1. James Madison University Department of Economics
The Economics of
Stormwater Runoff
Management and
Potential Synergies of
Cooperation
An analysis of BMP cost data from James Madison University
Garrett Hodgson
3/28/2016
2. 1
Table of Contents
Abstract........................................................................................................................................................3
Acknowledgements ....................................................................................................................................4
Background Information...........................................................................................................................5
Introduction................................................................................................................................................5
What is Stormwater runoff? .................................................................................................................5
Point Source VS Non-Point Source......................................................................................................6
Pollution Runoff and the Environment: .........................................................................................7
Valuing the Negative Externality .........................................................................................................8
Efficient Pollution Control..............................................................................................................10
Regulation and Policy Controls for Mitigating.....................................................................................11
Stormwater Runoff at JMU ....................................................................................................................11
JMU Stormwater management plan(s) ............................................................................................11
Overview................................................................................................................................................11
Chesapeake Bay Preservation Act..................................................................................................12
ESC and SWM plans ........................................................................................................................13
Total Maximum Daily Load Reduction Requirements ...............................................................13
Construction General Permits........................................................................................................14
SWPPP...............................................................................................................................................14
IDDE ..................................................................................................................................................14
The EPA, MS4’s and NPDES ..........................................................................................................15
Minimum Control Measures for Phase II.....................................................................................16
Room for Improvement at JMU.............................................................................................................16
Advancement in Stormwater Management Strategies: Economies of Scale ...................................17
Empirical application methodology ............................................................................................................17
Results.........................................................................................................................................................18
Econometric concerns .........................................................................................................................21
Discussion of Potential Synergies to Take Advantage of Economies of Scale:................................21
Issues of Coordination.............................................................................................................................21
Barriers to potential cooperation.......................................................................................................22
Project Timing/Differences ............................................................................................................22
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Competing interests.........................................................................................................................23
Acknowledgements of Potential Synergies.......................................................................................24
Conclusion.................................................................................................................................................25
Works Cited...........................................................................................................................................- 26 -
Appendix .................................................................................................................................................- 28 -
4. 3
Abstract
In a world with rapid population growth and urbanization, changes in the characteristics of the
land are important considerations when trying to determine social costs of development. Impervious
land that has been compacted or developed is unable to slow stormwater runoff and is less effective at
mitigating pollution. In 2014, NOAA (2014) estimated damages from flooding across the US to be around
2.86 billion dollars. In compliance with the EPA and other regulatory agencies, standards and
benchmarks are developed in order to yield a socially optimal amount of runoff at the lowest cost to
society.
The purpose of this James Madison University case study is to assess the presence of economies
of scale for different types of BMPs (best management practices). Tentative evidence is found to
support the presence of potential cost savings by observing economies of scale, and is cited as a reason
for project combinations and cooperation between permit holders.
5. 4
Acknowledgements
The author would like to acknowledge several people and agencies that played an integral part
in this research project. A special thanks to the faculty and staff of James Madison University, including
Scott Milliman, Maria Papadakas, and Angela Smith were vital resources for narrowing down the scope
of the project and providing research assistance in both the methodology and the relevant background
water quality information. Dale Chestnut of the James Madison University Stormwater Management
department provided all of the data used in the regression section this analysis, as well as background
information on the workings of the JMU stormwater department and their relation to EPA and Clean
Water Act regulations. MS4 permit team leader and environmental Specialist II Jamie Bauer was also a
useful point of contact regarding preexisting instances of cooperation across MS4 permittees. Without
the generous help of these individuals and their respective departments this analysis would not have
been attainable.
6. Background Information
Introduction
An overview of water quality as a public
good sets the framework for how property
rights are assigned and how individuals demand
for swimmable and fishable waters is taken into
account when attempting to value the negative
externality. As a public good with negative
externalities, there is likely going to be private
underproduction due to the inability of private
firms to charge consumers of the good (the
essence of non-excludability). No one is willing
to purchase socially optimal quantities since
private marginal benefit is greater than the
social marginal costs for higher units. Altruism
and warm glow effects1
are unlikely to
accommodate for the lack in production of
water quality as a public good.
Different management strategies can
be developed under the broadness of Clean
Water Act so that best practices can be tailored
to specific cases and geographic locations. The
EPA typically is the overseeing entity for many
of the different requirements for compliance
with stormwater laws. Erosion control and
polluted stormwater runoff are just two of the
many different goals and objectives of these
various policies and permits that are relevant to
this case study of James Madison University and
are then described in detail. Putting the issue
into an economic framework allows for
economists to empirically test for inefficiencies
that arise when the optimal equilibrium point
and the actual equilibrium point differ. For the
case study of potential per unit cost savings can
be observed due to the presence of economies
of scale in different stormwater management
BMPs. Significant results confirming the
1
Altruism and warm glow effects refer to when
people value the cost or benefits to others in making
consumption choices and when people care about
the total level of the public good as well as their own
optimal combination respectively.
presence of economies of scale were found by
doing an OLS regression analysis in SAS. These
cost savings can be applied across different
projects and potentially across different permit
holders if further cooperation towards TMDL
reduction goals is induced.
What is Stormwater runoff?
As land becomes compacted or
developed, there will be a level of surface
impermeability that impairs water coming down
in the form of rain to be absorbed into the
ground. Taking this into consideration, it is easy
to see how this problem is a growing concern
for the future of city and suburb development.
Rainfall typically is more of a blessing rather
than a curse, but as urban areas grow larger and
denser, these estimated rainfall events start to
cause issues for local watersheds. As rainfall
comes down, it is meant to be soaked up by the
natural landscape, helping to replenish soil
moisture, plants and forests, as well as water
tables. These species and processes are what
one might refer to as an ecosystem service. Our
natural surroundings are capable to removing
pollutants and contaminants from water,
storing it in the soil until it is broken
down/recovered by other plants.
While nature does an extraordinary job
of filtering out pollutants from the surface and
producing clean, potable water, it is the portion
of the rain that does not get absorbed by the
soils and biotic factors in the environment that
causes problems in local bodies of water.
Gravity sweeps water away that is not able to
be absorbed, funneling it to the lowest point
and paths of least resistance until it can enter
into a body of water (whether that be a stream,
river, lake, bay, or directly into the ocean).
Flooding has been becoming more and more of
an issue. NOAA data cites damages coming from
flooding across the US in 2014 of approximately
$2,861,426,089 (NOAA, 2014). It is important
for this paper that the difference between
natural flooding and urban runoff flooding be
distinguished. Maher (1980) does a good job of
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breaking down the difference in types of
flooding, describing natural runoff generated in
an undeveloped watershed and conversely
flooding that is generated by the additional
runoff that comes off of impermeable surfaces.
