EPA/600/R-12/600 | March 2013 | www.epa.gov/gateway/science
United States
Environmental Protection
Agency
Evaluation of Dry Wells and Cisterns for
Stormwater Control: Millburn Township, NJ
Office of Research and Development
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EPA/600/R-12/600
October 2012
Evaluation of Dry Wells and Cisterns for
Stormwater Control: Millburn Township,
New Jersey
Prepared by
Dr. Robert Pitt and Leila Talebi
The University of Alabama
Tuscaloosa, AL 35487
Under the direction of
Melvin Singer
Environmental Consultant
Millburn Township, NJ 07041
Field data supplied by
Dr. Ramjee Raghavan and Hunter Blair
Pars Environmental Inc.
Robbinsville, NJ 08691
Modeling and analysis by
Dr. Robert Pitt and Leila Talebi
The University of Alabama
Tuscaloosa, AL 35487
EPA Contract: EP-C-08-016
EPA Project Officers
Richard Field and Anthony N. Tafuri
Urban Watershed Management Branch
U.S. Environmental Protection Agency
Edison, NJ 08837
Office of Research and Development
U.S. Environmental Protection Agency
Cincinnati, OH 45268
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Abstract
The primary objective of this project was to investigate the effectiveness of the
Township of Millburn's use of on-site dry wells to limit stormwater flows into the local
drainage system. The objective was to examine this stormwater management
alternative applicable for mature urban and suburban communities to reduce
stormwater discharges associated with new development and redevelopment. This
objective was achieved by collecting and monitoring the performance of dry wells during
both short and long-periods. The water quality beneath dry wells and in a storage
cistern was also monitored during ten rain events.
There were varying levels of dry well performance in the area, but most were able to
completely drain within a few days. However, several had extended periods of standing
water that may have been associated with high water tables, poorly draining soils (or
partially clogged soils), or detrimental effects from snowmelt on the clays in the soils.
The infiltration rates all met the infiltration rate criterion of the state guidelines for
stormwater discharges to dry wells (but not the state regulations that only allow roof
runoff to be discharged to dry wells and those that prohibit dry well use in areas of
shallow water tables). Overall, most of the Millburn dry wells worked well in infiltrating
runoff. Although the dry wells provided no significant improvements in water quality for
constituents of interest for the infiltrating water, they resulted in reduced mass
discharges of flows and pollutants to surface waters and reduced runoff energy, major
causes of local erosion problems.
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Acknowledgements
Many people helped make this project a success. We are especially grateful for the help
of Mel Singer, environmental consultant and resident of the Township of Millburn, who
developed the concept for the project and was instrumental in organizing the different
project groups and who helped secure funding from the EPA. The Township of Millburn
personnel (especially Thomas Watkinson, Millburn Township Engineer, Tim Gordon,
Township Manager, Sandra Haimoff, Mayor, Martha Annoi, and others), the home
owners who allowed access for the study sites, and especially to the PARS
Environmental, Inc. personnel (Ramjee Raghavan and Hunter Blair, and others) who
helped coordinate, install equipment, and conduct the measurements and sampling, are
thanked. Special thanks are also extended to Richard Field, Mary Stinson, Anthony N.
Tafuri and Sivajini Gilchrist who provided the EPA funding and directed the project
through the US Environmental Protection Agency.
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Contents
Abstract i
Acknowledgements ii
Contents iii
Tables vii
Figures xi
Glossary xiv
Chapter 1 Executive Summary 1
Description of Millburn and Its Dry Wells 1
Project Objectives and Findings 3
Primary Report Questions 5
Infiltration Tests at Millburn Dry Well Installations 8
Factors Affecting Infiltration Rates 10
Water Quality Observations 16
Results and Conclusions 19
Chapter 2 Background of Millburn Stormwater Management using Dry Wells 24
Description of Millburn Dry Wells 24
Chapters Millburn, NJ, Study Site Descriptions 32
Site Descriptions 33
Aerial Photos of Study Locations 35
Land Cover Descriptions of Study Sites 41
Features Affecting Water Use 42
Population, Residences, and Householder Data 42
Soil types 43
Groundwater Conditions in the Township of Millburn 50
Rainfall Characteristics in Northern New Jersey 50
Summary of Site Characteristics 54
Chapter 4 Millburn Township Stormwater Regulations and New Jersey State
Groundwater Disposal and Water Reuse Regulations and other Guidance 56
Millburn Township Stormwater Regulations 56
New Jersey Groundwater Disposal Criteria for Stormwater 57
Beneficial Use Regulations 60
Unrestricted Urban Reuse 60
Restricted Urban Reuse 61
Criteria that May Affect Irrigation as a Beneficial Use of Stormwater 62
Treatment Methods to Enhance Stormwater Quality for Beneficial Uses 67
Off-the-Shelf Treatment Systems 67
Summary of Millburn Township and New Jersey Groundwater Disposal Regulations
and Treatment Options 68
Chapter 5 Beneficial Uses of Stormwater for Infiltration/Recharge, Millburn, NJ . 72
Groundwater Recharge 72
Infiltration Tests at Millburn Dry Well Installations 74
Rainfall Measurements 75
Infiltration Measurements 80
Infiltration Equations 81
in
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Morton Infiltration Equation 81
Green-Ampt Infiltration Equation 82
Infiltration as a Function of Soil Texture and Compaction 83
Fitted Morton Equation Parameters for Millburn Dry Well Infiltration Measurements.. 85
Fitting Observed data to Morton's Equation 85
Statistical Groupings of Site Data for Morton Coefficients 89
Fitting Observed Data to Green-Ampt Equation 95
Regression Analysis for f vs. 1 /F (Green-Ampt) 96
Summary of Recharge Observations with Dry Wells 99
Factors Affecting Infiltration Rates 100
Observed Infiltration Coefficient Values Compared to Literature Values 121
Chapter 6 Dry Well Disposal Water Quality Observed in Millburn, NJ 124
Sampling Locations 124
Sampling Procedure 126
Results of Dry Well and Cistern Water Sample Analyses 129
Bacteria 129
Nutrients 131
Chemical Oxygen Demand (COD) 134
Metals 135
Herbicides and Pesticides 137
Statistical Analyses and Discussion 138
Group Box Plots 140
Paired Line Plots 142
Time Series Plots 144
Log-normal Probability Plots and Anderson-Darling Test Statistic 145
Mann Whitney Test 147
Paired Sign Test for Metal Analyses 150
Comparisons of Observed Water Quality to NJ Groundwater Disposal Criteria 150
Summary of Water Quality Observations 152
Chapter 7 Alternative Stormwater Management Options for Millburn, NJ 153
Approach for Examining Alternative Stormwater Management Options for Millburn 153
WinSLAMM Background Information 154
Stormwater Controls in WinSLAMM and Calculation Processes 155
Regional Rainfall and Runoff Distributions and Sources of Stormwater Discharges 156
Sources of Runoff from Different Source Areas 157
Dry Well Analyses for Millburn Residential Areas 160
Stormwater used for Irrigation of Landscaped Areas in Millburn 166
Millburn, New Jersey Water Use 166
The Urban Water Budget and Stormwater Reuse in U.S. Residential Areas 167
Calculating the Benefits of Rainwater Harvesting Systems and Evapotranspiration
Rates 169
Irrigation Water Use 170
Roof Harvesting and Water Tank Sizes 173
Use of Cisterns for Irrigation of Roof Runoff in Conjunction with Dry Wells 176
Rain Gardens used in Millburn Residential Areas 178
IV
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Summary of Stormwater Management Alternatives for Millburn 181
Chapter 8 Conclusions and Recommendations 183
Dry Well Performance Observations 183
Infiltration Rates and Drainage Times 183
Dry Well Water Quality Observations 187
Comparisons of Observed Water Quality to NJ Groundwater Disposal Criteria 190
Summary of Alternative Stormwater Management Options for Millburn 191
References 193
Appendix A. Primary and Follow-up Report Questions 195
Primary Report Questions 195
1) Are the implementation activities working? 195
2) What is the impact of the effectiveness in various soil types? 196
3) Is it more important to address roof runoff versus other runoff sources such as
driveways and patios, etc? 197
4) Are there any maintenance requirements needed for the dry wells? 197
5) What is the life cycle of the dry wells? 198
6) Do the efficiencies of the dry wells change with time, and are there any
differences in their effectiveness in different soil types over time? 198
7) What is the impact to long-term maintenance requirements for the storm sewers?
198
8) What are the impacts on the water table and on the local water supply? 199
9) What is their impact on groundwater quality? 199
10) Is erosion of the top soil reduced by directing the Stormwater runoff to the dry
wells versus letting the Stormwater runoff drain across properties? 199
11) Does directing Stormwater runoff to the dry wells filter and improve the quality of
the Stormwater? 199
Follow-up Questions Pertaining to the use of Millburn Township Dry Wells 200
1) Evaluate the ordinance that was created by the Township of Millburn to control
erosion and flooding 200
2) Observe if the existing dry wells are working and whether a long-term
maintenance program is valid 200
3) Will the use of the Stormwater model, determine the full reduction of Stormwater
flow and the impact on local streams and the drainage system? 201
4) Use actual field data to determine if there are any improvements in water quality
due to the installation of the dry wells 201
5) Can the existing design of the dry well systems be improved to maximize their
effectiveness, such as in areas where the soil characteristics are poor should the
depth the dry well be increased, or whether cisterns should be recommended over
dry wells or should a system of a combination of cisterns and dry wells be used . 201
6) Is it a good idea to recharge the water from the lawn and/or tee driveways?
Should the water from these areas be filtered? 202
7) Should the inlet of the dry wells have some type of filtering system to increase the
longevity of the dry wells or cisterns? 202
8) Should the roof drainage be separated from the other runoff? 202
9) Are there other alternative designs that could be considered? 202
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10) How would you recommend the ordinance be modified? 202
11) Are there any seasonal variations that could be used to maximize the operations
of the dry wells? 203
12) Are there any proposed changes in the type of vegetation that would improve
stormwater retention? 203
13) With the average reconstruction of homes estimated between 1.5 to 2 percent
for the next ten years, what are the anticipated reductions in stormwater runoff and
the anticipated improvement in water quality? 203
14) What is the cost comparison to treating stormwater with dry wells versus a large
municipal project? 204
15) What are the potential savings in water consumption with the use of cisterns and
what would be the average savings to the resident in annual water bills versus the
added costs of a cistern system over dry well system? 204
16) Are there any drawbacks in raising the water table by installing the dry wells?
204
17) What are the economic benefits in reducing the amount of flooding and erosion
after the installation of the dry wells? Did the model show the improvements? 205
18) How can the model be used as a tool for Millburn and the surrounding
communities as a model in mature urban settings to treat stormwater? 205
Appendix B. Descriptions of Millburn, NJ, Study Sites 207
Plans and Topographic Maps 207
Appendix C. Soils and Infiltration Measurements at Millburn Dry Well Study
Locations 220
Rain Gage Data and Analysis 221
Infiltration Analysis 240
Appendix D. Dry Well Water Quality Analyses 321
Probability Plots 321
Mann-Whitney Test Results 327
Paired Line Plots 335
Time Series Plots 342
Appendix E. Urban Evapotranspiration (ET) Values for Irrigation Calculations.. 346
Evapotranspiration Data 346
ASCE Standardized Reference Equation 346
Rainmaster 347
Evapotranspiration 347
VI
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Tables
Table 1-1. Summary of Infiltration Conditions with Time 11
Table 1-2. Observed and Reported Morton Equation Coefficients 15
Table 1-3.Summary of Mann-Whitney Test for Paired Data 18
Table 1-4. Summary of Paired Sign Test for Metal Analysis 19
Table 1-5. Observed and Reported Morton Equation Coefficients (average and
COV values) 21
Table 1-6. Groundwater Quality Criteria for the State of New Jersey Compared to
Observed Water Quality from Dry Wells 21
Table 2-1. Cost Breakdown for a Typical Dry Well Installation 27
Figure 2-4A. Site photographs of dry wells in Millburn 27
Figure 2-4B. Site photographs of dry wells in Millburn 28
Figure 2-4C. Site photographs of dry wells in Millburn 29
Table 3-1. Infiltration Monitoring Dry Well Locations, Millburn 33
Table 3-2. Water Quality Monitoring Dry Well and Cistern Locations, MillburnJ... 34
Table 3-3. Dates of Final Construction Drawings, Impervious Drainage Areas, and
Dry Well Storage Volumes for Selected Dry Wells Studied 34
Table 3-4. Land Covers for Study Sites (Area, ft2) 41
Table 3-5. Land Covers for Study Sites (Area, %) 42
Table 3-6. Summary of Census 2000 Information Zip Codes 07078 and 07041 43
Table 3-7. Locations of Infiltration Monitoring Sites and Soil Conditions in
Millburn and Short Hills, NJ 43
Table 3-8 Summary of soil characteristics 49
Table 3-9. Newark, NJ, Rain Characteristics (1948-1999) 51
Table 3-10. NJ 24 hour Rainfall Frequency Data 54
Table 4-1. Minimum Design Permeability Rates for Dry Wells 58
Table 4-2. Unrestricted Urban Reuse Regulations for New Jersey 61
Table 4-3. Restricted Urban Water Reuse Regulations for New Jersey 62
Table 4-4. Texas Reuse Water Quality Criteria for Irrigation and EPA Potable
Water MCLs 64
Table 4-4. Texas Reuse Water Quality Criteria for Irrigation and EPA Potable
Water MCLs (cont.) 65
Table 5-1. Groundwater Contamination Potential for Stormwater Pollutants Post-
Treatment 73
Table 5-2. List of Rain Gages Closest to Monitoring Site Locations 77
Table 5-3. Example Summary of Rainfall Information (2/25/2011 - R3) 78
Table 5-5. Morton Infiltration Coefficient Values Typically used in Urban Drainage
Projects 82
Table 5-6. Morton parameters 82
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Table 5-7. Green-Ampt parameters 83
Table 5-8. Morton Coefficients 84
Table 5-9. fc Summary Values and Conditions for 258 Main St 91
Table 5-10. fc Summary Values and Conditions for All of the Other Sites 91
Table 5-11. f0 Summary Values and Conditions for 258 Main St. and 8 South
Beechdroft Rd 93
Table 5-12. f0 Summary Values and Conditions for All of the Other Sites 93
Table 5-13. k Summary Values and Conditions for 258 Main St 95
Table 5-14. k Summary Values and Conditions for All of the Other Sites 95
Table 5-15. Green-Ampt parameters 98
Table 5-16. Summary of Infiltration Conditions with Time 101
Table 5-17. Infiltration Rates Averaged Over Event Durations for A and B Surface
Soils and Well-Drained A Subsurface Soils 118
Table 5-18. Infiltration Rates Averaged Over Event Durations for C and D Surface
Soils and Well-Drained A and B Subsurface Soils 119
Table 5-19. Infiltration Rates Averaged Over Event Durations for C and D Surface
Soils and Poorly-Drained A and B Subsurface Soils Having Extended Standing
Water 120
Table 5-20. Observed and Reported Morton Equation Coefficients 122
Table 6-1. Water Quality Monitoring Locations 125
Table 6-2. Rain Depths for Monitored Events 126
Table 6-3. Summary Table of Standard Methods, Procedures, and Quality
Assurance 128
Table 6-4. Summary of Sampling Results for Total Coliform Bacteria 130
Table 6-5. Summary of Sampling Results for E. coli 131
Table 6-6. Summary of Sampling Results for Total Nitrogen as N 132
Table 6-7. Summary of Sampling Results for NO3 plus NO2 as N 132
Table 6-8. Summary of Sampling Results for Total Phosphorus as P 134
Table 6-9. Summary of Sampling Results for COD 135
Table 6-10. Summary of Sampling Results for Lead 136
Table 6-11. Summary of Sampling Results for Copper 136
Table 6-12. Summary of Sampling Results for Zinc 137
Table 6-13. Summary of Sampling Results for Herbicides and Pesticides 138
Table 6-14. Summary of Anderson-Darling p-values 147
Table 6-15.Summary of Mann-Whitney Test for Paired Data 148
Table 6-16. Summary of Paired Sign Test for Metal analysis 150
Table 6-17. Groundwater Quality Criteria for the State of New Jersey Compared to
Observed Water Quality from Dry Wells 151
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Table 7-1. Source Areas in MiIIburn Residential Land Use (average of investigated
sites) 157
Table 7-2. Runoff Volume Sources (%) for Millburn Residential Area (Newark 1952-
1999 rain series) 158
Table 7-3. Particulate Solids Sources (%) for Millburn Residential Area (Newark
1952-1999 rain series) 159
Table 7-4. Summary of Census 2000 Information for Millburn, NJ, Zip Codes
07078 and 07041 166
Table 7-5 Breakdown of Residential Water Usage in the United States 168
Table 7-6 Average ET0 by Month for New Middlesex and Ringwood, NJ 170
Table 7-7. Irrigation Needs to Satisfy Evapotranspiration Requirements for Essex
County, NJ 171
Table 7-8. Irrigation Needs to Satisfy Heavily Irrigated Lawn for Essex County, NJ
172
Table 7-9. Roof Runoff Harvesting Benefits for Regional Conditions (Medium
Density Residential Land Uses, silty soil conditions) 175
Table 8-1. Summary of Infiltration Conditions at Several of the Test Locations. 184
Table 8-2. Observed and Reported Morton Equation Coefficients 187
Table 8-3. Summary of Mann-Whitney Test for Paired Data 189
Table 8-4. Summary of Paired Sign Test for Metals Analyses 190
Table 8-5. Groundwater Quality Criteria for the State of New Jersey Compared to
Observed Water Quality from Dry Wells 190
Table C-1. Summary of Infiltration Hydrant Water Test (11 Woodfield Dr) 241
Table 6a. 11 Woodfield Dr. (D surface HSG soil conditions, and A and B
subsurface soil conditions) 254
Table 6b. 15 Marion (D surface HSG soil conditions, and A and B subsurface soil
conditions) 254
Table 6c. 258 Main St. (A and D surface HSG soil conditions, and A subsurface
soil conditions) 255
Table 6d. 2 Undercliff Rd (C surface HSG soil conditions, and A and B subsurface
soil conditions) 255
Table 6e. 383 Wyoming Ave (C surface HSG soil conditions, and A subsurface
soil conditions) 256
Table 6f. 260 Hartshorn Dr (D surface HSG soil conditions, and A and B
subsurface soil conditions) 256
Table 6g. 87/89 Tennyson Dr (D surface HSG soil conditions, and A and B
subsurface soil conditions) 257
Table 6h. 1 Sinclair Terrace (D surface HSG soil conditions, and A subsurface soil
conditions) 259
IX
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Table 6i. 142 Fairfield Dr (D surface HSG soil conditions, and A and B subsurface
soil conditions) 259
Table 6j. 8 So. Beechcroft Rd (2 years old, D surface HSG soil conditions, and A
and B subsurface soil conditions) 259
Table 6k. 7 Fox Hill Lane (2.3 years old, D surface HSG soil conditions, and A and
B subsurface soil conditions) 260
Table 61. 9 Fox Hill Lane (D surface HSG soil conditions, and A and B subsurface
soil conditions) 260
Table 6m. 11 Fox Hill Lane (D surface HSG soil conditions, and A and B
subsurface soil conditions) 260
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Figures
Figure 1-1. Peerless Concrete Products, Butler, NJ, supplies the dry wells to
many of the sites in Millburn 2
Figure 1-3. Time series example of dry well water levels for a two month period at
11 WoodfieldDr 9
Figure 1-4. Example of site with poorly draining dry well 13
Figure 1-5. Example of site with good draining dry well 13
Figure 1-6. Log-normal probability plots for the site located on 135 Tennyson
Road (shallow vs. deep) 17
Figure 1-7. Township map showing locations having varying standing water
conditions in monitored dry wells 20
Figure 2-1. Schematic of Millburn Dry Wells 25
Figure 2-2. Peerless Concrete Products, Butler, NJ supplies the dry wells to many
of the sites in Millburn 25
Figure 2-3. Installed dry well in Millburn, NJ, showing the surrounding blanket of
crushed stone before completion of the backfilling 26
Figure 2-5. Cistern monitoring location on Minnisink Rd 30
Figure 2-6. Example dry wells completely draining and with standing water 31
Figure 3-1. Millburn, NJ, high density residential neighborhood 32
Figure 3-2. A medium density residential neighborhood in Millburn, NJ 33
Figure 3-3. Locations of infiltration dry wells (blue icons) and cistern (79
Minnisink, green icons) and water quality monitoring dry wells (red icons) 36
Figure 3-4 Aerial and dry well photos for study areas in Millburn, NJ 40
Figure 3-5. Soil Map for the Township of Millburn 45
Figure 3-6. Hydrologic Soil Group Index of the Township of Millburn for Surface
Soils 46
Figure 3-7. Hydrologic Soil Group Index of the Township of Millburn for Shallow
Subsurface Soils 2ft Deep 47
Figure 3-8. Rain depth distribution with time for Newark, NJ, 1948-1999 51
Figure 3-9. Probability distribution of rain events and runoff quantities for
Newark, NJ (1982-1992) 52
Figure 3-10. Northern New Jersey IDF curve 53
Figure 4-1. Example dry well included in the New Jersey Stormwater Manual 58
Figure 4-2. Typical dry well used in Millburn study areas and volume calculations.
59
Figure 5-1. Time series example of dry well water levels for a two month period at
11 WoodfieldDr 75
Figure 5-2. Photos of rain gages (R1, R2, R3 shown during site calibration) 77
XI
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Figure 5-3. Example of a rain event graph 78
Figure 5-4. Location of dry wells (blue icons), rain gages (yellow icons), and
water quality samplers (red icons for dry wells and green icon for cistern) 79
Figure 5-5. Infiltration studies for a dry well located at 383 Wyoming 80
Figure 5-6. Effects of soil moisture and soil compaction on infiltration rates 84
Figure 5-7. Example of observed data, fitted Morton equation, rain depth, and
water stage in a dry well for three different rain events in a selected dry well 88
Figure 5-8. Box and whisker plot of fc data showing two sets of data 90
Figure 5-9. Box and whisker plot of f0 data showing two sets of data 92
Figure 5-10. Box and whisker plot of k data showing two sets of data 94
Figure 5-11. An example of fitted obsereved data to Morton equation and Green-
Ampt equation 96
Figure 5-12. Residual plots for Morton and Green-Ampt fitted values 96
Figure 5-13. Morton and Green-Ampt fitted curves for observed data 97
Figure 5-14. Linear regression of ft vs MFt for some sites in Millburn, NJ 99
Figure 5-15. Hydrant water test infiltration plots 103
Figure 5-15. Hydrant water test infiltration plots (cont.) 104
Figure 5-16. Time series plots of the water levels for the long-term infiltration
tests at the dry wells 105
Figure 5-17. Township map showing locations having varying standing water
conditions in monitored dry wells 117
Figure 5-18. Infiltration rates averaged over event durations for A and B surface
soils and well-drained A subsurface soils 118
Figure 5-19. Infiltration rates averaged over event durations for C and D surface
soils and well-drained A and B subsurface soils 119
Figure 5-20. Infiltration rates averaged over event durations for C and D surface
soils and poorly-drained A and B subsurface soils having extended standing
water 120
Figure 6-1. PVC Pipe arrangement in dry wells 124
Figure 6-2. Locations of Water Quality Sampling Sites in Millburn, NJ 125
Figure 6-3. Group Box Plot for Total coliform 141
Figure 6-4. Group Box Plot for E. coli 141
Figure 6-5. Group Box Plot for Total Nitrogen as N 141
Figure 6-6. Group Box Plot for NO3 and NO2 as N 141
Figure 6-7. Group Box Plot for Total Phosphorus as N 141
Figure 6-8. Group Box Plot for COD 141
Figure 6-9 Paired line plots, 135 Tennyson Road 143
Figure 6-10 Time series plots, 135 Tennyson Road 145
Figure 6-11 Log-normal probability plots, 135 Tennyson Road 146
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Figure 7-1. Long-term rain depths for individual Newark, NJ, rains (1948-1999). 156
Figure 7-2. Newark, NJ, rain and runoff distributions (1982-1992) 157
Figure 7-3. Runoff volume source contributions for different rain events for
Millburn, NJ 159
Figure 7-4. Particulate solids mass source contributions for different rain events
for Millburn, NJ 160
Figure 7-5. WinSLAMM version 10 screen shot of the biofilter control setup as a
dry well 161
Figure 7-6. Roof runoff volume reductions using dry wells in Millburn, NJ 162
Figure 7-7. Outfall runoff volume reductions using dry wells for the control of roof
runoff in Millburn, NJ 163
Figure 7-8. Drainage times required for full dry wells 6 ft and 3 ft deep for different
infiltration rates 164
Figure 7-9. Roof runoff volume reductions using a single 6 ft deep dry well or two
3 ft deep dry wells 165
Figure 7-10. Clogging potential of dry wells in Millburn, NJ 166
Figure 7-11. Essex County NJ daily per capita Water Use 167
Figure 7-12. A summary of the monthly rainfall pattern for Millburn Data 168
Figure 7-13. Plot of supplemental irrigation needs to match evapotranspiration
deficit for Essex County, NJ 171
Figure 7-14. Plot of supplemental irrigation needs to match heavily watered lawn
deficit for Essex County, NJ 172
Figure 7-15. WinSLAMM, version 10, input screen for water tanks/cisterns 174
Figure 7-16. Roof runoff and water tank storage production function for Millburn
Township residential areas (typical silty soil conditions) 174
Figure 7-17. Water storage tank benefits for supplemental irrigation to meet
heavily irrigated lawn deficits, Millburn, NJ 176
Figure 7-18. Production functions for cisterns and dry wells in residential areas,
Millburn, NJ 177
Figure 7-19. Input screen for rain gardens in WinSLAMM, version 10 179
Figure 7-20. Rain garden performance for impervious areas for different soil
infiltration rates, Millburn, NJ 180
Figure 7-21. Clogging potential of rain gardens receiving roof runoff, Millburn, NJ
(about 7% of the roof area) 181
Figure 8-1. Township map showing locations having varying standing water
conditions in monitored dry wells 186
Figure 8-2. Log-normal probability plots for dry well samples located at 135
Tennyson Road (shallow vs. deep) 188
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AD
AN OVA
ASCE
BDL
BGS
BMP
BOD5
CBOD
Cl
COD
COV
DEM
EPA
ET
ETA
FAO
HOPE
HN03
HSG
IDF
LDL
MCL
MPN
N.J.A.C
ND
NJDEP OPRA
NOAA
NPDES
NRCS
NSQD
NTU
PVC
SAR
SCS
SMCLs
Std Dev
TN
TSS
UDFCD
UDL
USDA
USGS
WinSLAMM
WUCOLS
Glossary
Anderson-Darling Statistical Test
Analysis of Variance
American Society of Civil Engineers
Below Detection Limit
Below Ground Surface
Best Management Practice
Five Day Biochemical Oxygen Demand
Carbonaceous Biochemical Oxygen Demand
Confidence Interval
Chemical Oxygen Demand
Coefficient of Variation
Digital Elevation Model
Environmental Protection Agency
Evapotranspiration
Estimated Time of Arrival
Food and Agriculture Organization
High-density Polyethylene
Nitric Acid
Hydrologic Soil Group
Intensity, Duration, Frequency
Lower Detection Limit
Maximum Contaminant Limits
Most Probable Number
New Jersey Administrative Code
Not Detected (below detection limits)
NJ Department of Environmental Protection - Open Public Records Act
National Oceanic and Atmospheric Administration
National Pollutant Discharge Elimination System
Natural Resources Conservation Service
National Stormwater Quality Database
Nephelometric Turbidity Units
Polyvinyl Chloride
Sodium Absorption Ratio
Soil Conservation Service
Secondary Maximum Contaminant Levels
Standard Deviation
Total Nitrogen
Total Suspended Solids
Urban Drainage and Flood Control District
Upper Detection Limit
United States Department of Agriculture
United States Geological Survey
Source Loading and Management Model
Water Use Classification of Landscape Species
XIV
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Chapter 1 Executive Summary
Description of Millburn and Its Dry Wells
The Township of Millburn, Essex County, NJ, is located near New York City, and less
than 10 miles from Newark International Airport. The 2010 US census indicated the
Township had a population of 20,149. Housing costs are very high (According to
Wikipedia, Millburn had the highest annual property tax bills in NJ in 2009 at an average
of more than $19,000 per year, compared to the statewide average property tax that
was $7,300, the highest statewide average in the country). There are about 5,900
detached homes in the Township and about 1,500 have dry wells.
In 1999, the Township of Millburn created an ordinance that required increased runoff
from new impervious areas to be directed into seepage pits (dry wells). The purpose of
this project was to investigate the effectiveness of this ordinance, specifically to
examine the use of dry wells as a technique to redirect surface runoff to the local
shallow groundwater. The objective of this approach is to reduce local drainage and
erosion problems associated with new development and increased impervious areas of
currently developed areas. The slower release of the shallow groundwater to surface
streams also better simulates natural hydrologic patterns with reduced in-stream
problems associated with increased rapid surface runoff. The Township of Millburn has
a stable population where there is little vacant land. All new construction within the
community is performed on previously developed plots.
The Millburn Township stormwater regulations (Development Regulations) list dry wells
as one option for minimizing increased flows associated with new (and increased)
development. They do not include any specific criteria for their use, except for a
statement pertaining to a 60 cm (2 ft) blanket of crushed stone surrounding the dry well.
Specifically, they do not describe applicable soil characteristics, groundwater conditions,
or suitable source waters. The NJ State stormwater regulations also requires the
infiltration of excess water above natural conditions associated with development or
land modifications (either maintaining the pre-development groundwater recharge or
preventing excess surface runoff). The state dry well regulations describe the
construction of the dry wells, the acceptable soil conditions (NRCS hydrologic soil
groups, HSG, A and B), groundwater conditions (at least 60 cm or 2 ft above seasonal
water table), and source waters (roof runoff only).
A dry well is a subsurface infiltration stormwater disposal practice that receives
stormwater runoff from surrounding areas for subsurface disposal to shallow
groundwater. Most of the dry wells in the Township of Millburn are precast concrete
structures (Figure 1-1), with open bottoms resting on 0.6 m (2 ft) crushed stone layers
and with 0.6 m (2 ft) of crushed stone surrounding the dry wells. Most of the dry wells
receive water directly from roof drain leaders or by storm drain inlets located in
driveways or small parking lots. Some also have grated covers and receive surface
runoff from the surrounding lawn or paved areas.
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Figure 1 -1. Peerless Concrete Products, Butler, NJ, supplies the dry wells to many of the sites in
Millburn (photo from http://www.peerlessconcrete.com/).
Figure 1-2 shows typical dry well installations. Many of the dry wells are located in
landscaped areas and have open covers, allowing surface runoff from the lawns to
enter the dry wells, as well as the subsurface piped roof runoff. Some are also located
in paved areas, also allowing surface runoff from the driveways to enter along with the
roof runoff.
Backyard dry well showing lawn area also
as a source.
Backyard dry well showing driveway runoff
also as a source.
Figure 1-2. Typical Millburn dry well locations.
-------
Fifteen dry wells were monitored for water levels during periods ranging from 2 months
to one year, or by controlled tests using Township water from fire hydrants. Four
systems (three dry wells and one cistern) were also monitored for water quality during
10 storms to indicate any differences in water quality directly below the dry well (or at
the cistern inlet) compared to deeper depths at least 0.6 m (2 ft) below the bottom of the
crushed stone layer, or at least 1.2 m (4 ft) below the bottom of the dry well itself (or in
the cistern). Four rain gages were also installed near the dry wells.
The study sites were surveyed to obtain detailed development characteristics that affect
the amount of runoff from the different source areas. Soil information was also
compiled. Most of the surface soils were of NRCS hydrologic soil group (HSG) C or D
category, indicating poor infiltration potential. However, subsurface soils where the dry
wells were located were mostly in the HSG A or B categories (glacial deposits) with
much improved infiltration potentials. The groundwater in the area may be as shallow as
2.4 to 3 m (8 to 10 ft) below the ground surface in low-lying areas along the river, but
otherwise is expected to be greater than 8 m (25 ft) below the ground surface in
general.
Project Objectives and Findings
The overall objective of this project was to investigate the effectiveness of Millburn's
stormwater management practices that rely on the use of dry wells to limit stormwater
discharges into the local drainage system. Millburn has separate sewers and there are
concerns about drainage problems developing in areas of new construction. The city
has been pleased with the performance of the dry wells. This project quantified their
performance and offered suggestions for improved stormwater management in the
area.
Both short- and long-term infiltration monitoring was conducted in a selection of Millburn
dry wells. There were varying levels of dry well performance in the area, but most were
able to completely drain within a few days. However, several had extended periods of
standing water that may have been associated with high water tables, poorly draining
soils (or partially clogged soils), or detrimental effects from snowmelt. The infiltration
rate characteristics were separated into three conditions: 1) HSG A and B surface soils
having well-drained HSG A subsurface soils; 2) C and D surface soils and well-drained
A and B subsurface soils; and, 3) C and D surface soils and poorly drained subsurface
soils with long-term standing water. Even sites having surface C and D soils (not
acceptable infiltration sites according to the NJ dry well standards) had much better
subsurface conditions where the dry wells were located. The infiltration rates for these
conditions were less than for the excellent areas having HSG A and B surface soils, but
all met the infiltration rate criterion of the state guidelines.
Water samples were collected at one cistern and three dry well locations during ten
rains. The samples were analyzed for nutrients and heavy metals, and selected
-------
samples were also tested for pesticides and herbicides. The samples were collected
directly below the dry wells (or at the inlet of the cistern) for comparison to water
samples collected deeper (at least 1.2 m (4 ft)) beneath the dry wells (and at the outlet
of the cistern). Various statistical tests were used to compare the measured water
quality to detect any significant differences due to operation of the dry wells. The paired
sample sets did not indicate any significant differences for any of the water quality
constituents for these samples for the dry wells (ten events in three dry wells). The
cistern outlet median total coliform values were greater than the inflow median values,
indicating possible re-growth; however, the median E. coll and COD cistern outlet
values were less than the inflow values for these constituents. These findings indicate
that the dry wells did not significantly change the water quality for the monitored
stormwater constituents. If the influent stormwater is of good quality, the dry wells can
be a safe disposal method. However, the bacteria and lead concentrations exceeded
the groundwater disposal criteria for NJ and may require treatment if the aquifer is
critical (even though these were the runoff conditions and were not affected either by
increases or decreases, by the dry wells).
Dry wells may be a preferred option in cases that are allowed by the NJ dry well
disposal regulations for stormwater which limits their use to areas having excellent soils
(HSG A or B; although subsurface soils should be considered also), where the
groundwater table is below the dry well system (to prevent standing water in the dry
wells and very slow infiltration), and to only receive roof runoff water (generally the best
quality runoff from a site and the snowmelt from roofs would not be contaminated with
deicing salts). The Millburn Township stormwater regulations do not restrict dry well
disposal to just roof runoff, but also includes disposal of all excess runoff from new
development as one option.
Beneficial uses of the roof runoff for irrigation may be a preferred alternative, and in
many cases may be less costly than dry wells, especially considering increasing water
utility rates and the desire to conserve highly treated domestic water supplies.
Groundwater recharge may be an important objective for an area and dry well use
addresses that objective. However, "over-irrigation" (beyond the plants
evapotranspiration (ET) deficit needs, but less than would produce direct runoff) also
addresses that objective and would also conserve domestic water while offering better
groundwater protection than the dry wells.
Rain gardens are another viable alternative for stormwater management in the Millburn
area, especially as they provide some groundwater quality protection and can be
incorporated into the landscaping plans of homes. They likely require additional
maintenance, similar to any garden, but can be located to receive runoff from several
source areas on a site, increasing the overall stormwater management level. In some
areas, they have even been incorporated along roads, as curb-cut biofilters, resulting in
significant overall runoff volume reductions, but with special care to prevent premature
clogging and appropriately sized to handle the large flow volumes.
-------
It is important to use alternative stormwater control options when dry well use is
restricted, such as with the following conditions:
• poor infiltration capacity of subsurface soil layers
• concerns about premature clogging or other failures due to sediment discharges or
saline snowmelt discharges to dry wells
• seasonal or permanent high water tables
• concerns about groundwater contamination potential
Primary Report Questions
The following questions were listed during the development of this project by Millburn
Township personnel, in addition to others that were asked during the review of the final
report: (see appendix A for a comprehensive list of primary and follow-up questions)
1) Are the implementation activities working?
At most of the monitoring locations, the dry wells drained quickly and completely after
rains (within a day or two for full dry wells). However, some locations experienced
standing water for extended periods and would be considered to not be working as
intended. Basically, more careful site evaluations and design, along with better control
of the source waters entering the dry wells, are needed. In critical situations, alternative
stormwater controls should be considered.
2) What is the impact of the effectiveness in various soil types?
Originally, it was thought that the surface soil characteristics would have little affect on
the performance of the dry wells, as they are subsurface devices and most of the water
is percolating from the dry wells at depth and not near the surface. At all of the Millburn
test locations, the subsurface soils had better infiltration characteristics compared to the
surface soils; in fact, the subsurface soils were all HSG A or B, which meet the State's
dry well design standards, even though the surface soils were mostly HSG C or D soils.
The measured infiltration rates from all of the dry wells meet the minimum rates
specified by the State's design guidance, but there were substantial variations, as noted
below (average infiltration rates for typical storm durations):
• A and B surface soils and having well-drained A subsurface soils (190 mm/hr or
7.6 in./hr)
• C and D surface soils and having well-drained A and B subsurface soils (43
mm/hr or 1.7 in./hr)
• C and D surface soils and having poorly-drained subsurface soils with long-term
standing water (20 mm/hr or 0.8 in./hr)
Generally, the lowest infiltration rates associated with long-term saturated conditions
averaged about 12 mm/hr (0.5 in./hr). Again, all of these rates satisfied the State's
design guidance. However, several sites had long-term standing water and never
-------
drained completely, while other locations required several weeks to drain (and seldom
were the dry periods long enough to allow complete drainage).
Therefore, even though the site conditions met the design guidance, some locations still
had standing water. It is likely that seasonal (or possibly long-term) high water tables
occurred at some of the locations. The lack of site specific groundwater depth
information did not allow this to be verified, but the performance of some of the drain-
down curves supports this finding.
In other cases, the rates appeared to vary by season, with some incidences of standing
water mostly in the spring and sometimes in the winter. It is thought that soil chemistry
changes due to saline snowmelt waters entering the dry wells from non-roof areas were
responsible for these periods of reduced performance. De-icing chemicals would likely
be heavily applied near home walkways, porches, steps and driveways (but not roofs). If
this water was allowed to enter the dry wells and if there was clay in the surrounding
soils, sodium adsorption ratio (SAR) imbalances would disperse the clays and cause
significant reductions in the infiltration rates. In most cases, excess sodium would be
rinsed from soils over a few months, partially restoring the infiltration conditions.
However, problems would continue to reoccur with subsequent saline snowmelt
discharges to the dry wells.
Therefore, the sites that had sandy surface and subsurface soils (HSG A and B soils)
performed the best. It was thought that the other sites would also perform well, having
good subsurface soils, but their characteristics were not likely as good as the other
locations (even in the same soil category), and the likely presence of small to moderate
amounts of clay would be more sensitive to SAR problems.
3) Is it more important to address roof runoff versus other runoff sources such as
driveways and patios, etc?
Roof runoff contributes about one-third of the average annual runoff for the Millburn
residential areas, a typical value compared to other residential areas in the US.
However, the roof runoff only contributes about 11 % of the TSS. Other source areas,
such as driveways on the private property, are important runoff sources. Streets
contribute about one-fourth of the runoff. Patios are not very significant as their runoff is
mostly directed to the landscaped areas where it can infiltrate. After the roofs, the
driveways should be controlled (such as by using rain gardens near the lower ends of
the driveways near the streets, as many are steeply sloped from the house to the
roads). Dry wells for driveways (or other paved areas besides roofs) should not be
considered due to the much greater sediment load that would likely cause premature
failure by clogging.
4) Are there any maintenance requirements needed for the dry wells?
-------
It is difficult to maintain the dry wells as they are buried. The bottoms are open and
resting on crushed stone allowing the penetration of silts and clays into the voids. These
materials cannot be easily removed. However, leaves and other vegetation debris on
top of the crushed stone could possibly be removed without disturbing the rocks. Many
of the dry wells have grated openings allowing surface runoff from the surrounding
areas to directly flow into the dry wells. During construction, erosion sediment may enter
the dry wells which would significantly hinder their performance. As noted, organic
matter from the surrounding areas can also directly enter the dry wells through these
surface openings. It is recommended that only directly connected roof leaders enter the
dry wells (in compliance with the state regulations) and that the dry wells be inspected
and superficially cleaned periodically. Leaf filters should also be installed on the roof
gutters or down spouts or capture these materials before they are discharged into the
dry wells. If needing maintenance to remove the silts and sands from the crushed stone,
much of the crushed stone would have to be removed and replaced, a costly option
similar to totally rebuilding the dry well. Prevention (such as by only allowing roof runoff
to enter the dry wells) is therefore key to long-term satisfactory performance.
5) What is the impact of dry wells on groundwater quality?
Residential roof runoff has few contaminants and should therefore be the preferred
source of water directed to the dry wells (although bacteria may be a problem, and other
pollutants may periodically be a concern, especially if zinc and copper materials are
used on the roofs). The dry wells provided no significant improvements to the quality of
the stormwater, based on the limited sampling conducted during this study. If other
source waters enter the dry wells (such as from driveways and streets), groundwater
contamination would be a much greater concern. The best quality waters in residential
areas that should not present a significant groundwater hazard and is most suitable for
direct infiltration is roof runoff. However, bacterial and lead concentrations observed
below the dry wells frequently exceeded the NJ groundwater disposal limits and some
additional control may therefore be needed.
6) Evaluate the ordinance that was created by the Township of Millburn to control
erosion and flooding.
The local Millburn Township ordinance should be modified to allow dry well use only in
areas already having good stormwater runoff quality (such as would be expected for
most roofs), or require suitable pretreatment, such as effective grass filtering. In
addition, the local ordinance should also prohibit dry well use in areas having seasonal
or permanent high water tables, as those conditions result in long-term standing water
in the dry wells. If located in areas having poorly draining subsurface soils, the dry well
designs need to be modified (greatly enlarged) to account for the more slowly draining
conditions. It is recommended that dry well use be restricted to roof runoff, and
alternatives that infiltrate water through surface soils (such as rain gardens) be used to
treat driveway and parking lot runoff (or in areas having shallow groundwater). Irrigation
of landscaped areas using roof runoff (and pretreated paved area runoff) is also a
-------
suitable option that can provide economic benefits to the land owner and should be
encouraged by the ordinance.
Infiltration Tests at Millburn Dry Well Installations
Infiltration tests were conducted during two project phases: the first phase filled the dry
wells with domestic water from Township fire hydrants and the decreasing water levels
were recorded; the second phase used continuous water level monitoring in a fewer
number of dry wells during many rains. The infiltration measurements were conducted
using continuous recording (10 minute observations) LeveLoggers by Solintest that
were installed in the dry wells. The short-term tests were conducted in dry wells
throughout the Township to measure the influence of many of the conditions present in
the community. These tests were conducted using water from fire hydrants and included
filling the dry wells completely. The LeveLoggers were then used to record the drop in
water level over time. The long-term tests were conducted in fewer dry wells (based on
the number of LeveLoggers available). These were installed for several months to over
a year and continuously recorded the water levels in the dry wells every 10 minutes.
Close-by rain gages were also used to record local rains associated with these events.
These rain and water level data were downloaded by PARS Environmental personnel
and uploaded to their ftp website where University of Alabama researchers downloaded
the data for analysis.
The first step in the data analyses of the long-term tests was to plot the data as time
series. Figure 1-3 is an example time series plot of the water levels recorded over a two
month period at 11 Woodfield Dr. showing six separate events (the first peak only
shows the dropping water levels from the Oct 13, 2009 event). The infiltration
characteristics of the dry well installations were calculated from the recession curves of
these individual rain events. The infiltration rates for each ten minute step were
calculated based on the drop in water level per time increment, resulting in infiltration
rate plots of in./hr vs. time since the peak water level. These are classical infiltration rate
plots and statistical analyses were used to calculate infiltration rate equation parameters
for two common infiltration equations (Morton and Green-Ampt).
-------
120
.
I
•
.
.
E 60 '•
1
0 *
(
,*-"•
i
;
•
10/13/2009
10/Z4/2009
\
10000
HWoodfield Dr
10/13/2009 - 12/18/2009
12/09/2009 1
12/13/2009
/
/
t
20000 30000 4OOOO 50000 60000 70000 BOOOO 90000 100000
Time (min)
Figure 1-3. Time series example of dry well water levels for a two month period at 11 Woodfield Dr.
Groundwater recharge is a suitable beneficial use of stormwater in many areas as it is
used to augment local groundwater resources. This study showed how the dry wells
could be very effective in delivering the stormwater to the groundwater. Even though the
surface soils were almost all marginal for infiltration options, the relatively shallow dry
wells were constructed into subsurface soil layers that had much greater infiltration
potentials. However, some of the monitored dry well locations experienced seasonal
high groundwater elevations, restricting complete draining of the dry wells after rains.
While surface and subsurface soil information is readily available for the Township (and
in most other areas of the country), the presence of the shallow water table (or bedrock)
is not well known. This makes identifying the most suitable locations for dry wells
difficult, as the seasonal groundwater should be at least 4 m (12 ft) below the ground
surface (or 60 cm, 2 ft, below the lowest gravel fill layer beneath the dry well: 2 ft of
surface cover, 6 ft dry well concrete structure, 2 ft lower gravel layer, and 2 ft of
separation above the high seasonal groundwater depth).
Calculating the benefits of the dry wells (including developing sizing requirements)
requires the use of an appropriate infiltration equation, preferably as part of a
continuous model examining many years of actual rainfall data for a specific area. Two
commonly used infiltration equations (Morton and Green-Ampt) were evaluated for their
potential use to calculate groundwater recharge at the case study locations in the
Township of Millburn, NJ. The fitted graphs and resulting derived equation parameters
showed that although the Morton equation usually indicated a better fit to the observed
data, the calculated parameters of both infiltration models were not close to values
reported in the literature, especially for urban areas. This is likely because the infiltration
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characteristics in the dry wells were mostly affected by subsurface conditions compared
to the literature values that were compared to surface soil characteristics. When the
subsurface conditions are used in the comparisons, the observed and literature values
are in better (but still not close) agreement. Therefore, locally measured infiltration test
data at a scale approaching the size and depth of the final devices should be used for
more reliable design guidance, instead of relying on literature values.
Factors Affecting Infiltration Rates
The data analyses of the infiltration data resulted in several interesting conclusions. One
of the first issues noted by the field personnel when installing the water level recorders
and observing the dry wells over time was that some of the locations experienced
periodic (or continuous) long-term standing water in the dry wells, indicating seasonal or
permanent high water table conditions, or partially clogged dry wells.
Table 1-1 summarizes the dry well performance observed during the monitoring
program, including the length of monitoring, hydrograph behavior, and the presence of
standing water (and the percentage of time when the dry well was dry). Figures 1-4 and
1-5 are time series plots of the water levels for the long-term infiltration tests at two dry
wells representing a site with poorly draining conditions and another site with rapid
drainage conditions. These plots show the water elevations in the dry wells along with
the corresponding rain depths as recorded at the nearest rain gage. The rain data
indicate the total rain depth and the start and end times; the graphs cover too long of a
period to show variable rain intensities during the rains. The times and depths are the
most important rain information for these measurements as they relate most closely to
the runoff quantity and the dry well water elevations.
10
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Table 1-1. Summan
11 Woodfield Dr.
15 Marion Dr.
383 Wyoming Ave.
258 Main St.
260 Hartshorn
2 Undercliff Rd
87/89 Tennyson
Start date of
series
Oct 1 1 , 2009
June 17,
2010
July 16, 2009
June 16,
2010
August 9,
2010
July 18, 2009
August 10,
2010
End date of
series
December
20, 2009
August 6,
2010
October 14,
2009
Augusts,
2010
August 1,
2011
October 6,
2009
August 5,
2011
# of dry well
events
1 hydrant
5 rains (1
small rain
missing)
1 hydrant
5 rains (2
small rains
missing)
1 hydrant
6 rains (2
small rains
missing)
5 rains (2
smaller rains
missing)
Many
1 hydrant
3 rains
Many
/ of Infiltration Conditions with Time
% of time
dry well
was dry
89%
71%
81%
98%
10%
79%
0%
Consistent shape
with time?
Consistent shape
with time
Consistent shape
with time
Consistent shape
with time
Consistent shape
with time
Consistent shape
with time
Consistent shape
with time
Consistent shape
with time
Standing water after
events?
Quickly drained
(within a day); No
standing water at any
time
Several days to drain;
No standing water at
anytime
Several days to drain
if full;
No standing water at
anytime
Very rapid drainage
time;
No standing water at
anytime
Slow drainage time
(about a week if full),
but dry if given
enough time between
rains
Several days to drain
if full;
No standing water at
anytime
Very slow drainage
time (a couple of
weeks); standing
water and never dry
during this year period
Other comments
15 hours total drainage
time during hydrant test
4.5 days total drainage
time during hydrant test
1 day total drainage time
during hydrant test
Clogging or poor soils,
not high water table.
Possible SAR issues in
the Winter and Spring,
recovered by mid-
summer.
10 days total drainage
time during hydrant test
Slow drainage may be
due to saturated
conditions, never reached
stable low water level. If
due to SAR, did not
recover.
11
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7 Fox Hill
8 So. Beechcroft
142 Fairfield
36 Farley Place
Start date of
series
August 7,
2010
July 19, 2009
August 10,
2010
June 16,
2010
End date of
series
March 23,
2011
September
27, 2009
March 4,
2011
August 5,
2010
# of dry well
events
Many
1 hydrant
6 rains
many
3 rains
% of time
dry well
was dry
2%
71%
66%
97%
Consistent shape
with time?
Consistent shape
with time
Consistent shape
with time for rains,
but hydrant test (at
end of monitoring
period at end of
Sept) was very
rapid
Somewhat
inconsistent shape
with time
Consistent shape
with time
Standing water after
events?
Slow drainage time
(about a week or two
if full), but dry if given
enough time between
rains
Quickly drained
(within a day or two if
full); No standing
water at any time
Quickly drained
(within a day or two if
full) to poorly drained
(a week for moderate
rains); Standing water
during periods of large
and frequent rains
Very rapid drainage
time;
No standing water at
anytime
Other comments
Clogging or poor soils
especially in Spring,
possibly SAR issues, not
high water table
3 hours total drainage
time (half full) during
hydrant test
Slowly drained conditions
in Spring likely due to
saturated conditions, or
SAR. Not likely due to
high water table
12
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260 Hartshorn
120
~. 100
i*
; so
I
60
40
S 20
0
1
- 2
- 3
- 4
- 5
n
sa
•water
stage
-rain
event
Time
Figure 1-4. Example of site with poorly draining dry well.
120
100
80
60
I
20
383 Wyoming Ave.
Hydrant test
\
0.5
1
- L5 ^
2 S-
2.5
3
3.5
4
•water
stage
•rain
depth
Time
Figure 1-5. Example of site with good draining dry well.
13
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In almost all cases, the general shapes of the recession limbs (water elevation drops
with infiltration) are similar for all observations at the same site, including the hydrant
tests. However, some changed with time, including several that indicated slower
infiltration with more standing water conditions in the winter and spring. This may be
due to SAR issues (sodium adsorption ratio) that results in dispersed clays from high
sodium content in snowmelt. Normally, snowmelt would not affect these units if only roof
runoff is directed to the dry wells. However, if walkway or driveway runoff drains to dry
wells, de-icing salts may be in the snowmelt, increasing the SAR and decreasing the
infiltration rates.
Standing water was observed in the dry well at 87/89 Tennyson when sufficient time
occurred to allow the water to reach a consistent minimum water level of about 0.9 m (3
ft). It is expected that this site very likely has a shallow water table condition. The
drainage rates were very slow, so the inter-event periods were not sufficiently long to
enable drainage to the stable water level until after about a two week dry period. The
slow drainage rate may have been caused by saturated conditions associated with
groundwater mounding. Several sites (260 Hartshorn, 7 Fox Hill, and 142 Fairfield)
experienced periodic slow- draining conditions, mainly in the spring that could have
been associated with SAR problems. The slow infiltration rates could be due to poor
soils (with the clays resulting in SAR problems), or saturated soil conditions. The other
sites all had rapid drainage rates that were consistent with time.
Another obvious factor affecting the observed infiltration rates was that one or two of the
locations had significantly higher infiltration rates than the other sites (all having no
standing water issues). These sites were the ones indicated as having the highest
surface infiltration rate potentials (even though the infiltration rates of the dry wells were
mostly affected by the subsurface soil conditions, which were mapped as being similar
A and B conditions for all locations). It is therefore expected that these locations had
better subsurface soil conditions compared to the other sites, even though mapped as
being similar.
Therefore, the Township of Millburn infiltration rate characteristics were separated into
three conditions:
• A and B surface soils having well drained A subsurface soils
• C and D surface soils having well drained A and B subsurface soils
• C and D surface soils having poorly drained A and B subsurface soils with long-
term standing water
Table 1-2 compares the observed Horton equation coefficients for the sites having well-
drained subsurface soils with equation coefficients that have been reported in the
literature. The standing water data are not used in these calculations as most of the
observations could not be successfully fitted to the Horton equation. The almost steady
infiltration rates (but with substantial variation) were all very low for those conditions and
14
-------
likely represent the fc (long-term constant rate) conditions only and were therefore
included in that parameter category.
Table 1-2. Observed and Reported Morton Equation Coefficients
Surface A and B soils well drained A subsurface soils
(average and COV)
Surface C and D soils well drained A and B subsurface
soils (average and COV)
UDFCD (2001) A soils (average)
UDFCD (2001) B soils (average)
UDFCD (2001) C and D soils (average)
Pitt, etal. (1999) Clayey, dry and non-compacted (median)
Pitt, etal. (1999) Clayey, other (median)
Pitt, etal. (1999) Sandy, compacted (median)
Pitt, etal. (1999) Sandy, non-compacted (median)
Akan (1993) Sandy soils with little to no vegetation
Akan (1993) Dry loam soils with little to no vegetation
Akan (1993) Dry clay soils with little to no vegetation
Akan (1993) Moist sandy soils with little to no vegetation
Akan (1993) Moist loam soils with little to no vegetation
Akan (1993) Moist clay soils with little to no vegetation
f0 (in./hr)
44.6 (0.53)
4.3 (0.64)
5.0
4.5
3.0
11
2
5
34
5
3
1
1.7
1
0.3
fc (in./hr)
5.6 (0.2)
0.45 (0.85)
1.0
0.6
0.5
3
0.25
0.5
15
k(1/min)
0.06 (0.22)
0.01 (0.63)
0.04
0.11
0.11
0.16
0.06
0.1
0.08
(1 in./hr = 25.4mm/hr)
f0 = initial infiltration rate (in./hr)
fc = final infiltration rate (in./hr)
k = first order rate constant (1/min)
The very large observed f0 value (45 in./hr) for the A and B surface soil sites that are
well drained is greater than any of the reported literature values, and only approaches
the observations for the non-compacted sandy soil conditions (34 in./hr) observed by
Pitt, et al. (1999). The subsurface soil conditions affecting the dry well infiltration rates
are likely natural with little compaction. Also, the subsurface soils at that location are
noted as being sandy loam (A) and stratified gravelly sand to sand to loamy sand (A).
The other sites having smaller f0 rates (4.3 in./hr) are described as gravelly sandy loam
(A) and fine sandy loam (B) and are similar to many of the reported literature values for
sandy soils, with some compaction.
The large fc value (5.6 in./hr) observed for the well-drained A and B surface soil location
is bracketed by the non-compacted clayey and sandy soil conditions (3 and 15 in./hr)
reported by Pitt, etal. (1999), but is substantially larger than the other reported values.
The fc value observed for the well-drained C and D surface soil site (0.45 in./hr) is
similar to the other reported values (0.5 to 1.0 in./hr). The k first-order rate values (0.01
and 0.06 1/min) are similar, but on the low side, of the reported values (0.04 to 0.11
1/min).
In order to most accurately design dry well installations in an area, actual site
observations of the expected infiltration rates should be used instead of general
literature values. This is especially true for surface infiltration devices (such as rain
15
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gardens), where compaction due to construction activities and general urban use will
have a much greater effect than on the deeper subsurface soils. Also, all of the sites in
this study had improved infiltration characteristics with depth compared to expected
surface conditions; in other cases, this may not be true. Criteria based only on surface
soil conditions are likely not good predictors of deeper dry well performance. Luckily,
county soil surveys do have some subsurface soil information that was found to be
generally accurate during this study. Unfortunately, shallow water table conditions are
not well known for the area and that characteristic can have a significant detrimental
effect on the observed dry well performance.
