precipitation event. As the event continues, the easily detached sediment has been washed away, and the remaining material will be more resistant to erosion. Figure 5.1 shows the decrease in sediment production over time when the data for all 14 sites are combined. Figure 5.2 visually illustrates the decrease in sediment over time for site A (grassed site with least total sediment). These results clearly show the effect of the “first flush” of sediment during the first 5 minutes of the

ra infall event.

Figure 5.1 : Average sediment concentration in samples over time for all 14 sites. T=0 when runoff reaches the sample point. Figure 5.2 : Runoff samples from site A are arranged by time, with T=1 on the right, through T=30 on the left.

### 20

5.1 Effect of Traffic During Testing
Each site test consisted of three individual rainfall simulator runs. The initial run (Run 1)
on each site was completed on the road “as is” with no pre

- traffic stresses other than normal use. Between Run 1 and Run 2, twenty light truck passes were run over the road segment. Again betwe en Run 2 and Run 3, an additional twenty light truck passes were done. The se passes were done in an effort to accelerate the pressures and stresses that roads would see
under normal use

. Figure 5.3 illustrates the sediment results for each individual run of the rainfall simulator. Most sites, as expected, showed an increase in sediment production after traffic had been applied. Ten of the 14 sites experience sediment increases of 50% or greater
be tween runs 1 and 3. Two of the 14 sites (sites T and I) showed very little difference in sediment production between runs 1, 2, and 3. Contrary to expected, t wo of the sites (sites G and F) showed significantly less sediment when tested after traffic. Si tes G and F were located in succession, about 500 feet apart, on a main “trunk” line road. Their resistance to traffic may have been a function of their material and frequent use.

5.2 Influencing Factors As part of this study, measurements and notes wer e taken on as many site parameters as possible. It was hoped that the amount of sediment production from the road segments
could be linked to one or more site variable s such as road slope, road width, or road composition. Unfortunately, there was no strong correlation of sediment production to any one factor or combination of factors. The factors are discussed separately below.

Figure 5.3 Sediment results from individual runs of the rainfall simulator. All roads were subject to 20 vehicle passes before run 2 and again before run 3.

### 21

5.2 .1 Road Slope and Sediment Road slope refers to the linear grade of the roadway. Road slope was one of the criteria used in choosing road segments to test. The 14 road segments tested were chosen in part because they represented a fairly wide distribution of slopes from 3.3% to over 20%. The relationship between road slope and
average sediment production is illustrated in Figure 5. 4

. The correlation between road slope and sediment ge neration is very weak (R 2 =0.2 4 ), meaning that in this study, road slope had little determination on the average amount of sediment generated. Part of the reason slope was not a large factor may be the spatially limited rainfall event. The RainMaker only produced rainfall on 100 linear feet of roadway. In a natural rain event, portions of roadway outside the test section would be receiving rainfall and generating runoff that would flow onto the test section. In this situation, an increase in road slope w ould cause increase velocities of runoff and increased erosion. While the rainfall simulator does a good job at simulating the impact erosion of rainfall, it lacks the ability to generate rainfall on a large enough area to simulate the extent of rill and gully erosion that occurs in a real storm. The slope for each road segment is included in Table 4.1. It is worth noting that road slope showed a slightly better correlation (R 2 increase from 0.24 to 0.32 ) to sediment production in the first run
of the Ra inMaker that was completed before traffic passes (Figure 5.5 ). Sediment production
from r uns 2 a nd 3, done after traffic passes, had less correlation with road slope.

5.2

. 2 Road Width and Sediment The width of the road was measured in two ways. First, the width of the actual traveled
road way was measured. This measurement was typically based on the presence or absence of vegetation. Vegetated areas beside the road that d o not typically see traffic were considered
berms . The width of the road including ber m s was also measured since the berms, although typically not driven on, can still contribute sediment to the test sections

. Road w idths ranged Figure 5.4 : Road slope in relation to average sediment production. (Site A omitted because of grass cover)

Figure 5.5 : Road slope in relation to sediment production from RUN 1 only. (Site A omitted because of grass cover)

