LONG-TERM PHOSPHORUS LOADING FROM ONSITE WASTEWATER SYSTEMS TO SURFACE WATERS
A Dissertation Presented
By
Frank Leslie Schellenger, Jr.
to
The Department of Civil and Environmental Engineering
In partial fulfillment of the requirements for the degree of
Doctor of Philosophy
In the field of
Environmental Engineering
Northeastern University Boston, Massachusetts
May 2018
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ABSTRACT
Accelerated eutrophication caused by oversupply of nutrients from anthropogenic sources has impaired surface waters, especially lakes, in many places in the
United States and worldwide. Nitrogen and phosphorus oversupply to surface waters has frequently caused overgrowth of aquatic plants and blooms of phytoplankton (algae) that damage fisheries, recreation, and property values. In many surface waters, phosphorus is the “limiting” nutrient, without which this overgrowth or bloom does not occur. Efforts to prevent, remediate, and mitigate the effects of phosphorus oversupply generally focus on surface sources and transport pathways of phosphorus, but review of the research literature suggests that phosphorus transport from domestic onsite wastewater systems (OWSs) via groundwater has not been considered a significant source because of sorption, and this source is not effectively addressed in lake management. We hypothesize that, with increasing time-in-use of an OWS, phosphorus may be transported via the groundwater surficial aquifer to a down-gradient surface water in ecologically relevant amounts. Here we develop a model of this transport and quantify the total phosphorus load transported in a time-variable manner from all the OWSs in a watershed via the groundwater to surface waters, especially lakes. The results suggest that the phosphorus load from OWSs may be significant and should be considered in efforts to manage the effects of lake eutrophication. iii
DEDICATION
None of the work resulting in this dissertation would have been possible without the loving support of my wife, Eileen Penney, who selflessly supported me financially and emotionally throughout the several years it required. This dissertation is dedicated to her. I love you, Ei.
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PREFACE
My research was motivated by some experience as a Conservation
Commissioner in the town of Hanson, Massachusetts, USA. One of the principal duties of this municipal government position is to protect the surface water resources of the town from loss or deterioration due to human land-use and development. The town is home to a number of lakes, both natural and impounded, and shares several lakes with other towns. In the course of my tenure as a commissioner, I participated in an ad hoc committee to address the problem of eutrophication of Oldham Pond, a lake shared by Hanson and the neighboring town of Pembroke. The lake had been the subject of studies in the past to determine the sources and to estimate the loading of nutrients, especially phosphorus (P), which had caused annual algae blooms for several years.
Although these studies did not explicitly identify onsite wastewater systems
(OWSs) as a major source of P, OWSs were acknowledged as a potential source, if close to the lake and especially if in a “failed” state. Management efforts to remediate the condition of the lake by reducing the P load had been undertaken by Pembroke, aimed at stormwater run-off, and “failed” OWSs.
These efforts had not been too successful, as annual algae blooms continued.
The ad hoc committee was established to obtain participation in this effort by
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Hanson. Since I had prior experience as an OWS installer and inspector, I surmised that P loading from OWSs may not only be attributed to “failed” systems, but may come from working systems. I found that this view is not popular.
While enrolled at Northeastern University, I used Oldham Pond as a source of class projects. I prepared a lake water budget for one course, modeled the lake using Lake2K for another course, and used ArcGIS to view the groundwater contours around the lake in another. Research for these projects eventually led me to the USGS field study of the wastewater effluent plume from
Otis Air Force Base on Cape Cod (LeBlanc 1984). Here was an “Aha” moment: the phosphorus plume from the wastewater treatment sand filter beds had migrated 1700 feet in about 42 years (1936 to 1978), and was impinging on
Ashumet Pond in Mashpee and Falmouth, MA. I looked for other field studies that reported P transport from OWSs. Among these, research reported by people at Waterloo University in Ontario, Canada stood out. From these beginnings, this dissertation was born.
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ACKNOWLEDGEMENTS
Many people participated in the effort to bring this dissertation into being in one way or another. Special thanks are due to my advisor, Prof. Ferdi Hellweger, who patiently guided this effort, and to committee members Professors Phil
Larese-Casanova, Annalisa Onnis-Hayden, and Ed Beighley who agreed to review it.
Many others helped me along the way. The staff at the Hanson Health
Department, Theresa Cocio and Donna Tremontana, gave me unlimited access to the records of OWSs in the Oldham Pond watershed, and Lisa Cullity of the
Pembroke Health Department provided important data from Pembroke OWS records. Margaret Digiorno, Northeastern Class of 2016, deserves kudos for her
GIS work that led to Chapter 5, and Prof. Tess Russo of Penn State provided valuable data for that part of the research.
Several members of the Pembroke Watershed Association deserve mention: Patti and Chuck McCabe gave me unlimited access to the records of
PWA’s water quality sampling of Oldham Pond, and provided training in the sampling process and allowed me to come along. Sarah and Ken Trant allowed me to participate in the PWA sampling program for OP in 2013 and 2014. Ray and Betty Holman encouraged my research and kindly provided a reference to
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Northeastern. I am also happy to acknowledge my fellow commissioners on the
Hanson Conservation Commission, Phil Lindquist, Dave Harris, and John
Kemmett, and our very able administrative assistant, Becky Nehiley, who encouraged me along the way. Mr. Lindquist and our Conservation Agent, Rich
Vacca, kindly provided references to Northeastern.
Most of all, I wish to thank my loving family. My daughter, Alexandra, was my classmate, commuting companion, and lunchtime rummy opponent for four years as she earned her own Ph.D. in 2016, ahead of me. She is a constant inspiration. My wife, Eileen Penney, supported me in every way, including financially. Without her love and encouragement, this work would not have been done.
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TABLE OF CONTENTS
ABSTRACT …………………………………………………………………………….. ii
DEDICATION ………………………………………………………………………….. iii
PREFACE …………………………………………………………………………...… iv
ACKNOWLEDGEMEMTS …………………………………………………………… vi
TABLE OF CONTENTS …………………………………………………………..… viii
LIST OF TABLES …………………………………………………………………….. xii
LIST OF FIGURES ………………………………………………………………….. xvi
CHAPTER 1 Introduction …………………………………………………………... 1
CHAPTER 2 Literature Review………………………………………………...... 6
2.1 Introduction ………………………………………………………………...... 6
2.2 Field Research on Phosphorus Transport from Wastewater Infiltration Beds ……………………………………………………………… 7
2.3 Field Research on Phosphorus Transport from Individual Household OWSs ………………………………………………………….. 12
2.3.1 Research on Phosphorus Transport from OWSs at a Watershed Level …………………………………………………...… 12
2.3.2 Research on Phosphorus from Individual Household OWSs ….... 14
2.4 Conclusion ………………………………………………………………….. 26
CHAPTER 3 Model Development ……………………………………………….. 28
3.1 Introduction …………………………………………………………………. 28
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3.2 Conceptual Model …………………………………………………….…..... 28
3.3 Phosphorus Flow and Transport Equations and Analytical Solutions … 33
3.4 Phosphorus Loading Model ………………………………………...... 40
3.5 Trial Application of the Model ……………………………………………… 43
3.5.1. The Cambridge, Ontario site ………………………………………... 43
3.5.2 Dispersivities αx, αy, and αz …………………………………………... 44
3.5.3 Sorption Distribution Coefficient, Kd ………………………………… 48
3.5.4 Additional Parameter Estimates for Phosphorus Transport ……… 50
3.5.5 Phosphorus Loading ………………………………………………….. 52
3.6 Application of the 1-D Model to Other OWS Sites ………………………. 54
CHAPTER 4 Case Study: Oldham Pond ……………………………………….. 56
4.1 Introduction ………………………………………………………………….. 56
4.2 Phosphorus Loading from Onsite Wastewater Systems to a Lake (at Long Time Scales) ……………………………………………………… 59
4.2.1 Abstract ………………………………………………………………... 60
4.2.2 Introduction ……………………………………………………………. 61
4.2.3 Materials and Methods ………………………………………………. 63
4.2.3.1 Study Site ………………………………………………………. 63
4.2.3.2 Model Description ……………………………………………... 66
4.2.3.3 Model Inputs ………………………………………………….... 70
4.2.4 Results and Discussion ……………………………………………... 71
4.2.4.1 Time series of P loading to the lake ………………………… 71
4.2.4.2 Relation to trophic state and other loading estimates …….. 74
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4.2.4.3 Parameter sensitivity analysis and uncertainty (Monte Carlo) analysis …………………………………………………... 77
4.2.4.4 Effect of vadose zone immobilization and travel time ……… 77
4.2.4.5 Effectiveness of past and potential future management actions …………………………………………………………..... 78
4.2.4.6 Relation to Other Studies ……………………………………… 80
4.2.4.7 Management perspective ……………………………………... 80
4.2.4.8 Outlook ………………………………………………………….. 81
4.2.5 Acknowledgments ………………………………………………….... 82
4.2.6 References …………………………………………………………… 82
4.2.7 Supplement to Paper: Phosphorus Loading from Onsite Wastewater Systems to a Lake (at Long Time Scales) ………….. 82
4.2.7.1 Contents ………………………………………………………... 82
4.2.7.2 Accounting for Time-variable Source Function Using Superposition …………………………………………………… 84
4.2.7.3 Model inputs ……………………………………………………. 85
4.2.7.4 Illustration of Model Behavior ………………………………… 91
4.2.7.5 BEC (1993) P Loading Calculation and Revised Loading Calculation ……………………………………………………… 92
4.2.7.6 Parameter sensitivity analysis and uncertainty (Monte Carlo) analysis …………………………………………………. 96
4.2.7.6.1: Parameter sensitivity analysis …………………………. 96
4.2.7.6.2 Uncertainty (Monte Carlo) analysis using the local ranges …………………………………………………….. 98
4.2.7.6.3 Uncertainty (Monte Carlo) analysis using the literature ranges …………………………………………. 98
4.2.7.7 Supplement References …………………………………….. 101
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Appendix 4.1 Visual Basic Module Used in the Excel Calculations ……... 102
CHAPTER 5 Application of the Model at a National Level (NatMod) ……. 107
5.1 Introduction ………………………………………………………………... 107
5.2 Method and Procedures …………………………………………………. 108
5.2.1 Watersheds ………………………………………………………….. 109
5.2.2 Distance to Surface Water ……………………………………….... 110
5.2.3 Constant Parameters ……………………………………………..... 112
5.2.3.1 Hydraulic Conductivity, Hydraulic Gradient, and Effective Porosity Parameters ………………………………………..... 114
5.2.3.2 Non-sewered Population ……………………………………... 117
5.2.3.2.1 Estimating Non-sewered Population for decades 1970-90 .. 118
5.2.3.2.2 Estimating Non-sewered Population for decades other than 1970-90 …………………………………………………… 119
5.2.3.2.3 Combining Non-sewered Population to HUC12 Watersheds …………………………………………………….. 121
5.2.4 Time …………………………………………………………………. 122
5.3 Results………………………………………………………………………….. 123
5.3.1 National Level Results ……………………………………………... 123
5.3.2 Results at the Regional Level ……………………………………... 128
5.3.3 Example Regional Results: Maumee River Basin ………………. 130
5.4 Conclusions ……………………………………………………………………. 134
Appendix 5.1 Flow Charts for Procedures Used to Determine x, Ks, i, n, and Population by HUC 12 ……………………………………………………….. 136
CHAPTER 6 Summary …………………………………………………………... 138
REFERENCES …………………………………………………………………….. 142
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LIST OF FIGURES
Chapter 3: Model development
Figure 3.1: Schematic View of a Typical, Conventional OWS ………………….. 29
Figure 3.2: Na+ concentration along the plume core at Cambridge, Ont. 10 years after OWS installation; field measurements by Robertson et al. (1991), and model curves by 3-D and 1-D analytical solutions ………………46
Figure 3.3: Na+ loading at the plume front at Cambridge, Ont. 10 years after OWS installation; model curves by 3-D and 1-D analytical solutions ………………………………………………………………………….. 47
Figure 3.4: Phosphorus Concentration vs. distance from the SAS, measured and modeled, Cambridge, Ont. site. Model value of 3 Kd = 6.4cm /g. Data points from Table 3.2. Solid curves from the 1-D model results at 10, 17, and 20 years. Dashed curves from the 3-D model results …………………………………………………………… 49
Figure 3.5: Phosphorus loading breakthrough curves at various OWS ages, Cambridge, Ont. site. Curves are for 10 yrs, 20 yrs, 40 yrs (2017), 60 yrs, 80 yrs, and 100 yrs. Solid curves are the 1-D model results, and dashed curves are the 3-D model results ……………………… 52
Figure 3.6: Phosphorus Loading at 128 m from the SAS versus Time, Cambridge, Ont. OWS ………………………………………………………….. 54
Chapter 4: Case Study: Oldham Pond
Figure 4.1: Environs of Oldham Pond in Hanson and Pembroke, Massachusetts (from USGS topographical map, Hanover Quadrangle, Massachusetts – Plymouth County, 7.5 minute series, 2015) ……………………………………………………………………………… 56
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Figure 4.2: Oldham Pond Watershed, Pembroke and Hanson, Plymouth County, Massachusetts. All 859 OWS locations shown as green circles, and groundwater flow paths shown as red lines. Stippled polygons are wetlands or cranberry bogs …………………………………… 64
Figure 4.3: Model overview, illustrating the three stages of the model for a conventional septic system …………………………………………………… 66
Figure 4.4: Estimated total phosphorus loading to Oldham Pond from OWSs versus time, 1750 through 2750, and Monte Carlo uncertainty analysis. Triangles are loading estimates by Baystate Environmental’ Consultants, Inc. (BEC 1993) and Comprehensive Environmental Inc. (CEI 2011) respectively, and circles are adjusted values as described In the text and Supplement 4.2.7.5 …………………………………………... 74
Figure 4.5: Comparison of phosphorus loading by model stage ……………. 78
Figure 4.6: Comparison of model estimated phosphorus loading to estimates (1) if no laundry detergent phosphorus ban (blue dashed curve), (2) if All OWSs were built as cesspools (red dashed curve) and (3) if all OWSs were replaced by a sewer system and WWTP in 2030 (green dashed curve) ………………………………………………… 79
Figure 4.7: Sample loading calculation for a single OWS illustrating superposition. The OWS was installed as a CP in 1952 and replaced by a SS in 1986. Loading changed in 1994 with the laundry detergent phosphorus ban ………………………………………………………………… 85
Figure 4.8: Distribution of cesspool replacement dates for the Town of Hanson, MA, grouped by decade …………………………………………….. 87
Figure 4.9: Surface elevation vs. high groundwater elevation for test-pit data for OWSs in the Oldham Pond watershed …………………………….. 89
Figure 4.10: Determination of best-fit Kd, value, based on Ashumet Pond data (LeBlanc 1984, Walter et al. 1996) ……………………………………... 91
Figure 4.11: Loading curves for 5 sample OWSs with different life histories .... 92
Figure 4.12: Comparison of the Number of OWSs Contributing to Well P Concentration vs. the Number Contributing to LIP Sample P Concentration in 1988-9 at Oldham Pond …………………………………… 94
Figure 4.13: (A - E) Parameter sensitivity analysis. (F) Monte Carlo analysis using the literature ranges; upper and lower bounds are 95th and 5th percentile values ………………………………………………………. 99
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Chapter 5: Application of the Model at a National Level (NatMod)
Figure 5.1: Mean Euclidean Distance to Surface Water, x (m). Note that the State of Indiana has provided input to the USGS of a denser network of flowlines, which reduces the mean Euclidean Distance compared to the rest of the U.S. (USGS 2017) ……………………………. 111
Figure 5.2: Hydraulic Conductivity, Ks.(m/yr), based on the GLHYMPS Project (Gleeson et al. 2011, Gleeson et al. 2014, Russo, 2016) ……….. 115
Figure 5.3: Soil Effective Porosity, n, based on the GLHYMPS Project (Gleeson et al. 2011, Gleeson et al. 2014, Russo, 2016) ………………... 116
Figure 5.4: Mean Hydraulic Gradient, i, based on the GLHYMPS Project (Gleeson et al. 2011, Gleeson et al. 2014, Russo, 2016) ………………… 116
Figure 5.5: Average Percent of Households Sewered vs. the Logarithm of Population Density for U.S. Counties, 1970 – 90 ………………………. 120
Figure 5.6: Non-sewered Population (persons served by OWSs), by HUC12, 2010 ………………………………………………………………….. 122
Figure 5.7: Comparison of U.S. Population and Wastewater Phosphorus Loads (sources: population, U.S. Census; loads, this chapter results) …. 124
Figure 5.8: Estimated Total Phosphorus Load from OWSs to Surface Waters in the U.S. (Gg/yr) from 1790 ……………………………………….. 125
Figure 5.9: Estimated Phosphorus Loads from OWSs to Surface Waters in 2020, kg/yr/ha. Selected watersheds outlined in blue: see 5.3.2 and Table 5.2 text ……………………………………………………………... 126
Figure 5.10: Comparison of the Estimated National Phosphorus Load from OWSs to Surface Waters vs. (1) an Estimated Load if No Laundry Detergent P Ban were Implemented in 1994, and (2) an Estimated Load if OWSs were Replaced by Wastewater Treatment Plants by 2030 (Gg/yr) ………………………………………………………... 127
Figure 5.11: Estimated Total Phosphorus Load from OWSs to Surface Waters as a Percentage of 2002 SPARROW Estimated Total Load for Selected Watersheds ……………………………………………………... 130
Figure 5.12: (a) Maumee River Basin Major (HUC8) Watersheds. (b) Maumee River Basin: 252 HUC12 Watersheds; Major Watersheds (HUC8) outlined in red …………………………………………. 131
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Figure 5.13: Estimated Total Phosphorus Load from Onsite Wastewater Systems to Surface Waters in the Maumee River Basin, in kg/yr and kg/ha/yr ……………………………………………………………… 132
Figure 5.14: Estimated Total Phosphorus Loads from OWSs to Surface Waters in 2020 for the Maumee River Basin (kg/ha/yr) …………………… 133
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LIST OF TABLES
Chapter 3: Model Development
Table 3.1: Na+ concentration vs. distance from the SAS, Cambridge, Ont. site (data adapted from Robertson et al. 1991) ………………………… 45
Table 3.2: Phosphorus concentrations in the septic system plume vs. distance from the SAS, Cambridge, Ont. site (Robertson et al. 1991, Robertson 1995, Robertson et al. 1998, Robertson 2003) …………………. 48
Table 3.3: Values of variables and parameters for the Cambridge, Ont. site. (References as noted.) …………………………………………………………. 51
Chapter 4: Case Study: Oldham Pond
Table 4.1: Parameter values ……………………………………………………….. 72
Table 4.2: Flow, P Concentration, and P Load, Oldham Pond, 1987-8. Modified from BEC (1993) ……………………………………………………… 95
Chapter 5: Application of the Model at a National Level (NatMod)
Table 5.1: Values of Constant Parameters used in the Phosphorus Loading Calculations …………………………………………………………………….. 113
Table 5.2: Regional Watersheds and Total Phosphorus Loads as estimated by the SPARROW model (SPARROW no date). Note: SPARROW 2002 loads were obtained from the decision support system at the referenced website. The DSS was discontinued in July 2017 …………………………. 129
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CHAPTER 1
Introduction
The ecology of surface waters relies on the existence of plant life, including aquatic plants (macrophytes) and phytoplankton. This plant life requires nutrient elements and other compounds in the water column or bottom sediment.
Among the necessary nutrients, nitrogen and phosphorus generally control the amount of plant life, by being in more or less short supply compared to other required nutrients. In nature, supply of nutrients to surface waters is controlled by weathering and decay of natural materials, and the nutrients are carried to the surface waters by run-off of precipitation or infiltration to groundwater that then discharges to the surface waters. Over-supply of nutrients, or eutrophication, causes over-growth of plant life, especially blooms of phytoplankton, popularly called algae. Such over-growth affects the ecology of surface water bodies, usually for the worse. From the human standpoint in particular, harmful algae blooms caused by over-supply of nitrogen and/or phosphorus, adversely affect fisheries, drinking water supplies, and recreation.
My research focuses on the nutrient phosphorus (P). This element is necessary for all living things, including the plants and algae growing in a water body. Although many other elements are also necessary, including nitrogen,
2 they are generally sufficiently available in inland freshwaters. In contrast, phosphorus is not naturally available in over-supply, so it is most often the
“limiting” nutrient, without which the over-growth of plants and summer algae blooms do not occur. My research was initially motivated by the eutrophication problem as observed in the local southeastern Massachusetts and Cape Cod area. Here are found many lakes and their tributary streams that are being over- supplied with phosphorus and exhibit annual over-growth of aquatic plants and blooms of algae.
The natural process of eutrophication is slow – the supply of phosphorus to a water body may take millennia. The current eutrophication problems have arisen because of the way people interact with the environment. Aside from the natural inputs, the principal sources of phosphorus supplies to surface waters stem from the ways people use fertilizer and pesticides, dispose of wastes and wastewater, and manage stormwater. Many research studies have addressed the sources of phosphorus and its transport to a water body. These sources include decaying vegetative debris, animal waste, human waste, roadway dirt, fertilizers and pesticides, and others. Transport pathways include point sources
(outfalls) of wastewater and stormwater; surface runoff of stormwater or irrigation water; groundwater flow, including infiltrated water; and atmospheric particle deposition. According to most studies, point sources and surface runoff account for the greatest transport of phosphorus. Once the phosphorus is in the surface water body, especially a lake, recycling from the bottom sediment may have a role in transporting phosphorus to the water column.
3
In many watersheds, the anthropogenic sources supply most of the phosphorus to surface waters and enhance eutrophication and the attendant plant life over-growth. In rural areas, phosphorus from agriculture dominates, and over-supply of phosphorus to surface waters is related to fertilizer use and management of animal wastes. In urban and suburban areas, population drives the phosphorus supply, which is dominated by wastewater disposal and stormwater runoff from impervious surfaces. Many watersheds have a combination of rural and urban sources of phosphorus. Local efforts to prevent, remediate, and mitigate eutrophication and its effects often address point sources and surface runoff and have varying degrees of support and success, but in general are not very effective over time.
Groundwater transport of phosphorus to surface waters is rarely considered, because past research studies have concluded that phosphorus does not move very far or very fast in soils. Consequently, few prevention, remediation, or mitigation measures for groundwater phosphorus transport have been developed. My research is aimed at revisiting the groundwater transport of phosphorus, focusing on phosphorus that enters the groundwater from onsite wastewater systems (OWSs). We hypothesize that, at a watershed level, phosphorus from OWSs is being transported via groundwater surficial aquifers to surface waters in ecologically relevant amounts, and that OWS time-in-service
(age) is an important variable in phosphorus transport.
In Chapter 2 we review the research literature for studies of OWSs. As stated above, our focus is on the nutrient phosphorus, and on transport of
4 phosphorus to surface water bodies, especially lakes. Research has been done over many years to determine whether and to what degree phosphorus in OWS effluent is transported to the water table and then via the groundwater surficial aquifer to surface waters. The paradigm that phosphorus doesn’t move very far, very fast in groundwater is reviewed. Research that shows phosphorus in OWS effluent reached the water table and was transported by the groundwater surficial aquifer is highlighted. OWS age/time-in-service is also emphasized.
Chapter 3 presents a simple mechanistic model to estimate the total phosphorus load from an OWS to a point down-gradient in the groundwater surficial aquifer, for all times since the OWS began service. The model results illustrate that, over a long time, phosphorus from OWSs that enters the groundwater surficial aquifer may be transported down-gradient, and eventually to a surface water body.