“Flooding may be both a phenomenon of
nature and an externality produced by man,
though it should be recognized that “natural”
flooding causes no damage unless downstream
residents occupy the floodplain” (Maher, 1980).
The difference in runoff rates between
developed and natural land areas are depicted
in Figure 1. Shows how the flow rate increases
significantly when land is unregulated and
developed.
Figure 1 Runoff-Frequency Curve (Maher, 1980).
Frequency refers to the yearly rain event (aka how
much water is expected to runoff for a 5, 10, 25, 50,
and 100 year storm event)
Issues dealing with flow rate are the
most difficult to combat do to extreme weather
and the associated unpredictability of such
events. The inability of the surface to absorb
and slow down this runoff process is
exacerbating pre-existing watershed
management issues. Decreasing returns to scale
of urbanization effect on flow rates have been
found in studies including Hollis (1975) and
Espey, et al (1965). There is a point where
undeveloped land becomes too saturated and
the remaining water runs off in such a way that
makes the ground seem impermeable. Hollis
found that when the peak flow of a 100 year
storm event is doubled, it has the same impacts
on erosion as paving 30% of the watershed. The
effect of urbanization thus needs to be
considered in terms of an externality. The
difference between the natural flooding that
occurs for a specific rain event and the
developed flooding from that same event can
help to quantify the flooding externality. As the
levels of impermeability are increasing, the
probability of a major flooding event increases
and thus greater negative externalities are
created that need to be managed. Failing to
observe this externality comes as a result of
imperfect information about the true private
and social costs that are associated with the
remediating and mitigation of stormwater
runoff.
Point Source VS Non-Point Source
Point source pollution can be defined as
pollution that enters into a waterway from a
specific and known discharge point. More
formally, point source pollution is water
pollution coming from a single point, such as a
sewage-outflow pipe (U.S. Geological Survey,
2011). The national Water Quality Monitoring
council (2007) cites point source pollution as
pollution discharged through a pipe or some
other discrete source from municipal water-
treatment plants, factories, confined animal
feedlots, or combined sewers. The commonality
is that these are known areas where pollution is
being discharged into a local body of water.
These sources are easily regulated and must be
accounted for thanks to the rise in rules and
regulations sprouting from the EPA. There are
also limits on how quantity of discharge from
regulated point source polluters. One example
of allowable discharge of polluted water is
combined sewer overflows (CSO’s). Combined
sewer systems are historically used and
currently a practice that is being phased out
thanks to development of separate waste water
and storm water pathways. CSO’s occur when
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heavy rain events cause a rush of water into the
combined sewer system. The overloaded
system then has to discharge untreated or
partially treated human and industrial waste, as
well as other toxic materials and debris
collected by stormwater runoff. Long term CSO
plans are required for jurisdictions that have
this source of pollution. Even though these
polluters are allowed to discharge waste, the
standards set by the EPA are designed to
prevent permanent damage to waterways as a
result of the dumping. Having some control and
authoritative accountability is better than
pollution that comes from an undeterminable
source.
The same water quality monitoring
glossary from the U.S. Geological Survey (2011)
defines non- point source pollution as
“pollution discharged over a wide land area, not
from one specific location. These are forms of
diffuse pollution caused by sediment, nutrients,
organic and toxic substances originating from
land-use activities, which are carried to lakes
and streams by surface runoff.” Additionally,
Non-point source pollution is contamination
that occurs when rainwater, snowmelt, or
irrigation washes off plowed fields, city streets,
or suburban backyards. As this runoff moves
across the land surface, it picks up soil particles
and pollutants, such as nutrients and pesticides.
Non-point source pollution can be a tricky fix
that requires a better understanding for
stormwater flow and knowledge of accidentally
discharged pollution that ends up coating paved
surfaces.
Pollution Runoff and the
Environment:
With aspects of public goods, these
surfaces are obviously going to be subject to
unaccountable polluters that do not feel any of
the consequences of their negative actions
directly. As more and more users pollute these
areas, the pollutants build up until the next big
rain event, where rushing water washes away
surface containments down the gradient
towards whatever body is closest. A study by
Line et al (1996) reports findings of stormwater
runoff containing compounds including
acrolein, methylene chloride, xylenes, toluene,
tetrachloroethylene, trichloroethylene,
pentachlorophenol, and aldrin, as well as
concentrations of aggregate organics, nitrogen,
phosphorus, and sediment. Also included in this
study are a list of different heavy metals that
were found, ranging from arsenic and antimony
to mercury and zinc, with copper and zinc being
the most prevalent (found in all 40 runoff sites
tested) (Line et al, 1996). Buildup of these both
chemical and physical pollutants in local
waterways is the exact reason there needs to
be controls and rules set in place. Local
waterways take the blunt of the pollutants as
riparian buffers do their best to filter out what
they can. It is easy to see the negative impacts
on both plant and animal species all across the
US and the globe; this is not a localized issue.
The cyclical property of water movement and
transformation leads all of the heavy and toxic
pollutants to the lowest sink level where they
accumulate with other pollutants that have
runoff from other areas. It is here at the end of
the watershed that one can see the worst
impacts of pollution runoff.
Biological impacts of stormwater runoff
are often put on the backburner, with the
effects on humans taking precedence over
biodiversity loss or endangerment of indicator
species. For starters, disruption of natural
ecosystems tends to lead to the presence of
invasive species, especially weeds. Ehrenfeld
and Schneider (1983) studied cedar swamps in
the New Jersey Barrens and found that the
natural wetlands subjected to varying amounts
of urbanization were often changed due
specifically to stormwater runoff. Native plants
were replaced with weeds and exotic plants
that are more adapted to harsh growing
conditions. Uptake of phosphorus and lead in
the plants were observed and attributed to the
presence of stormwater runoff. The University
of Washington (Pedersen, 1981; Richey et al,
9. 8
I98l; Perkins, 1982; Richey, 1982; Scott et al,
1982; Ebbert et al, 1983; Pitt and Bissonnette,
1984; Prych and Ebbert, undated), found urban
creeks to be significantly degraded in
comparison to rural creeks. While the urban
creeks were not to the point to being unable to
support aquatic life, they were found to have
higher dissolved oxygen levels that can be
attributed to the depressed fish populations
(Pitt et al, 1995). In the same study, significant
differences were noticed in the biological
makeup of species. Declining water quality in
the urban test creek is considered to be the
main cause of for the difference in type of fish
that live in that area. More sensitive coho
salmon are replaced with less sensitive
cutthroat trout. There was also a significant
decrease in the number of benthic organisms
found in the urban creeks. Mayflies, stoneflies,
caddisflies, and beetles (organisms that are
commonly regarded to as sensitive indicators of
environmental degradation) were rarely
observed in the urban Kelsey Creek but were
quire abundant in the forested Bear Creek (Pitt
et al, 1995). Clams (unionidae) are also a good
indicator of a specific environmental stressor,
turbidity and siltation. Heavy rainfall leads to
heavy stormwater runoff, increasing the
turbidity of the urban area stream. These clams
are very sensitive specifically to heavy siltation
and unstable sediment, which comes as no
surprise as the observed population numbers
for this species in the urban river were
nonexistent and abundant in the natural creek.