### 22

from 10 feet to 15 feet in width, with an average of 12.0 feet. The road and berm combined width ranged from 11 feet to 17 feet with an average of 14.1 feet. The correlation of road width and “road+berm” width in relation to total sediment production is illus trated in Figure 5. 6

. Although neither factor showed a strong correlation with sediment production, the “road+berm” width did have a better correlation (R 2 =0.19) than road width alone (R 2 =0.02). The widths for each road segment are included in Table 4.1. Just as with road slope, it is worth noting that road width showed a better correlation (R 2 increase from 0.19 to 0.31) to sediment production in
the first run of the RainMaker that was completed before traffic passes (Figure 5.7 ). Sediment production f rom runs 2 and 3, done after traffic passes, had less correlation with road width.

5.2 .3 Road Use and S ediment Road use, or traffic volume , was approximated using field observations and maps. The 14 sites tested encompassed a wide array of traffic volumes. Some roads served as main

access routes to the majority of the oil and gas wells and tank batteries

. These roads routinely
see traffi c such as loaded tanker trucks, pickup trucks, and all

- terrain v ehicles. Some roads were secondary, only serving a handful of wells. Site A was on a gated road where the traffic level was low enough to allow grass to cover most of the roadway.
Each road segment was assigned a rating from 1 (lowest) through 5 (highest) to approximate its traffic level. Use levels
were based on field observations of traffic and wear, and on the amount of wells the
road accessed. The use level for each road segment is inc luded in Table 4.1. The
correlation between road use level and Figure 5.8 : Road use, or traffic volume, in relation to average sediment production. Figure 5.6 : Road width, with and without berm, in relation to averag e sediment production. (Site A omitted because of grass cover and indeterminate width ) Figure 5.7 : Road width, with and without berm, in relation to RUN 1 sediment production. (Site A omitted because of grass cover and indeterminate width )

### 23

sediment production was very weak (R 2 =0.06). Visual differences in road use can be seen in pictures in individual site results.

5.2

. 4 Road Strength and S ediment
The in

- place strength of each road segment was
measured usi ng a dynamic cone penetrometer [ DCP ]

. The DCP, pictured in Figure 5. 9 , consists of a pointed
steel shaft with a st andard weight that is free to slide up
and down. Following ASTM standards (D6951/D6951M

09) , t he weight is lifted and dropped repeatedly from a know height in order to slowly drive the pointed end of the shaft into the road surface. In simplest terms, the ease of
which the shaft can be driving into the road can be
correlated to the strength of the road. This strength is often expressed as the road ’ s “California Bearing Ratio” [CBR]

. The DCP was used to provide an inexpensive and quick approximation of the CBR for each
site. The CBR rating was developed for measuring the load

- bearing capacity of soils used for building roads. The stronger the
surface is
, the more resistant it is to penetration, the higher its CBR rating. A CBR of 3 equates to tilled farmland, a CBR of 4.75 equates to turf or moist clay, while moist sand may have a CBR of 10. High quality crushed rock has a CBR over 80.
The standard material for this test is
crushed California limestone which has a value of 100 ( Salgado, 2003). All CBR testing was done on the same day to eliminate soil moisture and weather as
variables. The Cone Penetrometer was run at five random locations on each road segment to a depth of 100mm. The five data points were then averaged and used to determine the CBR for each site. CBRs ranged from a low of 31 for the grassed site (Site “ A ”) , to a high of 141 ( Site

“ T ”)

. As illustrated in Figure 5.10 , the CB R ha d almost no correlation with the actual amount of sediment produced from each site (R 2 =0.08). However, when the amount of sediment increase between Run 1 and Run 3 for each site is compared to road hardness, a relationship is found . Figure 5. 11 illustrates that roads with Figure 5.10 : Road strength, expressed as California Bearing Ratio, in relation to average sediment production. (Site A omitted because of grass cover . No data for Site B & C) Figure 5.9 : The dynamic cone

penetrometer pictured here is used to measure road surface strength.

