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Storm Water Runoff from Natural Gas Well Sites in North Texas:

Sampling, Modeling, and Management Options

Kenneth E. BanksDavid J. Wachal

City of Denton, Texas

David Wachal is now with ESRI Professional Services

Research demonstrated within this presentation was partially financed through grants from the U.S. Environmental Protection Agency

US Natural Gas Development end of 2010

Source: The U.S. Energy Information Administration (EIA) “Number of Producing Gas Wells” Release date : 4/30/2012

Texas through 2011: 100,966 I yr. increase of 5952, ~6.3%

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Study Area – Denton, Texas

• Population ~117,000• Denton City Limits ~160 sq km• Denton ETJ ~207 sq km• Rainfall averages 99 cm / yr• In top 10 list of fastest growing cities in the nation

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Cumulative disturbance area for wells drilled 2002-2006

StudyArea

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Sediment

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Heavy Metals

Petroleum Hydrocarbons

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Gas well concerns intensify in urban settings

• Concerns include air emissions, surface contamination, groundwater, noise and light pollution, safety, road damage, property values, effects on soil stability, etc..

• NIMBY now includes NUMBY in the urban setting.

Research Questions

• Is storm water runoff from natural gas well

development sites impacted?

• If so, what impacts exist and to what extent?

• Can impacts be modeled?

• Can impacts be mitigated?

• Do impacts indicate runoff from these sites

should be regulated?

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Research Objectives

1. Characterize storm water runoff

– Sediment

– Petroleum Hydrocarbons

– Heavy Metals

– Water Chemistry

2. Evaluate modeling approaches

3. Develop model parameters using rainfall simulation

4. Evaluate Best Management Practices (BMPs) (modeling-economics)

Study Design and Data Collection

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Natural Gas Well Site

Cut SlopePad Site

Monitoring Point

Runoff

Pressure Transducer

Intake

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10

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Valor > discretionDiscretion is the better part of valor, Act 1

Discretion > Valor

Discretion is the better part of valor, Act 2

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Sampled Events

0

20

40

60

80

100

120

140

160

Site 2

Site 3

Site 4

Site 2R

Site 3R

Rainfall(mm)

25.4 mm = 1 inch

n=17 n=12

n=11

n=5

n=5

Parameters Analyzed

Water Chemistry

Metals Petroleum Hydrocarbons

Sediment

Alkalinity Arsenic TPH TSS

Calcium Cadmium BTEX Turbidity

Chlorides Chromium

Conductivity Copper

Hardness Iron

pH Lead

TDS Manganese

Nickel

Zinc

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Wilcoxon Rank-Sum and Ratio of Medians

Parameter n/n p-value Ratio

Alkalinity 40/10 <0.0001 6.9

Chlorides 40/10 0.0058 1.7

Conductivity 40/10 <0.0001 1.2

Hardness 40/10 <0.0001 3.2

pH 40/10 <0.0001 1.2

TDS 40/10 0.0561 1.2

Calcium 36/8 <0.0001 8.0

TSS 39/8 <0.0001 157.1

Turbidity 37/9 <0.0001 42.5

Iron 36/8 <0.0001 13.5

Manganese 36/8 <0.0001 28.9

Nickel 36/8 0.0027 3.2

(Provided for those with an adequate number of samples above detection)

Metals – Previous Research

Hudak and Banks (2006)“Urban Watersheds”

Kayhanian et al. (2001)“Highway Construction Sites”

Gas Well Site Metals

Reference Site Metals

Gas Well Site Metals

Reference Site Metals

=

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Wilcoxon Rank-Sum and Ratio of Medians

Parameter n/n p-value Ratio

Alkalinity 40/10 <0.0001 6.9

Chlorides 40/10 0.0058 1.7

Conductivity 40/10 <0.0001 1.2

Hardness 40/10 <0.0001 3.2

pH 40/10 <0.0001 1.2

TDS 40/10 0.0561 1.2

Calcium 36/8 <0.0001 8.0

TSS 39/8 <0.0001 157.1

Turbidity 37/9 <0.0001 42.5

Iron 36/8 <0.0001 13.5

Manganese 36/8 <0.0001 28.9

Nickel 36/8 0.0027 3.2

Sediments and Petroleum Hydrocarbons

• Sediment yields at gas well sites in this study ranged from 29 to 41 t/ha/yr

• TPH was below detection limits for all samples

• BTEX was detected in a few gas well sample but EMCs were below the detection limit

• BTEX was detected in all samples at reference site 2R

• TPH / BTEX did not exceed State WQ Standards

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How much is 41 tonnes??

