Licking Creek Sediment TMDL

Franklin County, Pennsylvania

Prepared by:

Approved by EPA, May 25, 2021

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TABLE OF CONTENTS

EXECUTIVE SUMMARY......................................................................................................................................................................................... 1

Table 1. Summary of Annual Average TMDLAvg Variables for the Licking Creek Subwatershed .............................. 1

Table 2. Summary of 99th Percentile Daily Loading TMDLMax Variables for the Licking Creek Subwatershed ........ 1

INTRODUCTION ...................................................................................................................................................................................................... 2

Table 3. Aquatic-Life Impaired Stream Segments in the Licking Creek Subwatershed per the 2018 Final

Pennsylvania Integrated Report ................................................................................................................................ 3

Figure 1. Licking Creek Subwatershed. ...................................................................................................................... 4

Table 4. Existing NPDES Permitted Discharges in the Licking Creek Subwatershed and their Potential Contribution

to Sediment Loading. ................................................................................................................................................ 5

TMDL APPROACH ................................................................................................................................................................................................... 8

SELECTION OF THE REFERENCE WATERSHED ....................................................................................................................................... 8

Table 5. Comparison of the Impaired (Licking Creek) and Reference (Wooden Bridge Creek) Watersheds. ............ 9

Table 6. Existing NPDES Permitted Discharges in the Wooden Bridge Creek Subwatershed and their Potential

Contribution to Sediment Loading. ......................................................................................................................... 12

Figure 2. Licking and Wooden Bridge Creek Subwatersheds. ................................................................................. 15

Figure 3. Wooden Bridge Creek Subwatershed. ...................................................................................................... 16

Figure 4. Substrate conditions within valley reaches of the Licking Creek Subwatershed. ..................................... 17

Figure 5. Substrate conditions within the mountain/hilly reaches of the Licking Creek Subwatershed. ................. 18

Figure 6. Landscapes within the Licking Creek Subwatershed. ............................................................................... 19

Figure 7. Agricultural practices in the Licking Creek Subwatershed that may exacerbate sediment loading ......... 20

Figure 8. Agricultural practices in the Licking Creek Subwatershed that may be protective against sediment

loading .................................................................................................................................................................... 21

Figure 9. Stream substrate conditions in the Wooden Bridge Creek Subwatershed. .............................................. 22

Figure 10. Example landscapes within in the Wooden Bridge Creek Subwatershed. .............................................. 23

Figure 11. Example practices in the Wooden Bridge Creek Subwatershed that may be protective against

agricultural pollution. ............................................................................................................................................. 24

Figure 12. Example practices in the Wooden Bridge Creek Subwatershed that may exacerbate sediment loading.

................................................................................................................................................................................ 25

HYDROLOGIC / WATER QUALITY MODELING ....................................................................................................................................... 26

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Figure 13. Riparian buffer analysis in the Licking Creek Subwatershed .................................................................. 29

Figure 14. Riparian buffer analysis in the Wooden Bridge Creek Subwatershed. ................................................... 30

CALCULATION OF THE TMDL ........................................................................................................................................................................ 31

Table 7. Existing Annual Average Loading Values for the Wooden Bridge Creek Subwatershed, Reference ......... 31

Table 8. Existing Annual Average Loading Values for the Licking Creek Subwatershed, impaired ........................ 31

Table 9. Calculation of the Annual Average Sediment TMDL Value for the Licking Creek Subwatershed ............. 32

CALCULATION OF LOAD ALLOCATIONS ................................................................................................................................................... 32

MARGIN OF SAFETY .......................................................................................................................................................... 33

WASTELOAD ALLOCATION .................................................................................................................................................. 33

Table 10. Annual Average Wasteload Allocations for Existing NPDES Permitted Discharges in the Licking

Creek Subwatershed ............................................................................................................................................... 33

LOAD ALLOCATION ............................................................................................................................................................ 35

LOADS NOT REDUCED AND ADJUSTED LOAD ALLOCATION ........................................................................................................ 35

Table 11. Average Annual Load Allocation, Loads Not Reduced and Adjusted Load Allocation ............................ 35

CALCULATION OF LOAD REDUCTIONS ..................................................................................................................................................... 36

Table 12. Annual Average Sediment Load Allocations for Source Sectors in the Licking Creek Subwatershed ...... 36

CALCULATION OF DAILY MAXIMUM “TMDLMAX” VALUES ................................................................................................................ 36

Table 13. Calculation of TMDLMax Value for the Licking Creek Subwatershed ........................................................ 37

Table 14. Wasteload Allocations during 99th percentile loading for Existing NPDES Permitted Discharges in the

Licking Creek Subwatershed .................................................................................................................................. 37

Table 15. 99th Percentile of Daily Loading TMDL (TMDLMax) Variables for the Licking Creek Subwatershed ......... 39

Table 16. Allocation of the 99th Percentile Daily Sediment Load Allocation (LAMax) for the Licking Creek

Subwatershed ......................................................................................................................................................... 39

CONSIDERATION OF CRITICAL CONDITIONS AND SEASONAL VARIATIONS ......................................................................... 40

SUMMARY AND RECOMMENDATIONS ...................................................................................................................................................... 40

PUBLIC PARTICIPATION .................................................................................................................................................................................. 41

CITATIONS .............................................................................................................................................................................................................. 41

APPENDIX A: BACKGROUND ON STREAM ASSESSMENT METHODOLOGY ................................................................. 43

Table A1. Impairment Documentation and Assessment Chronology ...................................................................... 45

APPENDIX B: MODEL MY WATERSHED GENERATED DATA TABLES ........................................................................................ 48

Table B1. “Model My Watershed” Land Cover Outputs for the Licking Creek Subwatershed. ............................... 49

Table B2. “Model My Watershed” Land Cover Outputs for the Wooden Bridge Creek Subwatershed. ................. 49

Table B3. “Model My Watershed” Hydrology Outputs for the Licking Creek Subwatershed ................................. 50

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Table B4. “Model My Watershed” Hydrology Outputs for the Wooden Bridge Creek Subwatershed. .................. 50

Table B5. Model My Watershed outputs for sediment in the Licking Creek Subwatershed. .................................. 51

Table B6. Model My Watershed outputs for sediment in the Wooden Bridge Creek Subwatershed. .................... 51

APPENDIX C: STREAM SEGMENTS IN THE LICKING CREEK SUBWATERSHED WITH SILTATION IMPAIRMENTS ...................................................................................................................................................................................................................................... 52

Table C1. Stream segments with siltation impairments in the Licking Creek Subwatershed. ................................ 56

APPENDIX D: EQUAL MARGINAL PERCENT REDUCTION METHOD ............................................................................................ 57

Table D1. Sediment Equal Marginal Percent Reduction calculations for the Licking Creek Subwatershed. .......... 59

APPENDIX E: LEGAL BASIS FOR THE TMDL AND WATER QUALITY REGULATIONS FOR AGRICULTURAL OPERATIONS ......................................................................................................................................................................................................... 60

CLEAN WATER ACT REQUIREMENTS ..................................................................................................................................... 61

PENNSYLVANIA CLEAN STREAMS LAW REQUIREMENTS, AGRICULTURAL OPERATIONS..................................................................... 62

APPENDIX F: COMMENT AND RESPONSE ................................................................................................................................................ 63

1

Executive Summary

“Total Maximum Daily Loads” (TMDLs) for sediment were developed for the Licking Creek Subwatershed

(Figure 1) to address the siltation impairments noted in the 2018 Final Pennsylvania Integrated Water

Quality Monitoring and Assessment Report (Integrated Report), including the Clean Water Act Section

303(d) List. Agriculture and grazing related agriculture were identified as the cause of these impairments.

Because Pennsylvania does not have numeric water quality criteria for sediment, the loading rates from a

similar unimpaired watershed were used to calculate the TMDLs.

“TMDLs” were calculated using both a long-term annual average value (TMDLAvg) which would be protective

under most conditions, as well as a 99th percentile daily value (TMDLMax) which would be relevant to

extreme flow events. Existing annual average sediment loading in the Licking Creek Subwatershed was

estimated to be 8,059,738 pounds per year. To meet water quality objectives, annual average sediment

loading should be reduced by 36% to 5,123,400 pounds per year. Allocation among the annual average

TMDL variables is summarized in Table 1. To achieve these reductions while maintaining a 10% margin of

safety and an allowance for point sources, annual average sediment loading from croplands should be

reduced by 45% whereas loading from hay/pasture lands, and streambanks should be reduced by 42%

each.

Table 1. Summary of Annual Average TMDLAvg Variables for the Licking Creek Subwatershed

lbs/yr:

Pollutant TMDLAvg MOSAvg WLAAvg LAAvg LNRAvg ALAAvg

Sediment 5,123,400 512,340 66,591 4,544,469 39,212 4,505,256

TMDL=Total Maximum Daily Load; MOS = Margin of Safety; WLA=Wasteload Allocation (point sources); LA = Load Allocation (nonpoint sources). The LA is further divided into LNR = Loads Not Reduced and ALA=Adjusted Load Allocation. Subscript “Avg” indicates that these values are expressed as annual averages.

Current 99thpercentile daily loading in the Licking Creek Subwatershed was estimated to be 235,368

pounds per day of sediment. To meet water quality objectives, 99th percentile daily sediment loading

should be reduced by 37% to 147,166 pounds per day. Allocation of the 99th percentile daily TMDL

variables is summarized in Table 2.

Table 2. Summary of 99th Percentile Daily Loading TMDLMax Variables for the Licking Creek Subwatershed

lbs/d:

Pollutant TMDLMax MOSMax WLAMax LAMax LNRMax ALAMax

Sediment 147,166 14,717 1,726 130,724 1,128 129,596

TMDL=Total Maximum Daily Load; MOS = Margin of Safety; WLA=Wasteload Allocation (point sources); LA = Load Allocation (nonpoint sources). The LA is further divided into LNR = Loads Not Reduced and ALA=Adjusted Load Allocation. Subscript “Max” indicates that these values are expressed as 99th percentile for daily loading.

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Introduction

Licking Creek is a tributary of the West Branch of the Conococheague Creek, with the confluence

approximately 3.5 miles southeast of Mercersburg Borough. This Total Maximum Daily Load (TMDL)

document has been prepared to address the siltation impairments noted for a subwatershed of Licking

Creek per the 2018 Final Integrated Report (see Appendix A for a description of assessment methodology).

The study watershed (Figure 1) contained approximately 90 stream miles, all of which were designated for

trout stocking (Table 3).

Agriculture and grazing related agriculture were identified as the source of the impairments. The removal

of natural vegetation and disturbance of soils associated with agriculture increases soil erosion leading to

sediment deposition in streams. Excessive fine sediment deposition may destroy the coarse-substrate

habitats required by many stream organisms.

While Pennsylvania does not have numeric water quality criteria for sediment, it does have applicable

narrative criteria:

Water may not contain substances attributable to point or nonpoint source discharges in concentration or amounts sufficient to be inimical or harmful to the water uses to be protected or to human, animal, plant or aquatic life. (25 PA Code Chapter 93.6 (a)); and, In addition to other substances listed within or addressed by this chapter, specific substances to be controlled include, but are not limited to, floating materials, oil, grease, scum and substances which produce color, tastes, odors, turbidity or settle to form deposits. (25 PA Code, Chapter 93.6 (b)).

While agriculture has been identified as the source of the impairments, this TMDL document is applicable to all significant sources of sediment and solids that may settle to form deposits.