### 24

a lower strength or CBR tend to be more
effected (larger sediment increase) by the traffic that the sites were subjected to between runs ( R 2 =0. 61 ). Roads with a higher strength or CBR were less affected by traffic. The CBRs for each road segment are
included in Table 4.1.
A correlation also exists between the use or traffic level assigned to each road
, and
the road strength expressed as the California Bearing Ratio. Figure 5. 12 illustrates that as road use increases, the strength or CBR of the road surface increases as well (R 2 =0.84)

. 5.2.5 Road Composition and S ediment As part of the effort to quantify the characteristics of each site, road surface samples

Table 5.1 : Composition of road surface samples. Samples are in order of increasing sediment production. Figure 5.11 : The relationship of strength, expressed as California Bearing Ratio, to the percent of sediment increase from Run 1 to Run 3. ( No data for Site B & C) Figure 5.12 : The relationship of strength, expressed as California Bearing Ratio, to the traff ic volume level. ( No data for Site B & C) R 2 =0. 61

Figure 5.13 : The relationship of the percent sand, silt, and clay in road surface samples to average sediment production. ( Site A omitted because of grass cover )

### 25

were taken and analyzed for composition. The samples were obtained by excavating an area approximately two square feet by four inches deep in the surface of each site. Material sample
location s were randomly located on each test section. These samples were taken to the soils lab at Penn State University for analysis. The samples were first screened to obtain the size distribution of the larger particles. Any particles passing through a #10 screen (1/10 th of an inch nominal max size) were further analyzed to determine the percent sand, silt, and clay in the sample. Ta ble 5.1 lists the composition of each sample. There were no significant effect s on sediment production that could be predicted by any one particle size or combination of particle sizes in the samples taken from the road surface. Figure 5. 13 shows that t here is not a significant correlation between the amount of sand silt and clay in the road surface samples and average sed i ment production.

5.3 Multi

- V ariable Analysis No one variable showed a strong correlation with the amount of sediment produced from the road segments. This is most likely due to the high number of variables involved in determining sediment loss. There is, however, an interesting point of discussion when looking at the combined effect of road slope and width on sediment productio n both before and after
traffic stresses. If road slope and road width are combined into a “slope/width” factor, it presents a stronger correlation to sediment production than either factor alone (Figure 5.14).
The R 2 for “slope/width” correlation to sedi ment on run 1 was 0.51, compared to an R 2 of 0.32 and 0.30 for road slope and width individually. One interesting result of this analysis is that the “slope/width” factor
shows a much better correlation with sediment production from run 1 before traffic stresses. Runs 2 and 3, after traffic,
show a much lower correlation. These
observations can be co mbined with trends found in road strength (S ection 5.2.4 ) to generate some general theories on sediment production. Initially, without traffic stress, the amount of sediment production from each road segment is best correlated with the slope and
width o f the road (a s the slope and width of the road increases, sediment production increases (Figure 5.14) ) . For runs 2 and 3 of the RainMaker , each done after 20 vehicle passes, road slope and width played less of a role in determining sediment production. I nstead, sediment Figure 5.14 : Road “slope+width” factor, in relation to average sediment production for each run. (Site A omitted because of grass cover )

### 26

production from runs 2 and 3 can best be explained by the road strength. Road strength was shown to be a g o od indicator of how much sediment would increase on the sites after being stressed by traffic (Figure 5.11). Roads with the lowest strength, measured by CBR, had the highest percentage of sediment increase after traffic stresses. Roads with the highest s trength
showed little sediment increase , and some even showed a decrease, in runs 2 and 3 after traffic

stresses.

5.4 Sediment Production After Aggregate Placement The second part of this study looked at sediment production after the placement of pit

- run aggregate and Driving Surface Aggregate. As stated earlier, p it

- run is a
term used to describe a relatively cheap locally derived material o f varying quality
and DSA is a specially designed aggregate specification designed to achieve maximum compacted density to resist traffic and erosion. The DSA used in this study was limestone based, although limestone is not required. DSA is a processed commercial product that is typically more expensive than pit

- run. D epending on the site location and aggregate source
, DSA may also have to be hauled a
substantial distance which also increases the cost . The Allegheny National Forest has been using DSA o n roads adjacent to streams in an effort to reduce sediment pollution . More information about DSA is available from PennDOT specification MS