= 2.24 loads

Sediment Concentration (mg/l)

1 10 100 1000 10,000 100,000

Wolman and Schick (1967)

Gas Well Sites

Daniel et al. (1979)

Madison et al. (1979)

Schueler and Lugbill (1990)

Nelson (1996)

Kayhanian et al. (2001)

USGS (2000)

COD - Hickory Creek

Reference Sites

EMC Range

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City Of DentonQuarterly Sampling

Summary

• Petroleum Hydrocarbons were not prevalent in storm water runoff at gas well sites

• Metals at gas well sites were:

– higher than at reference sites

– higher than local urban storm water

– similar to highway construction sites

• Total Suspended Sediment at gas well sites were:

– 157 times higher than at reference sites

– 36 times higher than at the outlet of the Hickory Creek Watershed

– Similar to other types of construction sites

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Evaluation of Runoff and Sediment Yield Predictions

• Evaluate WEPP predictions of runoff and sediment

• Why…

– monitoring data is limited

– can be used to develop “what if” scenarios

– provide defendable information for local decision making

– Allowed modeling of cut and fill slopes as a system

Steps in Model Calibration

• Set parameters (management conditions; soil conditions, etc.)

• Input slope information

• Input climate information

• Run the model

• Compare observed and predicted values

– Error = Observed minus Predicted

• Evaluate error results using goodness-of-fit indicators

• Adjust parameters and rerun the model

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Performance Ratings

(Moriasi et al., 2007)

NSE = Nash–Sutcliffe efficiency (NSE)RSR = ratio of RMSE(root mean square errors) to standard deviation Percent bias (PBIAS) = describes the average tendency of simulated data to be larger or smaller than their observed counterparts.

NSE ranges between negative infinity and 1.0, with NSE = 1 being the optimal value. RSR varies from an optimal value of 0 (which indicates zero RMSE) to a large positive value. The better the model simulation performs, the lower the RMSE , and therefore the lower the RSR score.

Model Validation (17 events)NSE’ = “Very Good” RSR’ = “Very Good” PBIAS’ = “Good/Very Good”

NSE’=.90RSR’=.28PBIAS’=15

NSE’=.99RSR’=.12PBIAS’=-2

NSE’=.86RSR’=.38PBIAS’=16

NSE’=.86RSR’=.38PBIAS’=-11

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Summary

• The results demonstrate that WEPP can effectively model runoff and sediment from natural gas well sites

• Therefore, the model can be used to…

– Evaluate potential sediment impacts

– Evaluate management alternatives to minimize impacts

• Work suggested future rainfall simulation study to better parameterize the “pad” portion of the site. From a storm water perspective, the pad is quite complex…….

Rainfall Simulation Study Design

• Dry Run - 58 mm/hr on existing soil conditions

• Wet Run - 58 mm/hr, applied 24 hours after dry run

• Very Wet Run

• - 58 mm/hr

– increased to 104 mm/hr

– decreased to 58 mm/hr

– Applied 30 minutes after wet run

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Data Collection

Modeling• Used WEPP to model runoff and sediment from plot area

for each plot and each run type (18 runs)

– Input calculated Ki values (interrill erodibility (mass-time/length4))

– Adjusted Kef (effective conductivity) until predicted runoff equaled observed runoff

NSE = .90 = “very good” RSR = .30 = “very good”PBIAS = 13.7 = “very good”

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Modeling Continued…

• WEPP was run in continuous simulation mode (30-years)

• Predicted annual average sediment yields for pad sites (t/ha/yr)

– Ranged from 5.0 to 11.0

– Average of 7.4

Results

• Interrill Erodibility (Ki) parameter for gas well pad sites = mean of 681,699 kg s/m4

• Hydraulic Conductivity (Kef) parameter = mean of 30 mm/hr

• Sediment yield from the “pad” portion of a gas well site ranges from 5.0 to 11.0 t/ha/yr

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Modeling Erosion and Sediment Control BMPs

• Evaluate the effectiveness of six BMPs –specifically for natural gas well sites

• Demonstrate a practical approach for quantitatively evaluating BMP alternatives based on

– Soil type

– Slope condition

– Site management goals

– Implementation cost

Methodology• For each slope and soil combination sediment

yields were modeled with and without BMPs

• BMP Efficiencies were calculated accordingly:

ER = (SYwithout BMP – SYwithBMP) / SYwithout BMP

ER = (50 tons – 10 tons) / 50 tons = 80% efficiency

Mulching Filter Strip Silt Fence

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Percent Slope

Modeled Site Slopes

0

1

2

3

4

5

0 20 40 60 80 100

0

1

2

3

0 20 40 60 80 100

4.5% Slope2.9% Slope1.8% Slope

Each slope was simplified to 9 slope segment for modeling

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Methodology• For each slope and soil combination sediment

yields were modeled with and without BMPs

• BMP Efficiencies were calculated accordingly:

ER = (SYwithout BMP – SYwithBMP) / SYwithout BMP

ER = (50 tons – 10 tons) / 50 tons = 80% efficiency

ResultsSediment Yield without BMPs (tonnes/ha/yr)