Water Quality Observations
Water samples were collected at three dry wells and at one cistern during ten rains. The
samples were analyzed for nutrients and heavy metals, and selected samples were also
tested for pesticides and herbicides. The samples were collected directly below the dry
wells (or at the inlet of the cistern) for comparison to water samples collected at least
0.6 m (2 ft) below the 0.6 m (2 ft) gravel layer beneath the dry wells (and in the cistern),
for a total subsurface flow path of at least 1.2 m (4 ft) through the crushed stone and
subsurface soil (more than the minimum 2 ft separation to the groundwater table as
required by the NJ stormwater infiltration regulations). Various statistical tests were
used to compare the water quality from the inlet to the outlet locations to detect any
significant differences due to operation of the dry wells.
Log-normal probability plots were used to identify the range, randomness, and normality
of the data. The log-normal probability plots are shown for inflow vs. cistern, and for the
cistern and deep vs. shallow for each sampling site. Figure 1-6 includes example paired
log-normal probability plots for one of the sites (135 Tennyson Road, Millburn, NJ
07078) for different parameters including bacteria, nutrients, and COD. For these plots,
most of the data are seen to overlap within the limits of the 95% confidence limits,
indicating that the data are likely from the same population. Also, the data seem to
generally fit a straight line, indicating likely log-normal data distributions, as verified by
the Anderson-Darling test statistic.
16
-------
Probability Plot of 135 Shallow, 135 Deep
Lognormal-95%CI
Total coliform (MPN)
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
E. coli (MPN)
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
Jtt£l3£}
fflfflfl
1.0 10.0
Total Nitrogen as N (mg/L)
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
ou--,
I 60--!-
Scale N AD
0.1 1.0
NO3 - N (mg/L)
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
0.10 1.00
Total Phosphoras as P (mg/L)
Figure 1-6. Log-normal probability plots for the site located on 135 Tennyson Road (shallow vs.
deep)
Table 1-3 shows the output obtained using MINITAB for nonparametric Mann-Whitney
comparisons between paired data. Except for the bacteria and COD results for the
cistern site, as noted previously, all paired sample sets did not indicate significant
differences for these numbers of samples at the 0.05 level for the numbers of sample
pairs available.
17
-------
Table 1-3.Summary of Mann-Whitney Test for Paired Data
Parameter
Total
Conforms
£. co/;
Total
Nitrogen as
N
NO3 plus
N02-N
Total
Phosphorus
as P
COD
p-value
Significant Difference
Observes?
(at level of 0.05)
p-value
Significant Difference
Observes?
(at level of 0.05)
p-value
Significant Difference
Observes?
(at level of 0.05)
p-value
Significant Difference
Observes?
(at level of 0.05)
p-value
Significant Difference
Observes?
(at level of 0.05)
p-value
Significant Difference
Observes?
(at level of 0.05)
79 Inflow vs.
79 Cistern
0.03
Yes (but cistern
median values
were larger than
the inflow median
values)
0.05
Yes (cistern
median values
significantly less
than the inflow
median values)
0.86
No
0.14
No
0.77
No
0.04
Yes (cistern
median values
significantly less
than the inflow
median values)
135 Shallow vs.
135 Deep
0.40
No
0.60
No
0.50
No
0.24
No
0.94
No
0.14
No
18 Shallow vs.
18 Deep
0.16
No
0.69
No
0.42
No
0.15
No
0.10
No
0.40
No
139 Shallow vs.
139 Deep
0.72
No
1
No
0.64
No
0.77
No
0.27
No
0.83
No
Table 1-4 lists the results for the paired sign test (used because of numerous non-
detected values) for lead, copper and zinc observations for the cistern and dry well
samples. No statistically significant differences were seen between the sample sets for
the heavy metals for the numbers of samples available.
18
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Table 1-4. Summary of Paired Sign Test for Metal Analysis
Metal
Lead
Copper
Zinc
p-value
Significant Difference in Medians?
p-value
Significant Difference in Medians?
p-value
Significant Difference in Medians?
79 Inflow
vs.
79 Cistern
>0.06
No
0.13
No
0.45
No
135 Shallow
vs.
135 Deep
>0.06
No
*
*
0.45
No
18 Shallow
vs.
18 Deep
0.18
No
>0.06
No
>0.06
No
139 Shallow
vs.
139 Deep
>0.06
No
*
*
>0.06
No
All the results are below detection limit (BDL), therefore it is not possible to do a paired sign test
Statistical analyses indicated that the differences in water quality between the shallow
and the deeper samples were not significant for the number of sample pairs available
(p-values were > 0.05). However, significant differences were found (p< 0.05) between
the quality of inflow samples and cistern samples for total coliforms (possible re-growth),
E. co//, and COD (concentration reductions). These findings indicate that the dry wells
do not significantly change the water quality for most of the stormwater constituents. If
the influent water quality is of good quality, the dry wells can be a safe disposal method
for stormwater quality. However, most of the bacteria and lead concentrations exceeded
the groundwater disposal criteria for NJ and may require treatment, if the aquifer is
critical.
Results and Conclusions
Dry wells may be a preferred option in cases that are allowed by the NJ dry well
disposal regulations for stormwater which limits their use to areas having excellent soils
(HSG A or B), where the groundwater table is below the dry well system (to prevent
standing water in the dry wells and very slow infiltration), and to only receive roof runoff
water (generally the best quality runoff from a site and not contaminated with deicing
salts). However, the beneficial uses of roof runoff should be the preferred option, and in
many cases may be less costly, especially considering increasing water utility rates and
the desire to conserve highly treated domestic water supplies. Shallow groundwater
recharge may be an important objective for an area, but "over" irrigation (beyond the
plants ET deficit needs, but less than would produce direct runoff) would also contribute
to that objective, at the same time as conserving water and offering better groundwater
protection.
Figure 1-7 is a map showing the general infiltration rate conditions for Millburn. Most of
the monitored dry wells were along a ridge between the two main drainages of the
Township, with no obvious pattern of high water conditions, except that the high
standing water dry wells were located along a line to the southwest along the ridge and
are located fairly close to headwaters of streams (high water tables were noted in areas
19
-------
with nearby streams, but that was assumed to be in the larger stream valleys and not at
the headwaters). The sites that had high standing water long after the events ended had
substantially reduced infiltration rates. In the analyses, these rates were considered to
be the constant (final) rates observed, with no initial rate data or first-order decay Morton
coefficients used (relatively constant, but very low infiltration rates). Three of the sites
had severely degraded infiltration conditions (260 Hartshorn, 87/89 Tennyson, and 7
Fox Hill). These sites all received runoff from the entire property or from multiple
impervious areas (and are 1 to 5 years old). It is not known if the source water or
groundwater conditions affected the drainage conditions at these sites. Dry wells
receiving runoff from all impervious areas would have a greater silt load and likely clog
prematurely compared to sites only receiving roof runoff.
'ng Avenue
DEM
Value
- High : 588.236
- Low: 31.4229
• Sites with all or most events having high water table conditions
Standing water of several inches including seasonal high water table conditions
• Completely drained with no high water table conditions
0 0.2 0.4
1.2
1.6
• Miles
Figure 1-7. Township map showing locations having varying standing water conditions in
monitored dry wells.
Table 1-5 compares the observed Horton equation coefficients for the two well-drained
categories. The standing water data are not shown on this table as most of the
20
-------
observations could not be successfully fitted to the Morton equation. The almost steady
infiltration rates (but with substantial variation) were all very low for those conditions and
likely represent the fc conditions only and were therefore included in that parameter
category.
Table 1-5. Observed and Reported Morton Equation Coefficients (average and COV values)
Surface A and B soils well drained A subsurface soils
(average and COV)
Surface C and D soils well drained A and B subsurface
soils (average and COV)
f0 (in./hr)
44.6 (0.53)
4.3 (0.64)
fc (in./hr)
5.6 (0.2)
0.45 (0.85)
k(1/min)
0.06 (0.22)
0.01 (0.63)
(1 in./hr = 25.4mm/hr)
Even sites having surface C and D soils (not acceptable infiltration sites according to
the NJ dry well standards) had much better subsurface conditions where the dry wells
were located than the surface conditions. The infiltration rates for these conditions were
less than for the excellent areas having A and B surface soils, but all met the infiltration
rate criteria of the state guidelines.
Table 1-6 lists the most stringent regulatory levels for groundwater contaminants
derived from N.J.A.C. 7:9C (2010), along with the range of observed concentrations for
each constituent during these tests. The microbiological and lead concentrations
frequently exceeded the groundwater disposal criteria.
Table 1-6. Groundwater Quality Criteria for the State of New Jersey Compared to Observed Water
Quality from Dry Wells
Constituent
Microbiological
criteria2
Nitrate and Nitrite
Nitrate
Phosphorus
COD
Lead
Copper
Zinc
Groundwater Quality
Criterion1
Standards promulgated in
the Safe Drinking Water
Act Regulations (N.J.A.C.
7:10-1 et seq.)3
10
10
n/a
n/a
0.005
1.3
2.0
Observed Range
Total coliform:
1 to 36,294 MPN/lOOmL
f. co//:lto8,469MPN/100
mL
0.0 to 16.5
(one sample had a
concentration of 16.5 mg/L)
0.1 to 4.7
0.02 to 1.36
5.0 to 148
BDLtoO.38
BDLtol.l
BDLtoO.14
Fraction of samples that
exceed the criteria
Total coliform: 63 of 71
samples exceeded the
criterion for total coliforms
E. coir. 45 of 71 samples
exceeded the criterion for
f . coli
lof 71 samples exceeded
the criterion for nitrates
plus nitrites
0
n/a
n/a
33 of 71 samples exceeded
the criterion for lead
0
0
21
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Constituent
2,4-D
2,4,5-TP (Silvex)
2,4,5-T
Aldrin
Alpha-BHC
beta-BHC
delta-BHC
gamma-BHC (Lindane)
alpha-Chlordane
gamma-Chlordane
Dieldrin
4,4 -ODD
4,4 -DDE
4,4 -DDT
Endrin
Endosulfan sulfate
Endosulfan-l
Heptachlor
Heptachlor epoxide
Methoxychlor
Toxaphene
Groundwater Quality
Criterion1
0.07
0.06
0.7
0.00004
0.00002
0.00004
n/a
0.00003
n/a
n/a
0.00003
0.0001
0.0001
0.0001
0.002
0.04
0.04
0.00005
0.0002
0.04
0.002
Observed Range 1
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
0.00003
0.00002 to 0.000024
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
0.000032 to 0.000034
Not Detected
0.00003 to 0.000035
Not Detected
Not Detected
Fraction of samples that
exceed the criteria
0
0
0
0
0
0
n/a
0
n/a
n/a
0
0
0
0
0
0
0
0
0
0
0
Ground water quality criteria and observed range are expressed as mg/L unless otherwise noted.
2 Pursuant to prevailing Safe Drinking Water Act Regulations any positive result for fecal coliform is in
violation of the MCL and is therefore an exceedance of the ground water quality criteria.
350MPN/100ml_
Reference evapotranspiration (ET) rates for the Millburn area range from about 0.4
mm/day (0.015 in./day) during January to about 4 mm/hr (0.16 in./hr) during May
through July. The period of maximum ET also corresponds to the period of maximum
rainfall in the area, reducing the need for irrigation (and also the sizes of long-term
water storage tanks). Therefore, the beneficial use of roof runoff for irrigation is limited if
it is used only to meet the irrigation demand. However, irrigation can also be used as a
stormwater management option with excess water being used to recharge the shallow
groundwater and to meet the increased moisture needs of some heavily watered lawns
(such as common Kentucky Bluegrass).
Rain gardens are another viable alternative for stormwater management in the Millburn
area, especially as they provide some groundwater quality protection and can be
incorporated into the landscaping plan of the site. They likely require additional
maintenance; similar to any garden, but they can be placed to receive runoff from
several of the source areas on a site, increasing the overall stormwater management
level. They have even been incorporated along roads, as curb-cut biofilters, resulting in
significant overall runoff volume reductions (but with special care to prevent pre-mature
clogging, reduced salt discharges, and appropriately sized to handle the large flow
volumes).
22
-------
Alternative stormwater options should be used when dry well use should be restricted,
such as with the following conditions:
• poor infiltration capacity of subsurface soil layers;
• concerns about premature clogging or other failures due to sediment;
discharges or snowmelt discharges to dry wells;
• seasonal or permanent high water tables; and,
• concerns about groundwater contamination potential.
23
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Chapter 2 Background of Millburn Stormwater Management
using Dry Wells
In 1999, the Township of Millburn created an ordinance that required increased runoff
from new impervious areas to be directed into seepage pits (dry wells). The purpose of
this project was to investigate the effectiveness of this ordinance, specifically to
examine the use of dry wells as a technique to redirect surface runoff to the local
shallow groundwater. The objective of this approach is to reduce local drainage and
erosion problems associated with new development and increases in impervious areas
of currently developed areas. The slower release of the shallow groundwater to surface
streams also better simulates natural hydrologic patterns with reduced in-stream
problems associated with increased rapid surface runoff. The Township of Millburn has
a stable population where there is little vacant land and that all new construction within
the community is performed on previously developed plots. This ordinance has
impacted over 1500 properties where seepage pits have been installed on both
commercial and residential properties.
Description of Millburn Dry Wells
A dry well is a subsurface infiltration stormwater disposal practice that receives
stormwater runoff from surrounding areas for subsurface disposal to shallow
groundwater. Dry wells reduce the direct discharges of stormwater runoff to surface
receiving waters or to downstream stormwater treatment facilities. Figure 2-1 is a
schematic of a dry well in Millburn. The dry wells of this study are precast concrete
structures (Figure 2-2), with open bottoms resting on 0.6 m (2 ft) crushed stone layers
and with 0.6 m (2 ft) of crushed stone surrounding the dry wells. Most of the dry wells
receive water directly from roof drain leaders or by storm drain inlets located in
driveways or small parking lots. Some also have grated covers and receive surface
runoff from the surrounding lawn or paved areas.
24
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: Drain
: sewer
: soil
Figure 2-1. Schematic of Millburn Dry Wells
Figure 2-2. Peerless Concrete Products, Butler, NJ supplies the dry wells to many of the sites in
Millburn (photo from http://www.peerlessconcrete.com/).
About 85% of the dry wells receive roof runoff only, and about 98% are in residential
areas. The general design requirements are to provide 9 m3 (250 ft3) of void volume in
25
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the dry wells for every 110 m2 (1,000 ft2) of impervious drainage area. In most cases,
one perforated concrete tank dry well is used for every 110 m (1,000 ft2) of impervious
area. The most common dry wells used are open bottomed precast 1.8 m (6 ft) diameter
and 1.8 m (6 ft) deep having numerous holes. These are installed with a 0.6 m (2 ft)
blanket of crushed stone on the bottom and around the sides (Figure 2-3). The dry wells
also have overflows to the storm drain system. The subgrade soils' permeability rate
must be sufficient to drain the runoff in the tank within 72 hr (NJ Stormwater BMP
Manual, pg 9.3-1). Each of these dry wells has about 4.8 m3 (170 ft3) of void storage, so
the average 1.5 dry well per average lot provides about 7.1 m3 (250 ft3) of storage, or
the amount required for 90 m2 (1,000 ft2) of impervious surfaces. Roof leaders enter the
dry wells directly, after passing through a small cleanout. In some cases, a water
storage tank (non-perforated) is installed upgradient from the dry well with a small pump
to provide irrigation water. The lot sizes where the dry wells are used range from 9.1 m
(30 ft) by 30 m (100 ft) to 2 acre sites, although most are 1,900 to 2,800 m2 (20,000 to
30,000 ft2), with an average of about 1-1/2 dry wells per lot.
Figure 2-3. Installed dry well in Millburn, NJ, showing the surrounding blanket of crushed stone
before completion of the backfilling (photo from Mel Singer).
26
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The Township estimates the cost of a typical dry well installation to be about $4,100
(Table 2-1). They have also found that with most of the roof water being directed to the
dry wells instead of into residents' plant beds, the dry wells can save homeowners as
much as $700 per year in landscape maintenance costs since the roof drain discharge
doesn't wash away the mulch and erode topsoil.
Table 2-1. Cost Breakdown for a Typical Dry Well Installation
Dry well (6 ft dia., 6 ft deep)
Clean stone (2 ft at bottom and sides)
Excavation (10ftx10ftx9ft deep)
Manhole Casting
Drain Pipes (sch. 40 PVC)
TOTAL
$1,000
$680
$1,200
$300
$900
$4,080
1 ft = 3.05m
Photographs of dry wells and surrounding areas in Millburn are shown in Figures 2-4
through 2-6. Figure 2-4 shows typical dry wells located in both front and backyards in
the area that were considered for the initial controlled infiltration tests using Township
fire hydrant water. Some of these locations were not used due to access problems or
distance from the fire hydrants. They show that many of the dry wells are located in
landscaped areas and have open covers, allowing surface runoff from the lawns to
enter the dry wells, as well as the subsurface piped roof runoff. Some are also located
in paved areas, also allowing surface runoff from the driveways to enter along with the
roof runoff. Figure 2-5 shows the home with the cistern that was included in the water
quality monitoring, including the inlet strainer filter to capture leaves from the roof.
Figure 2-6 shows two examples of dry wells, one that is draining well and the other with
long-term standing water. Both were open to the surface and received runoff from
landscaped areas and contained some lawn and leaf debris.
Front yard dry well also receiving lawn area
inflows.
Backyard dry well sealed against surface
inflows.
Figure 2-4A. Site photographs of dry wells in Millburn.
27
-------
Backyard dry well showing lawn area also
as a source.
Front yard dry well only receiving roof
runoff.
Backyard dry well on Wyoming St.
showing driveway runoff also as a source.
Backyard dry well at new home on
Parsonage Hill Rd used for water quality
monitoring; sealed against surface inflows.
Figure 2-4B. Site photographs of dry wells in Millburn.
28
-------
Frontyard dry well at new home used for
water quality monitoring on Slope Drive
open grating receives surface inflows in
addition to roof runoff.
Backyard dry well at new home on
Tennyson Rd. used for water quality
monitoring (monitoring well caps shown),
sealed against surface inflows.
Figure 2-4C. Site photographs of dry wells in Millburn.
29
-------
Landscaping in yard having underground
cistern.
•r IT?.. < • •
Cistern inlet filter.
v, •-*.-
.
Cistern irrigation pump.
Figure 2-5. Cistern monitoring location on Minnisink Rd.
30
-------
Dry well showing crushed stones at bottom
with some minor lawn debris.
Dry well with standing water and some
leaves.
Figure 2-6. Example dry wells completely draining and with standing water.
31
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Chapter 3 Millburn, NJ, Study Site Descriptions
Millburn, NJ, is a typical affluent suburb in New Jersey in the southwest corner of Essex
County and is situated about 21 miles west of New York City. It is a mature community
of 6,450 acres (about 10 square miles), with less than 15 per cent of its land vacant.
There are approximately 7,195 residential homes with a population of 20,149 (2010 US
census). The community has a normal mix of commercial and retail establishments,
parks and schools and an upscale shopping mall.
About 5,900 homes are detached single-family units and about 1,500 have dry wells.
Some also have water storage tanks before the seepage pits for irrigation use
withdrawals. The city has no above ground detention facilities. About 60% of the
community water supply is from public wells. The groundwater table is as shallow as 2.4
to 3 m (8 to 10 ft) along the river in town. The soils vary greatly in the community, with
large amounts of clayey soils. The following photographs show some of the
neighborhoods in Millburn (from Google).
Figure 3-1. Millburn, NJ, high density residential neighborhood (Google)
32
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Figure 3-2. A medium density residential neighborhood in Millburn, NJ (Google)
Site Descriptions
Table 3-1 lists locations of the study sites in the Township of Millburn, Essex County, NJ
where dry well water level measurements were obtained for different rain events. All of
the study sites are residential buildings with one or two families. Three of the dry wells
as well as the cistern were also instrumented with monitoring underdrains for water
quality monitoring. Table 3-2 lists water quality sampling locations.
Table 3-1. Infiltration Monitoring Dry Well Locations, Township of Millburn, NJ, 07078
1 Sinclair Terrace
15 Marion Avenue
258 Main Street
36 Farley Place, Short Hills (Linda's Florist)
11 Fox Hill Lane
11 Woodfield Drive
142 Fairfield Drive
2 Undercliff Road
260 Hartshorn Drive
383 Wyoming Avenue
7 Fox Hill Lane
8 South Beechcroft Road
87/89 Tennyson Drive
9 Fox Hill Lane
33
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Table 3-2. Water Quality Monitoring Dry Well and Cistern Locations, Township of Millburn, NJ,
07078
135 Tennyson Road (dry well location)
18 Slope Drive (dry well location)
139 Parsonage Hill Road (dry well location)
79 Minnisink Road (cistern location)
Table 3-3 is a summary of the impervious drainage areas, and the dry well system
storage volumes for some of the monitored dry wells, along with the drainage area to
storage volume and approximate date of construction. These dates were on the plan
drawings and maps. The ages of the dry wells monitored therefore ranged from about 5
years to new. The ratios of the drainage areas to the storage volumes ranged from
about 5 to 10 ft2 per ft3 (or 17 to 33 m drainage area per m3 of storage). Unfortunately,
this information is not complete for all of the test areas and some of the information is
suspect. It was hoped that this information could be compared to the observed
performance of the dry wells to indicate any degradation with age or source area
treated.
Table 3-3. Dates of Final Construction Drawings, Impervious Drainage Areas, and Dry Well
Storage Volumes for Selected Dry Wells Studied
Site Location
11
Woodfield
Dr
383
Wyoming
Ave.
260
Hartshorn
87/89
Tennyson
Drive
1 Sinclair
11 Fox Hill
Lane
7 Fox Hill
Lane
8S
Beechcroft
Drainage
area (ft2)
900
600
5,003
6,044
1,324
3,633
3,633
15,000
Description
of Drainage
Area
Driveway
Lawn Area*
Impervious
Area
Impervious
Area
Addition
Entire
Property
Entire
Property
Water drains
from several
properties *
Date (from
maps)
11/29/2007
6/11/2009
5/6/2009
4/18/2005
7/11/2008
2/21/2008
3/18/2008
8/23/2007
Tank Specifications
Tank
dia. (ft)
6
8
8
8
7.5
3.5
3.5
6
Tank
depth
(ft)
6
6
6
8
4.5
7
7
5.25
Number
of tanks
1
2
3
2
1
5
5
1
Volume
per
tank
(ft3)
170
300
300
338
199
67
67
148
Total
volume
of dry
wells
(ft3)
170
600
900
675
199
337
337
148
Ratio of
contributing
area to dry
well volume
(ft2/ft3)**
5.3
1.0(?)*
5.6
9.0
6.7
10.8
10.8
101 (?)*
* Likely errors in source area descriptions
**The local design guidelines require 250 ft3 of dry well storage (including void space in the crushed
stone blanket) for every 1,000 ft2 impervious drainage area (ratio of 4)
(1 ft = 3.05 m, 1 ft2 = 0.093 m2)
34
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Aerial Photos of Study Locations
Figure 3-3 is a large scale map showing the locations of the study areas in the
Township of Millburn (www.maps.google.com). The following are aerial photographs for
each site as well as some of the dry wells. Appendix A also includes drawings of the dry
well installations for each site.
35
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,:<
142 Fairfield DrM
8 Beechcroft
7, 9, 11 Fox
•-..
11 Woodfield
139 Parsonage
135 Tennyson
383 Wyoming Ave
Q 87, 89 Tennyson U
I 260 Hartshorn Dr
79 Mmnismk
15 Marion Ave.
Figure 3-3. Locations of infiltration dry wells (shown with blue icons) and cistern (79 Minnisink, green icon) and water quality monitoring
dry wells (shown with red icons)
36
-------
Dry well (8 South Beechcroft)
11 Woodfield Dr.
Dry well (11 Woodfield Dr.)
Figure 3-4A Aerial Photos and photos of dry wells for study areas in Millburn, NJ
37
-------
1 Sinclair Terrace
Dry well (11 Fox Hill LN)
Dry well with standing water (1 Sinclair
Terrace)
Figure 3-4B Aerial Photos and photos of dry wells for study areas in Millburn, NJ
38
-------
383 Wyoming
258 Main St.
Dry well with standing water (383
Wyoming)
Dry well (258 Main St.)
9 Fox Hill Lane
Dry well with standing water (9 Fox Hill)
Figure 3-4C Aerial Photos and photos of dry wells for study areas in Millburn, NJ
39
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Dry well (2 Underchff Rd)
Figure 3-4D Aerial Photos and photos of dry wells for study areas in Millburn, NJ
(www.maps.google.com)
40
-------
Land Cover Descriptions of Study Sites
The land covers of the project sites, including roofs, driveways, sidewalks, streets,
landscaped areas, patios, etc. are shown in Table 3-4. The percentage of each of these
land covers is shown in Table 3-5. These data were calculated from the plan maps for
each home obtained by PARS Environmental, Inc. from the Township.
Table 3-4. Land Covers for Study Sites (Area, ft )
8 South
Beechcroft
2,800
2,030
384
3,200
21,243
381
40
162
30,240
1.4
11 Fox Hill
2,183
1,125
50
1,650
11,003
277
16,288
2.7
43 Browning
Road S.H
2,376
980
110
2,200
10,557
486
16,710
2.6
1 Sinclair
terrace
3,216
1,438
237
1,900
22,277
433
88
29,589
1.5
7 Fox Hill
2,435
1,070
380
1,800
10,952
369
17,006
2.6
9 Lancer
3,360
2,214
448
2,100
14,189
537
288
23,136
1.9
135
Tennyson Dr
1,096
990
792
274
3,240
12,680
19,076
2.3
79 Minnisink
Rd
9,150
5,200
3,200
2,600
3,000
24,450
47,600
0.9
18 Slope Dr
3,713
2,812
1,406
0
6,000
10,125
24,056
1.8
139
Parsonage
Hill Rd
4,560
2,246
2,722
272
5,775
18,692
34,267
1.3
Minimum
1,096
980
0
0
1,650
10,125
16,288
0.9
Maximum
9,150
5,200
3,200
2,600
6,000
24,450
486
537
88
288
47,600
2.7
Average
3,489
2,011
812
476
3,087
15,617
151
101
45
25,797
1.9
Standard
Deviation
2,201
1,292
1,232
761
1,586
5,507
201
204
28
99
9,926
0.6
Coefficient of
Variation
(COV)
0.6
0.6
1.5
1.6
0.5
0.4
1.3
2.0
3.2
2.2
0.4
0.3
(1 ft2 = 0.093 m2)
41
-------
As shown in Table 3-5, most of land cover is landscaped (62%), while roofs make up
about 13% of the areas and streets make up about 12.5% of the areas. The variations
of these major areas are relatively small, with the COVs of these three areas all less
than 0.5. The housing densities for these ten homes ranged from about 1 to 3 homes
per acre, with an average of about 2 homes per acre.
Table 3-5. Land Covers for Study Sites Area, as a percentage)
8 South
Beechcroft
9.3
6.7
0.0
1.3
10.6
70.2
1.3
0.1
0.0
0.5
100.0
11 Fox Hill
13.4
6.9
0.0
0.3
10.1
67.6
1.7
0.0
0.0
0.0
100.0
43 Browning Road
S.H
14.2
5.9
0.0
0.7
13.2
63.2
2.9
0.0
0.0
0.0
100.0
1 Sinclair terrace
10.9
4.9
0.0
0.8
6.4
75.3
0.0
1.5
0.3
0.0
100.0
7 Fox
14.3
6.3
0.0
2.2
10.6
64.4
2.2
0.0
0.0
0.0
100.0
9 Lancer
14.5
9.6
0.0
1.9
9.1
61.3
0.0
2.3
0.0
1.2
100.0
135 Tennyson Dr
5.7
5.2
4.2
1.4
17.0
66.5
0.0
0.0
0.0
0.0
100.0
79 Minnisink Rd
19.2
10.9
6.7
5.5
6.3
51.4
0.0
0.0
0.0
0.0
100.0
18 Slope Dr
15.4
11.7
5.8
0.0
24.9
42.1
0.0
0.0
0.0
0.0
100.0
139 Parsonage Hill
Rd
13.3
6.6
7.9
0.8
16.9
54.5
0.0
0.0
0.0
0.0
Minimum
4.9
0.0
0.0
6.3
42.1
0.0
0.0
0.0
0.0
100.0
Maximum
19.2
11.7
7.9
5.5
24.9
75.3
2.9
2.3
0.3
1.2
Average
13.0
7.5
2.5
1.5
12.5
61.6
0.8
0.4
0.0
0.2
Standard
Deviation
3.7
2.4
3.3
1.6
5.7
9.8
1.1
0.8
0.1
0.4
Coefficient of
Variation (COV)
0.3
0.3
1.3
1.0
0.5
0.2
1.4
2.1
3.2
2.3
Features Affecting Water Use
Population, Residences, and Householder Data
Demographic information is needed when evaluating beneficial stormwater use potential
for an area. Information concerning population and householder social-economic
conditions was obtained from the U.S. Census Bureau, based on the 2000 census for
the Millburn Township zip codes 07078 and 07041. Household data was also confirmed
by the Township Engineer.
42
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Table 3-6. Summary of Census 2000 Information for Zip Codes 07078 and 07041 (Source: U.S.
Census Bureau)
.,. _ . _, ... Total Housing Occupied Average
Z,pCode Populat,on Unjts Housing Units Household Size
07078
07041
Total
12,849
6,880
19,729
4,337
2,809
7,146
4,256
2,747
7,003
3.02
2.5
2.81
Soil types
Soil characteristics are also needed when evaluating stormwater infiltration and
recharge potential for an area and for designing these control practices. Table 3-7 lists
locations of sites where infiltration measurements were made, along with the ID of each
as shown on the map (Figure 3-5). Figure 3-5 is a map of surface soil types for the
Township of Millburn. The soil spatial and tabular map data were obtained from the
Natural Resources Conservation Service (NRCS) Soil Survey for Essex County and
imported into ArcMap 10. Most of the sites have "BowtB" soil type (Boonton - Urban
land, Boonton substratum complex, terminal moraine). Figure 3-6 shows the Hydrologic
Soil Group (HSG) for the surface soils.
Table 3-7. Locations of Infiltration Monitoring Sites and Soil Conditions in Millburn and Short Hills,
NJ
Street Address
1 Sinclair Terrace
15 Marion Avenue
258 Main Street
11 Fox Hill Lane
1 1 Woodfield Drive
142 Fairfield Drive
2 Undercliff Road
260 Hartshorn Drive
383 Wyoming Avenue
7 Fox Hill Lane
79 Minnisink Road
8 South Beechcroft Road
87/89 Tennyson Drive
9 Fox Hill Lane
36 Farley PI
City
Millburn
Millburn
Millburn
Millburn
Millburn
Millburn
Millburn
Millburn
Millburn
Millburn
Millburn
Millburn
Millburn
Millburn
Short Hills
Latitude
40.749
40.729
40.717
40.743
40.740
40.751
40.724
40.739
40.730
40.742
40.736
40.743
40.735
40.742
40.718
Longitude
-74.307
-74.311
-74.308
-74.314
-74.322
-74.310
-74.300
-74.331
-74.291
-74.314
-74.332
-74.314
-74.350
-74.315
-74.326
ID on Map
(Fig. 3-5)
1
2
3
4
5
6
7
8
9
10
11
12
13 and 14
15
16
Surface
Soil
Name1
BowtB
BowtB
DuuB
BowtB
BowtB
BowtB
BowrB
BowtB
BowrB
BowtB
BowtC
BowtB
BowtB
BowtB
UrbanB
Surface Soil HSG2
D
D
A and D
D
D
D
C
D
C
D
D
D
D
D
D
Natural Resources Conservation Service (NRCS)
Source: So;7 Survey of Essex County, New Jersey Report, USDA, NRCS.
Table 3-8 summarizes the surface and subsurface soil characteristics for the Millburn
sites using the NRCS on-line soil survey. All the sites have surface soils with hydrologic
43
-------
soil group (HSG) "C" or "D", except for the Main St. area that has "A" soils. Group "A"
soils have a high infiltration rate (low runoff potential) when thoroughly wet. These
consist mainly of deep, well drained to excessively drained sands or gravelly sands.
These soils have a high rate of water transmission. Group "C" Soils have slow infiltration
rates when thoroughly wet. These consist mainly of soils having a layer that impedes
the downward movement of water or soils of moderately fine to fine texture. Group "D"
soils have a very slow infiltration rate (high runoff potential) when thoroughly wet. These
consist chiefly of clays that have a high shrink-swell potential, soils that have a high
water table, soils that have a claypan or clay layer at or near the surface, and soils that
are shallow over nearly impervious material. Group D soils have a very slow rate of
water transmission. All of the sites' subsurface soils shown on Table 3-8 are well
drained. The dry wells are usually 2.4 m or 8 ft deep (2 ft of surface cover with a 6 ft tall
concrete perforated tank), with another 2.4 m (2 ft) of gravel, so the main infiltration
layer is from 0.6 m (2 ft) to about 3.1 m (10 ft) below the ground surface. The soil profiles
indicate increased infiltration potentials at these deeper soil depths, with all subsurface
soils being group A or B from about 2.4 m (2 ft) and deeper, as shown on Figure 3-7,
which likely better indicates the potential function of the dry wells compared to the
surface soil conditions.
44
-------
soil Map Units
^\ other [
^\ BoeBc |
| BoeCc [^
"^ BoeDc [^
I I BogBc [
| BogC [
| BogDc [^
[J BouB [
^| BouC |
| BowrB |
I I BowrC f
| BowtB
| BowtC
] BowlD
| CatcA
] DunB
] DunC
] DunD
| DuuB
] DuuC
I FmhAt
|HanCc
| HasB
| HctBc
| NazA
| PbpAt
] PecmB
| PecmBc
] PecmC
| PecmCc
PeeuuB
| GrpA [ _ PohA
HanBc \~ PrkA
| QY | UdbooB
| TunkD ^B UdtJunB
| TunkE | 1 UdhalB
| URBONB | | UdhorB
| URBOOB | | UdkttB
| URDUNB ^H UdpecB
| URKTTB | | WATER
| URPOMB
| USBONB |
| USDUNB
| UcdAt
I UdbonB
] YaohEh
0 0.25 0.5
1.5
(Miles
Figure 3-5. Soil Map for the Township of Millburn (NRCS; http://soils.usda.gov/)
45
-------
soil Map Units
other B B A/D Q Zl B/D E B CID I I N'A
• A ~|B ~~| c ID
0 0.25 0,5 1
1.5
I Miles
Figure 3-6. Hydrologic Soil Group Index of the Township of Millburn for Surface Soils (NRCS; http://soils.usda.gov/)
46
-------
Hydrologic Soil Group (Depth of 2 ft)
other ^B A/B BID Q
• A B ID
N/A
0 0.25 0.5
1.5
I Miles
Figure 3-7. Hydrologic Soil Group Index of the Township of Millburn for Shallow Subsurface Soils 2 ft Deep (NRCS;
http://soils.usda.gov/)
47
-------
48
-------
Table 3-8 Summary of soil characteristics
(Source: http://websoilsurvey.nrcs.usda.gov/app/HomePage.htm)
Address
383 Wyoming Ave.
90 Chestnut St.
258 Main St.
260 Hartshorn
142 Fairfield
87/89 Tennyson
7 Fox Hill
9 Fox Hill
11 Fox Hill
8 South Beechcroft
2 Undercliff
Linda's Flower
15 Marion
11 Woodfield Dr
9 Lancer
1 Sinclair Terrace
36 Farley Place
Soil Name
Boonton-
Urban land,
Boonton
substratum
complex, red
sandstone
lowland
Dunellen
sandy loam
Boonton -
Urban land,
Boonton
substratum
complex,
terminal
moraine
Boonton -
Urban land,
Boonton
substratum
complex
Boonton -
Urban land,
Boonton
substratum
complex
Urban land,
Boonton
substratum
Slope
(%)
3-8
3-8
3-8
8-15
0-8
0-8
KSat
Moderately
low to
moderately
high (0.06 to
0.20 in./hr)
High (1.98 to
5.95 in./hr)
Moderately
low to
moderately
high (0.06 to
0.20 in./hr)
Moderately
low to
moderately
high (0.06 to
0.20 in./hr)
Moderately
low to
moderately
high (0.06 to
0.20 in./hr)
Moderate to
moderately
rapid
Drainage
class
Well
drained
Well
drained
Well
drained
Well
drained
Well
drained
Well
drained
Typical profile and associated Hydrologic
Soil Groups for subsurface soils
0 tol in.: Slightly decomposed plant (C)
1-3 in.: Silt loam (C)
3-10 in.: Loam (C)
10-27 in.: Gravelly loam (B)
27-67 in.: Gravelly fine sandy loam (A)
67-83 in.: Gravelly sandy loam (A)
0-42 in.: Sandy loam (A)
42-70 in.: Stratified gravelly sand to sand
to loamy sand (A)
0 to 1 in.: Highly decomposed plant (D)
1-24 in.: Sandy loam (B)
24-42 in.: Gravelly sandy loam (A)
42-60 in.: Fine sandy loam (B)
0-5 in.: Loam (B/C)
5-30 in.: Silt loam (B)
30-40 in.: Gravelly fine sandy loam (A)
40-47 in.: Fine sandy loam (A)
47-72 in.: Loamy sand (A)
0-5 in.: Loam (B/D)
5-30 in.: Silt loam (B)
30-40 in.: Gravelly fine sandy loam (A)
40-47 in.: Fine sandy loam (A)
47-72 in.: Loamy sand (A)
0-12 in.: impervious material (D)
12-47 in.: silt loam (C)
47-72 in.: loamy sand (A)
Capacity of the most limiting layer to transmit water
1 inch = 2.54 cm
Source: http://websoilsurvey.nrcs.usda.gov/app/HomePage.htm
49
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Groundwater Conditions in the Township of Millburn
Unfortunately, groundwater depth conditions are not readily available for the Township
of Millburn. The geology in the area is comprised mostly of glacial deposits down to
bedrock and bedrock in that area is encountered anywhere between 30 m to 60 m (100
to 200 ft) below the ground surface (bgs). The water table is generally encountered > 9
m (>25ft) bgs (personnel communication, Michael D. Moore, PG, LSRP, Senior Project
Manager, PARS Environmental, Inc., Robbinsville, NJ). The NJDEP OPRA database
generally shows depth to water measurements at:
http://datamine2.state.ni.us/DEP OPRA/OpraMain/categories?categorv=WS+Well+Per
mits
However, groundwater depth data were not available for the study area, although other
sites in Essex County were included. The groundwater table is reported by the
Township to be as shallow as 2.4 to 3 m (8 to 10 ft) along the river in town. Therefore, it
is assumed that generally, shallow groundwater conditions are not likely in the study
area, except possibly in low-lying areas.
Rainfall Characteristics in Northern New Jersey
Long-term rainfall characteristics for Newark, NJ, were examined as part of this study.
As noted elsewhere in this report, four short-term rain gages were installed in the
project vicinity to obtain rain information corresponding to the monitoring activities.
However, because these were only in use for several months, they do not provide
adequate information concerning the expected long-term rain conditions in the area.
Therefore, more than 50 years of continuous rain records covering the period from May
1948 through December 1999 from the Newark International Airport (located less than
10 miles from the Township of Millburn) were examined. WinSLAMM was used to
combine the individual hourly rain depths supplied by Earthlnfo CDRoms (of NOAA
data) into rain events. Each rain event was defined as having measureable rainfall (at
least 0.025 cm (0.01 in.) of rain) with a preceding interevent dry period of at least 6 hr.
Table 3-9 summarizes this rain information for this period.
50
-------
Table 3-9. Newark, NJ, Rain Characteristics (1948 through 1999)
Total per year
Minimum
1st percentile
10th percentile
25th percentile
50* percentile (median)
75* percentile
90th percentile
99th percentile
Maximum
Average
Standard deviation
COV
Rain depth
(in.)
44.0
0.01
0.01
0.01
0.04
0.18
0.55
1.11
2.81
8.25
0.42
0.60
1.4
Rain duration (hr)
810
1
1
1
2
5
11
18
34
80
7.8
7.8
1.0
Average event
rain intensity
(in./hr)
0
0.01
0.01
0.02
0.03
0.07
0.12
0.35
1.00
0.05
0.07
1.3
Preceding
interevent dry
period (days)
331
0.04
0.3
0.4
0.8
2.3
4.4
7.2
14.8
33.9
3.2
3.1
1.0
1 in. = 2.54 cm
Figure 3-8 shows the distribution of the rain depths with time for this 52 year period. The
three largest rains (15 to 20 cm, or 6 to 8 in.) are quite distinct from the other events.
Figure 3-9 (Pitt 1999) displays probability plots of rain events (by count) and runoff
volumes for ten years for the Newark airport. This plot shows that the median rain depth
is about 5 mm (0.2 in.), but this rain (and smaller events), only accounts for about 10%
of the total annual runoff volumes from typical residential and commercial sites. Most
(about 75%) of the annual runoff, and therefore stormwater pollutants, are associated
with rains in the range from about 10 mm to 64 mm (0.4 to 2.5 in.), with about another
15% of the runoff associated with rains smaller than 10 mm (0.4 in.) and about 10% of
the annual runoff associated with rains larger than about 64 mm (2.5 in.).
01
0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000
Time (days)
Figure 3-8. Rain depth distribution with time for Newark, NJ, for 1948 through 1999 (WinSLAMM
rain file data plot).
51
-------
Accumlative
Residential
Runoff
Quantity
Accumlative
Commercial
Runoff
Quantity
0.01
Rain (inches)
Figure 3-9. Probability distribution of rain events and runoff quantities for Newark, NJ (1982
through 1992) (Pitt 1999).
Typical rain durations (10 to 90th percentiles) range from about 1 to 18 hr, with the
median duration being 5 hr. The average total event (average duration of 5 hr) rain
intensity is only about 0.8 mm/hr (0.03 in./hr) and rarely exceeds 9 mm/hr (0.35 in./hr),
with the recorded maximum only being about 25 mm/hr (1 in./hr). Peak shorter duration
rain intensities are much larger, according to the local IDF (intensity, duration,
frequency) relationship, shown on Figure 3-10. For a 10 minute time of concentration
(typical for a small urban drainage area), the one year frequency rain intensity is about
90 mm/hr (3.5 in./hr), increasing to about 160 mm/hr (6.3 in./hr) for a rain that is
expected only once every 100 years (1% probability of occurring in any one year). It is
interesting to note that the 25 mm/hr (1 in./hr) maximum intensity for the typical 5 hour
duration that was observed at the Newark airport in this 52 year period is expected to be
exceeded with about a 2% probability per year, as observed (slightly extrapolated off
the chart), indicating good agreement.
52
-------
RAINFALL INTENSITY-DURATION
FREQUENCY CURVE - NORTHERN REGION
10.0
9.0
8.0
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
FIOURE;10-D
BDC09MR-05
DURATION OF STORM IN MINUTES
10 15 20 30 40 5060 120 180
•^
-:-
L !
-
3
N.
v
BASE
'*
YS
^
:^J^
^\^
>ON RAIN)
NEW/
I
^
^>
\>
^
ALLFB
RK.N6
^
^W
^v^
§
^
\
^
^
EQUENCYJOATA,
wjeasev
AR AND 15- YEAR SfORMS AR
EINTB
^
1OA/
u-cu
'Q-
^
X
\^"N
ATL
TED
X
Js
'"^N
V
\
f:
%
••-
-
X
\
S
•4\
Fb
S
S
s
^
*
01
3>
^
7&J&
^^
Lh
IE 2,
&h?
°fe- *s
"^^
^ :
\ N
s \
\\
N>
2005
RAINFALL INTENSITY IN/HR
10 15 20 30 40 5060 120 180
DURATION OF STORM IN MINUTES
10-22
NJDOT Design Manual - Roadway
Drainage Design
Figure 3-10. Northern New Jersey IDF curve (NJDOT Design Manual:
http://www.state.ni.us/transportation/eng/documents/BDC/pdf/DMR-Sec10.pdf)
Table 3-10 lists the rainfall totals that are expected in a 24 hour period with different
frequencies for New Jersey counties. The Township of Millburn is located in Essex
County, having an 86 mm (3.4 in.) rainfall expected in 24 hrwith about a 50%
probability in any one year. This 2-year rainfall amount is the design storm depth to be
53
-------
used in the design of groundwater recharge devices to infiltrate excess runoff compared
to pre-development conditions.
Table 3-10. New Jersey 24 hour Rainfall Frequency Data (rainfall in in.) (NJDOT Design Manual:
http://www.state.ni.us/transportation/eng/documents/BDC/pdf/DMR-Sec10.pdf)
County
Rainfall Frequency Data
1-Year
Atlantic | 2.8
Bergen | 2.8
Burlington
2.8
Camden | 2.8
Cape May | 2.8
Cumberland | 2.8
Essex
Gloucester
2.8
2.8
Hudson | 2.7
Hunterdon | 2.9
Mercer
Middlesex
2.8
2.8
Monmouth | 2.9
Morris
Ocean
3.0
3.0
Passaic I 3.0
Salem
Somerset
2.8
2.8
Sussex j 2.7
Union
Warren
2.8
2-Year
3.3
3.3
3.4
3.3
3.3
3.3
3.4
3.3
3.3
3.4
3.3
3.3
3.4
3.5
3.4
3.5
3.3
3.3
3.2
3.4
2.8 [ 3.3
5-Year
4,3
4.3
4,3
4.3
4.2
4.2
4.4
4.2
4.2
4.3
4,2
4,3
4.4
4,5
4.5
4,4
4.2
4.3
4.0
4,4
4.2
10-Year
5.2
5.1
5.2
5.1
5.1
5.1
5.2
5.0
5.0
5.0
5.0
5.1
5.2
5.2
5.4
5.3
5.0
5.0
4.7
5.2
4.9
25-Year
6.5
6.3
6.4
6.3
6.4
6.4
6,4
6.2
6.2
6.1
6.2
6.4
6.5
6.3
6,7
6.5
6.2
6,2
5.7
6.4
5.9
50-Year
7.6
7.3
7.6
7,3
7,5
7,5
7,5
7.3
7,2
7.0
7.2
7.4
7.7
7.3
7.9
7.5
7.3
7.2
6.6
7.5
6.8
100-Year
8.9
8.4
8.8
8.5
8.8
8.8
8.7
8.5
8,3
8.0
8.3
8.6
8.9
8,3
9.2
8.7
8.5
8.2
7.6
8.7
7.8
1 in. = 25.4 mm
Summary of Site Characteristics
The Township of Millburn, Essex County, NJ, is located near New York City, and less
than 10 miles from Newark International Airport. The 2010 US census indicated the
Township had a population of 20,149. Housing costs are very high (According to
Wikipedia, Millburn had the highest annual property tax bills in New Jersey in 2009 at
more than $19,000 per year, compared to the statewide average property tax that was
$7,300 which was the highest in the country). There are about 5,900 detached homes in
the Township and about 1,500 have dry wells. Fifteen dry wells were monitored for
water levels during periods ranging from two months to one year, or by controlled tests
using Township water from fire hydrants. Four systems (three dry wells and one cistern)
were also monitored for water quality during 10 storms to indicate any difference in
water quality directly below the dry wells (or at the cistern inlet) compared to deeper
54
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depths at least 0.6 m (2 ft) below the crushed stone layer beneath the dry wells (or in
the cistern). Four rain gages were also installed near the dry wells.
The study sites were surveyed to obtain detailed development characteristics that affect
the amount of runoff from the different source areas. Soil information was also
compiled. Most of the surface soils were of HSG C or D category, indicating poor
infiltration potential. However, subsurface soils where the dry wells were located were
mostly of HSG A or B category (glacial deposits) with much improved infiltration
potentials. The groundwater in the area may be as shallow as 2.4 to 3 m (8 to 10 ft)
below the ground surface in low-lying areas along the river, but otherwise is expected to
be greater than 8 m (25 ft) below the ground surface in general.
The annual rainfall for the area is about 1,120 mm (44 in.) and the median interevent
period is about two days. The median rain depth is about 5 mm (0.2 in.), but this rain
(and smaller events), only accounts for about 10% of the expected total annual runoff
volumes from typical residential and commercial areas. Most (about 75%) of the annual
runoff, and therefore stormwater pollutants, is associated with rains in the range from
about 10 to 64 mm (0.4 to 2.5 in.), with about another 15% of the runoff associated with
rains smaller than 10 mm (0.4 in.) and about 10% of the annual runoff associated with
rains larger than about 64 mm (2.5 in.). The New Jersey requirements for stormwater
list the 2-year, 24-hr rainfall amount of 87 mm (3.4 in.) for the design of groundwater
recharge devices to infiltrate excess runoff compared to pre-development conditions.
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Chapter 4 Millburn Township Stormwater Regulations and New
Jersey State Groundwater Disposal and Water Reuse
Regulations and other Guidance
This report section summarizes the Development Regulations and Zoning Ordinance of
the Township of Millburn and the applicable New Jersey Groundwater Disposal
standards applicable to dry wells. Also summarized are regulations and guidance
pertaining to beneficial uses of stormwater, from New Jersey, and elsewhere.
Millburn Township Stormwater Regulations
The following sections of the Development Regulations and Zoning Ordinance of the
Township of Millburn, Essex County, NJ (as amended through Dec 14, 2004) are the
local stormwater regulations pertaining to new developments in the Township:
"Stormwater Runoff
The provisions of this section apply to all major subdivisions and site plans.
No land area shall be developed by any person such that:
a. The rate of stormwater runoff occurring at the site is increased over what occurs
under existing conditions;
b. The drainage of adjacent areas is adversely affected;
c. Soil erosion during and after development is increased over what naturally occurs;
d. Soil absorption and groundwater recharge capacity is adversely affected by the
proposed development;
e. The natural drainage pattern is significantly altered.
In order to supplicate as nearly as possible natural drainage conditions, regulations and
control of stormwater runoff and erosion for any land area to be developed shall be
through onsite stormwater detention and/or ground absorption systems such as:
a. Detention areas; which may be excavated basins, basins created through use of
curbs, stabilized earthen berms or dikes, or any other form of grading which serves
to temporarily impound and store water;
b. Rooftop storage through temporary impoundment and storage of stormwater on
flat or slightly pitched building rooftops by use of drain outlets which restricts the
stormwater runoff from the roof surface;
c. Dry wells or leeching basins which control stormwater runoff through ground
absorption and temporary storage;
56
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d. Any system of porous media, such as gravel trenches drained by porous wall or
perforated pipe, which temporarily stores and dissipates stormwater through ground
absorption;
f. Any combination of the above mentioned techniques which limit stormwater runoff
from a given site to what presently occurred there.
Stormwater detention facilities shall be designed to contain an amount equal to the
increase in volume of runoff which would result from development of any site. The
volume of runoff shall be computed on the basis of the total runoff which is produced by
the flood of record for the area involved, more specifically, 170 mm (6.6 in.) of rainfall in
7 hr. The system shall be designed to store the SCS Type III 100-yr, 24-hr storm.
Underground storage facilities which are designed to percolate water into the soil should
be surrounded by a blanket of crushed stone or gravel which is to be a minimum 24"
thick. The stone shall be separated from surrounding soil by an appropriate geotextile
fabric to be approved by the Township Engineer."
This local ordinance includes dry wells as a management option. However, there are no
guidelines on how they are to be constructed (except for the 24 in. thick gravel layer
surrounding the device). Their performance is to retain the existing runoff rate. Most of
the dry wells are constructed in locations of existing development and this requirement
is commonly interpreted as pertaining to increased runoff associated with the
modifications and expansions of the existing site. If pertaining to new construction, this
requirement would then refer to predevelopment conditions. A design storm is described
for stormwater detention facilities, but it is not clear if this also affects the dry well
designs. Also, there are no requirements pertaining to the source waters that can be
directed to the dry wells.
The following section summarizes the New Jersey state regulations pertaining to dry
wells that do include various restrictions for their use, specifically soil compatibility,
depth to groundwater, and allowable source waters.
New Jersey Groundwater Disposal Criteria for Stormwater
The New Jersey Stormwater Best Management Practices Manual (Standard for Dry
Wells - Chapter 9.3) includes specific design criteria for dry wells used for the disposal
of stormwater. It requires sufficient storage volumes in the dry well to contain the design
storm runoff volume without overflow, while the subgrade soils' permeability rate must
be sufficient to drain the stored runoff within 72 hr. Also, the manual requires that the
bottom of the dry well (including the lower crushed stone layer) must be at least 2 ft
above the seasonal high water table or bedrock and be as level as possible to uniformly
distribute runoff infiltration over the subgrade soils. The construction of a dry well must
be done without compacting the dry well's subgrade soils. The New Jersey Stormwater
Best Management Practices Manual (Standard for Infiltration Basins - Chapter 9.5)
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further requires that dry wells be used to collect only roof runoff and that the maximum
drainage area to a dry well be less than one acre.
For infiltration purposes, the manual requires Hydrologic Soil Group A and B soils for
dry wells designed for storms greater than the groundwater recharge storm. Additional
permeability requirements are presented below in Table 4-1. It should be noted that if
the dry well does receive runoff and associated pollutants from larger storm events, a
minimum permeability rate of 0.5 in./hr (12.7 mm/hr) must be used.
Table 4-1. Minimum Design Permeability Rates for Dry Wells
Maximum Design Storm
Groundwater Recharge
Storm water Quality
Minimum Design Permeability Rate (In./hr)
0.2
0.5
1 in./hr = 25.4 mm/hr
Figure 4-1 is a generic dry well illustration with its main components labeled from the
New Jersey Stormwater Manual. This is an example of a stone filled dry well, while the
installations monitored during this project were all perforated concrete vaults with no
rock fill.
I
I
BUILDING
FOUNDATION
ULtjJ,
V
I
ROOF LEADER
CAP END OF PIPE
FILTER FA8RIC UNES
TOP. BOTTOM. AND
SIOCS OF DRY WFII
FOOT PLATE
Source: Smith, Demer, and Normann
Source: Adapted from Standards for Soil
Erosion and Sediment Control in New Jersey
Figure 4-1. Example dry well included in the New Jersey Stormwater Manual.
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Specifically, the Stormwater Management Rules require that a proposed major land
development comply with one of the following two groundwater recharge requirements:
• Requirement 1: That 100% of the site's average annual pre-developed
groundwater recharge volume be maintained after development; or
• Requirement 2: That 100% of the difference between the site's pre- and post-
development 2-year runoff volumes be infiltrated.
Chapter 6 of the New Jersey Stormwater Manual includes guidance and spreadsheets
for the calculations of the design storm conditions for a specific site. Figure 4-2 shows a
typical dry well used in the Millburn study area along with the sizing values showing how
the installation complies with the regulations.
CAUPCELL FOUNtHW 1JN
UCHI OU^f hH*ME A GRATE '
(OR /M*PflWEO EQUAL)
AIUJST
WITH COMCBCTE BLOCK
Oft WPROVLQ
C.P.E
STCNf '•VBAPPEP IK|
flfiOTFXTlUL M.T£«
FASRfC (NON-WOVEN)
REftMEQ VOlWME OF DErtlWW fifl TOWNS-*.'
OHOiWiMce 250 CF / tow §r Of
. ARIA
9 ?.?S Round J 2 _ ' J05 ,
STONE WJW
VTIL. w. l.-Q
jw
!J ie ^
- awj it -*o
31B
VOLUUt NtO'B
3.7 Jj |
VOLUME OF
(ft tf! S'.
Stoha
Figure 4-2. Typical dry well used in Millburn study areas and volume calculations.
59
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Beneficial Use Regulations
Many states in the U.S. have regulations and guidelines relating to reuse of waste
waters. Currently, there are no federal regulations directly governing water reuse
practices in the U.S. During a review by the U.S. EPA (2004), 26 states were found that
had adopted regulations regarding the reuse of reclaimed water, 16 states had
guidelines or design standards, and eight states had no regulations or guidelines. Some
states have developed regulations for water reuse specifying water quality requirements
or treatment processes to derive the maximum resource benefits of reclaimed water
with respect to public health and protecting the environment. These states have set
standards for reclaimed water quality and/or specified minimum treatment requirements.
Generally, where unrestricted public exposure is likely in the reuse application,
wastewater must be treated to a high degree prior to its application. Where exposure is
not likely, however, a lower level of treatment is usually accepted. The most common
parameters for which water quality limits are imposed are BODs, TSS, turbidity, and
total or fecal coliform bacteria counts.