- 0450

- 0004 or from the
Center’s website at www.dirtandgravelroads.o rg

. Previous research conducted by the Center has showed that DSA reduced sediment production by over 90% for at least two years after
p lacement when compared to native surfaced road s in Potter County. This research is also
available on the Center’s website. Figure 5. 16 visua lly depicts each of the four sites for both the existing road surface and the new road aggregate. All four sites showed sediment reductions after new aggregate placement ranging from 39% to 95% compared to the existing road surface. It is worth noting, however, that the two sites w h ere new pit

- run was placed had significantly higher “existing road” sediment production than the two sites where DSA was placed. Th is was not planned and is simply a result random road location when Allegheny National Forest personnel performed work on the road system in early 2011. This higher “existing road” sediment production may have helped show a more significant sediment reduc t ion for the new pit

- run sites. Figur e 5 .15 : Su mmary of sediment reductions found between existing road surfaces and new aggregate surfaces.

### 27

Figure 5. 16 : Visual comparison of the four sites in exiting condition during testing in 2010 and with new aggregate during testing in 2011 . Average sediment production for three runs is included on each photo

.

The two new pit

- run sites examined in this part of the study averaged 26.1 pounds of sediment per 30 minute event. This is slightly higher than the sediment production of 24.7 pounds per event that was found when all 13 “existing condition” tests (excluding gr ass road on site A ) were averaged. This means that while the pit

- run sites did produce reductions in sediment compared to the “existing road” test for their individual sites, the sediment productions found were typical of other existing pit

- run surfaces t ested. The two new DSA sites examined in this part of the study averaged 2.5 pounds of sediment per 30 minute event. This is significantly lower than all of the “existing road” testing done where sediment production averaged 24.7 pounds. Both DSA sites were significantly below the sediment production rates of even the lowest “existing road” test of 7.4 lbs found on site T. In fact, the sediment production from the two DSA sites was most similar to the grassed
road tested on site A. The DSA on site C sh owed an extremely high sediment reduction of
95% , which is similar to previous studies conducted by the Center. The DSA on site C also had the lowest sediment production figure found in the study by far
, even including the grassed road
on Site A (0.8 lbs avg; 1.5 lbs, 0.5 lbs, 0.4 lbs in individual runs) . It should also be noted that

### 28

both DSA sites showed significant reduction in sediment production in sequential runs, an
indication that traffic stre sses between runs did not generate additional sediment f rom the aggregate. This discussion is illustrated in figure 5.17

.

Fig ure 5. 17 : Summary of average sediment production by road type. All figures are in pounds of
s ediment produced per mile of road. Note the differing number of each type of sites that was available for use in obtaining average.

### 29



## CH APTER 6 : Conclusions

The construction and maintenance of access roads is an often
overlooked environmental impact of oil and gas development. Acces s roads can represent a significant change in land use patterns, e s pecially in forested watersheds. These roads, almost all of which are unpaved, not only generate significant sediment, but also add to the hydrologic connectivity of the watershed. The purpose of this study was to quantify
sediment runoff rates from exist ing shallow oil well access road in the Allegheny National Forest. It is important to note that the sediment figures obtained in this study should be considered conservative. Sediment product i on rates from an
actual rain event of similar magnitude can be expected to be higher
because :

 The rainfall simulator produces rainfall on 100’ of roadway. In actual rain events, runoff from upslope sections of roadway would have
entered all of the test section . In addition to rainfall falling directly on
other secti ons of the road, many sites would also experience water running onto the road from adjacent banks, well pads, and other
areas in a nat u ral event. This additional volume of water would have
caused more erosion on each of the test sect i on s

.

 The size and velocity of raindrops from the RainMaker were wit hin the range of natural rain events. Both drop size and velocity, however, were towards the low end of the expected range . Larger drop size and higher vel o city would also contribute to increa sed
sediment detachment.

 The rainfall simulator was only run during the summer and after two days of dry weather. Running the simulator in other times of year, such as during spring thaw, may yield more sediment.
The Center’s rainfall simulator showed that even a modest
rainstorm ( 0.6” in 30 minutes, 2 month

- recurr e nce ) causes these road s to produce significant amounts of sediment. The average sedim ent production from these roads before traffic stresses was 840 po unds per mile for a single 30 minute event. If traffic stresses are introduced onto the road, the average sediment production increases 83% to 1,540 pounds per mile for a single 30 minute event. Figure 6.1 : Testing on site “E”.