Chapter 4 provides a case study in southeastern Massachusetts, USA that illustrates use of the model at the local watershed level. For many watersheds in southeastern Massachusetts and Cape Cod, and elsewhere in the world, the surface water body is a lake. Depending on the degree of development in the lake watershed, the cumulative phosphorus load transported from the many
OWSs to the lake can be a very significant part of the total load. Because many lake watersheds have been developed for a long time, these lakes may be experiencing higher phosphorus loads from OWSs than previously estimated.
The model developed in Chapter 3 is used here to estimate the total phosphorus load from OWSs to the lake via the groundwater surficial aquifer over a long time.
5
Emphasis is placed on using local data to determine values of the parameters required by the model.
Chapter 5 explores extending the use of the model to the national scale, evaluates the data available, and performs preliminary calculations. Although the methodology can readily be applied at the national scale, the uncertainty in the results is excessively large due to uncertainties in national-scale input datasets.
Conclusions and further research needs are discussed in Chapter 6, and all references are given in Chapter 7.
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CHAPTER 2
Literature Review
2.1 Introduction
Research has shown that phosphorus is the nutrient of concern in the eutrophication of inland, freshwater lakes where it is often the “limiting” nutrient, that is, the nutrient without which the aquatic plants and phytoplankton cannot grow and reproduce (Schindler 2006, 2012,). Thus, an oversupply of phosphorus may result in nuisance overgrowth of aquatic plants and/or algae blooms. Here, we consider the possible contribution of phosphorus in domestic wastewater transported via groundwater to the eutrophication of lakes.
Groundwater transport of wastewater effluent has been a subject of research for more than 50 years, and this research has largely been prompted by the fact that wastewater applied to the soil carries a heavy load of the nutrients nitrogen and phosphorus that contribute to eutrophication of surface waters. The underlying questions have always been: do the nutrients in the wastewater reach the groundwater, and if so, are they transported far enough to reach a surface water to which the groundwater discharges (Holman et al. 2008). In the case of nitrogen, the research conclusion is mostly “yes”, and has prompted management efforts to prevent and/or mitigate this nitrogen flux. In the case of
7 phosphorus, however, researchers have frequently concluded that soils will effectively immobilize wastewater effluent phosphorus in the unsaturated/vadose zone before the effluent reaches the water table and enters the groundwater surficial aquifer. Under certain conditions, some phosphorus may break through, but the saturated soils of the surficial aquifer will sufficiently retard the phosphorus so that it will not threaten a down-gradient surface water. This literature review revisits these conclusions about phosphorus transport.
Wastewater application to the soil is generally carried out in two ways: (1) by applying the effluent of a wastewater treatment plant to infiltration beds, and
(2) by applying the effluent from an onsite wastewater system (OWS), e.g. a septic tank or cesspool, to a soil absorption system (SAS). In Section 2.2 we review research on infiltration beds, and in Section 2.3, we focus on OWSs, with specific emphasis on individual household (domestic) OWSs. In both cases, we discuss reported research performed as field studies, including follow-up modeling efforts if relevant. Laboratory studies are treated only as necessary to elucidate the discussion.
2.2 Field Research on Phosphorus Transport from Wastewater Infiltration
Beds
Infiltration beds, whether used in conjunction with wastewater treatment plants or large OWSs, generally have a high loading rate and are much larger and deeper than the SASs of household systems. However, discussion of the
8 former is instructive, as research performed on infiltration beds provides substantial evidence of phosphorus transport in the groundwater surficial aquifer.
Research by the USGS at Joint Base Cape Cod, formerly the
Massachusetts Military Reservation, began in 1978 on the effluent plume from infiltration beds adjacent to Otis Air Force Base. These beds were used as secondary treatment of effluent from the base wastewater treatment plant.
Effluent application to the first beds began in 1936, and continued until 1995. By the mid-1970s, nitrogen contamination in a down-gradient drinking water well in
Falmouth, MA prompted a full-scale study of the effluent plume. Among the results, researchers found a phosphorus plume that stretched 1700 feet (518 m) to Ashumet Pond, a lake on the Mashpee/Falmouth town border (LeBlanc, 1984).
The surficial aquifer through which the groundwater moves is sand and gravel laid down during the glacier retreat about 10,000 years ago. The overlying unsaturated soil is also primarily sand. This sandy feature is common to southeastern Massachusetts and Cape Cod and to other regions worldwide.
Research at the Otis/Ashumet site continued for many years (Bussey and Walter
1996, Walter et al. 1996, Walter and LeBlanc 1997, McCobb et al. 2003), and the phosphorus transport was modeled (Stollenwerk 1996, Parkhurst et al. 2003).
Model results indicated that after use of the infiltration sand beds was discontinued in 1995, the phosphorus would continue to be transported toward
Ashumet Pond for decades, perhaps more than a hundred years (Parkhurst et al.
2003). This finding prompted the design of a reactive barrier to intercept the
9 plume in an effort to sequester the phosphorus (McCobb et al 2009, McCobb and
LeBlanc 2011).
Also in 1978, a study was conducted in Vineland, NJ of the movement of wastewater constituents from infiltration sand beds (Koerner and Haws, 1979).
These beds were used as secondary treatment of effluent from two adjacent wastewater treatment plants operated by the City of Vineland and the Landis
Sewerage Authority. The Vineland beds had been used since 1928, and the
Landis beds since 1948. The results showed that phosphorus had been transported down-gradient from these beds in concentrations higher than background. In the case of the Vineland beds, phosphorus was found in elevated concentrations about 1,000 m away, toward the Maurice River. The phosphorus plume from the Landis beds had reached the Parvin and Tarkiln branches, tributaries of the Maurice River, about 335 m away. An interesting conclusion of this research was that the surface waters (rivers) diluted the phosphorus to a concentration so low that there was little concern. We note that load is not the same as concentration; a low concentration in a large flow can be a large load. The terminal water body in the sub-watershed is Union Lake, in
Millville, NJ, and it seems likely the load of phosphorus to the rivers would likely enter the lake. Union Lake was known to be eutrophic in 1973, although the condition was not attributed to the Vineland and Landis infiltration beds (USEPA
1976).
Colman and Friesz (2001) studied the septic tank system that serves the public restrooms at Walden Pond, Concord, MA in 1988-9 and determined that
10 phosphorus had not reached the groundwater. The infiltration bed there had been in use for 25 years, with seasonal (primarily summer) loading and a depth to groundwater of 12 m. In a later modeling study, Colman (2005) based the model on the Otis AFB and Walden Pond studies. He posited a single sand bed with a 50 foot (15.24 m) unsaturated zone, and showed that phosphorus would enter the groundwater and be transported some distance over 50 years. After 50 years, model loading to the sand bed was ended, and the model results showed that phosphorus transport would continue for 200 years. Colman used a phosphorus concentration criterion to calculate the distance transported, and did not quantify the load transported.
The research by a Waterloo University group at Langton, Ontario, Canada in 1991 should be included in a discussion of sand beds (Harman et al. 1996;
Robertson and Harman 1999). There, a school had applied its septic tank effluent to an infiltration bed for 44 years. Loading to the system was “seasonal” in the sense of the school year. The results indicated that the efficiency of the sand bed was about 17%, and elevated phosphate levels were present 75 m down-gradient from the bed. The research team concluded that:
“The mobility of the phosphate plume at this site suggests that septic
-3 systems can be significant contributors of PO4 to nearby surface-water
bodies. These observations suggest that over time the capacity of soils to
attenuate septic system phosphate can be consumed, allowing phosphate
to advance at a slow but potentially significant rate.”
11
Continued research at the site after loading to the system was discontinued found that phosphorus continued to move in the groundwater surficial aquifer
(Robertson and Harman 1999).
Eveborn et al. (2012) reported on field studies conducted in Sweden
(dates not given) on four sand beds with ages 14 to 22 years, and estimated that phosphorus removal efficiency of the beds was 8 to 16%; the efficiency of one bed was determined to be 12% based on mass balance calculations of phosphorus retained in the bed. They concluded that:
“From a soil chemistry perspective there are reasons to be skeptical to
the widely held view of the large P removal capacity of STS [soil treatment
systems] since it needs ad hoc hypotheses to explain how sand- and
gravel-like materials can accumulate P well above their P sorption
capacity. …”
Their research did not include determination of phosphorus transport down- gradient, but the low infiltration bed efficiency implies that a significant phosphorus load likely reached the groundwater surficial aquifer.
Andres and Sims (2013) reported a 2008-9 field study of infiltration beds serving restrooms in a park in Delaware. The authors found phosphorus contamination of the groundwater after a little more than 25 years of use.
Concentration of orthophosphate in the groundwater approached the effluent concentration > 45 m down-gradient from the 8.5 m deep bed. This result may indicate that the ability of the sand beds to remove phosphorus from the effluent was exhausted, and that the efficiency therefore approached 0%.
12
The results of these field research studies on infiltration beds provide evidence that phosphorus is not completely immobilized in the unsaturated/vadose zone, and that phosphorus may reach the water table and be transported in the groundwater surficial aquifer. With sufficient time, the distance covered by this transport may reach a surface water body. In all these cases, however, the effluent loading rate was much higher than for an individual household OWS.
2.3 Field Research on Phosphorus Transport from Individual Household
OWSs
Research on household OWSs can be subdivided into two general approaches: (1) OWSs studied in the aggregate for an area, and (2) OWSs studied singly.
2.3.1 Research on Phosphorus Transport from OWSs at a Watershed Level
There are few examples of field studies of watersheds containing multiple OWSs. Among them are the following.
Vanek (1991, 1993) conducted a field study in 1989 and again in 1991 near Lake Bysjön and Vomb, Sweden. He found high concentrations of phosphorus in groundwater in the near-shore areas and littoral zone where the groundwater discharged to the lake, down-gradient from the village of Vomb, which was served by OWSs. These OWSs and adjacent agricultural fields were the only sources of phosphorus to the groundwater and were “… the most likely sources of groundwater-transported phosphorus …” to the lake.
13
Weiskel and Howes (1992) studied the impact of OWSs in a portion of the watershed for Buttermilk Bay, an estuary in Wareham and Bourne, MA in 1986-8.
This portion of the watershed included 524 households/OWSs. Using data from four (4) OWSs and several monitoring wells, they measured the transport of nutrients to the surface water, using a “streamtube” approach. They concluded that about 0.3% of effluent phosphorus reached the surface water body. Ages of the selected OWSs were 10 to 75 years, but their locations in the watershed were not clearly identified. However, Valiela and Costa (1988) performed a field study of Buttermilk Bay using a mass balance approach and calculated that 18% of the phosphorus load to groundwater from the approximately 2000 OWSs in the watershed reached the surface water body, and that this load (1,360 kg/yr) represented 75% of the phosphorus load to Buttermilk Bay.
A field study by Moore et al. (2003) in the Seattle, WA region reported that lakes having developed watersheds that were unsewered had higher incidence of eutrophication than lakes in sewered watersheds. The report did not explicitly address phosphorus transport as the cause, but one can infer that this cause was in play for these inland, freshwater lakes.
Jarosiewicz and Witek (2014) performed a field study of a small lake in
Poland (Boruja Mala Lake) in 2007-8. Phosphorus concentration measurements were taken in the lake littoral zone and in off-shore wells. The authors determined that groundwater was the largest source of nutrients. The source of high phosphorus in one area was thought to be OWS effluent from a Boy Scout camp.
14
Kang et al. (2005) concluded from a field study in 1998-9 that phosphorus influx from groundwater is a larger source of phosphorus to Lake Persimmon, FL than recycling from the bottom sediment, and that the latter is not a major source.
There was no indication, however, of the source of the phosphorus in the groundwater.
Meinikmann et al. (2015) performed a field study of groundwater transport of phosphorus to Lake Arendsee, in Germany. The authors did not determine the sources of phosphorus, but surmised that leaking sewer pipes and OWSs were possible culprits.
The above examples of field studies performed over an area/watershed provide some evidence of phosphorus transport via the groundwater surficial aquifer to a surface water body. Research that specifically implicates household
OWSs as a major watershed source of phosphorus to surface waters is rare, however. Most field research has been performed on single OWSs, and this research and researchers’ conclusions are reviewed below.
2.3.2 Research on Phosphorus from Individual Household OWSs
Before reviewing reports of single OWS field studies, it is appropriate to acknowledge some of the literature reviews that have been written over the 50 years or so that this research has been performed.
Dudley and Stephenson (1973) is valuable for the authors’ literature review: The authors reviewed Woodward et al. (1961), a Minnesota study that concluded system age and density were factors in groundwater contamination.
15
The authors also reviewed a Childs et al. (1974) field study of 11 systems near
Houghton Lake in Michigan and noted that 2 of the systems had significant down-gradient phosphorus transport. They also reviewed the Bouma et al.
(1972) field study and highlighted 5 systems in Wisconsin that had phosphorus
“enrichment” of groundwater at 3 sites. The authors’ conclusion: phosphorus contamination of groundwater is likely from septic systems that have a high water table, coarse sand soil, heavy system loading, and age.
Bicki et al. (1984) is a very detailed literature survey to 1984. Part 3.3 of their report deals with phosphorus from OWSs. Many papers are reviewed, including more than 40 field studies. Although many of the field studies report transport of phosphorus to the groundwater surficial aquifer and down-gradient, the general conclusion is that phosphorus does not move very far in most soils, unless the soil is coarse sand, or the water table is high, or the hydraulic loading rate is high. There is no consideration of system age, i.e. time in service, in this survey. Jones and Lee (1977) provide a literature survey that concludes that phosphorus does not move very far in soils below septic systems. The survey cites many of the same papers as Bicki et al. (1984) and provides more extensive summaries.
Reneau et al. (1989) is a literature review primarily focused on biological contaminants and nitrogen. The authors emphasized the efficacy of the unsaturated (vadose) zone for contaminant removal. Discussion of phosphorus indicated there is little transport (“except in a few isolated instances”), due to sorption and precipitation, with numerous references. Field study references are
16 few, however: Dudley and Stephenson (1973), Reneau and Pettry (1976), and
Jones and Lee (1977); all these field studies used OWSs of low ages (see below). The authors’ conclusion:
“Most field studies indicate that phosphorus contamination is limited to
shallow groundwaters …. More extensive phosphorus transport is
observed for coarser textured soils that are low in hydrous oxides or in
situations where there is both poor effluent distribution and rapid flow
away from the [OWS].”
Stolt and Reneau (1991) provided a literature review to 1991 with a heavy focus on nitrogen and pathogens. Review of phosphorus literature is in pp 66-83 of their report. Literature was surveyed separately for laboratory and field studies. Field studies reviewed included most of those addressed by earlier reviewers, with some later additions. This review does not address OWS age/time-in use. From the summary:
“In most soils in which Fe and AI are present in a reactive form, and flow
rates are minimal, P movement is minimal and concerns for pollution of
ground or surface waters from P applied in a OSWDS are unfounded.
Phosphorus pollution to the groundwater can occur in cases where the
water tables are near the surface, soils have coarse textures, flow rates
are increased due to strong soil structure, loading rates are high, soils
have a low P adsorption capacity, or when P capacity of a soil has been
met. The major factor contributing to P movement is the flow rate.
Increased flow rates are generally associated with soils of coarse textures,
17
strong structure or macro voids associated with biological activity, or high
water tables.”
Cardona (1998) reviewed a limited number (8) of phosphorus related field study references and asserted the usual conclusion that P does not move far in soils: “Phosphorus contributions to surface and subsurface waters from OSWS are minimal.”
USEPA (2002) is a very comprehensive document, with valuable advice.
Section 3 of their report discusses phosphorus transport, and much of the literature cited is also reviewed in the reports listed above. Phosphorus transport is acknowledged, but generally limited to coarse sands, high water tables, and high loading. This report addresses OWS density and ages as potential problems for phosphorus transport and acknowledges time as a contributor in limiting the effectiveness of soils for removing phosphorus.
Gill et al. (2004) is primarily a literature review describing OWSs and performance factors for soils in Ireland. Sorption and precipitation of phosphorus in soils and phosphorus retention are described. The general conclusion is that phosphorus is not a problem, with the usual caveat about proximity to a water body.
Beal et al. (2005) is a literature survey with emphasis on Australia. The authors reviewed mainly vadose zone studies; however, their Table 3 identifies groundwater plume studies. The report concluded there is little or no impact from phosphorus transport. The studies reviewed generally do not address system age.
18
Lewandowski et al. (2015) provide an extensive literature survey and bibliography on groundwater transport of nutrients, including phosphorus. Their objective was to show that groundwater transport of nutrients can be a significant source of these nutrients to surface waters. Although not specific to studies of
OWSs, a number of OWS field studies are cited as examples.
Turning to research studies on single OWSs, the work of the Waterloo
University group deserves special attention for their research at several sites in
Ontario, Canada. Besides their work at Langton cited in section 2.2 above, research was performed on an OWS over 10 years, from 1987 through 1997 at a
Cambridge, Ontario site in service from 1977 on. The OWS was sited in calcareous sand. The research team characterized the effluent plume and monitored the phosphorus concentrations in the groundwater down-gradient from the soil absorption system. Results indicated substantial phosphorus transport in the 20 years of operation. (Robertson et al. 1991; Robertson 1995; Robertson
2003). It will be instructive to return to Cambridge in Chapter 3.
Research on other single OWSs by the Waterloo University group was summarized by Robertson et al. (1998). The authors reviewed the field studies on eight (8) other sites (besides Cambridge and Langton, see above). Five of the eight had phosphorus plumes that had traveled a significant distance in the groundwater. Of these five, only one, Harp Lake, had been in use more than 20 years; this 29 year old OWS also had the lowest concentration of phosphorus reaching the water table. Soils at this site were identified as non-calcareous sandy till, and depth to the water table was about 1 m. Despite the high reported
19 efficiency of the unsaturated zone (about 99.7%), phosphorus was reaching the down-gradient lake at concentrations of about 0.1 mg/l. Load was not quantified.
The other four (4) OWS with significant plumes were sited in calcareous sand. One of these, Long Point 2, had only been in use for 6 years (Robertson and Harman, 1999). Further research at this site was performed, and at year 16, the plume had moved further down-gradient (Robertson 2008). The author attributed this result to the calcareous nature of the sand, which did not immobilize phosphorus by precipitation reactions, but retarded the phosphorus only by reversible sorption. This later research is significant for the author’s use of a one-dimensional analytical model for comparison to the field results. Using the model, the author determined that the phosphorus plume would reach Lake
Erie, 170 m down-gradient, in about 200 years. Phosphorus loading was not quantified, however.
In contrast to results of field studies on OWSs sited in calcareous sand, the Waterloo University group found that OWSs sited in non-calcareous sand retarded phosphorus more strongly. (See Harp Lake, above.) Research at a residential site near the Muskoka River, Ontario (Robertson et al. 1991;
Robertson et al. 1998; Robertson 2003) found that a phosphorus plume in the groundwater had not been established by year 10 of use. It should be noted that the vadose zone at Muskoka was about 3 m of fine, silty (13% silt) sand.
Phosphorus retention in the vadose/unsaturated zone was attributed to acidic soil conditions that allowed phosphorus precipitation reactions with Fe and Al. A study by Zanini et al. (1998), explored this idea in depth, using four (4) Ontario
20 sites (Cambridge, Muskoka, Langton, and Harp Lake) previously studied. The conclusion was reiterated in the report of research at a 20 year old Parry Sound,
Ontario site (Robertson, 2012). This phosphorus retention mechanism has been often cited in later research literature in support of the conclusion that phosphorus from OWSs is not a problem.
Wall and Webber (1970) reported a field study of 11 OWSs near Canal
Lake, Ontario. The report is primarily aimed at providing a suitability index for soils for siting septic systems. However, the field data for phosphorus are given for 10 sites, all seasonal use cottages near the lake, and unoccupied at the time
(1968). The results showed some phosphorus transport to the groundwater, but there was no indication of distance down-gradient. Depth to groundwater was ≤
36 in (< 1 m). Soils were various, and calcareous. The ages of the OWSs were not given.
NY Dept. of Health (1972) reported on a field study of six (6) OWSs on
Long Island to determine the pollution effects of different detergent surfactants.
The OWSs ranged in age from 1-10 years. Phosphorus transport down-gradient was found in all but the youngest system. Soils were glacially deposited sand, fine to coarse. Depth to the water table varied, with 2 cases of cesspools in the water table. This report is cited by others (e.g. Jones and Lee 1977, Bicki et al.
1984) as showing that phosphorus does not move very far in soils, but that conclusion is not supported by the report.
Bouma et al. (1972) reported a field study of 25 OWSs in Wisconsin.
Eight (8) of the systems showed some phosphorus transport down-gradient in
21 the groundwater. The range of system ages was 0-12 years except for one system that was 19 years old. This study focused on removal of pathogens and the properties of soils suited to that purpose. No conclusions about phosphorus transport were given.
Childs et al. (1974) provided phosphorus plume data for five (5) OWSs near Houghton Lake, MI where phosphorus transport down-gradient was shown.
Ages of the OWS were 10 to 20 years. This paper suggests there are concerns about plume characterization in most other field studies, because the effluent plume may not follow the regional groundwater flow.
Dudley and Stephenson (1976) reported a field study of 11 OWS sites in
Wisconsin in 1971-3; system ages ranged from 0 to 11 years in 1971. The authors observed significant phosphorus transport to the water table and down- gradient for 4 systems in medium to coarse sand with depths to the water table greater than 10 feet. Their conclusion: OWS in coarse sand or having a high water table may cause groundwater contamination by phosphorus. They made a passing mention of system age as a factor.
Sikora and Corey (1976) performed an assessment of nitrogen and phosphorus transformations in the SAS unsaturated/vadose zone of OWSs. The phosphorus discussion is focused on the SAS unsaturated/vadose zone and relies on the work of others, primarily column studies (not reviewed here). Much of the discussion addresses calcareous soils and “high” phosphorus concentrations (as found in OWS effluent). The study did not include transport of phosphorus below the water table. Their conclusion:
22
“… problems with P contamination of ground water would be expected
primarily with very “clean” sandy soils, soils with high water tables or
shallow soils over creviced bedrock, and even on most of these soils the
contamination would probably not become apparent until the soil
absorption field had been in operation for a number of years.”
Eveborn et al. (2012) note that this paper is the source of the claim in USEPA
(2002) that 85 to 95% of phosphorus is removed in the vadose zone. (See
Eveborn et al. (2012) above for a dissenting view).
An oft-cited report by Reneau and Pettry (1976) reports field studies of two
(2) OWSs of ages 15 and 4 years in Chesterfield County, VA. Some down- gradient data were taken over a three year period and showed little phosphorus transport from either system. Most data, however, was taken in the vadose zones where phosphorus fractions in the soil were determined. It is not clear that all the phosphorus in the effluent from the septic tanks is accounted for in the data. Despite the fact that a substantial amount of phosphorus was found in the soil below and adjacent to the SAS, one should account for any phosphorus that was in the effluent that is not in that soil over the service life of the OWS.
Viraraghavan and Warnock (1976, a and b) performed a field study in
1972-4 on a household OWS near Ottawa, Ontario, Canada, primarily to determine the efficiency of the OWS unsaturated zone, using an “experimental”
SAS added to an existing SAS. Lysimeters were used to collect effluent below the SAS. The efficiency of phosphorus reduction achieved in this 2 year study was not high: 25 – 50%, although a fluctuating water table was an important
23 factor. Down-gradient transport of phosphorus was not addressed.