Empty clam shells were found however,
indicating that there has been a shift in change
in the characteristics of the stream that lead to
the phasing out of this species.
Plenty more examples of shifts in
ecosystems could be cited to prove the point
that urbanization has caused local ecosystems
to change. The case of the clams also goes to
show that it isn’t just an issue of pollution and
toxicity, but of flow rates that change
sedimentation patterns as well. It is hard
however to pinpoint (especially in a legal sense)
who is responsible for causing the unwanted
shift in the ecosystems. Assigning blame for
production processes that produce negative
externalities such as the ones degrading natural
ecosystems can be a tricky procedure, and one
to not take lightly. Willingness to coordinate in
government programs that get turned into laws
isn’t the concern; the real concern is to what
degree do we force people to modify their
habits in order to observe optimal pollution
levels and reductions in biodiversity loss? For
this, a better development of stormwater as a
negative externality is needed.
Valuing the Negative Externality
With non-rivalrous and non-
excludability aspects, watershed management
is a difficult task, like all public good
management. Standard economic theory of
managing externalities, especially cases
involving pollution, give economists an idea of
what needs to be done with regards to flooding
and stormwater runoff. The end goal is to make
the individuals that are urbanizing and
developing land responsible for the costs to
society they have involving local waterways and
watersheds. There are efficient solutions in
order to remedy the negative externality issue;
the largest issues that come into play are who
does the cost of management fall on and what
can be how to manage growth. This section
goes into how negative externalities create
dead weight loss in a market for clean
waterways.
Externality producers are unlikely to
find motivating to internalize an externality
without some form of coercion. It is likely that,
unless that developer is intrinsically concerned
for the damages to the environment that are
encompassed in land development, any
developer will choose to raise private costs in
an attempt to mitigate social costs. In
accordance with externality theory, this means
that there is likely an overproduction of the
good (in this case it is an overproduction of
stormwater runoff) than what would be
considered socially optimal. This distance
10. 9
between the private marginal costs the
developers of land face and the social marginal
costs gives the externality value. Luckily in this
case, it is not just people that are being harmed
by the pollution that are vested in cleaning up
pollution. Environmentalists and
conservationists have done good work to bring
stormwater runoff into the public eye,
enlightening uninformed citizens of dangers
that lurk in their local waterways as a result of
uncontrolled pollution runoff. Often marginal
levels of pollution are undetectable without
sampling equipment, and the public good can
still be consumed, thus rendering an optimal
level of pollution.
For stormwater runoff externalities,
there is going to be some abatement costs
associated with pollution reduction. The goal
now for society is to minimize both the
abatement costs of pollution (by internalizing
the externality to the producer rather than the
consumers of the public good) and minimize
damages to the environment. At the
intersection of the aggregate marginal average
cost and the aggregate marginal demand, the
equilibrium level of pollution and optimal tax
rate can be found. This information applied to
specific instances of land producing stormwater
runoff gives value to how much the externality
should be taxed in order to mitigate pollution
down to the socially optimal amount. In theory,
this application of economics is a solution to the
issue of stormwater externalities, however the
issue isn’t the theory, and it is the aggregation
of preferences that makes this valuation so
difficult. This theoretical framework found in
figure 2 paints the picture that
environmentalists want, a higher value of the
externality that needs to be incorporated into
the private costs of production. It is in policy
where these findings prove too weak without
empirical evidence to warrant rules and
regulations that would increase the
accountability needed to achieve optimal levels
of pollution.
Figure 2 Social Gains from Technological Change in Pollution
Control (Milliman and Prince, 1988)
Coase theorem simplifies the “costless”
and “perfectly informed” bargaining that is
required between producers and consumers to
fully internalize the externality. In a small
numbers game, this bargaining could work;
assuming that individuals do not specifically
care how property rights are granted and can
agree to a mutually advantageous agreement.
However, watershed pollution is hardly a game
of small numbers of people that are affected.
Having the vested citizens pay for pollution
reduction practices such as MS4’s or other
forms of best management practices (BMPs) is
an impossible negotiation to be made
considering the vast number of people that are
affected. In a single area, there can be
thousands of people that rely in some way
shape or form on ecosystem services that are
inhibited in the presence of pollution and
flooding. Coordinating with each person to find
how they value the resource, independent of
other peoples’ answers, is an aggregation
process that is completely unattainable. Issues
11. 10
with free riding by public members that want
cleaner waters but would rather someone else
pay are hard to overcome, which is why a Coase
solution is unlikely going to be the answer to
any stormwater management program other
than those involving only a handful of affected
citizens.
Efficient Pollution Control
In agreement with standard public good
theory, efficient pollution control is an issue
that requires members of society to attempt to
minimize the sum of the polluters’ abatement
costs as well as the pollution damages suffered
by the victims of pollution. Maher (1980) states
“it is unrealistic to assume that victims [of
pollution] merely treat water quality as a given
and are reduced to merely altering their normal
inputs so as to maximize their profits given the
existing level of pollution.” What is required is
that victims take some form of preventative
measure to ensure safety from the pollution of
a public good. Currently signs pepper riparian
zones, warning of the dangers of consuming fish
from local rivers due to a previously
unregulated market. A local example is the
persisting issue of mercury present in local
waterways, specifically the Shenandoah River
and the South Fork. Figure 3 below shows the
overlapping segments of pollution impairments
of the South Fork River. Mercury is present in
essentially the entire river thanks to unchecked
pollution from upstream. Health concerns, like
the ones involved with mercury poising, are
externalities that have failed to be accounted
for in the valuation of social marginal costs of
pollution producing production.
Figure 2 was created by the author using data retrieved from VA
DEQ Category 4&5 Impaired Waters Listings for 2012 & 2014
A trap presents itself if the case of
mercury is looked at from a polluter/victim
framework. Ideally, a combination of broad
based upstream abatement and downstream
mitigation policies are going to be the most
efficient way to go about regulating and
managing the public good. Here however,
pollution has already happened and the long
lasting effect of deposition of mercury on the
riverbed means that there are longer run
consequences that need to be dealt with
downstream. For now, new regulations have
prohibited the deposition of pollutants like
mercury, but downstream mitigation is still an
issue that needs to be addressed. At any given
level of an externality, the victims should go to
undertake prevention measures to the point
where their marginal propensity to consume
equals their marginal demand. For other
pollutants besides mercury, efficient pollution
control can be applied/is being applied to
minimize damages felt by victims.