### 30 Looking beyond the immediate study watersheds , there were 9,764 existing wells within the Allegheny
National Forest in 200 9 . These wells are accessed by a network of 1, 695 miles of
road
, not including ANF owned roads ( US DA

- FS Unpublished , 20 10 a ). Combining this information with the results of the study indicate that a single
30 minute rainfall event of 0.6” can be

e s timated to generate over 1,106 tons of sediment from existing oil and gas roads in the Allegheny National Forest. Projections are that the network of 1, 695
mil es of existing oil and gas roads will increase to 2, 258 miles by 2020 ( USFS Unpublished,
2010 a ). This increases the estimated sediment production from 1,1 0 6 tons to over 1,470 tons per storm event from oil and gas roads in the forest in 2020

. In order t o minimize sediment delivery to streams
, roads should be built away from streams and avoid stream crossings. Also, roads should be maintained to avoid directing road runoff to streams. Results reported by Bloser and Scheetz [2008] show significant sedim ent
reduction s ranging from 31 % to 94 % by app l ying individual road drainage control practices that
reduce and control the volume of road runoff. These practices include raising the roads profile, installing grade breaks, adding additional drainage out lets, and berm removal

. The combined
sediment reduc t i on effects of these practices have not been studied, but can be expe c ted to be greater than that of the individual practices. Results reported by Bloser and Scheetz [2008] can be used to compare the sed iment production results found on the oil access roads in this study with the Center’s previous RainMaker findings on State Forest and Municipal roads. Please note that the earlier study was completed with the Center’s “first

- generation” RainMaker. The s torm intensities of the first and second generation Rai n Makers are very similar (0.55” per 30 minutes for old and 0.62” per 30 minutes for new), and the procedures used were virtually identical, allowing some generalizations to be made by comparing results of the two studies. The Center’s previous
research was completed on five “as

- is” roads, two municipal owned, and three State Forest
owned. The averaged sediment productions in the previous study ranged from 0.7 pounds to 12.2 pounds, with an average of 5.6 pounds per 30 minute event. The 14 oil access roads in this study ranged from 3.2 pounds to 60 pounds, with an average of 25 pounds per 30 minute Figure 6.2 : This image, taken in the Grunder watershed in late March after a natural rain event, illustrates the effect of poor road material, excessive moisture, and vehicle traffic on sediment generation. (photo courtesy ANF)

### 31

event. The oil access roads in this study produced an average of 450% more sediment than the public roads in the Center’s previous study, despite only a 13% inc rease in rainfall intensity in the new study. This grea t er sediment production is likely due to the lack of consideration of drainage structures, road shape, and quality surface materials. Municipal and Forestry roads are open to the public and must meet user standards, including the passage of passeng e r cars. These access roads have no user standards except to be passable by truck or All Terrain
Vehicle. One of the secondary goal s of this study was to begin to determine which road factors played a role in determining the amount of sediment generated by the various road segments. While none of the individual factors tested (slope, CBR , etc) showed a strong relationship to the amount of sediment produced, there were a number of noteworthy observations:

 There was a significant “First Flush” effect
, in which sediment concentrations in runoff were significantly higher at the beginning of each test, and slowly decreased over each 30 minute event (Details in Figure 5.1).

 Roads that served as “trunk lines” or accessed more well pad s had a higher CBR indicating they have much more compacted surfaces . These roads also showed the
lowest percentage of sediment increases after being stressed by traffic. R oads with lower traffic showed large increases in sediment p roduction after traffic stresses.

 Site “ A ” was similar to all other sites, except that the low amount of traffic on the road allowed the establishment of grass over most of the road surface. Site “ A ” had the lowest
CBR and was the most impacted by traff ic stresses. Traffic removed some grass cover and created rutting, causing sediment production to increase over 600% between run 1
and run 3. Despite its relatively steep slope (14.7%), Site A produced significantly less
sediment than the other sites ( 3.2 pounds on S ite A versus 24.7 pound average for other
sites ). Furthermore, during Run 1 of the RainMaker before traffic, sediment production from this site was only 1.0 pound in 30 minutes. This would suggest that significant
sediment redu c tions coul d be achieved by establishing grass on access roads with low
traffic volumes.