Sawhney and Starr (1977) performed a field study in 1975-6 of effluent and phosphorus movement from a 6 year old OWS. The system was unique in that the SAS consisted of two trenches which could be alternately loaded with effluent from the septic tank. The study was limited to the vadose zone of a
“rested” trench. The authors concluded that:
“…a soil with a deep water table below the drainfield should effectively
renovate wastewater effluent for a number of years and should permit only
minimum additions of phosphorus to the groundwater.”
Jones and Lee (1977, 1979) reported a 1972-6 field study in Burnett
County, WI of a single septic system over the first four years of use, by 2 persons, 9 mos of the year. The authors reported no movement of phosphorus down-gradient. This study is often cited and has been influential in supporting the conclusion that phosphorus transport from OWSs to surface waters is not a problem.
Rea and Upchurch (1980) reported a field study of a 50 year old OWS near White Trout Lake, FL. Phosphorus transport >1 mg/l was >15 m down- gradient in fine to very fine sand with 0.7 to 4% clay. The phosphorus had not yet reached the lake, 34 m away. Clearly, retardation of P was high in this case.
The authors caution that soil heterogeneities cause changes in the shape and position of the plume that are not reflected in a single plume down-gradient model.
24
Gilliom and Patmont (1983) performed a field study of phosphorus transport from eight (8) near-lake septic systems in Washington that addressed septic system age. The OWSs studied were in use 20-40 years. Data was taken in the first 3 months of one year (1981). It isn’t clear that the septic system plume centerlines were intersected. Phosphorus was assumed to move at the same velocity as the groundwater. Distances to the sampling wells were 10 to
50 meters. The authors reported that less than 1% of effluent phosphorus moved to the wells, except for one system that had surface breakout. We note that 1% was still a lot (0.150 mg/l average). The phosphorus movement was in seasonally saturated soil below the OWS, in perched groundwater.
Whelan and Barrow (1984 a and b) reported a field study of phosphorus movement in the vadose zones of seven (7) OWSs near Perth, Australia. Ages of the OWS studied ranged from 4 to 40 years. The authors found higher phosphorus concentrations deeper in the unsaturated zones of older OWSs.
They estimated phosphorus would reach the groundwater at the same concentration as the incoming effluent within a few years of installation of an
OWS in the soil studied (coarse, non-calcareous sand) and that “…within a period of a few years after installation, most of the phosphate discharged from septic tanks in the Perth area moves into the groundwater”. No measurements were made of down-gradient transport.
Alhajjar and Harkin (1985) described field studies in Wisconsin on 17 very young OWSs (ages 0-5 years). The study compared the performance of OWSs for households using phosphate laundry detergent (8 systems) and for
25 households using phosphate-free detergents (9 systems). They reported no phosphorus was transported to the groundwater from any of the OWSs. They concluded that no phosphorus ban is needed in areas served by OWSs, and
“… properly functioning septic systems are not a source of P to
groundwater, are not a biological nuisance, and do not contribute to lake
eutrophication”
Chen (1988) reported on groundwater sampling of 17 near-lake OWSs for
8 lakes in New York State. Results showed that phosphorus concentrations were higher than background in many of the samples, up to 100 feet (30.5 m) from the systems. The systems were in various soils and slopes. No system age data were given.
Postma et al. (1992) reported a field study of three (3) seasonally used
OWSs near Charlestown, RI. The ages of the systems were 7-10 years, and were used only in the summer. The authors reported “minimal migration” of phosphorus, although wells at 6 m showed significant phosphorus concentrations, and no measurements were taken at greater distances. It is not clear that the plumes were completely characterized by the wells around the
OWSs. Retardation of phosphorus was evident, but not retention over time.
Corbett et al. (2000) and Corbett et al. (2002) reported a field study of three (3) OWSs on St. George Island, Florida, a barrier beach, and provided data for phosphorus transport. Ages of the 3 systems studied were < 2 years, but
“significantly elevated” levels of phosphorus were observed down-gradient “at wells beyond 50 m from the drainfields”.
26
Humphrey and Driscoll (2011) reported on a year-long field study (2007-8) to measure phosphate and coliform bacteria from 16 OWSs to groundwater in
-3 Carteret County, North Carolina. Elevated levels of PO4 were found in groundwater below 8 OWSs sited in sand. Ages of the OWSs were not reported.
2.4 Conclusion
This literature review of field research highlights the fact that phosphorus transport in OWS effluent depends on many site-specific factors. For example, phosphorus retention in the unsaturated/vadose zone of an OWS by sorption and precipitation depends on effluent chemical properties, effluent loading rate and frequency, soil chemical and physical properties, depth of the unsaturated zone, and perhaps other factors. Over many years of field research on individual household OWSs, researchers have concluded that phosphorus will be immobilized by most soils unless the effluent loading is high, the sand is coarse, the depth to the water table is short, and the surface water body is close. Some of the conclusions of these studies have been cited numerous times, and summarized in several literature reviews, and have had a large impact on OWS design and regulatory requirements. Most of this research has been performed on OWSs that were in use for only a relatively short time, and this fact is relevant to the development of the paradigm. Phosphorus may be highly retarded in the unsaturated/vadose zone, and phosphorus may not appear at the water table for some time. Reports of research on older OWSs generally show some phosphorus breakthrough to the surficial aquifer and transport down-gradient.
27
Yet, even for “young” OWSs, cases of phosphorus breakthrough and transport down-gradient have been reported. It seems reasonable to conclude that time is on the side of phosphorus movement in soils, and that eventually, as OWS age/time-in-service increases, some phosphorus will reach the water table and then be transported in the groundwater surficial aquifer to a surface water body.
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CHAPTER 3
Model Development
3.1 Introduction
In order to estimate the load of phosphorus from the OWSs in a watershed to a surface water body via the groundwater, a simple mathematical model of phosphorus transport in the surficial aquifer is desirable. Here, we use a one- dimensional solution to the advection-dispersion-retardation equation (see
Schnoor 1996, Domenico and Swartz 1990) with constant parameters as the model. We chose this model in lieu of a numerical model such as PHAST
(Parkhurst et al. 2003, Colman 2005) because the data requirement is commensurate with available data for the study site. We apply the model to a well-studied OWS in Cambridge, Ontario, Canada (Robertson et al. 1991,
Robertson 1995, Robertson et al. 1998, Robertson 2003) to illustrate its use.
3.2 Conceptual Model
Effluent from an OWS is discharged to soil and infiltrates to the groundwater. A typical OWS is shown schematically in Figure 3.1. Many conventional systems are fed by gravity, with blackwater (toilet waste) and greywater (laundry, dishwasher, bath and other drains) collected from various
29 sources in the building and directed to a septic tank buried outside the building.
There, heavier solids settle to the bottom, and lighter solids float to the top as scum. Between these layers is wastewater containing dissolved species and suspended solids, some of which settle during the retention time in the tank. The environment in the tank is anaerobic, and solids are digested over time by microbial action, or removed by periodic maintenance. Liquid effluent flows intermittently from the tank (as wastewater is added to the tank, an equal volume of liquid effluent flows out).
The effluent leaving the septic tank moves through a distribution box to the soil absorption system (SAS). There are a number of variations of the conventional system. Effluent may be distributed to pipes in trenches, or in a
“field” arrangement. In some cases, the effluent is distributed to chambers rather
Septic Tank Soil Absorption System (SAS) and Unsaturated (Vadose) Zone Water Body
Effluent Plume
Flow Direction Groundwater/Aquifer (Saturated Zone)
Bedrock/Aquaclude
Figure 3.1: Schematic View of a Typical, Conventional OWS.
30 than pipes, and the chambers may be set in trenches or in a “field” arrangement.
Some OWSs distribute effluent to “drywells”, usually circular pits with open bottoms and perforated barrel. Some OWSs route the effluent from the septic tank to a pump chamber and dose it to the SAS by pumps. Early OWSs did not use a septic tank, but route the wastewater to a cesspool, from which the effluent flows from the open-work sides. In all these variations, however, the end result is effluent applied to the soil of the SAS.
As it enters the SAS. the effluent encounters a “biomat”, where microbes are acting on dissolved and suspended organic matter. The biomat is a thin layer of dense, biologically active matter that prevents the effluent from infiltrating quickly. In theory, once the OWS is mature, this biomat ensures that the effluent is spread over the entire SAS area, suspended solids are trapped, and microbes have the opportunity to digest more of the dissolved species and trapped solids.
Once through the biomat, the effluent infiltrates vertically through an unsaturated zone of soil, called the vadose zone, primarily sand, but often including some silt and clay. The vadose zone is normally aerobic, and treatment of the effluent includes oxidation reactions that remove most enteric bacteria, viruses, and many organics not trapped in the biomat. Depending on the soil content of metal hydroxides, the vadose zone is also where some of the phosphorus is sorbed and where some may be precipitated, thereby preventing it from reaching the water table. The treated effluent then reaches the water table, where it enters the surficial aquifer, also called the saturated zone. Dissolved nutrients and other
31
constituents remaining in the effluent enter the surficial aquifer/saturated zone and are transported down-gradient by the movement of the groundwater.
The total phosphorus concentration in the effluent from the septic tank to the SAS is designated Ceff. The effluent may contain dissolved inorganic and organic phosphorus compounds as well as suspended solids containing phosphorus. Ceff depends on a number of factors including the amount of phosphorus contributed via blackwater and greywater streams, as well as the biological conversion of organic phosphorus compounds in the solid waste in the septic tank. Thus, Ceff is highly variable because of the number of household occupants and their water use habits, which in turn affects the residence time of the wastewater and solids in the tank. The effluent phosphorus concentration
-3 (PO4 as P) has been found to range from 1.2 to 21.8 mg/L, with a median of 9 mg/L and an average after 1990 (i.e. post – phosphate laundry detergents) of 8.4 mg/L (McCray et al. 2005). Research has shown that 85 – 90 % of the effluent
-3 phosphorus is dissolved, inorganic orthophosphate, PO4 (McCray et al. 2005), and since we use total phosphorus in the model, we divide the McCray et al
(2005) values by 0.875, the mid-point of the range.
For the purpose of the model, the concentration of phosphorus that reaches the water table is designated Co, and Co < Ceff. Co depends primarily on the soil properties and the depth of the unsaturated/vadose zone of the SAS. We define the “efficiency” of this zone as:
= (Ceff – Co) / Ceff Eq. 3.1
Research has shown that phosphorus may be strongly retarded by sorption and,
32 to some extent, by precipitation, in the vadose zone (Robertson 1995, Zanini et al. 1998, Robertson 2012). The efficiency of phosphorus immobilization in this zone has been reported to be as high as 99% for some soil conditions and vadose zone depths. The range, however, is very wide, with reported lows of
<12% (Robertson et al. 1991, Eveborn 2012). Heufelder and Mrockza (2006) have summarized the factors that affect the concentration of phosphorus that reaches the water table. Their research at the Massachusetts Alternative Septic
System Testing center in Barnstable, Massachusetts used typical septic system designs with the SAS in sand typical of southeastern MA and Cape Cod. They determined that an average of 47% of the phosphorus in the effluent from the septic tank reached the water table when the vadose zone depth was 5 feet (1.5 m), the minimum requirement for most Massachusetts septic systems. Depths greater than 5 feet can be expected to have greater efficiency, and conversely, the efficiency can be expected to be less for depths less than 5 feet. In addition, the efficiency of an OWS that uses a cesspool is considered to be less than that of a conventional septic system because the bottom of the pit is likely closer to the water table.
Co is assumed to be a constant step input to the surficial aquifer/saturated zone, which requires the further assumption that the OWS has been in use long enough to have reached a steady state. “Steady state” is said to exist when phosphorus sorption and precipitation reactions are retarding phosphorus at a rate that allows the same concentration Co to reach the water table at all times
33
(Robertson et al. 1991, Robertson 1995, Beal et al. 2005). See the further discussion in section 3.3, below.
Once in the surficial aquifer, the effluent is advected in the direction of groundwater flow, as well as dispersed in all three directions, horizontal, vertical, and transverse to flow. Again, depending on the soil properties, phosphorus will be retarded by sorption. In this conceptual model, the surficial aquifer is unconfined, saturated sand and gravel, with some silt and/or clay, and the aquifer is underlain by an aquaclude, usually bedrock, but sometimes dense silt, clay, or glacial till that is much less permeable than the sand. This type of aquifer is common in southeastern Massachusetts and Cape Cod, other parts of the U.S., and other places in the world, especially where the soil is glacially derived.
3.3 Phosphorus Flow and Transport Equations and Analytical Solutions
Groundwater movement in the surficial aquifer is characterized by an average pore water velocity, designated by u. The velocity of the groundwater may have components in all three directions: horizontal (ux), transverse (uy), and vertical (uz), and the horizontal component is chosen to be in the down-gradient direction. This horizontal component is generally much larger than the other two, and dissolved constituent transport is therefore primarily down-gradient. The forcing function for groundwater movement is the hydraulic gradient, the difference in head between locations. Advection is the term used to describe flow forced by the hydraulic gradient. The groundwater velocity is determined using the Darcy equation, in the form:
34
u = Ks × i / n Eq. 3.2 where Ks is the saturated hydraulic conductivity of the soil in the aquifer, i is the hydraulic gradient (slope of the water table) between the SAS and some down- gradient point, and n is the effective porosity of the soil (Freeze and Cherry
1979). Although all the terms in this equation may vary in three dimensions, the model assumes there are no components of velocity in the transverse and vertical directions.
Once the effluent plume enters the aquifer, it is subject to dispersion. An important driver of dispersion is the requirement that different small elements of the liquid must travel different paths around soil particles. Travel paths of different lengths tend to make the plume spread in the principal advection direction, i.e. down-gradient. Travel paths that lead away from this direction tend to make the plume spread in the lateral and vertical directions. Dispersion is characterized by a soil property called dispersivity, designated by α. Like the groundwater velocity, dispersivity has components in three dimensions. In a sand aquifer, the component in the down-gradient direction (αx) is much larger than the lateral (αy) or vertical (αz) components (Robertson et al. 1991, LeBlanc 1984,
Garabedian et al. 1991).
Because phosphorus is subject to retardation by sorption to the soil, this process must be accounted for in any mathematical formulation of flow and transport. Many studies of phosphorus retardation are performed using laboratory columns in batch tests that measure phosphorus amount adsorbed by the soil vs. amount of phosphorus transported through the column by the pore
35 water. The resulting plot is a sorption isotherm, and a curve is fitted to the data.
For low phosphorus concentrations, the relationship is frequently found to be linear: S = Kd × C, where S is the amount adsorbed, mg P/kg soil, C is the aqueous concentration, mg P/l, and the constant slope, Kd has the units l/kg soil
3 (cm /g soil). Kd is called the linear sorption distribution coefficient. For higher phosphorus concentrations, a non-linear model (e.g. Langmuir, Freundlich) must be chosen (McCray et al. 2005), which would require a numerical solution to the flow and transport equation. Our model uses the linear model, on the assumption that the phosphorus concentration in the groundwater is sufficiently low. Kd is an important parameter. Values of Kd from batch sorption tests vary widely, and depend strongly on soil properties. In general, tests of the local soils are required for research in a given geographical area. On the other hand, Kd may be obtained for a field study by observing the retardation of phosphorus in an effluent plume. The usual method is to treat Kd as a fitting parameter, and use measured phosphorus concentration data from the effluent plume to determine a
“best fit” value of Kd for the phosphorus breakthrough curve using the solution to the flow and transport equation. (We illustrate this method in section 3.5.3, below.) When batch sorption tests of the local soil or field phosphorus concentration data are not available, a value of Kd must be assumed based on literature values determined by research in soils elsewhere. This value is highly uncertain, and is likely a large source of error in flow and transport calculations.
The flow and transport process can be described using the advection- dispersion-retardation (ADR) equation (e.g. Schnoor 1996, Domenico and
36
Schwartz 1990). The equation in three dimensions (3-D) is:
¶C u ¶C u a ¶2C u a ¶2C u a ¶2C = - x + x x + x y + x z Eq. 3.3 ¶t R ¶x R ¶x2 R ¶y2 R ¶z2
K r where: R =1+ d b Eq. 3.4 n where C is the concentration of the contaminant of interest (phosphorus) in the groundwater, t is time, ux is average pore water velocity, x is distance from the effluent source in the direction of groundwater flow, R is retardation, ρb is the soil bulk (dry) density in the saturated aquifer, and n is the effective porosity. This version of the 3-D ADR equation is based on the assumptions that (1) there are no transverse (y) or vertical (z) components of the average pore water velocity;
(2) dispersivities αx, αy, and αz are constant; (3) we ignore possible reactions of dissolved phosphorus as it moves in the saturated zone, for example, a chemical reaction that removes phosphorus from the aqueous solution.
If we assume there is no dispersion in the transverse (y) or vertical (z) directions, the 3-D ADR equation reduces to a one-dimensional (1-D) equation:
¶C u ¶C u a ¶2C = - x + x x Eq. 3.5 ¶t R ¶x R ¶x2
Here we present analytical solutions for both the 3-D and 1-D ADS equations. As noted above, the effluent reaching the water table/aquifer below the SAS is considered to enter the water table as a continuous step input with phosphorus concentration Co. The boundary conditions for a continuous step input are (Schnoor 1996):
37
1. C = Co at x = 0 and t ≥ 0. x = 0 is in the aquifer directly below the edge of
the OWS soil absorption area on the down-gradient side (in the direction
of groundwater flow). Time t = 0 is when use of the OWS begins, assumed
to be when it is installed. Co is the total dissolved phosphorus
concentration in the effluent when it reaches the water table from the
vadose zone, and is assumed to be constant, that is, the system is at
steady state.
2. C = 0 for x ≥ 0 and t = 0, that is, there is no phosphorus concentration in
aqueous solution in the aquifer down-gradient from the septic system
before the septic system is installed. If there is a background phosphorus
concentration in the aquifer, it is not included in C.
3. ∂C/∂t = 0 at t = ∞. This condition ensures that C does not increase above
Co.
Clearly, the first boundary condition is unrealistic. “Steady state” can exist only when the phosphorus concentration that reaches the water table is constant.
This condition is thought to exist when phosphorus adsorption to soil particles and subsequent precipitation of sparingly soluble phosphate minerals continues at a level that allows the same amount of phosphorus to pass through the vadose zone to the water table all the time. The concept of vadose zone efficiency is based on this idea. Because phosphorus may be strongly retarded in the vadose zone by some soils, transport to the water table may take awhile from OWS installation to establishment of “steady state”. Some phosphorus concentration less than Co may reach the water table. However, the boundary condition is
38 acceptable for our purpose, which is to consider very long times. We will assume that the time from startup to “steady state” is short.
In addition, phosphorus retardation in the vadose zone may change with time. Most field studies of OWS effluent plumes are carried out over a relatively short time (months to a few years) and at a specific time in the operating life of the OWS. Typically, these studies have occurred early in OWS life (see Chapter
2). The resulting measure of vadose zone efficiency may be high. Over longer times (decades), the influx of phosphorus to the water table will likely increase as sorption sites in the vadose zone are used up and as local desorption occurs, resulting in a higher average Co. We have ignored this possibility in assuming
“steady state”. In all cases for this model, the value of Co will be considered a constant, although it is more likely a (complex) function of time.
Under the assumptions and boundary conditions given, the 3-D ADR equation has been solved analytically, using a rectangular “patch” source of dimensions Y and Z, set in a plane perpendicular to the x-axis at x = 0
(Domenico and Schwartz 1990). Two (2) solutions have been given. The first solution places the top of the “patch” at the water table and the x-axis also at the top of the “patch” (see Domenico and Schwartz (1990) Figure 17.8 (a), page
647). This form of the solution is appropriate when ux is much larger than the vertical flow velocity of the effluent entering the water table, as is typical of conventional septic systems. The solution is reported by Domenico and Robbins
(1985) as:
39
푢 푌 푌 푥 − 푥 푡 푦 + 푦 − 퐶표 푅 2 2 퐶 = 푒푟푓푐 [ 1/2] {푒푟푓 [ 1/2] − 푒푟푓 [ 1/2]} 8 푢푥 2(훼 푥) 2(훼 푥) 2 (훼푥 푅 푡) 푦 푦 Eq. 3.6 푧 + 푍 푧 − 푍 × {푒푟푓 [ 1/2] − 푒푟푓 [ 1/2]} 2(훼푧푥) 2(훼푧푥)
A second form of the 3-D solution was reported by Domenico and Robbins
(1985); it places the “patch” in the aquifer at some distance below the water table
(see Domenico and Schwatrtz (1990) Figure 17.8 (b), page 647). In this case, the center of the patch is on the x-axis at x = 0. This form of the solution allows for vertical dispersion upward, toward the water table, in cases when the downward velocity of the effluent entering the saturated zone from the vadose zone is relatively high compared to the pore water velocity in the aquifer. In this form, Z is replaced by Z/2 in Eq.3.6. This version of the 3-D solution was used by
Robertson et al. (1991) for their tracer test at the Cambridge, Ontario site, discussed in section 3.5.2.
Using the same boundary conditions as above, the analytical solution to the 1-D ADR equation was reported by Ogata and Banks (1961) as:
퐶표 (푅푥 − 푢푥푡) 푥 (푅푥 + 푢푥푡) 퐶 = {푒푟푓푐 1/2 + [푒푥푝 ( ) 푒푟푓푐 1/2]} Eq. 3.7 2 2(훼푥푢푥푅푡) 훼푥 2(훼푥푢푥푅푡)
In this case, the continuous step source is assumed to be a point source.
These solutions assume the parameters are constant values. The assumption of constant parameters is based on the underlying assumption that the aquifer consists of a porous medium (mostly sand) that is homogeneous and isotropic. In general, we will use average values of saturated hydraulic
40
conductivity, Ks, bulk density, ρb, and effective porosity, n, as reported in the literature. The bulk density, ρb is determined by the relationship n = 1 – ρb/ρs where the soil density, ρs is usually assumed to be 2.65 g/cm3 (Freeze and
Cherry 1979). The average pore water velocity, ux, may be reported based on field observations, but is usually found using Darcy’s law (Eq. 2). Dispersivities,
αx, αy, and αz, may be reported based on field tracer tests (e.g. Robertson et al
1991, LeBlanc 1984); we will generally use an average literature value. The sorption distribution constant, Kd may be reported in the literature based on laboratory column studies or determined by field retardation observations, using the curve fitting approach described above. We will prefer a curve fitting approach when field data are available.
3.4 Phosphorus Loading Model
Our objective is to determine the total phosphorus loading to a surface water body (a lake) from all the OWS in the lake’s watershed. The result will require that a load from each OWS to the lake be calculated and then all the loads summed. For simplicity, we consider the 1-D case first.
The load of phosphorus delivered to the OWS is determined by the volume of wastewater and the concentration of phosphorus in the wastewater.
However, we are interested only in the phosphorus load to the soil, that is, the load released from the septic tank. This load, designated Weff, is the product of the average effluent flow rate, designated Q, and the average effluent phosphorus concentration at the septic tank outlet, Ceff, that is: Weff = Q × Ceff.
41
We assume the average flow rate from the septic tank equals the flow rate to the
SAS, and the flow rate to the water table; in other words, there is no build-up of effluent water anywhere in the system. This flow rate is determined by water use by the people who use the facility (household) served by the OWS, that is: Q = number of persons in the household × the volume of water used per person per time.