To minimize the social costs of
pollution, marginal abatement costs for the
entire community must be set to equal the
12. 11
marginal demand curve found by the vertical
summation of each individual’s demand curve.
These marginal abatement costs and marginal
prevention costs are not equal across all
polluters and victims. These costs do not need
to be equal for summation of optimal pollution
prevention/mitigation. Since abatement
benefits are non-rival, but private
prevention/mitigation measures such as water
filters are, there will likely need to be further
inquiry into benefit levels and how this will
affect free rider mentality. As you will see later
in the paper, abatement measures are
prominent in today’s decision making processes
for determining how to eliminate pollution and
protect the environment. Instead of making it
the responsibility of the citizens with access to
waterways as public goods, regulations have
been created aimed at limiting the amount of
pollution that comes out, rather than focusing
on how we deal with pollution once it is
present.
Regulation and Policy Controls
for Mitigating
Stormwater Runoff at JMU
JMU Stormwater management
plan(s)
Overview
In the previous regimes consistent with
practices before regulations, polluters owned
the right to pollute. With the rise of the EPA and
other regulatory government agencies, these
rights are slowly being taken away, starting with
the largest populations. Phase I of the National
Pollutant Discharge Elimination System
(NPDES), established and overseen by the EPA,
began in the early 1990’s as a way to start
regulating the biggest offenders. The goal of
this first phase was to require medium to large
population areas (as defined later) to develop
and implement a Storm Water Management
Plan/Program with the goal of reducing the
discharge of pollutants to the maximum extent
practicable (California Environmental Protection
Agency, 2013). This is a step in the right
direction for assigning accountability, and in
2003 Phase II of this storm water program was
implemented, involving smaller population
areas and other non-traditional small
populations such as campuses, prisons, military
bases, etc.
This section of the paper entails a brief
overview of the different regulations that
govern stormwater management practices at
James Madison University. JMU has already
made a pledge for keeping its campus an
environmentally conscious one, but along with
that pledge, accountability has been created by
the Environmental Protection Agency and the
Virginia Department of Environmental Quality.
Regulations themselves vary in breadth and
scope, but these programs were developed in
order to make sure that various construction
activities and other activities involving
stormwater sewer systems operate in such a
way as to preserve and protect local water
quality. As you will see, many different rules,
regulations, regulatory bodies, and coordinators
work hard to keep up with the new and
changing stormwater management rules that
have come about in the past decades. The
scope of this analysis looks at the various MS4
BMP projects that have been implemented by
James Madison University in compliance with
the new limitations and restrictions that have
been made. James Madison falls under the
Phase II regulations as a small municipal storm
sewer system operator. Also what defines JMU
under the MS4 permit program is the fact that
the university is located in an urban area. By
EPA definition, an urban area is a land area
comprising one or more places – central
place(s)- and the adjacent densely settled
surrounded area – urban fringe – that together
have a residential population of at least 50,000
13. 12
and an overall population density of at least
1,000 people per square mile (Chestnut, 2015).
Additional environmental precautions,
such as the Spill Prevention Control &
Countermeasure (SPCC) plan, have been around
long before Phase II requirements. A SCC plan
was prepared for JMU initially in 1975 in order
to establish the correct procedures to prevent
discharges of oil from facilities, as well as to
contain such discharges if/when they do occur.
This goal is expected to be maintained and
regularly updated as facilities update. This SPCC
is just one example of additional BMP plans that
are utilized by JMU in order to stay in
compliance. Nutrient management plans are
also an important aspect of operations that
need to be in compliance with the various
forms of regulations and regulatory bodies.
Below are the various acts, policies, regulations,
and codes associated with stormwater
management specifically for JMU.
Requirements for different regulations in other
cities and counties will dictate what kinds of
control measures need to be put into place. As
for this specific location, being a public
university means that additional rules will apply
to stormwater runoff control than private areas,
but the idea remains the same; for any area
with unmanaged stormwater runoff a certain
level of control measures must be implemented
in order to protect local ecosystems and
waterways.
Chesapeake Bay Preservation Act
"Healthy state and local economies and a
healthy Chesapeake Bay are integrally
related; balanced economic development
and water quality protection are not
mutually exclusive."-Bay Act, 1988
The first sentence of the Chesapeake Bay
Preservation Act (CPBA) sums up the motives
behind the framework. This act serves as a
critical element of Virginal’s non-point source
management program. Virginia Code § 62.1-
44.15:67. starts with a plan for cooperation
between state and local programs. Local
governments have the initiative for planning
and implementing provisions included in this
article. The law requires that for program
compliance, regulations that are associated
with erosion and sediment control (ESC) and
stormwater management (SWM) plans must be
considered. As deficiencies are found in
compliance with these rules, local governments
will have to come up with a schedule for
compliance in order to correct for the violation.
Heavy fines may be levied as penalties for non-
compliance. These fines are deposited to the
Stormwater Management Fund established in §
62.1-44.15:29. and can then be used to pay for
other state programs as needed.
After all is said and done, it is the
responsibility of the Commonwealth of Virginia
to make its resources available in order to
provide assistance to localities in implementing
and enforcing the requirements of this act. The
State Water Control Board is charged with the
upkeep of these regulations specifically in the
Tidewater area of Virginia; however they
provide assistance not only to Tidewater local
governments but also to planning district
commissions and Soil and Water Conservation
Districts (SWCD) that are participating in this
program across the state. Technical assistance
in the form of publications, research projects,
computer equipment provisions, and others has
been combined with financial assistance as well.
Grant programs started in the early 1990’s and
have been helping the planning district
commissions and SWCD’s develop agricultural
soil and water quality conservation plans on
farmlands. Local governments have a bit of
leeway when it comes to what the local
programs end up looking like. This flexibility of
local governments allows for programs to be
designed to represent unique local
characteristics and challenges that may line up
with pre-existing community goals.
14. 13
ESC and SWM plans
The Erosion and Sediment Control plan
and the Stormwater Management plan are two
independent plans of action to deal with
different laws and regulations. Virginia Erosion
Sediment Control Law and Regulations (§62.1‐
44 et seq. as amended, and 9VAC25‐840 et seq.
as amended, respectively) outline the general
specifications of what needs to be accounted
for in plan design and reporting. The ESC plan
was implemented at JMU in 2009 as a measure
to prevent sediment from construction and
other land disturbing activities. The ESC is a site
specific plan that identifies best management
practices and control measures to be
implemented during a land-disturbing activity of
10,000 square feet or more, as part of a
common plan of development (JMU (1), 2015).