According to the “Model My Watershed” application, land use in this watershed is estimated to be 46%

forest/naturally vegetated lands, 48% agriculture, and 6% mixed development (including developed open

space). The agricultural lands were approximately equally divided between croplands (22% of total

landcover) and pasture/hay lands (26% or total land cover, see Appendix B, Table B1). There were eight

NPDES permitted discharges in the watershed where sufficient information existed to estimate their

contribution to point source sediment loading (Table 4). All were small facilities and minor sediment

sources.

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Table 3. Aquatic-Life Impaired Stream Segments in the Licking Creek Subwatershed per the 2018 Final Pennsylvania Integrated Report

HUC: 2070004 – Conococheague

Source EPA 305(b) Cause

Code Miles Designated Use

Grazing Related

Agriculture Nutrients 6.8 TSF, MF

Ag. or Grazing Related

Ag. Siltation 25.6 TSF, MF

HUC= Hydrologic Unit Code; TSF=Trout Stocking; MF= Migratory Fishes The use designations for the stream segments in this TMDL can be found in PA Title 25 Chapter 93. See Appendix C for a listing of each stream segment and Appendix A for more information on the listings and listing process

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Figure 1. Licking Creek Subwatershed. Stream segments within the watershed were either listed as

attaining for aquatic life use, impaired for siltation, or impaired for siltation and nutrients per the 2018

final Integrated Report (see PA DEP’s 2018 Integrated Report Viewer available at:

https://www.depgis.state.pa.us/integrated_report_viewer/index.html)

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Table 4. Existing NPDES Permitted Discharges in the Licking Creek Subwatershed and their Potential Contribution to Sediment Loading. Based on permit limits Based on eDMR data

Permit No. Facility Name mean lb/yr max lb/d mean lbs/yr max lbs/d

PAG123849 Herbruck Poultry Ranch, Inc. NA NA NA NA

PA0085979 Guest Farm Village WWTP 1,095 19 83 20

PAM417009 McCulloh Long Farm Quarry NA NA NA NA

PA0085278 Deerwood Mtn Estates WWTP 12,024 198 5 0.7

PA0087050 Valley Creek Estates 1,142 19 332 42

PAG043919 Tonia Metcalf SFS 8 0.07 NA NA

PAG043917 Jason Petre SFTF 16 0.13 NA NA

PA0080608 Camp Tohiglo WWTP 1,096 18 42 7

PA0080501 Montgomery Elem WWTP 53 0.9 14 1.7

PAG043903 Twin Hill Meadows Phase II 32 0.3 NA NA

Permits within the watershed were based on DEP’s eMapPA available at http://www.depgis.state.pa.us/emappa/ and EPA’s Watershed Resources Registry

available at https://watershedresourcesregistry.org/map/?config=stateConfigs/pennsylvania.json

eDMR= electronic discharge monitoring report, which may be generated at

http://cedatareporting.pa.gov/Reportserver/Pages/ReportViewer.aspx?/Public/DEP/CW/SSRS/EDMR

NA – Not applicable.

In Pennsylvania, routine, dry-weather discharges from concentrated animal feeding operations (CAFOs) are not allowed. Wet weather discharges are controlled

through best management practices (BMPs), which result in infrequent discharges from production areas and reduced sediment loadings from lands under the

control of CAFOs owner or operators, such as croplands where manure is applied. Although not quantified in this table, sediment loadings from CAFOs is

accounted for in the modeling of land uses within the watershed, with the assumption of no additional CAFO-related BMPs.

Note that given their transient nature, any stormwater construction permits were not included above.

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Guest Farm Village.

Permit based values. Permit issued November 16, 2017 and amended February 22, 2018 lists a 3 lbs/d average monthly TSS limit, which was multiplied by 365 days in a year to calculate the mean annual load. The maximum daily concentration was calculated using their instantaneous maximum TSS concentration limit of 20 mg/L and their design flow of 0.0372 MGD times a peaking factor of 3 per their permit.

eDMR based values. During preparation of the initial draft of this TMDL, eight months of eDMR data were available for this facility. For the average annual sediment load, the monthly average values in lbs/d for these 8 months was averaged and the resultant value was multiplied by 365 days in a year. Maximum daily sediment load was calculated using the highest reported daily maximum flow for these 8 months along with the assumption that they discharged at their instantaneous maximum permitted TSS concentration limit of 20 mg/L.

McCulloh Long Farm Quarry.

While the permit gives TSS concentration limits of 35 mg/l 30-day average, 70 mg/l daily max and 90 mg/l instantaneous max, total settleable solids by volume may be measured as an alternative, and there was no requirement to measure flow. Thus, there were effectively no load limits for this facility. Note however, this pollution source may be accounted for in the nonpoint source modelling by land use.

Deerwood Estates.

Permit based values. According to their permitting fact sheet, this facility had a design flow of 0.018 MGD, but they have received approval to expand to 0.395 MGD. The higher of these flow values, along with a 10 mg/L TSS concentration limit per their permit issued December 20, 2018 was used to calculate the permit based annual average sediment loading. The same flow value times a peaking factor of 3 along with their permitted instantaneous maximum TSS concentration limit of 20 mg/L was used to calculate the maximum daily sediment load.

eDMR based values. For the annual average sediment load, two full years of monthly reported TSS concentrations (in mg/L) and average monthly flow values (in MGD) were used to calculate the average load for each month in lbs/d. This value was then multiplied by the number of days in a month and all months of the year were summed to calculate two annual loads that were then averaged. For the maximum daily sediment load, the daily maximum flow value reported from November 2017 to July 2020 was used along with the instantaneous maximum permitted TSS concentration of 20 mg/L to generate the maximum value was reported in the above table.

Valley Creek Estates.

Permit based values. Their permit issued August 30, 2018 lists a 30 mg/L average monthly total suspended solids concentration, and this value, along with their design flow of 0.0125 MGD was used to calculate the annual average value reported in the above table. For the maximum daily sediment load, the design flow with peaking factor of 3 along with the permit’s instantaneous maximum total suspended solids concentration of 60 mg/L was used to derive the daily maximum sediment load. eDMR based values. For the annual average sediment load, two full years (2018-2019) of data where the average monthly flow was reported were analyzed. These flow values, with the reported average monthly TSS concentrations, were used to calculate the monthly average sediment load in lbs/d. These values were multiplied by the number of days in each month, and the monthly total loads were added within each year to calculate the total annual load. The two total annual loads were then averaged to generate the value reported above. For the daily maximum sediment load, the daily maximum flow in eDMR data from November 2017 through July 2020 was used along with an instantaneous maximum permit value of 60 mg/L TSS.

Tonia Metcalf.

Small flow wastewater treatment facility for a single-family residence. Assume an average daily flow of 262.5 gpd and a daily maximum flow of 400 gpd. The average flow with an average monthly TSS concentration of 10 mg/L was used to calculate the annual average loadings. A 20 mg/L TSS concentration along with an assumed peak daily flow of 400 gpd were used to calculate the daily max loads. No eDMR data were available.

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Jason Petre.

Small flow wastewater treatment facility serving two adjacent residences per the water quality management permit issued June 2012. Assume an average daily flow of 525 gallons per day and a maximum flow of 800 gallons per day. The average flow with an average monthly TSS concentration of 10 mg/L was used to calculate the annual average loadings. A 20 mg/L TSS concentration along with the assumed peak daily flow were used to calculate the daily max load. TSS concentration limits were based on the NPDES permit issued June 15, 2012. No eDMR data were available.

Camp Tohiglo. eDMR based values. The average annual sediment load was determined based on three full years of data for which there were average monthly flow and average monthly TSS concentrations reported. These values were used to calculate the average TSS load for each month, and then all months within the year were summed to calculate an annual load. The three annual loads were then averaged to calculate the average annual load. The daily max sediment load was calculated using the reported daily maximum flow value for each month from January 2017 through July 2020. The highest of these flows, with an assumed 60 mg/L TSS concentration (the instantaneous maximum permit value) were used to calculate the maximum daily load. Permit based values. Their permit issued April 2017, 2019 listed a design flow of 0.012 MGD and average monthly effluent limits of 30 mg/L TSS. These values were used to estimate the mean annual sediment load. The maximum daily sediment load was calculated using an assumed peaking factor of 3 for the average annual flow and the instantaneous maximum TSS concentration of 60 mg/L.

Montgomery Elementary WWTP.

eDMR based values. Average annual sediment load was based on two full years of eDMR data where average monthly flow and TSS concentration were reported for each month (2018 and 2019). For each month, the average daily load was calculated. The average daily load was multiplied by the number of days in each month, and all the months were summed to calculate an annual load. The two years were then averaged to calculate the mean annual load reported in the table. The daily maximum sediment load was calculated based on monthly reported daily maximum flows from November 2017 through July 2020 and an instantaneous maximum permit value of 20 mg/L TSS. The highest value was reported above. Permit based values. Their permit issued December 20, 2018 lists a flow value of 0.00175 MGD. This value, along with an average monthly TSS concentration limit of 10 mg/L was used to calculate their average annual sediment load. The aforementioned design flow with a peaking factor of 3, along with the instantaneous maximum TSS permit concentration limit of 20 mg/L was used to calculate the daily max sediment load.

Twin Hills Meadows Phase II.

As of August 2017, the site had not been developed. Due to unknown current status but likely minimal influence, it was included as an existing pollutant source nevertheless. Based on their permit issued January 20, 2011, this was a small flow wastewater treatment facility with a design flow of 0.0016 MGD. Additional permitting information indicates that it was to serve four residences. Thus, assuming an average flow of 262.5 gpd/residence, average flow is estimated at 1050 gpd or 0.001050 MGD. The average flow, along with an average monthly TSS concentration limit of 10 mg/L was used to calculated average annual sediment load. The design flow, along with an instantaneous maximum TSS concentration limit of 20 mg/L was used to calculate the maximum daily load.

8

TMDL Approach

Although watersheds must be handled on a case-by-case basis when developing TMDLs, there are basic

processes that apply to all cases. They include:

1. Collection and summarization of pre-existing data (watershed characterization, inventory

contaminant sources, determination of pollutant loads, etc.);

2. Calculation of a TMDL that appropriately accounts for any critical conditions and seasonal

variations;

3. Allocation of pollutant loads to various sources;

4. Submission of draft reports for public review and comments; and

5. EPA approval of the TMDL.

Because Pennsylvania does not have numeric water quality criteria for sediment, the “Reference

Watershed Approach” was used. This method estimates loading rates in both the impaired watershed as

well as a similar watershed that is not listed as impaired. Then, the loading rates in the unimpaired

watersheds are scaled to the area of the impaired watershed so that necessary load reductions may be

calculated. It is assumed that reducing loading rates in the impaired watershed to the levels found in the

unimpaired watershed will result in the impaired stream segments attaining their designated uses.

Selection of the Reference Watershed

In addition to anthropogenic influences, there are many other natural factors affecting sediment loading

rates and accumulation within a watershed. Thus, selection of a reference watershed with similar natural

characteristics as the impaired watershed is crucial. Failure to use an appropriate reference watershed

could result in problems such as the setting of reduction goals that are unattainable, or nonsensical TMDL

calculations that suggest that loadings in the impaired watershed should be increased.

To find a reference site, the Department’s Integrated Report GIS-based website (available at

https://www.depgis.state.pa.us/integrated_report_viewer/index.html), or GIS layers consistent with the

integrated report, was used to search for nearby watersheds that were of similar size as the Licking Creek

Subwatershed but lacked stream segments listed as impaired for aquatic life. Once potential references

were identified, they were screened to determine which ones were most like the impaired watershed with

regard to factors such as landscape position, topography, bedrock geology, hydrology, soil drainage types,

land use etc. Furthermore, benthic macroinvertebrate and physical habitat assessment scores were

reviewed to confirm that a reference was acceptable. Preliminary modelling was conducted to make sure

that use of a particular reference would result in reasonable pollution reductions. A particular challenge in

finding a reference for the Licking Creek Subwatershed was its very large size, as it is difficult to find a

comparably sized watershed that lacked aquatic life impairments. This factor alone disqualified the use of

many nearby reference watersheds.