There is a wide range of uses of reclaimed water, but most states do not have
regulations that cover them all. Current regulations and guidelines may be divided into
the following reuse categories (U.S.EPA, 2004):
• Unrestricted urban reuse - irrigation of areas in which public access is not
restricted, such as parks, playgrounds, school yards, and residences; toilet
flushing, air conditioning, fire protection, construction, ornamental fountains,
and aesthetic impoundments.
• Restricted urban reuse - irrigation of areas in which public access can be
controlled, such as golf courses, cemeteries, and highway medians.
• Agricultural reuse on food crops - irrigation of food crops which are intended
for direct human consumption, often further classified as to whether the food
crop is to be processed or consumed raw.
• Agricultural reuse on non-food crops - irrigation of fodder, fiber, and seed
crops, pasture land, commercial nurseries, and sod farms.
• Unrestricted recreational reuse - an impoundment of water in which no
limitations are imposed on body-contact water recreation activities.
• Restricted recreational reuse - an impoundment of reclaimed water in which
recreation is limited to fishing, boating, and other non-contact recreational
activities.
Unrestricted Urban Reuse
Unrestricted urban water reuse involves irrigation of areas in which public access is not
restricted, such as parks, playgrounds, school yards, and residences; toilet flushing, air
conditioning, fire protection, construction, ornamental fountains, and aesthetic
impoundments. This water therefore requires a higher degree of treatment than for
restricted uses. In general, all states that specify a treatment process require a
minimum of secondary treatment and treatment with disinfection prior to unrestricted
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urban reuse. These requirements obviously pertain to sanitary wastewaters, with
minimal relevance to other waters, such as stormwater. Some states require additional
levels of treatment such as oxidation, coagulation, and filtration. Some of the States,
such as Texas, do not mention the type of treatment processes required and sets water
quality limits on the reclaimed water. Table 4-2 shows the reclaimed water quality and
treatment requirements for unrestricted urban reuse for New Jersey.
Table 4-2. Unrestricted Urban Reuse Regulations for New Jersey
Treatment
BOD5
TSS
Turbidity
Coliform
Bacteria
Secondary treatment, filtered (chemical addition
before filtration)
Not specified
5 mg/L (not to be exceed before disinfection)
not to exceed 2 NTU
Fecal conforms:
- 2.2/100 ml (7-day median)
- 14/100 ml (maximum any one sample)
Limits on BODs range from 5 to 30 mg/L. Texas and Georgia require a BODs limit of
5 mg/L while Massachusetts, Nevada, Tennessee and Washington require a BODs limit
of 30 mg/L. Some states have different ranges of BOD5 for different time ranges. For
example, North Carolina requires that BODs not exceed 10 mg/L (monthly average),
while the daily average of BOD5 should not exceed 15 mg/L. Some states such as
Florida and Ohio specify limits on CBOD which is respectively 20 mg/L and 25 mg/L.
Limits on TSS vary from 5 to 30 mg/L. Florida, Georgia, Indiana, and New Jersey
require a TSS limit of 5.0 mg/L prior to disinfection, while North Dakota, Tennessee, and
Washington require that TSS not exceed 30 mg/L. South Carolina and North Carolina
have different limits of TSS for daily and monthly averages. Limits on turbidity range
from 1 to 10 NTU, but most of the states require an average turbidity limit of 2 NTU and
a not-to-exceed limit of 5 NTU. Average fecal and total coliform limits range from non-
detectable to 23 counts per 100 mL Higher single sample fecal and total coliform limits
are allowed in several state regulations. Florida requires that 75% of the fecal coliform
samples taken over a 30 day period be below detectable levels, with no single sample
in excess of 25 counts per 100 mL, while Massachusetts requires a median of no
detectable fecal coliform per 100 mL over continuous seven-day sampling periods, and
not to exceed 14 counts per 100 mL in any one sample.
Restricted Urban Reuse
Restricted urban reuse involves: irrigation of areas in which public access can be
controlled, such as golf courses, cemeteries, and highway medians. Thus, treatment
requirements may not be as strict as for unrestricted urban reuse. Some States impose
the same requirements on both unrestricted and restricted urban access reuse, while
others adjusted different requirements for the restricted and unrestricted categories.
Table 4-3 shows the reclaimed water quality and treatment requirements for restricted
urban reuse for New Jersey. The only difference between the New Jersey unrestricted
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and restricted urban reuse regulations is that the restricted regulations do not contain a
specified turbidity limit.
Table 4-3. Restricted Urban Water Reuse Regulations for New Jersey
Treatment
BOD5
TSS
Turbidity
Coliform
Secondary treatment, filtered (chemical addition before filtration)
Not specified
5 mg/L (not to exceed before disinfection)
Not specified
Fecal:
- 2.2/100 ml (7-day median)
- 14/100 ml (maximum any one sample)
Limits on BODs range from 5 mg/L to 70 mg/L. Georgia requires a BODs limit of 5 mg/L
where Maryland requires a BOD5 limit of 70 mg/L. Some states have different ranges of
BODs for different time ranges. For example South Carolina requires that BODs not to
exceed 30 mg/L (monthly average) where the daily average of BOD5 should not exceed
45 mg/L. Some States such as Ohio specify limits on CBOD which is 40mg/L. Limits on
TSS vary from 5 mg/L to 90 mg/L. Georgia and Massachusetts require a TSS limit of
5.0 mg/L prior to disinfection and Maryland requires that TSS not exceed 90 mg/L.
South Carolina and North Carolina have different limits of TSS for daily and monthly
averages. Limits on turbidity range from 2 to 10 NTU, but most of the states require an
average turbidity limit of 2 NTU and a not-to-exceed limit of 5 NTU. Average fecal and
total coliform limits range from 2.2 counts per 100 mL to 200 counts per 100 ml. Higher
single sample fecal and total coliform limits are allowed in several state regulations.
Criteria that May Affect Irrigation as a Beneficial Use of Stormwater
There are few regulations restricting irrigation use of stormwater, although irrigation of
food and fodder crops are included in some of the above described restricted and
unrestricted urban water reuse regulations. Existing irrigation regulations focus on
public health and restrict bacteria levels in water that may be in contact with the public.
However, water quality criteria have been in place for many years recommending water
quality levels to prevent damage to the plants themselves. These are mostly for heavy
metal concentrations. Several cooperative extension services provide suggested water
quality guidelines. Table 4-4 is from the Texas Cooperative Extension Service, for
example, that lists specific irrigation water quality guidelines. In many cases, short-term
use allows higher concentrations compared to long-term use.
This table also lists potable water drinking water standards (MCLs, or maximum
contaminant limits) for reference. Potable uses require that the harvested water be
treated to drinking water standards. In many areas, stormwater is a significant water
source for the local drinking water supplies. Many states set drinking water levels based
on U.S. EPA MCLs; however, testing of the harvested water is based only on the
likeliest contaminants. These would be issued typically by the state's department of
health and would be reflected in testing requirements for well water. On this table, the
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irrigation criteria are less restrictive than the MCLs, with some exceptions, including:
chromium, copper, fluoride, and zinc. No drinking water MCLs exist for several of the
metals for which irrigation criteria are listed, including: cobalt, lithium, molybdenum,
nickel, and vanadium. The copper and zinc are common stormwater contaminants that
may hinder irrigation use. In addition, these two metals can be dramatically affected by
the use of certain materials commonly used in the construction of storage and delivery
facilities (galvanized metal roofs and storage tanks and copper pipes or other plumbing
fittings).
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Table 4-4. Texas Reuse Water Quality Criteria for Irrigation and EPA Potable Water MCLs
(Irrigation: http://lubbock.tamu.edu/irrigate/documents/2074410-B1667.pdf: Drinking Water:
http://water.epa.gov/drink/contaminants/upload/mcl-2.pdf)
Constituent
Aluminum (Al)
Arsenic (As)
Beryllium (Be)
Boron (B)
Cadmium (Cd)
Chromium (Cr)
Cobalt (Co)
Copper (Cu)
Fluoride (F-)
Iron (Fe)
Lead (Pb)
Irrigation Criteria (Texas)
Short-Term
Use (mg/L)
20
2.0
0.5
2.0
0.05
1.0
5.0
5.0
15.0
20.0
10.0
Long-Term
Use (mg/L)
5.0
0.10
0.10
0.75
0.01
0.1
0.05
0.2
1.0
5.0
5.0
Remarks
Can cause nonproductivity in acid soils, but
soils at pH 5.5 to 8.0 will precipitate Al and
eliminate toxicity
Toxicity to plants varies widely
Toxicity to plants varies widely
Essential to plant growth. Toxic to many
sensitive plants at 1 mg/L.
Toxic to beans, beets, and turnips at 0.1
mg/L.
Lack of knowledge on plant toxicity.
Toxic to tomatoes at 0.1 mg/L. Tends to be
inactivated by neutral and alkaline solutions.
Toxic to many plants at 0.1 to 1 .0 mg/L.
Inactivated by neutral to alkaline soils.
Not toxic to plants in aerated soils, but can
contribute soil acidification and loss of P and
Mo
Can inhibit plant cell growth.
EPA Potable Water MCLs
MCLs (M)/
SMCLs (S)
0.05-2.0(5)
0.01 (M)
0.004 (M)
0.005 (M)
0.1 (M)
1.3(M)/1.0(S)
4.0 (MJ/2.0 (S)
0.3 (S)
0.015 (M)
Remarks
Circulatory system damage;
skin damage; cancer
Internal lesions
Kidney damage
Allergic dermatitis
Short-term: Gastrointestinal
distress; Long-term: Liver and
kidney damage
Bone disease
Children: Physical/mental
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Constituent
Lithium (Li)
Manganese
(Mn)
Irrigation Criteria (Texas)
Short-Term
Use (mg/L)
2.5
10.0
Long-Term
Use (mg/L)
2.5
0.2
Remarks
Tolerated by most crops up to 5 mg/L; mobile
in soils. Toxic at low doses to citrus.
Toxic to number of crops at low
concentrations.
EPA Potable Water MCLs
MCLs (M)/
SMCLs (S)
0.05 (S)
Remarks
delays; Adults: Kidney damage
Table 4-4. Texas Reuse Water Quality Criteria for Irrigation and EPA Potable Water MCLs (continued)
(Irrigation: http://lubbock.tamu.edu/irrigate/documents/2074410-B1667.pdf: Drinking Water:
http://water.epa.gov/drink/contaminants/upload/mcl-2.pdf)
Constituent
Mercury
Molybdenum
(Mo)
Nitrate-N
Nitrite-N
Nickel (Ni)
Selenium (Se)
Irrigation Criteria (Texas)
Short-Term
Use (mg/L)
0.05
2.0
0.02
Long-Term
Use (mg/L)
0.01
0.2
0.02
Remarks
Nontoxic at normal concentrations. Toxic to
livestock if forage grown in soils with high
levels of available Mo.
Toxic to number of plants at 0.5 mg/L.
Reduced toxicity at neutral to alkaline pH.
Toxic to plants at low concentrations and to
livestock if forage grown in soils with added
Se.
EPA Potable Water MCLs
MCLs (M)/
SMCLs (S)
0.002 (M)
10.0(M)
1.0 (M)
0.05 (M)
Remarks
Kidney damage
Methemoglobinemia
Numbness; Circulatory
problems
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Constituent
Vanadium (V)
Zinc (Zn)
Irrigation Criteria (Texas)
Short-Term
Use (mg/L)
1.0
10.0
Long-Term
Use (mg/L)
0.1
2.0
Remarks
Toxic to many plants at low concentrations.
Toxic to many plants at wide concentration
variation. Reduced toxicity at increased pH (>
6) and in fine-textured or organic soils.
EPA Potable Water MCLs
MCLs (M)/
SMCLs (S)
5.0 (S)
Remarks
Original Source of Irrigation Water Quality Standards Data: Rowe, D.R. and I.M. Abdel-Magid. 1995. Handbook of
Wastewater Reclamation and Reuse. CRC Press, Inc. 550pp.
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Treatment Methods to Enhance Stormwater Quality for Beneficial Uses
Off-the-Shelf Treatment Systems
Many small-scale, rapid treatment systems have been developed that could be used to
treat stormwater runoff for beneficial uses, including the following (with some examples
provided in the following discussion):
• Rainwater harvesting treatment systems
• Aquaculture water treatment systems
• Well water treatment for indoor potable use
• Swimming pool water treatment systems
Rainwater Harvesting Treatment Systems
Rainwater harvesting systems typically are designed to capture relatively-clean runoff
from roofs. The website www.harvesth2o.com specializes in information relevant to the
rainwater harvesting industry. The focus of many of the treatment systems is
nonpotable reuse, such as landscape irrigation.
Rainwater harvesting systems usually consist of piping or gutters and cisterns or water
tanks, plus possible filtering or other treatment systems. Storage tanks range in size
from 130 liter (35 gallon) "rain barrels" to several thousand gallon underground storage
tanks. Depending on the size and visibility of the cistern, tank materials can be plastic
(typically opaque HOPE), wood, or galvanized metal. The interior of the tank should be
constructed from materials that are relatively unreactive with water, even during long-
term storage, and that do not allow light into the system to minimize algae growth
(Virginia Rainwater Harvesting Manual, 2009 available at:
http://dcr.virginia.gov/documents/stmrainharv.pdf. Screens often are used either at the
gutter, in the piping system, or at the entry to the cistern to capture leaves and other
large debris. For example, Rainwater Management Solutions
(www.rainwatermanagement.com) sells mesh screen filters (having aperture sizes
ranging from 280 to 1,000 micrometers) that are placed in the gutter system. Mesh
sizes in this range are not likely to provide removal of pollutants other than leaves and
other large debris. Meshes that are not cleaned regularly are likely to have a buildup of
leaves and, as the leaves degrade, nutrients likely will leach from the leaves and end up
in the cistern. The leaching of nutrients into the system from degrading leaves is why
rainwater harvesting guidance recommends opaque tanks to prevent algal growth.
Many water harvesting system vendors also sell water purification systems that can be
attached to the cistern outlet. These systems usually consist of a membrane filter and a
UV disinfection unit. They are very similar, or in some cases identical, to point-of-use
drinking water systems used in homes having private wells. The nominal pore size of
the filters used in these units can range from < 1 to several hundred micrometers.
Systems such as the SkyHarvester (Watertronics, Inc., at:
www.watertronics.com/?gclid=CPPt1KrT7KgCFYXd4Aod5XfuCg#/skvharvester) allow
more treatability options to be added to roof runoff harvesting system. SkyHarvester
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includes filtration components that remove particles >75 urn for drip irrigation systems,
plus the system can be used with reverse osmosis or ultrafiltration units. The
UrbanGreen Rainwater Harvesting System, sold by Contech Construction Products, Inc.
(www.contech-cpi.com/Products/Stormwater-Management/Rainwater-
Harvesting.aspx?gclid=CJXpuZiV7KgCFcTd4AodyhZtEw) consists of filtration down to
2-5 urn and disinfection (chlorination or UV light) can be attached to the tank and
operated in-line prior to use. Sediment filters can remove solids greater than the pore
size opening and those pollutants that are associated with the solids. However, these
filters do not remove dissolved pollutants effectively unless a chemically-active media is
included. For example, the Contech Downspout Filters contain a treatment media to
provide removal of many dissolved constituents, including zinc. The Rainwater Store
(http://therainwaterstore.com/index.php/) provides products from several manufacturers,
including a range of cartridge inserts for filter units. Some cartridges contain activated
carbon to enhance pollutant removal. In general, rainwater harvesting system vendors
do not report treatment effectiveness information. However, because these systems are
similar to those used in the aquaculture and drinking water industry, their efficiencies
and effluent quality can be estimated.
Swimming Pool Water Treatment Systems
Although not typically used to treat stormwater for beneficial uses, the technologies long
used for treating swimming pool water (focusing on bacteria levels for safe water
contact) could be used for maintaining acceptable water quality in water storage tanks
and to meet the bacteria limits in the reuse criteria. Most of these units use a
recirculating pump system having a sand filter and a disinfection unit. Systems are now
available that use ozone, reverse osmosis, and even chitosan to maintain
bacteriological quality, but historically, chlorine (usually added as Trichloro-S-
Triazinetrione, Sodium Dichloro-S-Triazinetrione, or calcium hypochlorite) was used.
With recirculation, it is possible to maintain good bacteriological conditions in storage
tanks, even without maintaining a high chlorine residual (such as required by some of
the water reuse standards).
Summary of Millburn Township and New Jersey Groundwater Disposal
Regulations and Treatment Options
The above discussions summarize regulations and guidance that may affect the
beneficial uses of stormwater, along with specific regulations from Millburn Township
and New Jersey pertaining to the use of dry wells for the disposal of stormwater to the
subsurface.
The Millburn Township stormwater regulations (in their Development Regulations) list
dry wells as one option for minimizing increased flows associated with new (and
increased) development. They do not include any specific criteria for their use, except
for a statement pertaining to a 60 cm (2 ft) blanket of crushed stone surrounding the dry
well. Specifically, they do not describe applicable soil characteristics, groundwater
conditions, or suitable source waters. In contrast, while the New Jersey stormwater
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regulations require the infiltration of excess water above natural conditions associated
with development or land modifications (either maintaining the pre-development
groundwater recharge or preventing excess surface runoff), they also include additional
guidance. The state dry well regulations describe the construction of the dry wells, the
acceptable soil conditions (HSG A and B), groundwater conditions (at least 60 cm or 2 ft
above seasonal water table), and source waters (roof runoff only).
Most of the reuse regulations available from different regulatory agencies were originally
written to pertain to reuse of sanitary wastewaters and do not specifically address
stormwater as a source water. There are a few regulations, however, that were
specifically prepared to regulate the beneficial uses of stormwater. All of these focus on
public health issues and contain restrictive levels of bacteria, typically with lower
allowable limits where public access is not well controlled, and with higher allowable
limits for water non-contact situations and where access can be well controlled. These
bacteria levels will be difficult to meet without further treatment. In addition, irrigation
criteria may affect stormwater use for certain plants, especially if galvanized metals or
copper is in contact with either the collection, storage, or distribution areas of the rain
water harvesting systems. Situations where groundwater recharge is direct with dry
wells or injection wells, or other methods providing little treatment, may also result in
adverse water quality.
Many people have questioned the application of the fecal indicator bacteria criteria to
non-human contamination sources, especially considering the commonly observed very
large indicator bacteria levels found in many stormwater flows. However, the EPA
recently published (December 2011 Federal Register) their new proposed recreational
water quality criteria pertaining to bacteria indicators. The following is a quote from that
report describing why they feel that the bacteria indicator criteria should apply to all
recreational waters, irrespective of contamination source:
"While human sources of fecal contamination are fairly consistent in the potential human
health risks posted during recreational exposure, non-human sources of fecal
contamination, and thus the potential human health risks, can vary from site-to-site
depending on factors such as: the nature of the non-human source(s), the fecal load
from the non-human source(s), and the fate and transport characteristics of the fecal
contamination from deposition to the point of exposure. Nonhuman fecal sources can
contaminate recreational bodies of water via direct fecal loading into the body of water,
and indirect contamination can occur via runoff from the land. The fate and transport
characteristics of the zoonotic pathogens and FIB present under these conditions can
be different (e.g., differences in attachment to particulates or differences in susceptibility
to environmental parameters affecting survival). For more information on pathogenic
risks from nonhuman sources, see Review of Zoonotic Pathogens in Ambient Waters
(U.S. EPA, 2009a). EPA did not develop nationally applicable criteria values that adjust
for the source of the fecal contamination, for non-human sources. Rather, EPA
recommends that States use these nationally applicable criteria in all waters designated
for primary contact recreation."
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Some of the stormwater constituents in roof runoff would likely have concentrations
greater than the associated numeric criteria. The most potentially problematic
constituents (where the exceedences are the greatest), include bacteria, followed by the
solids and turbidity values. The metals having the potentially greatest exceedences
include cadmium and zinc. Generally, roof runoff has better water quality than other
stormwater source areas, with most stormwater source areas (such as parking lots and
street runoff, and even landscaped areas) likely exceeding the numeric criteria for:
BODs, COD, TSS, and fecal coliforms. Therefore, none of the stormwater or source
waters would likely be able to meet the numeric criteria for stormwater beneficial uses,
with the bacteria being the most problematic, and the solids and turbidity values also
being an issue. Roof runoff is the preferred source water for beneficial stormwater uses,
but treatment, especially for bacteria, will likely be necessary.
Different materials are used in the collection, drainage, and storage components (such
as gutters, pipes and storage tanks) of stormwater beneficial use systems. Some
materials can degrade runoff water even with very short contact times, and would be a
problem even if used for the collection surface. Other materials, however, require
extended exposure periods to degrade the water, such as would be evident in storage
tanks. The most significant potential problems are associated with galvanized metal
roofs or gutter and tanks, plus copper pipe or other plumbing fixtures used in the
systems. These materials can elevate the zinc and copper concentrations to
problematic concentrations during rain events, while extended contact, such as storage
tanks, can cause very high concentrations.
Treatment of stormwater before most beneficial uses may therefore be needed. For
simple irrigation use, bacteria reductions may be necessary, and the prevention of
excessive metal concentrations through careful selection of materials. Cistern and water
tank storage can reduce most bacteria levels to close to the regulation's numeric
values, although some additional treatment may be needed. Roof runoff typically has
excessive bacteria levels, especially during the non-winter months and if trees are over
the roofs (providing habitat for birds and squirrels). Depending on the water quality of
the source stormwater and the intended beneficial use, different water quality treatment
options can be examined. There are a number of commercial units available that would
be suitable that can reduce the solids, bacteria, and heavy metals in the water before
use. Simple storage in cisterns and water tanks may approach the guideline values for
roof and yard runoff (most which were developed for treated sanitary wastewater), and
measures to minimize scour resuspension of deposited sediments, would likely be
sufficient to protect public health. More contaminated source waters may require more
sophisticated treatment options.
As noted elsewhere in this report, the Millburn dry wells worked well in infiltrating runoff,
except in areas having high water tables, or if poor subsurface soils exist. However, as
noted elsewhere in this report, they provided no significant improvement in water quality
for constituents of interest. Therefore, the local Millburn Township ordinance should be
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modified to allow dry well use only in areas already having good water quality (such as
would be expected for most roofs), or require suitable pretreatment. In addition, the
local ordinance should also prohibit dry well use in areas having seasonal or permanent
high water tables, as those conditions result in long-term standing water in the dry wells.
If located in areas having poorly draining subsurface soils, their designs need to be
modified to account for the more slowly draining conditions. Overall, it is recommended
the dry well use be restricted to roof runoff water sources, and alternatives that infiltrate
water through surface soils (such as rain gardens) be used to treat driveway and
parking lot runoff. Irrigation of landscaped areas using roof runoff (and pretreated paved
area runoff) is also a suitable alternative that also provides economic benefits to the
land owner.
71
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Chapter 5 Beneficial Uses of Stormwater for Infiltration and
Recharge in Millburn, New Jersey
Groundwater Recharge
Infiltrating groundwater through surface soils or infiltration stormwater controls (rain
gardens, biofilters, percolation ponds, etc.) or more direct recharging of groundwater
using stormwater (dry wells, injection wells, porous pavements, gravel trenches, etc.)
are the two mechanisms used to discharge stormwater to the groundwater as a
receiving water. The first mechanism is usually focused on removing stormwater from
the immediate surface water regime as a stormwater management tool, while the
second method is more to recharge local groundwater supplies for future use.
One of the earliest comprehensive reports investigating groundwater recharge was the
committee report prepared for the National Research Council (1994; Ground Water
Recharge using Waters of Impaired Quality). This report contained many international
case studies, mostly examining treated sanitary wastewaters, but also some on
stormwater. The main focus was groundwater recharge for later beneficial uses,
including potable use. The case studies that addressed potable use were mainly
associated with soil-aquifer treatment and had substantial subsurface residence times.
Short residence times and little aquifer movement of the recharged water would be
more similar to a storage tank, with reduced improvements in water quality.
The potential for infiltrating stormwater to contaminate groundwater is dependent on the
concentrations of the contaminants in the infiltrating stormwater and how effective those
contaminants may travel through the soils and vadose zone to the groundwater. Source
stormwaters from residential areas are not likely to be contaminated with compounds
having significant groundwater contaminating potential (with the exception of high
salinity snowmelt waters). In contrast, commercial and industrial areas are likely to have
greater concentrations of contaminants of concern that may affect the groundwater
quality adversely. Therefore, pretreatment of the stormwater before infiltration may be
necessary, or treatment media can be used in a biofilter, or as a soil amendment, to
hinder the migration of the stormwater contaminants of concern to the groundwater.
Again, these concerns are usually more of a problem in industrial and commercial areas
than in residential areas.
Pitt, et al. (2010) summarized prior research on potential groundwater contamination.
Table 5-1 can be used for initial estimates of contamination potential of stormwater
affecting groundwater. This table includes likely worst case mobility conditions using
sandy soils having low organic content. If the soil was clayey and/or had a high organic
content, then most of the organic compounds would be less mobile than shown. The
72
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abundance and filterable fraction information is generally applicable for warm weather
stormwater runoff at residential and commercial area outfalls. The concentrations and
detection frequencies would likely be greater for critical source areas (especially vehicle
service areas) and critical land uses (especially manufacturing industrial areas), with
greater groundwater contamination potential.
Table 5-1. Groundwater Contamination Potential for Stormwater Pollutants Post-Treatment.
Compound
Class
Nutrients
Pesticides
Other
organics
Pathogens
Heavy
metals
Salts
Compounds
Nitrates
2,4-D
y-BHC (lindane)
Atrazine
Chlordane
Diazinon
VOCs
1,3-dichlorobenzene
Benzo(a) anthracene
Bis (2-ethyl-hexyl)
phthalate
Fluoranthene
Naphthalene
Phenanthrene
Pyrene
Enteroviruses
Shigella
P. aeruginosa
Protozoa
Cadmium
Chromium
Lead
Zinc
Chloride
Surface Infiltration
with Minimal
Pretreatment (such as
rain gardens and
swales)*
Low/moderate
Low
Moderate
Low
Moderate
Low
Low
Low
Moderate
Moderate
Moderate
Low
Moderate
Moderate
High
Low/moderate
Low/moderate
Low
Low
Low/moderate
Low
Low
High
Surface Infiltration
with Sedimentation
or Filtration
Pretreatment*
Low/moderate
Low
Low
Low
Low
Low
Low
Low
Low
Low
Moderate
Low
Low
Moderate
High
Low/moderate
Low/moderate
Low
Low
Low
Low
Low
High
Subsurface Injection
with Minimal
Pretreatment (such
as in dry wells and
porous pavements)
Low/moderate
Low
Moderate
Low
Moderate
Low
Low
High
Moderate
Moderate
High
Low
Moderate
High
High
High
High
High
Low
Moderate
Moderate
High
High
NOTE: Overall contamination potential (the combination of the subfactors of mobility, abundance, and
filterable fraction) is the critical influencing factor in determining whether to use infiltration at a site. The
ranking of these three subfactors in assessing contamination potential depends of the type of treatment
planned, if any, prior to infiltration.
* Even for those compounds with low contamination potential from surface infiltration, the depth to the
groundwater must be considered if it is shallow (1 m or less in a sandy soil). Infiltration may be
appropriate in an area with a shallow groundwater table if maintenance is sufficiently frequent to replace
contaminated vadose zone soils.
Modified from Pitt, et al. 1994
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Therefore, groundwater contamination potential of infiltrating stormwater can be
reduced by:
1) careful placement of the infiltrating devices and selection of the source waters.
Most residential stormwater is not highly contaminated with the problematic
contaminants, except for chlorides associated with snowmelt.
2) commercial and industrial area stormwater would likely need pretreatment of
reduce the potential of groundwater contamination associated with stormwater.
The use of specialized media in the biofilter, or external pre-treatment may be
needed in these other areas.
Infiltration Tests at Millburn Dry Well Installations
Infiltration tests were conducted during two project phases: the first phase filled the dry
wells with domestic water from Township fire hydrants and the decreasing water levels
were recorded; the second phase used continuous monitoring in a fewer number of dry
wells during many rains.
Much information was collected as part of this research project in Millburn to measure
actual performance of the dry wells. Both short and long-term infiltration measurements
were conducted at many locations. This data were analyzed and are summarized in this
report section, with more detailed data included in Appendix B.
The infiltration measurements were conducted using continuously recording (10 minute
observations) LeveLoggers by Solintest that were installed in the dry wells. Short-term
tests were conducted in many dry wells throughout the Township to measure the
influence of many of the conditions present in the community. These tests were
conducted using water from fire hydrants and included filling the dry wells completely.
The LeveLoggers were then used to measure the drop in water level over time. The
long-term tests were conducted in fewer dry wells (based on the number of
LeveLoggers available). These were installed for several months to over a year and
continuously recorded the water levels in the dry wells every 10 min. Close-by rain
gages were also used to record local rains associated with these events. These rain
and water level data were downloaded by PARS Environmental personnel and
uploaded to their FTP site where University of Alabama researchers downloaded the
data for analysis.
The first step in the data analyses was to plot the data as time series. Figure 5-1 is an
example time series plot of the water levels recorded over a two month period at 11
Woodfield Dr. showing 6 separate events (the first peak only shows the dropping water
levels from the Oct 13, 2009 event). The infiltration characteristics of the dry well
installations were calculated from the recession cures of these individual rain events.
The infiltration rates for each 10 minute step were calculated based on the drop in water
level per increment, resulting in plots of infiltration rates vs. time since the peak water
74
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level. These are classical infiltration rate plots and statistical analyses were used to
calculate infiltration rate equation parameters for two common infiltration equations
(Morton and Green-Ampt).
120
'
u bj
1
0 I
(
J( 10/13/2009
10/24/2009
\
!
I
,_..... ..
10000
11 Woodfield Dr
10/13/2009 - 12/18/2009
12/09/2009 L
~| 12/13/2009 |
/
t{
t
20000 30000 4:0:0 50000 eoooo 70000 BOOOO 90000 100000
Time (min)
Figure 5-1. Time series example of dry well water levels for a two month period at 11 Woodfield Dr.
The following discussions present and compare these results with the varying site
conditions.
®
Rainfall Measurements
Four rain gages were installed in the study area for this project (HOBO data logging
rain gage data logger). The rain gauges are battery-powered rainfall data collection and
recording systems which included a HOBO® Pendant Event data logger integrated into
a tipping-bucket rain gauge. Below is a list of the locations of the four rain gages. Figure
5-2 shows photos of three of the rain gages (with some undergoing calibration).
• R1: Private house on top of chimney slab at 1 Delwick Lane - Calibrated and
launched at 14:00 on 5/22/09.
• R2: Roof of Township's maintenance garage on Essex Rd - Calibrated and
launched at 12:00 on 5/13/09.
• R3: Municipal Par 3 Golf Course on White Oak Ridge Rd - Calibrated and
launched at 16:00 on 5/13/09.
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R4: Old tennis court at Greenwood Gardens on Old Short Hills Rd - Calibrated
and launched at 16:00 on 5/6/09.
R2: Roof of Township's maintenance
garage (gage being calibrated)
R2: Roof of Township's maintenance
being calibrated)
R3: Municipal Par 3 Golf Course (gage
being calibrated)
R4: Old tennis court at Greenwood
Gardens (with top funnel removed)
76
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R2: Millburn Township Garage rooftop rain
gage location.
R1: Residential rooftop rain gage location
(located near chimney).
Figure 5-2. Photos of rain gages (R1, R2, and R3 are shown during site calibration).
Figure 5-4 shows the locations of the rain gages and the monitoring locations, while
Table 5-2 lists the monitoring sites and corresponding closest rain gage locations.
Table 5-2. List of Rain Gages Closest to Monitoring Site Locations
Rain Gage
R1: 1 DelwickLn
R2: 345 Essex St
R3: 335 White
Oak Ridge Rd
R4: 274 Old
Short Hills Rd
Dry well Locations
1 1 Woodfield Dr
1 5 Marion Ave
258 Main St
2 Undercliff Rd
383 Wyoming Ave
260 Hartshorn Dr
79 Minnisink Rd
87/89 Tennyson Dr
36 Farley PI
1 Sinclair Terrace
142FairfieldDr
8 Beechcroft Rd
7 Fox Hill Ln
9 Fox Hill Ln
11 Fox Hill Ln
ID on Map (Figure 5-4)
1
2
3
4
5
6
7
Sand 9
16
10
11
12
13
14
15
The rain gages provided information about the start time, end time, duration, depth and
average intensity of each rain event. Each rain event is defined as a separate rain event
that has at least 6 hr of no rain before and after the recorded rainfall. The rain
77
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information corresponding to the infiltration data is summarized for each infiltration
event monitored, as shown in Table 5-3 and Figure 5-3. The rainfall graphs and
information are presented in Appendix B, along with the infiltration information.
Table 5-3. Example Summary of Rainfall Information (2/25/2011 - R3) (1 in. = 25.4 mm)
Start time
2/25/201 1
0:25
End time
2/25/201 1
18:44
Duration
(hi)
18:19
Depth
(in.)
1.36
Average intensity
(in./hr)
0.06
R3:: 335 White Oak Ridge Rd (2/25/2011)
19:12 0:00 4:48 9:36 14:24 19:12 0:00
Time
Figure 5-3. Example of a rain event graph. (1 in. = 25.4 mm)
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Figure 5-4. Location of dry wells (blue icons), rain gages (yellow icons), and water quality samplers (red icons for dry wells and green
icon for cistern).
79
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Infiltration Measurements
The water levels in the dry wells were recorded using Solinist Levelogger Gold and
Barologger monitors. The Levelogger Gold is an absolute data logger which measures
water levels and temperature. The Levelogger Gold devices use a sensitive
piezoresistive silicon pressure transducer packaged in a stainless steel housing. The
Levelogger converts the total pressure reading to its corresponding water level
equivalent, after correction for changing atmospheric pressure from the Barologgers.
The water levels were recorded every 10 min.
Initial infiltration studies were conducted by quickly filling selected dry wells with water
from Township fire hydrants and recording the subsequent fall of the water levels.
These infiltration studies were performed after at least a 72 hr dry period. The
photographs in Figure 5-5 show the process of filling the dry well with the Township fire
hydrant water at one of the test sites. Table 5-4 describes the Township water infiltration
tests for the seven selected sites.
Figure 5-5. Infiltration studies for a dry well located at 383 Wyoming: rapidly filling the dry well
with water from the fire hydrant and recording the fall of water level.
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Table 5-4. Test Characteristics for Township Fire Hydrant Infiltration Tests at Seven Dry Wells
Location
1 Sinclair Terrace
2 Undercliff Road
383 Wyoming
8 South Beechcroft
9 Fox Hill Lane
11 Fox Hill Lane
1 1 Woodfield Road
Fill Date
7/15/2009
10/2/2009
10/2/2009
10/2/2009
10/2/2009
10/2/2009
10/13/2009
Start Fill
Time
10:40
09:07
10:14
12:07
12:44
13:16
10:07
Stop Fill
Time
11:30
09:26
10:43
12:15
13:15
14:00
10:30
Total Fill
Time
(min)
50
19
29
8
31
44
23
Total Fill
Volume from
Hydrant (gal)
3,300
2,500
2,900
900
2,600
3,400
3,600
Fill Rate
(gal/min)
66
132
100
113
84
77
157
Infiltration Equations
Site soil evaluations included infiltration measurements, along with soil density, texture,
and moisture determinations. The water infiltration data can be fitted to soil water
infiltration models, such as the Green-Ampt (1911), the Kostiakov (1932), the Morton
(1940) and the Philip's (1957) equations. Although various infiltration equations have
different mathematical structures and calibration parameters, their estimates are all
premised on observed water infiltration data (in./hr as a function of time). The most
common Green-Ampt and Morton equations were examined during this project and are
briefly described in the following discussions.
Horton Infiltration Equation
One of the most commonly used infiltration equations was developed by Horton (1940).
The equation is as follows:
f = fc + (fo - fc)e
-kt
(1)
Where f is the infiltration rate at time t (in./hr), f0 is the initial infiltration rate (in./hr), fc is
the final (constant) infiltration rate (in./hr), and k is first-order rate constant (hr~1 or min"1).
This equation assumes that the rainfall intensity is greater than the infiltration capacity
at all times and that the infiltration rate decreases with time (Bedient and Huber 1992).
This is a reasonable assumption for ponded conditions, such as in the dry wells. The
capacity of the soil to hold additional water decreases as the time of the storm increases
because the pores in the soil become saturated with water. The Horton equation's major
drawback is that it does not consider the soil water storage availability after varying
amounts of infiltration have occurred, but only considers infiltration as a function of time
(Akan 1993). However, integrated forms of the equation can be used that do consider
the amount of water added to the soil. It is recommended that fc, f0, and k all be
obtained through field data, but they are rarely measured locally. Table 5-5 shows
commonly used Horton infiltration parameter values, as summarized by Denver's Urban
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Drainage and Flood Control District (2001). This summary is for the four NRCS
hydrologic soil groups corresponding to HSG sandy (A) to clayey (D) conditions. The
coefficient values for C and D soils are the same, with B soils having only slightly
increased infiltration rates.
Table 5-5. Morton Infiltration Coefficient Values Typically used in Urban Drainage Projects (Urban
Drainage and Flood Control District, UDFCD 2001)
HSG
A
B
C
D
Initial
infiltration rate,
f0 (in./hr)
5.0
4.5
3.0
3.0
Final
infiltration rate,
fc (in./hr)
1.0
0.6
0.5
0.5
First-order rate
constant (1/hr)
2.52
6.48
6.48
6.48
First-order rate
constant
(1/min)
0.04
0.11
0.11
0.11
1 in./hr = 25.4 mm/hr
Akan (1993) presented a somewhat more detailed table for the initial infiltration rates
(the other coefficients did not change greatly for the different soil conditions). Akan
shows the effects of antecedent moisture and vegetation on these initial infiltration
rates.
Table 5-6. Morton parameters (Akan, 1993)
Soil Type
Sandy soils with little to no vegetation
Dry loam soils with little to no vegetation
Dry clay soils with little to no vegetation
Dry sandy soils with dense vegetation
Dry loam soils with dense vegetation
Dry clay soils with dense vegetation
Moist sandy soils with little to no vegetation
Moist loam soils with little to no vegetation
Moist clay soils with little to no vegetation
Moist sandy soils with dense vegetation
Moist loam soils with dense vegetation
Moist clay soils with dense vegetation
fo (in./hr)
5
3
1
10
6
2
1.7
1
0.3
3.3
2
0.7
1 in./hr = 25.4 mm/hr
Green-Ampt Infiltration Equation
Another common equation for infiltration calculations is by Green-Ampt. The Green-
Ampt equation calculates cumulative infiltration as the water flows into a vertical soil
profile (Green and Ampt, 1911).
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(2)
Where: ft is infiltration rate, cm/hr; i// is the initial matric potential of the soil (in.); A# is
the difference of soil water content after infiltration with initial water content (in.3/ in.3); K
is hydraulic conductivity (in./hr); and Ft is the cumulative infiltration at time t (in.). This
equation requires a linear relationship between ft and (1/Fj. Table 5-7 shows some
typical Green-Ampt equation parameter values suggested by Rawls, etal. (1983).
Table 5-7. Green-Ampt
Soil type
sand
loamy sand
sandy loam
loam
silt loam
sandy clay loam
clay loam
silty clay loam
sandy clay
silty clay
clay
Porosity
0.437
0.437
0.453
0.463
0.501
0.398
0.464
0.471
0.430
0.479
0.475
Darameters
Effective
porosity
0.417
0.401
0.412
0.434
0.486
0.330
0.309
0.432
0.321
0.423
0.385
Rawls, etal. 1983)
Suction
head (mm)
49.5
61.3
110.1
88.9
166.8
218.5
208.8
273.0
239.0
292.2
316.3
Hydraulic
conductivity (mm/h)
117.8
29.9
10.9
3.4
6.5
1.5
1.0
1.0
0.6
0.5
0.3
Infiltration as a Function of Soil Texture and Compaction
Hydrologic models must contain a process to address the infiltration of rain water into
the soil. The infiltration process in most models is usually dependent on the porosity and
moisture content of the soil: in an unsaturated soil, infiltration usually is initially rapid but
then declines to a constant value as the soil becomes saturated. Soil infiltration is an
issue in urban watershed management due to concerns of groundwater contamination
and because poor infiltration conditions after land development, which is one of the
causes of increased surface runoff (in addition to increased amounts of impervious
surfaces) (Pitt, etal. 1994 and 1995). It has been well documented that during
urbanization, soils are greatly modified, especially related to soil density. Increased soil
compaction results in soils that do not behave in a manner predicted by traditional
infiltration models. It is crucial, therefore, that stormwater engineers better understand
infiltration in disturbed urban soils. Laboratory and field tests can be used to determine
expected infiltration behavior of disturbed urban soils for a specific area.
Since the early 1990s, Pitt, et al. (1999) has conducted a series of laboratory and field
tests on soils covering a wide range of soil textures, densities, and stiffness. As shown
in Figure 5-6, these field tests highlighted the importance of compaction on the
83
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infiltration rate of soils. For sandy soils, minimal effects are seen associated with
antecedent moisture conditions compared to soil compaction. For the clayey soils, both
the compaction level and antecedent moisture conditions are likely important in
determining the infiltration rate. Table 5-8 summarizes the Morton equation coefficients
for these urban soils, showing the dramatic effect soil density has on the infiltration
characteristics.
Three dimensional plots of infiltration rates
for sandy soil conditions.
Three dimensional plots of infiltration rates
for clayey soil conditions.
Figure 5-6. Effects of soil moisture and soil compaction on infiltration rates (Pitt, eta/. 1999).
Table 5-8. Morton Coefficients (Pitt, et a/. 1999)
Infiltration
Parameter
fo (in./hr)
fc (in./hr)
k(l/min)
Soil Group
Clay - Dry Noncompact
Clay-Other
Sand-Compact
Sand-Noncompact
Clay - Dry Noncompact
Clay-Other
Sand-Compact
Sand-Noncompact
Clay - Dry Noncompact
Clay-Other
Sand-Compact
Sand-Noncompact
90%
42
7
42
52
20
0.75
5
24
0.3
0.18
0.28
0.32
75%
24
3.75
12
46
12
0.5
1.25
19
0.22
0.1
0.2
0.2
50%
11
2
5
34
3
0.25
0.5
15
0.16
0.06
0.1
0.08
25%
7
1
1.5
24
0.75
0
0.25
9
0.07
0.03
0.05
0.03
10%
5
0
0
0.25
0.25
0
0
0
0.05
0
0.016
0
1 in./hr = 25.4 mm/hr
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Fitted Horton Equation Parameters for Millburn Dry Well Infiltration
Measurements
Fitting Observed data to Horton's Equation
The initial infiltration data analysis was to prepare plots of the observed infiltration data
in order to evaluate major trends and groupings of the data. Observed data included
water stage in dry wells for every 10 min. The differential values of water stages in a dry
well for each event were divided by time to calculate the infiltration rates as a function of
time. Data from each site for each event/infiltration test was fitted to the Horton
infiltration equation and the equation parameters were derived forf0, the initial infiltration
capacity, fc, the constant infiltration capacity as t approaches infinity, and k, a soil
parameter that controls the rate of decrease of infiltration rate. For some of the sites, the
Horton equation was not able to be fitted to the observed data, as little change occurred
with time. This typically occurred for narrow ranges of the dry well water depth and
when standing water due to shallow water tables. For these conditions, the observed
rates most likely corresponded to the fc values, the saturated infiltration rate (f0 and k
were not calculated).
Figure 5-7 shows the observed infiltration rates and the fitted Horton equation
parameter values for the dry well located at 7 Fox Hill Ln, Millburn, NJ, as an example.
Graphs are for three different actual rain events representing observed data, fitted
Horton equations, rain depths, and the water stage in the dry well. The remaining
observed data along with fitted Horton graphs for each dry well and each event are
presented in Appendix B. Some initial rates were very large, but the rates decreased
quickly with time.
Basic statistical analyses, including average, minimum, maximum, standard deviation,
and COV are included for all the data, as well as ANOVA test and residual plots for
some of the fitted Horton equations in comparison to Green-Ampt equation.
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7-Fox Hill Lane -10/01/2010
0:00 4:48 9:36 14:24 19:12 0:00 4:48
•Fitted Horton Equation
Observed Data
• Rain Depth
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7-Fox Hill Lane -10/01/2010
3.5
2.5
r 1.5
1
0.5
0
0:00
4:48
9:36 14:24 19:12
Time (min)
0:00
4:48
•Fitted Horton Equation
Observed Data
•Water stage in drywell
7-Fox Hill Lane -12/01/2010
4.5
i:00 4:48 9:36 14:24 19:12 0:00 4:48 9:36
Time (min)
•Fitted Horton Equation
Observed Data
•Rain Depth
87
-------
7-Fox Hill Lane -12/01/2010
14:24
19:12 0:00
Time (min)
4:48
9:36
•Fitted Morton Equation
Observed Data
-Water stage in dry we 11
7-Fox Hill Lane: 02/24/2011 - 02/25/2011
3.5
0
19:12 0:00 4:48 9:36 14:24 19:12 0:00 4:48 9:36
Time (min)
•Fitted Horton Equation
Observed Data
•Rain Depth
7-Fox Hill Lane: 02/24/2011 - 02/25/2011
3.5
0:00 4:48 9:36 14:24 19:12
Time (min)
0:00
4:48
9:36
•Fitted Horton Equation
Observed Data
•Water stage in drywell
Figure 5-7 Example of observed data, fitted Horton equation, rain depth, and water stage in a dry
well for three different rain events in a selected dry well. (1 in./hr = 25.4 mm/hr)
88
-------
Tables 6a through 6n in Appendix B are a summary of the best-fit Morton equation
parameter values based on infiltration tests for some sites at Millburn, NJ, for different
rains. Three types of tables are included for the tests:
- Infiltration study test: A table summarizing Morton parameters, infiltration
study test characteristics and water depth in the dry wells.
- Infiltration for rain events: Fitted observed data to Morton's equation
resulting forf0, fc, and k values.
- Infiltration for rain events when fitting the observed data to Morton's
equation results in f0= fc (and k is therefore not applicable): A table
summarizing statistical analysis for f0 = fc, rain characteristics of
corresponding rain event, and water depth in the dry wells.
Statistical Groupings of Site Data for Horton Coefficients
Multiple iterations of grouped box and whisker plots and ANOVA tests were used to
identify data groupings. The data were not normally distributed so ANOVA based on
ranks and Mann-Whitney Rank Sum nonparametric tests were used to calculate the
significance that the data did not originate from the same populations.
There were two distinct sets for the fc data: the 258 Main St location vs. all of the other
sites combined. Figure 5-8 shows these two data sets.
89
-------
6 -
^ ^ 4 .
.c
o
2 -
0 -
•
-f-
I 1
1 2
All Sites vs, 258 Main St Site
Figure 5-8. Box and whisker plot of fc data showing two sets of data. (1 in./hr = 25.4 mm/hr)
The results of the final Mann-Whitney Rank Sum test for fc are shown below:
Normality Test (Shapiro-Wilk) Failed (P < 0.050)
Group N
Combined 81
258 Main 3
Missing
0
0
Median
0.33
5.308
25% 75%
0.22 0.568
4.662 6.808
Mann-Whitney U Statistic= 0.000
T = 249.000; n (small) = 3; n (big) = 81; P = 0.004
The difference in the median values between the two groups is greater than would be
expected by chance; there is a statistically significant difference, with P = 0.004. Tables
5-9 and 5-10 summarize the values and test conditions for these two sets of data.
90
-------
Table 5-9. fc Summary Values and Conditions for 258 Main St.
number
Minimum
Maximum
Average
Median
Std Dev
COV
fc (in./hr)
3
4.66
6.81
5.59
5.31
1.10
0.20
Rain Depth
(in.)
3
0.69
1.34
1.08
1.22
0.35
0.32
Max. depth of
water in dry
well (in.)
3
22.32
54.77
43.57
53.62
18.41
0.42
Min. depth of
water in dry
well (in.)
3
0.11
0.67
0.44
0.53
0.29
0.67
1 in. = 25.4 mm
Table 5-10. fc Summary Values and Conditions for All of the Other Sites
number
Minimum
Maximum
Average
Median
Std Dev
COV
fc (in./hr)
81
0.05
2.37
0.45
0.33
0.38
0.85
Rain Depth
(in.)
63
0.22
2.90
1.20
1.15
0.76
0.63
Max. depth of
water in dry
well (in.)
81
6.51
93.85
50.45
53.76
22.93
0.45
Min. depth of
water in dry
well (in.)
81
0.00
82.98
20.88
10.07
24.15
1.16
1 in. = 25.4 mm
Similar tests were conducted to identify significant groups for the f0 data. Figure 5-9 is
the final box and whisker plot, showing the two data groups: 258 Main St, plus 8 So.
Beechcroft vs. all the data combined.
91
-------
Fo for Different Millburn Locations
60 -
-g- 40-
0
20 -
0 -
±
I 1
1 2
Site Location
Figure 5-9. Box and whisker plot of f0 data showing two sets of data. (1 in./hr = 25.4 mm/hr)
The results of the final Mann-Whitney Rank Sum test for f0 are shown below:
Normality Test (Shapiro-Wilk) Failed (P < 0.050)
Group N Missing Median
All the rest combined 43 0 3.116
258 Main & 8 So. Beechcroft 7 0 45.29
Mann-Whitney U Statistic= 0.000
T = 329.000; n (small) = 7; n (big) = 43; P = <0.001
25% 75%
1.941 5.631
19.78 74.916
The difference in the median values between the two groups is greater than would be
expected by chance; there is a statistically significant difference: P = <0.001.
Tables 5-11 and 5-12 summarize the values and test conditions for these two
sets of data.
92
-------
Table 5-11. f0 Summary Values and Conditions for 258 Main St. and 8 So Beechdroft Rd.
number
Minimum
Maximum
Average
Median
Std Dev
COV
fo
(in./hr)
7
16.12
75.14
44.55
45.29
23.74
0.53
Rain Depth
(in.)
6
0.52
1.71
1.14
1.28
0.45
0.39
Max. depth
of water in
dry well (in.)
7
16.76
54.77
38.29
41.29
14.98
0.39
Min. depth of
water in dry
well (in.)
7
0.10
1.94
0.54
0.32
0.65
1.21
1 in. = 25.4 mm
Table 5-12. f0 Summary Values and Conditions for All of the Other Sites
number
Minimum
Maximum
Average
Median
Std Dev
COV
fo
(in./hr)
43
1.01
13.95
4.34
3.12
3.20
0.74
Rain Depth
(in.)
60
0.22
2.90
1.20
1.07
0.77
0.64
Max. depth
of water in
dry well (in.)
77
6.51
93.85
51.28
54.45
23.07
0.45
Min. depth of
water in dry
well (in.)
77
0.00
82.98
21.93
12.06
24.32
1.11
1 in. = 25.4 mm
Similar tests were conducted to identify significant groups for the k data. Figure 5-10 is
the final box and whisker plot, showing the two data groups: 258 Main St vs. all the
other data combined.
93
-------
k rate for Different Millburn Sites
0.08
0.06 -
~ 0.04 -
0.02 -
0.00 -
T
Site Locations
Figure 5-10. Box and whisker plot of k data showing two sets of data.
The results of the final Mann-Whitney Rank Sum test for k are shown below:
Normality Test (Shapiro-Wilk) Failed (P < 0.050)
Group N Missing Median 25% 75%
All others combined 46 0 0.0135 0.0075 0.02
258 Main 3 0 0.06 0.045 0.07
Mann-Whitney U Statistic= 1.000
T = 143.000; n (small) = 3; n (big) = 46; P = 0.005
The difference in the median values between the two groups is greater than would be
expected by chance; there is a statistically significant difference, with P = 0.005. Tables
5-13 and 5-14 summarize the values and test conditions for these two sets of data.
94
-------
Table 5-13. k Summary Values and Conditions for 258 Main St.
number
Minimum
Maximum
Average
Median
Std Dev
COV
k
(1/min)
3
0.05
0.07
0.06
0.06
0.01
0.22
Rain Depth
(in.)
3
0.69
1.34
1.08
1.22
0.35
0.32
Max. depth of
water in dry
well (in.)
3
22.32
54.77
43.57
53.62
18.41
0.42
Min. depth
of water in
dry well (in.)
3
0.11
0.67
0.44
0.53
0.29
0.67
1 in. = 25.4 mm
Table 5-14. k Summary Values and Conditions for All of the Other Sites
number
Minimum
Maximum
Average
Median
Std Dev
COV
k
(1/min)
46
0.002
0.050
0.014
0.014
0.009
0.666
Rain Depth
(in.)
63
0.22
2.90
1.20
1.15
0.76
0.63
Max. depth of
water in dry
well (in.)
81
6.51
93.85
50.45
53.76
22.93
0.45
Min. depth
of water in
dry well (in.)
81
0.00
82.98
20.88
10.07
24.15
1.16
1 in. = 25.4 mm
Fitting Observed Data to Green-Ampt Equation
The Green-Ampt equation calculates cumulative infiltration assuming water flowing into
a vertical soil profile. Figure 5-11 is an example comparison between fitted Morton and
Green-Ampt equations for one of the events at a selected dry well, as well as statistical
analysis and residual plots. The remaining graphs are in Appendix B.
95
-------
10
8
383 Wyoming Ave. 8-02-2009
f=0.928+4.522exp(-0.003t)
Observed
Morton
Green Ampt
200
400
600 800
Time (min)
1000
1200
1400
Figure 5-11. An example of fitted obsereved data to Morton equation and Green-Ampt equation (1
in. = 25.4 mm)
Residual Plot (Horton)
Fitted Value
Residual Plot (Green-Ampt)
8 10
Fitted Value
Figure 5-12. Residual Plots for Horton and Green-Ampt fitted values
Regression Analysis for f vs. 1/F (Green-Ampt)
ANOVA
Regression
Residual
Total
Intercept
X Variable 1
df
1
131
132
Coefficients
1.676322
5.26193
SS
51.25879
51.81269
103.0715
Standard
Error
0.062127
0.462214
MS
51.25879
0.395517
tStat
26.98234
11.38418
F
129.5995
p-value
2.4E-55
2.67E-21
Significance F
2.67E-21
Lower 95%
1.553421
4.34756
Upper 95%
1.799223
6.1763
96
-------
Linda's Flower 06-17-2010
200 400
Time (mini
600
Linda's Flower 07-14-2010
100
Time (min)
200
Linda's Flower 08-01-2010
258 Main St - 06-17-2010
200
Time (min)
400
40 80
Time (mm)
2 Undercliff Rd 10/2/2009
383 Wyoming Ave. 7-26 2009
250 500
Time (min)
750
0 200 400 600 800 1000
Time (min)
383 Wyoming Ave. 7-29-2009
383 Wyoming Ave. 8 02 2009
f=l. 139+9.114exp -O.CKBSt
10
8
f=0.928+5.45exp(-0.003t)
0 400 800 1200 1600
Time (min)
500 1000
Time (min)
1500
Figure 5-13. Morton and Green-Ampt fitted curves for observed data, (dots: observed data, red
line: Morton and green line:Green-Ampt. The Morton equation is written on each graph) (1 in. =
25.4 mm)
97
-------
As it is shown in Figure 5-13, the Morton equation usually had a better fit to the data
compared to the Green-Ampt equation for the Millburn data. However, for some sites,
the Green-Ampt equation was a better fit. As noted previously, a linear relationship
between ft and (1/Fj is needed to determine the Green-Ampt equation parameters.
Figure 5-14 presents the linear regressions of ft vs (1/Fj for the monitored sites. The
only visually acceptable linear regression is associated with the observations from the
258 Main St. site (the only location that had soils in the A group from the surface to
about 1.1m (3.5ft) deep). This site also had the best Green-Ampt fitted equation shown
in Figure 5-13 as well. In almost all cases, the linear relationship between ft vs (1/Fj is
unacceptable (except for this one location), making the Morton equation a more suitable
tool for calculating expected infiltration for the dry wells.
Table 5-15. Green-Ampt parameters
Site Address
Linda's Flower
258 Main St.
2 Undercliff
383 Wyoming Ave.
Date
06-17-2010
07-14-2010
08-01-2010
06-17-2010
10-02-2009
7-26-2009
Hydraulic
conductivity K (in./hr)
estimated
2.435
2.685
3.131
1.018
0.557
1.039
Rawls et al.