Plan requirements for both ESC and SWM plans
are in the form of a Plan Preparer/Review
Checklist in order to maintain a level of
consistency and ensure proper steps will be
taken plan in response to the presence of
pollution. The checklist consists of a narrative
that includes the supporting calculations, and
the construction sheets or site plans. To add to
the list of requirements, JMU is required to
comply with the Construction and Professional
Services Manual, which go over state policy,
standards and procedures for the procurement
of services dealing with construction and
contract management. These two management
plans are part of a larger construction blueprint,
the Stormwater Pollution Prevention Plan.
Total Maximum Daily Load
Reduction Requirements
Part of the stormwater management
plan implemented by JMU entails the
calculation of the total maximum daily load
(TMDL) that a waterbody can be exposed to.
The Environmental Protection Agency (2015)
explains the development of TMDL’s in depth.
In a general sense, the Environmental
Protection Agency (EPA) is the overseeing body
for this regulation. States are responsible for
developing TMDL’s and then submitting them
to the EPA for approval. Under section 303(d) of
the Clean Water Act, territories are required to
submit a list of impaired waters that are too
polluted or otherwise too degraded to meet
water quality standards. The law thus requires
that the state establish priority rankings for
waters that make the list of impaired waters,
and from this priority ranking TMDL’s are
developed. With the authority of the Clean
Water Act, the EPA then either approves or
disapproves the pollution reduction calculation,
and is then held responsible for a further
development as a replacement for the lacking
TMDL. TMDL’s are developed by determining
the load capacity of the body of water so that
appropriate control actions may be taken place.
Both point and non-point sources of pollution
are identified so that they can be allocated a
portion of the allowable pollution load. In most
cases, the allowable load from any specific
source is lower than its current level,
warranting clean up measures. This program
isn’t necessarily a permit based approach to
pollution control (even though it has aspects of
such). Instead this program enlists pollution
budgets as a means of identifying and reaching
a targeted level of pollution (much as
permitting and tradable permits do). Retrieved
from the EPA Program Overview for TMDLS
(2015):
Expressed mathematically, the TMDL
equation is:
𝑇𝑀𝐷𝐿 = 𝛴𝑊𝐿𝐴 + 𝛴𝐿𝐴
+ 𝑀𝑂𝑆
Where WLA is the sum of wasteload allocations
(point sources), LA is the sum of load allocations
(nonpoint sources and background) and MOS is
the margin of safety.
As the TMDL calculations are approved by the
EPA, they are generally embodied though
National Pollution Discharge Elimination
Systems (NPDES, which will be described later
15. 14
in the analysis). A further exploration into this
equation was not relevant for the economies of
scale analysis, therefore it was not pursued
further. Section 402 of the CWA requires that
point source pollution discharges must be
controlled by including water quality based
limits in the permits that are issued to point
source polluters. As for non-point source
pollution, a plethora of different local, state,
and federal funding programs are in existence
to help provide assistance and cost-share
programs to the states that are in charge of
implementation. In addition, funding for
voluntary actions and environmental groups
involved may be attained as long as grant
money is used for a project aimed at reducing
non-point source pollution.
Construction General Permits
This permit application proves relevant
to the topic of stormwater management
because of land disturbance issues. Many
localities within Virginia are already a part of a
Virginia Stormwater Management Program
(VSMP). General permit registration in these
areas are required to file for a permit when
more than one acre of land is disturbed, or
cases where less than one acre is being
disturbed, but it is part of a larger common plan
of development. Land-disturbing activity that is
not located within a locality with a VSMP are
required to apply for individual permits from
the VA DEQ. Part of this construction general
permit is the requirement of a Stormwater
Pollution Prevention Plan (SWPPP).
SWPPP
The Stormwater Pollution Prevention
Plan (SWPPP) is considered the basis for the
Construction General Permit and the VA
Stormwater Management Program. The general
permit requires that an activity operator
develops a site specific SWPPP for activities
disrupting one or more acres. Approved erosion
and sediment control plans, stormwater
management plans, pollution prevention plans,
and additional control measures are the four
requirements of all SWPPP’s. This permit is
required and must be prepared before
submitting the registration statement for the
initial permit coverage. It is then reviewed by
either a VSMP authority personnel or the VA
DEQ. This part of the overall permitting process
in responsible for developing the specific water
quality and quantity requirements that are
required to be met. The steps and techniques
outlined in this part of the permitting process
are focused at reducing pollutants in the
stormwater that runs off from the construction
site. A complete list of SWPPP requirements can
be found in part II of the Construction General
permit.
IDDE
With the purpose of establishing
methods for controlling the introduction of
pollutants into the MS4, Illicit Discharge
Detection and Elimination (IDDE) systems have
been created as part of the Virginia Stormwater
Management Program permit. By definition,
illicit discharge in this context means any
discharge to a MS4 system that is not composed
entirely of stormwater (except for such
discharge in compliance with VPDES or state
permit, discharge from firefighting activities,
and discharge identified as being in compliance
with 9VAC25‐870‐400 D 2 c (3). Included in the
list of prohibited materials to discharge are, but
are not limited to: oil, anti‐freeze, grease,
chemicals, wash water, paint, animal waste,
garbage, and litter. Part of the IDEE program are
annual field screenings that observe MS4
outfalls for any evidence that might suggest
illicit discharge may exist, as well as notification
of spills and tracking procedures. Enforcement
aspects involve either verbal notice or written
notice consisting of any one of seven
disciplinary actions ranging anywhere from fees
and penalties to dismissal, where appropriate. It
is the responsibility of the stormwater
coordinator in the case of JMU to provide
training about stormwater pollution and
prevention as well as educational materials
16. 15
about IDEE that can be dispersed through
members of the community. This program is
just another example of plans that local and
state governments have been working on
implementing, providing necessary
accountability for aspects regarding stormwater
pollution control.