The load of phosphorus entering the surficial aquifer at the water table, designated Wo, is determined by the “efficiency” of the vadose zone, and is given by Wo = Q × Co. Using the definition of “efficiency” given above, Co may be found by:
Co = Ceff – (η × Ceff ) = Wo / Q Eq. 3.8
In the aquifer at the plume front, the phosphorus load, designated W, is given by:
W = C × Af × ux Eq. 3.9 where Af is the area of the plume at the plume front. For the 1-D case, there are no y and z components of loading flux, so the value of Af × ux at steady state is simply Q. Using Eq. 3.7 and the relationships for Wo and W, Eq. 3.8 and 3.9, gives:
ì æ ö ü æW öï (Rx - uxt) x (Rx +uxt) ï W = ç o ÷íerfc + expç ÷erfc ý Eq. 3.10 è 2 ø 1/2 a 1/2 îï 2(axux Rt) è x ø 2(axux Rt) þï
In the 3-D case, Wo is determined as in the 1-D case. However, the value of W at the plume front must be found by integrating across the y and z dimensions at a given value of x and t. The 3-D analytical solutions use a rectangular “patch” source of dimensions Y and Z in the plane perpendicular to
42 the x axis. Transverse dispersion causes the plume to expand in both y and z directions. Ideally. the rectangular shape of the patch is retained at the plume front. Conceptually, the value of W is the sum of the C × ux values at every point in that rectangle. This is the same as saying that C × ux is integrated from -∞ < y
< ∞ and -∞ < z < ∞, and W is the (double) sum of C × ux × dy × dz, i.e.:
¥ ¥
W = ò ò Cux¶y¶z Eq. 3.11 -¥ -¥ where C is given by the 3-D analytical solution, Eq. 6. As above, if the patch source is placed below the water table, Z is replaced by Z/2.
We approximate the integration by solving for C at the center-points of cells Δy by Δz, where Δy = Δz = 0.01 m, for a given value of x and t, and assume that each value of C holds for the area Δy × Δz. We sum the cell values of C as we proceed (ΣΣC), and compute C values for the entire plume front, Af, until the cells no longer contribute significantly to the sum. We then compute ΣΣC × ux ×
Δy × Δz, to obtain W.
The calculations of W require that the dimensions of the “patch”, i.e. Y and
Z be specified. At the source, Wo is determined by (water use volume/time × Co,) as described above, but Wo is also equal to (Co × ux × Ap), where Ap is the
“patch” area. Therefore, Ap = Wo/(Co × ux). Since Ap = Y × Z, it is necessary to specify these dimensions, or one of them and a ratio Y/Z. We will use the ratio
Y/Z = 8/1.75, for reasons discussed below. Thus, the algebraic solutions are:
8 W Y = ´ o Eq. 3.12 1.75 Coux and
43
1.75 W Z = ´ o Eq. 3.13 8 Coux
3.5 Trial Application of the Model
Because our goal is to calculate the phosphorus loading, W, from an OWS to a water body (lake) a distance, x, away, we determined to consider whether the 1-D analytical solution to the ADS equation is appropriate to use. We reasoned that the dissolved phosphorus in the plume should all reach the receiving water body even if it were dispersed in the transverse and vertical directions. We therefore considered a well-studied OWS and applied both the 1-
D and 3-D solutions to confirm the ability of the model analytical solutions to predict the same phosphorus loading. We chose a septic system in Cambridge,
Ontario, Canada for which detailed field studies have been reported in the literature.
3.5.1. The Cambridge, Ontario site
For over ten years, a site in Cambridge, Ontario, Canada was studied by the Waterloo Centre for Groundwater Research at the University of Waterloo,
Ontario (Robertson et al. 1991, Robertson 1995, Robertson et al. 1998,
Robertson 2003). The research provided data on phosphorus plume extent at 10,
17, and 20 years after installation of the system. The system was installed in
1977 and served a domestic residence having four (4) full-time residents. During the time of the study, 1987 – 1997, the system was 10 to 20 years old. The system consists of a conventional septic tank and soil absorption system (similar
44 to Figure 3.1). Effluent flows by gravity from the tank to the SAS, which consists of perforated pipes trenched into medium sand to provide about 2 meters of unsaturated depth to the groundwater. The underlying surficial aquifer consists of fine to coarse sand, “with coarser material dominating”.
3.5.2 Dispersivities αx, αy, and αz
During the intensive study of the OWS at the Cambridge, Ont. site during
1987, measurement of the Na+ concentrations in the effluent plume provided data that allowed estimation of the dispersivity in three dimensions (Robertson et al. 1991). Because the dispersivities are parameters of the model, we first take the opportunity to review their work and apply our model.
The researchers used the Na+ concentrations as a tracer, assuming that
Na+ is conservative, that is, non-reactive and non-sorbing in the saturated zone/aquifer. They then used one of the two “patch” 3-D analytical solutions (Eq.
3.6) to model the Na+ plume at the Cambridge site. They chose to place the
“patch” source below the water table in the middle of the shallow aquifer at
Cambridge to allow vertical dispersion in both z directions. By comparing their
Na+ field data to this model solution, they confirmed their dispersivity estimates.
We use this solution to reconfirm their results. We then use the alternate 3-D solution that places the top of the “patch” at the water table, as well as the 1-D solution, for comparison. The Na+ tracer used by Robertson et al. (1991) had a
“steady state” concentration at the source of 80 mg/L. This value is used in our
45
+ model as Co for Na . Note that the value for retardation, R = 1, since we assume
+ no sorption of Na , and thus Kd = 0.
Our model was run for Na+ concentration, C vs. distance, x, using an average pore water velocity ux = 30 m/yr, the same as used by Robertson et al.
(1991). We took the field data for Na+ concentration vs. distance in the direction of groundwater flow, i.e. the x-direction, from Robertson et al. (1991), Figure 8.
These data are given in Table 3.1. For our model, time, t, was set to 10 years, the age of the Cambridge septic system when Robertson et al. (1991) obtained their data.
Robertson et al. (1991) reported the best fit to the field data, using the 3-D analytical solution, was: αx = 1 m, αy = 0.01 m, and αz = 0.004. These values produced the curves shown in Figure 3.2. The 3-D solution with the “patch” placed below the water table duplicates the result given by Robertson et al.
(1991). The curve depicts the concentrations along the plume axis, and this
Distance from the SAS (m) Na+ concentration, (mg/L) 0 78.5 2 80.1 8 85.5 20 73.9 30 71.6 42 75 53 67 60 62.4 94 63.5 128 52
Table 3.1: Na+ concentration vs. distance from the SAS, Cambridge, Ont. site (data adapted from Robertson et al. 1991).
46
90
80
70
60
50
40
Measured (Robertson et al 1991) 30 Modeled 3-D, 2-sided
20 Modeled 3-D, 1-sided Na+ Concentration (mg/L) Concentration Na+ Modeled 1-D 10
0 0 10 20 30 40 50 60 70 80 90 100 110 120 130 Distance from the SAS, x (m) Figure 3.2: Na+ concentration along the plume core at Cambridge, Ont. 10 years after OWS installation; field measurements by Robertson et al. (1991), and model curves by 3-D and 1-D analytical solutions.
“two-sided” solution (z-direction) allows dispersion in both the vertical up and down directions. Dispersion in both lateral and both vertical directions lowers the centerline concentration with distance. The 3-D solution with the ”patch” placed at the water table shows a less good fit. This “one-sided” solution does not allow any dispersion in the vertical up direction, so the loss of concentration at the centerline is less.
Using a value of αx = 1 m, the 1-D model solution, Eq. 3.10, does not provide a good fit for Na+ concentration. The 1-D model calculates the concentration as if all the solute is transported along the plume axis, with no lateral or vertical dispersion. However, our loading approach to solute transport
47 assumes that all the solute load that enters the water table/aquifer reaches a given distance with sufficient time. Based on the reported family water use of 1.3
3 + m /day and the Na concentration at the input to the aquifer (Co = 80 mg/l), the input load is Wo = 0.104 kg/day, or about 38 kg/yr. We use this value in the 3-D and 1-D model solutions, Eqs. 3.10 and 3.11, to produce Figure 3.3. The loading curves overlap for the three solutions. The result suggests that if a solute is transported conservatively, i.e. without retardation (Kd = 0), the solute load will very quickly move down-gradient. Figure 3.3 also suggests that using the 1-D solution gives a result sufficiently like the 3-D solutions to justify considering the
1-D solution in subsequent calculations of phosphorus loading.
40
35
30
25
20
10 yr, 3-D 2-sided Na+ Load, kg/yr Load, Na+ 15 10 yr, 3-D 1-sided 10 yr, 1-D 10
5
0 0 50 100 150 200 250 300 350 400 Distance from SAS, m
Figure 3.3: Na+ loading at the plume front at Cambridge, Ont. 10 years after OWS installation; model curves by 3-D and 1-D analytical solutions.
48
3.5.3 Sorption Distribution Coefficient, Kd
A Cambridge site value for the sorption distribution coefficient, Kd, is required for the model analytical solutions for phosphorus load. This value is used to calculate the retardation, R. A value of Kd may be estimated from laboratory column studies or from literature values, but is otherwise unknown, and may be used as a fitting parameter in the model. This latter method is illustrated below.
Table 3.2 gives field data for phosphorus concentration in the effluent plume for the Cambridge, Ont. site obtained by the researchers at 10, 17, and 20 years. Kd is determined by plotting phosphorus concentration in the plume, C,
Year System Age Distance Measured Source(s) (Time, t, from SAS, phosphorus years) x (m) concentration, C (mg/l) 1987 10 0 4.6 Robertson et al. 1991 10 1.0 12.5 0.1
1994 17 0 4.6 Robertson 1995 13 3.0 20 1.9 Robertson et al. 1998 23 1.0 25 0.1 30 0
1997 20 0 4.6 Robertson 2003 20 3.0 25 1.0 30 0.1
Table 3.2: Phosphorus concentrations in the septic system plume vs. distance from the SAS, Cambridge, Ont. site (Robertson et al. 1991, Robertson, 1995, Robertson et al. 1998, Robertson 2003).
49 vs. distance from the SAS, x, for both the measured data and for the model solutions for years 10, 17, and 20. The breakthrough curves from the three analytical solutions were then fitted to the field data by adjusting the value of Kd used by the model until the model curves fit the field data as nearly as possible,
3 to a value of 6.4 cm /g. This value of Kd indicates that retardation of phosphorus in the saturated zone is low. Figure 3.4 depicts the results described. The 3-D model solutions give nearly identical curves, which are lower than the 1-D solution curve. This result is attributed to dispersion, which reduces the phosphorus concentration along the plume axis. For the purpose of curve fitting
5
4.5
4
3.5
3
2.5
2
1.5
Phosphorus Concentration, mg/l Concentration, Phosphorus 1
0.5
0 0 5 10 15 20 25 30 Distance from SAS, m
10 year measured 17 year measured 20 year measured 10 year 1-D Model 17 year 1-D Model 20 year 1-D Model 10 year 3-D 2-sided Model 17 year 3-D 2-sided Model 20 year 3-D 2-sided Model 10 year 3-D 1-sided Model 17 year 3-D 1-sided Model 20 year 3-D 1-sided Model Figure 3.4: Phosphorus Concentration vs. distance from the SAS, measured and 3 modeled, Cambridge, Ont. site. Model value of Kd = 6.4 cm /g. Data points from Table 3.2. Solid curves from the 1-D model results at 10, 17, and 20 years. Dashed curves from the 3-D model results.
50
to determine Kd, however, all three solutions give similar results, again suggesting that the 1-D solution is acceptable for our purpose.
3.5.4 Additional Parameter Estimates for Phosphorus Transport
Application of the model solutions to phosphorus transport at the
Cambridge site requires that values be estimated or determined for parameters other than dispersivity and sorption distribution constant. Based on measurements over several years, the Waterloo research team concluded that the sorption sites in the unsaturated zone were filled before monitoring began in
1987, and that continuing attenuation of phosphorus is achieved by precipitation reactions in the unsaturated/vadose zone (Robertson 1995, Robertson et al.
1998, Zanini et al. 1998, Robertson 2003). Their conclusion was based on results that showed the phosphorus concentration in the aqueous solution reaching the water table was about constant, a condition they called “steady state”. We used an average value of this concentration as Co in our model. Table 3.3 provides the data used for our model solutions, taken from the referenced study reports. The average of phosphorus concentration measurements for the effluent from the septic tank entering the SAS indicates (Table 3.3) that the SAS is about 25% efficient at removing phosphorus from the effluent. The vadose zone sand is reported to be calcareous, with high alkalinity that buffers the effluent plume to maintain circumneutral pH (Robertson et al. 1998). Research has shown that calcareous sand is not as efficient at retarding phosphorus as acidic sand
(Robertson et al. 1998).
51
Parameter Value Value(s) Source(s) or variable used reported Ceff 6.3 mg/L 8 (1987) Robertson et al. 1991. 6.3 (1994) Robertson 1995: average 1987-94; range 1.4 - 14.2 mg/L. 6.4 (1994) Robertson et al 1998. 6.3 (1997) Robertson 2003.
Co 4.6 mg/L 4 (1987) Robertson et al. 1991. 4.6 (1994) Robertson 1995: range 3 - 6 mg/L, average 4.6 mg/L. 4.9 (1994) Robertson et al. 1998: average 4.9 4.8 (1997) mg/L. Robertson 2003, Table 2.
η .25 .50 (1987) Robertson et al. 1991. .27 (1994) Robertson 1995. .23 (1994) Robertson et al 1998. .24 (1998) Robertson 2003.
ux 32 m/yr 0.088 Robertson et al. 1991: range 20 – 40 m/day m/yr.
n 0.35 0.35 Robertson et al. 1991.
Year 1977 1977 Robertson et al. 1991. Installed
System 10 (1987) Robertson et al. 1991. age 17 (1994) Robertson 1995. 20 (1997) Robertson 2003.
Number of 4 4 Robertson et al. 1991. Persons
Water use 1.3 1 m3/day Robertson et al. 1991: “~1 m3/day”. m3/day 1.3 m3/day Robertson 2003.
Table 3.3: Values of variables and parameters for the Cambridge, Ont. site. (References as noted.)
52
3.5.5 Phosphorus Loading
As a test case, we used the three analytical solutions to calculate the phosphorus loading, W, at distance, x, for various times, t, assuming the
Cambridge OWS remained in continuous use. We found that all three analytical solutions gave nearly the same results for W. Figure 3.5 shows the results for various t values from 10 to 100 years.
2.5
2
1.5
1 Phosphorus Loading, kg/yr Loading, Phosphorus 0.5
0 0 20 40 60 80 100 120 140 Distance from SAS, m
10 years, 3-D 10 years, 1-D 20 years, 3-D 20 years, 1-D 40 years, 3-D 40 years, 1-D 60 years, 3-D 60 years, 1-D 80 years, 3-D 80 years, 1-D 100 years, 3-D 100 years, 1-D Figure 3.5: Phosphorus loading breakthrough curves at various OWS ages, Cambridge, Ont. site. Curves are for 10 yrs, 20 yrs, 40 yrs (2017), 60 yrs, 80 yrs, and 100 yrs. Solid curves are the 1-D model results, and dashed curves are the 3-D model results.
These results yield three important conclusions:
1. The 1-D analytical solution to the ADS equation gives results sufficiently
comparable to the 3-D solutions to justify the use of this 1-D solution to
53
provide phosphorus loading calculations for our subsequent work.
Curves for all three solutions nearly overlap; the small differences
between the 1-D solution and the 3-D solutions may be attributed to the
numerical integration required for the “patch” solutions. This result is not
unexpected, since we are calculating mass flux at the distance, x, which
should be the same regardless of the solution used.
2. With increasing time, the phosphorus loading to the water table, Wo ≈
2.18 kg/yr, moves down-gradient in the aquifer. The model predicts that,
by 2017, this loading value would have reached more than 15 m (~50 ft)
from the Cambridge SAS. The significance of this result is that 50 feet is
the minimum setback of a SAS from a surface water body in many states,
including Massachusetts. For the Cambridge site, the entire load of
phosphorus that reaches the water table (Wo) would be entering a water
body at this minimum distance after only 38 years of continuous OWS
use. Greater setbacks allow longer times for this loading value to reach a
down-gradient water body.
3. The model predicts that significant loading (greater than 0.5 kg/yr) will
have reached down-gradient distances greater than 100 m before 2068,
and the distance for that loading value increases with time. This
conclusion is significant because the NPSLAKE model used for
Massachusetts phosphorus TMDLs assumes that the total phosphorus
loading to a surface water body includes an estimated contribution of 0.5
kg/yr from an OWS within 100 m of the water body, regardless of OWS
54
age, and no contribution from OWS further away (Mattson and Isaacs
1999).
Figure 3.6 shows the loading curve at x = 128 m at decadal times, assuming the OWS remains in continuous use. This distance was chosen because it was the reported maximum length of the effluent plume in 1987, when the Cambridge OWS was in use for 10 years. The model predicts that phosphorus loading at this distance will begin about 2070, and will increase to a maximum equal to Wo by about 2160.
2.5
2
1.5
1 Phosphorus Loading, kg/yr Loading, Phosphorus
0.5
0 2000 2020 2040 2060 2080 2100 2120 2140 2160 2180 2200 Year Figure 3.6: Phosphorus Loading at 128 m from the SAS versus Time, Cambridge, Ont. OWS.
3.6 Application of the 1-D Model to Other OWS Sites
Use of the 1-D analytical solution for loading, Eq. 3.10, provides an estimate of phosphorus loading from a single OWS at any given distance and
55 time. When the distance to a surface water body via the groundwater flow path is known, the load to the water body can be estimated at every time from the beginning of OWS use. Use of the model requires that the model parameters be estimated (or determined by field measurements) for the location of the OWS
(see Table 3.2 for the Cambridge, Ont. site}. For OWSs that share similar soil properties, parameter values determined at one location, or averages over several similar sites, may be the only data available. Thus, literature values of these parameters must be used with caution.
It is also important to note that the model estimates the load of phosphorus to the surface water body, but not necessarily into the water body.
The model does not account for any possible attenuation of the phosphorus load due to reactions at the groundwater/surface water interface. The value of the model, however, is its usefulness at the watershed level, to estimate the total phosphorus load from OWSs.
In a developed watershed having many OWSs, the load contribution from each OWS can be calculated and the results summed to estimate the total phosphorus load from all the OWSs in the watershed. In this case, parameter values for each OWS could be used, but would require a substantial amount of field work to obtain adequate data to estimate the values. A useful estimate may be made using average parameter values for the watershed as a whole, assuming that these average values apply. This approach has been used in the case study presented in Chapter 4.
56
CHAPTER 4
Case Study: Oldham Pond
4.1 Introduction
We applied the model developed in Chapter 3 to the OWSs in the watershed of Oldham Pond, a lake in Pembroke and Hanson, Massachusetts.
This lake is one of several in this local area (Figure 4.1).
Figure 4.1: Environs of Oldham Pond in Hanson and Pembroke, Massachusetts (from USGS topographical map, Hanover Quadrangle, Massachusetts – Plymouth County, 7.5 minute series, 2015.
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Oldham Pond was chosen for this case study for several reasons.
• The lake is eutrophic; annual blooms of algae and macrophytes impair the
lake for recreation, and degrade water quality of this “tributary to a public
water supply”, the down-gradient lake, Furnace Pond. Local management
efforts have not been effective. These efforts included many of the
standard methods aimed at reducing phosphorus overland flow, i.e.
improvements in stormwater management; street sweeping; outreach to
cranberry farmers to limit fertilizer and pesticide use; an upgrade to a
summer camp wastewater treatment system; and education of residents
on lawn fertilizer use and septic system maintenance. When these efforts
did not eliminate the annual blooms, alum treatment was prescribed; it
didn’t work either.
• The lake is shallow, and summer stratification is limited to a few, relatively
small “deep holes”. Mixing of the lake by wind and boating recreation
breaks up any stratification in a short time. Thus, recycling of phosphorus
from the lake bottom sediments is not considered a major source of
loading.
• The watershed is small relative to the lake area, and surface tributaries to
the lake are few and short. Surface run-off of phosphorus is limited on an
areal basis, and phosphorus that reaches a surface water is quickly
transported to the lake with little attenuation.
• The lake is the terminal water body in its watershed; there are no lakes
upstream from which a phosphorus load could be introduced.
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• The lake lies in glacially deposited sand and gravel, with little silt or clay.
The lake is largely sustained by groundwater from the underlying surficial
aquifer.
• The watershed is nearly fully developed by residential households, given
the zoning regulations of the two towns, and nearly all the 859 OWSs in
the watershed serve single family households.
• The water table throughout the watershed is shallow, which limits the
depth of the SAS for most OWSs. When combined with the mostly sand
soil, this limited depth ensures the SAS efficiency of the mature OWS will
not be high.
For all these reasons, it is reasonable to hypothesize that groundwater provides a major phosphorus influx to the lake, and OWSs are the primary source of this phosphorus.
In addition, previous studies of the Oldham Pond watershed, the lake, and similar areas in southeastern Massachusetts have been performed, to provide relevant data for parameter estimation. Finally, Oldham Pond was chosen for a case study because town records are accessible and were made available to me for OWSs, including design and installation data in most cases, so each OWS location, depth of the water table, and OWS time-in-service could be determined.
Based on field research reported in the literature (see chapter 2), time appears to be a major variable. OWS time-in-service, combined with the distance phosphorus is transported (the down-gradient flow path) and the flowline gradient, affects the time when the phosphorus load may reach the surface water
59 body. Because each OWS in a watershed may have a different installation time, the combined phosphorus load to the surface water body must account for the time-in-service, flow path length and gradient of each OWS. The model accounts for these, and the town data allowed for their inclusion.
The paper and “supplement” reproduced in Section 4.2 describes the application of the model to Oldham Pond and reports the results and conclusions. This paper was submitted to Lake and Reservoir Management, a peer-reviewed publication, and is under review. Note that the Reference sections have been omitted from both the main paper and the “supplement”; all references are included in REFERENCES. Also, Appendix 4.1 has been included at the end to provide the Visual Basic algorithm used by the Ms Excel program to calculate the phosphorus load, W, for each OWS (information not included in the paper or
“supplement”).
4.2 Phosphorus Loading from Onsite Wastewater Systems to a Lake (at Long
Time Scales)
Frank L. Schellenger and Ferdi L. Hellweger*
Civil and Environmental Engineering Department, 400 Snell Engineering Center,
Northeastern University, 360 Huntington Avenue,
Boston, Massachusetts 02115, United States.
*Corresponding author phone: (617) 373-3992; e-mail: [email protected]
[Short Title: Septic system P loading to a lake over a long time]
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4.2.1 Abstract
Phosphorus from onsite wastewater systems (OWSs, septic systems, cesspools) enters the groundwater and may migrate to and contribute to eutrophication of down-gradient lakes. Since phosphorus sorbs relatively strongly to soil solids, this source is often dismissed in lake management. However, phosphorus adsorption is reversible, and given enough time, some phosphorus will eventually reach the lake. We investigated the magnitude and timing of phosphorus loading to a lake using a model which accounts for cesspools and septic systems, the laundry detergent phosphorus ban, loss of phosphorus in the vadose zone, and transport and adsorption/desorption (retardation) in the aquifer. We parameterized the model and applied it to estimate phosphorus loading to a case study lake for all 859 OWSs in the watershed from years 1750 to 2750. We compared our results with phosphorus budgets based on measurements by others. The model predicts that groundwater input of phosphorus from OWSs by itself can account for the current eutrophic state of the lake and will continue to increase. We performed parameter sensitivity and
Monte Carlo uncertainty analyses and illustrated the effects of removal in the vadose zone and travel time in the aquifer. Our model suggests that past management actions (cesspool to septic system conversion, laundry detergent phosphorus ban) effectively reduced the 2016 load by 39%. A centralized waste water treatment facility would eliminate the OWS loading, but the half-life due to the existing phosphorus reservoir is long (20 years).