(1983)
0.429
1.17
0.429
0.13-0.43
1 in. = 25.4 mm
Linda's Flower 06-17-
2010
Linda's Flower 07-14-
2010
Linda's Flower 08-01-2010
c
••=, 2
= 1.5/F + 2.7
R2 = 0.55
0 0.4 0.8 1.2 1.6
258 Main St - 06-17-2010
2 Undercliff Rd
10/2/2009
383 Wyoming Ave. 7-26-
2009
98
-------
23
20
•Z1 15
f=83/F+1.0
R2 = 0.96
0.1 0.2
1/Ffin1)
0.3
Figure 5-14. Linear regression of ft vs 1/F, for some sites in Millburn, NJ. (1 in. = 25.4 mm)
Summary of Recharge Observations with Dry Wells
Groundwater recharge is a suitable beneficial use of stormwater in many areas used to
augment local groundwater resources. This study showed how the dry wells could be
very effective in delivering the stormwater to the shallow groundwaters. Even though the
surface soils were almost all marginal for infiltration options, the relatively shallow dry
wells were constructed into subsurface soil layers that had much greater infiltration
potentials. However, some of the monitored dry well locations experienced seasonal
high groundwater elevations, restricting complete draining of the dry wells after rains.
While surface and subsurface soil information is readily available for the Township (and
in most other areas of the country), the presence of the shallow water table (or bedrock)
is not well known. This makes identifying the most suitable locations for dry wells
difficult, as the seasonal groundwater should be at least 2.4 m (8 ft) below the ground
surface (or 60 cm, 2 ft, below the lowest gravel fill layer beneath the dry well).
Calculating the benefits of the dry wells (including developing sizing requirements)
requires the use of an appropriate infiltration equation, preferably as part of a
continuous model examining many years of actual rain fall data for a specific area. Two
commonly used infiltration models, the Morton and Green-Ampt equations, were
evaluated for their potential use to calculate groundwater recharge at the case study
locations in the Township of Millburn, NJ. The fitted graphs and resulting derived
equation parameters indicate that although the Morton curve is usually a better fit to the
observed data, the calculated parameters of both infiltration models are not close to
values reported in the literature for urban areas. This is likely because the infiltration
characteristics in the dry wells were mostly affected by subsurface conditions compared
to the literature values that were compared to the surface soil characteristics. When the
subsurface conditions are used in the comparisons, the observed and literature values
are in better (but still not close) agreement. Therefore, locally measured infiltration test
data at a scale approaching the size and depth of the final devices should be used for
more reliable design guidance, instead of rely on literature values.
99
-------
Factors Affecting Infiltration Rates
The data analyses of the infiltration data indicated several interesting conclusions. One
of the first issues noted by the field personnel when installing the level recorders and
observing the dry wells over time is that some of the locations experienced periodic (or
continuous) standing water in the dry wells, indicating seasonal or permanent high
water table conditions, or partially clogged dry wells.
Figures 5-15 and 5-16 are time series plots of the water levels for the long-term
infiltration tests at the dry wells and are very informative concerning the trends and
overall behavior of the infiltration characteristics at the different sites. The hydrant water
tests are shown separately (with expanded time scales), and are also shown on the
longer period plots. The plots show the water elevations in the dry wells along with the
corresponding rain depths as recorded at the nearest rain gage. In some cases, dry well
activity is indicated with no corresponding rainfall. This is likely due to variable (small)
rains in the areas that were not recorded at all of the gages. The rain data indicate the
total rain depth and the start and end times; the graphs cover too long of a period to
show variable rain intensities during the rains. The times and depths are the most
important rain information for these measurements, as they relate most closely to the
runoff quantity and the dry well water elevations.
In almost all cases, the general shapes of the recession limbs (water elevation drops
with infiltration) are similar for the same site, including the hydrant tests. However, some
changed with time, including several that indicated slower infiltration with more standing
water conditions in the winter and spring. This may be due to SAR issues (sodium
adsorption ratio) that results in dispersed clays from high sodium content in snowmelt.
Normally, snowmelt would not affect these units if only roof runoff is directed to the dry
wells. However, if walkway or driveway runoff drains to dry wells, de-icing chemicals
(heavy salt loads) may be in the runoff.
Standing water was observed in the dry well at 87/89 Tennyson when sufficient time
occurred to allow the water to reach a consistent minimum water level (about 0.9 m or 3
ft deep). It is expected that this site very likely has a high water table condition. The
drainage rates were very slow, so the interevent periods were not sufficiently long to
enable drainage to the stable water level until after about a two week dry period. The
slow drainage rate may have been caused by saturated conditions.
Several sites (260 Hartshorn, 7 Fox Hill, and 142 Fairfield) experienced periodic slowly
draining conditions, mainly in the spring that could have been associated with SAR
problems. The slow infiltration rates could be due to poor soils (with the clays resulting
in SAR problems), or saturated soil conditions.
The other sites all had rapid drainage rates that were consistent with time.
100
-------
Table 5-16. Summary of Infiltration Conditions with Time
11 Woodfield Dr.
15 Marion Dr.
383 Wyoming Ave.
258 Main St.
260 Hartshorn
2 Undercliff Rd
87/89 Tennyson
Start date of
series
Oct 1 1 , 2009
June 17,
2010
July 16, 2009
June 16,
2010
August 9,
2010
July 18, 2009
August 10,
2010
End date of
series
Dec 20,
2009
August 6,
2010
October 14,
2009
Augusts,
2010
August 1,
2011
October 6,
2009
August 5,
2011
# of dry well
events
1 hydrant
5 rains (1
small rain
missing)
1 hydrant
5 rains (2
small rains
missing)
1 hydrant
6 rains (2
small rains
missing)
5 rains (2
smaller rains
missing)
Many!
1 hydrant
3 rains
Many
% of time
dry well
was dry
89%
71%
81%
98%
10%
79%
0%
Consistent shape
with time?
Consistent shape
with time
Consistent shape
with time
Consistent shape
with time
Consistent shape
with time
Consistent shape
with time
Consistent shape
with time
Consistent shape
with time
Standing water after
events?
Quickly drained
(within a day); No
standing water at any
time
Several days to drain;
No standing water at
anytime
Several days to drain
if full;
No standing water at
anytime
Very rapid drainage
time;
No standing water at
anytime
Slow drainage time
(about a week if full),
but dry if given
enough time between
rains
Several days to drain
if full;
No standing water at
anytime
Very slow drainage
time (a couple of
weeks); standing
water and never dry
during this year period
Other comments
1 5 hr total drainage time
during hydrant test
4.5 days total drainage
time during hydrant test
1 day total drainage time
during hydrant test
Clogging or poor soils,
not high water table.
Possible SAR issues in
the Winter and Spring,
recovered by mid-
summer.
10 days total drainage
time during hydrant test
Slow drainage may be
due to saturated
conditions, never reached
stable low water level. If
due to SAR, did not
recover.
101
-------
7 Fox Hill
8 So. Beechcroft
142 Fairfield
36 Farley Place
Start date of
series
August 7,
2010
July 19, 2009
August 10,
2010
June 16,
2010
End date of
series
March 23,
2011
September
27, 2009
March 4,
2011
Augusts,
2010
# of dry well
events
Many
1 hydrant
6 rains
many
3 rains
% of time
dry well
was dry
2%
71%
66%
97%
Consistent shape
with time?
Consistent shape
with time
Consistent shape
with time for rains,
but hydrant test (at
end of periods at
end of Sept) was
very rapid
Somewhat
inconsistent shape
with time
Consistent shape
with time
Standing water after
events?
Slow drainage time
(about a week or two
if full), but dry if given
enough time between
rains
Quickly drained
(within a day or two if
full); No standing
water at any time
Quickly drained
(within a day or two if
full) to poorly drained
(a week for moderate
rains); Standing water
during periods of large
and frequent rains
Very rapid drainage
time;
No standing water at
anytime
Other comments
Clogging or poor soils
especially in Spring,
possibly SAR issues, not
high water table
3 hr total drainage time
(half full) during hydrant
test
Slowly drained conditions
in Spring likely due to
saturated conditions, or
SAR. Not likely due to
high water table
102
-------
HWoodfield Dr- Hydrant test
HI
I
i
40
35
30
25
20
10
o/,
*?
Q/,
*?
''
•'
15 hr total drainage time
1 Sinclair Terrace - Hydrant test
Time
28 hr total drainage time
15 Marion Drive - Hydrant test
-, 7°
J.60
^ 50
B-
•° 30
« 20
GO
™ 10
IX)
5 °
Time
,-. 5°
_c
^ 40
-------
2 Undercliff Rd. - Hydrant test
~. 60
I 50
m
40
«•»
*»
H*
fi 10
| °
N.
Time
10 days total drainage time
8 So. Beechcroft - Hydrant test
18
7 16
ir 14
« 12
* 10
t §
= 6
'« 4
» ^
- 0
I
Time
3 hr total drainage time (only half full as too rapid infiltration
to fill dry well to full depth)
9 Fox Hill Ln-Hydrant test
About 20 days total drainage time (extrapolated as rains
interrupted test)
11 Fox Hill Ln - Hydrant test
.
Time
8 days total drainage time
Figure 5-15. Hydrant water test infiltration plots (cont.).(1 in. = 25.4 mm)
104
-------
fin
^n
m
i
&" dn
£
Q.
V
•o
•- 9H
1
5 JO
0
7n
fiO
7
•— * c;n
_ 50
1
>• /in
_C
« on
i
1 n
6
11 Woodfield Dr
Hydrant test
-i
/ '
y/ U
1
I
|
i . 11 It
Time
15 Marion Drive
Hydrant test
i
\ I \
\ \\ \
\N l\ N N V
X X X X X X
Time
water
- i stage
- 1,5 _____
2 —. rain
t event
—
-------
120
100
s
•o
.£
01
1
5
£
80
60
20
383 Wyoming Ave.
Hydrant test
\
Time
0.5
water
stage
•rain
depth
2.5
- 3
3.5
70
"d" 60
40
V
H
10
0
258 Main st
Time
- 0.5
1
1.5 _..
_c
2 jT
0
2.5
- 3
- 3.5
- 4
4.5
V
•water
stage
•rain
event
Figure 5-16. Time series plots of the water levels for the long-term infiltration tests at the dry wells
(cont.)
106
-------
(1 in. = 25.4 mm)
260 Hartshorn
120
—. 100
g
t
80
.= 60
e
« 40
I
20
%>,
u
"V, ^
^% ^%
%,
%
Time
^
%
'-?0
^
^
%
- 1
2
f
3
•water
stage
•ram
event
tt
^
**
%
260 Hartshorn
120
100
8°
c 60
g,
I 40
20
- 1
2 T
41
3 -a
n
cc
•water
stage
•rain
event
- 5
Time
107
-------
Figure 5-16. Time series plots of the water levels for the long-term infiltration tests at the dry wells
(cont.)
(1 in. = 25.4 mm)
120
260 Hartshorn
a.
ai
•o
n
t£.
•water
stage
•rain
event
Time
60
50
40
30
20
10
0
2 Undercliff Rd
0
h 0.2
0.4
- 0.6
0.8
1
1.2
1.4
1.6
1.8
2
•water
stage
-Rain
event
Time
108
-------
Figure 5-16. Time series plots of the water levels for the long-term infiltration tests at the dry wells
(cont.)
(1 in. = 25.4 mm)
87/89 Tennyson
•water
stage
•rain
event
Time
109
-------
87/89 Tennyson
•water
stage
rain
event
Time
Figure 5-16. Time series plots of the water levels for the long-term infiltration tests at the dry wells
(cont.)
(1 in. = 25.4 mm)
87/89 Tennyson
water
stage
•rain
event
Time
x
110
-------
87/89 Tennyson
180
160
•ram
event
•Series
5
Time
Figure 5-16. Time series plots of the water levels for the long-term infiltration tests at the dry wells
(cont.)
(1 in. = 25.4 mm)
7 Fox Hill
water
stage
rajn
event
111
-------
7 Fox Hill
120
— 100
80
11
I
I
60
40
20
Time
•water
stage
•ram
event
Figure 5-16. Time series plots of the water levels for the long-term infiltration tests at the dry wells
(cont.)
(1 in. = 25.4 mm)
112
-------
100
90
7 80
i" 70
I 60
•o
.E 50
5 30
™ on
5 iU
10
0
7 Fox Hill
u
(V N
x/\.
^\J xv
\
^B
r\
N r^
\j \ i\
s
^ \ r
\J
^ %, X X X *
Time
- 0.5
water
1 7 stage
•o
.E rain
- 2 t£ event
- 2.5
O
80
70
I 60
m
S 50
•o
.E 40
I30
10
0
/
8 So. Beechcroft
1
ll
VN^
1
1
I I
V \
Hydrant test
\
5
Time
0
0.5
1
1.5 ,.
^ water
2 ^ stage
•o
•| rain
3.5 K event
4
4.5
5
Figure 5-16. Time series plots of the water levels for the long-term infiltration tests at the dry wells
(cont.)
(1 in. = 25.4 mm)
113
-------
140
oi
£• 80
60
£ 40
k
142 Fairfield
Time
- 0.5
- 1
1.5 ^
2 g-
•o
e
2.5 »
3
- 3.5
4
•water
stage
-rain
event
120
100
^ 80
g
60
40
20
142 Fairfield
Time
- 0.5
- i
water
•o
2.5
•ram
event
3
3.5
Figure 5-16. Time series plots of the water levels for the long-term infiltration tests at the dry wells
(cont.)
(1 in. = 25.4 mm)
114
-------
7n
•£ ™
"3
>- an
C tu
Q]
CD
k
w
t! ?n
1 n
s<
t-_ i
Tim
36 Farley PI
e
X
- 0.5
1
water
1.5 7 Sta8e
«-»
2 °-
•a
- 2.5 ^ event
- 3
- 3.5
Figure 5-16. Time series plots of the water levels for the long-term infiltration tests at the dry wells
(cont.)
(1 in. = 25.4 mm)
The New Jersey dry well disposal regulations for stormwater require that the seasonal
water table be no closer than two ft below the bottom of the dry well (and underlying
rock storage area) due to expected deceased performance (and increased groundwater
contamination potential). Water table information was not readily available and some of
the dry wells were apparently constructed in areas having water tables that were too
shallow. The following list shows the water table conditions at the dry well monitoring
locations:
• Sites having no standing water after the events (completely drained with no apparent
high water table conditions):
11 Woodfield Dr
15 Marion
258 Main St
1 Sinclair Terrace (only one observation)
8 South Beechcroft Rd
11 Fox Hill Lane (only one observation)
36 Farley Place
115
-------
• Sites having a few standing water conditions after the events (standing water of
several inches, or more, indicating possible seasonal high water table conditions):
2 Undercliff Rd (one high water condition out of 3 observations; July 29 2009
event)
383 Wyoming Ave (one high water condition out of 5 observations; July 29 2009
event)
142 Fairfield Dr (two high water conditions out of 7 observations; Feb 26, 2011
and March 7, 2011 events)
Sites with all or most events having high water conditions:
260 Hartshorn Dr (16 of 19 observations had high water conditions; 8/25/10,
5/30/11, and 7/8/11 drained almost completely)
87/89 Tennyson Dr (20 out of 20 observations had high water conditions)
7 Fox Hill Lane (9 of 11 observations had high water conditions; 8/22/10 and
12/13/10 drained almost completely)
9 Fox Hill Lane (only 1 observation)
Figure 5-17 is a map showing these conditions for the Township. Most of the monitored
dry wells were along a ridge between the two main drainages of the Township, with no
obvious pattern of high water conditions, except that the high standing water dry wells
were located along a line to the southwest along the ridge and are located fairly close to
headwaters of streams (high water tables were noted in areas with nearby streams, but
that was assumed to be in the larger stream valleys and not at the headwaters). The
sites that had high standing water long after the events ended had substantially reduced
infiltration rates. In the analyses, these rates were considered to be the constant (final)
rates observed, with no initial rate data or first-order decay Horton coefficients used
(relatively constant, but very low infiltration rates).
116
-------
ing Avenue
DEM
Value
- High : 588.236
- Low: 81.4229
Sites with all or most events having high water table conditions
Standing water of several inches including seasonal high water table conditions
Completely drained with no high water table conditions
0 0.2 0.4
0.3
1.2 1.6
zz^^^M Miles
Figure 5-17. Township map showing locations having varying standing water conditions in
monitored dry wells.
Another obvious factor affecting the observed infiltration rates was that one or two of the
locations had significantly higher infiltration rates than the other sites (all having no
standing water issues). These sites were the ones indicated as having the highest
surface infiltration rate potentials (even though the infiltration rates of the dry wells were
mostly affected by the subsurface soil conditions, which were mapped as being similar
A and B conditions for all locations). It is therefore expected that these locations had
better subsurface soil conditions compared to the other sites, even though mapped as
being similar.
Therefore, the Township of Millburn infiltration rate characteristics were separated into
three conditions:
• A and B surface soils and having well drained HSG A subsurface soils
• C and D surface soils and having well drained A and B subsurface soils
117
-------
• C and D surface soils and having poorly drained A and B subsurface soils with
long-term standing water
The infiltration rate conditions for these Township of Millburn situations are presented in
Figures 5-18 through 5-20 and Tables 5-17 through 5-19.
*" 2 S
2 20 -
o
•^
re
k
V
oo
re
V
10 1fl
c
V
w
re
4
>
\
\
\
\
4
•
>
\
\
\
>
\
\
\
4
K
^
~~~
^
4
V
^
= 17.304xJ
•\2 ~ 0 985
^\__
0.433
3
^
~~~-~
-^
^
>•
0.1 1 10 100
Infiltration Duration (hrs)
Figure 5-18. Infiltration rates averaged over event durations for A and B surface soils and well-
drained A subsurface soils. (1 in./hr = 25.4 mm/hr)
Table 5-17. Infiltration Rates Averaged Over Event Durations for A and B Surface Soils and Well-
Drained A Subsurface Soils
duration
(hrs)
0.5
1
2
4
8
24
48
72
infiltration rate averaged over
duration of event (in./hr)
24.1
18.7
13.0
9.1
6.1
3.9
3.3
3.1
cov
0.3
0.3
0.3
0.3
0.4
0.6
0.8
0.8
(1 in./hr = 25.4 mm/hr)
118
-------
3.5
^ n
™ 9 R
Q)
1
§
S 2.0 -
V
H
» 1.5 -
V
>
n
»1 n -
I
0.5 -
0.0
4
\
^
\
\
\
>
^
\
\
\
x 4
\
^
x
X
\
^
.
x
y = 2.6
R2 =
^
\
blbx*
0.9S?
V
).325
S
-
>
>-^
--^
^
0.1 1 10 100
Infiltration Duration (hrs)
Figure 5-19. Infiltration rates averaged over event durations for C and D surface soils and well-
drained A and B subsurface soils. (1 in./hr = 25.4 mm/hr)
Table 5-18. Infiltration Rates Averaged Over Event Durations for C and D Surface Soils and Well-
Drained A and B Subsurface Soils
duration
(hrs)
0.5
1
2
4
8
24
48
72
infiltration rate averaged over
duration of event (in./hr)
3.0
2.7
2.2
1.9
1.5
0.9
0.7
0.7
cov
1.0
1.0
0.9
0.9
0.8
0.6
0.6
0.6
(1 in./hr = 25.4 mm/hr)
119
-------
7 R
^ T n
.C AU
_C
W
*J
CD
k.
C
O 1 c
rage infiltrati
•" h
3 I
rtal event ave
3 h
n C
I- "
On
4
>•
\
\
\
\
x<
\
\
V
4
K,
\
•x
^
4
t*
~-
y= 1.4796X0-3
R2 = 0.9899
^
»-
57
-*
:
0.1 1 10 100
Infiltration Duration (hrs)
Figure 5-20. Infiltration rates averaged over event durations for C and D surface soils and poorly-
drained A and B subsurface soils having extended standing water. (1 in./hr = 25.4 mm/hr)
Table 5-19. Infiltration Rates Averaged Over Event Durations for C and D Surface Soils and Poorly-
Drained A and B Subsurface Soils Having Extended Standing Water
duration
(hrs)
0.5
1
2
4
8
24
48
72
infiltration rate averaged over
duration of event (in./hr)
1.9
1.6
1.2
0.9
0.7
0.4
0.4
0.4
cov
1.2
1.1
1.0
0.9
0.8
0.6
0.6
0.6
(1 in./hr = 25.4 mm/hr)
120
-------
These figures and tables show that the over-all event infiltration rate decreases as the
duration increases. For example, for a typical 5 hour rain period (having about a 6 hour
runoff period), the event-averaged infiltration rate would be about 190 mm (7.6 in.) per
hour for the best conditions having A or B surface soils and well-drained subsurface A
and B soils. This reduces to about 43 mm (1.7 in.) per hour for the C or D surface soils
having well-drained subsurface A and B soils. For the condition having standing water
and poorly drained subsurface soils, the infiltration rates would be about 20 mm (0.8 in.)
per hour. Complete drainage times for the best soil conditions for this event would be
several hours, extending to about a day for the intermediate condition, and several days
for the condition with standing water. Of course, for the situation having standing water,
the "dry" well may never drain completely if the standing water was associated with a
high water table. If the standing water observations were due to clogging from debris,
the dry wells may eventually drain completely, if enough time occurs between rains.
The New Jersey stormwater regulations require the infiltration of excess water above
natural conditions associated with development or land modifications (either maintaining
the pre-development groundwater recharge or preventing excess surface runoff), for the
24-hr, 2-year storm, which is about 86 mm (3.4 in.) for Essex County. The dry well
regulations describe the construction of the dry wells, the acceptable soil conditions
(HSG A and B), groundwater conditions (at least 2 ft or 60 cm above seasonal water
table), and source waters (roof runoff only). The minimum design infiltration rate for
groundwater recharge is 5 mm/hr (0.2 in./nr) while it is 12 mm/hr (0.5 in./hr) for
stormwater quality use. These design standards for total event infiltration rates would
not be met only for conditions having standing water for very long event durations. The
largest rain that had infiltration measurements during this study was about 74 mm (2.9
in.), close to the design storm value.
Observed Infiltration Coefficient Values Compared to Literature Values
Table 5-20 compares the observed Morton equation coefficients with values that have
been reported in the literature. The standing water data are not shown on this table as
most of the observations could not be successfully fitted to the Morton equation. The
almost steady infiltration rates (but with substantial variation) were all very low for those
conditions and likely represent the fc conditions only and were therefore included in that
parameter category.
121
-------
Table 5-20. Observed and Reported Morton Equation Coefficients
Surface A and B soils well drained A subsurface soils
(average and COV)
Surface C and D soils well drained A and B subsurface
soils (average and COV)
UDFCD (2001) A soils (average)
UDFCD (2001) B soils (average)
UDFCD (2001) C and D soils (average)
Pitt, etal. (1999) Clayey, dry and non-compacted (median)
Pitt, etal. (1999) Clayey, other (median)
Pitt, etal. (1999) Sandy, compacted (median)
Pitt, etal. (1999) Sandy, non-compacted (median)
Akan (1993) Sandy soils with little to no vegetation
Akan (1993) Dry loam soils with little to no vegetation
Akan (1993) Dry clay soils with little to no vegetation
Akan (1993) Moist sandy soils with little to no vegetation
Akan (1993) Moist loam soils with little to no vegetation
Akan (1993) Moist clay soils with little to no vegetation
f0 (in./hr)
44.6 (0.53)
4.3 (0.64)
5.0
4.5
3.0
11
2
5
34
5
3
1
1.7
1
0.3
fc (in./hr)
5.6 (0.2)
0.45 (0.85)
1.0
0.6
0.5
3
0.25
0.5
15
K(1/min)
0.06 (0.22)
0.01 (0.63)
0.04
0.11
0.11
0.16
0.06
0.1
0.08
(1 in./hr = 25.4 mm/hr)
The very large observed f0 value (45 in./hr) for the A and B surface soil sites that are
well drained is greater than any of the reported literature values, and only approaches
the observations for the non-compacted sandy soil conditions (34 in./hr) observed by
Pitt, et al. (1999). The subsurface soil conditions affecting the dry well infiltration rates
are likely natural with little compaction. Also, the subsurface soils at that location are
noted as being sandy loam (A) and stratified gravelly sand to sand to loamy sand (A).
The other sites having smaller f0 rates (4.3 in./hr) are described as gravelly sandy loam
(A) and fine sandy loam (B) and are similar to many of the reported literature values for
sandy soils, with some compaction.
The largest fc value (5.6 in./hr) observed for the well-drained A and B surface soil
location is bracketed by the non-compacted clayey and sandy soil conditions (3 and 15
in./hr) reported by Pitt, et al. (1999), but is substantially larger than the other reported
values. The fc value observed for the well-drained C and D surface soil site (0.45 in./hr)
is similar to the other reported values (0.5 to 1.0 in./hr). The k first-order rate values
(0.01 and 0.06 1/min) are similar, but on the low side, of the reported values (0.04 to
0.11 1/min).
In order to most accurately design dry well installations in an area, actual site
observations of the expected infiltration rates should be used instead of general
literature values. This is especially true for surface infiltration devices (such as rain
gardens), where compaction will have a much greater effect than on the deeper
subsurface soils. Also, all of the sites in this study had improved infiltration
characteristics with depth compared to expected surface conditions; in other cases, this
may not be true. Criteria based only on surface soil conditions are likely not good
122
-------
predictors of deeper dry well performance. Luckily, county soil surveys do have some
subsurface soil information that was found to be generally accurate during this study.
Unfortunately, shallow water table conditions are not well known for the area and that
characteristic can have a significant detrimental effect on the observed dry well
performance.
123
-------
Chapter 6 Dry Well Disposal Water Quality Observed in Millburn,
NJ
During construction of three new dry wells, shallow and deep monitoring well
underdrains were installed to collect percolating water for analyses during ten rain
events. The water quality of these samples were compared to water quality criteria to
identify potential groundwater contamination issues associated with dry well use in
these typical installations and also to identify differences in the water quality as it
passed through the dry well gravel layer and at least two feet of underlying soil.
Sampling Locations
Three dry wells in Millburn were instrumented with monitoring well underdrains for
sampling, as shown in Figure 6-1. The shallow monitoring well underdrain was
constructed directly below the dry well near the surface of the gravel layer and a deeper
one was installed at least 0.6 m (2 ft) below the bottom of the gravel layer (the NJ state
requirement for closest groundwater). Therefore, the deep monitoring location was at
least 1.2 m (4 ft) below the bottom of the dry well. Water samples were manually
pumped from these monitoring well underdrains during or immediately after the rains
and analyzed for a range of typical stormwater pollutants.
SOIL
2" dia PYC pipe
perfororated on the
horizontal section
and up to 2' on
vertical
Seepage Pit'
Figure 6-1. PVC Pipe arrangement in dry wells
Table 6-1 lists the addresses of the sampled dry wells in Millburn. Water samples were
collected during or after ten storm events from these dry wells involving a total of two
samples for each location; one from directly below the dry well ("shallow") and the other
from the deeper monitoring well underdrain ("deep"). Samples were also collected from
the inlet and outlet locations at an underground water storage cistern at 79 Minnisink
Road, Millburn, NJ. Figure 6-2 shows the locations of these sampling locations.
124
-------
Table 6-1. Water Quality Monitoring Locations
Dry Well and Cistern Sampling Site Locations
135 Tennyson Road, Millburn, NJ, 07078 (dry well location)
18 Slope Drive, Millburn, NJ, 07078 (dry well location)
139 Parsonage Hill Road, Millburn, N,J 07078 (dry well location)
79 Minnisink Road, Millburn, NJ, 07078 (cistern location)
79 Minnisink
Rd (cistern)
Cwnmmtty
139
Parsonage
*
Fox Mil
' Ktn,
3.
Millburn
*, Jsffwaon
y
1
Figure 6-2. Locations of Water Quality Sampling Sites in Millburn, NJ.
Table 6-2 lists the rain depths for the ten monitored rains. A storm is defined as a rain
event producing at least 2.5 mm (0.1 in.) of total rainfall and produces sufficient flow for
collection of samples for analysis. A rain free period of 3 hr was used to define separate
rain events. A water volume of 2 L was collected during each sampling event at each
sampling location.
125
-------
Table 6-2. Rain Depths for Monitored Events
Date
10/20/2010
7/29/201 1
8/5/201 1
08/10/2011
08/16/2011
08/17/2011
08/18/2011
08/22/201 1
08/25/201 1
08/28/2011**
Rain Depth
0.10 in.*
0.15 in.*
0.14 in.*
0.12 in.*
0.15 in.
0.20 in.
0.10 in.
0.50 in.
0.25 in.
9 in.
*The data from these rains was obtained from http://www.wunderqround.com/
while the other rains were obtained from on-site rain gages.
**Hurricane Irene rain began about 3:00 pm on 08/27/2011 and finished at
about 10:00 am on 08/28/2011, producing record rainfall for the area.
(1 in. = 25.4 mm)
Sampling Procedure
The samples obtained after each event were packaged, cooled, and transported by
PARS personnel to the University of Alabama laboratory for analyses. The samples
were preserved and stored in a sample storage refrigerator according to requirements
described in Table 6-3 upon arrival to the laboratory until analysis. HOPE containers
were used for all samples and subsamples received in the laboratory. Each water
sample was analyzed for bacteria (total coliform and E. coli), total nitrogen, total
phosphorus, and chemical oxygen demand using the standard procedures listed in
Table 6-3. Also, each analysis for each sample was duplicated.
For bacteria analyses (using IDEXX QuantiTray methods) all analyses were conducted
within 24 hr of sampling. This delay is longer than the desired 6 hrs holding time for
bacteria analyses but were used to indicate approximate bacteria levels; based on prior
storage tests, the observed bacteria levels were likely about half the levels that may be
expected with fresher samples. Therefore, if the results were greater than the criteria
after 24 hr holding times, they are very likely also greater than if the samples were
analyzed within the shorter holding time. If the results were very low, they would
probably also be low if analyzed earlier. Samples for metal analyses were all preserved
by acidification to a pH less than 2 using ultra-pure HMOs and then stored at 4 C before
analyses at the outside laboratory (Stillbrook Environmental Laboratories, Fairfield, AL).
For all the other parameters, sample preservation was according to recommended
methods as shown on Table 6-3.
126
-------
127
-------
Table 6-3. Summary Table of Standard Methods, Procedures, and Quality Assurance
Parameter
Total nitrogen
(asN)
Nitrate plus
nitrite (as N)
Total
phosphorus (as
P)
COD (as C)
Pesticides
Herbicides
Heavy Metals
(Cu, Pb, Zn)
Analytical Method
Number and Name
Persulfate digestion
method (HACH
10071)
SM 4500-NO3-D&E
Cd reduction
(HACH 8039)
SM 4500-P-E
Colorimetric,
Ascorbic Acid,
Single Reagent,
EPA 365.2 (HACH
8190)
Mercury free
dichromate
digestion (HACH
800)
SW846-8081A
SW846-8081A
ICP
Preservation
Method/Maximum Holding
Time
Cool 4°C/48hrs or
preservation with H2SO4 to a
pH of <2 required and cool
4C; holding time 28 days
Cool4°C/48hror
preservation with H2SO4 to a
pH of <2 required if samples
will not be analyzed within a
48 holding time
Cool 4°C/48hrs or
preservation with H2SO4 to a
pH of <2 required and cool
4C; holding time 28 days
Cool4°C/48hror
preservation with H2SO4 to a
pH of <2 required if samples
will not be analyzed within a
48 holding time
Cool 4°C/7days
Cool 4°C/7days
Acidification to pH 1-2 (ultra-
pure HNOs)/6 months
Sample Volume and
Sample Container
100 ml_ HOPE, acid
washed with HCI
100 ml_ HOPE, acid
washed with HCI
100 ml_ glass, rinsed
with HCI, then distilled
water
100mL HOPE, acid
washed with HCI
2L sample volume,
amber glass with
Teflon liner, pre-
cleaned
2L sample volume,
amber glass with
Teflon liner, pre-
cleaned
100 mLHDPE
Processing
Summary
Analyses
performed on
whole sample
Analyses
performed on
whole sample
Analyses
performed on
whole sample
80-120
4-1
E
o
is
&
0
Q
1 mg/L
0.002 mg/L**
0.020 mg/L
<10
0.5 ug/kg
0.5 ug/kg
5 ug/L for Pb;
20 ug/L for Cu
and Zn
S?
5x
O
03
^
O
3
80-120
80-120
80-120
80
80-120
80-120
85-115
S?
ecision
i—
Q_
<10
<10
<10
<10
<10
<10
<15
to
to
o
-------
Results of Dry Well and Cistern Water Sample Analyses
All samples were analyzed in duplicate for each analytical run. The following discussion
is a summary of the results for each measured parameter. Only samples from three of
the locations were available for the first event, and cistern samples were not obtained
during the second and fourth events. Therefore, seven to ten samples were available
from each sampling location.
Bacteria
Tables 6-4 and 6-5 summarize the total coliform and E. coll levels. The upper detection
limit (UDL) of this method is 2,419.2 MPN/100 ml and the lower detection limit (LDL) is
1 MPN/100 ml for both indicator organisms. After completion of the first two rounds of
sampling, it was observed that most bacteria levels exceeded the UDL (even with the
24 hr maximum delay that was longer than the desired standard 6 hr holding time).
Therefore, one of the samples per site was diluted 10 times to increase the UDL to
24,192 MPN/100 mL. For some samples, 20 times dilution was applied to increase the
UDL to 48,384 MPN/100 mL. As can be seen from Table 6-4, wide ranges of bacteria
levels were detected for all events at all locations. The geometric means for the total
coliform results were 17 to 15,106 MPN/100 mL, while the geometric means for the E
co// results (setting half of the detection limits for nd values) were 4 to 358 MPN/100 mL.
The cistern related sample bacteria levels were generally lower than for the dry well
samples. The last event listed in Tables 6-4 and 6-5 has the highest values of bacteria
observed and occurred during the record 9 inch rainfall of Hurricane Irene. Total
coliform levels were higher in the cistern than the inflow and generally the deep
locations in each site had higher values of total coliform, possibly indicating some
regrowth in the gravel layer.
129
-------
Table 6-4. Summary of Sampling Results for Total Coliform Bacteria (MPN/100 mL)
Date
10/20/2010
7/29/201 1
8/5/201 1
8/10/2011
8/16/2011
8/17/2011
8/18/2011
8/22/201 1
8/25/2011*
8/28/201 1
Location
79
Inflow
10
36
11
11
1
1
9,374
79
Cistern
83
34
2,024
25,406
1,483
2,609
374
1 1 ,672
135
Shallow
1,317
8,469
1,909
15,971
36,294
5,316
12,409
1,210
43
25,406
135
Deep
1,785
3,629
18,147
15,174
36,294
8,480
11,672
25,406
332
25,406
18
Shallow
404
199
14,711
36,294
11,672
25,406
7,698
620
18,539
18
Deep
8,469
18,147
36,294
31,961
25,406
18,539
15,346
1,251
25,406
139
Shallow
352
352
12,351
36,294
18,539
14,207
15,346
2,021
18,539
139
Deep
8,469
364
13,122
31,961
5,562
9,374
8,911
1,589
25,406
Basic Statistics
Number
Average
Min
Max
Median
Geometric
Mean
StDev
COV
7
1,349
1
9,374
11
17
3,539
2.6
8
5,461
34
25,406
1,753
1,119
8,915
1.6
10
10,834
43
36,294
6,892
4,010
12,040
1.1
10
14,632
332
36,294
13,423
8,199
11,791
0.8
9
12,838
199
36,294
11,672
4,703
12,428
1.0
9
20,091
1,251
36,294
18,539
15,106
11,060
0.6
9
13,111
352
36,294
14,207
5,881
1 1 ,466
0.9
9
11,640
364
31,961
8,911
6,615
10,562
0.9
*This sample was received in the laboratory two days after sampling and the measured bacteria levels
are therefore likely lower than expected compared to fresh samples.
130
-------
Table 6-5. Summary of Sampling Results for E. coli (MPN/100 mL)
Date
10/20/2010
7/29/201 1
8/5/201 1
8/10/2011
8/16/2011
8/17/2011
8/18/2011
8/22/201 1
8/25/2011*
8/28/201 1
Location
79
Inflow
3
<20
<1
<1
<1
<1
5,087
79
Cistern
<22
3
287
22
14
269
4
5,562
135
Shallow
<22
6,752
471
239
7,183
352
281
343
6
2,817
135
Deep
<22
268
550
227
360
195
381
3,128
2
2,716
18
Shallow
<2
10
222
57
85
20
41
2
70
18
Deep
2
15
57
36
125
58
124
25
68
139
Shallow
252
252
154
215
106
42
70
6
99
139
Deep
8,469
162
136
180
46
39
62
24
1,593
Basic Statistics
Number
Average
Min
Max
Median
Geometric
Mean
StDev
COV
2
2,545
<1
5,087
<1
4
3,595
1.4
7
880
3
5,562
22
45
2,068
2.4
9
2,049
6
7,183
352
358
2,914
1.4
9
870
2
3,128
360
210
1,178
1.4
8
63
2
222
49
22
70
1.1
9
57
2
125
57
36
44
0.8
9
133
6
252
106
90
91
0.7
9
1,190
24
8,469
136
174
2,775
2.3
* This sample was received in the laboratory two days after sampling and the measured bacteria levels
are therefore likely lower than expected compared to fresh samples.
Nutrients
Tables 6-6 to 6-8 summarize the observed concentrations for the nutrients total
nitrogen, NOs plus NCb, and total phosphorus. The total nitrogen as N varied from zero
(ND, reported as zero by this test method) to 16.5 mg/L. The NOs plus NC^
concentrations ranged between 0.2 to 3.2 mg/L. The total phosphorus concentrations
ranged from 0.02 to 1.36 mg/L. The median values for most of the locations were about
the same for shallow or deep samples and for inflow or cistern samples, except for one
of the sites in which the deep samples had higher TN median values than for the
shallow samples. As shown later with the statistical tests, there were no significant
differences between the shallow and deep sample nutrient concentrations, based on the
number of samples available.
131
-------
Table 6-6. Summary of Sampling Results for Total Nitrogen as N (mg/L) (* Standard solution)
Date
10/20/2010
7/29/2011
8/5/201 1
8/10/2011
8/16/2011
8/17/2011
8/18/2011
8/22/2011
8/25/2011
8/28/2011
Location
79
Inflow
6
1.5
1
1
0.5
1.5
3
79
Cistern
1
2
1
7
1
0.5
3.5
3
135
Shallow
1
1.5
0.5
1
1.5
1.5
1.5
2
2
3.5
135
Deep
2
2.5
1.5
1
1
1.5
4
1.5
1.5
2
18
Shallow
2
0
1
1
3.5
2
2.5
16.5
3
18
Deep
4
3
5.5
1.5
6.5
1
1.5
3.5
2
139
Shallow
0.5
1.5
1.5
0
1.5
4.5
1.5
6.5
1.5
139
Deep
3.5
1
1.5
1.5
0.5
1.5
6
3.5
2
1*
mg/L
1.5
0.5
1
0.5
1
0.5
0.5
1
1
10*
mg/L
10.5
8
9.5
8
9.5
9
9
10
10
Basic Statistics
Number
Average
Min
Max
Median
StDev
COV
7
2.1
0.5
6.0
1.5
1.9
0.9
8
2.4
0.5
7.0
1.5
2.2
0.9
10
1.6
0.5
3.5
1.5
0.8
0.5
10
1.9
1.0
4.0
1.5
0.9
0.5
9
3.5
0.0
16.5
2.0
5.0
1.4
9
3.2
1.0
6.5
3.0
1.9
0.6
9
2.1
0.0
6.5
1.5
2.1
1.0
9
2.3
0.5
6.0
1.5
1.7
0.7
9
0.8
0.5
1.5
1.0
0.4
0.4
9
9.3
8.0
10.5
9.5
0.9
0.1
* These are QA samples at 1 and 10 mg/L as N.
Table 6-7. Summary of Sampling Results for NO3 plus NO2 as N (mg/L)
Date
10/20/2010
7/29/2011
8/5/2011
8/10/2011
8/16/2011
8/17/2011
8/18/2011
8/22/2011
8/25/2011
8/28/2011
Location
79 Inflow
2.5
3.15
Error*
0.8
0.75
0.8
0.6
79
Cistern
0.9
0.8
1.9
0.55
0.45
0.3
0.4
0.7
135 Shallow
0.8
0.9
0.8
1.65
1.5
1.1
0.6
0.6
0.1
0.4
135 Deep
1.1
0.8
0.5
0.85
0.45
0.65
0.45
0.6
0.3
0.4
18 Shallow
0.9
0.8
1.7
0.8
1.55
0.5
0.7
0.6
0.2
18 Deep
1.4
4.7
2.05
0.8
Error
0.7
0.75
1.2
1
139
Shallow
0.8
1
1.95
1.1
Error
0.3
0.45
0.6
0.2
139
Deep
1.1
2
0.5
3.2
0.25
0.65
0.7
0.4
0.5
Basic Statistics
Number
Average
Min
Max
Median
StDev
COV
6
1.43
0.60
3.15
0.8
1.1
0.8
8
0.75
0.30
1.90
0.6
0.5
0.7
10
0.85
0.10
1.65
0.8
0.5
0.6
10
0.61
0.30
1.10
0.6
0.2
0.4
9
0.86
0.20
1.70
0.8
0.5
0.6
8
1.58
0.70
4.70
1.1
1.3
0.8
8
0.80
0.20
1.95
0.7
0.6
0.7
9
1.03
0.25
3.20
0.7
1.0
0.9
132
-------
* The error occurred because the samples were muddy that interfered with the test results.
133
-------
Table 6-8. Summary of Sampling Results for Total Phosphorus as P (mg/L)
Data
Date
10/20/2010
7/29/2011
8/5/2011
8/10/2011
8/16/2011
8/17/2011
8/18/2011
8/22/2011
8/25/2011
8/28/2011
Location
79
Inflow
0.39
0.06
0.02
0.08
0.035
0.19
0.18
79
Cistern
0.05
0.49
0.07
0.14
0.05
0.04
0.52
0.12
135
Shallow
0.235
0.04
0.085
0.215
0.225
0.14
0.05
0.045
0.05
0.11
135
Deep
0.15
0.05
0.075
0.085
0.095
0.115
0.19
0.08
0.08
0.07
18
Shallow
0.09
0.17
0.67
0.12
0.085
0.2
0.12
0.14
0.28
18
Deep
0.35
1.1
1.36
0.105
0.145
0.2
0.205
0.16
0.33
139
Shallow
0.095
0.125
0.465
0.165
0.135
0.12
0.125
0.13
0.22
139
Deep
0.42
0.43
0.125
0.135
0.085
0.1
0.075
0.11
0.11
1*
mg/L
0.335
0.33
0.335
0.34
0.335
0.33
0.335
0.325
0.325
3*
mg/L
0.985
0.975
0.98
0.99
0.975
0.975
0.975
0.98
0.98
Basic Statistics
Number
Average
Min
Max
Median
StDev
COV
7
0.14
0.02
0.39
0.08
0.13
1.0
8
0.19
0.04
0.52
0.10
0.20
1.1
10
0.12
0.04
0.24
0.10
0.08
0.7
10
0.10
0.05
0.19
0.08
0.04
0.4
9
0.21
0.09
0.67
0.14
0.18
0.9
9
0.44
0.11
1.36
0.21
0.46
1.0
9
0.18
0.10
0.47
0.13
0.11
0.7
9
0.18
0.08
0.43
0.11
0.14
0.8
9
0.33
0.33
0.34
0.34
0.01
0.0
9
0.98
0.98
0.99
0.98
0.01
0.0
* Standard solution (P as PO4,
data)
multiply by 3.1 for standard solution concentrations as P, like the other
Chemical Oxygen Demand (COD)
The COD concentration in different locations and for various storm events ranged from
5.0 to 148 mg/L. Also, as shown later, the statistical analyses did not indicate any
significant differences between the shallow and deep samples for any location (or inflow
or cistern samples), for the number of samples available.
134
-------
Table 6-9. Summary of Sampling Results for COD (mg/L)
Date
10/20/2010
7/29/201 1
8/5/201 1
8/10/2011
8/16/2011
8/17/2011
8/18/2011
8/22/201 1
8/25/201 1
8/28/201 1
Location
79
Inflow
50.5
30
19.5
17
26
51
22.5
79
Cistern
11.3
40.5
17
10
5
9
29
15
135
Shallow
23.7
39
38
46.5
73
49
38.5
25
33.5
40
135
Deep
34.5
22
31.5
19
21.5
50
55
39.5
24.5
20.5
18
Shallow
19
20
55
51
62.5
29.5
19.5
55
18.5
18
Deep
9
52
148
29.5
131
36.5
24
75
25
139
Shallow
34
50
39.5
49
45.5
44
36
50.5
36
139
Deep
55.5
51
51
33
27
48
35.5
41.5
45.5
Basic Statistics
Number
Average
Min
Max
Median
StDev
COV
7
30.9
17.0
51.0
26.0
14.2
0.5
8
17.1
5.0
40.5
13.2
11.9
0.7
10
40.6
23.7
73.0
38.8
13.9
0.3
10
31.8
19.0
55.0
28.0
12.8
0.4
9
36.7
18.5
62.5
29.5
18.7
0.5
9
58.8
9.0
147.5
36.5
49.5
0.8
9
42.7
34.0
50.5
44.0
6.5
0.2
9
43.1
27.0
55.5
45.5
9.6
0.2
Metals
Total forms of lead, copper and zinc were analyzed for each sample. The detection
limits for lead, copper, and zinc were 0.005 mg/L, 0.02 mg/L and 0.02 mg/L,
respectively. There were many below detection limit (BDL) values in the results. The
maximum observed concentration for lead was 0.38 mg/L which occurred in a deep
sample under a dry well. The maximum concentration of copper was 1.1 mg/L which
occurred in a cistern influent sample. The concentrations of zinc in all samples ranged
from BDL to 0.14 mg/L for the different storm events. The statistical analyses did not
detect any significant differences between any of the paired heavy metal values, based
on the number of samples available.
135
-------
Table 6-10. Summary of Sampling Results for Lead (mg/L)
Date
10/20/2011
7/29/2011
8/5/2011
8/10/2011
8/16/2011
8/17/2011
8/18/2011
8/22/2011
8/25/2011
8/28/2011
Location
79 Inflow
BDL
BDL
0.005
0.007
BDL
0.007
BDL
79 Cistern
BDL
BDL
BDL
0.089
BDL
BDL
0.005
0.007
135 Shallow
0.013
BDL
BDL
0.014
BDL
BDL
BDL
BDL
BDL
BDL
135 Deep
0.015
BDL
BDL
0.012
BDL
0.027
0.028
BDL
BDL
BDL
18 Shallow
0.031
0.009
0.186
0.011
0.314
0.031
0.025
0.025
0.01
18 Deep
0.058
0.038
0.282
0.038
0.291
0.06
0.029
0.022
0.011
139 Shallow
0.009
BDL
0.012
0.006
0.013
BDL
BDL
BDL
BDL
139 Deep
0.381
BDL
BDL
BDL
BDL
BDL
BDL
BDL
BDL
Basic Statistics
Number
Average
Min
Max
Median
StDev
COV
3
0.0063
BDL
0.007
BDL
0.0011
0.18
3
0.034
BDL
0.089
BDL
0.048
1.4
2
0.014
BDL
0.014
BDL
0.00070
0.052
4
0.021
BDL
0.028
BDL
0.0081
0.40
9
0.071
0.009
0.31
0.025
0.11
1.57
9
0.092
0.011
0.29
0.038
0.11
1.2
4
0.01
BDL
0.013
BDL
0.0032
0.32
1
0.38
BDL
0.38
BDL
NA
NA
Note: Detection Limit = 0.005 mg/L
Table 6-11. Summary of Sampling Results for Copper (mg/L)
Data
10/20/2011
7/29/2011
8/5/201 1
8/10/2011
8/16/2011
8/17/2011
8/18/2011
8/22/2011
8/25/2011
8/28/2011
Location
79 Inflow
0.86
0.82
0.61
0.61
0.51
1.05
0.22
79 Cistern
0.22
0.05
0.12
1.13
0.06
0.16
0.21
0.13
135 Shallow
BDL
BDL
BDL
BDL
BDL
BDL
BDL
BDL
BDL
BDL
135 Deep
BDL
BDL
BDL
BDL
BDL
BDL
BDL
BDL
BDL
BDL
18 Shallow
0.02
BDL
0.03
BDL
0.04
BDL
BDL
BDL
BDL
18 Deep
BDL
BDL
0.06
BDL
0.05
BDL
BDL
BDL
BDL
139 Shallow
BDL
BDL
BDL
BDL
BDL
BDL
BDL
BDL
BDL
139 Deep
0.1
BDL
BDL
BDL
BDL
BDL
BDL
BDL
BDL
Basic Statistics
Number
Average
Min
Max
Median
StDev
COV
7
0.67
0.22
1.05
0.61
0.27
0.40
8
0.26
0.05
1.13
0.14
0.36
1.4
10
NA
NA
NA
NA
NA
NA
10
NA
NA
NA
NA
NA
NA
3
0.03
BDL
0.04
BDL
0.01
0.33
2
0.055
BDL
0.06
BDL
0.0070
0.13
10
NA
NA
NA
NA
NA
NA
1
0.1
BDL
0.1
BDL
NA
NA
136
-------
Note: Detection Limit = 0.02 mg/L
Table 6-12. Summary of Sampling Results for Zinc (mg/L)
Date
10/20/2011
7/29/201 1
8/5/201 1
8/10/2011
8/16/2011
8/17/2011
8/18/2011
8/22/201 1
8/25/201 1
8/28/201 1
Location
79 Inflow
0.14
0.13
0.1
0.08
0.06
0.13
BDL
79
Cistern
0.08
0.03
0.02
0.13
0.02
0.03
0.04
0.02
135
Shallow
0.02
0.14
0.04
0.05
0.06
BDL
BDL
BDL
BDL
BDL
135
Deep
0.03
0.04
0.07
0.05
0.12
0.06
0.03
BDL
BDL
BDL
18
Shallow
BDL*
BDL
0.04
BDL
0.05
BDL
BDL
BDL
BDL
18
Deep
0.03
BDL
0.04
BDL
0.05
BDL
BDL
BDL
BDL
139
Shallow
0.02
BDL
BDL
0.04
0.02
BDL
BDL
BDL
BDL
139
Deep
0.11
BDL
BDL
0.02
BDL
BDL
BDL
BDL
BDL
Basic Statistics
Number
Average
Min
Max
Median
StDev
COV
6
0.11
BDL
0.14
0.12
0.032
0.30
8
0.046
0.02
0.13
0.03
0.039
0.85
5
0.062
BDL
0.14
0.05
0.046
0.74
7
0.057
0.03
0.12
0.05
0.031
0.55
2
0.045
BDL
0.05
BDL
0.0070
0.16
3
0.04
BDL
0.05
BDL
0.01
0.25
3
0.027
BDL
0.04
BDL
0.012
0.43
2
0.065
BDL
0.11
BDL
0.064
0.98
Note: Detection Limit = 0.02 mg/L
* BDL = Below Detection Limit
Herbicides and Pesticides
Table 6-13 shows the results for the pesticide and herbicide analyses for three samples
obtained during the October 20 2011 event. Only these three samples were analyzed
for these analytes due to their costs. None of these constituents were found in the
cistern sample, while alpha and gamma chlordane, endosulfan-l, and heptachlor
epoxide were found in both of the two dry well samples.
137
-------
Table 6-13. Summary of Sampling Results for Herbicides and Pesticides
Herbicides (|jg/L)
Pesticides (|jg/L)
2,4-D
2,4,5-TP (Silvex)
2,4,5-T
Aldrin
Alpha-BHC
beta-BHC
delta-BHC
gamma-BHC
(Lindane)
alpha-Chlordane
gamma-Chlordane
Dieldrin
4,4'-DDD
4,4'-DDE
4,4'-DDT
Endrin
Endosulfan sulfate
Endrin aldehyde
Endrin ketone
Endosulfan-l
Endosulfan-ll
Heptachlor
Heptachlor epoxide
Methoxychlor
Toxaphene
10/20/2010
135
Shallow
ND*
ND
ND
ND
ND
ND
ND
ND
0.03
0.02
ND
ND
ND
ND
ND
ND
ND
ND
0.032
ND
ND
0.03
ND
ND
135
Deep
ND
ND
ND
ND
ND
ND
ND
ND
0.03
0.024
ND
ND
ND
ND
ND
ND
ND
ND
0.034
ND
ND
0.035
ND
ND
Cistern
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND = Not Detected (below detection limits)
Statistical Analyses and Discussion
A number of complementary statistical analyses of the water quality data were
conducted using MINITAB and MS-Excel software:
• Group box plots. These plots compare the ranges of observed concentrations
between different sampling locations. These plots enable a rapid, visual
comparison of data from different sampling locations. If a median value (the
central line in the box) is above or below an adjacent box (the 25th and 75th
percentiles), the data sets are likely significantly different. These plots also
138
-------
indicate the data symmetry and the presence of unusually high or low
concentration values. In many cases, the concentration axis is plotted with a log
scale. These plots can include data from many locations on the same figure for
easy overall comparisons.
• Paired line plots. These exploratory data analysis plots compare paired data
from single sites. The paired concentrations are connected with lines so trends
between the two locations can be readily seen. The goal is to have parallel lines,
or converging lines, indicating consistent differences. If many of the connecting
lines cross with no pattern being obvious, then the sets of data are likely not
correlated.
• Time series plots. These are also exploratory data analyses plots and indicate if
concentrations vary with time. These are most appropriate for relatively long time
periods of data observations, or to observe repeating trends (such as seasonal or
other time series variations).
• Log-normal probability plots. These plots show a single (or few) set(s) of data
on a single plot. The data is ranked and scored for probability. The probability
axis has a distorted, but symmetrical, scale that results in a straight line of the
concentration values if the data are normally distributed. The concentration scale
can be plotted with a log scale to indicate log-normal probability. Two sets of data
plotted on the same figure, especially with a fitted best fit line with confidence
limits, are easy to compare to indicate if they are from the same population.
• Anderson-Darling (AD) p test for normality. This statistical test complements the
probability plots by indicating if the data are significantly different from the fitted
normal distribution. If the calculated AD p test statistic is smaller than 0.05, the
data are significantly different from a normal distribution. If the p-value is larger
than 0.05, insufficient data are available to indicate they are different and the
observed data are usually assumed to be normally distributed (especially if the p-
value is relatively large).
• Mann-Whitney comparison tests. If the data are not normally distributed, then
nonparametric statistical tests are needed, compared to the more commonly
used parametric tests. In this data evaluation, it was desired to compare paired
sets of observations (incoming water vs. cistern water; shallow vs. deep
observation well underdrain water). The Mann-Whitney test is a nonparametric
test for paired data (simultaneous observations from both sampling locations)
that considers the actual observation values (and not just relative values as in the
less powerful Sign Test).
• Paired Sign Test (metals only). This is the simplest nonparametric paired
sample comparison test that can be used if there are many non-detectable
observations, as long as the other observation of the pair is detectable. This test
139
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compares the relatively magnitude of the values only and not the specific values.
For these data, this test was used to examine the heavy metal data as many of
those observations were non-detectable and the Mann-Whitney test could
therefore not be used with these data.
The following sections discuss these analyses and provide some of the output
examples, with the remaining output information presented in Appendix C.
Group Box Plots
Figures 6-3 to 6-8 shows the group box plots for each measured parameter including
bacteria, nutrients, and COD. Too many of the heavy metals results were not detected
and could not be effectively plotted. These plots show the data for all of the sites and
(non-metal) constituents. There are no apparent visual trends between any of the paired
data.
140
-------
Total coliform
40000-
30000-
|
£ 20000-
8
T!
H 10000-
0-
*
1
[
--,
T
-^
J 1
79 Inflow 79 Cistern 135 Sha low 135 Deep 18 Shallow 18 Deep 139 Shallow 139 Deep
E-Coli
9000-
8000-
7000-
6000-
Q. 5000-
| 4000-
" 3000-
2000-
1000-
0-
Inflow 79 Cistern 135 Shallow 135 Deep 18 Shallow 18 Deep 139 Shallow 139 Deep
Figure 6-3. Group Box Plot for Total coliform
Figure 6-4. Group Box Plot for E. coli
Total Nitrogen as N (mg/L)
mg/L)
P 6
79 Infbw 79 Cistern 135 Sha bw 135 Deep 18 Sha bw 18 Deep 139 Shallow 139 Deep
1
79 Infbw 79 Cistern 135Shalbw 135 Deep 18 Shallow 18 Deep 139Shalbw 139 Deep
Figure 6-5. Group Box Plot for Total Nitrogen as
N
Figure 6-6. Group Box Plot for NO3 and NO2 as
N
1.4-
1.2-
f 1.0-
Q.
a 0.8-
?
Total Phosphor
o o o
M 4i 0.