The EPA, MS4’s and NPDES
In 1970, the environmental Protection
Agency (EPA) was established in order to
consolidate in one agency a variety of federal
research, monitoring, standard-setting and
enforcement activities to ensure environmental
protection. Twenty years later, the EPA
promulgated rules in order to establish Phase I
of the National Pollutant Discharge Elimination
System (NPDES). NPDES incorporate TMDL
wasteload allocations as part of the general
permit under section 402 of the CWA. This
program prescribed to the operators of urban
areas totaling more than 100,000 people is in
charge of overseeing Municipal Separate Storm
Sewer System (MS4) projects. These MS4
permits were designed to manage stormwater
that was polluted, before it got into local
waterways. Urban areas are commonly known
for large areas of impermeable surfaces. These
surfaces attribute to increased runoff volume
and velocity, both of which have the power to
change hydrological aspects of streambeds,
riparian zones. The loss of aquatic life and
riparian life from these turbid waters attribute
to even worse water quality. The runoff from
roads, parking lots, rooftops, and other
impervious surfaces contains many pollutants,
some of which don’t just harm plants and
smaller aquatic life, but can be deadly to
humans (lead poisoning from contaminated fish
is the first issue that comes to mind).
Permitting is by far the most popular
control for managing and mitigating stormwater
runoff. Permits such as the NPDES are used in
order to create the level of accountability that is
required in order to force polluters legally to
manage discharge into the stormwater and
river pathways, both point and non-point
source. NPDES permits, when required, cover
the issue of stormwater discharge from MS4’s,
areas of population greater than 100,000,
industrial activities, and construction activities
that disturb at least 5 acres. Specific discharge
prohibitions listed in Phase I (specifically Region
2, Order No. R2-2009-0074) include aspects
such as compliance with discharge prohibitions
and reviewing water limitations. If unacceptable
discharge is detected through the required
monitoring, then the polluter is given no more
than 30 days to notify whatever regional
authority about the pollution, current BMPs and
plans for further BMPs to prevent or reduce the
discharge of pollutants that are causing or
contributing to the exceedance of the water
quality standard (WQS). Plenty of different
management practices can be used to remove
pollution, many of which will be introduced
later in the discussion.
The focus of this assessment of
stormwater runoff management however is
more focused than general Phase I or Phase II
case studies. Specifically, James Madison
University (JMU) and the MS4 permit that has
been assigned to this campus will be looked at
more closely as the example of a policy control.
Making specific entities responsible for the land
the possess, whether it’s JMU, the local sector
of the Virginia Department of Transportation, or
the city of Harrisonburg, Va., is the goal of the
permitting system, but also the source of many
political challenges and (to put it nicely) free
rider issues.
By definition, a MS4 means a
conveyance or system of conveyances, including
roads with drainage systems, municipal streets,
catch basins, curbs, gutters, ditches, man-made
channels, or storm drains (Chestnut, 2015). The
MS4 is not part of a combined sewer system;
instead it involves the separate pieces involved
in carrying stormwater runoff into local
waterways as a point source of overflow. While
this is all seemingly well put together, there is
still one more aspect before the issue of
17. 16
stormwater waste management becomes
involved. In compliance with EPA regulations
and the Stormwater Phase II Final Rule (which
tightens preexisting regulations that require
operators of regulated small MS4’s to obtain
the NPDES permit mentioned previously.
Minimum Control Measures for
Phase II
As a community that falls under the
Phase II requirement in the state of Virginia, in
order to comply with the permit program JMU
must follow all six of the minimum controls. The
Phase II MS4 Program requirement found in
9VAC25-890-40 Section II.A states:
“The operator of a small MS4 must
develop, implement, and enforce a MS4
Program designed to reduce the
discharge of pollutants from the small
MS4 to the maximum extent practicable
(MEP), to protect water quality, to
ensure compliance by the operator with
water quality standards, and to satisfy
the appropriate water quality
requirements of the Clean Water Act
and its attendant regulations. The MS4
Program must include the minimum
control measures described in
paragraph B of this section.
Implementation of best management
practices consistent with the provisions
of an iterative MS4 Program required
pursuant to this section constitutes
compliance with the standard of
reducing pollutants to the "maximum
extent practicable," protects water
quality in the absence of a TMDL
wasteload allocation, ensures
compliance by the operator with water
quality standards, and satisfies the
appropriate water quality requirements
of the Clean Water Act and regulations
in the absence of a TMDL WLA.”
The six minimum control measures described in
9VAC25-890-40 Section II.B are:
1. Public Education and Outreach on
Stormwater Impacts
2. Public Involvement/Participation
3. Illicit Discharge Detection and
Elimination
4. Construction Site Runoff Control
5. Post-Construction Stormwater
Management in New Development and
Redevelopment
6. Pollution Prevention/Good
Housekeeping for Municipal Operations
Development of these 6 minimum controls
is required by the holder of the permit in order
to be in compliance. It is here that the best
management practices (BMPs) are prescribed to
be implemented in order to have a plan for
reducing waste entering in to the local
waterway. Each BMP2
listed contains a program
description, measurable goals/expected results,
schedule of activities, and a department
responsible for the coordination and continued
oversight after implementation. Many BMPs
also contain rationales as for why that specific
BMP was chosen to be implemented.
Room for Improvement at JMU
After discussions with involved parties
from JMU, stormwater management practices
have the potential to be streamlined for better
efficiency. Of potential solutions to stormwater
problems, the most commonly cited remedies
included public outreach/education and
coordination with competing interest groups.
These two issues are important aspects of not
only prescribed to varying plans and
regulations, but are basic areas for
improvement that may lead to least cost
2
And there are quite a few listed for each of the 6
minimum control measures. For a complete list of
BMPs and other JMU specific stormwater
management refer to Section 3 of the James
Madison University Municipal Separate Storm Sewer
(MS4) plan by Dale Chestnut (2015).
18. 17
solutions. As the first two minimum control
measures as described in Phase II, public
education and involvement plays a large part of
the initiatives set forth by the university and the
state. In an interview with Stormwater
Coordinator for JMU Dale Chestnut, he claims
education is the biggest part of helping to
reduce pollution, and also one of the more
difficult parts; getting people to understand
why certain practices are bad for the
environment, and specifically how certain
practices like illicit dumping and littering cause
problems for the people in charge of
stormwater management.
Advancement in Stormwater
Management Strategies:
Economies of Scale
The land JMU occupies is known for
having type C and D soil types. What this means
is that development of these kinds of areas has
very high potential for runoff since the soils
have such a slow infiltration rate. C type soils
consist chiefly of soils having a layer that
impedes the downward movement of water or
soils of moderately fine texture or fine texture
(ArcGIS Resources, 2016). Group D soils consist
mainly of clays with high shrink-swell potential
and soils that have a clay layer near the surface,
making them nearly impervious materials
(ArcGIS Resources, 2016). These soils types
attribute to high cost estimations for BMP
projects, however are not kept track of and
therefore cannot be included in the regression
analysis as a relevant variable. These costs
(while quite difficult to acquire from
government sources) are required as part of the
TMDL point requirement required by the
various stormwater management plans.