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Considering that it was nearby (only about 15 miles away), occupied a similar landscape position, was

within the Appalachian Mountain Section of the Ridge and Valley Physiographic Province (Figure 2), and not

listed as impaired for sediment, the Wooden Bridge Creek in Fulton County was explored for use as a

reference. Since it is required that the reference watershed be +/-30% of the impaired watershed’s area, a

delineation point was chosen upstream of the mouth of Wooden Bridge Creek to create a subwatershed

that was approximately the same size as the impaired watershed (Figure 3).

It was ultimately concluded that the Wooden Bridge Creek Subwatershed was a suitable reference (Table

5).

Table 5. Comparison of the Impaired (Licking Creek) and Reference (Wooden Bridge Creek) Watersheds.

Licking Creek Wooden Bridge Creek

Phys. Province1

61% Great Valley Section

of the Ridge and Valley

Province

39% Appalachian

Mountain Section of the

Ridge and Valley Province

Appalachian Mountain

Section of the Ridge and

Valley Province

Area2, km2 80.5 66.4

Land Use2

48% Agriculture

46% Forest/Natural

Vegetation

6% Developed Areas

32% Agriculture

59% Forest/Natural

Vegetation

8% Developed Areas

Soil Infiltration3

10% Group A

24% Group B

2% Group B/D

36% Group C

5% Group C/D

23% Group D

7% Group A

24% Group B

3% Group B/D

8% Group C

0% Group C/D

25% Group D

Dominant Bedrock4

69% Shale

15% Limestone

7% Sandstone

3% Dolomite

3% Quartzite

93% Sandstone

7% Argillaceous

Sandstone

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2% Argillaceous Limestone

<1% Calcareous Shale

Average

Precipitation5, in/yr 40.4 40.4

Average Surface

Runoff5, in/yr 2.6 2.9

Average Elevation5

(ft) 792 1,191

Average Slope5 12% 13%

Stream Channel

Slope5

1st Order: 5.0%

2nd Order: 0.7%

3rd Order: 0.2%

1st Order: 2.8%

2nd Order: 1.5%

3rd Order: 0.4%

1Per PA_Physio_Sections GIS layer provided by Pennsylvania Bureau of Topographic and Geological Survey, Dept. of

Conservation and Natural Resources. The estimate was corrected for the portion occurring in Maryland, which was not

shown in this GIS layer but presumed to occur within the Appalachian Mountain Section of the Ridge and Valley

Province. 2MMW output 3As reported by Model My Watershed’s analysis of USDA gSSURGO 2016 4Per Bedrock Geology GIS layer provided by Pennsylvania Bureau of Topographic and Geological Survey, Dept. of

Conservation and Natural Resources and the MDgeol_poly_dd GIS layer provided by USGS. 5As reported by Model My Watershed

Based on the summaries of landcover reported by the “Model My Watershed” application, both

watersheds had substantial amounts of agricultural landcover, though the amount was greater in the

Licking Creek Subwatershed versus the Wooden Bridge Creek Subwatershed (48 versus 32%). Of the

agricultural lands however, there was an approximately even division between croplands and hay/pasture

lands in the Licking Creek Subwatershed (22 versus 26% of total landcover, respectively) whereas

agricultural lands were dominated by hay/pasture lands rather than croplands in the Wooden Bridge Creek

Subwatershed (24% versus 8% of total landcover). The amount of naturally vegetated lands was modestly

lower in the Licking Creek Subwatershed versus the Wooden Bridge Creek Subwatershed (46 versus 59% of

total landcover) and the amount of developed lands were approximately the same (6 versus 8%) (Table 5).

Both watersheds had substantial amounts of both well and poorly drained soils, and the calculated surface

runoff rates and average topographic slopes were very similar in the two watersheds. Stream channel

slopes were also similar between the two watersheds, though 2nd order segments were substantially

steeper in the reference subwatershed and 3rd order segments were moderately steeper. With regard to

bedrock, both watersheds were dominated by non-karst sedimentary formations, though the Licking Creek

Subwatershed was dominated by shale whereas the Wooden Bridge Creek Subwatershed was dominated

by sandstone.

A potentially concerning difference between the Licking Creek Subwatershed and the Wooden Bridge Creek

Subwatershed was that stream segments within the Wooden Bridge Creek Subwatershed were attaining a

11

High-Quality Cold-Water Fishes designation whereas stream segments within the Licking Creek

Subwatershed were designated for Trout Stocking. Use of a watershed that is actually attaining a special

protection status (high quality of exceptional value) as a reference for a non-special special protection

watershed could cause prescribed pollution reductions to be unnecessarily stringent. However, this concern

was dismissed because other non-special protection potential reference watersheds were identified that

had similar or even lower estimated sediment loading than the Wooden Bridge Creek Subwatershed.

Finally, there were three small wastewater treatment plants in the Wooden Bridge Creek Subwatershed

that presently contributed a similar total sediment relative to those that occurred within the Licking Creek

Subwatershed (see Tables 4 and 6).

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Table 6. Existing NPDES Permitted Discharges in the Wooden Bridge Creek Subwatershed and their Potential Contribution to Sediment Loading.

Based on permit limits Based on eDMR data

Sediment Load Sediment Load

Permit No. Facility Name mean lb/yr max lb/d mean lb/yr max lb/d

PA0088242 Country View

Farms LLC1 NA NA NA NA

PA0266078 Robbie & Danyell

Dickinson Farm1 NA NA NA NA

PA0083020 Forbes Road HS &

Elem 731 9 63 5

PA0248029 Hustontown STP 852 14 250 5

PA0083186 HMS Host Sideling

Hill TPK Plaza 1,218 20 194 6

Permits within the watershed were based on DEP’s eMapPA

available at http://www.depgis.state.pa.us/emappa/ and EPA’s Watershed Resources Registry available at

https://watershedresourcesregistry.org/map/?config=stateConfigs/pennsylvania.json.

eDMR= electronic discharge monitoring report, which may be generated at

http://cedatareporting.pa.gov/Reportserver/Pages/ReportViewer.aspx?/Public/DEP/CW/SSRS/EDMR

Note that given their transient nature, stormwater construction permits were not included above.

1In Pennsylvania, routine, dry-weather discharges from concentrated animal feeding operations (CAFOs) are not allowed. Wet weather discharges are controlled

through best management practices, which result in infrequent discharges from production areas and reduced sediment loadings from lands under the control of

CAFOs owner or operators, such as croplands where manure is applied. Although not quantified in this table, pollutant loading from CAFOs is accounted for in the

modeling of land uses within the watershed, with the assumption of no additional CAFO-related BMPs.

Forbes Road HS & Elem.

Permit based values. Based on their permit with an effective date of January 1, 2020, the design flow was 0.012 MGD. This value, along with the

average monthly TSS concentration limit of 20 mg/L was used to calculate the annual average sediment load. Max daily values were calculated assuming

a peaking factor of 3 for flow along with the instantaneous maximum permit value for TSS of 30 mg/L.

13

eDMR based values. Based on one full year of data (2019) where average monthly flows and total suspended solids concentrations were reported. Note

that where there were “‹” symbols, the number value without the symbol was used. All calculated daily sediment loads were summed for all 12 months to

generate the total annual load. Reported daily maximum flows for each month from June 2018 through July 2020 along with the instantaneous maximum

total suspended solids concentration limit of 30 mg/L per their permit were used to generate the maximum daily loads. The highest of those values was

reported above.

Hustontown Joint Sewer Authority

Permit based values. Based on their permit issued July 16, 2020, design flow was 0.028 MGD. This value, along with the average monthly TSS

concentration limit of 10 mg/L were used to calculate the annual average sediment load. Max daily values were calculated assuming a peaking factor of 3

for flow, along with the instantaneous maximum permit value for TSS of 20 mg/L.

eDMR based values. For sediment, monthly reported average monthly TSS concentrations along with monthly reported average monthly flows from

August 2019 through July 2020 were used to generate the average annual load shown above. The daily load for each month was multiplied by the

number of days in the month, and all the months were summed to estimate the yearly load. The maximum daily flow reported for each month from June

2019 through July 2020 along with the instantaneous maximum TSS concentration of 20 mg/L per their permit was used to estimate the maximum daily

load. The highest resultant value was reported above.

HMS Host Sideling Hill TPK Plaza.

Permit based values. Per their permit issued September 19, 2014, design flow was 0.04 MGD. This value, along with the average monthly TSS

concentration limit of 10 mg/L was used to calculate the annual average sediment load. Max daily values were calculated assuming a peaking factor of 3

for flow along with the instantaneous maximum permit value for TSS of 20 mg/L.

eDMR based values. At the time when the first draft was being developed, there was one full year of eDMR data (2019) where average monthly flow and

TSS concentrations were reported for each month. These values were used to generate an average daily load for each month which was then multiplied

by the number of days in the month to calculate the total load for each month. These loads were summed to calculate the annual value reported above.

For the maximum daily sediment load, daily maximum flow values for each month from August 2018 through July 2020 along with the instantaneous

maximum TSS concentration limit of 20 mg/L per their permit was used to calculate daily maximum load for each month. The highest of those values was

reported above.

14

After selecting the potential reference, the two watersheds were visited during August 2020 to determine

the severity of pollution, confirm the suitability of the reference, as well as to explore whether there were

any obvious land use differences that may help to explain why one watershed was impaired for sediment

while the other was attaining. Furthermore, observations and photographs were also used from a previous

March 2020 visit to the Wooden Bridge Creek Subwatershed as part of another study.

A substantial fine sediment deposition problem was obvious in many stream segments of the Licking Creek

Subwatershed, especially in the valley reaches of the lower mainstem (Figure 4). In contrast, tributary

segments in the more mountainous and hilly regions tended to not have obvious problems (Figure 5).

It is hypothesized that the impairments in the watershed were due primarily to the very high amount of

agricultural landcover in general, and croplands in particular, in the Great Valley Region, (Figure 6). At

nearly half of the watershed’s overall landcover, with near complete dominance of the lowlands, the

intensity of agriculture in this watershed was such that impairment may be expected even if agricultural

best management practice (BMP) implementation was good. Furthermore, the low relief topography in the

Great Valley Region of the lower watershed may create conditions favorable to sediment (Figures 1 and 6).

While there were some obvious areas where improvements could have been made, especially with regard

to the establishment of more expansive riparian buffers and livestock exclusion fencing, (Figure 7),

agricultural practices did not appear to be exceptionally problematic in this watershed (Figure 8), though it

was difficult to consider factors such as tillage practices during summer crop growth.

Observations of the Wooden Bridge Creek Subwatershed suggested that streambed substrate was typically

rockier and with less fines in comparison of the Licking Creek Subwatershed. However, some fine sediment

deposition was observed in some pools, and there also appeared to be localized areas with heavy fines

deposition (Figure 9). Like the Licking Creek Subwatershed, the valley areas of the Wooden Bridge Creek

Subwatershed had substantial agricultural landcover while the mountainous areas were dominated by

forest. However, expansive forested riparian buffers appeared to be much more common along the valley

reaches of the Wooden Creek Subwatershed, perhaps due in part due to its greater channel incision versus

the Licking Creek Subwatershed (Figures 1 and 3). There were however instances where substantial

improvements could have been made Wooden Bridge Creek Subwatershed, especially with regard to

fencing cattle from streams and protecting drainageways.