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Key Words: cesspool, eutrophication, groundwater, onsite wastewater disposal, phosphorus, septic system.
4.2.2 Introduction
Cultural eutrophication of lakes is a world-wide problem that is associated with harmful algae blooms and other symptoms (Schindler 2006, Dodds et al.
2009, Paerl et al. 2011), and phosphorus inputs are often considered the primary cause (Schindler 2006, Lewis and Wurtsbaugh 2008). Phosphorus can enter a lake from a number of sources, including wastewater treatment plants, tributaries, and direct runoff. Internal loading (i.e., recycling from the sediment bed) can also be an important source (Cooke et al. 2005).
Groundwater is another source of nutrients to surface waters
(Lewandowski, et al. 2015, Meinikmann et al. 2015), and onsite wastewater systems (OWSs) have long been recognized as a possible source of groundwater contamination (Beal et al. 2005, Humphrey and Driscoll 2011,
Oosting and Joy 2011, Eveborn et al. 2012). Nutrients from OWSs may travel to down-gradient surface waters and contribute to their eutrophication. Based on studies of chemical reactions in OWS effluent plumes, a consensus developed that nitrogen (as nitrate) has the potential to travel great distances down-gradient from an OWS (see for example, Dudley and Stephenson 1973, Jones and Lee
1979, Bicki et al. 1984). On the other hand, these studies have reported that the unsaturated (vadose) zones of OWS soil absorption systems are highly efficient at sequestering phosphorus, and have concluded that phosphorus will be
62 sufficiently retarded by sorption or immobilized by precipitation so that movement is limited to a few meters at most (Reneau and Pettrey 1976, Stolt and Reneau
1991). For some older systems, down-gradient transport of phosphorus was found (Dudley and Stephenson 1973, Reneau and Pettrey 1976, Gilliom and
Patmont 1983); these were viewed as isolated cases, and down-gradient movement from a well-designed and maintained OWS is generally not considered a threat to surface waters (Sikora and Corey 1975, Jones and Lee
1979, Reneau et al. 1989). Consequently, the contemporary nutrient management process is based on this paradigm. Remediation and restoration efforts for eutrophic lakes and other surface waters generally focus on controlling above-ground nutrient sources (Cooke et al 2005).
Ignoring the phosphorus contribution of OWSs to a lake may not be warranted at long time scales. Some studies of phosphorus behavior in the OWS vadose zone have found that sorption of phosphate anions to aluminum and iron hydroxide coatings on soil particles, and the subsequent precipitation of mineral phosphates, is enhanced at groundwater pH values below circumneutral (e.g.
Robertson 2003 and 2012). Precipitation may be a permanent loss process, but phosphorus sorption is reversible (Dudley and Stephenson 1973, Whelan and
Barrow 1984, Walter et al. 1996). There are a number of studies that explored the long-term transport of phosphorus from an OWS in groundwater (e.g.
Koerner and Haws 1979, LeBlanc 1984, Robertson 2003, Andres and Sims
2013, Jarosiewicz and Witek 2014). Findings from these studies suggest that,
63 given sufficient time, phosphorus can move down-gradient for a significant distance.
From the standpoint of eutrophication, the total load to a lake has to be considered, so studies of individual OWSs are of limited utility. A number of studies have estimated groundwater phosphorus loading from the watershed to a surface water body, which found the load to be significant and suggested OWSs as a potential source (Vanek 1991, Moore et al. 2003, Jarosiewicz and Witek
2014, Meinikmann et al. 2015). However, these studies do not provide a quantitative link to OWSs. To our knowledge there have been no studies that combine the estimated loading from all the OWSs in a watershed with the long- term dynamics of transport and retardation in the groundwater, and quantify the relationship to the trophic state of the receiving lake.
We estimated the cumulative loading of phosphorus from all the OWSs in a lake watershed at a long time scale, from the installation of the first OWS to when the present-day loadings from all the OWSs in the watershed reach the lake. We used a simple model of phosphorus transport to predict the time- variable phosphorus load from each system to a down-gradient lake, and then summed the loads to obtain the total loading.
4.2.3 Materials and Methods
4.2.3.1 Study Site
Oldham Pond is a 232 ac (93.89 ha) lake with mean depth of 8.7 ft (2.65 m) located on the border between the towns of Pembroke and Hanson, Plymouth
64
County in southeastern Massachusetts, United States (Figure 4.2). The watershed is small, comprising 763 ac (308.78 ha), with four (4) small tributary streams to the lake (CEI 2011). The watershed is located in a coastal plain that slopes gently toward Massachusetts Bay. The local climate is mild temperate.
Town of N Pembroke 300 m
Oldham Pond
Town of Hanson
Figure 4.2. Oldham Pond Watershed, Pembroke and Hanson, Plymouth County, Massachusetts. All 859 OWS locations shown as green circles, and groundwater flow paths shown as red lines. Stippled polygons are wetlands or cranberry bogs.
The lake occupies about 30.4% of the watershed, and 2/3 of the area is land and wetlands (BEC 1993, CEI 2011). Like most of the lakes in southeastern
Massachusetts, including Cape Cod, Oldham Pond lies in glacially deposited sand and gravel and is in contact with an underlying aquifer (Carlson and Lyford
65
2005). Groundwater studies (BEC 1993, Carlson and Lyford 2005) have concluded that the lake receives much of its inflow from groundwater, and that some outflow from the lake is recharge to the groundwater. The general flow of groundwater in the region is from west to east, under the lake, toward
Massachusetts Bay (Carlson and Lyford 2005). Locally, along the shoreline the groundwater gradient is toward the lake.
The lake is surrounded by residential development and serves as a major recreation venue for swimming, boating, and fishing. It is eutrophic, and supports blooms of algae each summer. In recent years, these blooms have been dominated in late summer by cyanobacteria, and have often forced Town officials to close the lake for swimming. Two studies have been performed to characterize the nutrient enrichment to the lake and to identify potential remedial actions (BEC
1993, CEI 2011). These studies concluded that the lake is receiving excess phosphorus input from a number of sources, including overland and point source runoff and recycling from the lake-bottom sediment. Inputs from groundwater were considered, but were not accounted for in detail in the belief that phosphorus is readily sorbed to the iron-rich soil and thereby immobilized (BEC
1993, CEI 2011). Our study addresses the phosphorus loads to the lake only from OWSs via the groundwater, and does not address the phosphorus loads from all sources. Our estimate of the P load delivered to the lake from OWSs is not affected by any other sources.
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4.2.3.2 Model Description
The model considers three stages of total phosphorus transport: (1) loading from the cesspool or septic tank, (2) loading to the groundwater, and (3) loading to the lake (Figure 4.3). The equations for these three stages are described below. The focus of the model is on the long-term (10+ years) dynamics resulting from development (i.e., installation of systems), cesspool to septic system conversion, laundry detergent phosphorus ban, and travel time
(advection and retardation). Variability at shorter timescales (e.g., seasonality of hydrology or household occupancy) is not considered.
1. Leaving cesspool or septic tank
Vadose zone
2. Entering water table
Aquifer
3. Entering lake
Figure 4.3: Model overview, illustrating the three stages of the model for a conventional septic system.
Stage 1: Loading from the Cesspool or Septic Tank: Wastewater is conveyed to a cesspool or septic tank, where heavier solids sink to the bottom and lighter solids form a scum at the top (USEPA 2002). Solids and scum are periodically removed as part of regular system maintenance. The liquid between contains
67 mostly dissolved species. In a conventional septic tank system, liquid effluent is piped to the soil adsorption system (SAS). Before the advent of regulations requiring the use of a septic tank and SAS, a cesspool was common. A cesspool serves the same purposes as the later septic tank, but is built with porous sides and bottom. Effluent is released primarily from the sides of the cesspool. With the advent of septic system regulations, many cesspools were replaced by septic systems and the cesspools abandoned. On the other hand, if a cesspool does not fail by overflowing or backing up, most State (including Massachusetts) regulations do not require its replacement. The phosphorus loading from the cesspool or septic tank, Weff (M/T), is given by
Weff = Ceff × Qo Eq. 4.1 where Ceff is the concentration of phosphorus in the effluent leaving the cesspool
3 3 or septic tank (M/L ), and Qo is the effluent flow rate (L /T). Averages of Ceff and
Q0 are considered constant, but Ceff can change due to the laundry detergent phosphorus ban.
Stage 2: Loading to the Groundwater: The effluent from the conventional septic system is distributed to the SAS via perforated pipes. Below these pipes is a depth of unsaturated soil, also called the vadose zone. After leaving the cesspool or septic tank, the effluent travels vertically through this vadose zone to the groundwater table. Depending on the soil texture, pH, content of metal hydroxides, and depth to the aquifer, a fraction of the phosphorus is sorbed or precipitated, preventing it from reaching the groundwater.
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Typically, system installation depths and soil properties are not consistently available, so we use a removal efficiency. The efficiency of the vadose zone in removing phosphorus, η, is defined as
η = (Ceff - Co)/Ceff Eq. 4.2 where Co is the concentration of phosphorus in the effluent as it reaches the
3 water table (M/L ). The loading from the vadose zone to the groundwater, Wo
(M/T), is given by
Wo = Co × Qo Eq. 4.3
Wo is assumed to be a constant step input to the water table/saturated zone, which assumes that the septic system is mature enough to have reached a steady state. “Steady state” exists when phosphorus sorption and precipitation reactions are retarding phosphorus in the vadose zone at a rate that allows the same load to reach the water table at all times (Robertson 1995, Beal et al.
2005). The efficiency is different for cesspools and conventional septic systems.
For cesspools, the bottom is typically deeper than a conventional SAS and the travel depth through and removal in the vadose zone is less, which can be accounted for by using a lower removal efficiency.
Stage 3: Loading to the Lake: Stage 3 considers transport in the aquifer. Once in the aquifer, the effluent plume is advected in the direction of groundwater flow, as well as dispersed in all three dimensions, horizontal, vertical, and transverse to flow. Depending on the soil properties, phosphorus will be retarded by sorption, which is modeled as an instantaneous and reversible process (i.e., local
69 equilibrium). In this conceptual model, the groundwater is an unconfined aquifer of glacially derived sand and gravel typical of southeastern Massachusetts, including Cape Cod, and the aquifer is underlain by an aquaclude, usually bedrock, but sometimes dense silt, clay, or glacial till that is much less permeable than the sand. The focus of our study is on the long-term dynamics, and for that purpose the groundwater hydraulics are considered constant in time (i.e., constant flow velocity). These processes can be described using the advection- dispersion-sorption (ADS) equation (Domenico and Schwartz 1990, Schnoor
1996). Here, we are concerned with the total loading to the lake. Although there will be some vertical and lateral dispersion of the plume, this will not affect the total load to the lake. We therefore use the one-dimensional version of the ADS equation. For a continuous step input, and in terms of loading, W, the analytical solution to the 1-D ADS equation is (Ogata and Banks 1961):
ì æ ö ü æW öï (Rx - uxt) x (Rx +uxt) ï W = ç o ÷íerfc + expç ÷erfc ý Eq. 4.4 è 2 ø 1/2 a 1/2 îï 2(axux Rt) è x ø 2(axux Rt) þï
K r where: R =1+ d b Eq. 4.5 n
In this equation, erfc is the complimentary error function, t is time (T); and x is distance in the direction of groundwater flow (L). ux is the average pore water
2 velocity in the x direction (L/T ). αx is the dispersion coefficient in the x direction
3 3 3 (L). ρb is the soil bulk density (M/L ), and n is the effective porosity (L /L ). Kd is the linear sorption distribution coefficient (L3/M). R is the retardation due to sorption (dimensionless). The model accounts for the time lag between the input
70 to and output from the aquifer (to the lake) due to advection and adsorption/desorption (retardation).
The total phosphorus load to the lake, W, is calculated using Eq. 4.4 for each OWS in the watershed. Calculations were done in MS Excel, using a custom function written in Visual Basic. The input loading, Wo, can change in time for any OWS, by replacement of a cesspool with a conventional septic system and/or a switch to use of a non-phosphorus detergent. Even for those cases when a cesspool was replaced by a conventional septic system, the long time scale of phosphorus transport in groundwater necessitates explicit consideration; the cesspool may have been eliminated, but the plume from it is still “en route” to the down-gradient lake. The analytical solution assumes a continuous step input, but time-variable input can be modeled by combining multiple solutions using the principle of superposition (Freeze and Cherry 1979); see Supplement 4.2.7.2 for an illustration of this superposition calculation.
4.2.3.3 Model Inputs
The Oldham Pond watershed contains 859 OWSs serving residences and a few small commercial facilities. We assumed that this number will remain constant in the future, as the watershed is nearly completely developed. A build- out analysis by CEI (2011) indicates that infill development of less than 2% on an area basis (about 13 residences) can be accommodated in the watershed.
The model inputs include, for each of the 859 OWSs, the installation time and cesspool to septic system conversion date (if applicable) and the location in
71 the watershed, which was used to derive the flow path using GIS functions (see
Supplement 4.2.7.3 for details). The average flow rate (Qo) was based on census data on household occupancy. Groundwater water elevations were based on observations or estimated from ground level and used to calculate the hydraulic slope. The cesspool and septic tank effluent concentrations (Ceff) were based on literature values reported by McCray et al. (2005). Vadose zone efficiency () was based on the work of Heufelder and Mrockza (2006) on Cape Cod, MA.
Hydraulic conductivity (Ks), effective porosity (n), and longitudinal dispersivity (x) were based on reported literature values. The distribution coefficient (Kd) was determined from data on the phosphorus plume from the Otis Air Force Base infiltration beds (LeBlanc 1984), using a curve fitting approach. Model inputs are provided in Table 4.1 with literature references, and further described in
Supplement 4.2.7.3.
4.2.4 Results and Discussion
4.2.4.1 Time series of P loading to the lake
Phosphorus loading calculations were performed for the 859 OWSs in the
Oldham Pond watershed at a time step of one year and summed to give the total phosphorus loading to the lake for each year from 1750 to 2750 (Figure 4.4); see
Supplement 4.2.7.4 for sample loading time series for five OWSs. This time period starts when the first OWS was installed and ends when the present-day loading (i.e., assuming no additional development in the watershed going forward) from all OWSs reaches the lake. The loading increases with time as the
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Table 4.1 Parameter Values
Parameter Sym- Units Value Literature Sources/ bol Used Values Notes (Range) Effluent Ceff mg/L concentration CP, before 15.0 (6.3- 6.3-24.9 a, e, 5 1994 ban 24.9) CP, after 1994 9.6 (1.4- 1.4-16.2 a, e, 5 ban 16.2) SS, before 15.0 (6.3- 7.2, 6.3-24.9 a, e, 1, 5 1994 ban 24.9) SS, after 1994 9.6 (1.4- 7.2, 1.4-16.2 a, e, 1, 5 ban 15.2)
SAS efficiency η - CP 0.25 (0.21 – 0.293) SS 0.5 (0.457 – 0, 0.27, 0.47, a, 10, 1, 6, 0.543) 0.99 11 Saturated KS m/ 13.7 (8.64- 91.5, 21.9, a, 3, 2, 7, hydraulic day 86.4)* 13.7, 8 conductivity 8.64-86.4
Effective soil n - 0.39 (0.30- 0.35, 0.39, a, 2, 3, 8, porosity 0.42) 0.30-0.42 c
Longitudinal αx m 1.0 (0.1- 1.0, 0.96, 0.1- a, 2, 4, 9, dispersivity 100)* 100 d
3 Soil bulk density ρb g/cm 1.617 b
3 Linear sorption Kd cm /g 5.0 (4.6 – 1.4-478 a, 5,6 coefficient 7.0)*
Average Distance x m 180.9 [5.0 – to 853.0] Oldham Pond Average ux m/yr 217.2 Groundwater Velocity 3 Average Effluent Qo m /yr/ 218.45 Loading hsehold Rate CP: cesspool; SS: septic system; SAS: soil absorption system.
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Table 4.1: Parameter Values, cont’d
Sources: 1. Robertson (1995); 2. Robertson et al. (1991); 3. Walter et al. (1996); 4. LeBlanc (1984); 5. McCray et al. (2005); 6. Heufelder and Mrockza (2006); 7. Carlson and Lyford (2005); 8. Freeze and Cherry (1979); 9. Garabedian et al. (1991); 10. Robertson (2008); 11. Robertson et al. (1998). Notes: a. Values in ( ) parentheses are ranges used in the parameter sensitivity and uncertainty analyses. For ranges marked with “*”, the Monte Carlo selection was done in log space. 3 b. Saturated soil density, ρs, is assumed to be 2.65 g/cm , and soil bulk density is then given by ρb = (1 – n) * ρs (Freeze and Cherry, 1979). c. The effective porosity, n, of soils around Oldham Pond is taken as the same value reported by LeBlanc (1984), as typical of sands in the region. d. Longitudinal dispersivity, αx, for soils around Oldham Pond is taken as the same value reported by LeBlanc (1984) and by Robertson et al. (1991). Range for sensitivity per Garabedian et al. (1991). e. Values are total P, converted from literature ortho-P values assuming 87.5% of total P is ortho-P, based on a range of 85-90% (McCray et al. 2005).
phosphorus from more systems reaches the lake. After the 1994 laundry detergent ban, the loading declined briefly, but then resumed an increasing trend by 2010 as the number of contributing OWSs continued to increase. The model predicts that phosphorus loading from OWSs will continue into the future, even with no further development in the watershed.
in-lake total phosphorus concentration of 40 µg/l for 1987–8 (BEC 1993) and 66 µg/l for 2006 through 2010 (CEI 2011) show that the in-lake total phosphorus concentration increased by about 17.9% per decade from 1988 to
2010. There is a slight temporal mismatch: for the years corresponding to the observations, the model already predicts a decrease due to the phosphorus detergent ban. However, this may simply be a timing issue in the model (see the parameter sensitivity analysis, below and Supplement 4.2.7.6).
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1600
1400
1200
1000
800
600 Eutrophic
400
Mesotrophic 200
Oligotrophic 0 Phosphorus Loadingfrom OWS to Oldham Pond, kg/yr Pond,Oldham to OWS Loadingfrom Phosphorus 1750 1850 1950 2050 2150 2250 2350 2450 2550 2650 2750 Year This Model NPSLAKE BEC (1993) Adjusted CEI (2011) Adjusted BEC (1993) Original Estimate CEI (2011) Original Estimate Permissible Loading (Vollenweider 1975) Dangerous Loading (Vollenweider 1975) Monte Carlo Median Monte Carlo Lower 90th Percentile Monte Carlo Upper 90th Percentile Figure 4.4: Estimated total phosphorus loading to Oldham Pond from OWSs versus time, 1750 through 2750, and Monte Carlo uncertainty analysis. Triangles are loading estimates by Baystate Environmental Consultants, Inc. (BEC 1993) and Comprehensive Environmental Inc. (CEI 2011) respectively, and circles are adjusted values as described in the text and Supplement 4.2.7.5.
4.2.4.2 Relation to trophic state and other loading estimates
Trophic status bands for “permissible” and “dangerous” loading
(Vollenweider 1975) put these loads into the context of lake eutrophication
(Figure 4.4). Oldham Pond phosphorus loading from OWSs alone passed
Vollenweider’s “dangerous” level into the eutrophic zone by about 1960, and continues to be sufficient to maintain a eutrophic state, without considering any other source of phosphorus to the lake.
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We compared our results to an estimate using the NPSLAKE procedure of
Mattson and Isaac (1999), i.e. 0.5 kg/yr for each household within 100 m of the lake. This procedure is recommended by the Massachusetts Department of
Environmental Protection to estimate phosphorus loading from OWSs when establishing TMDLs according to the Clean Water Act (CWA 2002). Similar procedures based on export coefficients are used elsewhere in the U.S. and
Canada (see for example Paterson et al. 2006, Dillon et al. 1994). In 2016, there were 241 households within 100 m to Oldham Pond in the watershed; the
NPSLAKE procedure yields an estimated phosphorus loading substantially below our estimate (Figure 4.4).
Our estimate of phosphorus loading from OWSs via groundwater can be compared to independent estimates based on nutrient budgets. Baystate
Environmental Consultants (BEC) estimated the phosphorus loading by groundwater to the lake in 1988 (BEC 1993; Figure 4.4, “BEC (1993) Original
Estimate”). Their estimate was based on flow and concentration measurements, and included three important assumptions. First, outflow from the lake was based on a water budget of a downstream lake, and not actual flow measurements.
Second, an imbalance in the water budget was assumed to be due to missing runoff flows and not groundwater. Third, the groundwater concentration was based on measurements from littoral interstitial porewater (LIP) samples and the much lower concentrations at nearby wells. We used the measured outflow from the lake, attributed the missing flow to groundwater, and used the concentration from LIP samples only. We evaluated BEC’s well data and determined that it was
76 not representative of the groundwater entering the lake, because drinking water wells are purposefully sited away from septic systems (or OWSs are sited away from wells) in accordance with Massachusetts regulations “Title 5” (MADEP
2016), so that well phosphorus concentrations provide a biased (low) estimate for groundwater entering the lake. After this adjustment, the estimate of phosphorus loading by groundwater is substantially higher and closer to our model (Figure
4.4, “BEC (1993) Adjusted”). See Supplement 4.2.7.5 for details and additional discussion.
Comprehensive Environmental, Inc. (CEI) estimated the phosphorus input by groundwater in 2010 (CEI 2011; Figure 4.4, “CEI (2011) Original estimate”).
They based their estimate on runoff coefficient models and the concentration measurements by BEC (1993). For the groundwater, they also used only BEC’s
LIP sample data. When they compared their estimated total load (from all sources) to a value back-calculated from the in-lake phosphorus concentration
(using the method of Reckhow (1979)), they concluded that there is a large unaccounted for source. We attribute that source to groundwater, so the phosphorus loading by groundwater is substantially higher and is comparable to our model (Figure 4.4, “CEI (2011) Adjusted”).
4.2.4.3 Parameter sensitivity analysis and uncertainty (Monte Carlo) analysis
To quantify the sensitivity of the model to the input parameters we performed a parameter sensitivity analysis (see Supplement 4.2.7.6.1). The
77 results show that the magnitude of the loading is most sensitive to the effluent concentration (Ceff), and to a lesser extent, to the vadose zone phosphorus removal efficiency (). The timing of loading is sensitive to the hydraulic conductivity (Ks) and distribution coefficient (Kd). To quantify the overall uncertainty in the model results we performed a Monte Carlo analysis (Figure
4.4). The results show uncertainty in timing and magnitude. For example, the upper and lower 90% confidence intervals have final loading magnitudes about a factor of 1.4 and 2.0 different from the median or base values, respectively. This level of uncertainty is relatively high, and illustrates the need for more data specific to the Oldham Pond watershed. However, the model still provides important information for management. In climate science, models also have a high level of uncertainty, but it is recognized that they represent our best estimate, and their predictions are used for management (Maslin and Austin
2012). We also performed the Monte Carlo analysis using the full literature ranges of parameters (vs. the local ranges used above). The resulting uncertainty is substantially higher, further highlighting the need for site specific parameter estimates in these types of studies (see Supplement 4.2.7.6.3).
4.2.4.4 Effect of vadose zone immobilization and travel time
To illustrate the effect of phosphorus immobilization in the vadose/unsaturated zone and retardation in the aquifer/saturated zone, we compared the loading to the lake to that leaving the OWSs and entering the groundwater (Figure 4.5). The total load leaving all the OWSs increased with
78 development of the watershed and exhibits an abrupt drop in 1994 due to the detergent phosphorus ban. The load entering the groundwater is approximately proportional to this, although there are temporal differences in the vadose zone efficiency as cesspools are replaced by septic systems. The load to the lake reflects the retardation and travel time in the groundwater, and shows that the plumes of a substantial fraction of the OWSs are still en route to the lake.