What does this mean for the production
process? There is potential for scale economies
to be observed in stormwater management
BMPs due to their high costs. This section of the
paper includes a simple regression analysis in
order to determine the presence and extent of
economies of scale for stormwater
management. By focusing on coordination
between not only difference projects, but
difference entities as well, there is a potential
for cost savings for a specific baseline level of
pollution reduction. Currently, there have been
90 different BMPs installed throughout JMU’s
campus with the intent of reducing pollution
runoff and slowing stormwater runoff. These
practices include: detention basins, retention
basins, filterras, green roofs, hydrodynamic
separators, infiltration areas, oil and water
separators, rain tanks, sand filters, storm filters,
and rainwater harvesting equipment. Each
individual BMP provides a high level of filtration
and flood control, and can be used
independently or in addition to other BMPs3
.
Empirical application methodology
Development of the diminishing cost
aspects of different BMPs have been explored
in Wossink et al (2003) and Weiss et al (2007).
In Wossink et al (2003), construction costs and
annual operation costs were taken into account
in order to statistically analyze for the effects of
scale economies. Using present value
calculations to estimate total economic impacts
of each BMP, Wossink found that all BMPs
looked at (excluding bioretention not in sandy
soils) displayed economies of scale. Weiss et al
(2007) found decreasing costs per unit of
construction for all BMPs except bioretention
filters. The findings of this case study mimic the
findings of Wossink et al (2003) in many aspects
for economies of scale.
A similar approach was taken for the
economies of scale analysis and applied to the
cost data collected for different BMPs on JMU’s
campus. A segmented regression analysis was
applied using OLS in order to estimate
3
An analysis of economies of scope regarding
efficient usage of multiple BMPs for one treatment
area can and should be further developed in order to
assess further cost savings
19. 18
parameters that indicate the presence of
decreasing returns, a measure of economies of
scale. The model developed for this analysis is
as follows:
Single variable model 𝑙𝑛 𝑌 = 𝛽0 +
𝑙𝑛 𝛽1𝑋1 + Ԑ
Multivariable model 𝑙𝑛 𝑌 = 𝛽0 +
𝑙𝑛 𝛽1𝑋1 + 𝑙𝑛 𝛽2𝑋2 + Ԑ
Variable Y is “lrealcost”, which is the log
of the real total cost of each BMP, X1
represents “lat”, which is the log of the acres
treated. In addition, variable X2, the log of
efficiency “lEFF”, was added to the model as it
seemed to intuitively been a relevant variable
to explain cost. The addition of this second
independent variable resulted in a large
increase in the R-squared value for the
manufactured BMPs and only a small increase
in the R-squared for Bioretention BMPs. Logs of
the data were taken in an attempt to normalize
the data and limit the effect of outliers as well a
way of transforming the parameter estimates
into a percent change measure. The parameter
estimate for the independent variable (log of
acres treated) is expected to be 0 < 𝛽 < 1
for projects that show economies of scale. In
the segmented regression analysis, all of the
BMP practices were split up into four initial
categories, bioretention (one model including
only the log of acres treated and the other
including log of acres treated and log of the
efficiency metric) and manufactured (broken
into the same two categories as the
bioretention practices). From there OLS was
preformed and the parameter estimates were
found.
Results
Plotted against the size of each BMP, an
upward sloping trend line appears for these
regressions. The parameter estimates and
relative R-squared values are given in the table
and figures below:
Table 1
Model Results
Parameter
Estimate
R-
Squ
are
Model
P-Value
lat lEFF
All BMPs single
variable
0.2
383
1
0.18
91
0.0004
All BMPs multiple
variable
0.2
074
8
-
0.30
457
0.20
9
0.0011
Bioretention BMPs
single variable
0.6
170
6
0.45
65
0.0001
Bioretention BMPs
multiple variable
0.5
538
1
-
0.74
019
0.48
29
0.0001
Manufactured
BMPs single
variable
0.0
950
6
0.00
86
0.0509
Manufactured
BMPs multiple
variable
0.0
703
6
-
0.38
523
0.41
17
0.001
20. 19
3 Fit plot for single variable model including all BMPs
4 Fit Plot for the single variable bioretention model
5 Fit Plot for single variable Manufactured BMP model
The resulting SAS output mimics results
in similar studies for the presence of economies
of scale. The parameter estimates for log of
acres treated in all models is signed in the
expected fashion and falls in the range that
indicated decreasing returns and thus
economies of scale. As the acreage goes up, the
total cost also increases but this happens at a
diminishing rate. A parameter estimate closer
to zero is stronger evidence for economies of
scale than a parameter estimate close to one.
An estimate of exactly one would indicate
constant returns thus no economies of scale
and greater than one would indicate
diseconomies of scale as the cost increases at
an increasing rate. Statistical significance of the
model can be determined by preforming t-tests
for each variable and an f-test to determine
significance of the model in its entirety. R-
squared values from these various models
depicted in Table 1 above range from 0.1216 to
0.4829. These results are often considered low,
but due to the small sample sizes and high
variation nature of the data, these values are to
be expected. Resulting t-values also have a
fairly wide range, making some statistically
significant and other not. Looking that the Pr>F
21. 20
result, the value of this number can be used to
determine significance of the entire model.
Lower P-values for each independent variable
tell us that if randomly assigned, the value
would have a smaller chance of being from the
same group as another. The initial combined
regression of all BMPs at JMU listed in figure 3
show a positive upward slope. The associated
parameter estimates of .20715 indicates
decreasing returns (1 > β1 > 0) and economies
of scale, which is to be expected. The relevant
R-squared value indicates a line of best fit
explaining around 19% of the data, even after
log normalization.
There is a logical way to split up the
different types of BMPs in order to better
assess parameter estimates. Splitting up
practices based on bioretention and
manufactured categories allowed for a
segmented regression analysis to be applied.
The advantage of the segmented regression
method in this case is now there is clear
evidence for stronger economies of scale for
Manufactured BMPs than there are for
Bioretention projects. Similar studies have
found inconsistent results as to the nature of
economies of scale for Bioretention projects,
however different geographic properties and
total costs vary greatly across different areas;
finding the presence of economies of scale for
Bioretention in such a small area can work as
supporting evidence for incentivized
cooperation across other tightly located permit
holders in order to increase the land area
treated by each BMP practice.