It should also be noted that better streambed conditions and lesser fine sediment deposition within the

Wooden Bridge Creek Subwatershed may also be in part due to it having somewhat steeper stream channel

slopes in its downstream reaches versus the Licking Creek Subwatershed (Table 5). While such a difference

is not ideal, a margin of safety factor will be included with this TMDL to help compensate for such

differences.

15

Figure 2. Licking and Wooden Bridge Creek Subwatersheds. Stream segments within the watershed

were either listed as attaining for aquatic life use, impaired for siltation, or impaired for siltation and

nutrients per the 2018 final Integrated Report (see PA DEP’s 2018 Integrated Report Viewer available

at: https://www.depgis.state.pa.us/integrated_report_viewer/index.html)

16

Figure 3. Wooden Bridge Creek Subwatershed. All stream segments were listed as attaining for aquatic life per the 2018 Final

Pennsylvania Integrated Report.

17

Figure 4. Substrate conditions within valley reaches of the Licking Creek Subwatershed. Obvious fine sediment deposition occurred in

mainstem segments of the valley areas (A through C), as well as within the valley reach of the tributary shown in D. In many cases

however, rocky gravel and cobble substrate was observed in riffles, though it appeared to be embedded and coated with fines.

18

Figure 5. Substrate conditions within the mountain/hilly reaches of the Licking Creek Subwatershed. The upper mainchannel reaches had

less fine sediment deposition, particularly in riffle reaches, though fine deposits could still be observed in some pools. Likewise,

tributaries within or near higher relief areas of the watershed tended to have primarily rocky substrates, especially in riffles.

19

Figure 6. Landscapes within the Licking Creek Subwatershed. Much of the headwaters originated in

the primarily forested mountainous area, whereas the lower reaches flowed through the broad flat

“Great Valley” region of Pennsylvania, which was dominated by agriculture.

20

Figure 7. Agricultural practices in the Licking Creek Subwatershed that may exacerbate sediment loading. Photographs A through D show

stream reaches with inadequate buffering between crop and/or hay/pasture lands. Also note that photographs C and D show reaches

where cattle appeared to have direct access to the stream resulting in enhanced erosion and increased turbidity.

21

Figure 8. Agricultural practices in the Licking Creek Subwatershed that may be protective against sediment loading. Photographs A and B

show reaches with good forested and herbaceous riparian buffers. Photograph C shows an area where cattle were fenced out of the

stream, though ideally the riparian buffer would have been wider for better protection from runoff. Photograph D shows a drainageway

among croplands that has been protected with a shrub and grass buffer.

22

Figure 9. Stream substrate conditions in the Wooden Bridge Creek Subwatershed. Both stream segments coming out of mountainous

areas (A) as well as lower mainstem reaches (B and C) tended to be rocky, particularly in riffles, though fine sediment deposits could be observed in pools (C). Note that there appeared to be some localized areas with substantial fine sediment deposits, such as the pasture in

photograph D, but widespread impairment was not noted for this watershed.

23

Figure 10. Example landscapes within in the Wooden Bridge Creek Subwatershed. Similarly to the Licking Creek Subwatershed, headwater streams often originated in or near mountains while the

lower reaches passed through an agricultural area. However, there was far more forested area in the

valley reaches of the Wooden Bridge Creek Subwatershed, particularly along stream segments. This is

likely at least in part due to the greater degree of incision of stream segments in the Wooden Bridge

Creek Subwatershed.

24

Figure 11. Example practices in the Wooden Bridge Creek Subwatershed that may be protective against agricultural pollution. Even valley

stream segments often had expansive riparian buffers (A and B), in part because they tended to be naturally incised, as in A, though not

always, as in B. Photograph C shows a stream or drainageway with recent riparian buffer restoration whereas D shows a drainageway

protected with an herbaceous and shrub buffer.

25

Figure 12. Example practices in the Wooden Bridge Creek Subwatershed that may exacerbate sediment loading. Note the lack of

substantial riparian buffers (A through D), and cattle access to streams/drainageways with bare areas in photographs B through D. Note

however, as evident in photographs A, B and D, an allowance for forested riparian buffers was often made further downstream along such

low order tributaries.

26

Hydrologic / Water Quality Modeling

This section deals primarily with the TMDLAvg calculations, as use of annual average values were

determined to be the most relevant way to express the “TMDL” variables. For information about

modifications that were made to allow for calculation of TMDLMax, see the later “Calculation of a Daily

Maximum ‘TMDLMax’” section.

Estimates of sediment loading for the impaired and reference watersheds were calculated using the

“Model My Watershed” application (MMW), which is part of the WikiWatershed web toolkit developed

through an initiative of the Stroud Water Research Center. MMW is a replacement for the MapShed

desktop modelling application. Both programs calculate sediment and nutrient fluxes using the

“Generalized Watershed Loading Function Enhanced” (GWLF-E) model. However, MapShed was built

using a MapWindow GIS package that is no longer supported, whereas MMW operates with GeoTrellis,

an open-source geographic data processing engine and framework. The MMW application is freely

available for use at https://wikiwatershed.org/model/. In addition to the changes to the GIS framework,

the MMW application continues to be updated and improved relative to its predecessor.

In the present study, watershed areas were defined using MMW’s Watershed Delineation tool (see

https://wikiwatershed.org/documentation/mmw-tech/#delineate-watershed). Then, the mathematical

model used in MMW, GWLF-E, was used to simulate 28-years of daily water, nitrogen, phosphorus and

sediment fluxes. To provide a general understanding of how the model functions, the following excerpts

are quoted from Model My Watershed’s technical documentation.

The GWLF model provides the ability to simulate runoff, sediment, and nutrient (nitrogen and

phosphorus) loads from a watershed given variable-size source areas (e.g., agricultural,

forested, and developed land). It also has algorithms for calculating septic system loads, and

allows for the inclusion of point source discharge data. It is a continuous simulation model that

uses daily time steps for weather data and water balance calculations. Monthly calculations are

made for sediment and nutrient loads based on the daily water balance accumulated to

monthly values.

GWLF is considered to be a combined distributed/lumped parameter watershed model. For

surface loading, it is distributed in the sense that it allows multiple land use/cover scenarios,

but each area is assumed to be homogenous in regard to various “landscape” attributes

considered by the model. Additionally, the model does not spatially distribute the source areas,

but simply aggregates the loads from each source area into a watershed total; in other words

there is no spatial routing. For subsurface loading, the model acts as a lumped parameter model

using a water balance approach. No distinctly separate areas are considered for sub-surface

flow contributions. Daily water balances are computed for an unsaturated zone as well as a

saturated subsurface zone, where infiltration is simply computed as the difference between

precipitation and snowmelt minus surface runoff plus evapotranspiration.

With respect to major processes, GWLF simulates surface runoff using the SCS-CN approach

with daily weather (temperature and precipitation) inputs from the EPA Center for Exposure

Assessment Modeling (CEAM) meteorological data distribution. Erosion and sediment yield are

27

estimated using monthly erosion calculations based on the USLE algorithm (with monthly

rainfall-runoff coefficients) and a monthly KLSCP values for each source area (i.e., land

cover/soil type combination). A sediment delivery ratio based on watershed size and transport

capacity, which is based on average daily runoff, is then applied to the calculated erosion to

determine sediment yield for each source sector. Surface nutrient losses are determined by

applying dissolved N and P coefficients to surface runoff and a sediment coefficient to the yield

portion for each agricultural source area.

Evapotranspiration is determined using daily weather data and a cover factor dependent upon

land use/cover type. Finally, a water balance is performed daily using supplied or computed

precipitation, snowmelt, initial unsaturated zone storage, maximum available zone storage, and

evapotranspiration values.

Streambank erosion was calculated as a function of factors such as the length of streams, the monthly

stream flow, the percent developed land in the watershed, animal density in the watershed, the

watersheds curve number and soil k factor, and mean topographic slope

For a detailed discussion of this modelling program, including a description of the data input sources,

see Evans and Corradini (2016) and Stroud Research Center (2020).

Model My Watershed allows the user to adjust model parameters, such as the area of land coverage

types, the use of and efficiency of conservation practices, the watershed’s sediment delivery ratio, etc.

Default values were used for the modelling runs, except that the total average flows estimated primarily

from the eDMR data used to generate the loads in Tables 4 and 6, but also assuming 262.5 gallons per

day per residence served by small flow wastewater treatment facilities, were added into the model as

flow input. This added flow causes a minor increase in the loading associated with streambank erosion.

These flows were approximately 83.8 cubic meters per day in the Licking Creek Subwatershed and 108.8

cubic meters per day in the Wooden Bridge Creek Subwatershed.

After the modelling run, corrections were made for the presence of existing riparian buffers using the

BMP Spreadsheet Tool provided by Model My Watershed. The following paragraphs describe this

methodology.

Riparian buffer coverage was estimated via a GIS analysis. Briefly, landcover per a high resolution

landcover dataset (University of Vermont Spatial Analysis Laboratory 2016) was examined within 100

feet of NHD flowlines. To determine riparian buffering within the “agricultural area,” a polygon tool was

used to clip riparian areas that, based on cursory visible inspection, appeared to be in an agricultural-

dominated valley or have significant, obvious agricultural land on at least one side. The selection

polygons are shown in Figures 13 and 14. Then the sum of raster pixels that were classified as either

“Emergent Wetlands”, “Tree Canopy” or “Shrub/Scrub” was divided by the total number of non-water

pixels to determine percent riparian buffer. Using this methodology, percent riparian buffer was

determined to be 49% in the agricultural area of the impaired watershed versus 78% in the reference

watershed.

An additional reduction credit was given to the reference watershed to account for the fact it had more

riparian buffers than the impaired watershed. Applying a reduction credit solely to the reference

watershed to account for its extra buffering was chosen as more appropriate than taking a reduction

28

from both watersheds because the model has been calibrated at a number of actual sites (see

https://wikiwatershed.org/help/model-help/mmw-tech/) with varying amounts of existing riparian

buffers. If a reduction were taken from all sites to account for existing buffers, the datapoints would

likely have a poorer fit to the calibration curve versus simply providing an additional credit to a

reference site.

When accounting for the buffering of croplands using the BMP Spreadsheet Tool, the user enters the

length of buffer on both sides of the stream. To estimate the extra length of buffers in the agricultural

area of the reference watershed over the amount found in the impaired watershed, the approximate

length of NHD flowlines within the reference watershed was multiplied by the proportion of riparian

pixels that were within the agricultural area selection polygon (see Figure 14) and then by the difference

in the proportion of buffering between the agricultural area of the reference watershed versus that of

the impaired watershed, and then by two since both sides of the stream are considered. The BMP

spreadsheet tool then calculates sediment reduction using a similar methodology as the Chesapeake

Assessment Scenario Tool (CAST). The length of riparian buffers is converted to acres, assuming that the

buffers are 100 feet wide. For sediment loading the spreadsheet tool assumes that 2 acres of croplands

are treated per acre of buffer. Thus, twice the acreage of buffer was multiplied by the sediment loading

rate calculated for croplands and then by a reduction coefficient of 0.54 for sediment. The BMP

spreadsheet tool is designed to account for the area of lost cropland and gained forest when riparian

buffers are created. However, this part of the reduction equation was deleted for the present study

since historic rather than proposed buffers were being accounted for.

29

Figure 13. Riparian buffer analysis in the Licking Creek Subwatershed. A raster dataset of high-resolution land cover (University of Vermont Spatial Analysis Lab 2016) is shown within 100 feet

(geodesic) of either side of NHD flowlines. The rate of riparian buffering within the agricultural area

selection polygon was estimated to be about 49%.