0.0-
|
y
\
—
Total Phosphorus (mg/L)
P i ft t
= Ii
79 Inflow 79 Cistern 135 Shallow 135 Deep 18 Shallow 18 Deep 139 Shallow 139 Deep
COD (mg/L)
160-
140-
120-
100'
8 60-
Inflow 79 Cistern 135 Shallow 135 Deep 18 Shallow 18 Deep 139 Shallow 139 Deep
Figure 6-7. Group Box Plot for Total
Phosphorus as N
Figure 6-8. Group Box Plot for COD
141
-------
Paired Line Plots
Figure 6-9 shows the paired line graphs for shallow vs. deep sampling locations for one
of the dry well sites (135 Tennyson Road, Millburn, NJ 07078). The remaining sets of
plots are shown in Appendix C. As shown on Figure 6-9, the concentration values vary
with no consistent pattern: in some cases shallow samples may have higher bacteria
levels or nutrient levels as well as COD levels, while during other storms, the deep
samples may experience higher values.
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
Total Coliforms
135 Shallow
135 Deep
—*—10/20/2011
—•—7/29/2011
—*—8/5/2011
—W— 8/10/2011
—*—8/16/2011
—•—8/17/2011
—I—8/18/2011
8/22/2011
8/25/2011
—*—8/28/2011
E. coli
135 Shallow
135 Deep
10/20/2011
7/29/2011
8/5/2011
8/10/2011
8/16/2011
8/17/2011
8/18/2011
8/22/2011
8/25/2011
8/28/2011
142
-------
Total Nitrogen as N
•10/20/2011
•7/29/2011
•8/5/2011
•8/10/2011
-8/17/2011
8/18/2011
135 Shallow
135 Deep
8/25/2011
8/28/2011
Figure 6-9 Paired line plots for the site located on 135 Tennyson Road (shallow vs. deep)
0.25
0.15
0.1
a.
T5
NO3 plus NO2 as N
135 Shallow
135 Deep
Total Phosphorus as P
135 Shallow
135 Deep
10/20/2011
7/29/2011
•8/10/2011
•8/22/2011
8/25/2011
8/28/2011
-10/20/2011
-7/29/2011
8/5/2011
8/10/2011
•8/18/2011
•8/22/2011
•8/25/2011
8/28/2011
143
-------
COD
135 Shallow
135 Deep
10/20/2011
•7/29/2011
•8/5/2011
•8/10/2011
•8/16/2011
•8/17/2011
8/18/2011
•8/22/2011
8/25/2011
8/28/2011
Figure 6-9. Paired line plots for the site located on 135 Tennyson Road (shallow vs. deep)
(continued)
Time Series Plots
Figure 6-10 shows time series plots for one of the dry well locations as an example (135
Tennyson Road, Millburn, NJ 07078). The remaining set of time series plots is shown in
Appendix C. These are for relatively short periods (barely more than one month), so
obvious repeating trends are not expected.
135 Shallow
135 Deep
Total Nitrogen as N (mg/L)
— 0
i?/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
Event
Total Nitrogen as N (mg/L)
I
I/I
(B
7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
Event
144
-------
N03 and NO2 as N (mg/L)
7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
Event
N03and NO2 as N {mg/L}
2
1.8
C-1.6
•SB 1.4
.§12
^ 0.8
O 0.6
Z 0.4
0.2
0
7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
Event
Total Phosphorus as P (mg/L)
Total Phosphorus as P (mg/L)
0.25
E 0.2
0.15
0.1
0.25
O
J=
Q.
To
0.05
7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
Event
7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
Event
Figure 6-10 Time series plots for the site located on 135 Tennyson Road (shallow vs. deep)
COD (mg/L)
7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
Event
COD (mg/L)
7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
Event
Figure 6-10 Time series plots for the site located on 135 Tennyson Road (shallow vs.
deep)(continued)
Log-normal Probability Plots and Anderson-Darling Test Statistic
Log-normal probability plots were used to identify range, randomness, and normality of
the data and to determine what type of statistical comparison tests can be used. The
145
-------
Anderson-Darling (AD) statistical test was also conducted as part of these Minitab plots.
In the AD test, the null hypothesis is that data follow a normal distribution (log-normal for
these data as the data are plotted after log transformations). If the p-value is not less
than the chosen level of 0.05, there is insufficient evidence to reject the null hypothesis,
therefore the data fit the normal distribution. On the other hand, if the p-value is less
than the chosen level of 0.05, the hypothesis would be rejected, thus the data do not
follow a normal distribution. In this study, the log-normal probability plots are shown for
inflow vs. cistern, for the cistern and deep vs. shallow for each sampling site. Figure 6-
11 shows example paired log-normal probability plots for one of the sites (135
Tennyson Road, Millburn, NJ 07078) for different parameters including bacteria,
nutrients, and COD. The remaining sets of plots are shown in Appendix C. For these
plots, most of the data are seen to overlap within the limits of the 95% confidence limits,
indicating that the data are likely from the same population. Also, the data seem to
generally fit a straight line, indicating likely log-normal data distributions. The Anderson-
Darling test statistics are used to quantify if the data are log-normally distributed.
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
Total coliform (MPN)
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
E. col (MPN)
Figure 6-11 Log-normal probability plots for the site located on 135 Tennyson Road (shallow vs.
deep
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
:::tmti1]i
5iPi:
mff
Wlfl
r\
0.1 1.0 10.0
Total Nitrogen as N (mg/L)
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
•n
r
•7
0.1 1.0
NO3 - N (mg/L)
146
-------
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
0.01 0.10 1.00
Total Phosphorus as P (mg/L)
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
10 100
COD (mg/L)
Figure 6-11 Log-normal probability plots for the site located on 135 Tennyson Road (shallow vs.
deep)(continued)
Table 6-14 represents a summary of Anderson-Darling p-values for all parameters at all
sampling sites. The highlighted values less than 0.05 represent conditions when the
hypothesis would be rejected (these data do not follow a log-normal distribution). Due to
the presence of many below detection limit (BDL) values for the heavy metal analyses,
it is not possible to fit a log-normal distribution to the metal results.
Table 6-14. Summary of Anderson-Darling p-values.
Location
79 Inflow
79 Cistern
135
Shallow
135 Deep
18 Shallow
18 Deep
139
Shallow
139 Deep
Parameter
Total
coliform
0.047*
0.815
0.245
0.119
0.049
0.013
0.013
0.165
E. coli
<0.005
0.378
0.274
0.103
0.353
0.135
0.09
0.11
Total
Nitrogen as
N
0.567
0.513
0.456
0.236
<0.005
0.213
<0.005
0.589
NOsplus
NO2as
N
0.673
0.202
0.568
0.162
0.482
0.44
0.136
0.003
Total
Phosphorus as
P
0.885
0.157
0.168
0.421
0.253
0.158
0.018
0.011
COD
0.373
0.88
0.401
0.332
0.023
0.771
0.262
0.409
high-lighted conditions indicate data sets that were significantly different from normal distributions
Mann Whitney Test
The Mann-Whitney test, also called the rank sum test, is a nonparametric test that
compares two unpaired groups. Nonparametric tests are preferred when the values are
not normally distributed, or the distribution is unknown or mixed (as in this case). The
147
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Mann Whitney test was performed using MINITAB to test if the shallow samples have
significantly higher or lower concentrations than the deep values (same comparison test
for inflow vs. cistern). This test performs a hypothesis test of the equality of the two
population medians and calculates the corresponding point estimate and confidence
interval. The probability of these two medians being the same (within the confidence
interval) is then calculated. The p-value is used to evaluate the test results: if the
populations really have the same median, what is the chance that random sampling
would result in medians as far apart (or more so) as observed in this set of
observations? If the number of samples is small, the Mann-Whitney test has little power.
In fact, if the total sample size is seven or less, the Mann-Whitney test will always give a
p-value greater than 0.05 no matter how much the groups differ (in this study there are
only seven to ten samples at each location, so a larger critical p-value may be suitable).
However, the p values calculated for these data are all much larger than 0.05, except as
noted.
p-values less than, or equal to, a level of 0.05 are usually used to signify a significant
difference (indicating an error of 1 out of 20 cases). An assumption for the Mann-
Whitney test is that the data are independent random samples from two populations that
have the same shape (distribution). To make sure that the populations have the same
shape, over-laying probability plots were made for the two pairs of data in the previous
probability plots. In all the cases, the straight lines were very close to each other and the
bandwidths were quite similar. Therefore, the distributions can be reasonably assumed
to be the same shape, and the samples from the same population. Table 6-15 shows
the output obtained using MINITAB for comparison between paired data. Except for the
bacteria and COD results for the cistern site, all paired sample sets did not indicate
significant differences for these numbers of samples at the 0.05 level. The cistern
median total coliform values were greater than the inflow median values, indicating
possible re-growth; however, the median E. coli and COD cistern values were less than
the inflow values for these constituents.
Table 6-15.Summary of Mann-Whitney Test for Paired Data
Parameter
Total
Conforms
E. coli
Total
p-value
Significant Difference
Observes?
(at level of 0.05)
p-value
Significant Difference
Observes?
(at level of 0.05)
p-value
79 Inflow vs.
79 Cistern
0.03
Yes (but cistern
median values
were larger than
the inflow median
values)
0.05
Yes (cistern
median values
significantly less
than the inflow
median values)
0.86
135 Shallow vs.
135 Deep
0.40
No
0.60
No
0.50
18 Shallow vs.
18 Deep
0.16
No
0.69
No
0.42
139 Shallow vs.
139 Deep
0.72
No
1
No
0.64
148
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Parameter
Nitrogen as
N
NO3 plus
NO2-N
Total
Phosphorus
as P
COD
Significant Difference
Observes?
(at level of 0.05)
p-value
Significant Difference
Observes?
(at level of 0.05)
p-value
Significant Difference
Observes?
(at level of 0.05)
p-value
Significant Difference
Observes?
(at level of 0.05)
79 Inflow vs.
79 Cistern
No
0.14
No
0.77
No
0.04
Yes (cistern
median values
significantly less
than the inflow
median values)
135 Shallow vs.
135 Deep
No
0.24
No
0.94
No
0.14
No
18 Shallow vs.
18 Deep
No
0.15
No
0.10
No
0.40
No
139 Shallow vs.
139 Deep
No
0.77
No
0.27
No
0.83
No
149
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Paired Sign Test for Metal Analyses
Due to the presence of large numbers of below-detection concentration values for the
metal analyses, a simple paired sign test was used to compare each paired set of data.
In the paired sign test, the null hypothesis is that the population medians are similar. In
each pair of observations, a comparison was made to determine if there is an increase
from the shallow sample to the deep sample or if there was a decrease. The advantage
of the sign test is that if one part of the pair of data is not detected, while the other is, it
is still possible to determine which is larger. However, if both data parts in the pair are
not detected, it is not possible to determine which is larger and that pair is ignored in the
calculations. If the calculated p-value is less than 0.05, then the null hypothesis will be
rejected and the data are assumed to originate from different sample populations. Table
6-16 lists the results for the paired sign test for lead, copper and zinc data from the
cistern and dry well samples. No statistically significant differences are seen between
the sample sets for the heavy metals for the numbers of samples available.
Table 6-16. Summary of Paired Sign Test for Metal analysis
Metal
Lead
Copper
Zinc
p-value
Significant Difference in Medians?
p-value
Significant Difference in Medians?
p-value
Significant Difference in Medians?
79 Inflow
vs.
79 Cistern
>0.06
No
0.13
No
0.45
No
135 Shallow
vs.
135 Deep
>0.06
No
*
*
0.45
No
18 Shallow
vs.
18 Deep
0.18
No
>0.06
No
>0.06
No
139 Shallow
vs.
139 Deep
>0.06
No
*
*
>0.06
No
* All the results are BDL, therefore it is not possible to do a paired sign test
Comparisons of Observed Water Quality to New Jersey Groundwater Disposal
Criteria
Table 6-17 lists the most stringent regulatory levels for groundwater contaminants
derived from N.J.A.C. 7:9C (2010), along with the range of observed concentrations for
each constituent during these tests. Clearly, the microbiological and lead concentrations
frequently exceeded the groundwater criteria.
150
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Table 6-17. Groundwater Quality Criteria for the State of New Jersey Compared to Observed Water
Quality from Dry Wells
Constituent
Microbiological
criteria2
Nitrate and Nitrite
Nitrate
Phosphorus
COD
Lead
Copper
Zinc
2,4-D
2,4,5-TP (Silvex)
2,4,5-T
Aldrin
Alpha-BHC
beta-BHC
delta-BHC
gamma-BHC (Lindane)
alpha-Chlordane
gamma-Chlordane
Dieldrin
4,4 -ODD
4,4 -DDE
4,4 -DDT
Endrin
Endosulfan sulfate
Endrin aldehyde
Endrin ketone
Endosulfan-l
Endosulfan-ll
Heptachlor
Heptachlor epoxide
Methoxychlor
Toxaphene
Groundwater Quality
Criterion1
Standards promulgated in
the Safe Drinking Water
Act Regulations (N.J.A.C.
7:10-1 et seq.)3
10
10
0.005
1.3
2.0
0.07
0.06
0.7
0.00004
0.00002
0.00004
0.00003
0.00003
0.0001
0.0001
0.0001
0.002
0.04
0.04
0.04
0.00005
0.0002
0.04
0.002
Observed Range 1
Total coliform:
1 to 36,294 MPN/lOOmL
f. co//:lto8,469MPN/100
mL
0.0 to 16.5
(one sample had a
concentration of 16.5 mg/L)
0.1 to 4.7
0.02 to 1.36
5.0 to 148
BDLtoO.38
BDLtol.l
BDLtoO.14
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
0.00003
0.00002 to 0.000024
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
0.000032 to 0.000034
Not Detected
Not Detected
0.00003 to 0.000035
Not Detected
Not Detected
Fraction of samples that
exceed the criteria
Total coliform: 63 of 71
samples exceeded the
criterion for total coliforms
E. coir. 45 of 71 samples
exceeded the criterion for
E. coli
lof 71 samples exceeded
the criterion for nitrates
plus nitrites
0
33 of 71 samples exceeded
the criterion for lead
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Groundwater quality criteria and observed range are expressed as milligrams per liter (mg/L) unless
otherwise noted.2 Pursuant to prevailing Safe Drinking Water Act Regulations any positive result for fecal
151
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coliform is in violation of the MCL and is therefore an exceedance of the ground water quality criteria. 350
MPN/100ml_
Summary of Water Quality Observations
Shallow and deep samples beneath three dry wells and samples at the inflow and in the
cistern during ten storm events were analyzed for: total coliforms, E. coll, total nitrogen,
NOsplus N02, total phosphorus, COD, lead, copper, and zinc. Three samples were also
analyzed for pesticides and herbicides. Statistical analyses indicated that the
differences in water quality between the shallow and the deep samples were not
significant (p-values were > 0.05). However, significant differences were found (p< 0.05)
between the quality of inflow samples and cistern samples for total coliforms (possible
re-growth), E. coli, and COD.
These findings indicate that the dry wells did not significantly change any of the water
quality concentrations for the stormwater constituents observed. If the influent water
quality is of good quality, the dry wells can be a safe disposal method for stormwater
quality. However, the bacteria and lead concentrations exceeded the groundwater
disposal criteria for New Jersey and may require treatment, if the aquifer is critical.
152
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Chapter 7 Alternative Stormwater Management Options for
Millburn, New Jersey
Approach for Examining Alternative Stormwater Management Options for
Millburn
The use of the dry wells in Millburn was in response to problems due to increased flows
associated with increasing impervious areas during development and building
expansions. The Millburn dry well regulations were therefore developed to require the
use of dry wells to infiltrate these increased flows by specifying required dry well storage
volumes for new impervious areas. The New Jersey state dry well regulations pertaining
to Stormwater control also include several guidelines, specifically relating to NRCS soil
characteristics (A or B soils needed and associated minimum 5 or 12 mm/hr (0.2 or 0.5
in./hr) infiltration rates) and depth to the seasonal water table or bedrock (at least 2 ft
below the infiltration system) that restrict their use. These regulations also restrict the
source waters for infiltration to be roof runoff only. The 2-year runoff volumes are also to
be used for the calculations. Depending on their applicability and intended use, some
water quality criteria may also apply to the Stormwater management options. Fecal
indicator bacteria are likely of the most concern, while some heavy metals and nutrients
may also be of interest.
When evaluating the Millburn dry wells during this study, most appeared to be operating
well, with rapid infiltration and little standing water. However, several dry wells had
standing water problems, possibly associated with elevated water tables. In addition,
the water quality analyses did not indicate any significant improvement in the water
quality of the runoff water while being discharged through the dry wells. Therefore,
several alternatives were investigated that may offer some benefits for problematic
conditions. Described in this report section include:
• Brief summary of the WinSLAMM model. This tool was used to examine the
Stormwater management alternatives for Millburn, using regionally calibrated
conditions.
• Millburn area rainfall characteristics. Specifically, which rain conditions are
responsible for most of the runoff from the area? Newark International Airport
(located within 10 miles of Millburn) long-term rain information was used for these
analyses for the 1948 through 1999 period.
• Sources of runoff water for Millburn residential land uses. This analysis was
conducted to calculate the likely source contributions from all surface areas in the
153
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land use. Specifically, how does treatment of the roof runoff contribute to overall
stormwater flow reductions? Should other sources areas also be considered for
treatment?
• Dry well design alternatives. Specifically, the use of multiple dry wells, or
shallower dry wells, was examined. The multiple dry wells may be needed in
areas of marginal soils, while the shallower systems may be useful in areas
having high water tables.
• Irrigation beneficial use of roof runoff. This was examined based on the local
rainfall pattern, the regional evapotranspiration rates, and the irrigation limits of
the landscaping plants. Cisterns used by themselves and in conjunction with dry
wells were examined. Some homeowners are currently using cisterns in the area
as a cost-effective alternative to the dry wells, especially considering the very
high summer domestic water bills associated with landscaping irrigation.
• Rain garden use. The performance of rain gardens was examined as a function
of the soil infiltration rates and rain garden size for local conditions. The
advantage of rain gardens is that they are shallower and may not interact with
the high water tables in some areas (although they would still be deep enough to
penetrate through the more restrictive surface soils in this area). In addition, the
media used in the rain gardens would provide some treatment of the infiltrating
stormwater, especially compared to dry wells. As noted previously, lead and
bacteria levels in the infiltrating water in and beneath the monitored dry wells
frequently exceeded the New Jersey groundwater discharge criteria. Both of
these constituents would be much more likely to be significantly reduced through
infiltration using soils and other media, as in rain gardens, instead of the crushed
stone as in the dry wells.
WinSLAMM Background Information
WinSLAMM (Pitt and Voorhees 1995) was developed to evaluate stormwater runoff
volume and pollutant loadings in urban areas using continuous small storm hydrology
relationships, in contrast to single event hydrology methods that have been traditionally
used for much larger drainage design events. WinSLAMM determines the runoff based
on local rain records and calculates runoff volumes and pollutant loadings from each
individual source area within each land use category for each rain. Examples of source
areas include: roofs, streets, small landscaped areas, large landscaped areas,
sidewalks, and parking lots.
WinSLAMM is unique in many aspects. One of the most important aspects is its ability
to consider many stormwater controls (affecting source areas, drainage systems, and
outfalls) together, for a long series of rains. Another is its ability to accurately describe a
drainage area in sufficient detail for water quality investigations, but without requiring a
great deal of superfluous information that field studies have shown to be of little value in
154
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accurately predicting discharge results. WinSLAMM also applies stochastic analysis
procedures to more accurately represent actual uncertainty in model input parameters
in order to better predict the actual range of outfall conditions (especially pollutant
concentrations). However, the main reason WinSLAMM was developed was because of
errors contained in many existing urban runoff models. These errors in calculating
pollutant washoff from streets and runoff volume calculations during small and
intermediate storms were obvious when comparing actual field measurements to the
solutions obtained from algorithms used in other available models.
Stormwater Controls in WinSLAMM and Calculation Processes
WinSLAMM was used to examine a series of stormwater control practices, including dry
wells and water tanks for stormwater irrigation for residential land use conditions
observed in Millburn. The model evaluates the practices through engineering
calculations of the unit processes based on the actual design and size of the controls
specified and determines how effectively these practices remove runoff volume and
pollutants.
WinSLAMM does not use a percent imperviousness or a curve number to general runoff
volume or pollutant loadings. The model applies runoff coefficients to each "source
area" within a land use category. Each source area has a different runoff coefficient
equation based on factors such as: slope, type and condition of surface, soil properties,
etc., and calculates the runoff expected for each rain. The runoff coefficients were
developed using monitoring data from typical examples of each site type under a broad
range of conditions. The runoff coefficients are continuously updated as new research
data become available.
For each rainfall in a data set, WinSLAMM calculates the runoff volume and pollutant
load for each source area. The model then sums the loads from the source areas to
generate a land use or drainage basin subtotal load. The model continues this process
for the entire rain series contained in the range of rains specified in the rain file. It is
important to note that WinSLAMM does not apply a "unit load" to a land use. Each
rainfall produces a unique load from a modeled area based on the specific source areas
in that modeled area. The model replicates the physical processes occurring within the
stormwater control.
The model's output is comprehensive and customizable, and typically includes:
1. Runoff volume, pollutant loadings and event mean concentrations (EMCs) for a
period of record and/or for each event.
2. The above data pre- and post- for each stormwater management practice.
3. Removal by particle size from stormwater management practices applying
particle settling.
4. Other results can be selected related to flow-duration relationships for the study
area, impervious cover model expected biological receiving water conditions, and
life-cycle costs of the controls.
155
-------
A full explanation of the model's capabilities, calibration, functions, and applications can
be found at www.winslamm.com. For this project, the parameter files were calibrated
using regional East Coast MS4 monitoring data as contained in the National Stormwater
Quality Database (NSQD), available at:
http://www.unix.eng.ua.edu/~rpitt/Research/ms4/mainms4.shtml
Regional Rainfall and Runoff Distributions and Sources of Stormwater Discharges
The model can use any length of rainfall record as determined by the user, from single
rainfall events to several decades of rains. The rainfall file used in the calculations for
Newark International Airport (the closest long-term rainfall station to Millburn, at less
than ten miles away) was developed from hourly data obtained from Earthlnfo
CDROMs, using the 51 years from 1948 through 1999, as shown on Figure 7-1. This
period contained 5,401 rains, with an average depth of 11 mm (0.42 in.) and a
maximum depth of 210 mm (8.25 in.). Hurricane Irene monitored during this study
period resulted in more than 9 in. of rainfall, a historical record for the area.
2000
4000
6000
8000 10000 12000 14000 16000 18000 20000
Time (days)
Figure 7-1. Long-Term Rain Depths for Individual Newark, NJ, Rains. (1948 - 1999). (1 in. = 25.4
mm)
Figure 7-2 shows that the regional Stormwater runoff is heavily influenced by the small
to intermediate rains (data for the region shown for Newark, NJ). Almost all of the runoff
is associated with rains between about 7.6 to 76 mm (0.3 to 3 in.), the events for which
WinSLAMM is optimized. The 2-year rain depth for Essex County is about 86 mm (3.4
in.); rains of this event and smaller are responsible for about 90% of the total annual
runoff volumes. This rain depth is the design event for dry wells based on the New
Jersey dry well design criteria. The larger, rare drainage design events generally
contribute a very small portion of the typical year's runoff.
156
-------
10
<0
0)
o
c"
"5
o:
£
"i
•a
1
C
s
5
Q.
100
80 -
60 -
Accumlative
Rain
Count
Accumlatrve
Commercial
Runoff
Quantity
40 -
Accumlative
Residential
Runoff
Quantity
0.01
1
10
Rain (inches)
Figure 7-2. Newark, NJ, Rain and Runoff Distributions. (1982 through 1992 rains). (1 in. = 25.4 mm)
Sources of Runoff from Different Source Areas
WinSLAMM version 10 was used to calculate the relative source contributions of runoff
volume and particulate solids for the typical residential areas in Millburn. Tables 7-3
through 7-5 and Figures 7-3 and 7-4 include the source area contributions for the
Millburn residential stormwater. Table 7-1 shows the areas associated with each
surface, with a few minor source areas not included. Almost all of the impervious areas
are directly connected to the drainage system, with a few flat roofs (sheds), backyard
walkways, and decks and patios draining to pervious areas and are therefore
disconnected.
Table 7-1. Source Areas in Millburn Residential Land Use (average of investigated sites)
Percentage
Area:
Roofs
(directly
connected
pitched)
13.5%
Paved
Parking
(directly
connected)
3.4%
Driveways
(directly
connected)
7.8%
Sidewalks
(directly
connected)
1.7%
Street Areas
(intermediate
texture, 35 ft
wide)
11.8%
Landscaped
Areas (silty
soil)
60.8%
Land
Use
Total
100
1 ft = 0.3048m
157
-------
Table 7-2 summarizes the associated runoff volume contributions for these areas, and
Table 7-3 shows the particulate solids contributions for these areas, using the 1952
through 1999 rain series from the Newark International Airport. The landscaped area is
the largest single land cover, at about 61 %, but only contributes about 12% of the runoff
volume and 24% of the particulate solids contributions over this long time series. The
directly connected roofs are the single largest runoff contributor (at 33%), with the
streets the next most important contributor (at 27%). Driveways contribute a surprisingly
large portion of the runoff (at 18%). Figure 7-3 shows the runoff volume contributions for
different rain depths. This plot indicates the importance of the different source areas as
the rain depth changes. For the smallest rains, the directly connected roofs and the
streets are the most important sources, as typical. However, for the larger rains (greater
than about 51 mm (2 in.)), the landscaped areas contribute about 25% of the total runoff
volume. For stormwater controls only affecting the roofs, the maximum outfall runoff
reduction would therefore be about 33%. If driveways and parking areas could also be
controlled on site, the maximum outfall benefit could increase to about 60%. It is difficult
to reduce street runoff on private property, especially in an area having relatively steep
front yards, as in the Millburn area, and runoff from landscaping areas can only be
reduced by enhancing the soil structure (which may be possible during construction, but
difficult after construction).
Table 7-2. Runoff Volume Sources (%) for Millburn Residential Area (Newark 1952-1999 rain series)
Minimum:
Maximum:
Fl Wt Ave:
Rain
Total
(in.)
0.01
6.8
0.45
Roofs
(directly
connected
pitched)
25.8
74.1
33.1
Paved
Parking
(directly
connected)
6.2
25.9
6.7
Driveways
(directly
connected)
10.4
23.8
17.5
Sidewalks
(directly
connected)
2.3
5.2
3.8
Street Area
(intermediate
texture, 35 ft
wide)
15.8
36.3
26.7
Landscaped
Area (silty
soil)
0.1
25
11.9
Land
Use
Totals
100
100
100
(1 in. = 25.4 mm, 1 ft = 0.3048 m)
158
-------
Large Landscaped Area 1
I Street Area 1
iSidewalks/Walksl
Driveways 1
i Paved Parking/ Storage 1
I Roofs 1
456789
Rain Event Number (see key)
10 11 12
Figure 7-3. Runoff volume source contributions for different rain events for Millburn, NJ (Rain key:
1: 0.01 in., 2: 0.05 in.; 3: 0.1 in.; 4: 0.25 in.; 5: 0.5 in.; 6: 0.75 in.; 7: 1 in.; 8: 1.5 in.; 9: 2 in.; 10: 2.5
in.; 11: 3 in.; 12: 4 in.).
Table 7-3 and Figure 7-4 show similar data for participate solids (TSS). The
contributions from the different areas are different from the runoff volume sources.
Specifically, roof runoff has a much lower TSS concentration than other areas. For this
area, the following source area sheetflow TSS concentrations were typically modeled:
roof runoff <50 mg/L, driveway and street runoff about 100 to 150 mg/L, and
landscaping runoff about 200 mg/L. Therefore, roofs are only expected to contribute
about 11% of the long-term averaged TSS contributions, while the streets, landscaped
areas, and driveways each contribute about 25 to 30%. Figure 7-4 shows that
landscaped areas contribute almost half of the TSS for the largest rains, but contribute
little, until at least 25 mm (1 inch) rains.
Table 7-3. Particulate Solids Sources (%) for Millburn Residential Area (Newark 1952-1999 rain
series)
Minimum:
Maximum:
Fl Wt Ave:
Rain
Total
(in.)
0.01
6.8
0.45
Roofs
(directly
connected
pitched)
6.5
44.8
11
Paved
Parking
(directly
connected)
4.2
55.2
7.8
Driveways
(directly
connected)
7.9
43.2
24.2
Sidewalks
(directly
connected)
0.8
4.6
2.6
Street Area
(intermediate
texture, 35 ft
wide)
4.7
69.7
29.9
Landscaped
Area (silty
soil)
0.1
52.5
24.3
Land
Use
Totals
100
100
100
(1 in. = 25.4 mm, 1 ft = 0.305 m)
159
-------
Large Landscaped Area 1
i Street Area 1
i Sidewalks/ Wa I ks 1
I Driveways 1
i Paved Parking/ Storage 1
i Roofs 1
3456789
Rain Event Number (see key)
10 11 12
Figure 7-4. Particulate solids mass source contributions for different rain events for Millburn, NJ
(Rain key: 1: 0.01 in., 2: 0.05 in.; 3: 0.1 in.; 4: 0.25 in.; 5: 0.5 in.; 6: 0.75 in.; 7: 1 in.; 8: 1.5 in.; 9: 2 in.
10: 2.5 in.; 11: 3 in.; 12: 4 in.).
Dry Well Analyses for Millburn Residential Areas
WinSLAMM version 10 was used to calculate the effects of many dry well options. The
standard units are 1.8 m (6 ft) diameter, 1.8 m (6 ft) deep on top of 0.6 m (2 ft) of
crushed stone and 0.6 m (2 ft) of crushed stone around the sides. This is therefore
equivalent to 2.4 m (8 ft) diameter (5.6 m2 or 51 ft2) area, and 2.3 m (6.9 ft) depth, with
12.9 m3 (350 ft3) of volume storage per unit. Figure 7-5 is a screen shot of the basic
input screen used for the dry wells (a very simplified version of the biofilter control
practice).
160
-------
. Biofiltration Control Device
Mist Source Area Control Practice
Device Properties Biofilter Number 1
Add | Sharp Crested Weir
Add Other Outlet
Top Area (sf)
Bottom Area (sf)
Total Depth (fl)
Typical Width (ft) (Cost est. only)
Native Soil Infiltration Rate (in/hi)
Infil. Rate Fraction-Bottom (0-1)
I nfil. Rate Fraction-Sides (0-1)
Rock Filled Depth (It)
Rock Fill Porosity (0-1)
Engineered Media Type
Engineered Media Infiltration Rate
Engineered Media Depth (ft)
Engineered Media Porosity (0-1)
Inflow Hydrogiaph Peak to Average
Flow Ratio
51
51
7.50
10.00
1.000
N/A
1.00
1.00
000
0.00
0.00
000
0.00
N/A
3.80
Number of Devices in Source Area or ..
Upstream Drainage System
Height ftom datum to
bottom ot weir opening [ft]
Remove | Broad Crested Weir
Weir crest length (ft) 10.00
Weir crest width (ft) 0.25
Height from datum to
bottom ot weir npeninq I I'M
6.90
Add | Vertical Stand Pipe
Pipe diameter (It)
Heiqht above datum (ft) I
Add | Surface Discharge Pipe
Orifice Diameter (ft)
Invert elevation above datum (ft)
Add | D rain T ile/U nderdrain
Orifice Diameter (ft)
Invert elevation above datum (ft)
Add Evapotranspiration
':.nil poroviH' I >aturation
moisture content, 0-1)
Soil field moisture capacity [0-1)
Permanent wilting point [0-1]
Supplemental irrigation used?
Fraction of available capacity
when irrigation starts (0-1)
Fraction of available capacity
when irrigation stops (0-1)
. L'lOfiltei lhaf I-
Plant type
ET CropAdjusirnent Fa
Evaporation Add |
Month
Jan
Feb
Mar
Apr
May
Jun
Jui
Aug
Sep
Oct
Nov
Dec
Evapotrans-
piration
(in/day)
Evaporation
(in/day)
Plant Types
1 2 3
ivateF'ipe or Box Storage C Pipe C Box
Within Biofriter (check if Yes)
Diameter (ft)
Length (ft)
Perforated (check it Yes)
Bottom Elevation (ft above datum)
Discharge Ofifice Diameter (fM
(~~ Generation to Account for
Infiltration Rate Uncertainty
rrr^ Initial Water Surface
|U'UU Elevation (ft)
Select Native Soil
r Sand-8 in/hr
C Loamy sand - 2.5 in/hr
T Sandy loam-1.0 in/hi
<~ Loam • 0.5 in/hr
<~ Silt loam-0.3 in/hr
nfiltration Rate
f~ Clay loam-0.1 in/hr
f Silty clay loam-0.05 in/hr
f Sandy clay-0.05 in/hr
f Silly clay-0.04 in/hr
<" Clay-0.02 in/hr
Change
Geometry
Copy Biofilter
Dala
C Sandy silt loam-0.2 in/hi '"' Rain Barrel/Cistern - 0.00 in/hr
Paste Biofilter
Da!a
Biofilter Geometry Schematic
7.50'
6. SO1
(,«» -|
V
Select Particle
Size File
C:\Program Files (x8S)\WinSLAMM v10\NLIRP.CPZ
Refresh Schematic
Delete
Cancel
Continue
Control Practice 8: 1 LandUsett: 1 SourceAreaB: 1 jTotalArea: O.OBOacres LandUse: Residential 1 SouiceArea: Rood
Figure 7-5. WinSLAMM version 10 screen shot of the biofilter control setup as a dry well.
The analyses examined a range of subsurface soil infiltration rates, ranging from 2.5 to
130 mm/hr (0.1 to 5 in./hr). One, two, and three dry wells per residential lot were also
examined. Figures 7-6 and 7-7 are production function plots showing the annual runoff
volume reductions associated with using 1, 2, or 3 dry wells for the different infiltration
rates. Figure 7-6 is for the roof runoff volume reductions and shows that 90% reductions
in the annual roof runoff is expected to be infiltrated for about 1.5 dry wells per lot (the
typical average for Millburn) whenever the infiltration rate is at least about 7.6 mm/hr
(0.3 in./hr), slightly more than the minimum 5.1 mm/hr (0.2 in./hr) criterion in the state
dry well guidance. The 12 mm/hr (0.5 in./hr) state criterion would result in roof runoff
infiltration of close to 95% of the annual roof runoff. The 11 mm/hr (0.45 in./hr) fc
(constant Morton rate after saturation) observed for the C and D surface soils (well-
drained subsurface conditions) would result in similar annual roof runoff losses. With
two dry wells per lot, the annual roof runoff reductions are about 90% for infiltration
rates as low as 2.5 mm/hr (0.1 in./hr).
161
-------
1 nn ' f ^ ^ * *
on 1
g 90
« on
c SO
" 7n
3 /U „
•o 4
V
r£ fin
01
1 50
_D ^U
yi n
i 40
§ 30
3 30
2 in
3 iU
c
c
0
L
|
>
•
•
T
<
^
F 5
T
T
*% reduc of roof runoff for Idry
well
• % reduc of roof runoff for 2 dry
wells
% reduc of roof runoff for 3 dry
wells
1 1 10
Subsurface Infiltration Rate (in./hr)
Figure 7-6. Roof runoff volume reductions using dry wells in Millburn, NJ. (1 in./hr = 25.4 mm/hr)
Figure 7-7 is a similar plot, but for outfall (total residential area) runoff volume reductions
associated with the roof runoff dry wells. The long-term roof runoff percentage of the
total area runoff is 33% (only 11 % for TSS). Therefore, this plot shows values about
one-third of the roof runoff control plot: The maximum benefit for the whole area would
therefore be limited to about 33% runoff volume control.
162
-------
inn
on
""If an
mO
tl ~7fl
•o
HI
jJJ f:r\
0)
E so
_3 Z)U
^ >in
| 40
= -in r 1
= 30 •
"5
= ?n T
1
m
^
+
.
..
..
* % reduc of site runoff for 1 dry
well
• % reduc of site runoff for 2 dry
wells
% reduc of site runoff for 3 dry
wells
0.1 1 10
Subsurface Infiltration Rate (in./hr)
Figure 7-7. Outfall runoff volume reductions using dry wells for the control of roof runoff in
Millburn, NJ.
(1 in./hr = 25.4 mm/hr)
The expected modeled performance of the dry wells is similar to the observed level of
performance; they function well and completely drain the inflowing water with little
overflow. However, two problems occur: slow drainage times for some dry wells and
standing water in others. Figure 7-8 is a plot of the drainage times needed for dry wells
at 1.8 m (6 ft) and 0.9 m (3 ft) deep. The State dry well criterion of 72 hr for complete
drainage is met for full 1.8 m (6 ft) depth dry wells with at least 2.5 mm/hr (1 in./hr)
infiltration rates. In order to allow this criterion to be met in areas having lower infiltration
rates, it may be necessary to use shallower dry wells. As an example, a 0.9 m (3 ft)
deep dry well full of water would require at least 12 mm/hr (0.5 in./hr) infiltration rates to
meet the 72 hour criterion. As noted above for the long-term continuous simulations,
this drainage time is not needed to ensure good performance by having the dry wells
empty before the next rain. However, aquatic insect pests (mainly mosquitoes) can be a
problem with standing water after several days of quiescent conditions. Luckily, the dry
wells do not reach maximum depth for every rain (unless they were greatly undersized
and filled frequently). Therefore, the maximum drainage time should only infrequently
occur.
163
-------
4
1
T» inn
Drainage Time (hi
i
D '
t
s
S
\
•
"\
%,
\A.
*,
^
N
x
\
—
X
^ ^L
•
^s.
\
•-,
•
S
-*
X
^t
^^
^,
^fe
1L
^^^
x.
X
s
N
x
t
*total drainage time for 6 ft dry
well
• total drainage time for 3 ft dry
well
0.1 1 10
Subsurface Infiltration Rate (in./hr)
Figure 7-8. Drainage times required for full dry wells 6 ft and 3 ft deep for different infiltration
rates. (1 in./hr = 25.4 mm/hr,, 1 ft = 0.3048 m)
If the water table is high and enters the bottom of the dry well, long periods of standing
water may then occur, causing nuisance conditions. The use of multiple shallower dry
wells may therefore be an option to lessen the likelihood of the high seasonal water
table entering the dry well. Fewer hours of standing water will also occur in the
shallower dry well for the probable slower infiltration rates in the low lying areas. Figure
7-9 is a plot comparing the performance of two shallower 0.9 m (3 ft) deep dry wells
compared to a single 1.8 m (6 ft) deep dry well. The total storage volume is the same for
both options, but the shallower dry wells offer greater performance for the same
infiltration rates (especially at low rates). This is due to the shallower dry wells having a
larger infiltration area and an overall faster rate of drainage, resulting in the shallower
dry wells having more usable storage volume for more of the rains compared to the
single deeper dry well.
164
-------
1 nn ~™ ™
•~-* Qn
£
= sn
= BO
'5 70
3 /U
•o
«
tf en
«l
1 50
3 DU
5 40
£ 4°
= on
3 3U
DC
n Tn
3 zu
c
5 in
•
+
1
1
F
i
T
I
* % reduc of roof runoff for one 6
ft deep dry well
• % reduc of roof runoff for two 3
ft deep dry wells
0.1 1 10
Subsurface Infiltration Rate (in./hr)
Figure 7-9. Roof runoff volume reductions using a single 6 ft deep dry well or two 3 ft deep dry
wells. (1 in./hr = 25.4 mm/hr,, 1 ft = 0.3048 m)
Another issue that needs to be considered is the clogging potential of the dry wells.
Figure 7-10 is a plot indicating the time before sediment loads that may cause
significantly decreased infiltration in the dry wells (10 to 25 kg/m2 (2.1 to 5.1 Ib/ft2)
corresponding to about 4 to 10 mm (0.15 to 0.4 in.) sediment depth). As shown, these
sediment loads from the roof runoff may occur in as little as about 4 years to more than
10 years for infiltration rates greater than 6.4 mm/hr (0.25 in./hr). There is substantial
storage in the void space of the crushed stone beneath the dry well (about 250 mm), so
this sediment accumulation may cause lateral flow near the bottom of the stone layer
before fully restricting the infiltration. However, if additional sediment or debris enters
the dry wells (such as from surface flows from eroding areas and even from landscaped
areas during heavy rains), clogging may be responsible for premature reduced
performance.
165
-------
1 fi
1
ii2
$ i2
•o
Sin
_l
E
V o
E 8
^
$ ft
1
in /
CD
2
0
>
•
4
•
I
<
>
|
1
||_
IK
,
<
r
,
<
>•
* years to 10 kg/m2
• years to 25 kg/m2
1 1 10
Subsurface Infiltration Rate(in./hr)
Figure 7-10. Clogging potential of dry wells in Millburn, NJ. (1 in./hr = 25.4 mm/hr)
Stormwater used for Irrigation of Landscaped Areas in Millburn
Millburn, New Jersey Water Use
Population and water use changes with time affect future stormwater management. As
an example, these estimates are both needed when comparing opportunities for
beneficial uses of stormwater in residential areas. In the U.S., information concerning
population and household social-economic conditions is available from the U.S. Census
Bureau by zip code. Millburn, NJ, zip codes and population conditions are shown in
Table 7-4.
Table 7-4. Summary of Census 2000 Information for Millburn, NJ, Zip Codes 07078 and 07041.
(U.S. Census Bureau)
7. _ . _, ... Total Housing Occupied Housing Average Household
Z,pCode Populate Unjts PUnjts Sjze
07078
07041
Total
12,849
6,880
19,729
4,337
2,809
7,146
4,256
2,747
7,003
3.02
2.5
2.81
Domestic water use information is also available from the USGS ("Water use in the
United States," available at: http://water.usgs.gov/watuse/), by county. The water use
values are available for domestic uses and for several dates in recent years. Figure 7-
166
-------
11 is a plot of how these domestic water use values have changed in Essex County
(containing Millburn, NJ), which has ranged between 64 and 84 gal/person/day during
the time from 1985 to 2005, with the most recent rates being the lowest shown.
90 , — , — , — , — , — , — , — , — , — ,
-S 60
s
[50-
S 40
01
o.
T5 30 -
a
20 -
0 4
1980
1985
1990
•^
k^
^*
•*-
1995
Year
2000
2005
2010
Figure 7-11. Essex County NJ daily per capita Water Use.
The Urban Water Budget and Stormwater Reuse in U.S. Residential Areas
It is possible to determine the fraction of the irrigation water and toilet flushing water that
can be supplied by roof runoff. For example, the following lists example inside
household water use (no irrigation):
* bathing 42%
* laundry 11 %
* kitchen sink 15%
* dishwasher 8%
* bath sinks 12%
* toilet flushing 12%
This example household is for a working family with a child in school; the bathing water
use was therefore relatively high, while the toilet flushing water use was relatively low,
as the household residents are away from home much of the day. There were also wide
variations in water use for different days of the week, with weekday water use
(especially toilet flushing and laundry) being substantially less than for weekend water
use. The household water use was relatively constant throughout the year and
averaged about 340 L/c/day, liters per capita per day (90 gal/capita/day, gpcd), ranging
from 290 to 400 L/C/day (77 to 106 gpcd). Outside irrigation water use during the dry
months averaged about 190 Liters per day (50 gal/day), or 200 L/day (for a 0.5 acre
landscaped area) above the inside water uses listed above. Landscape irrigation may
occur for about 2 months at this level of use in this area.
167
-------
Table 7-5 is from a study by Aquacraft, Inc. and the American Water Works Association
Research Foundation for 12 different study sites (1999). The typical household in the
United States uses about 59% of its total water use for outdoor usage and 35% for
indoor usage (leakage and unknown uses make up the remaining 6%).
Table 7-5 Breakdown of residential water usage in the United States (Source:
http://www.aquacraft.com/Publications/resident.htm)
Fixture/End Use Indoor use percent Total use percent
Toilet
Clothes washer
Shower
Faucet
Other domestic
Bath
Dishwasher
Indoor Total
Leak
Unknown
Outdoor
TOTAL
30.9%
25.1%
19.4%
18.2%
2.7%
2.0%
1.7%
100.0%
NA
NA
NA
NA
10.8%
8.7%
6.8%
6.3%
0.9%
0.7%
0.6%
34.8%
5.5%
1.0%
58.7%
100.0%
The following is a summary of the monthly rainfall pattern for Millburn, NJ. The total
rainfall for Millburn is almost 1270 mm (50 in.) (slightly more than the NJ average of
about 1219 mm (48 in.) per year), ranging from about 76 to 130 mm (3 to 5 in.) per
month (most occurring from April thru July).
— Millburn, NJ
— New Jersey
— U.S. (Average of All Locations)
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Figure 7-12. A summary of the monthly rainfall pattern for Millburn Data from:
http://www.usa.com/millburn-ni-weather.htmtfHistoricalPrecipitation (1 in. = 25.4 mm)
168
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The estimated roof runoff for a typical 200 m2(2,000 ft2), 1- % level, house (roof area of
about 120 m2(1300 ft2)) would be about 150 m3 (40,000 gal) per year, for this area
having about 50 in. of rain a year. The total water use for this household could be about
400 m3 (100,000 gal) per year, with the amount used for toilet flushing being about 45
m3 (12,000 gal), with another 10 m3 (3,000 gal) used for landscaping irrigation. For this
example, the roof runoff would supply almost three times the amount of water needed
for toilet flushing and landscape irrigation. None of the other household water uses
would be suitable for supply by roof runoff due to health and safety considerations. The
rainfall varies between about 76 to 130 mm (3 to 5 in.) per month, with a rain occurring
about twice a week on the average. Rains occurring only once every two weeks can
occur during the most unusual conditions (the driest months when landscaping irrigation
is most needed). Therefore, a simple estimate for required roof runoff storage would be
two weeks for average toilet flushing (1.7 m3 or 450 gal), plus two weeks for maximum
landscaping irrigation (3 m3 or 700 gal). A total storage tank of 4.7 m3 (1250 gal) (a
typical septic tank size) would therefore be needed. Of course, a factor-of-safety
multiplier can be applied, depending on the availability of alternative water sources.
For a 0.5 acre residential lot, the annual stormwater generated would be about 650 m3
(170,000 gal) per year. The roof would produce about 25% of this total, pavement would
produce another 25%, and the landscaped area would produce about 50% of this total.
Therefore, the amount of stormwater used on-site for toilet flushing and irrigation of
landscaped areas would be only about 10% of the total generated. Therefore, most of
the runoff would still have to be infiltrated on-site, or safely conveyed and discharged.
Calculating the Benefits of Rainwater Harvesting Systems and Evapotranspiration
Rates
The following discussion presents a method to evaluate or determine the needed size of
water tanks needed to optimize the beneficial uses of stormwater. Irrigation of land on
the homeowner's property was considered the beneficial use of most interest.
Production function curves were prepared for the Millburn, NJ area, showing the
relationship between water tank size and roof runoff beneficial use.
Benefits associated with stormwater use for irrigation and other on-site uses can be
calculated based on site specific information. Specifically, source area characteristics
describing where the flows will originate and how the water will be used, are needed. In
the most direct case, this information is used in conjunction with the local rainfall
information and storage tank sizes to determine how much of the water needs can be
satisfied with the stormwater, and how the stormwater discharges can be reduced. The
following describes how WinSLAMM, the Source Loading and Management Model (Pitt
1997), was used to calculate the production functions that can be used to size storage
water tanks to maximize irrigation use for residential locations in Millburn.
On the average, each person uses approximately 240 Liters (64 gal) of water per day in
New Jersey. A significant amount is used each day to maintain outdoor landscaping.
With a little planning, the amount of water required for landscaping can be significantly
169
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reduced. The amount of water required for landscaping depends on the type and
location of the plants (i.e., lawn, annual flowers, trees and shrubs).
Essex County is near to the New Middlesex Co., NJ and Ringwood, NJ
evapotranspiration reference (ET0) stations. Table 7-6 describes the average ET0 for
these stations per month, with the average values used for these calculations for Essex
County.
Table 7-6 Average ET0 by Month for New Middlesex and Ringwood, New Jersey
January
February
March
April
May
June
July
August
September
October
November
December
New Middlesex County
New Jersey (in. /day)
0.02
0.03
0.09
0.14
0.17
0.17
0.18
0.16
0.14
0.10
0.09
0.04
Ringwood New Jersey
(in. /day)
0.01
0.03
0.12
0.12
0.14
0.14
0.13
0.11
0.10
0.13
0.11
0.05
Average ET0
(in. /day)
0.015
0.03
0.105
0.13
0.155
0.155
0.155
0.135
0.12
0.115
0.10
0.045
(1 in./day = 25.4 mm/day)
Irrigation Water Use
Tables 7-7 and 7-8 and Figures 7-13 and 7-14 are calculated supplemental irrigation
requirements for Millburn residential areas. These areas have roofs that are about 325
m2 (3,500ft2) (13.5% of the land use) and landscaped areas about 1,440 m2 (15,500ft2)
(61 % of the land use), with a relatively large roof to landscaped area ratio of about 0.23
(large homes and small lots). Table 7-7 and Figure 7-13 show the irrigation needs that
can be considered the minimum amount by minimally meeting the area
evapotranspiration requirements (assuming all of the rainfall contributes to soil moisture,
which is true for rains less than about 25 mm (1 inch) in depth, but some of the rain
flows to the storm drainage system for larger rains, as shown earlier, with no crop
adjustment factor). The monthly rainfall compared to the monthly ET is shown in Figure
7-13 and illustrates how supplemental irrigation would be needed in the summer
months, as expected. Table 7-7 shows these calculations, including the monthly
irrigation needs in gal per day per house. This rate would be used for minimally meeting
the ET needs without excessive irrigation. Excessive irrigation water would result in
runoff (if applied at a rate greater than the infiltration rate of the surface soils), and
recharge of the shallow groundwater. For a water conservation program, this irrigation
amount is usually the target. However, for a stormwater management goal, maximum
utilization of the roof runoff is desired.
170
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Table 7-7. Irrigation Needs to Satisfy Evapotranspiration Requirements for Essex County, NJ
Average monthly
rain (in./mo)
Average monthly ET
(in./mo)
deficit for ET needs
(in./mo)
Deficit ET needed
(gal/day/house)
0.36 acres
Jan
3.42
0.47
0.00
0
Feb
3.11
0.85
0.00
0
Mar
4.16
3.26
0.00
0
Apr
3.71
3.90
0.19
63
May
3.99
4.81
0.81
256
Jun
2.88
4.65
1.77
577
Jul
4.21
4.81
0.60
188
Aug
4.04
4.19
0.15
47
Sep
3.61
3.60
0.00
0
Oct
3.06
3.57
0.51
160
Nov
3.70
3.00
0.00
0
Dec
3.47
1.40
0.00
0
Total
Annual
43.37
38.47
4.03
39,200
gal/year
(1 in./mo = 25.4 mm/mo)
13
v
0
I deficit for ET needs (in/mo)
I Average monthly rain (in/mo)
Jan Feb Mar Apr May Jun
Oct Nov Dec
Figure 7-13. Plot of supplemental irrigation needs to match evapotranspiration deficit for Essex
County, NJ. (1 in./mo = 25.4 mm/mo)
For maximum use of the roof runoff, it is desired to irrigate at the highest rate possible,
without causing harm to the plants, or adverse groundwater elevation increases
(mounding). Therefore, Table 7-8 and Figure 7-14 show an alternative corresponding to
a possible maximum use of the roof runoff. For a "healthy" lawn, total water applied
(including rain) is generally about 25 mm (1 in.) of water per week, or 100 mm (4 in.) per
month. Excessive watering is harmful to plants, so indiscriminate over-watering is to be
avoided. Some plants can accommodate additional water. As an example, Kentucky
Bluegrass, the most common lawn plant in the US, needs about 64 mm/week (2.5
in./week), or more, during the heat of the summer, and should receive some moisture
during the winter. Table 7-8 therefore calculates supplemental irrigation for 12 mm (0.5
in.) per week in the dormant season and up to 64 mm/week (2.5 in./week) in the hot
171
-------
months. Natural rains are expected to meet the cold season moisture requirements. The
total irrigation needs for this moisture series is about 1,200 m3 (318,000 gal) per year
per home. This is about eight times the amount needed to "barely" satisfy the ET
requirements noted above. However, the roofs in the study area are only expected to
produce about 340 m3 (90,000 gal) of roof runoff per year, or less than a third of the
Bluegrass "needs" but more than twice the needs for the ET deficit. Therefore, it may be
possible to use runoff from other areas, besides the roofs, for supplemental irrigation.
Table 7-8. Irrigation Needs to Satisfy Heavily Irrigated Lawn for Essex County, NJ
Average monthly
rain (in./mo)
Lawn moisture
needs (in./mo)
Deficit irrigation
need (in./mo)
Deficit irrigation
needed
(gal/day/house)
0.36 acres
Jan
3.42
2.00
0.00
0
Feb
3.11
2.00
0.00
0
Mar
4.16
4.00
0.00
0
Apr
3.71
4.00
0.29
96
May
3.99
8.00
4.01
1263
Jun
2.88
8.00
5.12
1669
Jul
4.21
10.00
5.79
1826
Aug
4.04
10.00
5.96
1880
Sep
3.61
10.00
6.39
2081
Oct
3.06
8.00
4.94
1558
Nov
3.70
4.00
0.30
96
Dec
3.47
2.00
0.00
0
Total
Annual
43.37
72.00
32.80
318,000
gal/year
12.00
10.00
I Deficit irrigation need (in/mo)
I Average monthly rain (in/mo)
2.00
0.00
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Figure 7-14. Plot of supplemental irrigation needs to match heavily watered lawn (0.5 to 2.5
in./week) deficit for Essex County, NJ. (1 in./mo = 25.4 mm/mo)
The following discussions examine the effective use of this water for beneficial irrigation
use and the needed water storage tank (cistern) volumes for Millburn, NJ.
172
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Roof Harvesting and Water Tank Sizes
The monthly infiltration amounts in the landscaped areas, assuming silty soils, were
calculated using continuous WinSLAMM simulations for typical Millburn residential
areas. For the initial calculations, those values were subtracted from the monthly
evapotranspiration (ET) values to obtain the monthly moisture deficits per month, and
the daily deficits per house per day. These were the needed irrigation requirements in
order to meet the ET deficit values compared to the typical rainfall that naturally
infiltrates into the landscaped areas. This would be considered the minimum irrigation
water needed and is a conservative value. As noted above, it is possible to disposal of
excess stormwater to pervious areas with minimal harm to the vegetation (the main
concept applied to the use of bioretention and rain garden facilities).
These minimum monthly irrigation needs were used in the model examining different
storage volumes for water tanks or cisterns. The long term simulations examined the
actual rain series to determine how much water can be stored in the tanks from the roof
runoff and used for irrigation. Small storage volumes result in the tanks not being able to
store significant amounts of the roof runoff (most of the roof runoff would overflow the
tanks) and would be drained quickly after the rain. Large storage volumes would have
excess storage capacity and would seldom overflow, but the irrigation needs may not be
able to use all of the water. There is usually an optimal storage volume that is
associated with maximum amounts of roof runoff use. As noted, in most cases, more
water can be used for irrigation than indicated just by matching the ET deficits, so these
tank sizes and the irrigation needs can be considered the minimum values.
Figure 7-15 is the input screen in WinSLAMM, version 10, used to enter the information
for a continuous analysis for beneficial uses for different water storage tank
characteristics. Figure 7-16 contains plots of the roof runoff reductions vs. roof runoff
storage tank volumes for the Newark rain conditions and for silty soil conditions, the
most common surface soil found in the Millburn study area for storage tank sizes
ranging from very small 0.003 to very large 0.9 m (3 ft) of storage (volumes expressed
as the depth over the roof area (3,500 ft2); a 0.3 m (1 ft) storage volume corresponds to
about 100 m3 (3,500 ft3) of storage for this example, or two large tanks about 3 m (10 ft)
deep and 4.6 m (15 ft) in diameter). The 0.005 ft roof top storage volume corresponds to
a total tank storage volume of about 0.5 m3 (130 gal), or about four typical 35 gallon
rain barrels. As noted previously, the outfall runoff reduction benefits are about one-third
of the direct roof runoff reductions.