Stage 1: Loading to Soil, Weff Stage 2: Loading to Groundwater, Wo Stage 3: Loading to Lake, W 3000
2500
2000
1500
1000
500 Detergent P Ban,1994 Phosphorus Loading, kg/yr Loading, Phosphorus
0 1750 2250 2750 Year
Figure 4.5: Comparison of phosphorus loading by model stage.
4.2.4.5 Effectiveness of past and potential future management actions
We explored the effect of past management actions, including the 1994 detergent phosphorus ban and the conversion of cesspools to septic systems. If these management actions had not been implemented, phosphorus loading to the lake in 2016 would be 32% higher with no detergent phosphorus ban, and
64% higher with no ban and continued use of cesspools (Figure 4.6). These
79 differences increase for future years. In addition, the model is used to estimate the impact of replacing all OWSs by a sewer system and wastewater treatment plant (WWTP). Because design, site selection, licensing, and construction would take time, the year 2030 is used as a plant start date for illustration. We assume the effluent from the WWTP is discharged to the lake. Based on tertiary
2500
2000
1500
1000
Phosphorus Loading, kg/yr
No detergent P ban 500 Cesspools and No detergent P ban
Phosphorus Loading to Oldham Pond, kg/yr Pond, Oldham to Loading Phosphorus WWT in 2030
0 1750 1850 1950 2050 2150 2250 2350 2450 2550 2650 2750 Year Figure 4.6: Comparison of model estimated phosphorus loading to estimates (1) if no laundry detergent phosphorus ban (blue dashed curve), (2) if All OWSs were built as cesspools (red dashed curve) and (3) if all OWSs were replaced by a sewer system and WWTP in 2030 (green dashed curve).
treatment for phosphorus removal that achieves 100 µg/l P in the effluent
(USEPA 2007, MADEP 2004), the phosphorus loading from the plant could be as low as 18.73 kg/yr. Although the loading to the lake decreases rapidly at first, residual loading continues for many years due to the present reservoir of phosphorus in the groundwater (Figure 4.6). The time from installation to when the loading from OWSs and WWTP to the lake is cut in half is 20 years. The loading is estimated to decrease to Vollenweider’s “permissible” load by 2112.
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4.2.4.6 Relation to Other Studies
Our results add to the growing body of evidence that suggests phosphorus from OWSs can be a substantial contributor to eutrophication of downstream lakes. Our study is unique in that it explicitly links the OWS source to the lake loading and accounts for the dynamics of system installation, cesspool to septic system conversion, laundry detergent phosphorus ban, and transport and retardation in the groundwater. Past studies have established that groundwater input is significant and implicated OWSs (Vanek 1991, Jarosiewicz and Witek
2014, Meinikmann et al. 2015), or estimated loadings from OWSs, but did not consider the dynamics of transport to the downstream lake (Valiela and Costa
1988, Weiskel and Howes 1992, Dudley and May 2007). Our results suggest that long-term dynamics are important. For example, the model predicts the loading to the lake will continue to increase for several hundred years, even without additional OWSs, so long-term dynamics need to be considered.
4.2.4.7 Management perspective
Our results contradict the current paradigm that OWSs are not an important source of phosphorus, due to sorption and precipitation, and have serious implications for lakes with similar hydrology and watershed development.
They suggest that current lake management methods to prevent or remediate algae blooms and nuisance plants are not likely to be successful in the long term until the OWS source is addressed. If continued use of OWSs is elected in lieu of a sewer system and wastewater treatment plant, regulations for OWSs should be
81 changed to ensure vadose zone efficiency in immobilizing phosphorus is as high as possible. Additional and continued education of OWS users should emphasize decreased water use to lower the phosphorus load to the OWS, as well.
Further research is needed to quantify the impact of OWSs at the watershed level over extended times. More field research is also needed to establish local soil parameters at a watershed scale, especially local average values for Ks, Kd, and vadose zone efficiency, η, to reduce the uncertainty inherent in using average literature values from other watersheds.
4.2.4.8 Outlook
The model we have presented here can be applied to other lake watersheds and, with some modifications, to a larger scale - regional and national – to characterize the long-term impact of OWSs. Much of the required data are available in national databases, for example: population and household data from the U.S. Census; water use data from the U.S. Geological Survey; watershed and surface water body data from the National Hydrography Dataset
(USGS); soils data from the USDA-NRCS Soils Survey Manual; elevation data from the National Elevation Dataset (USGS). These data must be supplemented by local and regional data regarding groundwater aquifers. As in the Oldham
Pond study, there will be substantial uncertainty associated with the estimated
OWS loading in such a study. However, even “best estimate” or “worst case” loadings will be quite useful for lake managers.
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4.2.5 Acknowlegments
The authors thank Donna Tremontana and Theresa Cocio of the Hanson
Health Department and Lisa Cullity of the Pembroke Health Department who provided data. The lead author thanks Eileen M. Penney for financial support.
This paper was improved by review and comment by anonymous reviewers. This research did not receive any grant from funding agencies in the public, commercial, or not-for profit sectors.
4.2.6 References
References have been removed to the REFERENCES section.
4.2.7 Supplement to Paper: Phosphorus Loading from Onsite Wastewater
Systems to a Lake (at Long Time Scales)
Frank L. Schellenger and Ferdi L. Hellweger
4.2.7.1 Contents
4.2.7.2 Accounting for Time-variable Source Function Using Superposition.
Figure 4.7: Sample loading calculation for a single OWS illustrating
superposition.
4.2.7.3 Model inputs.
Figure 4.8: Distribution of cesspool replacement dates for the Town of
Hanson, MA. Grouped by decade.
83
Figure 4.9: Surface elevation vs. high groundwater elevation for test-pit
data for OWSs in the Oldham Pond watershed.
Figure 4.10 Determination of best-fit Kd value, based on Ashumet Pond
data.
4.2.7.4 Illustration of Model Behavior.
Figure 4.11: Loading curves for 5 sample OWSs with different life
histories.
4.2.7.5 BEC (1993) P Loading Calculation and Revised Loading Calculation.
Figure 4.12: Comparison of the Number of OWSs Contributing to Well P
Concentration vs. the Number Contributing to LIP Sample P Concentration
in 1988-9 at Oldham Pond.
Table 4.2: Flow, P Concentration, and P Load, Oldham Pond, 1987-8.
Modified from BEC (1993).
4.2.7.6 Parameter sensitivity analysis and uncertainty (Monte Carlo) analysis
4.2.7.6.1: Parameter sensitivity analysis.
4.2.7.6.2 Uncertainty (Monte Carlo) analysis using the local ranges.
4.2.7.6.3 Uncertainty (Monte Carlo) analysis using the literature ranges.
Figure 4.13: (A - E) Parameter sensitivity analysis. (F) Monte Carlo
analysis using the literature ranges.
4.2.7.7 Supplement References.
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4.2.7.2 Accounting for Time-variable Source Function Using Superposition.
The analytical solution (Eq. 4.4) is based on a step input loading.
However, the loading changes due to cesspool to septic system conversion and the 1994 laundry detergent phosphorus ban. A time-variable loading can be modeled using the principle of superposition.
For each OWS, the model calculates the phosphorus load to the lake for each year after initial installation. Our calculation procedure recognizes five (5)
OWS histories based on when a cesspool (CP) or conventional septic system
(SS) was in use, and it also accounts for the 1994 laundry detergent phosphate ban in Massachusetts: (1) CP, never replaced; (2) CP replaced by SS before
1994; (3) CP replaced by SS after 1994; (4) No CP, SS before 1994; and (5) No
CP, SS after 1994. Consider, for example, the case where a cesspool is replaced by a septic system before the 1994 detergent phosphorus ban (Figure 4.7).
Before the conversion, the load is calculated using the cesspool loading (green line). At the time of the conversion, the cesspool loading is removed by adding a negative load (blue line), and the septic system loading is added (red line). After
1994, the new (lower) loading is calculated (yellow line), and the pre-1994 load is removed by adding a negative load (purple line). The resulting loading to the lake is the sum of these five lines (black line).
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3
2
1
0 1950 1975 2000 2025 2050 2075 2100 Year
-1 Phosphorus Load, kg/yrLoad,Phosphorus
-2 CPhi SShi SSlo -SShi -CPhi Sum -3 Figure 4.7: Sample loading calculation for a single OWS illustrating superposition. The OWS was installed as a CP in 1952 and replaced by a SS in 1986. Loading changed in 1994 with the laundry detergent phosphorus ban.
4.2.7.3 Model inputs
There are currently 859 residences and small commercial facilities within the Oldham Pond watershed (MassGIS no date), and each has an OWS, as determined from Town Health Department files, accessed locally. We calculated the time-variable phosphorus loading from each of these systems to the lake from the time of installation going forward, and then summed them to estimate the annual loading to the lake. This calculation is done year-by-year for the entire range of years for which OWSs have existed in the watershed, and into future years. Following is a description of the model inputs given in Table 4.1, organized by the three model stages.
Stage 1. Loading from the Cesspool or Septic Tank
For each OWS, the initial installation of a system was assumed to occur when the residence or commercial building was built, as determined from Town
Assessors tax record data. Because the model calculations use different Weff and
Wo inputs for cesspools (CP) and conventional septic systems (SS), it was
86 necessary to specify when a CP was replaced by a SS. For the Town of Hanson, we obtained complete data for CP to SS replacement dates from the Health
Department (Figure 4.8). For the Town of Pembroke, these data were not readily available. Therefore, for OWSs first installed before 1962 (after which a SS would have been required), we used the distribution from Hanson to randomly assign
CP replacement dates to the 143 Pembroke cesspools. Ceff depends on a number of factors including the contributions of blackwater (toilet waste), and other wastewater streams (e.g. kitchen, bath, laundry), as well as the biological conversion of solid organic phosphorus compounds to soluble products. Ceff may also change in time due to the detergent phosphorus ban (e. g. in 1994 for
Massachusetts, Litke 1991). We assumed the average phosphorus concentration in septic tank effluent, Ceff, is constant before and after the 1994 detergent phosphorus ban, and we used the average values reported by McCray et al.
(2005) (Table 4.1).
The flow rate is determined by water use: Qo = (Number of persons in the household) × (volume of water used per person per time). The average household in Pembroke and Hanson, MA has 2.86 people (based on the 2010
U.S. Census). Average water use per person in Plymouth County, MA has been estimated as 65 gal/d (246 l/d) (Maupin et al. 2014), which is close to the U.S. median of 260 l/person/day (McCray et al. 2005). Thus, the household water use is about 257 m3/yr per household. This value is reduced by 15% for consumptive use (Masterson, et al. 2009), so the average household effluent flow (Qo) is 218 m3/yr.
87
70
60
50
40
30
20
10 Number of CPsSSReplaced byof Number
0 No SS 1970-79 1980-89 1990-99 2000-09 2010-15 Time of Replacement
Figure 4.8: Distribution of cesspool replacement dates for the Town of Hanson, MA, grouped by decade.
Stage 2. Loading to the Groundwater
The efficiency of phosphorus immobilization in the vadose zone has been reported to range from 0% to 99% (Robertson 2008, Robertson et al. 1998,
Eveborn et al. 2012). Researchers at the Massachusetts Alternative Septic
System Testing Center in Barnstable, MA used typical conventional septic system designs with the SAS in sand typical of southeastern MA and Cape Cod, and determined that an average of 47% of the phosphorus in the septic system effluent reached the water table when the vadose zone depth was 5 feet (1.5 m)
(Heufelder and Mrockza 2006). This is close to the minimum requirement for
Massachusetts septic systems of 4 feet (1.2 m) (MassDEP 2016). We used an efficiency 50%, which corresponds to the mid-point of the literature range and is close to the regional value of Heufelder and Mrockza (2006). It is likely that the
88 geology of this site (non-calcareous soils, low pH) is conducive for phosphorus mineral precipitation and that removal efficiency may be higher (Robertson 2003 and 2012), and we performed a sensitivity analysis on this parameter (see
Section 4.2.7.6, below). For cesspools, the efficiency is expected to be lower, so we used the midpoint of the range from 0% (minimum of literature range) to 50%
(value used for septic systems) (Table 4.1).
Stage 3: Loading to the Lake
To determine the distance of each OWS to the lake, x, we first developed a GIS map for the watershed, using the Town Assessors parcel (tax) maps for
Hanson and Pembroke (MassGIS no date). OWSs were plotted as a point layer.
The distance x was determined assuming that phosphorus that reached a stream or wetland connected to the lake would reach the lake in a short time compared to the time scale of the model calculations. The streams are short (0.1 – 1.5 km); using the method described by Smith et al. (1997), we determined that phosphorus loss in these small streams will be less than 1%. The small (1 – 20 ha) wetlands these streams drain are hydraulically connected to the lake, so that attenuation and loss of phosphorus will be minimal. This feature of the Oldham
Pond watershed may not apply to other lake watersheds.
The distance from the OWS to the down-gradient surface water was estimated assuming the groundwater topography mimics the surface topography
(see below). Calculations were done using the ArcHydro tools in ArcGIS.
Specifically, we filled sinks in the 10-m digital elevation model (DEM), set surface water features (lake, streams and wetlands) to null, and calculated flow direction
89
(Maidment 2002). We then used the flow path tracing tool to calculate the flow path for each system to the nearest surface water feature (Figure 4.2). We calculated the length of each path using ArcGIS functions.
The hydraulic gradient, i, is determined for each OWS from the average groundwater elevation at two locations along the flow path. This study is concerned with the long-term (i.e., 1,000 years) dynamics, and seasonal or inter- annual variability is not considered. The down-gradient location is the surface water body used to determine x, as described above, and the up-gradient location is the water table at the OWS. Data were collected from Town Health
Department records in both towns on the surface and high groundwater elevations for test pits required for the design of new or replaced septic systems.
31
29
27
25
23
21
19 y = 0.9305x - 0.2773
17 R² = 0.9393 Groundwater Elevation Elevation Groundwater(m)
15 17 22 27 32 Surface Elevation (m)
Figure 4.9: Surface elevation vs. high groundwater elevation for test-pit data for OWSs in the Oldham Pond watershed.
If surface elevation was not recorded, it was estimated from the DEM in the
ArcGIS file. These data show a relationship between groundwater elevation and
90 surface elevation (Figure 4.9). The resulting linear regression equation is used to estimate groundwater elevation from surface elevation when that information is not available.
The average pore water velocity, ux, was estimated using the Darcy equation, ux = Ks* i/n where i is the hydraulic gradient (slope of the water table).
Ks was estimated from literature values for medium to coarse sand and gravel similar to the aquifer sands around the lake. The range of Ks for sand, as is found in the unconfined aquifer underlying Oldham Pond), is 8.64 to 8.64 m/day
(Freeze and Cherry 1979). We used a value of 13.72 m/day, consistent with
Carlson and Lyford (2005). Dispersivity, αx, was estimated using literature values obtained from field tracer studies of macrodispersion. For the scale of OWS plume distances in the Oldham Pond watershed, about 10 to 1000 m, the range of αx is reported to be 0.1 to 100 m (Garabedian et al. 1991). We consider the tracer test performed by the USGS near Ashumet Pond in Mashpee and
Falmouth on Cape Cod, Massachusetts by Garabedian et al. (1991) to best represent the aquifer sands around Oldham Pond and elsewhere in southeastern
Massachusetts. They found longitudinal dispersivity αx = 0.96 m. We used αx = 1 m, which is also consistent with the value found by Robertson et al (1991) at the
Cambridge, Ontario site.
Calculation of retardation, R, requires values for n, ρb, and Kd. For medium to coarse glacial outwash sand typical of the aquifers in the region, n ranges from about 0.30 to 0.42 (LeBlanc 1984); we used n = 0.39; this value is consistent with the value used by LeBlanc (1984) and Walter et al (1996). The soil bulk density,
91
ρb was determined by the relationship n = 1 – ρb/ρs where the soil density ρs is assumed to be 2.65 g/cm (Freeze and Cherry 1979). The sorption distribution coefficient, Kd, was determined by curve-fitting phosphorus concentration and distance data from USGS research on the effluent plume from the Otis Air Force
Base near Ashumet Pond, Mashpee and Falmouth, Massachusetts. (LeBlanc
1984). Literature values range from 1.4 to 478 cm3/g (McCray et al. 2005). We
3 used Kd = 5.0 cm /g, the best fit we obtained (Figure 4.10).
8
7
6
5
4
3
2
1
0 PhosphorusConcentrationinGroundwatr, mg/L PhosphorusConcentrationinGroundwatr, 0 200 400 600 800 1000 1200 Distance from Infiltration Beds, x (m) Measured 43 yrs Modeled at 43 yrs, Kd = 7.0 Measured 57 yrs Modeled at 57 yrs, Kd = 5.0 Modeled at 57 yrs, Kd = 4.6
Figure 4.10: Determination of best-fit Kd, value, based on Ashumet Pond data (LeBlanc 1984, Walter et al. 1996).
4.2.7.4 Illustration of Model Behavior
We illustrate the behavior of the model using the loading time series for five sample OWSs. Sample loading time series for 5 systems representing different histories illustrate the effect of cesspool replacement and the 1994
92 laundry detergent phosphorus ban (Figure 4.11). For example, Case 2 represents an OWS where a cesspool was originally built, and then replaced by a septic system before the 1994 laundry detergent phosphorus ban.
CP, never a SS CP then SS before 1994 CP then SS after 1994 No CP, SS before 1994 No CP, SS after 1994
3
2
1 Phosphorus Loading, kg/yr Loading, Phosphorus
0 1930 1946 1962 1978 1994 2010 2026 2042 Year
Figure 4.11: Loading curves for 5 sample OWSs with different life histories.
4.2.7.5 BEC (1993) P Loading Calculation and Revised Loading Calculation.
Baystate Environmental Consultants, Inc. (BEC 1993) obtained flow and phosphorus concentration data for Oldham Pond, recorded in columns “Meas.
Flow” and “BEC Calc. P Conc.” in Table 4.2 below. They performed a water balance for Oldham Pond and then adjusted the flows based on (1) a mismatch in the inflow and outflow for the downstream lake, Furnace Pond, and (2) a mismatch in inflow and outflow for Oldham Pond. Their first adjustment reduced the flow from Oldham Pond to Furnace Pond. After this change, the Oldham
Pond total outflow (8.01 m3/min) was still larger than total inflow (6.19 m3/min), so
93 the second adjustment was to add the difference to the tributary inflows, in proportion. Their adjusted flows are shown in the column “BEC Adj. Flow.” They then calculated phosphorus loads as flow times concentration, recorded in the column “P Load.”
We suggest that a better estimate of the groundwater flow rate is obtained if (1) the lake outflow is based on measurements; and (2) the imbalance is attributed to groundwater flows. Because Oldham Pond and other lakes in the area are primarily groundwater fed (Carlson and Lyford 2005), the measured groundwater flow by temporary seepage meters is highly uncertain. Tributary flows to Oldham Pond have very little baseflow; these tributaries carry primarily storm drainage. We therefore recalculated the water balance based on measured surface outflow and adding the difference (outflow – inflow = 3.77 m3/min) to the groundwater inflow (*). Our adjustments are shown in the column “Re-adj. Flow.”
BEC (1993) computed the phosphorus concentration in groundwater by averaging observations taken from littoral interstitial pore water (LIP) measurements (173 µg P/l), and averaging observations from well samples (51
µg P/l), and then averaging these two averages, for a final average of 112 µg P/l.
We suggest that well samples should be excluded, on the basis that well phosphorus concentrations provide a biased (low) estimate for groundwater entering the lake. In general, drinking water wells are purposefully sited away from septic systems (or OWSs are sited away from wells), in accordance with
Massachusetts Title 5 regulations (MassDEP 2016). Five of the 7 wells tested by
BEC tested very low for TP. The two well samples that tested high for TP may
94 have come from wells that were installed down-gradient from the OWSs before the Title 5 regulations went into effect. We estimated the number of OWSs that contributed to well and LIP samples by visually tracing flow paths upstream and counting the number of households at the time of the BEC study. Figure 4.12 compares the number of contributing OWSs and the average TP concentrations.
This analysis supports the idea that well samples are biased low due to fewer contributing OWSs. In their 2010 study, Comprehensive Environmental Inc. (CEI
2011) made the same adjustment when using the BEC (1993) data. This adjustment is shown in the column “Adj P Conc.” Based on these assumptions, the groundwater loading is 424 kg/yr, and the total phosphorus load to the lake is
710.8 kg/yr (**), as recorded in the column “Revised P load.”
250
224
200
173
Number of Contributing OWSs 150 Average P Concentration. ug/l
100
51 50
37
Number of Contributing OWSs (red bars)(red OWSs Contributing of Number AverageTotal P Concentration (µg/L) (blue bars)(blue (µg/L) Concentration P AverageTotal
0 WELLS LIPS Figure 4.12: Comparison of the Number of OWSs Contributing to Well P Concentration vs. the Number Contributing to LIP Sample P Concentration in 1988-9 at Oldham Pond.
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Table 4.2: Flow, P Concentration, and P Load, Oldham Pond, 1987-8.
Modified from BEC (1993).
Station Meas. BEC BEC P load, Re-adj. Adj. P Revised see Flow, Adj. Calc. P kg/yr Flow, Conc. P load, BEC m3/min Flow, Conc., m3/min μg/l kg/yr m3/min μg/l Input Precipitation 2.11 2.11 24 26.6 2.11 24 26.6 Groundwater 0.89 0.89 112 52.4 4.66 * 173** 424 ** Stormwater PM-48 0.01 0.01 100 0.5 0.01 100 .5 PM-33 0.03 0.03 105 1.7 0.03 105 1.7 PM-34 0.03 0.03 217 3.4 0.03 217 3.4 PM-35 0.04 0.04 203 4.3 0.04 203 4.3 Tributaries PM-0 0.13 0.21 58 6.4 0.13 58 4 PM-1 1.23 2.00 103 108.2 1.23 103 66.6 PM-2 1.26 2.05 84 90.5 1.26 84 55.7 PM-46 0.29 0.47 182 45 0.29 182 27.8 Discharges PM-18 0.16 0.16 133 11.2 0.16 133 11.2 PM-49 0.01 0.01 0.01 24.3 0.01 0.01 24.3 Total 6.19 8.01 374.5 9.96 500.6 Waterfowl 2.0 2.0 Plant 58.7 58.7 Pumping Total Input 435.2 710.8 **
Outflow
Evaporation 1.37 1.37 1.37 Groundwater 0.03 0.03 0.03 Surface PM-4 9.48 7.53 9.48 Outflow Withdrawals PM-18 0.11 0.11 0.11 Storage -1.03 -1.03 -1.03 Change Total 9.96 8.01 9.96 For notes * and ** see text above.
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4.2.7.6 Parameter sensitivity analysis and uncertainty (Monte Carlo) analysis
4.2.7.6.1: Parameter sensitivity analysis
To quantify the sensitivity of the model to the input parameters we ran the model with each parameter at the minimum and maximum of their literature range (Figures 4.13A – E); parameter ranges are provided in Table 4.1).
Lower hydraulic conductivity (Ks) and higher retardation (Kd) slow down the phosphorus transport and shift the loading curve up in time (i.e., to the right,
Figure 4.13A). Conversely, higher Ks and lower Kd shift the curve back in time
(i.e., to the left). However, the ultimate long-term loading is not affected. Varying the effective porosity, n, and the dispersivity, αx, have little effect on loading over the entire time scale (Figures 4.13B and C).