30

Figure 14. Riparian buffer analysis in the Wooden Bridge Creek Subwatershed. A raster dataset of high-resolution land cover (University

of Vermont Spatial Analysis Lab 2016) is shown within 100 feet (geodesic) of either side of NHD flowlines. The rate of riparian buffering

within the agricultural area selection polygon was estimated to be about 78%.

31

Calculation of the TMDL The mean annual sediment loading rate for the unimpaired reference subwatershed (Wooden Bridge

Creek) was estimated to be 258 pounds per acre per year (Table 7). This was substantially lower than the

estimated mean annual loading rate in the impaired Licking Creek Subwatershed (406 pounds per acre

per year, Table 8). To achieve the loading rate of the unimpaired watershed, sediment loading in the

Licking Creek Subwatershed should be reduced to 5,123,400 pounds per year, or less (Table 9).

Table 7. Existing Annual Average Loading Values for the Wooden Bridge Creek Subwatershed, Reference

Source Area, ac Sediment,

lbs/yr

Sediment,

lb/ac/yr

Hay/Pasture 3,978 1,254,525 315

Cropland 1,321 1,221,013 924

Forest and Shrub/Scrub 9,657 47,099 5

Grassland/Herbaceous 37 2,919 79

Low Intensity Mixed Development 1,242 14,283 12

Medium Density Mixed Development 111 7,314 66

High Density Mixed Development 35 2,352 68

Streambank1 2,080,109

Point Sources 507

Extra Buffer Discount2 -399,522

total 16,380 4,230,599 258

1“Streambank” sediment loads were calculated using Model My Watershed’s streambank routine which uses length

rather than area.

2Accounts for the amount of extra riparian buffering in the agricultural area of reference watershed versus the

impaired watershed. For details on this calculation, see the “Hydrologic / Water Quality Modelling” section.

Table 8. Existing Annual Average Loading Values for the Licking Creek Subwatershed, impaired

Source Area, ac Sediment,

lbs/yr

Sediment,

lb/ac/yr

Hay/Pasture 5,131 447,972 87

Cropland 4,331 4,739,712 1,094

Forest and Shrub/Scrub 9,002 23,539 3

32

Wetland 183 473 3

Open Land 5 139 28

Bare Rock 2 2 1

Low Intensity Mixed Development 1,151 12,722 11

Medium Density Mixed Development 27 1,957 72

High Density Mixed Development 5 381 77

Streambank 2,832,309

Point Sources 532

total 19,837 8,059,738 406

“Streambank” loads were calculated using Model My Watershed’s streambank routine which uses length rather than

area.

Table 9. Calculation of the Annual Average Sediment TMDL Value for the Licking Creek Subwatershed

Pollutant

Mean Loading

Rate in

Reference,

lbs/ac/yr

Total Area in Impaired

Watershed, ac

Target TMDLAvg Value,

lbs/yr

Sediment 258 19,837 5,123,400

Calculation of Load Allocations In the TMDL equation, the load allocation (LA) is the load derived from nonpoint sources. The LA is

further divided into the adjusted loads allocation (ALA), which is comprised of the nonpoint sources

causing the impairment and targeted for reduction, as well as the loads not reduced (LNR), which is

comprised of the natural and anthropogenic sources that are not considered responsible for the

impairment nor targeted for reduction. Thus:

LA =ALA + LNR

Considering that the total maximum daily load (TMDL) is the sum of the margin of safety (MOS), the

wasteload allocation (WLA), and the load allocation (LA):

TMDL = MOS + WLA + LA,

then the load allocation is calculated as follows:

LA = TMDL - MOS - WLA

33

Thus, before calculating the load allocations, the margins of safety and wasteload allocations must be

defined.

Margin of Safety

The margin of safety (MOS) is a portion of pollutant loading that is reserved to account for uncertainties.

Reserving a portion of the load as a safety factor requires further load reductions from the ALA to

achieve the TMDL. For this analysis, the MOSAvg was explicitly designated as ten-percent of the TMDLAvg

based on professional judgment. Thus:

Sediment: 5,123,400 lbs/yr TMDLAvg * 0.1 = 512,340 lbs/yr MOSAvg

Wasteload Allocation

The wasteload allocation (WLA) is the pollutant loading assigned to existing permitted point sources as

well as future point sources. Where relevant, wasteload allocations under average annual conditions

were assigned as in Table 10. Existing wastewater treatment plants typically received sediment limits

based on design flows and existing total suspended solids (TSS) concentration limits per their permits.

Note that when compared with estimates of actual sediment loading per the eDMR analysis in Table 4,

these WLAs were typically permissive and unlikely to create an additional burden for a facility. This was

determined to be appropriate because the existing sediment loading from these point sources was

virtually negligible relative to the vastly greater loading estimated for nonpoint sources and forcing load

reductions from such facilities would likely be both expensive and ineffective when compared to

agricultural BMPs.

In addition, a 1% bulk reserves was included as part of the wasteload allocation to allow for insignificant

dischargers, such as small flow (design flow <2,000 gpd) wastewater treatment facilities, and minor

increases from point sources as a result of future growth of existing or new sources.

Table 10. Annual Average Wasteload Allocations for Existing NPDES Permitted Discharges in the Licking Creek Subwatershed

Sediment Load

Permit No. Facility Name lb/yr

PAG123849 Herbruck Poultry Ranch, Inc. Bulk Reserve

PA0085979 Guest Farm Village WWTP 1,095

PAM417009 McCulloh Long Farm Quarry Bulk Reserve

PA0085278 Deerwood Mtn Estates WWTP 12,024

34

PA0087050 Valley Creek Estates 1,142

PAG043919 Tonia Metcalf SFS Bulk Reserve

PAG043917 Jason Petre SFTF Bulk Reserve

PA0080608 Camp Tohiglo WWTP 1,096

PA0080501 Montgomery Elem WWTP Bulk Reserve

PAG043903 Twin Hill Meadows Phase II Bulk Reserve

Herbruck Poultry Ranch Inc. In Pennsylvania, routine, dry-weather discharges from concentrated animal feeding

operations (CAFOs) are not allowed. Wet weather discharges are controlled through best management practices

(BMPs), which result in infrequent discharges from production areas and reduced sediment loadings from lands

under the control of CAFOs owner or operators, such as croplands where manure is applied. Although not quantified

in this table, pollutant loading from CAFOs is accounted for as nonpoint source pollution in the modeling of land uses

within the watershed, with the assumption of no additional CAFO-related BMPs.

Guest Farm Village WWTP. The WLA was derived from the permit-based value in Table 4.

McCulloh Long Farm Quarry. Pollutant loading from this facility occurs via stormwater runoff, and thus would be accounted for in nonpoint source modelling of land uses within the watershed. Plus, given the small-scale nature of this operation relative to the overall watershed, the capacity available in the bulk reserves likely far exceeds the pollutant loading from this facility. Deerwood MTN Estates WWTP. This facility was previously approved for a large expansion to accommodate future residential development. The WLA was derived from the future expansion permit based value in Table 4. Valley Creek Estates. The WLA derived from the permit-based value in Table 4.

Tonia Metcalf SFS. Given that this is a small flow wastewater treatment facility (<2,000 gpd) the pollutant loading will be covered under the bulk reserve, which has more than enough capacity for this and the other small flow treatment facilities. Jason Petre SFTF. Given that this is a small flow wastewater treatment facility (<2,000 gpd) the pollutant loading will be covered under the bulk reserve, which has more than enough capacity for this and the other small flow treatment facilities. Camp Tohiglo WWTP. The WLA was derived from the permit-based value in Table 4. Montgomery Elementary WWTP. Given that this is a small flow wastewater treatment facility (<2,000 gpd) the pollutant loading will be covered under the bulk reserve, which has more than enough capacity for this and the other small flow treatment facilities. Twin Hill Meadows Phase II. Given that this is a small flow wastewater treatment facility (<2,000 gpd) the pollutant loading will be covered under the bulk reserve, which has more than enough capacity for this and the other small flow treatment facilities.

Therefore, WLAs were calculated as follows:

5,123,400 lbs/yr TMDLAvg * 0.01 = 51,234 lbs/yr bulk reserveAvg + 15,357 lb/yr permitted loads = 66,591

lbs/yr WLAAvg

35

Load Allocation

Now that the margin of safety and wasteload allocation has been defined, the load allocations (LA) is

calculated as:

Sediment: 5,123,400 lbs/yr TMDLAvg – (512,340 lbs/yr MOSAvg + 66,591 lbs/yr WLAAvg) = 4,544,469 lbs/yr

LAAvg

Loads Not Reduced and Adjusted Load Allocation

Since the impairments addressed by this TMDL were due to agriculture, sediment contributions from

forests, wetlands, open lands (non-agricultural herbaceous/grassland), bare rock, and developed lands

within the Licking Creek Subwatershed were considered loads not reduced (LNR). LNRAvg was calculated

to be 39,212 lbs/yr (Table 11).

The LNR were subtracted from the LA to determine the ALA:

Sediment: 4,544,469 lbs/yr LAAvg – 39,212 lbs/yr LNRAvg = 4,505,256 lbs/yr ALAAvg

Table 11. Average Annual Load Allocation, Loads Not Reduced and Adjusted Load Allocation Sediment

lbs/yr

Load Allocation (LAAvg) 4,544,469

Loads Not Reduced (LNRAvg):

Forest

Wetland

Open Land

Bare Rock

Low Intensity Mixed Development

Med. Intensity Mixed Development

High Density Mixed Development

39,212

23,539

473

139

2

12,722

1,957

381

Adjusted Load Allocation (ALAAvg) 4,505,256

Note, the ALA is comprised of the anthropogenic sources targeted for reduction: croplands, hay/pasturelands, streambanks

(assuming an elevated erosion rate). The LNR is comprised of both natural and anthropogenic sediment sources. While

anthropogenic, developed lands were considered a negligible sediment source in this watershed and thus not targeted for

reduction. Forests, wetlands, open land (non-agricultural herbaceous/grassland) and bare rock were considered natural

sediment sources.

36

Calculation of Load Reductions To calculate load reductions by source, the ALA was further analyzed using the Equal Marginal Percent

Reduction (EMPR) allocation method described in Appendix D. Although the Licking Creek sediment

TMDL was developed to address impairments caused by agricultural activities, streambanks were also

significant contributors to the sediment load in the watershed, and streambank erosion rates are

influenced by agricultural activities. Thus, streambanks were included in the ALA and targeted for

reduction.

In this analysis, croplands received a sediment reduction goal of 45% whereas hay/pasture lands and

streambanks received reduction goals of 42% (Table 12).

Table 12. Annual Average Sediment Load Allocations for Source Sectors in the Licking Creek Subwatershed

Load Allocation Current Load Reduction Goal

Land Use Acres lbs/yr lbs/yr

CROPLAND 4,331 2,607,056 4,739,712 45%

HAY/PASTURE 5,131 259,228 447,972 42%

STREAMBANK 1,638,972 2,832,309 42%

AGGREGATE 4,505,256 8,019,993 44%

Calculation of Daily Maximum “TMDLMax” Values When choosing the best timescale for expressing pollutant loading limits for siltation it must be

considered that:

1) Sediment loading is driven by storm events, and thus loads vary greatly even under natural

conditions.

2) Siltation pollution typically harms aquatic communities through habitat degradation as a result

of chronically excessive loading.

Considering then that siltation pollution has more to do with chronic degradation rather than acutely

toxic loads/concentrations, pollution reduction goals based on average annual conditions are much

more relevant than daily maximum values. Nevertheless, a truer “Total Maximum Daily Load” (TMDLMax)

is also calculated in the following.