173
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Cistern Control Device
F
L
E
irsl Source Area Control Practice Total Area: 0.080 acres
and Use: Residential 1 Cistern No. 1
ource Area: Roof 1
Device Properties Water Use Rate per Cistern
Top Surface Area (sf)
Bottom Surface Area (sf)
Height to Overflow (ft)
Rock Filled Depth (ft)
Rock Fill Porosity (0-1)
Inflow Hydrograph Peak to
Aveiage Flow Ratio
Number of Devices in Source
Area or Land Use
Runoff Fraction Entering
Devices (0-1)
Copy Cistern Data
Paste Cistern Data
HUSH
100.0
10.00
0.00
0.00
3.80
1
1.00
Delete
Month Water Use Rate
^_|__ (gal/day)
January 0.00
February
March
April
May
June
July
August
September
October
November
December
0.00
0.00
63.00
256.00
577.00
187.00
47.00
0.00
160.00
0.00
0.00
Cancel Continue
Control Practice 8 : 1 Land Use 8 : 1 Source Area 8 : 1
Figure 7-15. WinSLAMM, version 10, input screen for water tanks/cisterns.
•+=
u
100
90
80
m
ts.
V
E
I
01
HO
01
a.
•% roof runoff reduction
•% outfall runoff reduction
0
0.001 0.01 0.1 1
Volume of Cistern/Water Tank (ft3 storage per ft2 of roof area)
Figure 7-16. Roof runoff and water tank storage production function for Millburn Township
residential areas (typical silty soil conditions).
174
-------
Similar analyses for sandy soil areas result in lower levels of performance (about 50%
for 0.6 m (2 ft) of storage) compared to the clayey and silty soils (about 60% for 0.6 m or
2 ft of storage) because more of the rainfall falling directly on the sandy landscaped
areas contribute to soil moisture, resulting in less of an irrigation demand to match the
ET deficits. Table 7-9 summarizes the results of these calculations for silty soil
conditions for different areas of the US (Pitt and Talebi 2011). The Central and Great
Lakes areas have the highest potential level of control because the ET demands best
match the rain distributions. The East Coast, Southeast, and Southwest regions all have
moderate levels of control due to poorer matches of ET and rainfall, or greater amounts
of rainfall. The Northwest region has the poorest level of potential control, and large
storage tanks are not likely to be very effective due to small ET-infiltration deficits.
Table 7-9. Roof Runoff Harvesting Benefits for Regional Conditions (Medium Density Residential
Land Uses, silty soil conditions) (Pitt and Talebi 2011)
Region
Central
East Coast
Southeast
Southwest
Northwest
Great Lakes
total roof
area (% of
total
residential
area)
18.1
15.9
8.8
15.4
15.4
15.0
landscaped
area (% or
total
residential
area)
62.5
54.5
81.1
61.2
61.2
57.5
representative
city for rain fall
and ET values
Kansas City,
MO
Newark, NJ
Birmingham, AL
Los Angeles, CA
Seattle, WA
Madison, Wl
study period
annual rain
fall (average
in. per year)
(1995 to
2000)
33.5
53.0
49.8
16.7
41.7
28.7
roof runoff
control (%) for
0.025ft3
storage/ft2
roof area
(about 5 rain
barrels per
1,000 ft2 roof)
40%
24%
34%
35%
16%
46%
roof runoff control
(%) for 0.25 ft3
storage/ft2 roof
area (3 ft high by
6 ft diameter tank
per 1,000 ft2 roof)
78%
33%
41%
44%
16%
68%
roof runoff
control (%) for
1.0 ft3 storage/ft2
roof area (two 6
ft high by 10 ft
diameter tanks
per 1,000 ft2
roof)
90%
42%
42%
48%
19%
72%
(1 ft = 0.305 m, 1 ft" = 0.093 m", 1 ff = 0.028 mj)
The ratios of roof areas to landscaped areas for medium density land uses range from
0.11 to 0.29 (average of 0.25); these ratios for low density land uses range from 0.05 to
0.23 (most at 0.11); while the ratios for strip commercial areas range from 1.8 to 4.0
(most at 2.3). Low density residential area irrigation uses would therefore have a greater
potential benefit compared to the medium density areas, while the strip commercial
areas would have much poorer potential benefits due to the lack of landscaped areas to
irrigate and the relatively large roof areas contributing flows.
Figure 7-17 is a similar plot compared to Figure 7-16 but shows the irrigation needs to
meet the maximum moisture needs of a heavily watered Kentucky Bluegrass lawn. The
runoff reductions are much greater and reach 100% of the roof runoff (and 33% of the
whole area runoff), but only for very large storage volumes.
175
-------
100
•% roof runoff reduction
'% outfall runoff reduction
0.001 0.01 0.1 1
Volume of Cistern/Water Tank (ft3 storage per ft2 of roof area)
Figure 7-17. Water storage tank benefits for supplemental irrigation to meet heavily irrigated lawn
deficits (Millburn, NJ). (1 ft2 = 0.092 m2)
A storage volume of 7.6 cm (0.25 ft, or 6,500 gal or a storage tank about 3 m (10 ft) high
and 3 m (10 ft) in diameter) would therefore result in a roof runoff reduction ranging from
30 to 60%, depending on the irrigation rate actually used (from the minimum ET needs
to the heavily irrigated lawn needs). This is much less than was shown possible by
using the current dry well installations, but also results in significant domestic water
savings.
Use of Cisterns for Irrigation of Roof Runoff in Conjunction with Dry Wells
It may be feasible to use a dry well in conjunction with a water storage tank. The water
tank would be located next to the building and water withdrawn for beneficial irrigation
use. Overflowing water from the storage tank would then be directed to a dry well.
WinSLAMM, version 10, was used to calculate the simultaneous benefits of these
controls operating together at Millburn residential areas. Figure 7-18 is a plot of the
resulting reduction in roof runoff (total area reductions would be about one-third of these
values). Subsurface infiltration rates of 6.4 to 76 mm/hr (0.25 to 3 in./hr) were examined
in conjunction with storage tanks having 2.8 m3(100 ft3) storage (0.03 ft3/ft2 of roof
area), 8.5 m3 (300 ft3) (0.09 ft3/ft2), 1,000 ft3 or 28.32 m3 (0.26 ft3/ft2), and 3,000 ft3 or
84.95 m3 (0.86 ft3/ft2), along with no dry wells or no cisterns.
176
-------
Oft3/ft2
0.03 ft3/ft2
0.09 ft3/ft2
0.29 ft3/ft2
.86ft3/ft2
0.5 1 1.5 2 2.5
Soil Infiltration Rate for Dry Well (in./hr)
Figure 7-18. Production functions for cisterns and dry wells in residential areas, Millburn, NJ.
(1 in./hr = 25.4 mm/hr)
As shown, the use of dry wells is much more effective than cistern use alone. Basically,
maximum beneficial use of the roof runoff for irrigation does not require much storage at
this location due to the closely matched irrigation needs and the rainfall pattern. With
the conservative irrigation pattern (to only match the ET deficit after infiltration of the
rainwater which would prevent any seepage of water to the subsurface), the maximum
roof runoff irrigation use only reduces the study period runoff from from 26,000 m3to
21,000 m3 (930,000 ft3 to 750,000 ft3) (about 20%). However, it is not unreasonable to
over-irrigate the pervious areas for significantly increased runoff reductions as part of a
stormwater management strategy (in contrast to restricting irrigation as part of a water
conservation activity), as noted. The irrigation water applied that is excessive compared
to the ET requirements would contribute to shallow groundwater recharge, typically a
desirable benefit, as shown on this figure.
This analysis is a bit misleading because it implies that dry wells are much more
effective stormwater runoff volume controls. However, dry wells also provide little, if any,
protection to groundwater quality. In contrast, irrigation, and other surface stormwater
applications to pervious areas, can provide significant pollutant reductions by treatment
as it passes through the surface soils (treatment is provided by particulate trapping by
filtration in the soil column and some dissolved pollutant reductions are due to ion
exchange and sorption that can occur in surface soils that have a greater organic
content than the subsurface layers).
177
-------
The use of water storage tanks and irrigation also reduces the amount of sediment
discharged to the dry wells, significantly lengthening the time before critical sediment
loads would occur causing decreased infiltration. The decreased discharges of
sediment to the dry wells are about one-third to one-half with concurrent use of cisterns.
Rain Gardens used in Millburn Residential Areas
A popular stormwater control for roof runoff is the use of rain gardens. These are
relatively small planted areas (usually prairie plants having deep roots, but can be plain
turf grass with almost the same performance) located near buildings that receive runoff
from the roof. They are excavated to several feet deep and refilled with media mixtures,
such as sandy soil, possibly having some organic amendments. The media selection
can be based on water quality treatment objectives. There is a surface impoundment
allowing water to pool for short periods before infiltration. Excess water is allowed to
overflow to the adjacent lawn area. Rain gardens typically do not include underdrains
(which tend to significantly short-circuit the infiltrating water). Rain gardens can be
easily integrated into the landscaping around a home, but do require maintenance.
Figure 7-19 is an input screen for a rain garden in WinSLAMM, version 10. In these
calculations, basic 11 m2(120 ft2) rain gardens excavated to 0.9 m (3 ft) deep and back-
filled 60 cm (2 ft), with a 230 mm (9 inch) surface ponding depth were used. The only
outlet is a surface overflow located on the low end of the rain garden.
178
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B Biofiltration Control Device I"**-*""]
First Source Area Control Practice
Device Properties Biofilter Number 1
Top Area [sf] | 120
Total Depth (ft)
Typical Width (ft) (Cost est only)
Native Soil Infiltration Rate (in/hr)
I nfil. Rate Fraction-Bottom (0-1)
I nfil. Rate Fraction-Sides (0-1)
Rock Filled Depth (ft)
Rock Fill Porosity (0-1)
Engineered Media Type
Engineered Media Infiltration Rate
ste CUV
Engineered Media Porosity (0-1)
Inflow Hydrograph Peak lo Average
Flow Ratio
Number of Devices in Source Area or
Upstream Drainage System
aoo
1000
1 000
1.00
1.00
0.00
0.00
1.00
N/A
200
0.40
3.80
e
I" Activate Pipe or Bon Storage (~ Pipe C Box
Diameter (ft)
Length (ft]
Within Biofilter (check if Yes)
Perforated (check if Yes)
Bottom Elevation (ft above datum)
- [ • I'm etei ltt|
r Select Native Soil Infiltration Ra
C Sand -B in/hr C Claj
f~ Loamy sand - 2.5 in/hr (~ Silty
<~ Sandy loam -1.0 in/hr C Sar
C Loam -0.5 in/hr C Siltj
(~ Silt loam -0.3 in/hr f Claj
f Sandy silt loam - 0.2 in/hr ^" Rai
Select Particle I I C:\Prograrn Files [x
Size File | |
•
•
Add
Sharp Crested Weir Add
Weir Length (ft)
Height from datum to
bottom of we r ooenino fft)
Broad Crested Weir
Weir crest length (ft) 8.00
Weir crest wdth (ft) 0.50
Height from datum to 7 7R
bottom of we [opening (ft)
Add
Vertical Stand Pipe
Pipe diameter (ft) 1
Heiaht above datum (ft)
Add
Surface Discharge Pipe
Orifice Diameter If!
Number of offices in set
Add
Drain Tile/Underdrain
Orifice Diameter (ft)
Invert eleva
t on above datum (ft)
Number of offices in set
Use Random Number
P Generation to Account for
Infiltration Rate Uncertainty
rrr:: 1 nit al Water Surface
|uuu Elevation (It)
loam - 0.1 in/hr
clay loam - 0.05 n/hr
dy clay - 0.05 in/hr
clay - 0.04 in/hr
- 0.02 in/hr
i Barrel/Cistern - 0.00 in/hr
Change
Geometry
Copy Biofilter
Data
Paste Biofilter
Data
36)\WinSLAMM vIOWURP.CPZ
Control Practice S : 1 I Land Use S : 1 Source Area 8: 1
Stage
Number
1
3
4
5
Add
Other Outlet Evaporation Add |
Stage (ft
Uthet Outflow *
Rate (clsj
—1
•»
"•* "iEf E<^T
Jan
Feb
Mar
Apr
May
Evapotranspiration
Soil porosity :.atuat;on
moisture con ent 0-1 )
':.oil fipiH rfior
-------
100
90
o 80
«
at
-------
fin
c,n
= M
1
3!
__ /in
1
E
* an
E 30
TJ
ft
« ?n
,g ^u
ui
h
n
V
*• m
•
4
<
k
t
t
'
4
'
'
* years to 10 kg/m2
• years to 25 kg/m2
0.1 1 10
Subsurface Infiltration Rate (in. /hr)
Figure 7-21. Clogging potential of rain gardens receiving roof runoff, Millburn, NJ (about 7% of the
roof area). (1 in./hr = 25.4 mm/hr)
Summary of Stormwater Management Alternatives for Millburn
Dry wells may be a preferred option in cases that are allowed by the New Jersey dry
well disposal regulations for stormwater which limits their use to areas having excellent
soils (HSG A or B; although subsurface soils where the dry well is located should also
be considered), where the groundwater table is below the dry well system (to prevent
standing water in the dry wells and very slow infiltration), and to only receive roof runoff
water (generally the best quality runoff from a site and the snowmelt from roofs would
not be contaminated with deicing salts). However, irrigation beneficial uses of the roof
runoff should be the preferred option, and in many cases may be less costly, especially
considering increasing water utility rates and the desire to conserve highly treated
domestic water supplies. Shallow groundwater recharge may be an important objective
for an area, but "over" irrigation (beyond the plants ET deficit needs, but less than would
produce direct runoff) would also contribute to that objective, at the same time as
conserving water and offering better groundwater protection.
Reference evapotranspiration for the Millburn area ranges from about 0.04 mm/day
(0.015 in./day) during January to about 4 mm/hr (0.16 in./hr) during May through July.
The period of maximum ET also corresponds to the period of maximum rainfall in the
area, reducing the need for irrigation (and also the sizes of long-term water tanks).
Therefore, the beneficial use of roof runoff for irrigation is limited if it is only to meet the
irrigation demand. However, irrigation can also be used as a stormwater management
option with excess water being used to recharge the shallow groundwater and to meet
181
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the increased moisture needs of some heavily watered lawns (such as common
Kentucky Bluegrass).
Rain gardens are another viable alternative for stormwater management in the Millburn
area, especially as they provide some groundwater quality protection and can be
incorporated into the landscaping plan of the site. They likely require additional
maintenance; similar to any garden, but they can be placed to receive runoff from
several of the sources areas on a site, increasing the overall stormwater management
level. They have even been incorporated along roads, as curb-cut biofilters, resulting in
significant overall runoff volume reductions (but with special care to prevent pre-mature
clogging, reduced salt discharges, and appropriately sized to handle the large flow
volumes).
It is obviously viable to use alternative stormwater options when dry well use should be
restricted, such as with the following conditions:
• poor infiltration capacity of subsurface soil layers
• concerns about premature clogging or other failures due to sediment
discharges or snowmelt discharges to dry wells
• seasonal or permanent high water tables
• concerns about groundwater contamination potential.
182
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Chapter 8 Conclusions and Recommendations
Dry Well Performance Observations
The main purpose of this dry well study was to assist the Township of Millburn in
understanding the effectiveness of the Town Dry Well Ordinance and to determine
whether it should be modified and/or eliminated. The controversy arose due to
complaints by home owners and contractors due to the costs of the dry wells and that
the soil conditions around many of the dry wells prevented them from draining well, with
water remaining in the dry wells several days after a rain event.
A recent tour of the community by members of the project team highlighted that in areas
where the dry wells have been installed, the roof runoff from the properties is
substantially less, or non-existent, compared to sites where no dry wells are installed.
The lawns were greener and there was little or no evident erosion of the top soil. The
sites where the dry wells have not been installed exhibited flooding, extended water
ponding, and erosion of topsoil. The Township has several soil types and the lower
permeability of the clayey soils impacted the ability of the dry wells to drain quickly.
During the site investigations, the following observations were made:
• Dry wells with clay soils drain slowly. The Township has therefore modified the
dry well requirements in areas having clay soils by requiring a deeper trench and
filling it with more gravel. For example, one owner dug a 30 ft deep trench to
capture more runoff at one location.
• On properties without dry wells, the soil is eroded and runoff coming down the
driveways is intense. The water ponded on the lawns.
• There is a substantial savings of water that can be realized with the installation of
cisterns, allowing the beneficial use of the captured water for landscaping
irrigation. Cisterns combined with dry wells offer an effective means to maximize
the effectiveness of stormwater treatment, especially in poorly drained soils.
Infiltration Rates and Drainage Times
Table 8-1 is a summary of the observed site conditions and infiltration characteristics at
some of the monitoring locations. This table shows that there were varying levels of dry
well performance in the area, but most were able to completely drain within a few days.
However, several had extended periods of standing water that may have been
associated with high water tables, poorly draining soils (or partially clogged soils), or
detrimental effects from snowmelt on the clays in the soils.
183
-------
Table 8-1. Summary of Infiltration Conditions at Several of the Test Locations
11
Woodfield
Dr.
15 Marion
Dr.
383
Wyoming
Ave.
258 Main
St.
260
Hartshorn
2
Undercliff
Rd
87/89
Tennyson
7 Fox Hill
% of time
dry well
was dry
89%
71%
81%
98%
10%
(severely
degraded)
79%
0% (severely
degraded)
2% (severely
degraded)
Consistent
shape with
time?
Consistent
shape with
time
Consistent
shape with
time
Consistent
shape with
time
Consistent
shape with
time
Consistent
shape with
time
Consistent
shape with
time
Consistent
shape with
time
Consistent
shape with
time
Standing water
after events?
Quickly drained
(within a day);
No standing
water at anytime
Several days to
drain;
No standing
water at anytime
Several days to
drain if full;
No standing
water at anytime
Very rapid
drainage time;
No standing
water at anytime
Slow drainage
time (about a
week if full), but
dry if given
enough time
between rains
Several days to
drain if full;
No standing
water at anytime
Very slow
drainage time (a
couple of
weeks); standing
water and never
dry
Slow drainage
time (about a
week or two if
full), but dry if
given enough
time between
rains
Other comments
15 hr total drainage
time during hydrant
test
4.5 days total
drainage time during
hydrant test
1 day total drainage
time during hydrant
test
Clogging or poor
soils, not high water
table. Possible SAR
issues in the Winter
and Spring, recovered
by mid-summer.
10 days total drainage
time during hydrant
test
Slow drainage may
be due to saturated
conditions, never
reached stable low
water level. If due to
SAR, did not recover.
Clogging or poor soils
especially in Spring,
possibly SAR issues,
not high water table
Approximate
age of dry
well system
(years)
3 years
n/a
1 year
n/a
1 year
n/a
5 years
2 years
Ratio of
contributing
area to dry
well volume
(ft2/ft3)
5.3
(driveway)
n/a
1.0 (likely
incorrect)
(lawn area)
n/a
5.6
(impervious
areas)
n/a
9.0
(impervious
areas)
10.8 (entire
property)
184
-------
8 So.
Beechcroft
142
Fairfield
36 Farley
Place
% of time
dry well
was dry
71%
66%
97%
Consistent
shape with
time?
Consistent
shape with
time for
rains, but
hydrant test
(at end of
periods at
end of Sept)
was very
rapid
Somewhat
inconsistent
shape with
time
Consistent
shape with
time
Standing water
after events?
Quickly drained
(within a day or
two if full); No
standing water at
anytime
Quickly drained
(within a day or
two if full) to
poorly drained (a
week for
moderate rains);
Standing water
during periods of
large and
frequent rains
Very rapid
drainage time;
No standing
water at anytime
Other comments
3 hr total drainage
time (half full) during
hydrant test
Slowly drained
conditions in Spring
likely due to saturated
conditions, or SAR.
Not likely due to high
water table
Approximate
age of dry
well system
(years)
3 years
n/a
n/a
Ratio of
contributing
area to dry
well volume
(ft2/ft3)
101 (likely
incorrect
source
areas)
(several
properties)
n/a
n/a
Figure 8-1 is a map showing these general conditions for Millburn. Most of the
monitored dry wells were along a ridge between the two main drainages of the
Township, with no obvious pattern of high water conditions, except that the high
standing water dry wells were located along a line to the southwest along the ridge and
are located fairly close to headwaters of streams (high water tables were noted in areas
with nearby streams, but that was assumed to be in the larger stream valleys and not at
the headwaters). The sites that had high standing water long after the events ended had
substantially reduced infiltration rates. In the analyses, these rates were considered to
be the constant (final) rates observed, with no initial rate data or first-order decay Morton
coefficients used (relatively constant, but very low infiltration rates). Three of the sites
shown in Table 8-1 had severely degraded infiltration conditions (260 Hartshorn, 87/89
Tennyson, and 7 Fox Hill). These sites all received runoff from the entire property or
from multiple impervious areas (from 1 to 5 years old). It is not known if the source
water or groundwater conditions affected the drainage conditions at these sites. Dry
wells receiving runoff from all impervious areas would have a greater silt load and likely
clog prematurely compared to sites only receiving roof runoff.
185
-------
ing Avenue
DEM
Value
- High : 588.236
- Low: 81.4229
Sites with all or most events having high water table conditions
Standing water of several inches including seasonal high water table conditions
Completely drained with no high water table conditions
0 0.2 0.4
0.3
1.2 1.6
zz^^^M Miles
Figure 8-1. Township map showing locations having varying standing water conditions in
monitored dry wells.
The infiltration rate characteristics were separated into three conditions:
• A and B surface soils and having well drained HSG A subsurface soils
• C and D surface soils and having well drained A and B subsurface soils
• C and D surface soils and having poorly drained subsurface soils with long-term
standing water
Table 8-2 compares the observed Morton equation coefficients for the well-drained
categories. The standing water data are not shown on this table as most of the
observations could not be successfully fitted to the Morton equation. The almost steady
infiltration rates (but with substantial variation) were all very low for those conditions and
likely represent the fc conditions only and were therefore included in that parameter
category.
186
-------
Table 8-2. Observed and Reported Morton Equation Coefficients
Surface A and B soils well drained A subsurface soils
(average and COV)
Surface C and D soils well drained A and B subsurface
soils (average and COV)
f0 (in./hr)
44.6 (0.53)
4.3 (0.64)
fc (in./hr)
5.6 (0.2)
0.45 (0.85)
k(1/min)
0.06 (0.22)
0.01 (0.63)
(1 in./hr = 25.4 mm/hr)
Even sites having surface C and D soils (not acceptable infiltration sites according to
the New Jersey dry well standards) all had much better subsurface conditions where the
dry wells were located than the surface conditions. The infiltration rates for these
conditions were less than for the excellent areas having A and B surface soils, but all
met the infiltration rate criteria of the state guidelines.
Dry Well Water Quality Observations
Water samples were collected at three dry wells and at one cistern during ten rains. The
samples were analyzed for nutrients and heavy metals, and selected samples were also
tested for pesticides and herbicides. The samples were collected directly below the dry
wells (or at the inlet of the cistern) for comparison to water samples collected at least
0.6 m (2 ft) below the 0.6 m (2 ft) gravel layer beneath the dry wells (and in the cistern),
for a total subsurface flow path of at least 1.2 m (4 ft) through the crushed stone and
subsurface soil. Various statistical tests were used to compare the water quality from
the inlet to the outlet locations to detect any significant differences due to operation of
the dry wells.
Log-normal probability plots were used to identify range, randomness, and normality of
the data and to determine what type of statistical comparison tests can be used. Figure
8-2 shows example paired log-normal probability plots for one of the sites (135
Tennyson Road, Millburn, NJ 07078) for different parameters including bacteria,
nutrients, and COD. For these plots, most of the data are seen to overlap within the
limits of the 95% confidence limits, indicating that the data are likely from the same
population (no significant differences detected based on the number of samples
available).
187
-------
Probability Plot of 135 Shallow, 135 Deep
Lognormal-95%CI
Total coliform (MPN)
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
E. coli (MPN)
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
i-
•—
0.1 1.0 10.0
Total Nitrogen as N (mg/L)
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
I60'
g 50.
» 40.
/'
#/
y/
llTOlMiii
/ // //i
•7
Variable
I— 135 Shallow
IT- 135 Deep
0.1 1.0 10.0
NO3 - N (mg/L)
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
Probability Plot of 135 Shallow, 135 Deep
Lognormal - 95% CI
0.01 0.10 1.00
Total Phosphorus as P (mg/L)
Figure 8-2. Log-normal probability plots for dry well samples located at 135 Tennyson Road
(shallow vs. deep).
The Mann Whitney test was performed using MINITAB to test if the shallow samples
have significantly higher or lower concentrations than the deep values (same
comparison test for inflow vs. cistern).
Table 8-3 shows the Mann Whitney test results for comparison between the paired data.
Except for the bacteria and COD results for the cistern site, all paired sample sets did
not indicate significant differences for these numbers of samples. The cistern median
total coliform values were greater than the inflow median values, indicating possible re-
188
-------
growth; however, the median E. coli and COD cistern values were less than the inflow
values for these constituents.
Table 8-3. Summary of Mann-Whitney Test for Paired Data
Parameter
Total
Coliform
bacteria
E. coli
bacteria
Total
Nitrogen as
N
N03-N as N
Total
Phosphorus
as P
COD
p-value
Significant Difference
Observes?
(at level of 0.05)
p-value
Significant Difference
Observes?
(at level of 0.05)
p-value
Significant Difference
Observes?
(at level of 0.05)
p-value
Significant Difference
Observes?
(at level of 0.05)
p-value
Significant Difference
Observes?
(at level of 0.05)
p-value
Significant Difference
Observes?
(at level of 0.05)
79 Inflow vs.
79 Cistern
0.033
Yes (but cistern
median values
were larger than
the inflow median
values)
0.047
Yes (cistern
median values
significantly less
than the inflow
median values)
0.86
No
0.14
No
0.77
No
0.037
Yes (cistern
median values
significantly less
than the inflow
median values)
135 Shallow
vs.
135 Deep
0.40
No
0.60
No
0.50
No
0.24
No
0.94
No
0.14
No
18 Shallow
vs.
18 Deep
0.16
No
0.69
No
0.42
No
0.15
No
0.10
No
0.40
No
139
Shallow vs.
139 Deep
0.72
No
1
No
0.64
No
0.77
No
0.278
No
0.83
No
Due to a large number of below-detection values for the metal analyses, a simple paired
sign test was used to compare each paired set of data. Table 8-4 lists the results for the
paired sign test for lead, copper and zinc data from the cistern and dry well samples. No
statistically significant differences are seen between the sample sets for the heavy
metals for the numbers of samples available.
189
-------
Table 8-4. Summary of Paired Sign Test for Metals Analyses
Metal
Lead
Copper
Zinc
p-value
Significant Difference in Medians?
p-value
Significant Difference in Medians?
p-value
Significant Difference in Medians?
79 Inflow
vs.
79 Cistern
>0.06
No
0.13
No
0.45
No
135 Shallow
vs.
135 Deep
>0.06
No
*
*
0.45
No
18 Shallow
vs.
18 Deep
0.18
No
>0.06
No
>0.06
No
139 Shallow
vs.
139 Deep
>0.06
No
*
*
>0.06
No
All the results are BDL, therefore it is not possible to do a paired sign test
Comparisons of Observed Water Quality to New Jersey Groundwater Disposal
Criteria
Table 8-5 lists the most stringent regulatory levels for groundwater contaminants
derived from N.J.A.C. 7:9C (2010), along with the range of observed concentrations for
each constituent during these tests. The microbiological and lead concentrations
frequently exceeded the groundwater criteria.
Table 8-5. Groundwater Quality Criteria for the state of New Jersey compared to observed water
quality from dry wells
Constituent
Microbiological
criteria2
Nitrate and Nitrite
Nitrate
Phosphorus
COD
Lead
Copper
Zinc
2,4-D
2,4,5-TP (Silvex)
Groundwater Quality
Criterion1
Standards promulgated in
the Safe Drinking Water
Act Regulations (N.J.A.C.
7:10-1 et seq.)3
10
10
0.005
1.3
2.0
0.07
0.06
Observed Range
Total coliform:
1 to 36,294 MPN/lOOmL
E. co//:lto8,469MPN/100
mL
0.0 to 16.5
(one sample had a
concentration of 16.5 mg/L)
0.1 to 4.7
0.02 to 1.36
5.0 to 148
BDL to 0.38
BDL to 1.1
BDL to 0.14
Not Detected
Not Detected
Fraction of samples that
exceed the criteria
Total coliform: 63 of 71
samples exceeded the
criterion for total coliforms
E. coir. 45 of 71 samples
exceeded the criterion for
E. coli
lof 71 samples exceeded
the criterion for nitrates
plus nitrites
0
n/a
n/a
33 of 71 samples exceeded
the criterion for lead
0
0
0
0
190
-------
Constituent
2,4,5-T
Aldrin
Alpha-BHC
beta-BHC
delta-BHC
gamma-BHC (Lindane)
alpha-Chlordane
gamma-Chlordane
Dieldrin
4,4 -ODD
4,4 -DDE
4,4 -DDT
Endrin
Endosulfan sulfate
Endrin aldehyde
Endrin ketone
Endosulfan-l
Heptachlor
Heptachlor epoxide
Methoxychlor
Toxaphene
Groundwater Quality
Criterion1
0.7
0.00004
0.00002
0.00004
0.00003
0.00003
0.0001
0.0001
0.0001
0.002
0.04
0.04
0.00005
0.0002
0.04
0.002
Observed Range 1
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
0.00003
0.00002 to 0.000024
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
Not Detected
0.000032 to 0.000034
Not Detected
0.00003 to 0.000035
Not Detected
Not Detected
Fraction of samples that
exceed the criteria
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Ground water quality criteria and observed range are expressed as miligrams per liter (mg/L) unless
otherwise noted.
2 Pursuant to prevailing Safe Drinking Water Act Regulations any positive result for fecal coliform is in
violation of the MCL and is therefore an exceedance of the ground water quality criteria.
350MPN/100ml_
Statistical analyses indicated that the differences in water quality between the shallow
and the deep samples were not significant (p-values were > 0.05). However, significant
differences were found (p< 0.05) between the quality of inflow samples and cistern
samples for total coliforms (possible re-growth), E. coli, and COD. These findings
indicate that the dry wells do not significantly change the water quality for most of the
stormwater constituents. If the influent water quality is of good quality, the dry wells can
be a safe disposal method for stormwater quality. However, the bacteria and lead
concentrations exceeded the groundwater disposal criteria for New Jersey and may
require treatment, if the aquifer is critical.
Summary of Alternative Stormwater Management Options for Millburn
Dry wells may be a preferred option in cases that are allowed by the New Jersey dry
well disposal regulations for stormwater which limits their use to areas having excellent
soils (HSG A or B; although subsurface soils where the dry well is located should be the
consideration), where the groundwater table is below the dry well system (to prevent
standing water in the dry wells and very slow infiltration), and to only receive roof runoff
water (generally the best quality runoff from a site and the snowmelt from roofs would
191
-------
not be contaminated with deicing salts). However, irrigation beneficial uses of the roof
runoff should be the preferred option (possibly used in conjunction with the dry wells),
and in many cases may be less costly, especially considering increasing water utility
rates and the desire to conserve highly treated domestic water supplies. Shallow
groundwater recharge may be an important objective for an area, but "over" irrigation
(beyond the plants ET deficit needs, but less than would produce direct runoff) would
also contribute to that objective, at the same time as conserving water and offering
better groundwater protection.
Rain gardens are another viable option for stormwater management in the Millburn
area, especially as they provide some groundwater quality protection and can be
incorporated into the landscaping plan of the site. They likely require additional
maintenance; similar to any garden, but they can be placed to receive runoff from
several of the sources areas on a site, increasing the overall stormwater management
level. They have even been incorporated along roads, as curb-cut biofilters, resulting in
significant overall runoff volume reductions (but with special care to prevent pre-mature
clogging and appropriately sized to handle the large flow volumes.
It is obviously viable to use alternative stormwater options when dry well use should be
restricted, such as with the following conditions:
• poor infiltration capacity of subsurface soil layers
• concerns about premature clogging or other failures due to sediment
discharges or snowmelt discharges to dry wells
• seasonal or permanent high water tables
• concerns about groundwater contamination potential.
192
-------
References
Akan, A. O. Urban Stormwater Hydrology: A Guide to Engineering Calculations. Lancaster.
PA. Technomic Publishing Co., Inc. 1993.
ASCE. ASCE Standardized Reference Evapotranspiration Equation. Edited by R.G.
Allen, I.A. Walter, R.L. Elliott, T.A. Howell, D. Itenfisu, M.E. Jensen, and R.L. Snyder.
ASCE, Reston, VA. 216 pp. 2005.
Bedient, P.B., and Huber, W.C.. Hydrology andFoodplain Analysis. Reading, Massachusetts,
Addison-Wesley Publishing Co., 692 p. 1992.
EPA (U. S. Environmental Protection Agency). Guidelines for Water Reuse.
EPA/625/R04/018, U.S. Environmental Protection Agency, Office of Research and
Development, Center for Environmental Research Information, Cincinnati, Ohio. 2004.
EPA (U.S. Environmental Protection Agency). Recreational Water Quality Criteria.
Office of Water 820-D-11 -002. Dec 9, 2011.
Green,W.H. and G.A.,Ampt. "Studies on Soil Physics: I. Flow of Air and Water through Soils."
Journal of Agricultural Science. 4, 1-24. 1911.
Morton, R.E. An approach toward a physical interpretation of infiltration capacity. So/7
Science Society of America Proceedings 5, 399-417. 1940.
Jensen, M.E., R.D. Burman, and R.G. Allen, eds. Evapotranspiration and Irrigation
Water Requirements. New York. ASCE. 1990.
Kostiakov, A.M. On the dynamics of the coefficient of water percolation in soils and on
the necessity for studying it from a dynamic point of view for purposes of amelioration.
Trans 6, 17-21. 1932.
N. J.A.C. 7:9C. New Jersey Department of Environmental Protection. Water Monitoring and
Standards, Ground Water Quality Standards,
http://www.state.ni.us/dep/wms/bwqsa/docs/niac79C.pdf
MAS (National Academy of Science, Groundwater Recharge Committee). Ground Water
Recharge using Waters of Impaired Quality, National Academy Press, Washington,
D.C. 284 pages. 1994.
New Jersey Department of Environmental Protection. New Jersey Stormwater Best Management
Practices Manual, Chapter 9.3: Standard for Dry Wells, Chapter 9.5: Standard for Infiltration
Basins. February 2004.
NRCS; United States Department of Agriculture; Natural Resources Conservation
Service; http://soils.usda.gov/
Philip, J.R. "The theory of infiltration: 4. Sorptivity and algebraic infiltration equations."
Soil. Sci. 84,257. 1957.
Pitt, R. "Unique Features of the Source Loading and Management Model (SLAMM)." In:
Advances in Modeling the Management of Stormwater Impacts, Volume 6. (Edited by
W. James). Computational Hydraulics International, Guelph, Ontario and Lewis
Publishers/CRC Press, pp. 13-37. 1997.
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Pitt, R., J. Lantrip, R. Harrison, C. Henry, and D. Hue. (1999), Infiltration through
Disturbed Urban Soils and Compost-Amended Soil Effects on Runoff Quality and
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Cincinnati, Ohio. 231 pgs. December 1999.
Pitt, R. "Small storm hydrology and why it is important for the design of stormwater
control practices." In: Advances in Modeling the Management of Stormwater Impacts,
Volume 7. (Edited by W. James). Computational Hydraulics International, Guelph,
Ontario and Lewis Publishers/CRC Press, pp 61 - 91. 1999.
Pitt, R. J. Voorhees, and S. Clark. "Evapotranspiration and related calculations for
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James, E.A. McBean, R.E. Pitt and S.J. Wright). CHI. Guelph, Ontario, pp. 309-340.
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Pitt, R., S.E. Clark, and R. Field. "Groundwater contamination potential from infiltration
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194
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Appendix A. Primary and Follow-up Report Questions
Primary Report Questions
The Township concludes that the use of dry wells on private property where the
increased runoff originates eliminates the cost to the municipal government, while only
slightly increasing the cost to the property owner. Other objectives include the recharge
of the shallow groundwater, increased water conservation, decreased volumes and/or
delaying the delivery the stormwater entering the municipal drainage system, and
decreases of impacts on local streams and rivers. Observations by Township personnel
indicate that this strategy has reduced both flooding and soil erosion within the
Township. Because of the lower municipal costs associated with the implementation of
this approach, Federal, State and local agencies are asking:
• Are the implementation activities working?
• What is the impact of the effectiveness in various soil types?
• Is it more important to address roof runoff, versus other runoff sources such as
driveways and patios, etc.?
In addition to these basic questions, other issues that the Township would like
addressed by this study include:
1. Are there any maintenance requirements needed for the dry wells?
2. What is the life cycle of the dry wells?
3. Do the efficiencies of the dry wells change with time, and are there any
differences in their effectiveness in different soil types over time?
4. What is the impact to long term maintenance requirements for the storm sewers?
5. What are the impacts on the water table and on the local water supply?
6. What is their impact on groundwater quality?
7. Is erosion of the top soil reduced by directing the stormwater runoff to the dry
wells versus letting the stormwater runoff drain across properties?
8. Does directing stormwater runoff to the dry wells filter and improve the quality of
the stormwater?
Answers to these questions (presented below) and more are needed to support the
development of watershed implementation plans, to motivate stormwater control
practice implementation by stakeholders, and to ensure the vitality of the cost share
programs to retrofit properties in areas of extreme soil erosion promoting water
conservation.
1) Are the implementation activities working?
At most of the monitoring locations, the dry wells are draining quickly and
completely after rains (within a day or two for full dry wells). However, some
locations experienced standing water for extended periods and would be
195
-------
considered to not be working as intended. The likely reasons for these failures
are discussed in some of the following question responses. Basically, more
careful site evaluations and design, along with better control of the source waters
entering the dry wells, are needed. In critical situations, alternative stormwater
controls should be considered.
2) What is the impact of the effectiveness in various soil types?
Originally, it was thought that the surface soil characteristics would have little
effect on the performance of the dry wells, as they are subsurface devices and
most of the water is percolating from the dry wells at depth and not near the
surface. At all of the Millburn test locations, the subsurface soils had better
infiltration characteristics compared to the surface soils; in fact, the subsurface
soils were all HSG A or B, which meet the State's dry well design standards,
even though the surface soils were mostly HSG C or D soils. The measured
infiltration rates from all of the dry wells meet the minimum rates specified by the
State's design guidance, but there were substantial variations, as noted below
(average infiltration rates for typical storm durations):
• A and B surface soils and having well-drained HSG A subsurface soils
(190 mm/hror7.6 in./hr)
• C and D surface soils and having well-drained A and B subsurface soils
(43mm/hror 1.7 in./hr)
• C and D surface soils and having poorly-drained subsurface soils with
long-term standing water (20 mm/hr or 0.8 in./hr)
Generally, the lowest infiltration rates associated with long-term saturated
conditions averaged about 12 mm/hr (0.5 in./hr). Again, all of these rates
satisfied the State's design guidance. However, several sites had long-term
standing water and never drained completely, while other locations required
several weeks to drain (and seldom were the dry periods long enough to allow
complete drainage).
Therefore, even though the site conditions met the design guidance, some
locations still had standing water. It is likely that seasonal (or possibly long-term)
high water tables occurred at some of the locations. The lack of site specific
groundwater elevation information did not allow this to be verified, but the
performance of some of the drain-down curves supports this finding.
In other cases, the rates appeared to vary by season, with some incidences of
standing water. These mostly occurred in the spring and sometimes in the winter.
It is thought that soil chemistry changes due to snowmelt waters entering the dry
wells from non-roof areas were responsible for these observations. De-icing
chemicals would likely be heavily applied near home walkways, porches, steps
196
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and driveways (but not roofs!). If this water was allowed to enter the dry wells
and if there was some clay in the surrounding soils, sodium adsorption ratio
(SAR) imbalances would disperse the clays and cause significant reductions in
the infiltration rates. In most cases, excess sodium would be rinsed from soils
over a few months, partially restoring the infiltration conditions. However,
problems would continue to reoccur with subsequent saline snowmelt discharges
to the dry wells.
Therefore, the sites that had sandy surface and subsurface soils (HSG A and B
soils) performed the best. It was thought that the other sites would also perform
well having good subsurface soils, but their characteristics were not likely as
good as the other locations (even in the same soil category), and the likely
presence of small to moderate amounts of clay would be more sensitive to SAR
problems.
3) Is it more important to address roof runoff versus other runoff sources such as
driveways and patios, etc?
Roof runoff contributes about one-third of the average annual runoff for the
Millburn residential areas, a typical value compared to other residential areas in
the US. However, the roof runoff only contributes about 11 % of the TSS. Other
source areas, such as driveways on private property are significant contributors
to runoff. Streets also make up about one-fourth of the runoff. Patios are not very
significant as their runoff is mostly already directly to the landscaped areas where
most of it can infiltrate. After roofs, driveways should be controlled (such as by
using rain gardens near the lower ends of the driveways near the streets, as
many are steeply sloped from the house to the roads). Dry wells for driveways (or
other paved areas besides roofs) should not be considered due to the much
greater sediment load that would likely cause premature failure by clogging.
In addition to these basic questions, other issues that the Township wanted to be
addressed by this study were:
4) Are there any maintenance requirements needed for the dry wells?
It is difficult to maintain the dry wells as they are buried. The bottoms are open
and resting on crushed stone allowing the penetration of silts and clays into the
voids. These materials cannot be easily removed. However, leaves and other
vegetation debris on top of the crushed stone could be removed without
disturbing the rocks. Many of the dry wells have grated openings allowing surface
runoff from the surrounding areas to directly flow into the dry wells. During
construction, erosion sediment may enter the dry wells which would significantly
197
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hinder their performance. As noted, organic matter from the surrounding areas
can also directly enter the dry wells through these surface openings. It is
recommended that only directly connected roof leaders enter the dry wells (in
compliance with the state regulations) and that the dry wells be inspected and
superficially cleaned periodically. Leaf filters should also be installed on the roof
gutters or leaders or capture these material before they are discharged into the
dry well. If needing maintenance to remove the silts and sands from the crushed
stone, all of the crushed stone would have to be removed and replaced, a costly
option similar to totally rebuilding the dry well. Prevention is therefore key to long-
term satisfactory performance.
5) What is the life cycle of the dry wells?
If only receiving roof runoff, the dry wells should function for years (at least five to
ten years, likely much longer). However, if sediment is allowed to enter them,
their life can be shortened considerably. There is little data for older dry wells in
the area, so their full expected life cannot be accurately estimated, although
there is some indications of past failed dry wells that have been replaced since
they have started to be used in the area.
6) Do the efficiencies of the dry wells change with time, and are there any differences
in their effectiveness in different soil types over time?
Again, the short time of use of the Millburn dry wells does not allow any analysis
of their performance with time. The sites investigated during this study did
identify several problems in areas having marginal surface soils and high
standing water. It is not known if these issues changed with time, but more
careful site evaluations and the use of alternative stormwater controls in areas
having questionable conditions would result in better functioning stormwater
management for the Township.
7) What is the impact to long term maintenance requirements for the storm sewers?
The decreases in runoff volumes likely have little effect on the maintenance of
the storm sewers (roof runoff has little sediment, for example). Decreased flows
could reduce the flushing actions in the storm sewers, but this detrimental effect
is not expected to be significant for the storm sewers (maximum 30% reductions
in overall flows associated with complete roof runoff removal, but only a portion
of the roofs in the area are being controlled in the Township). However, slower
rates of increases of runoff with increased development will result in decreased
need for expansion of the storm sewers.
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8) What are the impacts on the water table and on the local water supply?
Increased recharge of the shallow groundwater will result in a rising of the water
table. However, this will be most significant very close to the dry wells and is not
expected to be widespread. If all increased stormwaters in the Township were
infiltrated, then this effect could be widespread. If dry wells were located near
buildings, there is the potential for seepage of water into basements. However,
the dry wells studied were mostly located large distances from the buildings. The
bigger concern is the potential effect of high water tables on the dry wells
themselves, with resulting greatly reduced infiltration capacities.
9) What is their impact on groundwater quality?
Roof runoff has few contaminants and should therefore be the preferred source
of water directed to the dry wells (although bacteria may be a problem, and other
pollutants may periodically be a concern, especially if zinc and copper materials
are used on the roofs). The dry wells had no significant benefit on the quality of
the stormwater, based on the limited sampling conducted during this study. If
other source waters enter the dry wells (such as driveways and streets),
groundwater contamination would be a much greater concern. The best quality
waters in residential areas and most suitable for direct infiltration is roof runoff.
10) Is erosion of the top soil reduced by directing the stormwater runoff to the dry wells
versus letting the stormwater runoff drain across properties?
Complete infiltration of the roof runoff results in about a 30% reduction in the
runoff volume (and flow rate), which results in reductions in energy of the flowing
water and erosion. Concentrated runoff from roof downspouts or outlets near
bare soil near the streets causes erosion of soils. With infiltration, this is
obviously reduced.
11) Does directing stormwater runoff to the dry wells filter and improve the quality of
the stormwater?
No, the dry wells provide no significant water quality benefit. Because the roof
runoff is the least contaminated water in the area, removing this component
actually will cause a small increase in the concentrations of the stormwater
pollutants from the whole area. The mass discharges of the pollutants will
decrease however, and as noted above, there is a possible decrease in erosion
hot spots that would result in decreased TSS levels in the site runoff.
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Follow-up Questions Pertaining to the use of Millburn Township Dry Wells
The following are follow-up questions that were asked during the review of the draft
report. Summary answers follow each question that are based on information obtained
during the research of the Millburn Township dry wells. Some of these questions directly
pertain to the scope of the work of the project and can be answered based on the
project activities, while others are new, follow-up issues associated with the report
conclusions and are beyond the scope of the current project. Some of these questions
also cover the same issues as the above questions.
1) Evaluate the ordinance that was created by the Township of Millburn to
control erosion and flooding.
A discussion of the local ordinance is in Section 4. The local Millburn Township
ordinance should be modified to allow dry well use only in areas already having
good stormwater quality (such as would be expected for most roofs), or require
suitable pretreatment, such as effective grass filtering. In addition, the local
ordinance should also prohibit dry well use in areas having seasonal or
permanent high water tables, as those conditions result in long-term standing
water in the dry wells. If located in areas having poorly draining subsurface soils,
the dry well designs need to be modified (greatly enlarged) to account for the
more slower draining conditions. It is recommended that dry well use be
restricted to roof runoff, and alternatives that infiltrate water through surface soils
(such as rain gardens) be used to treat driveway and parking lot runoff (or in
areas having shallow groundwater). Irrigation of landscaped areas using roof
runoff (and pretreated paved area runoff) is also a suitable option that also
provides economic benefits to the land owner and should be encouraged by the
ordinance.
2) Observe if the existing dry wells are working and whether a long-term maintenance
program is valid.
As noted in Section 5, the dry wells are "working" in that most are capable of
removing significant fractions of the stormwater runoff. However, they are not
working well when one considers the lack of water quality treatment (as
discussed in Section 6), or potential long-term problems due to clogging when
runoff from areas besides roofs is directed to the dry wells. Maintenance will
require replacement of most of the crushed stone in the bottom of the dry wells
and trapped silt. This will be needed frequently in locations where runoff from
eroding areas and most impervious areas is discharged to the dry wells. Periodic
inspection programs can be used to identify dry wells with standing water. These
200
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will need maintenance, unless the standing water is associated with high water
tables.
3) Will the use of the stormwater model, determine the full reduction of
stormwater flow and the impact on local streams and the drainage system?
The WinSLAMM model calibrated for the area was used to examine existing
areas, as described in Section 7, as part of the investigations of alternative
management options. Unless controls are used in existing areas to treat existing
flow sources, there can be no reduction in flows and impacts. With treatment of
flows from newly developed areas, the treated increment will result in less severe
increases in flows.
4) Use actual field data to determine if there are any improvements in water
quality due to the installation of the dry wells.
As discussed in Section 6, there were no observed improvements in water quality
in the stormwater after passing through the dry wells, the gravel blankets, and at
least 2 ft of soil. As noted in that section, overall reductions in flows and flow
energies associated with increased infiltration will decrease channel erosion
rates and pollutant transport compared to conditions with no treatment. However,
since the dry wells are not retrofitted to treat existing flows, there will be no
change in existing channel conditions; the rate of degradation should decrease,
however, if infiltration controls are used to partially infiltrate new flows.
5) Can the existing design of the dry well systems be improved to maximize
their effectiveness, such as in areas where the soil characteristics are poor
should the depth the dry well be increased, or whether cisterns should be
recommended over dry wells or should a system of a combination of
cisterns and dry wells be used?
Dry wells used in areas having marginal soils need to be enlarged to correspond
to the reduced infiltration rates. Areas that discharge to dry wells should be
restricted to roof runoff. Alternatives are discussed in Section 7 and include
cisterns and irrigation beneficial uses, and rain gardens for other impervious
areas. Shallow (but increased surface areas) dry wells can be used in some
areas with shallow groundwaters, but that may be an unreliable option compared
to the others described.
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6) Is it a good idea to recharge the water from the lawn and/or tee driveways? Should
the waterfront these areas be filtered?
These areas should be treated using rain gardens in preference to dry wells, as
discussed in Section 7. Infiltrating the water from impervious areas through
surface soils traps many of the stormwater pollutants to protect the groundwater
and can handle the silt load from these source waters much better than dry wells.
Deeper soils (such as those deep under the dry wells) have much less treatment
abilities and the silts are retained in the voids of the crushed stones, eventually
clogging the dry well bottoms. Rain gardens should be sized to be 5 to 20% of
the impervious drainage area, depending on the soil characteristics.
Pretreatment of the runoff ("filtering") is discussed in Section 4 and is much more
than simple straining of leaves and large debris (though that should be
worthwhile). Removal of silts requires substantial pretreatment to preserve dry
well performance and to protect groundwater quality.
7) Should the inlet of the dry wells have some type of filtering system to
increase the longevity of the dry wells or cisterns?
See #6 above. Section 4 discusses pretreatment methods for cistern use.
Removal of leaves and other material will be needed and only roof runoff should
be directed to the storage cisterns. Any pretreatment, including the removal of
leaves and other debris, will increase the longevity of the dry wells.
8) Should the roof drainage be separated from the other runoff?
Definitely, as discussed in Section 4, roof runoff has the least contaminants that
will clog dry wells and cause potential groundwater contamination. The NJ State
groundwater disposal regulations restrict the flows to dry wells to only roof runoff.
The local ordinance needs to be made in compliance with the state regulations.
The other site flows should be treated with rain gardens or reused through
storage in cisterns.
9) Are there other alternative designs that could be considered?
This has been addressed previously (enlarge for poor soils, shallower for shallow
groundwaters, only roof runoff).
10) How would you recommend the ordinance be modified?
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This has been addressed previously (only roof runoff to dry wells, encourage
beneficial uses for irrigation and rain gardens for other site area infiltration).
11) Are there any seasonal variations that could be used to maximize the operations of
the dry wells?
No snowmelt should be allowed to enter dry wells if contaminated with deicing
materials (another reason to prohibit driveway and other impervious area runoff
from being discharged to infiltration areas).
12) Are there any proposed changes in the type of vegetation that would improve
stormwater retention ?
This was not directly addressed in this report, as vegetation is not a component
of dry wells. Vegetation issues were discussed in relation to evapotranspiration
(ET) in Section 7 and in Appendix D of the report. Plants requiring large amounts
of water can be encouraged in order to better utilize the runoff from sites in order
to keep the cistern tanks smaller. They should also be able to withstand periods
of no irrigation. For use in areas of increased infiltration (such as in rain gardens),
local agencies usually have a plant list that works well for stormwater
management (usually native plants with deep roots). However, regular sod can
also be used in rain gardens with substantial benefits, usually requiring less
specialized landscaping maintenance.
13) With the average reconstruction of homes estimated between 1.5 to 2
percent for the next ten years, what are the anticipated reductions in
stormwater runoff and the anticipated improvement in water quality?
Unfortunately, unless all of the additional runoff associated with the new
developments is infiltrated to match natural conditions, there will be an increase
in runoff and a decrease in water quality. Only retrofitted infiltration and other
stormwater controls in existing developed areas can decrease current levels of
degradation. However, if one compares future development conditions with and
without runoff controls, then enhanced infiltration can have significant benefits
compared to future conditions without controls, but there would still be
degradation compared to current conditions. Section 7 shows that the current
Millburn residential landscaped areas are the largest single land cover, at about
61 %, but only contribute about 12% of the runoff volume and 24% of the
particulate solids contributions over a long time series. The directly connected
roofs are the single largest runoff contributor (at 33%), with the streets the next
most important contributor (at 27%). Driveways contribute a surprisingly large
203
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portion of the runoff (at 18%). For stormwater controls only affecting the roofs,
the maximum outfall runoff reduction would therefore be about 33%. If driveways
and parking areas could also be controlled on site, the maximum outfall benefit
could increase to about 60%. It is difficult to reduce street runoff on private
property, especially in an area having relatively steep front yards, as in the
Millburn area, and runoff from landscaping areas can only be reduced by
enhancing the soil structure (which may be possible during construction, but
difficult after construction).
14) What is the cost comparison to treating stormwater with dry wells versus a large
municipal project?
Comparative cost analyses were not within the scope of this project. Local dry
well costs are reported in Section 2 (about $4,000 per dry well). Section 7 also
discusses irrigation use cost savings. Large municipal projects for stormwater
management can include the components of the drainage infrastructure and
regional stormwater controls. The incremental costs associated with larger
drainage systems if no on-site infiltration controls are used may not be as
important as the costs associated with increased flooding damage in low lying
areas. The dry wells (and other on-site controls) are more effective for small and
intermediate sized rain events, with some benefits for the large drainage events.
The EPA has numerous reports describing direct and indirect stormwater
management costs and benefits, especially the supporting information included
in the Federal Register for new stormwater regulations.
15) What are the potential savings in water consumption with the use of cisterns and
what would be the average savings to the resident in annual water bills versus the
added costs of a cistern system over dry well system?
As noted above, detailed cost and benefit analyses were not part of this project.
However, Section 7 discusses some of the economic features of cistern storage
and beneficial uses of stormwater. Some of the homes in Millburn have very
large water utility charges during the summer for landscaping irrigation
(approaching $1,000 per month). The large cistern and irrigation systems used
for these large homes are costly (about $25,000 to $50,000), but there is a
significant positive payback after several years. In areas where the water costs
and the water needs are less, the payback may not be as rapid.
16) Are there any draw backs in raising the water table by installing the dry wells?
204
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Raising the water table has mixed effects in an area. In many urban locations,
the water tables are depressed compared to natural conditions due to increased
runoff of rainfall and decreased infiltration. Dry wells (and other infiltration
practices) may raise the water table in an area, but the effects are usually
localized. Some concerns are expressed due to increased basement flooding if
infiltration occurs near buildings. In areas of existing high water tables, the
performance of infiltration devices may be hindered. Saturated flow conditions
are orders of magnitude less than typical infiltration rates and dramatically
decrease the performance of dry wells if mounding intersects the infiltration zone
under the dry wells. Groundwater mounding below infiltration devices should
therefore be evaluated for an area, but is seldom an issue for relatively deep
water tables (about 10 ft or more). Regional water table elevation increases can
occur over an area if stormwater infiltration is widespread. Again, problems would
occur in areas currently experiencing shallow groundwaters. Infiltration should
not be encouraged in areas of shallow groundwaters. Most regulations prohibit
infiltration unless the water table is at least 3 ft below the bottom of the infiltration
device.
17) What are the economic benefits in reducing the amount of flooding and erosion
after the installation of the dry wells? Did the model show the improvements?
The evaluation of regional flooding and erosion economic issues was beyond the
scope of this project. Section 7 examined alternative stormwater management
options on-site and for the region, but cost estimates are not provided.
18) How can the model be used as a tool for Millburn and the surrounding
communities as a model in mature urban settings to treat stormwater?
WinSLAMM was calibrated for the eastern US based on municipal NPDES
information as provided in the National Stormwater Quality Database. Site-
specific development conditions for Millburn were obtained from Township data
sources, aerial photographs, and maps. The model was used to calculate the
benefits and limitations of many different stormwater management options. The
calibrated model and associated files also can be used in surrounding
communities to evaluate many stormwater options. The evaluation of the Millburn
dry wells is also expected to be applicable to the surrounding areas, but site-
specific soils, groundwater conditions, development characteristics, and
topographic conditions need to be considered.
In order to most accurately design dry well installations in an area, actual site
observations of the expected infiltration rates should be used instead of general
literature values. This is especially true for surface infiltration devices (such as rain
gardens), where compaction will have a much greater effect than on the deeper
subsurface soils. Also, all of the sites in this study had improved infiltration
205
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characteristics with depth compared to expected surface conditions; in other cases, this
may not be true. Criteria based only on surface soil conditions are likely not good
predictors of deeper dry well performance. Luckily, county soil surveys do have some
subsurface soil information that was found to be generally accurate during this study.
Unfortunately, shallow water table conditions are not well known for the Millburn area
and that characteristic can have a significant detrimental effect on dry well performance.