The phosphorus load leaving the septic tank or cesspool, Weff, does affect the long term phosphorus loading to the lake. Weff is proportional to the effluent flow rate, Qo, and the effluent concentration, Ceff. No range is given for Qo, since it depends on water use and number of persons in the household, for which ranges were not found. However, a wide range has been reported for Ceff
(McCray et al. 2005), and the sensitivity calculation shows that model–predicted loading varies accordingly (Figure 4.13D). However, it is unlikely that all households in the watershed would have an average Ceff at either extreme of the range. Educating OWS users to use less water is one way to lower the long term phosphorus loading to a lake.
97
Sensitivity calculations on the efficiency of the unsaturated/vadose zone
() are based on data from Heufelder and Mrockza (2006) for tests of a conventional septic system in soil similar to the Oldham Pond watershed. The range of efficiency for these tests is 46 to 54 %. Field studies performed in other locales on OWS vadose zones have reported a wide range of phosphorus removal efficiencies, and there is substantial uncertainty in this parameter, with a literature range of 0 – 99% (see Table 4.1). The range can be narrowed by considering the geology and pH, which affect phosphate precipitation (Robertson
2003 and 2012). Non-calcareous soils in the region generally have a pH below
6.0, and therefore may have a higher phosphorus precipitation rate. This would suggest a wider efficiency range than the one observed by Heufelder and
Mrockza (2006) and used here, and further suggests that better, local estimates of vadose zone efficiency, especially considering OWS age would be useful.
Some studies (Dudley and Stephenson 1973, Koerner and Haws 1979, Eveborn et al. 2012) have reported that efficiency may decline over time, which our model calculations do not address. Clearly, the higher the vadose zone efficiency, the lower the long term phosphorus loading to the lake. Higher efficiency is facilitated by siting OWS with maximum vertical distance to the water table, and in soils having low permeability, i.e. finer textured soils, and in soils having higher levels of metallic oxides, usually indicated by darker chroma (Heufelder and Mrockza
2006). The results of the sensitivity test on efficiency (Figure 4.13E) suggest that these recommendations of Heufelder and Mrockza (2006) should be incorporated into OWS regulations.
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4.2.7.6.2 Uncertainty (Monte Carlo) analysis using the local ranges
To quantify the overall uncertainty in the model results we performed a
Monte Carlo analysis (Figure 4.3). Specifically, we ran the model 10,000 times with randomly selected parameters within the local ranges (Table 4.1). Due to the limited information available (i.e., baseline values, ranges) we use a triangular distribution with peak at the baseline value and minima and maxima based on the observed range. For parameters that vary over several orders of magnitude the selection was done in log space (see Table 4.1).
The results from the Monte Carlo analysis show that there is substantial uncertainty in the model prediction (Figure 3, text, showing 90% confidence intervals). The time when the mesotrophic--eutrophic threshold is crossed is
1940 for the upper interval, 1951 for the median and 1984 for the lower interval.
At the end of the simulation, the upper and lower confidence intervals are about a factor of 1.4 and 2.0 different from the median or base values, respectively
(Figure 3, text). Much of the uncertainty can be attributed to the wide range in effluent phosphorus concentration values (see 4.6.6.1 and Figure 4.13D).
4.2.7.6.3 Uncertainty (Monte Carlo) analysis using the literature ranges
We also performed the Monte Carlo analysis using the literature ranges from Table 1, text (Figure 4.13F). Again, we ran the model 10,000 times with randomly selected parameters, using the same procedure as above. The results again show substantial uncertainty in the model prediction (Fig. 4.13F, showing
99
90% confidence intervals). These results stress the need to use site-specific parameter estimates, especially for Ks, Kd and vadose zone efficiency, η.
Figure 4.13: (A - E) Parameter sensitivity analysis. (F) Monte Carlo analysis using the literature ranges; upper and lower bounds are 95th and 5th percentile values.
High Ks Low Ks A Low Kd High Kd Base Model
2000
1500
1000
500 Phosphorus Loading, kg/yr PhosphorusLoading, 0 1750 1950 2150 2350 2550 2750 Year
B Base Case alphax low alphax high 1200
1000
800
600
400
200 Phosphorus Loading, kg/yr Loading, Phosphorus 0 1750 1950 2150 2350 2550 2750 Year
100
C Base Model n high n low 1200
1000
800
600
400
200
Phosphoruskg/yr Loading, 0 1750 1950 2150 2350 2550 2750 Year
D Base Case High Ceff Low Ceff 2000
1500
1000
500 Phosphorus Loading, kg/yr Loading,Phosphorus 0 1750 1950 2150 2350 2550 2750 Year
101
Base Model Low efficiency E High efficiency 1200
1000
800
600
400
200 Phosphoruskg/yr Load,
0 1750 1950 2150 2350 2550 2750 Year
F 1600
1400
1200
1000
800
600 Eutrophic
400
Mesotrophic
200 Phosphorus Loadingfrom OWS to Oldham Pond,Oldham kg/yr OWS Phosphorus Loadingfromto Oligotrophic 0 1750 1850 1950 2050 2150 2250 2350 2450 2550 2650 2750 Year This Model NPSLAKE BEC (1993) Adjusted CEI (2011) Adjusted BEC (1993) Original Estimate CEI (2011) Original estimate Permissible Loading (Vollenweider 1975) Dangerous Loading (Vollenweider 1975) Monte Carlo Median Monte Carlo Lower 90th Percentile Monte Carlo Upper 90th Percentile
4.2.7.7 Supplement References
References have been removed to the REFERENCES section.
102
Appendix 4.1 Visual Basic Module Used in the Excel Calculations
The following Visual basic module is used in the model calculations of the phosphorus load from an OWS via the groundwater surficial aquifer to a surface water. Variables and parameters are coded as follows:
CPonYear is the year the OWS was first installed. CPoffYear is the year a cesspool was replaced by a septic tank system; if there was never a cesspool, CPoffYear = CPonYear in the dataset. DetYear is the year of the laundry detergent P ban, 1994. W0CP1 is the value of Wo from a cesspool SAS before the ban. W0CP2 is the value of Wo from a cesspool SAS after the ban. W0SS1 is the value of Wo from a septic tank system SAS before the ban. W0SS2 is the value of Wo from a septic tank system SAS after the ban. ux is the value of the average groundwater velocity. x is the distance from the OWS to the surface water. alphax is the longitudinal dispersivity. R is the retardation. tYear is the time-step.
Function LakeLoad(CPonYear As Double, CPoffYear As Double, DetYear As Double, W0CP1 As Double, W0CP2 As Double, W0SS1 As Double, W0SS2 As Double, ux As Double, x As Double, alphax As Double, R As Double, tYear As Double)
Dim LoadLoad As Double Dim W As Double Dim t As Double Dim WCP1on As Double Dim WCP2on As Double Dim WSS1on As Double Dim WSS2on As Double Dim WCP1off As Double Dim WCP2off As Double Dim WSS1off As Double Dim WSS2off As Double
LakeLoad = -9
'Before house was built (Case 0) If (tYear <= CPonYear) Then LakeLoad = 0# GoTo 10 End If
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'DETERGENT SWITCH BEFORE SS If (DetYear <= CPoffYear) Then
'Never a Cesspool mode (Case 5) If (CPonYear > DetYear) Then
t = tYear - CPoffYear W = W0SS2 WSS2on = Model(W, ux, x, alphax, R, t)
LakeLoad = WSS2on
GoTo 10
End If
'Cesspool before DetYear mode If (tYear <= DetYear) Then
t = tYear - CPonYear W = W0CP1 WCP1on = Model(W, ux, x, alphax, R, t)
LakeLoad = WCP1on
GoTo 10
End If
'Cesspool after DetYear mode (Cases 1 and 3) If (tYear > DetYear And tYear <= CPoffYear) Then
t = tYear - DetYear W = W0CP2 WCP2on = Model(W, ux, x, alphax, R, t)
t = tYear - CPonYear W = W0CP1 WCP1on = Model(W, ux, x, alphax, R, t)
t = tYear - DetYear W = W0CP1 WCP1off = Model(W, ux, x, alphax, R, t)
LakeLoad = WCP2on + WCP1on - WCP1off
104
GoTo 10
End If
'Septic system after DetYear mode (Case3) If (tYear > CPoffYear) Then
t = tYear - CPoffYear W = W0SS2 WSS2on = Model(W, ux, x, alphax, R, t)
t = tYear - DetYear W = W0CP2 WCP2on = Model(W, ux, x, alphax, R, t)
t = tYear - CPoffYear W = W0CP2 WCP2off = Model(W, ux, x, alphax, R, t)
t = tYear - CPonYear W = W0CP1 WCP1on = Model(W, ux, x, alphax, R, t)
t = tYear - DetYear W = W0CP1 WCP1off = Model(W, ux, x, alphax, R, t)
LakeLoad = WSS2on + WCP2on - WCP2off + WCP1on - WCP1off
GoTo 10
End If
End If
'DETERGENT SWITCH AFTER SS If (DetYear > CPoffYear) Then
'Cesspool mode If (tYear <= CPoffYear Or CPoffYear = 0) Then
t = tYear - CPonYear W = W0CP1
105
WCP1on = Model(W, ux, x, alphax, R, t)
LakeLoad = WCP1on
GoTo 10
End If
'Septic before mode If (tYear > CPoffYear And tYear <= DetYear) Then
t = tYear - CPoffYear W = W0SS1 WSS1on = Model(W, ux, x, alphax, R, t)
t = tYear - CPonYear W = W0CP1 WCP1on = Model(W, ux, x, alphax, R, t)
t = tYear - CPoffYear W = W0CP1 WCP1off = Model(W, ux, x, alphax, R, t)
LakeLoad = WSS1on + WCP1on - WCP1off
GoTo 10
End If
'Septic system after mode If (tYear > DetYear) Then
t = tYear - DetYear W = W0SS2 WSS2on = Model(W, ux, x, alphax, R, t)
t = tYear - CPoffYear W = W0SS1 WSS1on = Model(W, ux, x, alphax, R, t)
t = tYear - DetYear W = W0SS1 WSS1off = Model(W, ux, x, alphax, R, t)
t = tYear - CPonYear W = W0CP1
106
WCP1on = Model(W, ux, x, alphax, R, t)
t = tYear - CPoffYear W = W0CP1 WCP1off = Model(W, ux, x, alphax, R, t)
LakeLoad = WSS2on + WSS1on - WSS1off + WCP1on - WCP1off
GoTo 10
End If
End If
10
End Function
Function Model(W As Double, ux As Double, x As Double, alphax As Double, R As Double, t As Double)
Dim TERM1 As Double Dim TERM2 As Double
TERM1 = (R * x - ux * t) / (2# * (alphax * ux * R * t) ^ 0.5) TERM2 = (R * x + ux * t) / (2# * (alphax * ux * R * t) ^ 0.5) If (x / alphax) > 700# Then W = (W / 2#) * (Application.WorksheetFunction.ErfC(TERM1)) Else W = (W / 2#) * (Application.WorksheetFunction.ErfC(TERM1) + Exp(x / alphax) * Application.WorksheetFunction.ErfC(TERM2)) End If Model = W
End Function
107
CHAPTER 5
Application of the Model at a National Level (NatMod)
5.1 Introduction
In Chapter 3, we presented a simple mathematical model for phosphorus transport from OWSs to surface waters via the groundwater surficial aquifer, at long time scales. Chapter 4 reported a case study of a lake watershed in southeastern Massachusetts, USA to estimate an annual phosphorus load to the lake from the 859 septic systems in the lake watershed for past, present, and future years, using data gathered at the local level. We concluded that the phosphorus loading to the lake from OWSs alone was sufficient to cause and maintain a eutrophic state.
Here, we extend this simple model to a larger spatial scale, to estimate phosphorus loading from OWSs to surface waters in watersheds over the entire coterminous United States (i.e. the “lower 48”). To make the computations feasible at the national scale, the model unit is a watershed rather than an individual OWS. The phosphorus loading calculation is made for each watershed by aggregating the phosphorus loading from all the OWSs in the watershed. We apply Eq. 3.10 to each watershed by assuming there is a single, “super OWS”, located at the mean distance from surface water, and serving the entire
108 population using OWSs in the watershed. Population served by sewers and wastewater treatment plants are excluded. We use a set of constant parameters to Eq. 3.10 to solve for phosphorus load as a function of average distance to surface water, x, for a specific time step, t. The model calculation uses parameters that are mean values for each watershed or assumed constants based on literature values. Although x and t are variables in Eq. 3.10, the distance x is fixed for each watershed by the location of the “super OWS” and the locations of surface waters (see Section 5.2.2). For this study, the time step is a decade. Summation of the phosphorus loads calculated for each watershed in a region, or nation-wide, provides an estimate of the phosphorus load from OWSs to surface waters for that large area.
5.2 Method and Procedures
This section is a collection of procedures for the preparation of the inputs to the model calculations. Each of the required inputs is discussed in the subsections below; the sources of the data are identified, and the method of processing the data to obtain a mean value for each watershed is described.
Most of the data are acquired as shapefiles for ArcGIS (ESRi); we use ArcMap
10.3. Processing the data requires ArcMap tools and MsExcel calculations, and we describe the movement between them. Since we are modeling the phosphorus load from OWSs to watersheds, it is necessary to “marry” the geography of watersheds to the geography of OWS use. The latter is given by data from the US Census (hence the decadal time step), for which the geography
109 is based on political boundaries, not watershed boundaries. The procedure for this “marrying” process is given in Section 5.2.3.2.3.
5.2.1 Watersheds
The United States Geological Survey (USGS) has mapped the watersheds of the United States at several spatial levels and assigned each watershed a Hydrologic Unit Code, or HUC (USGS no date). Here, we use the
“sub-watershed” division of USGS watersheds, identified by 12-digit HUCs
(HUC12s). We obtained boundary data for the HUC12s from the National
Hydrology Dataset (NHD no date). The NHD provides the shapefile that describes the boundaries of the HUC12 watersheds. We used the high resolution data snapshot from the NHD (http://nhd.usgs.gov/data.html). The data is available only in a geodatabase (.gdb) on their FTP site:
(ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Hydrography/NHD/National/
HighResolution/GDB/).
The geodatabase has two feature datasets: Hydrography and Watershed
Boundary Data (WBD), and the HUC12 boundaries are in the WBD. All files from the NHD come in the GCS_North_American_1983 coordinate system. We projected the files into the USA Contiguous Albers Equal Area Conic coordinate system to match the coordinate system used for the U.S. Census boundary shapefiles (see Section 5.2.3.2).
The ArcGIS interface with Excel requires that Excel files be saved in 1993-
2003 format (.xls). This version of the Excel format can only accommodate
110
~65,000 rows of data. We determined that there are 83,055 HUC12s in the lower
48 States. Of these, 579 HUC12s contain water only, e.g. large lakes, estuaries and coastal waters, leaving 82,476 HUC12s having land area. Since the HUC12 shapefile attribute table has >83,000 lines, we split the HUC12s and made 2 shapefiles, “east” and “west”. The division was arbitrary, based on numbers only, and could be modified to split the country along major watershed boundaries, for example at a HUC2 level (USGS no date).
5.2.2 Distance to Surface Water
The analytical solution used by the model calculations requires the distance to surface water, x, from the OWS. This distance is determined by calculating the average (mean) distance within each HUC12 watershed from any place in the HUC12. The “super OWS” is assumed to be at this location. Thus, the value of x is fixed for each HUC12 watershed. The calculation uses NHD data for waterbodies and flowlines (rivers and streams) to locate the surface waters.
The NHD provides shapefiles for flowlines (streams and rivers) and waterbodies (lakes). The features needed are in the Hydrography dataset: the
“NHDWaterbody” feature class contains all of the waterbodies, and the
“NHDFlowline” feature class contains the rivers/streams. We combined the shapefiles for HUC12 boundaries (“east” and “west”, see Section 5.2.1 above) and the flowlines and waterbodies shapefiles in an ArcMap map, and made a raster of the surface waters for the entire coterminous U.S., at 30 m resolution.
111
We then used the Euclidean Distance tool on the surface water raster with an output cell size of 30. This tool gave a Euclidean distance raster for the entire nation. Each pixel value gives the distance from its center to the nearest pixel classified as surface water. Then we used the Zonal Statistics as Table tool
(Spatial Analyst Tools/Zonal) with the “east” and “west” files to find the Mean
Euclidean distance within each HUC12 (Figure 5.1). The resulting attribute tables provided the mean distance to surface water, x, from any point within each
HUC12. We exported these tables to Excel for use as input to the model calculations.
Figure 5.1: Mean Euclidean Distance to Surface Water, x (m). Note that the State of Indiana has provided input to the USGS of a denser network of flowlines, which reduces the mean Euclidean Distance compared to the rest of the U.S. (USGS 2017).
112
5.2.3 Constant Parameters
The model calculations require values for average effluent phosphorus concentration, Ceff, average water use per person, vadose zone efficiency, η, soil bulk density, ρb, longitudinal dispersivity, αx, and sorption distribution constant,
Kd. These parameters are assumed constants using literature values, based on our previous work (Chapter 4 and Table 5.1). For each HUC12 watershed, values for saturated hydraulic conductivity, Ks, effective porosity, n, hydraulic gradient (slope of the water table), i, and non-sewered population are required, also. Although each parameter may take a different value from one watershed to another, all the parameters are treated as constant within a HUC12 watershed.
See Sections 5.2.3.1 and 5.2.3.2.
The concentration of phosphorus in the effluent leaving the septic tank of an OWS, Ceff, is given two (2) constant values (Table 5.1). Many states have instituted bans on phosphorus in laundry detergents, and the bans were enacted at different times (Litke 1999). For simplicity, we assumed that the ban in each
State was effective in 1994, when the major detergent makers discontinued phosphate builders in laundry detergent. The model calculation assigns a lower effluent phosphorus concentration from that year on (McCray et al 2005), which lowers the load to the water table for HUC12s. The model does not account for bans on dishwashing detergent phosphorus, some of which occurred in 2010.
Vadose zone efficiency, η, represents the phosphorus retardation and immobilization processes as the effluent moves downward in the unsaturated
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SAS. As was done in our previous work, we assumed a constant average value for OWSs (Table 5.1). The value chosen represents an average of literature values and assumes the OWSs are sufficiently mature to be in “steady state”, i.e. the same percentage of phosphorus received is being immobilized in the vadose zone at all times (Robertson 1995, Beal et al. 2005). Vadose zone efficiency is highly variable, and local conditions may predominate. This
Parameter Symbol Units Value Sources/ Used (Range) Notes Effluent concentration Ceff mg/L before 1994 ban 15.0 (6.3 - 24.9) c, 4 after 1994 ban 9.6 (1.4 - 15.2) c, 4
Average water use (none) L/person 246 10 SAS efficiency η - 0.5 (0 – 0.99) 1, 5, 8, 9
Longitudinal αx m 1.0 (0.1 - 100) 2, 3, 7, b dispersivity
3 Soil bulk density ρb g/cm See note a
3 Linear sorption Kd cm /g 15.1 (1.4 - 478) 4 coefficient
SAS: soil absorption system. Sources: 1. Robertson (1995); 2. Robertson et al. (1991); 3. LeBlanc (1984); 4. McCray et al. (2005); 5. Heufelder and Mrockza (2006); 7. Garabedian et al. (1991); 8. Robertson (2008); 9. Robertson et al. (1998); 10. U.S. Census. Notes: 3 a. Saturated soil density, ρs, is assumed to be 2.65 g/cm , and soil bulk density is then given by ρb = (1 – n) × ρs (Freeze and Cherry, 1979). b. Longitudinal dispersivity, αx, is taken as the same value reported by LeBlanc (1984) and by Robertson et al. (1991). Range for sensitivity per Garabedian et al. (1991). c. Values are total P, converted from literature ortho-P values assuming 87.5% of total P is ortho-P, based on 85-90% from McCray et al. (2005).
Table 5.1: Values of Constant Parameters used in the Phosphorus Loading Calculations.
114 parameter is one major source of uncertainty in the model results. Some research has concluded that vadose zone efficiency declines with time (Dudley and Stephenson 1973, Koerner and Haws 1979, Eveborn et al. 2012), so our assumption of constant efficiency may be conservative for long times.
5.2.3.1 Hydraulic Conductivity, Hydraulic Gradient, and Effective Porosity
Parameters
Hydraulic conductivity data for the coterminous U.S. were derived from the
GLHYMPS project (Gleeson et al. 2011, Gleeson et al. 2014) in the form of a polygon shapefile. The GLHYMPS data were given in log permeability (m2) and were converted to Ks values (m/sec) (Russo 2016). The shapefile was then converted to a raster having a 30 m cell size. The mean value of Ks for each
HUC12 was then obtained using the ArcGIS Zonal Statistics as Table tool with the files “east” and “west” (Figure 5.2), as was done for mean distance (Section
5.2.2 above). Inspection of Figure 5.2 reveals a limitation in the use of the
GLHYMPS dataset: the values of Ks are discontinuous across some jurisdictional
(i.e. State) boundaries. Gleeson et al. (2014) attribute this limitation to their use of different data sources. See Section 5.4 for discussion of the uncertainty in our results introduced by the use of this national dataset.
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Figure 5.2: Hydraulic Conductivity, Ks, (m/yr), based on the GLHYMPS Project (Gleeson et al. 2011, Gleeson et al. 2014, Russo, 2016).
Hydraulic gradient and porosity data were also obtained from the
GLHYMPS project as polygon shapefiles and processed in the same manner to obtain mean values of i and n for each HUC12. Some portions of the coterminous U.S. did not have values in the shapefiles, so we assumed values based on the overall averages across the country, based on the mean values calculated by the Zonal Statistics as Table tool (Figures 5.3 and 5.4). The parameters Ks, i, and n provide an estimated average groundwater velocity, ux, used by the model calculation, using the Darcy equation (Eq. 3.2).
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Figure 5.3: Soil Effective Porosity, n, based on the GLHYMPS Project (Gleeson et al. 2011, Gleeson et al. 2014, Russo, 2016).
Figure 5.4: Mean Hydraulic Gradient, I, based on the GLHYMPS Project (Gleeson et al. 2011, Gleeson et al. 2014, Russo, 2016).
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5.2.3.2 Non-sewered Population
The load of phosphorus introduced into the “super OWS” depends on the average phosphorus concentration in the wastewater (a literature-derived value,
Table 5.1), the average wastewater volume per person, per year (also literature- derived), and the number of people served by septic systems. The latter is determined from the US Census (hence the decadal time-step). For decades from 1970 through 1990, data were also available for the population served by sewers. These data were used to estimate the non-sewered population within each HUC12 for each decade from 1790 through 2010. For decades other than
1970 - 90, these estimates were made using a regression methodology described below. Because the Census data are compiled by political and enumeration areas rather than by watersheds, the population data do not match
HUC12 areas. These data were processed to combine them to the HUC12s using a population density approach.
U.S. Census data for each decade 1790 through 2010 were downloaded from the National Historical Geographic Information System (NHGIS 2011). For each Census decade, the County boundary shapefiles were also downloaded.
Population tables were taken for each County. Data on sewage disposal method were taken for 1970, 1980, and 1990, the only years available. For each Census decade, we created an ArcMap of the County boundaries and exported the attribute table. The exported table was then converted to Excel and saved in 97-
2003 (.xls) format. This file provides the County areas. The County population table is provided as a .csv table, which is opened by Excel and saved in .xls
118 format. For most of the decades, there are no data for the method of sewage disposal – these data are only available for 1970-90 Counties. For these 3 decades, the sewage disposal method data is also provided as a .csv table, which is opened by Excel and saved in .xls format.