Model My Watershed currently does not report daily loading rates, but its predecessor program,

“MapShed” does. Thus, for the calculation of TMDLMax values, modelling was initially conducted in

Model My Watershed, and the “Export GMS” feature was used to provide input data files that were run

in MapShed. The daily output was opened in Microsoft Excel (Version 2002), and current “maximum”

daily load was calculated as the 99th percentile (using the percentile.exc function) of estimated daily

37

sediment loads in both the Licking Creek (impaired) and Wooden Bridge Creek (reference)

Subwatersheds. The first year of data were excluded to account for the time it takes for the model

calculations to become reliable. 99th percentiles were chosen because 1) sediment loading increases

with the size of storm events, so, as long as there could be an even larger flood, true upper limits to

loading cannot be defined and 2) 99% of the time attainment of water quality criteria is prescribed for

other types of pollutants per PA regulations (see PA Code Title 25, Chapter 96, Section 96.3(e)).

As with the average loading values reported previously (see the Hydrologic / Water Quality Modelling

section), a correction was made for the additional amount of existing riparian buffers in the reference

watershed versus the impaired watershed. This was calculated simply by reducing the 99th percentile

loading rate for the reference watershed by the same reduction percentage that were calculated

previously for the average loading rate. After correcting for buffers, relevant point source loads from

Tables 4 and 6 were added in. eDMR based point source values were used where possible.

Then, similarly to the TMDLAvg values reported in Table 9, TMDLMax values were calculated as the 99th

percentile daily loads of the reference watershed, divided by the acres of the reference watershed, and

then multiplied by the acres of the impaired watershed. The TMDLMax loading rate was calculated as

147,166 pounds per day (Table 13), which would be a 37% reduction from the Licking Creek

Subwatershed’s current 99th percentile daily loading rate of 235,368 pounds per day.

Table 13. Calculation of TMDLMax Value for the Licking Creek Subwatershed

Pollutant

99th Percentile

Loading Rate in

Reference, lbs/ac/d

Total Land Area in

Impaired Watershed,

ac

Target

TMDLMax

Value, lbs/d

Sediment 7.4 19,837 147,166

Also, in accordance with the previous “Calculation of Load Allocations” section, the WLAMax would

consist of the sum of the wasteload allocations shown in Table 14 plus a bulk reserve defined as 1% of

the TMDLMax. The wasteload allocations for individual facilities were chosen with the intention that they

typically would not require reductions to current loading, considering that they were not a major source

of the sediment load and forcing reductions from such facilities would likely be both expensive and

ineffective when compared to agricultural BMPs.

As was the case with the MOSAvg, the MOS Max would be 10% of the TMDLMax. The LAMax would then be

calculated as the amount remaining after subtracting the WLAMax and the MOS Max from the TMDLMax.

See Table 15 for a summary of these TMDLMax variables.

Table 14. Wasteload Allocations during 99th percentile loading for Existing NPDES Permitted Discharges in the Licking Creek Subwatershed

Sediment Load

Permit No. Facility Name lb/d

38

PAG123849 Herbruck Poultry Ranch, Inc. Bulk Reserve

PA0085979 Guest Farm Village WWTP 19

PAM417009 McCulloh Long Farm Quarry Bulk Reserve

PA0085278 Deerwood Mtn Estates WWTP 198

PA0087050 Valley Creek Estates 19

PAG043919 Tonia Metcalf SFS Bulk Reserve

PAG043917 Jason Petre SFTF Bulk Reserve

PA0080608 Camp Tohiglo WWTP 18

PA0080501 Montgomery Elem WWTP Bulk Reserve

PAG043903 Twin Hill Meadows Phase II Bulk Reserve

Herbruck Poultry Ranch Inc. In Pennsylvania, routine, dry-weather discharges from concentrated animal feeding

operations (CAFOs) are not allowed. Wet weather discharges are controlled through best management practices

(BMPs), which result in infrequent discharges from production areas and reduced sediment loadings from lands

under the control of CAFOs owner or operators, such as croplands where manure is applied. Although not quantified

in this table, pollutant loading from CAFOs is accounted for as nonpoint source pollution in the modeling of land uses

within the watershed, with the assumption of no additional CAFO-related BMPs.

Guest Farm Village WWTP. The WLA derived from the permit-based value in Table 4.

McCulloh Long Farm Quarry. Pollutant loading from this facility occurs via stormwater runoff, and thus would be accounted for in nonpoint source modelling of land uses within the watershed. Plus, given the small-scale nature of this operation relative to the overall watershed, the capacity available in the bulk reserves likely far exceeds the pollutant loading from this facility. Deerwood MTN Estates WWTP. This facility was previously approved for a large expansion to accommodate future residential development. The WLA was derived from the future expansion permit based value in Table 4.

Valley Creek Estates. The WLA was derived from the permit-based value in Table 4.

Tonia Metcalf SFS. Given that this is a small flow wastewater treatment facility (<2,000 gpd) its pollutant loading will be covered under the bulk reserve, which has more than enough capacity for this and the other small flow treatment facilities. Jason Petre SFTF. Given that this is a small flow wastewater treatment facility (<2,000 gpd) its pollutant loading will be covered under the bulk reserve, which has more than enough capacity for this and the other small flow treatment facilities. Camp Tohiglo WWTP. The WLA was derived from the permit-based value in Table 4. Montgomery Elementary WWTP. Given that this is a small flow wastewater treatment facility (<2,000 gpd) its pollutant loading will be covered under the bulk reserve, which has more than enough capacity for this and the other small flow treatment facilities. Twin Hill Meadows Phase II. Given that this is a small flow wastewater treatment facility (<2,000 gpd) its pollutant loading will be covered under the bulk reserve, which has more than enough capacity for this and the other small flow treatment facilities.

39

Table 15. 99th Percentile of Daily Loading TMDL (TMDLMax) Variables for the Licking Creek Subwatershed

lbs/d:

Pollutant TMDLMax MOSMax WLAMax LAMax

Sediment 147,166 14,717 1,726 130,724

The modelling program however did not break down daily loads by land use type. Thus, the daily

maximum load allocation variables were calculated assuming the same distribution as occurred for the

annual average load allocation variables. For instance, if the streambanks allocation was 36% of LAAvg it

was assumed that it was also 36% of LAMax. While the distribution of sources likely changes with varying

flow levels, this might be an acceptable assumption considering that the largest flow events may control

the bulk of annual sediment loading (see Sloto et al. 2012). See Table 16 for a summary of these LAMax

variables.

Table 16. Allocation of the 99th Percentile Daily Sediment Load Allocation (LAMax) for the Licking Creek Subwatershed Annual Average

(lbs/yr) Proportion of

Load Allocation

Max Daily (lbs/d)

Load Allocation

Loads Not Reduced

Adjusted Loads Allocation

Croplands

Hay/Pasturelands

Streambanks

4,544,469

39,212

4,505,256

2,607,056

259,228

1,638,972

0.009

0.99

0.57

0.06

0.36

130,724

1,128

129,596

74,993

7,457

47,146

Because the modelling program did not break down daily loadings by land use types, the load allocations for

TMDLMax were calculated by assuming the same distribution as occurred for the LAAvg variables. For instance, if the

streambanks allocation was 36% of LAAvg it was assumed that it was also 36% of LAMax.

Because sediment loading varies so greatly with discharge, the TMDLMax value would probably only be

relevant on a handful of days each year with the highest flow conditions. And, while these times are

especially important to overall annual sediment loading (see-Sloto and Olson 2011, Sloto et al. 2012), it

is cautioned that reliance solely on a TMDLMax values may not be protective because chronic excessive

inputs occurring at lower discharge levels may be ignored. Take for instance an extreme scenario where

the TMDLMax value for sediment was met every day but never exceeded. In this case, annual sediment

loading in the Licking Creek Subwatershed would skyrocket to 53,715,551 lbs/yr, which is more than six-

times the current annual average. The TMDLAvg value on the other hand is sensitive to typical conditions,

40

extreme events, and long-term effects, and thus is the most relevant of the two TMDL targets for

achieving restoration in the Licking Creek Subwatershed. Therefore, while adherence with the loading

requirements of this TMDL include meeting both the TMDLAvg and the TMDLMax, BMP implementation

would ultimately be deemed adequate if the prescribed annual average reductions were satisfied.

Consideration of Critical Conditions and Seasonal Variations According to Model My Watershed’s technical documentation (see Stroud Water Research Center

2019), Model My Watershed uses a “continuous simulation model that uses daily time steps for weather

data and water balance. Monthly calculations are made for sediment and nutrient loads based on the

daily water balance accumulated to monthly values.” The source of the weather data (precipitation and

temperature) was a dataset compiled by USEPA ranging from 1963-1990. Therefore, variable flow

conditions and seasonal changes are inherently accounted for in the loading calculations. Furthermore,

this document calculates both annual average and 99th percentile daily TMDL values. See the discussion

of the relevance of these values in the previous section. Seeking to attain both of these values will be

protective under both long-term average and extreme flow event conditions.

Summary and Recommendations This document proposes a 36% reduction in annual average sediment loading for the Licking Creek

Subwatershed. To achieve this goal while maintaining a margin of safety and minor allowance for point

sources, it is proposed to reduce sediment loading from croplands by 45% and loading from hay/pasture

lands and streambanks by 42%. In addition, 99th percentile daily sediment loading should be reduced by

37%.

Reductions in stream sediment loading due to agricultural activities can be made through the

implementation of required Erosion and Sediment Control Plans (Pennsylvania Clean Streams Law, Title

25 Environmental Protection, Chapter 102.4) and through the use of BMPs such as conservation tillage,

cover crops, vegetated filter strips, rotational grazing, livestock exclusion fencing, riparian buffers, legacy

sediment removal etc.

Use of forested riparian buffers is widely recognized as one of the best ways to promote stream health.

Riparian buffers protect streams from sedimentation impairments by filtering these pollutants from

runoff and floodwaters and by protecting streambanks from erosion. However, riparian buffers are also

beneficial for many other reasons beyond just protecting from sedimentation. For instance, riparian

buffers may: filter out other pollutants such as nutrients and pesticides; provide habitat and nutrition

for aquatic, semi-aquatic and terrestrial organisms; and moderate stream temperature. Thus, use of

forested riparian buffers should be encouraged wherever possible.

Development of a more detailed watershed implementation plan is recommended. Further ground

truthing should be performed to assess both the extent of existing BMPs and to determine the most cost

effective and environmentally protective combination of new BMPs needed to achieve the prescribed

sediment reductions. Key personnel from the regional DEP office, the County Conservation District, and

41

other state and local agencies and/or watershed groups should be involved in developing a restoration

strategy. There are a number of possible funding sources for agricultural BMPs and stream restoration

projects, including: The Federal Nonpoint Source Management Program (§ 319 of the Clean Water Act),

PA DEP’s Growing Greener Grant Program, United States Department of Agriculture’s Natural Resource

Conservation Service funding, and National Fish and Wildlife Foundation Grants.

Public Participation

Public notice of a draft of this TMDL was published in the February 13th, 2021 issue of the Pennsylvania

Bulletin to foster public comment. A 30-day period was provided for the submittal of comments. No

comments were received.