206
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Appendix B. Descriptions of Millburn, NJ, Study Sites
Plans and Topographic Maps
This appendix contains several example site plans showing the residential area
development characteristics and dry well calculations.
207
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Figure B-1. 43 Browning Road S.H
208
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HOBS!!
/ 201.W I SINCLAIR TERRACE
•**••?*- ' —I • i"*"* •
RESTING CONDITIONS PLAN
GRAPHIC SCALE
Figure B-2. 1 Sinclair Terrace
209
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x,ffl -*fr'- *9»1
. - -;?•* dVf-n&r
-T *^: ^ "- ' .'Mfuu.!!^
I.
•L
CHESTNllT
STREET
Figure B-3. 90 Chestnut St
(SOWIDCItO.W)
•
••«. ' .'
- L>«KU (
210
-------
Figure B-4. 8 South Beechcroft
211
-------
Figure B-5. 11 Fox Hill Lane
212
-------
Figure B-6. 9 Lancer
213
-------
Figure B-7. 139 Parsonage Hill Rd
214
-------
Figure B-8. 79 Minnisink Rd
215
-------
x'"V'"
1
1
1
1
*r . I
/-s
II
1
TENNYSON DRIVE
Figure B-9. 135 Tennyson Drive
216
-------
Figure B-10. 18 Slope Drive
217
-------
»>••-:.<•
. '••>.*•,
•* • • /,
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OR
DRY Wfll
,,s - - ,> ! ,, i.r'E, ™r™ ™«
.'_ ^^y^Kir-,-,-!:^
Figure B-1 1 . Details of dry well - 79 Minnisink Rd
218
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4* SOWS 40
ROOF UEADEBS
•J/4" ft* TOO
2\" CROWED STONE
Alt AROUND
FILTER FABRIC
BOTTOM * SIDES
OF EXCAVATION
SE£PAGE_Pl.L—___
N.T.S.
944 X,?S=236 SO FT
T CALCOLADQKS
Px If X3 *84 78 F1T
+ 0*-5*XfTX3) -84 78 FT JO 4 = W FT J
«EO W» 3' DRY mi TANKS
« Ol€ 6' DEEP TANK
NEW ROOFED AREA
456 SF
NEW LOT COVERAGE
488 SF
TOTAL LAND DISTURBED
944 SF 10TAI
Figure B-12. Details of dry well - 135 Tennyson Drive
219
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STOW t*» C
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DRYWELL DESIGN
Figure B-13. Dry well (18 Slope Drive)
Appendix C. Soils and Infiltration Measurements at Millburn Dry
Well Study Locations
220
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Rain Gage Data and Analysis
R1: Mel Singer's house on top of chimney slab at 1 Delwick Ln - Calibrated and
launched at 14:00 on 5/22/09 by HDB
Start time
10/23/2009
10/27/2009
12/9/2009
12/13/2009
19:01
5:40
0:03
10:39
End time
10/24/2009
10/28/2009
12/9/2009
12/13/2009
20:34
14:04
11:38
18:38
Duration
(hr)
25:33
32:24
11:35
7:59
Depth
(in.)
2.20
1.60
2.01
0.99
Average
intensity
(in./hr)
0.09
0.05
0.17
0.12
2.5
1.5
0.5
0
Rl: 1 Delwick Ln (10/23/2009-10/24/2009)
14:24 19:12 0:00 4:48 9:36 14:24 19:12
Time
221
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Rl: 1 DelwickLn (10/27/2009-10/28/2009)
0:00 4:48 9:36 14:24 19:12 0:00 4:48 9:36 14:24
Time
Rl: 1 DelwickLn (12/9/2009)
14.5
21:36 0:00 2:24 4:48 7:12 9:36 12:00 14:24
11.5
Rl: 1 DelwickLn (12/13/2009)
13.8
9:36 10:48 12:00 13:12 14:24 15:36 16:48 18:00 19:12
Time
222
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R2: Roof of Township's maintenance garage on Essex Rd - Calibrated and launched at
12:00 on 5/13/09 by HDB
Start time
7/26/2009
7/29/2009
8/2/2009
8/21/2009
6/16/2010
6/22/2010
7/14/2010
8/1/2010
7/8/2011
8/1/2011
8/3/2011
16:46
10:00
6:29
23:54
23:45
18:33
9:02
8:21
16:02
0:25
16:28
End time
7/26/2009
7/29/2009
8/2/2009
8/22/2009
6/17/2010
6/22/2010
7/14/2010
8/1/2010
7/8/2011
8/1/2011
8/4/2011
23:22
19:13
12:55
10:43
0:41
18:54
10:04
9:54
20:46
0:42
4:02
Duration
(hr)
6:36
9:13
6:26
10:49
0:56
0:21
1:02
1:33
4:44
0:17
11:34
Depth
(in.)
1.37
1.33
1.31
1.90
0.69
0.37
1.22
1.34
0.73
0.46
0.65
Average
intensity
(in./hr)
0.21
0.14
0.20
0.18
0.74
1.06
1.18
0.86
0.15
1.62
0.06
1.6
1.4
^f 0.8
S" 0.6
O
0.4
0.2
0
15
1.4
1.2
=• 0.8
Q. 0.6
V
0 0.4
0.2
0
8:
R2: 345
Essex St (7/26/2009)
^ *j+.dP
40 4P^
{4
36 16:48 18:00
R2: 345
9
19:12 20:24 21:36 22:48 0:00
Time (date, time)
Essex St (7/29/2009)
«* ^f^
f+
* *P
24 9:36 10:48 12:00
^ V
f
1
1
/
13:12 14:24 15:36 16:48 18:00 19:12 20:24
Time
223
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R2: 345 Essex St (8/2/2009)
1.4
1.2
0.4
0.2
0
6:00
7:12 8:24 9:36 10:48 12:00 13:12 14:24
Time
R2: 345 Essex St (8/21/2009 - 8/22/2009)
1.6
-, 1'4
= 1.2
f
5> 0.8
0.6
0.4
0.2
0
21:36 0:00 2:24
4:48
Time
7:12 9:36 12:00
0.7
0.6
0.5
£
o
0.2
0.1
R2: 345 Essex St (6/16/2010 - 6/17/2010)
0
23:38 23:45 23:52 0:00 0:07 0:14 0:21 0:28 0:36 0:43
Time
224
-------
R2: 345 Essex St (6/22/2010)
0.4
0.35
0.3
"2 0.25
£ 0.2
| 0.15
0.1
0.05
0
18:31 18:34 18:37 18:40 18:43 18:46 18:48 18:51 18:54 18:57
Time
8:52
R2: 345 Essex St (7/14/2010)
10:04
10:19
f
u
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
8:09
R2: 345 Essex St (8/1/2010)
8:24
9:50
10:04
225
-------
R2: (7/8/2011)
0.1
0
15:36 16:48 18:00 19:12
Time
20:24
21:36
R2: (8/1/2011)
0:23 0:25 0:28 0:31 0:34 0:37
Time
0:40
0.7
0.6
0.5
I 0.4
0.3
0.2
0.1
0
14:24
R2: (8/3/2011)
16:48
2:24
4:48
226
-------
R3: Municipal Par 3 Golf Course on White Oak Ridge Rd - Calibrated and launched
at 16:00 on 5/13/09 by HDB
Start time
8/16/2010
8/22/2010
8/25/2010
9/13/2010
9/16/2010
9/27/2010
9/30/2010
10/1/2010
10/11/2010
11/4/2010
12/1/2010
12/12/2010
2/25/2011
2/28/2011
3/6/2011
3/10/2011
5/23/2011
5/30/2011
6/11/2011
6/17/2011
7/3/2011
16:24
12:41
2:00
17:00
15:55
7:40
4:14
1:41
18:29
3:26
1:05
0:57
0:25
3:50
7:55
2:47
22:19
6:07
1:26
13:45
4:46
End time
8/16/2010
8/22/2010
8/25/2010
9/13/2010
9/16/2010
9/28/2010
9/30/2010
10/1/2010
10/11/2010
11/5/2010
12/1/2010
12/13/2010
2/25/2011
2/28/2011
3/7/2011
3/11/2011
5/23/2011
5/30/2011
6/11/2011
6/17/2011
7/3/2011
20:53
20:42
10:21
17:58
22:14
12:36
10:01
13:05
23:57
7:35
15:07
6:51
18:44
11:30
3:29
8:05
23:17
6:41
5:29
18:22
21:23
Duration
(hr)
4:29
8:01
8:21
0:58
6:19
28:56
5:47
11:24
5:28
28:09
14:02
29:54
18:19
7:40
19:34
29:18
0:58
0:34
4:03
4:37
16:37
Depth
(in.)
0.26
1.53
0.43
0.51
0.61
0.69
1.83
2.53
0.71
1.16
1.88
1.87
1.36
0.49
2.78
2.90
0.68
0.27
0.56
2.78
0.33
Average
intensity
(in./hr)
0.06
0.19
0.05
0.53
0.10
0.02
0.32
0.22
0.13
0.04
0.13
0.06
0.06
0.06
0.14
0.10
0.70
0.48
0.14
0.62
0.02
0.3
0.25
-;. 0.2
_c
£ 0.15
a.
V
Q 0.1
0.05
0
15
R3: : 335 White Oak Ridge Rd (8/16/2010)
* +
^
1
A *
I
/
36 16:48 18:00 19:12 20:24 21:36
Time
227
-------
R3:: 335 White Oak Ridge Rd (8/22/2010)
12:00 13:12 14:24 15:36 16:48 18:00 19:12 20:24 21:36
Time
R3:: 335 White Oak Ridge Rd (8/25/2010)
1:12 2:24 3:36 4:48 6:00 7:12 8:24 9:36 10:48
Time (date, time)
R3:: 335 White Oak Ridge Rd (9/13/2010)
1655 17:02 17:09 17:16 17:24 17:31 1738 17:45 17:52 18:00
Time
228
-------
R3: : 335 White Oak Ridge Rd (9/16/2010)
0.7
0.6
0.5
lo.4
f 03
Q
0.2
0.1
0
15:36 16:48 18:00
19:12
Time
20:24 21:36 22:48
R3: : 335 White Oak Ridge Rd (9/27/2010 - 9/28/2010)
4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36 0:00 2:24 4:48
R3:: 335 White Oak Ridge Rd (9/30/2010)
9:36 10:48
229
-------
R3:: 335 White Oak Ridge Rd (10/1/2010)
0:00
12:00 14:24
0.2
0.15
£ 0.1
Q.
II
Q
0.05
R3:: 335 White Oak Ridge Rd (10/4/2010)
I
2:24 4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36
Time
R3:: 335 White Oak Ridge Rd (10/11/2010)
f
0.7
0.6
0.5
0.4
g 0.3
0.2
0.1
0
18:00 19:12
0:00 1:12
230
-------
R3:: 335 White Oak Ridge Rd (11/4/2010-11/5/2010)
0:00 4:48 9:36 14:24 19:12 0:00 4:48
9:36
R3:: 335 White Oak Ridge Rd (12/1/2010)
0:00 2:24 4:48 7:12 9:36 12:00 14:24 16:48
R3:: 335 White Oak Ridge Rd (12/12/2010 -12/13/2010)
1
1
___ 1
.E 1
S" 0
°0
0
0
19:12 0:00
4:48 9:36
231
-------
R3:: 335 White Oak Ridge Rd (2/25/2011)
0
21:36 0:00 2:24 4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36
Time
0.6
0.5
~- 0.4
,c
V
Q 0.2
0.1
0
R3:: 335 White Oak Ridge Rd (2/28/2011)
2:24
3:36 4:48 6:00 7:12 8:24 9:36 10:48 12:00
Time
R3: : 335 White Oak Ridge Rd (3/6/2011 - 3/7/2011)
4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36 0:00 2:24 4:48
Time
232
-------
R3:: 335 White Oak Ridge Rd (3/10/2011-3/11/2011)
0:00 4:48 9:36 14:24 19:12 0:00 4:48 9:36
R3:: 335 White Oak Ridge Rd (5/23/2011)
0
22:12 22:19 22:26 22:33 22:40 22:48 22:55 23:02 23:09 23:16
Time
R3:: 335 White Oak Ridge Rd (5/30/2011)
0.25
-> 0.2
£ 0.15
6:00 6:07 6:14 6:21 6:28 6:36 6:43
0.05
233
-------
0.6
0,5
-T. 0.4
I0'3
Q 0.2
0.1
0
1:
0.7
0.6
-. °'5
|03
0.1
0
13
0.35
0.3
0.25
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0.1
0.05
0
2
R3: : 335 White Oak Ridge Rd (6/11/2011)
£
t
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12 2:24 3:36 4:48 6:00
Time
R3: : 335 White Oak Ridge Rd (6/17/2011)
*_
f
I
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+/
f
12 14:24 15:36 16:48 18:00 19:12
Time (date, time)
R3: : 335 White Oak Ridge Rd (7/3/2011)
4. •
++** *
X
/ —
/
/
1
V
:24 4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36
Time
234
-------
R4: Old tennis court at Greenwood Gardens on Old Short Hills Rd - Calibrated and
launched at 16:00 on 5/6/09 by HDB
Start time
7/26/2009
8/21/2009
8/29/2009
8/22/2010
9/30/2010
10/1/2010
10/11/2010
11/27/2010
12/1/2010
12/12/2010
12/12/2010
2/24/2011
2/28/2011
3/6/2011
3/10/2011
3/16/2011
16:46
23:57
5:45
11:20
4:20
2:17
18:33
7:40
2:15
2:13
17:25
21:58
4:12
9:00
5:30
4:29
End time
7/27/2009
8/22/2009
8/29/2009
8/22/2010
9/30/2010
10/1/2010
10/12/2010
11/27/2010
12/2/2010
12/12/2010
12/13/2010
2/25/2011
2/28/2011
3/7/2011
3/11/2011
3/16/2011
0:17
18:25
12:27
19:19
9:42
16:48
5:52
12:36
1:05
11:38
3:18
13:46
11:32
3:22
4:33
8:48
Duration
(hr)
7:31
18:28
6:42
7:59
5:22
14:31
11:19
4:56
22:50
9:25
9:53
15:48
7:20
18:22
23:03
4:19
Depth
(in.)
1.38
1.71
0.52
1.43
0.92
1.73
0.17
0.34
0.67
0.33
0.23
0.59
0.22
1.15
0.98
0.23
Average
intensity
(in./hr)
0.18
0.09
0.08
0.18
0.17
0.12
0.02
0.07
0.02
0.04
0.02
0.04
0.03
0.06
0.04
0.05
1.6
1.4
1.2
0.8
0.6
0.4
0.2
0
R4: 274 Old Short Hills Rd (7/26/2009)
15:36 16:48 18:00
0:00
1:12
235
-------
R4: 274 Old Short Hills Rd (8/21/2009-8/22/2009)
1.8
1.6
1.4
o. 0.8
v
0 0.6
0.4
0.2
19:12 0:00 4:48 9:36 14:24 19:12 0:00
Time
R4: 274 Old Short Hills Rd (8/29/2009)
0.6
0.5
-7- 0.4
Q.
HI
Q 0.2
0.1
0 —*-
^
4:48 6:00 7:12 8:24 9:36 10:48 12:00 13:12
Time
R4: 274 Old Short Hills Rd (8/22/2010)
1.6
1.4
1.2
£ 0.8
a.
S 0.6
0.4
0.2
0
t
i
^
10:48 12:00 13:12 14:24 15:36 16:48 18:00 19:12 20:24
Time
236
-------
R4: 274 Old Short Hills Rd (9/30/2010)
3:36 4:48
9:36 10:48
R4: 274 Old Short Hills Rd (10/1/2010)
0:00 2:24 4:48 7:12 9:36 12:00 14:24 16:48
R4: 274 Old Short Hills Rd (10/11/2010)
0.18
0.16
0.14
_ 0.12
1 0.1
f
v
Q
0.08
0.06
0.04
0.02
16:48 19:12 21:36 0:00 2:24
Time
4:48 7:12
237
-------
R4: 274 Old Short Hills Rd {11/27/2010}
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
7:12
8:24
9:36 10:48
Time
12:00 13:12
R4: 274 Old Short Hills Rd (12/1/2010-12/2/2010)
0:00 4:48 9:36 14:24 19:12 0:00 4:48
R4: 274 Old Short Hills Rd (12/12/2010-12/13/2010)
0.35
0.3
0.25
1 0.2
f
0.15
0.1
0.05
t
1:12 2:24 3:36 4:48 6:00 7:12 8:24 9:36 10:48 12:00 13:12
Time
238
-------
R
0.7
J. °-6
f. 0.5
V
0 0.4
0.3
0.2
0.1
0
19
0.25
0.2
£ 0.15
g" 0.1
a
0.05
0
1.4
1.2
1
£ 0.8
.e
g-0.6
a
0.4
0.2
0
7:
4: 274 Old Short Hills Rd {2/24/2011 - 2/25/2011)
r
.X
^
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j^H^r
• +++<^
12 21:36 0:00 2:24 4:48 7:12 9:36 12:00 14:24 16:48
Time
R4: 274 Old Short Hills Rd (2/28/2011)
S
/'
/
,» * *
S
3:36 4:48 6:00 7:12 8:24 9:36 10:48 12:00
Time
R4: 274 Old Short Hills Rd (3/6/2011 - 3/7/2011)
++
.^^ +~
/
/
s
s •*
fxr
12 9:36 12:00 14:24 16:48 19:12 21:36 0:00 2:24 4:48
Time
239
-------
R4: 274 Old Short Hills Rd (3/10/2011-3/11/2011)
0:00 4:48 9:36 14:24 19:12 0:00
Time
4:48
R4: 274 Old Short Hills Rd (3/16/2011)
0.25
0.2
d 0.15
f
0.1
0.05
0
3:36
y*
4:48
6:00 7:12
Time
8:24
9:36
Infiltration Analysis
Tables 9 to 30 present summary of Morton parameters and rain characteristics as well
as statistical analysis for each dry well for infiltration study test and different rain events.
Table 6 is a site summary by event showing the test conditions, the Morton parameter
values, rain depth, and maximum and minimum dry well water levels during the event.
Also noted is the likely presence of high water table conditions at the end of the
monitoring event.
240
-------
11 WoodfieldDr
Table C-1. Summary of infiltration hydrant wateriest (11 Woodfield Dr)
Date
10-13-2009
Horton's parameters
fo
(in./hr)
13.945
fc
(in./hr)
1.2
k
(1/min)
0.012
Study Test
Start Time
10/13/2009
10:07
End Time
10/13/2009
10:30
Duration
(hnmin)
0:23
Fill Rate
(gal/min)
156.52
Water Depth
in Dry well
(in.)
Max.
43.68
Min.
0.72
Table C-2. Summary of Morton parameters (f0, fc, and k) for rain events (11 Woodfield Dr)
Date
10-24-2009
12-09-2009
Horton's Parameters
fo
(in./hr)
2.987
4.117
fc
(in./hr)
0.95
0.72
k
(1/min)
0.005
0.006
Rain Characteristics
Start Time
10/23/2009
5:40
12/9/2009
0:03
End Time
10/24/2009
20:30
12/9/2009
11:38
Duration
(hr:min)
25:33
11:35
Depth
(in.)
2.20
2.01
Average
intensity
(in./hr)
0.09
0.17
Water Depth in
Dry well (in.)
Max.
28.11
39.12
Min.
0.57
0.03
Table C-3. Summary of Morton parameters (fc; f0 and k are n/a) for different rains having
"constant" infiltration rates (11 Woodfield Dr)
Date
10/28/2009
12/13/2009
fc infiltration rate (in./hr)
Average
0.83
0.44
Std
Deviation
0.13
0.25
cov
0.16
0.56
Rain Characteristics
Start Time
10/27/2009
5:40
12/13/2009
10:39
End Time
10/28/2009
14:04
12/13/2009
18:38
Duration
(hr:min)
32:24
7:59
Depth
(in.)
1.6
0.99
Average
intensity
(in./hr)
0.05
0.12
Water Depth in
Dry well (in.)
Max.
11.1
9.02
Min.
0.45
0.2
Table C-4. Statistical Analysis for Morton parameters (fo, fc, and k) (11 Woodfield Dr)
Statistical
Analysis
Number of
Events
Minimum
Maximum
Average
Std Dev
COV
Horton's Parameters
f0(in./hr)
3
2.99
13.95
7.02
6.03
0.86
fc(in./hr)
5
0.44
1.20
0.83
0.28
0.34
k (1/min)
3
0.01
0.01
0.01
0.00
0.49
Water Depth in Dry
well (in.)
Max.
5
9.02
43.68
26.21
15.81
0.60
Min.
5
0.03
0.72
0.39
0.28
0.71
241
-------
15 Marion Ave
Table C-5. Summary of infiltration rain events (15 Marion Ave
Date
6-16-2010
Horton's Parameters
fo
(in./hr)
9.95
fc
(in./hr)
0.5
k
(1/min)
0.02
Rain Characteristics
Start Time
6/16/2010
23:45
End Time
6/17/2010
0:41
Duration
(hr:min)
0:56
Depth
(in.)
0.69
Average
intensity
(in./hr)
0.74
Water Depth in
Dry well (in.)
Max.
56.74
Min.
0.36
Table C-6. Summary of Morton parameters (fc; f0 and k are n/a) for different rains having
"constant" infiltration rates (15 Marion Ave)
Date
6-22-2010
7-14-2010
8-1-2010
fc infiltration rate (in./hr)
Average
0.20
0.30
0.34
Std
Deviation
0.16
0.18
0.26
Cov.
0.8
0.6
0.76
Rain Characteristics
Start Time
6/22/2010
18:33
7/14/2010
8:21
8/1/2010
8:21
End Time
6/22/2010
18:54
7/14/2010
10:04
8/1/2010
9:54
Duration
(hnmin)
0:21
1:02
1:33
Depth
(in.)
0.37
1.22
1.34
Average
intensity
(in./hr)
1.06
1.18
0.86
Water Depth in
Dry well (in.)
Max.
6.51
23.02
26.85
Min.
0.25
0.35
0.25
Table C-7. Statistical Analysis for Morton parameters (fo, fc, and k) (15 Marion Ave)
Statistical
Analysis
Number of Events
Minimum
Maximum
Average
Std Dev
COV
Horton's Parameters
f0(in./hr)
1
9.95
9.95
9.95
n/a
n/a
fc(in./hr)
4
0.20
0.50
0.34
0.12
0.37
k (1/min)
1
0.02
0.02
0.02
n/a
n/a
Water Depth in Dry
well (in.)
Max.
4
6.51
56.74
28.28
20.93
0.74
Min.
4
0.25
0.36
0.30
0.06
0.20
242
-------
258 Main St
Table C-8. Summary of Morton parameters (f0, fc, and k) for different events (258 Main St)
Date
06-17-2010
07-14-2010
08-01-2010
Horton's Parameters
fo
(in./hr)
34.653
75.142
74.916
fc
(in./hr)
5.308
6.808
4.662
k
(1/min)
0.06
0.07
0.045
Rain Characteristics
Start Time
6/16/2010
23:45
7/14/2010
8:21
8/1/2010
8:21
End Time
6/17/2010
0:41
7/14/2010
10:04
8/1/2010
9:54
Duration
(hr:min)
0:56
1:02
1:33
Depth
(in.)
0.69
1.22
1.34
Average
intensity
(in./hr)
0.74
1.18
0.86
Water Depth in
Dry well (in.)
Max.
22.32
53.62
54.77
Min.
0.11
0.67
0.53
Table C-9. Statistical Analysis for Morton parameters (fo, fc, and k) (258 Main St)
Statistical Analysis
Number of Events
Minimum
Maximum
Average
Std
COV
Horton's Parameters
f0(in./hr)
3
34.65
75.14
61.57
23.31
0.38
fc(in./hr)
3
4.66
6.81
5.59
1.10
0.20
k (1/min)
3
0.05
0.07
0.06
0.01
0.22
Water Depth in
Dry well (in.)
Max.
3
22.32
54.77
43.57
18.41
0.42
Min.
3
0.11
0.67
0.44
0.29
0.67
243
-------
2 Undercliff Rd
Table C-10. Summary of infiltration hydrant wateriest (2 Undercliff Rd)
Date
10-2-2009
Horton's parameters
fo
(in./hr)
3.881
fc
(in./hr)
0.566
k
(1/min)
0.013
Study Test
Start Time
10/2/2009
9:07
End Time
10/2/2009
9:26
Duration
(hnmin)
0:19
Fill Rate
(gal/min)
131.58
Water Depth
in Dry well
(in.)
Max.
54.21
Min.
0.23
Table C-11. Summary of Morton parameters (fc; f0 and k are n/a) for different rains having
"constant" infiltration rates (2 Undercliff Rd)
Date
7-29-2009
8-2-2009
fc infiltration rate (in./hr)
Average
2.368
0.17
Std
Deviation
0.007
0.093
Cov.
0.003
0.55
Rain Characteristics
Start Time
7/29/2009
10:00
8/2/2009
6:29
End Time
7/29/2009
19:13
8/2/2009
12:55
Duration
(hr:min)
9:13
6:26
Depth
(in.)
1.33
1.31
Average
intensity
(in./hr)
0.14
0.2
Water Depth in Dry well
(in.)
Max.
9.16
16.54
Min.
5.01 (high
watertable)
0.39
Table C-12 Statistical Analysis for Morton parameters (fo, fc, and k) (2 Undercliff Rd)
Statistical Analysis
Number of Events
Minimum
Maximum
Average
Std
COV
Horton's Parameters
f0 (in./hr)
1
3.88
3.88
3.88
n/a
n/a
fc(in./hr)
3
0.17
2.37
1.03
1.17
1.13
k (1/min)
1
0.01
0.01
0.01
n/a
n/a
Water Depth in
Dry well (in.)
Max.
3
9.16
54.21
26.64
24.16
0.91
Min.
3
0.23
5.01
1.88
2.71
1.45
244
-------
383 Wyoming Ave
Table C-13 Summary of infiltration hydrant wateriest (383 Wyoming Ave)
Date
10-2-2009
Horton's parameters
fo
(in./hr)
5.631
fc
(in./hr)
1.171
k
(1/min)
0.0045
Study Test
Start Time
10/2/2009
10:14
End Time
10/2/2009
10:43
Duration
(hnmin)
0:29
Fill Rate
(gal/min)
100.00
Water Depth
in Dry well
(in.)
Max.
40.65
Min.
0.53
Table C-14 Summary of Morton parameters (f0, fc, and k) for rain events (383 Wyoming Ave)
Date
7-26-2009
7-29-2009
8-02-2009
8-22-2009
Horton's Parameters
fo
(in./hr)
3.188
10.253
5.45
3.623
fc
(in./hr)
0.659
1.139
0.928
1.186
k
(1/min)
0.005
0.0035
0.003
0.03
Rain Characteristics
Start Time
7/26/2009
16:46
7/29/2009
10:00
8/2/2009
6:29
8/21/2009
23:54
End Time
7/26/2009
23:22
7/29/2009
19:13
8/2/2009
12:55
8/22/2009
10:43
Duration
(hr:min)
6:36
9:13
6:26
10:49
Depth
(in.)
1.37
1.33
1.31
1.9
Average
intensity
(in./hr)
0.21
0.14
0.2
0.18
Water Depth in Dry well
(in.)
Max.
22.73
75.85
77.87
35.82
Min.
0.22
7.34 (high
watertable)
0.43
0.37
Table C-15 Statistical Analysis for Morton parameters (f0, fc, and k) (383 Wyoming Ave)
Statistical Analysis
Number of Events
Minimum
Maximum
Average
Std
COV
Horton's Parameters
f0(in./hr)
5
3.19
10.25
5.63
2.80
0.50
fc(in./hr)
5
0.66
1.19
1.02
0.23
0.22
k (1/min)
5
0.00
0.03
0.01
0.01
1.27
Water Depth in
Dry well (in.)
Max.
5
22.73
77.87
50.58
24.88
0.49
Min.
5
0.22
7.34
1.78
3.11
1.75
245
-------
260 Hartshorn Dr
Table C-17 Summary of Morton parameters (f0, fc, and k) for different events (260 Hartshorn Dr)
Date
08-10-2010
08-22-2010
08-25-2010
09-16-2010
09-30-2010
10-01-2010
02-25-2011
03-07-2011
06-17-2011
07-08-2011
08-01-2011
08-04-2011
Horton's Parameters
fo
(in./hr)
8.774
8.4097
1.0131
2.411
8.158
5.862
1.897
1.586
9.6229
9.284
1.434
3.045
fc
(in./hr)
0.4
0.6
0.23
0.3
0.65
0.7
0.4
0.4
0.6
0.45
0.25
0.6
k
(1/min)
0.009
0.011
0.02
0.005
0.03
0.02
0.02
0.002
0.05
0.035
0.015
0.008
Rain Characteristics
Start Time
8/22/2010
12:41
8/25/2010
2:00
9/16/2010
15:55
9/30/2010
4:14
10/1/2010
1:41
2/25/2011
0:25
3/6/2011
7:55
6/17/2011
13:45
7/8/2011
16:02
8/1/2011
0:25
8/3/2011
16:28
End Time
8/22/2010
20:42
8/25/2010
10:21
9/16/2010
22:14
9/30/2010
10:01
10/1/2010
13:05
2/25/2011
18:44
3/7/2011
3:29
6/17/2011
18:22
7/8/2011
20:46
8/1/2011
0:42
8/4/2011
4:02
Duration
(hr:min)
8:01
8:21
6:19
5:47
11:24
18:19
19:34
4:37
4:44
0:17
11:34
Depth
(in.)
1.51
0.43
0.61
1.83
2.53
1.36
2.78
2.78
0.73
0.46
0.65
Average
intensity
(in./hr)
0.19
0.05
0.10
0.32
0.22
0.06
0.14
0.62
0.15
1.62
0.06
Water Depth in Dry well
(in.)
Max.
53.76
55.71
46.52
40.20
56.81
63.97
54.45
54.47
56.00
55.19
31.74
49.56
Min.
15.35 (high
watertable)
28.81 (high
watertable)
0.77
8.49 (high
watertable)
38.64 (high
watertable)
7.41 (high
watertable)
36.27 (high
watertable)
3 1.64 (high
watertable)
18.24 (high
watertable)
1.14
24.38 (high
watertable)
5.40 (high
watertable)
Table C-18 Summary of Morton parameters (fc; f0 and k are n/a) for different rains having
"constant" infiltration rates (260 Hartshorn Dr)
Date
08-16-2010
09-13-2010
09-27-2010
05-23-2011
05-30-2011
06-11-2011
07-03-2011
fc infiltration rate (in./hr)
Average
0.21
0.23
0.21
0.23
0.19
0.22
0.18
Std
Deviation
0.13
018
0.25
0.21
0.11
0.15
0.11
Cov.
0.6
081
1.19
0.93
0.6
0.68
0.62
Rain Characteristics
Start Time
8/16/2010
16:24
9/13/2010
17:00
9/27/2010
7:40
5/23/2011
22:19
5/30/2011
6:07
6/11/2011
1:26
7/3/2011
4:46
End Time
8/16/2010
20:53
9/13/2010
17:58
9/28/2010
12:36
5/23/2011
23:17
5/30/2011
6:41
6/11/2011
5:29
7/3/2011
21:23
Duration
(hnmin)
4:29
0:58
28:56
0:58
0:34
4:03
16:37
Depth
(in.)
0.26
0.51
0.69
0.68
0.27
0.56
0.33
Average
intensity
(in./hr)
0.06
0.53
0.02
0.70
0.48
0.14
0.02
Water Depth in Dry well
(in.)
Max.
29.91
28.47
29.58
41.68
24.07
19.16
19.74
Min.
7.87 (high
watertable)
14.62 (high
watertable)
20.48 (high
watertable)
15.31 (high
watertable)
0.94
11. 72 (high
watertable)
14.67 (high
watertable)
246
-------
Table C-19 Statistical Analysis for Morton parameters (f0, fc, and k) (260 Hartshorn Dr)
Statistical Analysis
Number of Events
Minimum
Maximum
Average
Std
COV
Morton's Parameters
f0(in./hr)
12
1.01
9.62
5.12
3.52
0.69
fc(in./hr)
19
0.18
0.70
0.37
0.18
0.48
k(1/min)
12
0.00
0.05
0.02
0.01
0.74
Water Depth in
Dry well (in.)
Max.
19
19.16
63.97
42.68
14.35
0.34
Min.
19
0.77
38.64
15.90
11.64
0.73
247
-------
87/89 Tennyson Dr
Table C-20 Summary of Morton parameters (f0, fc, and k) for rain events (87/89 Tennyson Dr)
Date
09-30-2010
10-01-2010
03-06-2011
03-11-2011
06-17-2011
Horton's Parameters
fo
(in./hr)
1.717
1.721
3.281
2.899
10.99
fc
(in./hr)
0.196
0.251
0.45
0.28
0.28
k
(1/min)
0.006
0.008
0.015
0.015
0.12
Rain Characteristics
Start Time
9/30/2010
4:14
10/1/2010
1:41
3/6/2011
7:55
3/10/2011
2:47
6/17/2011
13:45
End Time
9/30/2010
10:01
10/1/2010
13:05
3/7/2011
3:29
3/11/2011
8:05
6/17/2011
18:22
Duration
(hnmin)
5:47
11:24
19:34
29:18
4:37
Depth
(in.)
1.83
2.53
2.78
2.90
2.78
Average
intensity
(in./hr)
0.32
0.22
0.14
0.10
0.62
Water Depth in Dry well
(in.)
Max.
89.08
93.08
93.85
93.37
91.17
Min.
82.98 (high
watertable)
35.37 (high
watertable)
82. 135 (high
watertable)
46.85 (high
watertable)
64.71 (high
watertable)
Table C-21 Summary of Morton parameters (fc; f0 and k are n/a) for different rains having
"constant" infiltration rates (87/89 Tennyson Dr)
Date
08-10-2010
08-23-2010
08-25-2010
09-14-2010
09-28-2010
11-05-2010
12-01-2010
12-13-2010
02-28-2011
05-23-2011
05-30-2011
06-11-2011
07-08-2011
08-01-2011
08-04-2011
fc infiltration rate (in./hr)
Average
0.18
0.199
0.18
0.16
0.35
0.26
0.23
0.26
0.27
0.22
0.15
0.18
0.22
0.18
0.18
Std
Deviation
0.12
0.14
0.12
0.10
0.33
0.19
0.18
0.21
0.21
0.17
0.10
0.13
0.14
0.13
0.08
Cov.
0.64
0.72
0.67
0.64
0.94
0.73
0.79
0.81
0.78
0.75
0.68
0.73
0.65
0.7
0.48
Rain Characteristics
Start Time
8/22/2010
12:41
8/25/2010
2:00
9/13/2010
17:00
9/27/2010
7:40
11/4/2010
3:26
12/1/2010
1:05
12/12/2010
0:57
5/23/2011
22:19
5/30/2011
6:07
6/11/2011
1:26
7/8/2011
16:02
8/1/2011
0:25
8/3/2011
End Time
8/22/2010
20:42
8/25/2010
10:21
9/13/2010
17:58
9/28/2010
12:36
11/5/2010
7:35
12/1/2010
15:07
12/13/2010
6:51
5/23/2011
23:17
5/30/2011
6:41
6/11/2011
5:29
7/8/2011
20:46
8/1/2011
0:42
8/4/2011
Duration
(hnmin)
8:01
8:21
0:58
28:56
28:09
14:02
29:54
0:58
0:34
4:03
4:44
0:17
11:34
Depth
(in.)
1.51
0.43
0.51
0.69
1.16
1.88
1.87
0.68
0.27
0.56
0.73
0.46
0.65
Average
intensity
(in./hr)
0.19
0.05
0.53
0.02
0.04
0.13
0.06
0.70
0.48
0.14
0.15
1.62
0.06
Water Depth in Dry well
(in.)
Max.
67.23
80.90
83.47
50.06
51.81
58.29
71.94
83.88
89.79
83.67
74.62
69.38
81.71
61.96
73.23
Min.
45.66 (high
watertable)
74.83 (high
watertable)
34.33 (high
watertable)
45.91 (high
watertable)
48.77 (high
watertable)
26.45 (high
watertable)
44.4 (high
watertable)
26.63 (high
watertable)
74.40 (high)
69.66 (high
watertable)
58.65 (high
watertable)
63.55 (high
watertable)
46.41 (high
watertable)
56.53 (high
watertable)
72.4 (high
248
-------
16:28
4:02
watertable)
Table C-22 Statistical Analysis for Morton parameters (f0, fc, and k) (87/89 Tennyson Dr)
Statistical Analysis
Number of Events
Minimum
Maximum
Average
Std
COV
Morton's Parameters
f0(in./hr)
5
1.72
10.99
4.12
3.90
0.95
fc(in./hr)
20
0.20
0.45
0.29
0.10
0.33
k(1/min)
5
0.01
0.12
0.03
0.05
1.49
Water Depth in
Dry well (in.)
Max.
20
50.06
93.85
77.12
13.82
0.18
Min.
20
26.45
82.98
5.03
17.60
0.32
1 Sinclair Terrace
Table C-23 Summary of infiltration hydrant water test (1 Sinclair Terrace)
Date
07-15-2009
Horton's parameters
fo
(in./hr)
3.306
fc
(in./hr)
0.700
k
(1/min)
0.0015
Study Test
Start Time
7/15/2009
10:40
End Time
7/15/2009
11:30
Duration
(hnmin)
0:50
Fill Rate
(gal/min)
66.00
Water Depth
in Dry well
(in.)
Max.
51.02
Min.
0
249
-------
142 Fairfield Dr
Table C-24 Summary of Morton parameters (f0, fc, and k) for rain events (142 Fairfield Dr)
Date
08-10-2010
10-01-2010
10-07-2010
Horton's Parameters
fo
(in./hr)
3.061
3.010
1.543
fc
(in./hr)
0.051
0.61
0.548
k
(1/min)
0.01
0.002
0.01
Rain Characteristics
Start Time
10/1/2010
2:17
End Time
10/1/2010
16:48
Duration
(hnmin)
14:31
Depth
(in.)
1.73
Average
intensity
(in./hr)
0.12
Water Depth in
Dry well (in.)
Max.
35.55
73.75
25.95
Min.
0.64
0.28
0.49
Table C-25 Summary of Morton parameters (fc; f0 and k are n/a) for different rains having
"constant" infiltration rates (142 Fairfield Dr)
Date
08-22-2010
12-01-2010
02-26-2011
03-07-2011
fc infiltration rate (in./hr)
Average
0.33
0.33
0.32
0.72
Std
Deviation
0.63
0.18
0.51
0.37
Cov.
1.87
0.56
1.59
0.52
Rain Characteristics
Start Time
8/22/2010
11:20
12/1/2010
2:15
2/24/2011
21:58
3/6/2011
9:00
End Time
8/22/2010
19:19
12/2/2010
1:05
2/25/2011
13:46
3/7/2011
3:22
Duration
(hnmin)
7:59
22:50
15:48
18:22
Depth
(in.)
1.43
0.67
0.59
1.15
Average
intensity
(in./hr)
0.18
0.02
0.04
0.06
Water Depth in Dry well
(in.)
Max.
28.82
24.59
33.8
73.69
Min.
0.47
0.56
12.06 (high
watertable)
23.29 (high
watertable)
Table C-26 Statistical Analysis for Morton parameters (f0, fc, and k) (142 Fairfield Dr)
Statistical Analysis
Number of Events
Minimum
Maximum
Average
Std
COV
Horton's Parameters
f0(in./hr)
3
1.54
3.06
2.54
0.86
0.34
fc (in./hr)
7
0.05
0.72
0.42
0.23
0.54
k (1/min)
3
0.00
0.01
0.01
0.00
0.63
Water Depth in
Dry well (in.)
Max.
7
24.59
73.75
42.31
21.81
0.52
Min.
7
0.28
23.29
5.40
8.99
1.67
250
-------
8 South Beechcroft Rd
Table C-27 Summary of infiltration hydrant water test (8 Beechcroft Rd)
Date
10-02-2009
Horton's parameters
fo
(in./hr)
16.12
fc
(in./hr)
0.08
k
(1/min)
0.017
Study Test
Start Time
10/2/2009
12:07
End Time
10/2/2009
12:15
Duration
(hnmin)
0:08
Fill Rate
(gal/min)
112.50
Water Depth
in Dry well
(in.)
Max.
16.76
Min.
0.32
Table C-28 Summary of Morton parameters (f0, fc, and k) for rain events (8 Beechcroft Rd)
Date
7/26/2009
8/22/2009
8/29/2009
Horton's Parameters
fo
(in./hr)
45.29
45.95
19.78
fc
(in./hr)
2.02
0.3
0.24
k
(1/min)
0.026
0.011
0.009
Rain Characteristics
Start Time
7/26/2009
16:46
8/21/2009
23:57
8/29/2009
5:45
End Time
7/27/2009
0:17
8/22/2009
18:28
8/29/2009
12:27
Duration
(hnmin)
7:31
18:28
6:42
Depth
(in.)
1.38
1.71
0.52
Average
intensity
(in./hr)
0.18
0.09
0.08
Water Depth in
Dry well (in.)
Max.
41.29
47.04
32.25
Min.
1.94
0.10
0.13
Table C-29 Statistical Analysis for Morton parameters (f0, fc, and k) (8 Beechcroft Rd)
Statistical
Analysis
Number of Events
Minimum
Maximum
Average
Std
COV
Horton's Parameters
f0(in./hr)
4
16.12
45.95
31.79
16.05
0.50
fc(in./hr)
4
0.08
2.02
0.66
0.91
1.38
k (1/min)
4
0.01
0.03
0.02
0.01
0.48
Water Depth in
Dry well (in.)
Max.
4
16.76
47.04
34.34
13.20
0.38
Min.
4
0.10
1.94
0.62
0.88
1.42
251
-------
7 Fox Hill Ln
Table C-30 Summary of Morton parameters (f0, fc, and k) for rain events (7 Fox Hill Ln)
Date
08-10-2010
08-22-2010
09-30-2010
10-01-2010
11-05-2010
12-01-2010
12-13-2010
02-25-2011
02-28-2011
03-06-2011
03-11-2011
Horton's Parameters
fo
(in./hr)
3.667
2.800
2.200
3.506
1.701
3.891
2.189
3.116
1.941
2.748
1.924
fc
(in./hr)
0.19
0.57
0.39
0.46
0.34
0.49
0.368
0.45
0.423
0.40
0.276
k
(1/min)
0.013
0.014
0.014
0.014
0.015
0.020
0.017
0.020
0.019
0.021
0.018
Rain Characteristics
Start Time
8/22/2010
11:20
9/30/2010
4:20
10/1/2010
2:17
12/1/2010
2:15
12/12/2010
17:25
2/24/2011
21:58
2/28/2011
4:12
3/6/2011
9:00
3/10/2011
5:30
End Time
8/22/2010
19:19
9/30/2010
9:42
10/1/2010
16:48
12/2/2010
1:05
12/13/2010
3:18
2/25/2011
13:46
2/28/2011
11:32
3/7/2011
3:22
3/11/2011
4:33
Duration
(hnmin)
7:59
5:22
14:31
22:50
9:53
15:48
7:20
18:22
23:03
Depth
(in.)
1.43
0.92
1.73
0.67
0.23
0.59
0.22
1.15
0.98
Average
intensity
(in./hr)
0.18
0.17
0.12
0.02
0.02
0.04
0.03
0.06
0.04
Water Depth in Dry well
(in.)
Max.
50.13
58.29
58.85
63.98
42.51
59.5
56.53
57.44
56.39
56.73
58.05
Min.
18.32 (high
watertable)
1.34
46.7 (high
watertable)
10.07 (high
watertable)
5.62 (high
watertable)
5.65 (high
watertable)
0.19
41.48 (high
watertable)
23.97 (high
watertable)
42. 19 (high
watertable)
25.86 (high
watertable)
Table C-31 Statistical Analysis for Morton parameters (f0, fc, and k) (7 Fox Hill Ln)
Statistical Analysis
Number of Events
Minimum
Maximum
Average
Std
COV
Horton's Parameters
f0(in./hr)
11
1.70
3.89
2.70
0.77
0.28
fc(in./hr)
11
0.19
0.57
0.40
0.10
0.26
k (1/min)
11
0.01
0.02
0.02
0.00
0.17
Water Depth in Dry
well (in.)
Max.
11
42.51
63.98
56.22
5.59
0.10
Min.
11
0.19
46.70
20.13
17.24
0.86
252
-------
9 Fox Hill Ln
Table C-32 Summary of infiltration hydrant water test, "constant" rate (fc; f0 and k are n/a) (9 Fox
Hill Ln)
Date
10-02-2009
fc infiltration rate
(in./hr)
Average
0.12
Std
Deviation
0.16
Cov.
1.32
Study Test
Start Time
10/2/2009
12:44
End Time
10/2/2009
13:15
Duration
(hr:min)
0:31
Fill Rate
(gal/min)
83.87
Water Depth in Dry
well (in.)
Max.
21.06
Min.
9.023* (high
watertable)
'on 10/12/2009
11 Fox Hill Ln
Table C-33 Summary of infiltration hydrant water test (11 Fox Hill Ln)
Date
10-02-2009
Horton's parameters
fo
(in./hr)
1.09
fc
(in./hr)
0.25
k
(1/min)
0.012
Study Test
Start Time
10/2/2009
13:16
End Time
10/2/2009
14:00
Duration
(hnmin)
0:44
Fill Rate
(gal/min)
77.27
Horton's
parameters
Max.
31.73
Min.
0.12*
*on 10/12/2009
253
-------
Table 6a. 11 Woodfield Dr. (D surface HSG soil conditions, and A and B subsurface soil
conditions)
test
conditions
hydrant
Morton
constant
Morton
constant
date
10/13/2009
10/24/2009
10/28/2009
12/9/2009
12/13/2009
number
Minimum
Maximum
Average
Std Dev
COV
fo
(in./hr)
13.945
2.987
n/a
4.117
n/a
3
2.99
13.95
7.02
6.03
0.86
fc
(in./hr)
1.2
0.95
0.83
0.72
0.44
5
0.44
1.20
0.83
0.28
0.34
k
(1/min)
0.012
0.005
n/a
0.006
n/a
3
0.01
0.01
0.01
0.00
0.49
Rain
Depth
(in.)
n/a
2.2
1.6
2.01
0.99
4
0.99
2.20
1.70
0.54
0.31
Max.
depth
(in.)
43.68
28.11
11.1
39.12
9.02
5
9.02
43.68
26.21
15.81
0.60
Min.
depth
(in.)
0.72
0.57
0.45
0.03
0.2
5
0.03
0.72
0.39
0.28
0.71
water
table
conditions
OK
OK
OK
OK
OK
Table 6b. 15 Marion (D surface HSG soil conditions, and A and B subsurface soil conditions)
test
conditions
Morton
constant
constant
constant
date
6/16/2010
6/22/2010
7/14/2010
8/1/2010
number
Minimum
Maximum
Average
Std Dev
COV
fo
(in./hr)
9.95
n/a
n/a
n/a
1
9.95
9.95
9.95
n/a
n/a
fc
(in./hr)
0.5
0.2
0.3
0.34
4
0.20
0.50
0.34
0.12
0.37
k
(1/min)
0.02
n/a
n/a
n/a
1
0.02
0.02
0.02
n/a
n/a
Rain
Depth
(in.)
0.69
0.37
1.22
1.34
4
0.37
1.34
0.91
0.45
0.50
Max.
depth
(in.)
56.74
6.51
23.02
26.85
4
6.51
56.74
28.28
20.93
0.74
Min.
depth
(in.)
0.36
0.25
0.35
0.25
4
0.25
0.36
0.30
0.06
0.20
water
table
condition
s
OK
OK
OK
OK
254
-------
Table 6c. 258 Main St. <
test
conditions
Morton
Morton
Morton
date
6/17/2010
7/14/2010
8/1/2010
number
Minimum
Maximum
Average
Std Dev
COV
A and D surface HSG soil conditions, and A subsurface soil conditions)
f0 (in./hr)
34.653
75.142
74.916
3
34.65
75.14
61.57
23.31
0.38
fc (in./hr)
5.308
6.808
4.662
3
4.66
6.81
5.59
1.10
0.20
k
(1/min)
0.06
0.07
0.045
3
0.05
0.07
0.06
0.01
0.22
Rain
Depth
(in.)
0.69
1.22
1.34
3
0.69
1.34
1.08
0.35
0.32
Max.
depth
(in.)
22.32
53.62
54.77
3
22.32
54.77
43.57
18.41
0.42
Min.
depth
(in.)
0.11
0.67
0.53
3
0.11
0.67
0.44
0.29
0.67
water
table
condition
s
OK
OK
OK
Table 6d. 2 Undercliff Rd (C surface HSG soil conditions, and A and B subsurface soil conditions)
test
conditions
constant
constant
hydrant
date
7/29/2009
8/2/2009
10/2/2009
number
Minimum
Maximum
Average
Std Dev
COV
f0(in./hr)
n/a
n/a
3.881
1
3.88
3.88
3.88
n/a
n/a
fc (in./hr)
2.368
0.17
0.566
3
0.17
2.37
1.03
1.17
1.13
k
(1/min)
n/a
n/a
0.013
1
0.01
0.01
0.01
n/a
n/a
Rain
Depth
(in.)
1.33
1.31
n/a
2
1.31
1.33
1.32
0.01
0.01
Max.
depth
(in.)
9.16
16.54
54.21
3
9.16
54.21
26.64
24.16
0.91
Min.
depth
(in.)
5.01
0.39
0.23
3
0.23
5.01
1.88
2.71
1.45
water
table
condition
s
high
OK
OK
255
-------
Table 6e. 383 Wyoming Ave (C surface HSG soil conditions, and A subsurface soil conditions)
test
conditions
Morton
Morton
Morton
Morton
hydrant
date
7/26/2009
7/29/2009
8/2/2009
8/22/2009
10/2/2009
number
Minimum
Maximum
Average
Std Dev
COV
fo
(in./hr)
3.188
10.253
5.45
3.623
5.631
5
3.19
10.25
5.63
2.80
0.50
fc (in./hr)
0.659
1.139
0.928
1.186
1.171
5
0.66
1.19
1.02
0.23
0.22
k
(1/min)
0.005
0.0035
0.003
0.03
0.0045
5
0.00
0.03
0.01
0.01
1.27
Rain
Depth
(in.)
1.37
1.33
1.31
1.9
n/a
4
1.31
1.90
1.48
0.28
0.19
Max.
depth
(in.)
22.73
75.85
77.87
35.82
40.65
5
22.73
77.87
50.58
24.88
0.49
Min.
depth
(in.)
0.22
7.34
0.43
0.37
0.53
5
0.22
7.34
1.78
3.11
1.75
water table
conditions
OK
high
OK
OK
OK
Table 6f. 260 Hartshorn Dr (D surface HSG soil conditions, and A and B subsurface soil
conditions)
test
conditions
Morton
constant
Morton
Morton
constant
Morton
constant
Morton
Morton
Morton
Morton
constant
constant
constant
Morton
constant
Morton
Morton
Morton
date
8/10/2010
8/16/2010
8/22/2010
8/25/2010
9/13/2010
9/16/2010
9/27/2010
9/30/2010
10/1/2010
2/25/201 1
3/7/201 1
5/23/201 1
5/30/201 1
6/11/2011
6/17/2011
7/3/201 1
7/8/201 1
8/1/2011
8/4/201 1
f0 (in./hr)
8.774
n/a
8.4097
1.0131
n/a
2.411
n/a
8.158
5.862
1.897
1.586
n/a
n/a
n/a
9.6229
n/a
9.284
1.434
3.045
fc (in./hr)
0.4
0.21
0.6
0.23
0.23
0.3
0.21
0.65
0.7
0.4
0.4
0.23
0.19
0.22
0.6
0.18
0.45
0.25
0.6
k (1/min)
0.009
n/a
0.011
0.02
n/a
0.005
n/a
0.03
0.02
0.02
0.002
n/a
n/a
n/a
0.05
n/a
0.035
0.015
0.008
Rain
Depth
(in.)
n/a
0.26
1.51
0.43
0.51
0.61
0.69
1.83
2.53
1.36
2.78
0.68
0.27
0.56
2.78
0.33
0.73
0.46
0.65
Max.
depth
(in.)
53.76
29.91
55.71
46.52
28.47
40.2
29.58
56.81
63.97
54.45
54.47
41.68
24.07
19.16
56
19.74
55.19
31.74
49.56
Min.
depth
(in.)
15.35
7.87
28.81
0.77
14.62
8.49
20.48
38.64
7.41
36.27
31.64
15.31
0.94
11.72
18.24
14.67
1.14
24.38
5.4
water table
conditions
high
high
high
OK
high
high
high
high
high
high
high
high
OK
high
high
high
OK
high
high
256
-------
test
conditions
date
number
Minimum
Maximum
Average
Std Dev
COV
f0 (in./hr)
12
1.01
9.62
5.12
3.52
0.69
fc (in./hr)
19
0.18
0.70
0.37
0.18
0.48
k (1/min)
12
0.00
0.05
0.02
0.01
0.74
Rain
Depth
(in.)
18
0.26
2.78
1.05
0.87
0.82
Max.
depth
(in.)
19
19.16
63.97
42.68
14.35
0.34
Min.
depth
(in.)
19
0.77
38.64
15.90
11.64
0.73
water table
conditions
Table 6g. 87/89 Tennyson Dr (D surface HSG soil conditions, and A and B subsurface soil
conditions)
test
conditions
constant
constant
constant
constant
constant
Morton
Morton
constant
constant
constant
constant
Morton
Morton
constant
constant
constant
Morton
constant
constant
constant
date
8/10/2010
8/23/2010
8/25/2010
9/14/2010
9/28/2010
9/30/2010
10/1/2010
11/5/2010
12/1/2010
12/13/2010
2/28/201 1
3/6/201 1
3/11/2011
5/23/201 1
5/30/201 1
6/11/2011
6/17/2011
7/8/201 1
8/1/2011
8/4/201 1
number
Minimum
Maximum
Average
Std Dev
f0 (in./hr)
n/a
n/a
n/a
n/a
n/a
1.717
1.721
n/a
n/a
n/a
n/a
3.281
2.899
n/a
n/a
n/a
10.99
n/a
n/a
n/a
5
1.72
10.99
4.12
3.90
fc
(in./hr)
0.18
0.199
0.18
0.16
0.35
0.196
0.251
0.26
0.23
0.26
0.27
0.45
0.28
0.22
0.15
0.18
0.28
0.22
0.18
0.18
20
0.20
0.45
0.29
0.10
k
(1/min)
n/a
n/a
n/a
n/a
n/a
0.006
0.008
n/a
n/a
n/a
n/a
0.015
0.015
n/a
n/a
n/a
0.12
n/a
n/a
n/a
5
0.01
0.12
0.03
0.05
Rain
Depth
(in.)
n/a
1.51
0.43
0.51
0.69
1.83
2.53
1.16
1.88
1.87
n/a
2.78
2.9
0.68
0.27
0.56
2.78
0.73
0.46
0.65
18
0.27
2.90
1.35
0.93
Max.
depth (in.)
67.23
80.9
83.47
50.06
51.81
89.08
93.08
58.29
71.94
83.88
89.79
93.85
93.37
83.67
74.62
69.38
91.17
81.71
61.96
73.23
20
50.06
93.85
77.12
13.82
Min. depth
(in.)
45.66
74.83
34.33
45.91
48.77
82.98
35.37
26.45
44.4
26.63
74.4
82.135
46.85
69.66
58.65
63.55
64.71
46.41
56.53
72.4
20
26.45
82.98
55.03
17.60
water
table
conditions
high
high
high
high
high
high
high
high
high
high
high
high
high
high
high
high
high
high
high
high
257
-------
test
conditions
date
cov
f0 (in./hr)
0.95
fc
(in./hr)
0.33
k
(1/min)
1.49
Rain
Depth
(in.)
0.69
Max.
depth (in.)
0.18
Min. depth
(in.)
0.32
water
table
conditions
258
-------
Table 6h. 1 Sinclair Terrace (D surface HSG soil conditions, and A subsurface soil conditions)
test
conditions
hydrant
date
7/15/2009
fo
(in./hr)
3.306
fc
(in./hr)
0.7
k
(1/min)
0.0015
Rain
Depth
(in.)
Max.
depth
(in.)
51.02
Min.
depth
(in.)