 Without traffic stress, the best indicators of sediment product i on from the roads test ed

were road slope combined with road width. If the road is stressed by traffic , then sedim ent production becomes less depend e nt on road width and slope, and mor e depende nt on road strength as measured by the California Bearing Ratio

. The second component of this study looke d at changes in sediment produc t i on after the placement of new pit

- run and Driving Surface Aggregate surfaces. While b oth new pit

- run surfaces reduced sediment compared to the “existing road” tests, the amount of sediment produced was consistent with the average sediment production for all 13 “existing condition”

### 32

road tests as illustrated in figure 5. 17 . Because pit

- run material is simply excavated instead of
mined and processed, there is little q uality control and the product is highly variable. The use of pit

- run material represents the traditional approach to road maintenance for this part of Pennsylvania.
The sediment production rates found for the two DSA sites was approximately one

- tenth that of the pit

- run surfaces. This is consistent with previous research done by the Center that showed sediment production rat es well below 1 pound per run for at least two years after DSA placement on two separate sites in Potter County, PA, in 2008. DSA has been in use since 2000 in Pennsylvania and was designed to resist erosion and to pr o vide a longer lasting road
surface an d reduce runoff pollution to nearby streams. From this study and previous testing, it is clear that Driving Surface Aggregate significantly reduces sediment production compared to traditional “locally derived materials”. It is also important to note that the two DSA sites tested both showed a significant decrease in sediment in sequential individaul runs despite being subjected to traffic between runs. This shows that DSA provides greater surface durability and structural support for traffic loads. This is evidence that a hard and well graded aggregate is less likely to break down into finer particles under traffic and subsequently leave the road composite in storm run

- off or as dust. The likely result is significantly longer maintenance cycles related to required grading and/or re

- graveling (i.e.

– a longer elapsed time between needed reshaping of the road surface or replenishment of surface material). Along with the potential for significant long term environmental benefits, the long

- range economic be nefits should be considered when selecting road surface materials. In prioritizing the selection of different road surface materials, factors such as anticipated volume and type of traffic (mining and timber hauling), and proximity to surface waters might be emphasized.
While the environmental and traffic resistance road benefits of DSA may be apparent , it s

use does represent a significant cost increas e over locally derived materials such as pit

- run. This is especially tru e in locations such as the Allegh eny National Forest where DSA must be imported significant distances. In 2011, DSA was approxi mately 2.5 times more expensive than pit

- run for locations in the Allegheny National Forest. It is up t o individual road managers and departments to weight the benefits of DSA against the increase in cost. Over the past decade as aggregate costs have risen, Allegheny National Forest personnel have been focusing their DSA usage to environmentally sensitive locations. These include stream crossings and
streamside locations where road runoff to t he stream is unavoidable. DSA is typically used in approximately 300 foot stretch es around such streamside locations

. DSA has also been used on roads experiencing h igher traffic loads and volumes since it tends to hold up better to those
stresses. Sections of road that are not near streams and do not have excessive traffic have

### 33

continued to be surfaced with cheaper materials such as p it

- run. Additonally, considerat ion should be given to avoiding direct road discharge into streams throug the use of imporved drainage practices, regardless of the road surface selected . These drainage improvements may prove to be a more cost

- effective way to reduce sediment pollution t han the use of DSA alone

. However, i t is clear that the Allegheny National Forest’s use of DSA in locations where direct runoff to the stream is unavoidable is an effective practice to reduce sediment pollution.

Future Research This study was an effort to begin quantifying the sediment pollution generated by oil access roads on the Allegheny National Forest. The results of the study, with average sediment production of 1,300 pounds per mile for a single 30 minute 0.61” storm, ill ustrate the magnitude of the problem. There are many other potential topics that should be considered for future study:

 Analysis of the connectivity of the road drainage network and the stream network to
determine how much of the sedim e nt that is produced can be expected to reach a stream.

 Obtain additional data f r o m other test sites within the ANF . The 14 sites tested in this study represent only 1,400 linear feet of roadway, or about 0.02% of the known existing of oil access road in the Allegheny Nation al Forest. More test sites will yield more accurate sediment production figures, and may help to determine which road characteristics are closely tied to sediment production. Even nearby roads, if owned by a different company, may have different sedime n t product i on rates because a different set of standards and practices are used to maintain the road

.