Citations 'Maps throughout this document were created using ArcGIS® software by Esri. ArcGIS® and ArcMap™ are the intellectual property of Esri and are used herein under license. Copyright © Esri. All rights reserved. For more information about Esri® software, please visit www.esri.com.' Evans, B.M. and K.J. Corradini. 2016. Mapshed Version 1.5 Users Guide. Penn State Institutes of Energy and the Environment. The Pennsylvania State University. University Park, PA 16802 Mapshed Version 1.5.1. Penn State Institutes of Energy and the Environment. The Pennsylvania State University. University Park, PA 16802 Sloto, R. A. and L.E. Olson. 2011. Estimated Suspended -Sediment Loads and Yields in the French and

Brandywine Creek Basins, Chester County, Pennsylvania, Water Years 2008-09. USGS Scientific

Investigations Report 2011-5109. Available at https://pubs.usgs.gov/sir/2011/5109/support/sir2011-

5109.pdf

Sloto, R.A., A.C. Gellis, and D.G. Galeone. 2012 Total Nitrogen and Suspended-Sediment Loads and

Identification of Suspended-Sediment Sources in the Laurel Hill Creek Watershed, Somerset County,

Pennsylvania, Water Years 2010-11. USGS Scientific Investigations Report 2012-5250. Available at

https://pubs.usgs.gov/sir/2012/5250/support/sir2012-5250.pdf

Stroud Water Research Center. (2020). Model My Watershed [Software]. Version 1.26 Available from

https://wikiwatershed.org/. Technical documentation available at:

https://wikiwatershed.org/documentation/mmw-tech/

University of Vermont Spatial Analysis Laboratory. (2016). High-Resolution Land Cover, Commonwealth

of Pennsylvania, Chesapeake Bay Watershed and Delaware River Basin, 2013. Available at:

http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=3193

42

43

Appendix A: Background on Stream Assessment Methodology

44

Integrated Water Quality Monitoring and Assessment Report, List 5,

303(d), Listing Process

Assessment Methods:

Prior to developing TMDLs for specific waterbodies, there must be sufficient data available to assess

which streams are impaired and should be listed in the Integrated Water Quality Monitoring and

Assessment Report. Prior to 2004 the impaired waters were found on the 303(d) List; from 2004 to

present, the 303(d) List was incorporated into the Integrated Water Quality Monitoring and Assessment

Report and found on List 5. Table A1. summarizes the changes to listing documents and assessment

methods over time.

With guidance from EPA, the states have developed methods for assessing the waters within their

respective jurisdictions. From 1996-2006, the primary method adopted by the Pennsylvania Department

of Environmental Protection for evaluating waters found on the 303(d) lists (1998-2002) or in the

Integrated Water Quality Monitoring and Assessment Report (2004-2006) was the Statewide Surface

Waters Assessment Protocol (SSWAP). SSWAP was a modification of the EPA Rapid Bioassessment

Protocol II (RPB-II) and provided a more consistent approach to assessing Pennsylvania’s streams.

The assessment method sought to select representative stream segments based on factors such as

surrounding land uses, stream characteristics, surface geology, and point source discharge locations.

The biologist was to select as many sites as necessary to establish an accurate assessment for a stream

segment; the length of the stream segment could vary between sites. The biological surveys were to

include kick-screen sampling of benthic macroinvertebrates, habitat surveys, and measurements of pH,

temperature, conductivity, dissolved oxygen, and alkalinity. Benthic macroinvertebrates were typically

identified to the family level in the field.

The listings found in the Integrated Water Quality Monitoring and Assessment Reports from 2008 to

present were derived based on the Instream Comprehensive Evaluation protocol (ICE). Like the

superseded SSWAP protocol, the ICE protocol called for selecting representative segments based on

factors such as surrounding land uses, stream characteristics, surface geology, and point source

discharge locations. The biologist was to select as many sites as necessary to establish an accurate

assessment for a stream segment; the length of the stream segment could vary between sites. The

biological surveys were to include D-frame kicknet sampling of benthic macroinvertebrates, habitat

surveys, and measurements of pH, temperature, conductivity, dissolved oxygen, and alkalinity. Collected

samples were returned to the laboratory where the samples were subsampled for a target benthic

macroinvertebrate sample of 200 ± 20% (N = 160-240). The benthic macroinvertebrates in this

subsample were then typically identified to the generic level. The ICE protocol is a modification of the

45

EPA Rapid Bioassessment Protocol III (RPB-III) and provides a more rigorous and consistent approach to

assessing Pennsylvania’s streams than the SSWAP.

After these surveys (SSWAP, 1998-2006 lists or ICE, 2008-present lists) were completed, the biologist

determined the status of the stream segment. The decision was based on the performance of the

segment using a series of biological metrics. If the stream segment was classified as impaired, it was

then listed on the state’s 303(d) List or presently the Integrated Water Quality Monitoring and

Assessment Report with the source and cause documented.

Once a stream segment is listed as impaired, a TMDL typically must be developed for it. A TMDL

addresses only one pollutant. If a stream segment is impaired by multiple pollutants, each pollutant

receives a separate and specific TMDL within that stream segment. Adjoining stream segments with the

same source and cause listings are addressed collectively on a watershed basis.

Table A1. Impairment Documentation and Assessment Chronology Listing Date: Listing Document: Assessment Method:

1998 303(d) List SSWAP

2002 303(d) List SSWAP

2004 Integrated List SSWAP

2006 Integrated List SSWAP

2008-Present Integrated List ICE

Integrated List= Integrated Water Quality Monitoring and Assessment Report

SSWAP= Statewide Surface Waters Assessment Protocol

ICE= Instream Comprehensive Evaluation Protocol

Justification of Mapping Changes to 303(d) Lists 1998 to Present

The following are excerpts from the Pennsylvania DEP Section 303(d) narratives that justify changes in

listings between the 1996-2002 303(d) Lists and the 2004 to present Integrated Water Quality

Monitoring and Assessment Reports. The Section 303(d) listing process has undergone an evolution in

Pennsylvania since the development of the 1996 list.

In the 1996 Section 303(d) narrative, strategies were outlined for changes to the listing process.

Suggestions included, but were not limited to, a migration to a Global Information System (GIS),

improved monitoring and assessment, and greater public input.

46

The migration to a GIS was implemented prior to the development of the 1998 Section 303(d) list.

Because of additional sampling and the migration to the GIS, some of the information appearing on the

1996 list differed from the 1998 list. Most common changes included:

1. mileage differences due to recalculation of segment length by the GIS;

2. slight changes in source(s)/cause(s) due to new EPA codes;

3. changes to source(s)/cause(s), and/or miles due to revised assessments;

4. corrections of misnamed streams or streams placed in inappropriate SWP subbasins; and

5. unnamed tributaries no longer identified as such and placed under the named watershed

listing.

Prior to 1998, segment lengths were computed using a map wheel and calculator. The segment lengths

listed on the 1998 Section 303(d) list were calculated automatically by the GIS (ArcInfo) using a constant

projection and map units (meters) for each watershed. Segment lengths originally calculated by using a

map wheel and those calculated by the GIS did not always match closely. This was the case even when

physical identifiers (e.g., tributary confluence and road crossings) matching the original segment

descriptions were used to define segments on digital quad maps. This occurred to some extent with all

segments, but was most noticeable in segments with the greatest potential for human errors using a

map wheel for calculating the original segment lengths (e.g., long stream segments or entire basins).

Migration to National Hydrography Data (NHD)

New to the 2006 report is use of the 1/24,000 National Hydrography Data (NHD) streams GIS layer. Up

until 2006 the Department relied upon its own internally developed stream layer. Subsequently, the

United States Geologic Survey (USGS) developed 1/24,000 NHD streams layer for the Commonwealth

based upon national geodatabase standards. In 2005, DEP contracted with USGS to add missing streams

and correct errors in the NHD. A GIS contractor transferred the old DEP stream assessment information

to the improved NHD and the old DEP streams layer was archived. Overall, this marked an improvement

in the quality of the streams layer and made the stream assessment data compatible with national

standards but it necessitated a change in the Integrated Listing format. The NHD is not attributed with

the old DEP five-digit stream codes so segments can no longer be listed by stream code but rather only

by stream name or a fixed combination of NHD fields known as reachcode and ComID. The NHD is

aggregated by Hydrologic Unit Code (HUC) watersheds so HUCs rather than the old State Water Plan

(SWP) watersheds are now used to group streams together. A more basic change was the shift in data

management philosophy from one of “dynamic segmentation” to “fixed segments”. The dynamic

segmentation records were proving too difficult to manage from an historical tracking perspective. The

fixed segment methods will remedy that problem. The stream assessment data management has gone

47

through many changes over the years as system requirements and software changed. It is hoped that

with the shift to the NHD and OIT’s (Office of Information Technology) fulltime staff to manage and

maintain SLIMS the systems and formats will now remain stable over many Integrated Listing cycles.

48

Appendix B: Model My Watershed Generated Data Tables

49

Table B1. “Model My Watershed” Land Cover Outputs for the Licking Creek Subwatershed.

Table B2. “Model My Watershed” Land Cover Outputs for the Wooden Bridge Creek Subwatershed.

Type NLCD Code Area (km²) Coverage (%)

Open Water 11 0.14 0.18

Perennial Ice/Snow 12 0 0

Developed, Open Space 21 3.75 4.66

Developed, Low Intensity 22 0.91 1.12

Developed, Medium Intensity 23 0.11 0.14

Developed, High Intensity 24 0.02 0.03

Barren Land (Rock/Sand/Clay) 31 0.01 0.01

Deciduous Forest 41 35.59 44.22

Evergreen Forest 42 0.47 0.59

Mixed Forest 43 0.27 0.33

Shrub/Scrub 52 0.13 0.17

Grassland/Herbaceous 71 0.02 0.02

Pasture/Hay 81 20.78 25.82

Cultivated Crops 82 17.54 21.8

Woody Wetlands 90 0.51 0.63

Emergent Herbaceous Wetlands 95 0.23 0.28

Total 80.49 100

Type NLCD Code Area (km²) Coverage (%)

Open Water 11 0.01 0.02

Perennial Ice/Snow 12 0 0

Developed, Open Space 21 3.67 5.54

Developed, Low Intensity 22 1.36 2.05

Developed, Medium Intensity 23 0.45 0.68

Developed, High Intensity 24 0.14 0.22

Barren Land (Rock/Sand/Clay) 31 0 0

Deciduous Forest 41 35.03 52.79

Evergreen Forest 42 2.66 4.01

Mixed Forest 43 1.41 2.12

Shrub/Scrub 52 0.01 0.02

Grassland/Herbaceous 71 0.15 0.23

Pasture/Hay 81 16.11 24.27

Cultivated Crops 82 5.35 8.06

Woody Wetlands 90 0 0

Emergent Herbaceous Wetlands 95 0 0

Total 66.37 100

50

Table B3. “Model My Watershed” Hydrology Outputs for the Licking Creek Subwatershed

Table B4. “Model My Watershed” Hydrology Outputs for the Wooden Bridge Creek Subwatershed.