0
water
table
conditions
OK
Table 6i. 142 Fairfield Dr (D surface HSG soil conditions, and A and B subsurface soil conditions)
test
conditions
Morton
constant
Morton
Morton
constant
constant
constant
date
8/10/2010
8/22/2010
10/1/2010
10/7/2010
12/1/2010
2/26/201 1
3/7/201 1
number
Minimum
Maximum
Average
Std Dev
COV
fo
(in./hr)
3.061
n/a
3.01
1.543
n/a
n/a
n/a
3
1.54
3.06
2.54
0.86
0.34
fc
(in./hr)
0.051
0.33
0.61
0.548
0.33
0.32
0.72
7
0.05
0.72
0.42
0.23
0.54
k
(1/min)
0.01
n/a
0.002
0.01
n/a
n/a
n/a
3
0.00
0.01
0.01
0.00
0.63
Rain
Depth
(in.)
n/a
n/a
1.73
n/a
n/a
n/a
n/a
1
1.73
1.73
1.73
n/a
n/a
Max.
depth
(in.)
35.55
28.82
73.75
25.95
24.59
33.8
73.69
7
24.59
73.75
42.31
21.81
0.52
Min.
depth
(in.)
0.64
0.47
0.28
0.49
0.56
12.06
23.29
7
0.28
23.29
5.40
8.99
1.67
water
table
conditions
OK
OK
OK
OK
OK
high
high
Table 6j. 8 So. Beechcroft Rd (2 years old, D surface HSG soil conditions, and A and B subsurface
soil conditions)
test
conditions
Morton
Morton
Morton
hydrant
date
7/26/2009
8/22/2009
8/29/2009
10/2/2009
number
Minimum
Maximum
Average
Std Dev
COV
f0 (in./hr)
45.29
45.95
19.78
16.12
4
16.12
45.95
31.79
16.05
0.50
fc (in./hr)
2.02
0.3
0.24
0.08
4
0.08
2.02
0.66
0.91
1.38
k (1/min)
0.026
0.011
0.009
0.017
4
0.01
0.03
0.02
0.01
0.48
Rain
Depth
(in.)
1.38
1.71
0.52
n/a
3
0.52
1.71
1.20
0.61
0.51
Max.
depth
(in.)
41.29
47.04
32.25
16.76
4
16.76
47.04
34.34
13.20
0.38
Min.
depth
(in.)
1.94
0.1
0.13
0.32
4
0.10
1.94
0.62
0.88
1.42
water
table
conditions
OK
OK
OK
OK
259
-------
Table 6k. 7 Fox Hill Lane (2.3 years old, D surface HSG soil conditions, and A and B subsurface
soil conditions)
test
conditions
Morton
Morton
Morton
Morton
Morton
Morton
Morton
Morton
Morton
Morton
Morton
date
8/10/2010
8/22/2010
9/30/2010
10/1/2010
11/5/2010
12/1/2010
12/13/2010
2/25/201 1
2/28/201 1
3/6/201 1
3/11/2011
number
Minimum
Maximum
Average
Std Dev
COV
f0 (in./hr)
3.667
2.8
2.2
3.506
1.701
3.891
2.189
3.116
1.941
2.748
1.924
11
1.70
3.89
2.70
0.77
0.28
fc (in./hr)
0.19
0.57
0.39
0.46
0.34
0.49
0.368
0.45
0.423
0.4
0.276
11
0.19
0.57
0.40
0.10
0.26
k
(1/min)
0.013
0.014
0.014
0.014
0.015
0.02
0.017
0.02
0.019
0.021
0.018
11
0.01
0.02
0.02
0.00
0.17
Rain
Depth
(in.)
n/a
1.43
0.92
1.73
n/a
0.67
0.23
0.59
0.22
1.15
0.98
9
0.22
1.73
0.88
0.51
0.58
Max.
depth
(in.)
50.13
58.29
58.85
63.98
42.51
59.5
56.53
57.44
56.39
56.73
58.05
11
42.51
63.98
56.22
5.59
0.10
Min.
depth
(in.)
18.32
1.34
46.7
10.07
5.62
5.65
0.19
41.48
23.97
42.19
25.86
11
0.19
46.70
20.13
17.24
0.86
water table
conditions
high
OK
high
high
high
high
OK
high
high
high
high
Table 61. 9 Fox Hill Lane (D surface HSG soil conditions, and A and B subsurface soil conditions)
test
conditions
hydrant
date
10/2/2009
f0 (in./hr)
n/a
fc (in./hr)
0.12
k (1/min)
n/a
Rain
Depth
(in.)
n/a
Max.
depth
(in.)
21.06
Min.
depth
(in.)
9.023
water
table
conditions
high
Table 6m. 11 Fox Hill Lane (D surface HSG soil conditions, and A and B subsurface soil
conditions)
test
conditions
hydrant
date
10/2/2009
fo
(in./hr)
1.09
fc
(in./hr)
0.25
k
(1/min)
0.012
Rain
Depth
(in.)
n/a
Max.
depth
(in.)
31.73
Min.
depth
(in.)
0.12
water
table
conditions
OK
260
-------
Linda's Flower 06-17-2010
Linda's Flower 06-17-2010
f= 1.851+3.S45exp{-0.0065t)
100 200
300 400
Time (min)
Observed data
Horton
Green Ampt
500 600
7
6
5
I4
c
~3
2
1
0
(
y = 3.1064x+ 2.4359
R2 = 0.5032 ^^-^
+ + * ^^
g*^^
1
w
) 0.2 0.4 0.6 0.8 1 1.2 1.4
l/FOn1)
261
-------
Residual Plots for Morton and Green-Ampt fitted values
Residual Plot (Horton)
Fitted Value
2
1.5
1
0.5
rs
I o
OQ
i;
nt
-0.5
-1
-1.5
-2
Residual Plot (Green-Ampt)
Fitted Value
Regression Analysis for f vs. 1/F (Green-Ampt)
ANOVA
df
SS
MS
Significance
F
Regression
Residual
Total
1
58
59
16.62278
16.41058
33.03335
16.62278 58.74998
0.282941
2.24E-10
Coefficients
Standard
Error
t Stat p-value Lower 95%
Upper
95%
Intercept 2.435893 0.082297 29.5987 1.07E-36
X Variable 1 3.106365 0.405274 7.664854 2.24E-10
2.271157 2.600629
2.295121 3.917609
X Variable 1 Residual Plot
0.4 0.6 0.8 1 1.2 1.4
X Variable 1
Normal Probability Plot
20 40 60 80
Sample Pereentile
262
-------
Linda's Flower 07-14-2010
5
4C 1
. J ^
4
3.5
!«
«- 2
1.5
1
0.5
0
{
Linda's Flower 07-14-2010
k \
XA
*^Wt
v>
' f 1 A1 QJ
~^ \- 2.41bH
>^L^
^±^
-2.169exp(-O.C
L^ *•
"^*s=a
^
-i n^-fi
105tJ(—
^^Z!
^y^-
F —
"^4
* Observed
Horton
Green Anipt
) 50 100 150 200 250
Time (min)
"£•
_d
<^
5
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
[
v ~ 1 /1702x+ 2 685 — """""""
• R2 ^CUS47S^^^ A
**+ ^
-------
Residual Plots for Morton and Green-Ampt fitted values
0 °
3
•c n
1 '
-0.2
0 3
Residual Plot (Horton)
•
•
4-
+++
\+
£+ + + + *
* 4t
• 123- 5
W
; **
Fitted Value
1 *
c>
04
0 8
Residual Plot (Green Ampt)
*•
• ±
S
W
) 1 2 f3 4 5
|
^
+
•
Fitted Value
Regression Analysis for f vs. 1/F (Green-Ampt)
ANOVA
Regression
Residual
Total
Intercept
X Variable
1
df
1
20
21
Coefficients
2.684982
1.47021
SS
3.929311
3.247105
7.176416
Standard
Error
0.115014
0.298851
MS
3.929311
0.162355
tStat
23.34489
4.919545
F
24.20193
p-value
5.53E-16
8.27E-05
Significance F
8.27E-05
Lower 95%
2.445068
0.846818
Upper
95%
2.924897
2.093602
0.6 -
0.4 -
0 ^
HB
£-0.2 -
M
-0.4 -
-0.6 -
-0.8 -
X Variable 1 Residual Plot
„'•* '
^
) W 0.5 1 1.5
* +
X Variable 1
Normal Probability Plot
»*l:
1
o -
(
.»>*
^**+*
"^^^
AJ^^^^
^^
) 20 40 60 80 100
Sample Percentile
264
-------
Linda's Flower 08-01-2010
Linda's Flower 08-01-2010
f= 2.454+2.S33exp{-0.0055t
100
200 300
Time (niin)
400
Observed
Horton
Green Ampt
500
7
6
5
I4
0 0.2 0.4
= 2.6755x+3.1312
0.6 0.8
l/FOn1)
1.2 1.4
265
-------
Residual Plots for Morton and Green-Ampt fitted values
0 4
0.2
5 o
° (
0 2
Residual Plot (Horton)
+ * A
* *
* V
-
^A- ^ ^
^^^ ^
) 2 4 6
A-W*
^
^
A
4 *
Fitted Value
1 ^
0 5
— n
•S (
as
o
Residual Plot (Green Ampt)
%.
y>
JV
-i -^
i
w
) 2 « 4 6 8
*
•
Fitted Value
Regression Analysis for f vs. 1/F (Green-Ampt)
ANOVA
Regression
Residual
Total
df
1
43
44
Coefficients
SS
11.85864
19.20711
31.06574
Standard
Error
Significance
MS F F
11.85864 26.54858 6.13E-06
0.446677
t Stat p-value Lower 95%
Upper
95%
Intercept
X Variable
1 2.675481
3.13121 0.118969 26.31959 3.81E-28
2.891286 3.371133
0.519256 5.152531 6.13E-06
1.628302
i.72266
X Variable 1 Residual Plot
0.2 0.4 0.6 0.8 1 1.2 1.4
X Variable 1
Normal Probability Plot
:o
40 60
Sample Percentile
SO
100
266
-------
258 Main St - 06-17-2010
258 Main St- 06-17-2010
f= 5.308+;>9.345exp(
-0.06t)
40 60 80
Time (min)
100
Observed
Horton
Green Ampt
120
25
20
I15
_e
v 10
0.05
y = 83.217x+1.018
R2 = 0.
0.1 0.15
l/Fjin1)
0.2
0.25
267
-------
Residual Plots for Morton and Green-Ampt fitted values
Residual Plot (Horton)
Fitted Value
Residual Plot (Green-Ampt)
o
-0.5
-1
-1.5
Fitted Value
Regression Analysis for f vs. 1/F (Green-Ampt)
ANOVA
Significance
df_ SS MS F F
Regression
Residual
Total
1 2.60167 2.60167 561.9697
198 0.916652 0.00463
199 3.518323
9.75E-60
Standard Upper
Coefficients Error t Stat p-value Lower 95% 95%
Intercept
X Variable
1
-0.13475
0.01066 12.6412 3.05E-27
0.262705 0.011082 23.7059 9.75E-60
-0.15578 -0.11373
0.240851 0.284558
268
-------
X Variable 1 Residual Plot
0.8 -,
0.7 -
0.6 -
0.5 -
0.4 -
0.3 -
0.? -
0.1 -
0
-0.1 1
-0.2 -
X Variable 1
Normal Probability Plot
1.6
1.4
1.2
1
> 0.8
0.6
0.4
0.2
0
40 60
Sample Percentile
80
100
258 Main St - 07-14-2010
258 Main St - 07-14-2010
f= 6.808+68.334exp(-0.07t)
Observed
Morton
Green-Ampt
0 20 40 60
Time (min)
80
100
120
269
-------
0
0.1
0.12
270
-------
Residual Plots for Morton and Green-Ampt fitted values
Residual Plot (Horton)
Fitted Value
Residual Plot (Green-Ampt)
o
-0.5
-1
-1.5
Fitted Value
Regression Analysis for f vs. 1/F (Green-Ampt)
ANOVA
Significance
df_ SS MS F F
Regression
Residual
Total
1 2.60167 2.60167 561.9697
198 0.916652 0.00463
199 3.518323
9.75E-60
Standard Upper
Coefficients Error t Stat p-value Lower 95% 95%
Intercept
X Variable
1
-0.13475
0.01066 12.6412 3.05E-27
0.262705 0.011082 23.7059 9.75E-60
-0.15578 -0.11373
0.240851 0.284558
271
-------
X Variable 1 Residual Plot
0.8 -,
0.7 -
0.6 -
0.5 -
0.4 -
0.3 -
0.? -
0.1 -
0
-0.1 1
-0.2 -
X Variable 1
Normal Probability Plot
1.6
1.4
1.2
1
> 0.8
0.6
0.4
0.2
0
40 60
Sample Percentile
80
100
258 Main St - 08-01 -2010
258 Main St - 08-01-2010
f= 4.662+70.254exp(-0.045
20 40 60 80 100 120 140 160 180
Observed
Hart on
Green-Ampt
272
-------
0
0.1
0.12
273
-------
Residual Plots for Morton and Green-Ampt fitted values
Residual Plot (Horton)
Fitted Value
Residual Plot (Green-Ampt)
o
-0.5
-1
-1.5
Fitted Value
Regression Analysis for f vs. 1/F (Green-Ampt)
ANOVA
Significance
df_ SS MS F F
Regression
Residual
Total
1 2.60167 2.60167 561.9697
198 0.916652 0.00463
199 3.518323
9.75E-60
Standard Upper
Coefficients Error t Stat p-value Lower 95% 95%
Intercept
X Variable
1
-0.13475
0.01066 12.6412 3.05E-27
0.262705 0.011082 23.7059 9.75E-60
-0.15578 -0.11373
0.240851 0.284558
274
-------
X Variable 1 Residual Plot
0.8 -,
0.7 -
0.6 -
0.5 -
0.4 -
0.3 -
0.? -
0.1 -
0
-0.1 1
-0.2 -
X Variable 1
Normal Probability Plot
1.6
1.4
1.2
1
> 0.8
0.6
0.4
0.2
0
40 60
Sample Percentile
80
100
2 UndercliffRd 10-2-2009
4.5
2 UndercliffRd -10/2/2009
f=3.881+0.566exp(-0.013t)
0 100 200 300 400 500 600 700 800 900
Observed
Horton
Green Ampt
275
-------
3.5
2.5
y=2.9533x+0.397^,
R2 = 0.866,,
1-5
<^
1
0.5
0
0.2 0.4 0.6 0.8
1.2
276
-------
Residual Plots for Morton and Green-Ampt fitted values
-0.6
Residual Plot (Hortoa)
Fitted Value
0.6
0.4
0.2
a 0
a -0.2
-0.4
-0.6
-0.8
Residual Plot (Green-Ampt)
Fitted Value
Regression Analysis for f vs. 1/F (Green-Ampt)
ANOVA
Significance
df SS MS F F
Regression
Residual
Total
1 13.53029 13.53029 478.1812
74 2.093854 0.028295
75 15.62415
5.02E-34
Standard
Coefficients Error
t Stat p-value Lower 95%
Upper
95%
Intercept 0.397557 0.029966 13.2671 3E-21
XVariablel 2.953296 0.135055 21.86735 5.02E-34
0.337849 0.457265
2.684193 3.222399
X Variable 1 Residual Plot
0.6 «• 0.8 1
X Variable 1
3 -
2.5 -
2
1-5 -
1
0.5
0
Normal Probability Plot
0 20 40 60
Sample Percentile
100
277
-------
383 Wyoming Ave. 7-26-2009
383 Wyoming Ave. 7-26-2009
f=0.659+2.592exp -0.005
0 200
400 600
Time (min)
Observed
Morton
Green Ampt
800 1000
3.5
— 2.5
1.5
0.5
y=1.2117x+1.0399
278
-------
Residual Plots for Morton and Green-Ampt fitted values
Residual Plot (Horton)
Fitted Value
Residual Plot (Green-Ampt)
0.5
- 0
-0.5
-1
-1.5
Fitted Value
Regression Analysis for f vs. 1/F (Green-Ampt)
AN OVA
df
SS
MS
Significance
F
Regression
Residual
Total
1 8.909624 8.909624 75.30019
89 10.5306 0.118321
90 19.44023
1.75E-13
Standard
Coefficients Error
Upper
tStat p-value Lower 95% 95%
Intercept 1.039948 0.042319 24.57386 1.97E-41 0.95586 1.124035
X Variable
1 1.211721 0.139638 8.677568 1.75E-13 0.934263 1.48918
Residual Plot
Fitted Values
Normal Probability Plot
20 40 60 80 100
Sample Percentile
279
-------
383 Wyoming Ave. 7-29-2009
383 Wyoming Ave. 7-29-2009
"=1.139+9.114exF (-0.0035t)
Observed
Morton
Green Ampt
0 200 400 600 800 1000 1200 1400 1600
Time (min)
10
•e- 6
4
3
2
y- 11.123x+ 1.6122
R2 = 0.7367
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
l/Ffin1)
0.8
280
-------
Residual Plots for Morton and Green-Ampt fitted values
1
0.5
0
i
"5-0.5
T3
01
Residual Plot (Horton)
fe +
rv
5 10 15
•
* 4-
*
*
FittedValne
Residual Plot (Greeu-Ampt)
^
^ +
i " A *
(S 0 •
(1 f 4 6 8 10
n f ^p
I
FittedValne
Regression Analysis for f vs. 1/F (Green-Ampt)
AN OVA
Significance
df SS MS F F
Regression 1 89.86926 89.86926 324.6359 2.07E-35
Residual 116 32.11239 0.276831
Total 117 121.9817
Standard
Coefficients Error t Stat p-value Lower 95%
Intercept 1.612247 0.060141 26.80775 1.56E-51 1.49313
X Variable
1 11.12316 0.617348 18.01765 2.07E-35 9.900421
2.5
1.5
1 0.5
•a
UK 0
-------
383 Wyoming Ave. 8-02-2009
383 Wyoming Ave. 8-02-2009
928+4.522exp -O.OOSt
Observed
Horton
Green Ampt
200 400
600 800
Time (min)
1000 1200 1400
.4
3
2
1
0
-V-^
R2 = 0.4973
0.2 0.4 0.6 0.8
1.2 1.4
282
-------
Residual Plots for Morton and Green-Ampt fitted values
Residual Plot (Hortou)
Fitted Value
Residual Plot (Green-Ampt)
Fitted Value
Regression Analysis for f vs. 1/F (Green-Ampt)
ANOVA
Significance
df SS MS F F
Regression
Residual
Total
1 51.25879 51.25879 129.5995
131 51.81269 0.395517
132 103.0715
2.67E-21
Standard
Coefficients Error
tStat p-value Lower 95% Upper 95%
Intercept 1.676322 0.062127 26.98234 2.4E-55
XVariablel 5.26193 0.462214 11.38418 2.67E-21
1.553421 1.799223
4.34756 6.1763
-3 -
-4
X Variable 1 Residual Plot
0.5
X Variable 1
1.5
Normal Probability Plot
20 40 60
Sample Percentile
283
-------
383 Wyoming Ave. 8-22-2009
o
383 Wyoming Ave. 8-22-2009
Observed
Morton
Green Ampt
200
400 600
Axis Title
800
1000
3
2.5
2
1.5
1
0.5
y = 0.8101x+1.0727
0.5
1 1.5
1/Flin1)
2.5
284
-------
Residual Plots for Morton and Green-Ampt fitted values
"* n
$ i
K -02
Residual Plot (Hortoa)
1
&
I •
1^ * 4
L +
) lg^ 234
ft
I
*
A
Fitted Value
0 ^
1 n
T3
"T
£ n ">
£
0 4
0 6
0 8
I
1 2
Residual Plot (Greeo-Ampt)
^
ft^ *
k
fr\
3 0.5 lJ^l-£ 2 2-5 3
K
5f
^
Fitted Value
Regression Analysis for f vs. 1/F (Green-Ampt)
AN OVA
df
SS
MS
Significance
F
Regression
Residual
Total
1 2.771267 2.771267 23.2845
82 9.759448 0.119018
83 12.53072
6.37E-06
Standard
Coefficients Error
t Stat p-value Lower 95%
Upper
95%
Intercept 1.072661 0.046968 22.83825 2.7E-37
X Variable 6.37E-
1 0.810101 0.167883 4.825402 06
0.979227 1.166095
0.476129 1.144073
-1.5
X Variable 1 Residual Plot
0.5 1 1.5
X Variable 1
2.5
Normal Probability Plot
20 40 60 80
Sample Perceatile
285
-------
383 Wyoming Ave. 10-02-2009
383 Wyoming Ave. 10-02-2009
Observed
•Horton
Green Ampt
200 400 600 800
Time (min)
1000
1200
286
-------
Residual Plots for Morton and Green-Ampt fitted values
Residual Plot (Hortoa)
Fitted Value
2.5
Residual Plot (Green-Ampt)
Fitted Value
Regression Analysis for f vs. 1/F (Green-Ampt)
AN OVA
df
SS
MS
Significance
F
Regression
Residual
Total
1 43.29224
104 45.43946
105 88.7317
43.29224
0.436918
99.08553
8.52E-17
Standard
Coefficients Error
t Stat p-value Lower 95%
Upper
95%
Intercept
X Variable
1
1.640422 0.074959 21.88437 1.02E-40
5.861307 0.588829 9.954172 8.52E-17
1.491776 1.789067
4.693636 7.028977
X Variable 1 Residual Plot
0.2 0.4 0.6 0.8 1 1.2
X Variable 1
Normal Probability Plot
40 60
Sample Percentile
30
100
287
-------
1 Sinclair Terrace 07-15-2009
1 Scinclair Terrace 07-15-2009
f= 0.7+2.606exp(-0.0015t)
500
1000
Time (min)
1500
Observed
Morton
Green-Ampt
2000
0.5
1.5
2.5
288
-------
Residual Plots for Morton and Green-Ampt fitted values
Residual Plot (Hortoa)
Fitted Value
Residual Plot (Green-Ampt)
Fitted Value
Regression Analysis for f vs. 1/F (Green-Ampt)
AN OVA
Regression
Residual
Total
Intercept
X Variable
1
df
1
183
184
Coefficient
s
1.470
1.702
SS
16.316
58.449
74.765
Standard
Error
0.045
0.238
MS
16.31
6
0.319
tStat
32.74
6
7.147
F
51.085
p-value
1.91E-
78
2.04E-
11
Significance
F
2.04E-11
Lower 95%
1.381
1.232
Upper
95%
1.558
2.172
289
-------
Residual Plot
Fitted Value
Normal Probability Plot
20 40 60 80
Sample Percentile
15 Marion Drive 6-17-2010
1038070 15 Marion Drive 6-17-2010
f= 0.728+3.921exp(-0.013t)
4 Observed
^—Horton
—Green Ampt
500
1000
Time (min)
1500
2000
290
-------
0.5
1.5
Residual Plots for Morton and Green-Ampt fitted values
Residual Plot (Horton)
Fitted Value
Residual Plot (Green-Ampt)
o
-0.5
-1
-1.5
Fitted Value
Regression Analysis for f vs. 1/F (Green-Ampt)
ANOVA
Significance
df_ SS MS F F
Regression
Residual
Total
1 2.60167 2.60167 561.9697
198 0.916652 0.00463
199 3.518323
9.75E-60
Standard Upper
Coefficients Error t Stat p-value Lower 95% 95%
291
-------
Intercept -0.13475 0.01066 12.6412 3.05E-27 -0.15578 -0.11373
X Variable
1 0.262705 0.011082 23.7059 9.75E-60 0.240851 0.284558
0.8 -
0.7 -
0.6 -
0.5 -
M
| 0.4 -
1 0.3 -
0.1 -
0 -
-0.1 <
-0.2 -
X Variable 1 Residual Plot
^N| > + * *
> ^pfr^T +3
X Variable 1
Normal Probability Plot
1 6
1 ~>
0<
+
.
^
|
J
^^^^^^^^^^^^0fP
0 20 40 60 80 100
Sample Percentlle
11 Woodfield Drive
11 Woodfied Dr -10/13/2009
100 200 300 400 500 600 700 800 900 1000
11 Woodfied Dr -10/24/2009
200
400
600
Time (min)
800
1000
1200
292
-------
HWoodfied Dr -10/28/2009
200 400
Time (min)
600
11 Woodfield Dr -12/13/2009
500
Time {min)
1000
15 Marion Drive
15 Marion Dr. - 6/16/2010
500
1000
1500 2000 2500
Time (min)
3000
3500
4000
293
-------
15 Marion Dr. - 6/22/2010
200
400
600
800 1000
Time (min)
1200
1400
1600
15 Marion Dr. - 7/14/2010
500
1000
1500 2000 2500
Time (min)
3000
3500
4000
15 Marion Dr.-8/1/2010
500
1000
1500
Time (min)
2000
2500
3000
294
-------
2 Underclif Road
2 Undercliff Rd - 8/2/2009
500 1000 1500
2000 2500
Time (min)
3000 3500 4000 4500
260
Hartshorn
295
-------
260-Hartshorn- 8/10/2010
200 400 600 800
Time (min)
1000
1200
1400
260-Hartshorn- 8/12/2010
500
1000 1500
Time (min)
2000
2500
260-Hartshorn- 8/16/2010
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Time (min)
296
-------
260-Hartshorn- 8/22/2010
500
1000 1500
Time (min)
2000
2500
0
260-Hartshorn- 8/25/2010
500 1000 1500 2000
Time (min)
2500
3000
3500
297
-------
260-Hartshorn- 9/13/2010
500
1000
1500
Time (min)
2000
2500
3000
260-Hartshorn- 9/16/2010
500
1000 1500
Time (min)
2000
2500
260-Hartshorn-9/27/2010
500
1000 1500
Time (min)
2000
2500
298
-------
260-Hartshorn- 9/30/2010
200
400
600
Time (min)
800
1000
1200
260-Hartshorn-10/01/2010
200
400
600
800 1000
Time (min)
1200
1400
1600
1800
260-Hartshorn 12/20/2010
200 400 600 800
Time (min)
1000
1200
1400
1600
299
-------
260-Hartshorn 2/25/2010
500
1000
1500
Time (min)
2000
2500
3000
260-Hartshorn 3/7/2010
o
500 1000 1500 2000
Time (min)
2500
3000
3500
260-Hartshorn- 5/20/2011
500
1000 1500
2000 2500
Time (min)
3000 3500 4000
4500
300
-------
260-Hartshorn- 5/23/2011
500
1000 1500
2000 2500 3000
Time (min)
3500 4000 4500 5000
260-Hartshorn- 5/30/2011
200
400
600
800 1000 1200
Time (min)
1400
1600
1800
2000
260-Hartshorn- 6/11/2011
301
-------
260-Hartshorn- 6/15/2011
500
1000
1500
Time (min)
2000
2500
3000
0
260-Hartshorn- 6/17/2011
200 400 600 800
Time (min)
1000
1200
1400
260-Hartshorn- 7/3/2011
500
1000
1500
Time (min)
2000
2500
3000
302
-------
260-Hartshorn- 7/8/2011
10
9
8
7
I 6
.E
^ 4
3
2
1
0
500
1000
1500
Time (min)
2000
2500
3000
260-Hartshorn- 7/25/2011
^Seriesl
200
400
600 800
Time (min)
1000
1200
1400
260-Hartshorn- 8/1/2011
500
1000
1500
Time (min)
2000
2500
3000
303
-------
260-Hartshorn- 8/4/2011
100 200 300 400 500
Time (min)
600
700
800
87/79 Tennyson
87/89Tennyson - 5/23/2011
200 400 600 800
Time (min)
1000
1200
1400
304
-------
87/89Tennyson - 5/30/2011
200 400 600 800
Time (min)
1000
1200
1400
0.7
0.6
0.5
J= 0.4
lo.3
H-
0.2
0.1
0
0
87/89Tennyson - 6/11/2011
++
200 400 600 800
Time (min)
1000
1200
1400
12
10
8
87/89 Tennyson - 6/17/2011
500 1000 1500 2000 2500 3000
Time (min)
3500
4000
4500 5000
305
-------
87/89Tennyson -7/08/2011
1000
1500 2000
Time (min)
2500
3000 3500
87/89Tennyson -8/01/2011
500
1000
1500 2000 2500
Time (min)
3000
3500
4000
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
87/89 Tennyson - 8/04/2011
0 50 100 150 200 250 300 350 400 450 500
Time (min)
306
-------
87/89 Tennyson - 08/10/2010
0 1000 2000 3000 4000 5000 6000 7000 8000 9000
Time (min)
87/89 Tennyson - 08/23/2010
87/89 Tennyson - 08/25/2010
2000 4000 6000
8000 10000 12000 14000 16000 18000 20000
Time (min)
307
-------
87/89 Tennyson - 09/14/2010
500 1000 1500
2000 2500
Time (min)
3000 3500 4000 4500
87/89 Tennyson - 09/28/2010
500
1000 1500
Time (min)
2000
2500
87/89 Tennyson - 09/30/2010
200
400
600
Time (min)
800
1000
1200
308
-------
87/89 Tennyson -10/01/2010
500 1000 1500 2000 2500
Time (min)
3000
3500
4000
87/89 Tennyson -11/05/2010
0 500 1000 1500 2000 2500 3000 3500 4000 4500
Time (min)
87/89 Tennyson -12/01/2010
2000
4000
6000
Time (min)
8000
10000
12000
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87/89 Tennyson -12/13/2010
_ o
500
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Time (min)
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87/89 Tennyson - 02/25/2011
500 1000 1500 2000 2500 3000 3500 4000
87/89 Tennyson - 02/28/2011
500 1000 1500 2000
Time (min)
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310
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87/89 Tennyson - 03/06/2011
200
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Time (min)
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87/89 Tennyson - 03/11/2011
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Time (min)
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Fairfield
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142-Fairfield-08/10/2010
200 400 600 800 1000 1200 1400 1600 1800
Time (min)
1.2
0.8
4 0.6
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0.2
142-Fairfield-08/22/2010
100 200 300 400
Time (min)
500
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Time (min)
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312
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142-Fairfield-10/7/2010
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Time (min)
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142-Fairfield-12/l/2010
Time (min)
*Seriesl
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142-Fairfield- 2/26/2011
1000 2000
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Time (min)
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142 Fairfield - 3/7/2011
0 200 400 600
800 1000 1200 1400
Time (min)
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142_Fairfield_5/20/2011
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Time (min)
142_Fairfield_6/17/2011
o
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Time (min)
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8 South Beechcroft
8 S Beechcroft - 7/26/2009
80 100 120 140 160 180 200
0 20
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8 S Beechcroft - 8/22/2009
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315
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8 S Beechcroft -10/2/2009
100
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316
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7 Fox Hill Lane 8-10-2010
7-Fox Hill Lane - 8/10/2010
3.5
"? 2.5
200 400 600 800 1000 1200 1400 1600 1800 2000
Time (min)
7-Fox Hill Lane - 8/22/2010
200 400
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Time (min)
7-Fox Hill Lane - 9/30/2010
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7-Fox Hill Lane -10/01/2010
200 400 600 800
Time (min)
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7-Fox Hill Lane -11/05/2010
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Time (min)
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7-Fox Hill Lane -12/01/2010
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Time (min)
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7-Fox Hill Lane -12/13/2010
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Time (min)
7-Fox Hill Lane - 02/25/2011
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7-Fox Hill Lane - 02/28/2011
100 200 300 400 500 600 700 800
319
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7-Fox Hill Lane - 03/11/2011
o
200
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Time (min)
800
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9 Fox Hill Ln.
9 Fox Hill Lane -10/2/2009
1000
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Time (min)
4000
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6000
11 Fox Hill Ln.
11 Fox Hill -10/2/2009
500
1000
1500
Time (min)
2000
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320
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Appendix D. Dry Well Water Quality Analyses
Probability Plots
Probability Plot of 79 Inflow, 79 Cistern
Lognormal - 95% CI
»-H4
+j 70'
£ 60.
U 50'
V 40
°- 30
20'
10'
II II II II II
:: -TT--H—H-H—H-
i i ...
-H-/—rH
I !/•! I
—fyf~^~y
•w
\
n
Variable
- 79 Inflow
79 Cistern
Loc Scale N AD P
3.305 3.091 6 0.644 0.047
7.021 2.284 8 0.201 0.815
Total coliform (MPN)
Probability Plot of 18 Shallow, 18 Deep
Lognormal - 95% CI
Variable
- IS Shallow
IS Deep
Loc Scale N AD P
8.456 1.982 9 0.681 0.049
9.623 1.030 9 0.889 0.013
Total coliform (MPN)
Probability Plot of 139 Shallow, 139 Deep
Lognormal - 95% CI
Variable
— • — 139 Shallow
• 139 Deep
Loc Scale N
8.679 1.775 9
8.797 1.393 9
AD P
0.889 0.013
0.487 0.165
100 1000 10000 100000 1000000 10000000
Total coliform (MPN)
Figure D-1 Probability plots for total coliform in different locations
321
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Probability Plot of 79 Inflow, 79 Cistern
Lognormal - 95% CI
Variable
- 79 Inflow
79 Cistern
Loc Scale N AD P
1.778 3.176 7 1.087 <0.005
3.877 2.571 8 0.348 0.378
Probability Plot of 18 Shallow, 18 Deep
Lognormal - 95% CI
Variable
• 18 Shallow
IS Deep
Loc Scale N AD P
3.172 1.653 9 0.365 0.353
3.575 1.282 9 0.518 0.135
1.0
10.0 100.0
E. coli (MPN)
1000.0 10000.0
Probability Plot of 139 Shallow, 139 Deep
Lognormal - 95% CI
Variable
• 139 Shallow
139 Deep
Loc Scale N AD P
4.504 1.173 9 0.585 0.090
5.153 1.909 9 0.553 0.110
1.0
10.0
100.0 1000.0 10000.0 100000.0
E. coli (MPN)
Figure D-2 Probability plots for E.coli in different locations
322
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Probability Plot of 79 Inflow, 79 Cistern
Lognormal - 95% CI
i i iii
i i iii
i i iii
1.0 10.0
Total Ntrogen as N (nq/L)
Variable
— • — 79 Inflow
• 79 Cistern
Loc Scale N AD P
0.4297 0.8097 7 0.265 0.567
0.5372 0.8632 8 0.293 0.513
100.0
Probability Plot of 18 Shallow, 18 Deep
Lognormal - 95% CI
Loc Scale N AD P
0.06106 2.741 9 1.359 <0.005
0.9798 0.6400 9 0.213 0.788
Total Ntrogen as N (mg/L)
Probability Plot of 139 Shallow, 139 Deep
Lognormal - 95% CI
II II II II II
I I
J—I,
II II II II II
--H—H—!-!—H-H
70-
60-
50-
40
30
20
.-I --- l-l --- 1 -I --- M --
II II II II
l-l --- l-l --- l-l --- l-l --
It
l-l --- M --- 1-| --- !
Variable
• 139 Shallow
139 Deep
Loc Scale N AD P
-0.2442 2.604 9 1.502 <0.005
0.6126 0.7438 9 0.268 0.589
t^J ,£> ,£> ~ ^ ^ ^>^ /
•*"
"*>
V
Total Ntrogen as N (nq/L)
Figure D-3 Probability plots for total nitrogen in different location
323
-------
Probability Plot of 79 Inflow, 79 Cistern
Lognormal - 95% CI
Loc Scale N AD P
0.1365 0.7054 6 0.673 0.039
0.4450 0.5732 8 0.202 0.814
1.0
N03- N(mg/L)
10.0
Probability Plot of 18 Shallow, 18 Deep
Lognormal - 95% CI
i i 1111
i i i
LLLLLL-
I I I
I I I
hH-l-H—
I I I
I I I I 11
I I I I I I 11
I I I I I
l-U-UJ-L
I I I I I I I
I I I I I I I
1.0
I I I I I n
-I--H-H-H
I I I I I 11
. I I I I I 11
~T—i—rTTTTn—
I I I I I 11II
I I I I I 11II
I I I I I 11II
Mill
10.0
Variable
• 18 Shallow
IS Deep
Loc Scale N AD P
-0.3059 0.6326 9 0.360 0.363
0.2396 0.6389 8 0.440 0.213
NO3- N(ma/L)
Probability Plot of 139 Shallow, 139 Deep
Lognormal - 95% CI
Variable
139 Shallow
139 Deep
i i i 1 1
i i i 1 1
i i i 1 1
J._J-J.J.J.LU.
i i i 1 1
i i i 1 1 1 1 1
I I I I I
I I I I I
I I I I I
I I I I I
Loc Scale N AD P
0.4478 0.7405 8 0.136 0.958
0.2805 0.8038 9 0.300 0.509
HHH+1—
I I I I III
-I—I-UUU4I—
I I I I I III
1—I-H-M4I—
I I I I I III
I I I I I
4.-4-4.4.4-U4.
I I I I I
4-4-444- «4
I I I I I 1 1 1
i i i 11
-TTTTTTT
I I I I I
T-rTTTTlT
I I I I I
I I I I I I III
i—rrrrm—
i i i i i i in
-\—i—i-rrnTi—
i i i i i i in
m 1—I—1-l-hH+l—
II I I I I I I III
II I I I I I I III
htl 1—I—I-
1.0
NO3- N(nq/L)
10.0
Figure D-4 Probability plots for NOs in different location
324
-------
Probability Plot of 79 Inflow, 79 Cistern
Lognormal - 95% CI
Variable
— • — 79 Inflow
• 79 Cistern
Loc Scale N AD P
-2.417 1.043 7 0.173 0.885
-2.165 1.012 8 0.487 0.157
0.010 0.100 1.000
Total Phosphorus as P (mg/L)
10.000
Probability Plot of 18 Shallow, 18 Deep
Lognormal - 95% CI
Variable
• 18 Shallow
IS Deep
Loc Scale N AD P
-1.793 0.6440 9 0.419 0.253
-1.219 0.8901 9 0.493 0.158
0.01
0.10 1.00
Total Phosphorus as P (mg/L)
10.00
Probability Plot of 139 Shallow, 139 Deep
Lognormal - 95% CI
0.01
0.10
Total Phosphorus as P (mg/L)
1.00
Figure D-5 Probability plots for total phosphorus in different location
325
-------
Probability Plot of 79 Inflow, 79 Cistern
Lognormal - 95% CI
Loc Scale N AD P
3.347 0.4366 7 0.342 0.373
2.643 0.6671 8 0.179 0.880
I I I I I I 'I
-—-f—1
I /
14
10
COD (mg/L)
100
Probability Plot of 18 Shallow, 18 Deep
Lognormal - 95% CI
Variable
• 18 Shallow
IS Deep
Loc Scale N AD P
3.477 0.5357 9 0.800 0.023
3.746 0.8911 9 0.218 0.771
100
1000
COD (mg/L)
Probability Plot of 139 Shallow, 139 Deep
Lognormal - 95% CI
I L/l I
I 1,1 I I
i i/r i i
|M_|_!
i \A i
I lyl I
rrr
\*\ i
i /H i
-y-r1
i ,1 i
tp*-t-
" i i i i i i i i i "
. T—i—r~rT~i~rrr .
-4-t-H-r4H-|-H-r-
-+-+-I—i-i-+-i-
! I I I I I I I
-+-+-+-I—I-I-+H-
I I I I I I I I I
I L-4—I—I--I-I—1-|.
I I I I I I I I I
I I I I I I I I I
I I.-4.-4.-U4-U4.-I.
I I I I I I I I I
r-4-4-4-H-r44
III.
UH-1-
I I I I
I I I I
UUJ-I.
I I I I
fhfr
Variable
• 139 Shallow
139 Deep
Loc Scale N AD P
3.744 0.1550 9 0.413 0.262
3.740 0.2395 9 0.340 0.409
COD (mg/L)
Figure D-6 Probability plots for COD in different location
326
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Mann-Whitney Test Results
Mann-Whitney Test Results for Total Conforms
Mann-Whitney Test and Cl: 79 Inflow, 79 Cistern
N Median
79 Inflow 6 11.0
79 Cistern 8 1753.4
Point estimate for ETA1-ETA2 is -1472.3
95.5 Percent Cl for ETA1-ETA2 is (-11660.6,-23.3)
W = 28.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.0332
The test is significant at 0.0330 (adjusted for ties)
Since the p-value is less than the chosen a level of 0.05, you reject HO. Therefore,there
is a difference between the population medians.
Mann-Whitney Test and Cl: 135 Shallow, 135 Deep
N Median
135 Shallow 10 6892
135 Deep 10 13423
Point estimate for ETA1-ETA2 is -2965
95.5 Percent Cl for ETA1-ETA2 is (-16238,7259)
W=93.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.4057
The test is significant at 0.4048 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 18 Shallow, 18 Deep
N Median
18 Shallow 9 11672
18 Deep 9 18539
Point estimate for ETA1-ETA2 is -7848
95.8 Percent Cl for ETA1-ETA2 is (-18340,6242)
W = 69.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.1577
The test is significant at 0.1564 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 139 Shallow, 139 Deep
N Median
139 Shallow 9 14207
139 Deep 9 8911
Point estimate for ETA1-ETA2 is 2977
327
-------
95.8 Percent Cl for ETA1-ETA2 is (-9022,11988)
W=90.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.7239
The test is significant at 0.7237 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test Results for E. coli
Mann-Whitney Test and Cl: 79 Inflow, 79 Cistern
N Median
79 Inflow 7 1.0
79 Cistern 8 21.8
Point estimate for ETA1-ETA2 is -19.3
95.7 Percent Cl for ETA1-ETA2 is (-285.5,-0.0)
W = 38.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.0491
The test is significant at 0.0469 (adjusted for ties)
Since the p-value is less than the chosen a level of 0.05, you reject HO. Therefore,there
is a difference between the population medians.
Mann-Whitney Test and Cl: 135 Shallow, 135 Deep
N Median
135 Shallow 10 347.2
135 Deep 10 313.9
Point estimate for ETA1-ETA2 is 79.5
95.5 Percent Cl for ETA1-ETA2 is (-261.5,2589.6)
W= 112.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.5967
The test is significant at 0.5966 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 18 Shallow, 18 Deep
N Median
18 Shallow 9 40.7
18 Deep 9 57.0
Point estimate for ETA1-ETA2 is -11.2
95.8 Percent Cl for ETA1-ETA2 is (-55.0,41.8)
W=80.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.6911
328
-------
The test is significant at 0.6903 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 139 Shallow, 139 Deep
N Median
139 Shallow 9 105.9
139 Deep 9 136.0
Point estimate for ETA1-ETA2 is -3.5
95.8 Percent Cl for ETA1-ETA2 is (-1340.7,91.7)
W=85.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 1.0000
The test is significant at 1.0000 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test Results for Total Nitrogen as N
Mann-Whitney Test and Cl: 79 Inflow, 79 Cistern
N Median
79 Inflow 7 1.500
79 Cistern 8 1.500
Point estimate for ETA1-ETA2 is 0.000
95.7 Percent Cl for ETA1-ETA2 is (-1.999,2.001)
W=54.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.8622
The test is significant at 0.8593 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 135 Shallow, 135 Deep
N Median
135 Shallow 10 1.500
135 Deep 10 1.500
Point estimate for ETA1-ETA2 is 0.000
95.5 Percent Cl for ETA1-ETA2 is (-1.000,0.500)
W=96.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.5205
The test is significant at 0.5033 (adjusted for ties)
329
-------
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 18 Shallow, 18 Deep
N Median
18 Shallow 9 2.000
18 Deep 9 3.000
Point estimate for ETA1-ETA2 is -0.500
95.8 Percent Cl for ETA1-ETA2 is (-2.999,1.001)
W=76.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.4268
The test is significant at 0.4241 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 139 Shallow, 139 Deep
N Median
139 Shallow 9 1.500
139 Deep 9 1.500
Point estimate for ETA1-ETA2 is 0.000
95.8 Percent Cl for ETA1-ETA2 is (-1.999,0.999)
W=80.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.6588
The test is significant at 0.6437 (adjusted for ties)Since the p-value is not less than the
chosen a level of 0.05, you conclude that there is insufficient evidence to reject HO.
Therefore, the data does not support the hypothesis that there is a difference between
the population medians.
Mann-Whitney Test Results for NOs plus NO2 as N
Mann-Whitney Test and Cl: 79 Inflow, 79 Cistern
N Median
79 Inflow 6 0.800
79 Cistern 8 0.625
Point estimate for ETA1-ETA2 is 0.325
95.5 Percent Cl for ETA1-ETA2 is (-0.100,2.100)
W=57.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.1376
The test is significant at 0.1359 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 135 Shallow, 135 Deep
N Median
330
-------
135 Shallow 10 0.8000
135 Deep 10 0.5500
Point estimate for ETA1-ETA2 is 0.2000
95.5 Percent Cl for ETA1-ETA2 is (-0.1998,0.5999)
W= 121.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.2413
The test is significant at 0.2394 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 18 Shallow, 18 Deep
N Median
18 Shallow 9 0.800
18 Deep 8 1.100
Point estimate for ETA1-ETA2 is -0.375
95.1 Percent Cl for ETA1-ETA2 is (-1.200,0.100)
W = 65.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.1489
The test is significant at 0.1477 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 139 Shallow, 139 Deep
N Median
139 Shallow 8 0.700
139 Deep 9 0.650
Point estimate for ETA1-ETA2 is -0.050
95.1 Percent Cl for ETA1-ETA2 is (-0.901,0.500)
W = 68.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.7728
The test is significant at 0.7726 (adjusted for ties)Since the p-value is not less than the
chosen a level of 0.05, you conclude that there is insufficient evidence to reject HO.
Therefore, the data does not support the hypothesis that there is a difference between
the population medians.
Mann-Whitney Test Results for Total Phosphorus as P
Mann-Whitney Test and Cl: 79 Inflow, 79 Cistern
N Median
79 Inflow 7 0.0800
79 Cistern 8 0.0950
Point estimate for ETA1-ETA2 is -0.0150
95.7 Percent Cl for ETA1-ETA2 is (-0.3100,0.1300)
331
-------
W=53.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.7723
The test is significant at 0.7721 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 135 Shallow, 135 Deep
N Median
135 Shallow 10 0.0975
135 Deep 10 0.0825
Point estimate for ETA1-ETA2 is 0.0025
95.5 Percent Cl for ETA1-ETA2 is (-0.0400,0.1000)
W= 106.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.9397
The test is significant at 0.9396 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 18 Shallow, 18 Deep
N Median
18 Shallow 9 0.1400
18 Deep 9 0.2050
Point estimate for ETA1-ETA2 is -0.0750
95.8 Percent Cl for ETA1-ETA2 is (-0.4299,0.0250)
W = 66.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.1023
The test is significant at 0.1020 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 139 Shallow, 139 Deep
N Median
139 Shallow 9 0.1300
139 Deep 9 0.1100
Point estimate for ETA1-ETA2 is 0.0200
95.8 Percent Cl for ETA1-ETA2 is (-0.0300,0.0599)
W=98.5
332
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Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.2697
The test is significant at 0.2682 (adjusted for ties)Since the p-value is not less than the
chosen a level of 0.05, you conclude that there is insufficient evidence to reject HO.
Therefore, the data does not support the hypothesis that there is a difference between
the population medians.
Mann-Whitney Test Results for COD
Mann-Whitney Test and Cl: 79 Inflow, 79 Cistern
N Median
79 Inflow 7 26.00
79 Cistern 8 13.15
Point estimate for ETA1-ETA2 is 12.25
95.7 Percent Cl for ETA1-ETA2 is (1.01,33.99)
W=74.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.0372
The test is significant at 0.0371 (adjusted for ties)
Since the p-value is less than the chosen a level of 0.05, you reject HO. Therefore,there
is a difference between the population medians.
Mann-Whitney Test and Cl: 135 Shallow, 135 Deep
N Median
135 Shallow 10 38.75
135 Deep 10 28.00
Point estimate for ETA1-ETA2 is 8.75
95.5 Percent Cl for ETA1-ETA2 is (-3.50,19.01)
W= 125.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.1405
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 18 Shallow, 18 Deep
N Median
18 Shallow 9 29.50
18 Deep 9 36.50
Point estimate for ETA1-ETA2 is -7.00
333
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95.8 Percent Cl for ETA1-ETA2 is (-68.52,20.51)
W=75.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.4015
The test is significant at 0.4011 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
Mann-Whitney Test and Cl: 139 Shallow, 139 Deep
N Median
139 Shallow 9 44.00
139 Deep 9 45.50
Point estimate for ETA1-ETA2 is -1.00
95.8 Percent Cl for ETA1-ETA2 is (-10.00,9.00)
W=82.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.8253
The test is significant at 0.8250 (adjusted for ties)
Since the p-value is not less than the chosen a level of 0.05, you conclude that there is
insufficient evidence to reject HO. Therefore, the data does not support the hypothesis
that there is a difference between the population medians.
334
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Paired Line Plots
30,000
_ 25,000
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- 10,000
1
5,000
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40,000
35,000
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— 25,000
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Total coliform
8/5/2011
8/16/2011
8/17/2011
8/18/2011
8/22/2011
8/25/2011
8/28/2011
79 Inflow
79 Cistern
Total coliform
18 Shallow
18 Deep
7/29/2011
8/5/2011
8/10/2011
8/16/2011
8/17/2011
8/18/2011
8/22/2011
8/25/2011
8/28/2011
335
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336
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E. coli
139 Shallow
139 Deep
*— 7/29/2011
•-8/5/2011
^8/10/2011
- 8/16/2011
8/17/2011
*—8/18/2011
>—8/22/2011
•-8/25/2011
—8/28/2011
Figure D-8 Line plots for E. coli in different location
Total Nitrogen as N
8/5/2011
8/16/2011
8/17/2011
8/18/2011
8/22/2011
8/25/2011
8/28/2011
79 Inflow
79 Cistern
337
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I
18
16
14
12
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18 Shallow
18 Deep
-•-7/29/2011
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—i— 8/18/2011
— 8/22/2011
-8/25/2011
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Total Nitrogen as N
-•-7/29/2011
-A-8/5/2011
-*-8/10/2011
-*K-8/16/2011
—•—8/17/2011
—1—8/18/2011
— 8/22/2011
8/25/2011
139 Shallow
139 Deep
Figure D-9 Line plots for total nitrogen in different location
338
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Figure D-10 Line plots for NOs in different location
339
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Total Phosphorus as P
79 Inflow
79 Cistern
8/5/2011
8/16/2011
8/17/2011
8/18/2011
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•8/25/2011
•8/28/2011
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/
18 Shallow
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7/29/2011
8/5/2011
—•—8/10/2011
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—A—8/17/2011
-*- 8/18/2011
—•—8/22/2011
-*-8/25/2011
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0.5
Total Phosphorus as P
139 Shallow
139 Deep
7/29/2011
8/5/2011
8/10/2011
8/16/2011
8/17/2011
8/18/2011
8/22/2011
8/25/2011
8/28/2011
Figure D-11 Line plots for total phosphorus in different location
340
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COD
8/5/2011
-•-8/16/2011
-±-8/17/2011
-W- 8/18/2011
—*—8/22/2011
-*- 8/25/2011
—I—8/28/2011
79 Inflow
79 Cistern
COD
18 Shallow
18 Deep
-•-7/29/2011
-A-8/5/2011
-*—8/10/2011
—•—8/16/2011
—4^8/17/2011
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—A-7/29/2011
—W- 8/5/2011
—*—8/10/2011
—*-8/16/2011
—^8/17/2011
—•—8/18/2011
— 8/22/2011
—#—8/25/2011
8/28/2011
139 Shallow
139 Deep
Figure D-12 Line plots for COD in different location
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Time Series Plots
Total Nitrogen as N {mg/L}
^ 8
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£, 6
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7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
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7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
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Total Nitrogen as N (mg/L)
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342
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N03 - N {mg/L)
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7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
Event
IM03 - N {mg/L}
7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
Event
N03-IM{mg/L)
N03-N{mg/L)
5
4.5
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2.5
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7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
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7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
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N03 - N (mg/L)
N03 - N {mg/L}
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7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
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7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
Event
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Total Phosphorus as P (mg/L)
re
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0.6
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0.3
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2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
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| 0
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Total Phosphorus as P {mg/L)
Total Phosphorus as P {mg/L)
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344
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COD {mg/L)
7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
Event
COD {mg/L}
_ 60
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•79 Cistern
40
30
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7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
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120
100
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7/26/2011 8/5/2011 8/15/2011 8/25/2011 9/4/2011
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Event
9/4/2011
345
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Appendix E. Urban Evapotranspiration (ET) Values for Irrigation
Calculations
Knowledge of site ET conditions on a monthly basis is needed to determine the
irrigation deficit that can be met by using harvested stormwater. ET monitoring primarily
occurs in agricultural and wild land environments. With increasing water conservation
interests in urban areas, there have been new interests in applying the available ET
data to urban environmental conditions. ET data is needed when investigating sanitary
wastewater and stormwater reuse options applied to supplemental irrigation, and for
more accurate modeling of rain garden and green roof controls for stormwater
management. Climate-based methods are the most common method used to monitor
ET. Evapotranspiration potential, ET0, is normalized for a standard condition that
reflects agricultural conditions (usually for irrigated alfalfa). The ET0 value therefore
needs to be adjusted according to the soils, plants, and growing season conditions for
the site of interest. Most of these adjustment factors were developed for agricultural
situations and their use in highly disturbed urban environments has not been well-
documented. Pitt, et al. 2011 examined and mapped available ET0 values most suitable
for major urban areas.
Evapotranspiration Data
Applying agricultural and wildland ET information to urban areas can be useful, but
necessarily accurate. During a recent comparison of rain gardens in clay and sandy
soils by the United States Geological Survey (USGS), ET was used extensively to
compare bioretention performance for turf grasses and natural prairie vegetation (Selbig
2010). The ET was calculated using data collected from an onsite weather station and
compared to measured ET values by mass balances. The calculated ET values did not
compare accurately to the measured values, but both methods indicated similar trends.
The following discussion presents ET data for the Millburn, NJ area and a common
calculation method using local metrological data.
ASCE Standardized Reference Equation
The ASCE Standardized Equation (ASCE 2005) is the most recent in a series of
standards that have been adopted for reference ET calculations. Both the ASCE and
Food and Agriculture Organization (FAO-56) have approved versions of the equation
with only minor differences (standard crop height being the major difference). ASCE
reference ET can be calculated for only two crop heights, short (grasses) and tall
(alfalfa). The data available in this report was calculated for a short reference crop. The
346
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result, ET0 or ETr, is the reference ET for a well-watered crop. It is calculated in
millimeters per dayf — V and was then converted to inches per dayf— Y The general
\dizy / \day /
form for the equation is shown below in Equation D-1 .
Equation D-1. ASCE Standardized Reference Equation
0.408A(Rn - G) 4- Y
4 -f y(l + cdu,]
Rainmaster
Rainmaster by Irritrol is the most complete and easiest to use resource for estimated
average monthly ET rates for urban areas in the U.S. The method only requires a
nearby zip code to generate ET values for a site. This is a commercial site used as a
resource for their irrigation equipment business at:
http://www.rainmaster.com/historicET.asp. Monthly ET values for zip code 07041
(Millburn, NJ) shown on the proprietary Rainmaster ET web site are very similar to the
ASCE standardized reference ETo values, while the Kimberly Penman ETr values are
about 30% larger. The differences are associated with the adjustment factors that are
included in the different forms of the equations.
Evapotranspiration
ET is defined as the rate at which readily available water is removed from the soil and
plant surfaces expressed as the rate of latent heat transfer per unit area A,ETrgf or
expressed as a depth of water evaporated and transpired from a reference crop
(Jensen, et a/. 1990). Unless soil moisture is kept near field capacity, there will be times
when ET estimates outweigh actual ET removed from the soil. Calculated ET values for
the short reference crop for well watered cool season grasses is further modified for
specific plants. A plants actual ET is calculated from the product of these original
equations by multiplying ET0 by coefficients for each plant type providing a daily
estimate for the crop under well watered conditions. There are lists of approved
coefficients (such as WUCOLS III) for both grass reference and alfalfa values; however
these values are not interchangeable. Table D-1 shows some crop coefficient factors
(used to modify the reference ET0 values), along with the root depths. Generally, deeper
rooted plants can remove water from deeper soil layers.
Table D-1. Crop Coefficient Factors and Root Depths (Pitt, et a/. 2008)
Plant Crop Coefficient Root Depth (ft)
Factor (Kc)
Cool Season Grass (turfgrass) 0.80 1
Common Trees 0.70 3
Annuals 0.65 1
Common Shrubs 0.50 2
Warm Season Grass 0.55 1
Prairie Plants (deep rooted) 0.50 6
347
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Grasses are resilient plants and often recover in difficult drought conditions. However,
grasses have limitations such as shallow root depths that reduce their effectiveness in
stormwater reuse. Therefore, some users may believe that some plants and shrubs may
be modeled better using an alfalfa reference ET. Alfalfa has a much deeper root system
than turf grass. Hence some plants and shrubs with deeper root systems could have the
ability to remove water held deeper in the soil than grass, increasing the storage
potential for a site as well as reducing losses from runoff.
348
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