 Obtain additional data f r o m other test sites outside the ANF. Local geolog y and climate play a large role in determining sediment generation from unpaved roads. In addition,

o ther activities, such as wind farms and Marcellus gas d r illing, require access roads of

var yi ng densities and sizes where sediment production has not been quantified.

 In addition to testing “existing” roads, another beneficial study would be to determine sediment reductions achieved by implementing Best Management Practices (BMP) to reduce sediment generation on roads. By running the RainMaker on an existing road, then running it again at various timeframes after BMP installation, th e long term performance of the BMP in reducing sediment pollution could be quantified. For instance, grade brakes, broad

- based dips and maintaining road crown direct runoff to ditches and the forest floor and are effective at reducing runoff on the road s urface. They also reduce the length of roads that are hydrologically connected to streams.

 Run the rainfall simulator on different aggregate such as 2A or 2RC that are widely used for road surfacing throughout Pennsylvania. This can begin to address the question of

### 34

was it actually “DSA” that caused the sediment reduct i ons, or simply the use of a graded limestone aggregate. It is probable that both 2A and 2RC would also have significantly lower sediment productions than pit

- run. It would be useful t o compare their sediment produc t i ons to those of DSA found here and in previous studies.

### 35

REFEREN CES

ANF ( Allegheny National Forest )

. 2007. Final Environmental Impact Statement. Appendix F http://www.fs.fed.us/r9/forests/allegheny/projects/forest_plan_revision/FEIS

- LRMP/ (last accessed 10/26/2010)
Aron, G., D. Wall, E. White, C. Dunn , D. Kotz. 1986

. Field Manual of PA DOT Storm Intensity

- Duration

Frequency charts PDT

- IDF. Pennsylvania Stat e University, 1986
Coe, D. B.R. 2006. Sediment Production and Delivery from Forest Roads in the Sierra Nevada, California. M.S. Thesis, Colorado State University. 2006
Evans, B., S. Sheeder, K. Corradini, and W. Brown, 2003a

. AVGWLF User’s Guide, Version 5.0.2. Pennsylvania State University, Environmental Resources Research Institute, University Park, PA.
Food and Agriculture Organization of the United Nations, 1993

. Field Measurement of Soil Erosion and Runoff. http://www.fao.org/documents/show_cdr.asp?url_file=/ docrep/T0848E/t0848e

11.htm (Last Accessed April, 2006)
Foltz, R.B. 1993. Sediment Processes in Wheel Ruts on Unsurfaced Forest Roads. Ph.D Dissertation. University of Idaho, Moscow, 1993

Kahklen, Keith, 2001. A Method for Measuring Sediment Production from Forest Roads. USDA, Forest Service.
MacDonald L.H., R.W. Sampson, and D.M. Anderson. 2001. Runoff and Road Erosion at the Plot and Road Segment Scales, St. John, US Virgin Islands. Earth Surface Processes and Landforms

. Novotny, V., 2003. Water Quality: Diffuse Pollution and Watershed Management. John Wiley & Sons, Inc., New York.
Pennsylvania Department of Transportation, 1999 . Criteria for Applicability of Hydrologic and Hydraulic Methodologies. http://www.dot.state.pa.us/bridge/standards/Pubs/ 4319911. pdf ( Last Accessed April, 2005)
Pennsylvania Department of Environmental Protection, 2004. Pennsylvania’s Chesapeake Bay Tributary Strategy. http://www.dep.state.pa.us/hosting/pawatersheds/chesapeakebay/ docs/TribStrategy ( Last Accessed July, 2007)
Rogers,R.R. A Short Course in Cloud Physics , 2 ed. Pergamon Press, 1979

Salgado, R., S. Yoon

. 2003

. Dynamic Cone Penetration Assessment for Subgrade Assessment. Civil Engineering Joint Transportation Research Program, Purdue University, 2003.