Month

Stream Flow

(cm)

Surface

Runoff (cm)

Subsurface

Flow (cm)

Point Src

Flow (cm) ET (cm) Precip (cm)

Jan 5.27 0.89 4.37 0 0.5 6.99

Feb 5.92 0.86 5.06 0 0.76 7.05

Mar 6.3 0.41 5.89 0 2.34 8.11

Apr 5.35 0.08 5.27 0 5.4 7.97

May 3.77 0.28 3.48 0 10.1 10.69

Jun 2.87 0.97 1.89 0 12.53 9.93

Jul 1.07 0.28 0.79 0 10.09 9

Aug 0.51 0.28 0.23 0 8.75 9.19

Sep 0.99 0.82 0.17 0 5.97 8.94

Oct 1.29 0.62 0.67 0 3.97 7.94

Nov 1.53 0.42 1.11 0 2.13 8.57

Dec 3.96 0.69 3.27 0 1 8.2

Total 38.83 6.6 32.2 0 63.54 102.58

Month

Stream Flow

(cm)

Surface

Runoff (cm)

Subsurface

Flow (cm)

Point Src

Flow (cm) ET (cm) Precip (cm)

Jan 5.55 1.01 4.54 0.01 0.52 6.99

Feb 6.13 0.96 5.17 0 0.8 7.05

Mar 6.31 0.46 5.84 0.01 2.45 8.11

Apr 5.13 0.08 5.04 0 5.5 7.97

May 3.39 0.3 3.08 0.01 10.15 10.69

Jun 2.56 1.03 1.52 0 12.4 9.93

Jul 0.81 0.3 0.51 0.01 10.01 9

Aug 0.4 0.3 0.09 0.01 8.71 9.19

Sep 1.04 0.89 0.14 0 5.93 8.94

Oct 1.4 0.68 0.71 0.01 4 7.94

Nov 1.68 0.46 1.21 0 2.17 8.57

Dec 4.37 0.77 3.59 0.01 1.03 8.2

Total 38.77 7.24 31.44 0.07 63.67 102.58

51

Table B5. Model My Watershed outputs for sediment in the Licking Creek Subwatershed.

Table B6. Model My Watershed outputs for sediment in the Wooden Bridge Creek Subwatershed.

Sources

Sediment

(kg) Total P (kg)

Hay/Pasture 203,162.00 702.2

Cropland 2,149,529.10 2,714.40

Wooded Areas 10,675.10 22.4

Wetlands 214.4 1.5

Open Land 63.1 0.1

Barren Areas 0.7 0

Low-Density Mixed 1,121.40 2.8

Medium-Density Mixed 887.5 1.8

High-Density Mixed 172.8 0.3

Low-Density Open Space 4,648.40 11.7

Farm Animals 0 4,408.60

Stream Bank Erosion 1,284,494.00 300

Subsurface Flow 0 1,066.10

Point Sources 0 0

Septic Systems 0 0

Sources

Sediment

(kg) Total P (kg)

Hay/Pasture 568,945.60 915

Cropland 553,747.30 721.4

Wooded Areas 21,360.30 43.9

Wetlands 0 0

Open Land 1,323.80 1.5

Barren Areas 0 0

Low-Density Mixed 1,748.70 4.6

Medium-Density Mixed 3,317.20 7

High-Density Mixed 1,066.50 2.3

Low-Density Open Space 4,728.90 12.3

Farm Animals 0 1,278.00

Stream Bank Erosion 943,360.00 216

Subsurface Flow 0 449.4

Point Sources 0 0

Septic Systems 0 0

52

Appendix C: Stream Segments in the Licking Creek Subwatershed with Siltation Impairments

53

Stream Name: Assessed Use: Impairment Source: Cause: COMID: Miles:

Licking Creek Aquatic Life Agriculture Siltation 49496826 0.17

UNT Licking Creek Aquatic Life Agriculture Siltation 49480636 0.17

UNT Blue Spring Creek Aquatic Life Agriculture Siltation 49482936 0.63

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472412 0.23

Blue Spring Creek Aquatic Life Agriculture Siltation 49480594 0.36

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472396 0.28

UNT Licking Creek Aquatic Life Agriculture Siltation 49480580 0.81

UNT Licking Creek Aquatic Life Agriculture Siltation 49487194 0.30

UNT Licking Creek Aquatic Life Grazing Related Agric Siltation 49480710 1.17

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472380 0.23

UNT Licking Creek Aquatic Life Agriculture Siltation 49487936 0.01

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472442 0.19

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472422 0.26

Blue Spring Creek Aquatic Life Grazing Related Agric Siltation 49480586 0.29

UNT Licking Creek Aquatic Life Agriculture Siltation 49487306 0.05

UNT Licking Creek Aquatic Life Agriculture Siltation 49473888 0.70

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472368 0.25

UNT Licking Creek Aquatic Life Grazing Related Agric Siltation 49480712 0.60

UNT Licking Creek Aquatic Life Agriculture Siltation 49496112 0.16

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472432 0.19

Licking Creek Aquatic Life Agriculture Siltation 49496798 0.05

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472424 0.06

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472426 0.03

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472430 0.08

54

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472408 0.19

UNT Licking Creek Aquatic Life Agriculture Siltation 49487308 0.52

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472386 0.17

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472390 0.31

UNT Licking Creek Aquatic Life Agriculture Siltation 49488046 0.40

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472370 0.87

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472372 0.09

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472434 0.13

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472428 0.11

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472414 0.07

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472416 0.21

Blue Spring Creek Aquatic Life Grazing Related Agric Siltation 49480590 0.32

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472400 0.27

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472410 0.04

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472398 0.56

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472394 0.13

UNT Licking Creek Aquatic Life Agriculture Siltation 49488270 0.84

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472384 0.37

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472382 0.10

UNT Licking Creek Aquatic Life Grazing Related Agric Siltation 49480714 0.00

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472364 0.31

UNT Licking Creek Aquatic Life Agriculture Siltation 49480628 0.53

UNT Licking Creek Aquatic Life Agriculture Siltation 49480634 0.36

UNT Blue Spring Creek Aquatic Life Agriculture Siltation 49495642 0.88

Blue Spring Creek Aquatic Life Grazing Related Agric Siltation 49480588 0.64

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472404 0.11

Blue Spring Creek Aquatic Life Agriculture Siltation 49480596 0.09

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472374 0.08

55

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472388 0.04

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472366 0.18

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472444 0.21

Blue Spring Creek Aquatic Life Agriculture Siltation 49480598 0.06

UNT Blue Spring Creek Aquatic Life Agriculture Siltation 49480614 0.22

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472392 0.22

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472440 0.08

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472420 0.23

UNT Licking Creek Aquatic Life Agriculture Siltation 49480630 0.29

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472418 0.40

UNT Licking Creek Aquatic Life Agriculture Siltation 49480622 0.38

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472402 0.16

Blue Spring Creek Aquatic Life Agriculture Siltation 49487120 0.77

UNT Blue Spring Creek Aquatic Life Agriculture Siltation 49487454 0.58

Blue Spring Creek Aquatic Life Agriculture Siltation 49480612 0.40

UNT Licking Creek Aquatic Life Agriculture Siltation 49480582 1.42

UNT Licking Creek Aquatic Life Agriculture Siltation 49480584 0.14

UNT Licking Creek Aquatic Life Agriculture Siltation 49487304 0.27

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472376 0.17

UNT Licking Creek Aquatic Life Agriculture Siltation 49487938 0.07

UNT Licking Creek Aquatic Life Grazing Related Agric Siltation 49480716 0.51

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472436 0.07

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472438 0.14

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472406 0.22

Blue Spring Creek Aquatic Life Agriculture Siltation 49480592 0.34

UNT Licking Creek Aquatic Life Agriculture Siltation 49487192 0.01

Licking Creek Aquatic Life Grazing Related Agric Siltation 49472378 0.16

UNT Licking Creek Aquatic Life Grazing Related Agric Siltation 49480718 0.39

56

UNT Licking Creek Aquatic Life Agriculture Siltation 49487940 0.25

UNT Licking Creek Aquatic Life Grazing Related Agric Siltation 49480720 1.18

Table C1. Stream segments with siltation impairments in the Licking Creek Subwatershed.

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Appendix D: Equal Marginal Percent Reduction Method

58

Equal Marginal Percent Reduction (EMPR) (An Allocation Strategy)

The Equal Marginal Percent Reduction (EMPR) allocation method was used to distribute the Adjusted

Load Allocation (ALA) between the appropriate contributing nonpoint sources. The load allocation and

EMPR procedures were performed using a MS Excel spreadsheet. The 5 major steps identified in the

spreadsheet are summarized below:

Step 1: Calculation of the TMDL based on impaired watershed size and unit area loading rate of

reference watershed.

Step 2: Calculation of Adjusted Load Allocation based on TMDL, MOS, WLA and existing loads not

reduced.

Step 3: Actual EMPR Process:

a. Each land use/source load is compared with the total ALA to determine if

any contributor would exceed the ALA by itself. The evaluation is carried

out as if each source is the only contributor to the pollutant load of the

receiving waterbody. If the contributor exceeds the ALA, that contributor

would be reduced to the ALA. If a contributor is less than the ALA, it is set

at the existing load. This is the baseline portion of EMPR.

b. After any necessary reductions have been made in the baseline, the

multiple analyses are run. The multiple analyses will sum all the baseline

loads and compare them to the ALA. If the ALA is exceeded, an equal

percent reduction will be made to all contributors’ baseline values. After

any necessary reductions in the multiple analyses, the final reduction

percentage for each contributor can be computed.

Step 4: Calculation of total loading rate of all sources receiving reductions.

Step 5: Summary of existing loads, final load allocations, and percent reduction for each pollutant

source

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Table D1. Sediment Equal Marginal Percent Reduction calculations for the Licking Creek Subwatershed.

Cropland 4,739,712 yes 4,505,256 0.58 1,898,200 2,607,056 0.45

Hay/Pasture 447,972 no 447,972 3,280,281 0.06 188,744 259,228 0.42

Streambank 2,832,309 no 2,832,309 0.36 1,193,337 1,638,972 0.42

sum 8,019,993 7,785,538 1.00 3,280,281 4,505,256 0.44

Non-MS4 Sewershed

Current Load, lbs/yr

Any >

ALA?

If > ALA,

reduce to ALA

proportion

Reduction

Assign reductions still

needed per proportions after

intial adjust

ALA: subtract reductions

still needed from initial

adjust

How much

does sum

exceed ALA?

Proportions of

total after initial

adjust

60

Appendix E: Legal Basis for the TMDL and Water Quality Regulations for Agricultural Operations

61

Clean Water Act Requirements

Section 303(d) of the 1972 Clean Water Act requires states, territories, and authorized tribes to establish

water quality standards. The water quality standards identify the uses for each waterbody and the

scientific criteria needed to support that use. Uses can include designations for drinking water supply,

contact recreation (swimming), and aquatic life support. Minimum goals set by the Clean Water Act

require that all waters be “fishable” and “swimmable.”

Additionally, the federal Clean Water Act and the United States Environmental Protection Agency’s

(EPA) implementing regulations (40 CFR 130) require:

o States to develop lists of impaired waters for which current pollution controls are not stringent

enough to meet water quality standards (the list is used to determine which streams need

TMDLs);

o States to establish priority rankings for waters on the lists based on severity of pollution and the

designated use of the waterbody; states must also identify those waters for which TMDLs will be

developed and a schedule for development;

o States to submit the list of waters to EPA every two years (April 1 of the even numbered years);

o States to develop TMDLs, specifying a pollutant budget that meets state water quality standards

and allocate pollutant loads among pollution sources in a watershed, e.g., point and nonpoint

sources; and

o EPA to approve or disapprove state lists and TMDLs within 30 days of final submission.

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Pennsylvania Clean Streams Law Requirements, Agricultural Operations

Pennsylvania farms are required by law to operate within regulatory compliance by implementing the

applicable requirements outlined in the Pennsylvania Clean Streams Law, Title 25 Environmental

Protection, Part I Department of Environmental Protection, Subpart C Protection of Natural Resources,

Article II Water Resources, Chapters: § 91.36 Pollution control and prevention at agricultural

operations, § 92a.29 CAFO and § 102.4 Erosion and sediment control requirements. Water quality

regulations can be found at following website: http://www.pacode.com/secure/data/025/025toc.html

Agricultural regulations are designed to reduce the amount of sediment and nutrients reaching the

streams and ground water in a watershed.

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Appendix F: Comment and Response

This section is reserved for public comments and responses. No comments were received.