K-factor

0.17

Sandy Loam

K-factor

0.32

Clay Loam

K-factor

0.43

Silty Clay Loam

1.8% slope

12.1 19.5 29.1

2.9% slope

24.7 38.1 60.5

4.5% slope

56.0 85.2 134.5

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BMP Cost / Efficiency Example(Moderate Slope/Moderate Erodibility)

$0

$1,000

$2,000

$3,000

$4,000

$5,000

$6,000

$7,000

$8,000

$9,000

Seeding Mulching ErosionBlanket

Silt Fence Filter Strip SedimentBasin

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

BMP Site Cost Effeciency

BMPSiteCost

ER

Site Management Goal

Site Management Goal – measure of the acceptable level of reducedsediment yield through erosion prevention and sediment removal

Efficiency

Findings• With BMPs, sediment yields can be reduced by 50 to over 90

percent according to model results

• Soils and slope both influence BMP efficiency

• Methodology can be used to assist in the selection of BMPs according to various site factors and BMP site costs.

Note: The Reasonable and Prudent Practices for Stabilization (RAPPS) of Oil and Gas Construction Sites document used portions of this research to establish “decision trees” of management practices based on slope, rainfall-runoff erosivity factor (R), and soil characteristics

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Conclusions• Sediment yields at gas well sites in this study ranged from 29

to 41 t/ha/yr

• Metal concentrations were higher at gas well sites compared to reference sites and local urban watersheds

• WEPP was able to effectively model runoff and sediment yield from gas well sites

• Parameters were specifically developed for gas well pad sites – modeled average sediment yields from the pad site were 7.4 t/ha/yr over 30 year period

• Best Management Practices could reduce sediment yields by 50 to 90% for entire site

Recommendations

• Municipal / state governments should consider implementing erosion and sediment control provisions for natural gas development

• Types of erosion and sediment controls should be selected according to site-specific conditions. Selections can be refined by considering costs and efficiencies of BMPs

• Future research should focus on additional rainfall simulation studies and gas well site BMPs

slope K factor Management options

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Additional informationhttp://www.epa.gov/npdespub/stormwater/oilgas/

Wachal, D.J. and K.E. Banks and D.H. Hunter. 2006. “Collecting Stormwater at Small Gas Well Exploration and Production Sites”. Published in the Watershed and Wet Weather Technical Bulletin 11(6):10-15

Banks, K.E and D.J. Wachal. 2007. "Water Quality and Land Use: Analyzing relationships among multiple watersheds using contingency analysis". Stormwater: January / February 2007.

Wachal, D.J. and K.E. Banks. 2007. “Application of WEPP to Natural Gas Exploration and Production Sites”. Published in Proceedings of the American Society of Agricultural and Biological Engineers (ASABE): Fourth Conference on Watershed Management to Meet Water Quality and TMDL Issues: Solutions and Impediments to Watershed Management and TMDLS. March 2007.

Wachal, D.J. and K.E. Banks. 2007. “Sediment Impacts from Natural Gas Exploration and Production Sites”. Published in the proceedings of 2007 Annual International Meeting of the American Society of Agricultural and Biological Engineers (ASABE). June 17-20, 2007, Minneapolis, Minnesota.

Wachal, D.J. and K.E. Banks. 2007. “Integrating GIS and Erosion Modeling: A Tool for Watershed Management”. Published in the proceedings of the Twenty-Seventh Annual ESRI International User Conference 2007. June 18-22, 2007, San Diego, California.

Williams, H.F.L., D.L.Havens, K.E. Banks, and D.J. Wachal. 2007. Field-Based Monitoring of Sediment Runoff from Natural Gas Well Sites in Denton County, Texas, USA. Environmental Geology DOI 10.1007/s00254-007-1096-9.

Wachal, D.J., R.D. Harmel, K.E. Banks and P.F. Hudak. 2008. Evaluation of WEPP for Runoff and Sediment Yield Prediction on Natural Gas Well Sites. Transactions of ASABE 51(6): 1977-1986.

Wachal, D.J., K.E. Banks, P.F. Hudak and R.D. Harmel. Modeling Erosion and Sediment Control Practices with RUSLE 2.0: A Management Approach for Natural Gas Well Sites in Denton County, Texas, USA. Environmental Geology. DOI 10.1007/s00254-008-1259-3.

Havens, D.L. 2007. Assessment of Sediment Runoff from Natural Gas Well Development Sites. Masters Thesis, University of North Texas, Denton, Texas.

More information about WEPP can be found at http://www.ars.usda.gov/Research/docs.htm?docid=10621 (USDA Agricultural Research Service)

Contact Information

Kenneth Banks, Ph.D.

City of Denton

Phone: (940) 349-7165

email: kenneth.banks@cityofdenton.com