Scheetz, B.E., S. Bloser. 2008

. Environmentally Sensitive Maintenance Practices for Unpaved Roads: Sediment Reduction Study. Final Report Prepared for Ch esapeake Bay Commission
U.S. Department of Agriculture, Forest Service. 2010. unpublished Programmatic Effects of Private Oil and Gas Activity on the Allegheny National Forest. Pages 4

- 7.
U.S. Department of Agriculture, Forest Service. 2010 a

. Attachments 2 for unpublished Programmatic Effects of Private Oil and Gas Activity on the Allegheny National Forest. Page 23.
Ziegler A.D., R.A. Sutherland, and T.W. Giambelluca. 2000. Partitioning Total Erosion on Unpaved Roads into Splash and Hydraulic Components: The roles of Interstorm Surface Preparation and Dynamic Erodibility. Water Resources Research

.

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## A PPENDIX A

– RainMaker Data

The runoff rates and sediment concentration for all sites in this study are on the following tables. Sites are in order of increasing average sediment production, as listed throughout this report.

### 37

Appendix A: RainMaker Data: 

## SITE A 3.2 lbs average sed iment production

### 38

Appendix A: RainMaker Data: 

## SITE T 7.4 lbs average sediment production

### 39

Appendix A: RainMaker Data: 

## SITE S 7.9 lbs average sediment production

### 40

Appendix A: RainMaker Data: 

## SITE R 11.1 lbs average sediment production

### 41

Appendix A: RainMaker Data: 

## SITE K 12.7 lbs average sediment production

### 42

Appendix A: RainMaker Data: 

## SITE G 13.0 lbs average sediment production

### 43

Appendix A: RainMaker Data: 

## SITE I 14.7 lbs average sediment production

### 44

Appendix A: RainMaker Data: 

## SITE C 14.9 lbs average sediment production

### 45

Appendix A: RainMaker Data: 

## SITE L 28.4 lbs average sediment production

### 46

Appendix A: RainMaker Data: 

## SITE N 29.7 lbs average sediment production

### 47

Appendix A: RainMaker Data: 

## SITE E 35.9 lbs average sediment production

### 48

Appendix A: RainMaker Data: 

## SITE M 42.7 lbs average sediment production

Run 3 could not be complete due to water truck problems . Data in this report for run 3 was extrapolat ed based on the average sediment increase between runs 2 and 3 for the
other 13 sites.

### 49

Appendix A: RainMaker Data: 

## SITE F 43.1 lbs average sediment production

### 50

Appendix A: RainMaker Data: 

## SITE B 60.1 lbs average sediment production

### 51

Appendix A: RainMaker Data: 

## SITE F AFTER NEW PIT RUN
15.4 lbs average sediment production

Note that because the road project affected the drainage pattern of the road, less water was running at the sample point for each of the 4 “after aggregate” tests. For this reason, flow volumes from the “existing road” tests (in red) were used in combination with the “after aggregate” sediment concentration s in order to determine the total volume of sediment that was attributable to the aggregate and not lost water volume.

### 52

Appendix A: RainMaker Data: 

## SITE G AFTER NEW DSA
4.2 l b s average sediment production

Note that because the road project affected the drainage pattern of the road, less water was running at the sample point for each of the 4 “after aggregate” tests. For this reason, flow volumes from the “existing road” tests (in red) were used in combination with the “after aggregate” sediment concentration s in order to determine the total volume of sediment that was attributable to the aggregate and not lost water volume.

### 53

Appendix A: RainMaker Data: 

## SITE B AFTER NEW PIT

- RUN

36.8 l bs average sediment production

Note that because the road project affected the drainage pattern of the road, less water was running at the sample point for each of the 4 “after aggregate” tests. For this reason, flow volumes from the “existing road” tests (in red) were used in combination with the “after aggregate” sediment concentration s in order to determine the total volume of sediment that was attributable to the aggregate and not lost water
v olume.

### 54

Appendix A: RainMaker Data: 

## SITE C AFTER NEW DSA

0.8 l bs average sediment production

Note that because the road project affected the drainage pattern of the road, less water was running at the sample point for each of the 4 “after aggregate” tests. For this reason, flow volumes from the “existing road” tests (in red) were used in combination with the “after aggregate” sediment concentration s in order to determine the total volume of sediment that was attributable to the aggregate a nd not lost water volume.