We used the County population table as the base file and added columns for County Area and Population Density (D), where:
D = County Population / County Area Eq. 5.1
For decades other than 1970-90, we added a column for LOG D (see 5.2.4.2).
For all decades, we added a column for the percent of households served by sewers, called PERSEWER.
5.2.3.2.1 Estimating Non-sewered Population for decades 1970-90:
We used the sewage disposal method file, and added a column for
PERSEWER. The data are provided for the number of households served by sewers, the number of households served by septic systems, and the number of households served by “other” (e.g. privies, none). We elected to treat “other” households as served by OWS. The value of PERSEWER is calculated as:
PERSEWER = sewered households (sewered + septic systems + other) Eq.5.2
The values of PERSEWER were then imported to the County population file using a VLOOKUP statement. We then added a column for NSDENSITY and calculated it as:
NSDENSITY = (1 – PERSEWER) × D Eq. 5.3
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Here, we assume the percent of households served by OWS and the percent of the population served by OWS are the same, based on an average number of people per household.
Because the values of NSDENSITY are in units of people per m2, these values are very small, and subsequent use in ArcGIS is not recommended (a really small decimal is hard for GIS to store). Therefore, we added a column called INT (for “integer”), and calculated NSDENSITY × 109 and then used a
ROUND statement to round to an integer value. This operation makes the units people per 1,000 km2, which must be kept in mind for later use (see 5.2.5.3).
NOTE:
For the 1970 decade only, some values for the number of households
served by sewers in the County sewage disposal method file are given as
“-1”. We treated these entries as “0”, which assumes all households in that
County were served by OWS.
5.2.3.2.2 Estimating Non-sewered Population for decades other than 1970-
90:
Because the data obtained from NHGIS did not contain files for sewage disposal method, it was necessary to estimate PERSEWER for each County for each decade. We used a regression of the values reported for 1970-90 Counties. The values reported were combined in a single table containing the Population
Density (D) and PERSEWER. A third column was added for LOG (D). The
PERSEWER (PS) data were then “binned” by LOG (D), using bins 0.1 apart,
120 from the minimum value of LOG (D) to its maximum. The binned PS values were then averaged within each bin, and a plot of Average PS vs. LOG (D) was made
(Figure 5.5). For simplicity, a linear regression of Log (D) between -3 and -5 was used, and for Log (D) > 3, PS was assumed to be 100%. For Log (D) < -5, the population density (D) is very low, and we assumed a value of PS = 35%. The linear regression formula is:
PERSEWER (PS) = (0.30244764 × LOG (D)) + 1.86584425 Eq. 5.4
100%
90%
80%
70%
60%
50%
40%
Average PERSEWER (PS) PERSEWER Average 30%
20%
10%
0% -8 -7 -6 -5 -4 -3 -2 -1 0 Log (D)
Figure 5.5: Average Percent of Households Sewered vs. the Logarithm of Population Density for U.S. Counties, 1970 – 90.
Using this equation, and the simplifications noted above, a value of PERSEWER was estimated for each County, for each decade. Once PERSEWER is determined, the procedure continues as above, for NSDENSITY and INT.
NOTE:
For many of the decades, (perhaps all) some data were missing, and we
tried to add actual or estimated values whenever they could be found. The
121
objective was to have as complete a file as possible. In some cases,
however, values for both population and area were missing and could not
be found elsewhere or estimated. In these cases, the data line was
deleted. In all cases, however, data for Alaska, Hawaii, and Puerto Rico
were deleted.
5.2.3.2.3 Combining Non-sewered Population to HUC12 Watersheds
For each decade, we added the County data to the County map by converting the Excel file to a table, and then JOINed the table to the County shapefile. We then made a population raster on the INT field, that is, the number of people per area who are served by OWS. The final step was to combine the population raster with the HUC12 layers “east” and “west” using the Zonal
Statistics as Table tool to obtain the mean value of INT for each HUC12 (Figure
5.6). This procedure is necessary because the U.S. Census population data is reported by political boundaries (e.g. Counties), but the geographical extent of
HUC12s is by watershed.
The attribute table was then converted to Excel for use as input to the load calculations. The values given are mean non-sewered population density
(people/1000 km2) for each HUC12. This number must be multiplied by the
HUC12 area and by 1000 to get the actual number of people in the HUC12 who are served by OWSs. i.e. the population for the load calculation.
122
Figure 5.6: Non-sewered Population (persons served by OWSs), by HUC12, 2010.
5.2.4 Time
The final variable used by the analytical solution is time. We calculated the
OWS phosphorus load to surface water at a ten-year time step, measured from the time of the first Census. Because the non-sewered population changed with each decennial Census, the loading calculations were made by assuming the
OWS began operation five (5) years before the Census year. The loading calculation for the next decade required that the previous decade’s loading be subtracted, with the negative calculation beginning in the same year as the next decade. This superposition of positive and negative calculations is illustrated in
Chapter 4, Figure 4.7 in the Supplement. For any given decade, the sum of the loads from all HUC12s for positive and negative calculations yields the total
123 phosphorus loading for that decade. For the 2010 decade, only the positive calculation is made, and the estimated phosphorus load in succeeding decades increases with the assumption of no further change in the non-sewered population.
5.3 Results
5.3.1 National Level Results
The number of households in the U.S. served by OWSs has been growing for a long time. The amount of phosphorus put into the groundwater by these systems has increased in step with population growth, although the effect of the
1994 laundry detergent phosphorus ban is evident, and most of the recent population increase was served by sewers (Figure 5.7). Populations depicted in
Figure 5.7 are total U.S. population, the population served by sewers, and the population served by OWSs (non-sewered). Estimated wastewater phosphorus loads, depicted by dashed lines, are total generated, total directed to sewers, and total reaching the groundwater surficial aquifers from OWSs. In 1910, the estimated phosphorus load from OWSs to groundwater surficial aquifers at the water table was 22.4 Gg/yr, compared to 60.5 Gg/yr directed to sewers. By 2010, the estimated OWS phosphorus load was about 30.1 Gg/yr, versus 164.7 Gg/yr sent to sewers. The large amount of phosphorus in the groundwater is en route to (or has already reached) our surface waters.
124
350 350
300 TOTAL POPULATION 300
SEWERED POPULATION 250 250 NON-SEWERED POPULATION
OWS P LOAD TO THE WATER 200 TABLE, Wo 200 P LOAD TO SEWERS
150 TOTAL P LOAD, OWSs AND SEWERS 150
100 100 U.S. U.S. Population, millions
50 50 OWS P LoadWo, to theGg/yr Table, Water
0 0 1790 1810 1830 1850 1870 1890 1910 1930 1950 1970 1990 2010 Year Figure 5.7: Comparison of U.S. Population and Wastewater Phosphorus Loads (sources: population, U.S. Census; loads, this chapter results).
We calculated an estimated phosphorus load from OWSs to surface waters for each HUC12 watershed, for each decade from 1790, and combined the loads to obtain an estimate of the national total (Figure 5.8). The increasing load after 2010 does not include any increase (or decrease) in the number of households served by OWSs. The estimated phosphorus load to the surface waters of the U.S. in 2017 (2020 decade) is 4.45 Gg/yr.
125
14
12
10
8
6
4 Phosphorus Loading, Gg/yr 2
0 1790 1890 1990 2090 2190 2290 2390 2490 2590 2690 Year
Figure 5.8: Estimated Total Phosphorus Load from OWSs to Surface Waters in the U.S. (Gg/yr) from 1790.
Figure 5.9 depicts the variation of this load in 2020 across the country, normalized by area, i.e. kg/yr/ha. The results suggest that the greatest loads to surface waters from OWSs are occurring where saturated hydraulic conductivity
(Ks) is highest. This can be seen by comparing Figure 5.9 with Figure 5.2, the variation of Ks across the country, based on the GLHYMPS data (Gleeson, et.al.
2011, Gleeson et al. 2014, Russo 2016). However, this national dataset for Ks is based on hydrolithology, that is, the underlying geology, rather than the soil overburden. Values of Ks may be higher in regions where an overburden of sandy glacial, alluvial, or aeolian material dominates the surficial aquifer. An obvious example is the coastal areas of southern New England and Long Island,
126
where the surficial aquifers lie in relatively deep sand, and Ks is probably much higher than the GLHYMPS data suggests. There, the estimated phosphorus load to surface waters should be higher. Use of the GLHYMPS national dataset is, therefore, a source of uncertainty in the phosphorus load estimate, and may, in fact, yield a low estimate.
Figure 5.9: Estimated Phosphorus Loads from OWSs to Surface Waters in 2020, kg/yr/ha. Selected watersheds outlined in blue: see 5.3.2 and Table 5.2, text.
One successful management effort of the 20th century was the reduction/elimination of phosphorus as a builder in laundry detergents, which culminated in industry-wide substitution of phosphorus with organic builders in
1994 (Litke 1999). Our model calculations include this change (Figure 5.7).
127
Figure 5.10 depicts the estimated increase in phosphorus loading if this change had not been implemented.
Figure 5.10 also includes a hypothetical nationwide management effort to replace OWSs by 2030 by wastewater treatment plants (WWTP) that include phosphorus removal technology. We estimate a legacy phosphorus load to surface waters from OWSs will continue for many decades, pointing to an urgent need to perform new research and management sooner rather than later.
20
18
16 National P Load No P Ban 14 WWTP in 2030
12
10
8
6 Phosphorus Loading, Gg/yr
4
2
0 1750 1850 1950 2050 2150 2250 2350 2450 2550 2650 2750 Year Figure 5.10: Comparison of the Estimated National Phosphorus Load from OWSs to Surface Waters vs. (1) an Estimated Load if No Laundry Detergent P Ban were Implemented in 1994, and (2) an Estimated Load if OWSs were Replaced by Wastewater Treatment Plants by 2030 (Gg/yr).
128
5.3.2 Results at the Regional Level
Notwithstanding the uncertainty introduced by the national dataset, our estimate of phosphorus loading to surface waters from OWSs provides an opportunity to compare the OWS contribution to large-scale estimates of phosphorus loading by others. For example, 1997 SPARROW data for the contiguous U.S. provides an estimate of 381.8 Mkg/yr total phosphorus load to surface waters (SPARROW no date). For the corresponding decade (2000), we estimate the total phosphorus load from OWSs to surface waters was 3.81
Mkg/yr, or 1.0% of the SPARROW estimate. As noted above, this estimate is likely low, and reflects a need for improvement of the national dataset.
However, we also estimated the P load to surface waters for several regional watersheds for comparison to SPARROW 2002 load estimates (Figure
5.9). Table 5.2 identifies the HUC12s that make up the selected regional watersheds, and includes the estimated total phosphorus loads for 2002 from the
SPARROW model for the regional watersheds identified (SPARROW no date).
Each total phosphorus load shown is for the outlet of the watershed to a larger water body. The estimated phosphorus load to surface waters from OWSs for each of these regional watersheds was determined by summing the loads from the HUC12s in the larger watershed. These loads were then recalculated as a percentage of the 2002 SPARROW estimate. When put in context of total phosphorus load as determined by SPARROW, the OWS phosphorus load can be a substantial fraction that is increasing with time (Figure 5.11). Management
129
Watershed HUC 12s Total P Load at Water body at the Outlet, the Outlet kg/yr (SPARROW, 2002) Mississippi River 050100010101 to 117,262,456 Gulf of Mexico 080903020900 and 100200010101 to 111403070209 Maumee River 041000030101 to 1,280,362 Lake Erie 041000090904 Susquehanna 020501010101 to 2,315,379 Chesapeake River 020503061713 Bay Neuse River 030202010101 to 474,932 Atlantic Ocean 030202040904 Cape Fear River 030300020101 to 905,580 Atlantic Ocean 030300070810 Columbia River 170103010101 to 11,322,307 Pacific Ocean 170900120305
Table 5.2: Regional Watersheds and Total Phosphorus Loads as estimated by the SPARROW model (SPARROW no date). Note: SPARROW 2002 loads were obtained from the Decision Support System at the referenced website. The DSS was discontinued in July 2017.
efforts in these regional watersheds are focused on reducing phosphorus loading by surface runoff, from mainly agricultural activities and wastewater point sources. Our results suggest that phosphorus loading from OWSs should not be ignored.
130
14.0%
Mississippi 12.0% Maumee Susquehanna 10.0% Neuse Cape_Fear Columbia 8.0%
6.0%
4.0% P P Load from OWSs ( % of Total)
2.0%
0.0% 1800 1900 2000 2100 2200 2300 2400 2500 2600 2700 2800 Year Figure 5.11: Estimated Total Phosphorus Load from OWSs to Surface Waters as a Percentage of 2002 SPARROW Estimated Total Load for Selected Watersheds.
5.3.3 Example Regional Results: Maumee River Basin
The model calculations can be used to estimate the phosphorus load to surface waters from OWSs for any area, from the individual HUC12, to a County or State, or as shown above, to a region within the U.S. by combining the results from the appropriate HUC12s. The Maumee River basin (HUC4 = 0410) in Ohio,
Indiana, and Michigan (Figure 5.12) is an important example, due to the recent water quality problems in Toledo Ohio. There, elevated cyanobacteria toxin in the drinking water supply was blamed on an algae bloom caused by oversupply of phosphorus from the agricultural areas in the watershed (Henry 2014).
131
Figure 5.12: (a) Maumee River Basin Major (HUC8) Watersheds. (b) Maumee River Basin: 252 HUC12 Watersheds; Major Watersheds (HUC8) outlined in red.
This basin includes 252 HUC12s, as shown in the figure. The total phosphorus load to surface waters from OWS is estimated to be 41,567 kg/yr
(0.024 kg/yr/ha) in 2020 (Figure 5.13). This load can be compared to the 2002 estimate of the total phosphorus load from the Maumee River to Lake Erie made by the SPARROW model of 1,280,362 kg/yr (SPARROW no date). Based on our model calculations, the contribution from OWSs was 3.24% of this load in 2020.
Figure 5.13 shows the OWS contribution normalized by the 2002 SPARROW P load estimate; the figure illustrates how the OWS contribution may be expected to grow in the future.
Comparison of our results with total phosphorus loads determined by the
SPARROW model (SPARROW no date) show that, for HUC12s in which the phosphorus load found by SPARROW includes a large percentage due to
132
100,000
90,000 0.05 80,000
70,000 0.04
60,000
50,000 0.03
40,000 2020: 0.024 kg/yr/ha 0.02
30,000 41,567 kg/yr Total Phosphorus Total Load, Kg/yr
20,000 Phosphorus Total Load, kg/ha/yr Total P Load, kg/yr 0.01 Total P Load, kg/ha/yr 10,000
0 0 1790 1890 1990 2090 2190 2290 2390 2490 2590 2690
Year
Figure 5.13: Estimated Total Phosphorus Load from Onsite Wastewater Systems to Surface Waters in the Maumee River Basin, in kg/yr and kg/ha/yr.
housing development, the load due to OWS is also high, and represents a significant part of that percentage. Figure 5.14 shows our 2020 estimated P loads for HUC12s in the Maumee River basin. Phosphorus loads from OWS to surface waters are highest in the suburbs of Toledo, OH, Lima, OH, and Fort Wayne, IN.
This example illustrates the potential use of our method in management decisions about reduction of phosphorus loading to surface waters: the load to groundwater from OWS must be considered along with loads from all other sources.
133
Figure 5.14: Estimated Total Phosphorus Loads from OWSs to Surface Waters in 2020 for the Maumee River Basin (kg/ha/yr).
134
5.4 Conclusions
Our results show that the estimated phosphorus loading to surface waters due to OWSs is driven by time and soil properties, especially Ks. Soil properties influence the time lag of phosphorus transport, but OWSs in service for a longer time release more phosphorus to the water table/surficial aquifer, and this phosphorus load is transported by the groundwater a longer distance as time increases. In addition, the phosphorus load to the surface waters in a watershed increases as more people are served by OWSs, as indicated by the phosphorus load results from decade to decade. Taken together, these drivers suggest that the prevailing paradigm that phosphorus is largely immobile in soils has, for many years, justified the use of OWSs, but our model results suggest that this approach to wastewater management in suburban development is not sustainable.
We acknowledge that use of the GLHYMPS dataset (Gleeson et al. 2011,
Gleeson et al. 2014, Russo 2016) introduces substantial uncertainty in regional and national estimates because values of Ks and n are based on the underlying geology and contain “artifacts at some jurisdictional boundaries due to different data sources” (Gleeson et al. 2014). Before a better estimate can be made, a national dataset of Ks and n values needs to be developed based on the sandy overburden in which OWSs are built and through which the surficial aquifers flow.
Thus, the data to perform a national estimate are not completely available at this time. The results we present here provide the methodology and workflow for a
135 national estimate, but the resulting values are highly uncertain and should not be used in watershed scale mass balances used for management.
There are also other sources of uncertainty in our estimated phosphorus loads. Our use of a one-dimensional analytical solution to the ADR equation and average values of parameters over large areas and long times simplifies the computations and allows a “screening” analysis. Clearly, each parameter may vary spatially or temporally, or both. Future data collection and modeling may refine the results here, and we anticipate that refinement will be made using numerical models and better data as it is reported and compiled. For the purpose of informing the dialog on eutrophication of surface waters, our results are useful and long overdue.
The process used here can be used to estimate the potential phosphorus loading from OWSs to surface waters at any spatial scale, from the single
HUC12 watershed to regional areas, by selecting watersheds based on the
USGS classification, or based on SPARROW model regions, and combining the results from the appropriate HUC12s. This work can inform regional management at the individual HUC12 level or over an area that includes many
HUC12 watersheds. At a local watershed level, the “NatMod” model is limited by the use of large area average values of the parameters and the concept of a
“super OWS” located in the HUC12 watershed at an average distance to surface water. Local data will provide a better estimate at a sub-HUC12 watershed level, as shown in Chapter 4.
136
Appendix 5.1 Flow Charts for Procedures Used to Determine x, Ks, i, n, and Population by HUC 12
Mean HUC12 Areas A HUC12 Distance, x, Shapefile by HUC Shapefiles “east” & “west” B Zonal Statistics Tool
NHD Flowlines 30 m x 30 m Shapefile Raster Combined Euclidean Raster Distance Tool
NHD 30 m x 30 m Waterbodies raster Shapefile
NatMod Procedures 1
Shapefiles “east” B & “west”
Hydraulic Mean Ks by Conductivity Ks Raster HUC12 Shapefile
Effective GLHYMPS Zonal Statistics Mean n by Porosity n Raster Dataset Tool HUC12 Shapefile
Hydraulic Mean i by Gradient i Raster HUC12 Shapefile
NatMod Procedures 2
137
Appendix 5.1, cont’d
County Population County Census Population Log D C by Decade Density, D County Area
Regression, PS D vs. Log D
PERSEWER 1970
Sewage PERSEWER Disposal, 1970, Binned Average PS 1980, 1990 1980
PERSEWER 1990 NatMod Procedures 3
C
PERSEWER, Non-sewered NS Population D All Decades Population Density
NSDENSITY Raster
Shapefiles“ Zonal Statistics B “east” & west” Tool
NSDENSITY by HUC12 Mean Population by HUC12 A NatMod Procedures 4 HUC12 Areas
138
CHAPTER 6
Summary
Estimating the potential phosphorus load from OWSs to surface waters is important for management of eutrophication, especially for lakes with developed watersheds having many OWSs. Review of field research literature (Chapter 2) reveals that a household OWS effluent plume in the groundwater surficial aquifer may transport phosphorus down-gradient, and this phosphorus may, in time, reach a surface water body. My research is based on the idea that the combined phosphorus contributions of many onsite wastewater systems (OWSs) in a watershed may provide a load substantial enough to establish and/or sustain a eutrophic state in the surface water body.
We proposed a simple model in Chapter 3 to estimate the phosphorus load from an OWS via the groundwater surficial aquifer at any distance down- gradient from the OWS, at any time. We then illustrated the use of the model in
Chapter 4 by calculating an estimated total phosphorus load from all the OWSs in the lake watershed to Oldham Pond in Pembroke and Hanson,
Massachusetts, USA. The result suggests that OWSs in the watershed are providing a substantial and increasing phosphorus load to this lake well above the level needed to sustain a eutrophic state.
139
The resulting load estimate should be used with caution, by recognizing sources of uncertainty. First, use of the model requires that data be obtained for each OWS in the watershed. In some cases, data may not be readily available, and approximations may be needed. Second, the model uses constant average values of the parameters in the load calculation (Eq. 3.10). When possible, local values of these average parameters should be used. Otherwise, values from other locations similar to the subject location, or values from the literature must be assumed, and the ranges of these values introduce uncertainty. We suggest that research is needed to establish local values of the parameters if the model result is to be improved. Special attention should be given to local averages of soil-related parameters Ks and Kd. Also, the model estimate would be improved if the vadose zone efficiency, η, were researched to determine whether and how it varies with time. Some research literature suggests a high vadose zone efficiency when the OWS is “young” and a decline in efficiency with time (e.g.
Dudley and Stephenson 1973, Koerner and Haws 1979, Eveborn et al. 2012), and an empirical function, η(t), would be useful in the model calculations.
In Chapter 5, we provided a procedure for combining national datasets for watersheds at the HUC 12 level (USGS no date), for waterbodies and flowlines
(NHD no date), and for values of soil parameters Ks and n, and water table slope, i (Gleeson et al. 2011, Gleeson et al. 2014, Russo, 2016: the GLHYMPS dataset), with U.S. Census data on sewered population at a County level (NHGIS
2011). By positing a “super OWS” serving the non-sewered population in each watershed at the average distance from surface water, we estimated the total
140 phosphorus load from OWSs to surface waters for the entire coterminous United
States.
We determined that the GLHYMPS dataset, however, provides Ks values that are based on underlying geology, rather than the unconsolidated overburden through which the surficial aquifers flow. For much of the U.S., these values of Ks are too low for use in our model. Additional uncertainty is introduced by the discontinuity in Ks data at jurisdictional boundaries. Further research to compile parameter values at national or regional levels for the saturated soils of surficial aquifers would allow a better estimate of the national or regional phosphorus load from OWSs.
Notwithstanding the large uncertainty introduced by the GLHYMPS dataset, we used the model to estimate total phosphorus loads from OWSs to surface waters for several regional watersheds. We compared these estimated loads to published results of SPARROW model estimates of total phosphorus loads from all sources (SPARROW no date) to get a sense of the part OWSs may be playing in these regions. The results suggest that the OWS component of the load is significant in populated regions, despite the likelihood that the estimates are low due to the GLHYMPS dataset concern. The results also show that the OWS contribution of phosphorus to surface waters in the selected regions is growing with time and suggest that management efforts relative to eutrophication should address the OWS phosphorus source.
Overall, the value of my research is the unique combination of (1) a focus on phosphorus load versus concentration to explicitly quantify phosphorus load
141 at a distance over time, and (2) application of the method over an entire watershed to directly estimate the total phosphorus load from OWSs via the groundwater surficial aquifer to surface waters in a time-variable manner. An important result of this research is to illustrate how the load may increase with time, which has not been emphasized in previous research. My results suggest that the existing paradigm that phosphorus does not move very far or very fast in
OWSs requires further research and may have to be discarded. Management efforts to prevent, remediate, and mitigate the effects of lake eutrophication must consider this phosphorus load source. Our model is a valuable tool for quantifying the phosphorus load from OWSs at the watershed level.
In addition, the research approach to national/regional phosphorus loading from OWSs is unique in the method of combining hydrological data and U.S.
Census data for use in phosphorus load estimation. Although the national datasets may introduce significant uncertainty, application of the method at a large scale, regional to national, may also provide useful information about the transport of phosphorus from OWSs to surface waters.
142
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