In the single variable models, the
independent variable “lat” was found to be very
significant (Pr>t value being <.001) for
Bioretention, and for Manufactured BMPs, the
associated p-value is .0590. At the 10% level,
the log of acres treated variable is found to be
statistically significant in all single variable
models and the multivariable models. The
efficiency measure for manufactured BMPs
listed in figure 9 was found to have a significant
P-value, however the variable was not to found
to be significant in the bioretention model. 4
The upward sloping regression is similar
to those found in previous studies of economies
of scale of stormwater runoff. With this
information, potential advantages appear that
should lead to more cooperation; however the
current rules and regulations involved in
stormwater management tend to favor smaller,
more frequent projects over larger “catch all”
projects. Parameter estimates for the
independent variables in the model indicate
that there are stronger decreasing returns for
Manufactured BMPs than for Bioretention
BMPs. National proportion use of BMPs were
analyzed in Martin et al (2007); the findings of
this study concluded that by far, retention is the
most popular method used by the sample
participants. The view that bioretention
typically does not have the strongest aspects of
economies of scale, yet is the most popular
method for pollution and flood mitigation,
raises questions behind the reasoning for the
implementation of this BMP. Weiss et al (2007)
cites land costs as the reason behind why
Bioretention BMPs are unlikely to be subject to
decreasing returns and economies of scale,
since land prices vary greatly between different
areas. In addition, land purchases do not show
any cost savings benefits when larger plots of
land are purchased at a time. Demand for land
and proximity to high demand areas drive the
cost of land up, making larger scale bioretention
practices less attractive in comparison to other
alternatives. Most practices excluding
bioretention would be more efficient if larger
BMPs were established to treat larger parcels of
land, rather than scattered small practices.
These non-retention BMPs require much less
land and often experience diminishing growth
in acres needed as the since of the practice and
treatment areas expand. Savings from land
costs make (especially manufactured type)
BMPs more attractive as an alternative to
4
The remainder of the data with associated output
and fit diagnostics can be found in the appendix.
22. 21
bioretention; more impervious surface can be
treated with sacrificing less land to the BMP.
The sign of the parameter estimates for
efficiency in the different models were
surprisingly signed negative, indicating that as
the efficiency of the project increases, the real
cost decreases. If this truly is the case, it is hard
to understand why any project with less than
100% pollution removal efficiency would be
implemented. Statistical significance of these
findings varies widely, any only after corrections
for heteroscedasticity were the corresponding
P-values found to be significant. Considering the
fact that this variable is expected to be sign
positive yet is signed negative in all cases in this
analysis indicates the need for further research
looking specifically at efficiency measures and
how it relates to the real cost of the project.
Larger sample sizes across a wider variety of
land will help determine the actual effect
efficiency has on cost.
Econometric concerns
In order to control for the various
outliers in the data, a log-log transformation
was applied to normalize the data. In
developing the model, various issues
concerning multicollinearity, endogenity and
hertoscedasticity were taken into consideration
when analyzing regression results. Since the
model is not a time series, serial correlation
issues can be disregarded for this portion of the
analysis. Statistical significant at the 5% level
can be found for a few of the variables in the
different models, however small sample sizes
lead to less reliable t-values. With only one to
two degrees of freedom for the models,
variation is accounted for in the assigned
parameters but still report P-values and F-
values with high variance. For this reason, the
10% level was chosen, as it makes more sense
to allow for variation in the data and the small
sample sizes, that way findings are not so easily
discredited. There are likely other variables that
are relevant to this model, however due to the
nature of data collection for current permit
requirements, there are often many
inconsistencies in the different categories
reported and data for soil type and construction
adjustments are not kept track of. The
unavailable variables are to be included in the
error term of the model but not to be forgotten
about for they likely have a lot of power to
explain further variations in the data.
Outliers in the data can be attributed to
the high variable cost nature of these sorts of
projects. The fit diagnostics for each model can
be found in the appendix. There are 2 very
apparent outliers in both sets of segmented
regressions. These outliers are most visible
when observing Cook’s Distance value and on
the residual plot by quantile. The models
including all BMPs have more variation in the
data, but the sample sizes are more than
doubled those for the segmented regressions.
The validity of the cost data is difficult to cross
reference since there is typically only one
person or department in charge of the data and
it will more than likely be consolidated. The
only way to verify the accuracy of the data to
determine if the outliers are reporting errors or
simply just extreme cases of cost variation. The
known variation in the type of land is not
specifically reported. A metric for soil type and
a metric for whether or not the project hits rock
would be most useful in order to explain further
the variation in costs from project to project.
Discussion of Potential Synergies
to Take Advantage of Economies of
Scale:
Issues of Coordination
In the current state, rules and
regulations set forth by the CWA and the EPA
have been relaxed for the reason that
23. 22
broadness gives the governing agents more
freedom to address issues in ways that a locally
efficient. Not every BMP should be applied at
the same rate for different projects. There
consists an advantage in using certain practices
over others, especially when taking into
consideration land costs and soil types. If
coordination is taken advantage of and cost
savings are observed, the cost curve from
Figure 1 mentioned earlier in the paper will
move closer to the ideal social marginal cost
curve and decreasing the emissions produced.
Before this can be achieved, the issue of
coordination needs to be addressed and is done
so in the following 3 sections.
Barriers to potential cooperation
Despite potential cost savings,
interdepartmental and permittee cooperation is
limited due to barriers such as difference in
project timing and cost-sharing difficulties due
to competing interests. Lack of cooperation
between different MS4 permit holders is
apparent in every MS4 Program Annual Report.
How is it that the only facility with a current
nutrient management plan within the city of
Harrisonburg is the Heritage Oaks Golf Course,
when all of the JMU lies within the city
boundaries? Instances like this show the lack of
cooperation between not only JMU and
Harrisonburg, but VDOT as well. Cost saving
potentials that have been found in this paper’s
analysis and echoed by the findings of Weiss et
al (2007) and Wossink (2003). The application of
economies of scale from previously cited
material can be used to justify “larger” BMPs,
meaning more acres treated for a lower cost
per unit reduction (and thus a lower ATC curve),
as well as a combination of smaller proposed
practices to lower unit costs more so on the
construction cost side.
Project Timing/Differences
As projects are needed to prevent
pollution from entering in to a specific MS4
control (such as curb gutters), BMPs are
designed in order to mitigate whatever form of
pollution is needed to stay in compliance with
NPDES permits. Cost per acre savings are not on
the radar for small BMPs, according to JMU
Stormwater Coordinator Dale Chestnut. Rather
than focusing on the economies of scale aspect,
least cost solutions are preferred. Bioretention
projects are preferred because of their cost
effectiveness, but they are not always the most
practical solution because they take up too
much space. Initial capital investments and
annual operation costs are a major part of
decisions for placement of BMPs. Another
variable that has become increasing expensive
is the cost of having to purchase land to
develop some stormwater management
practice. Land costs, specifically in
Harrisonburg, have been rising, making these
kinds of projects more expensive. High rates of
urban development in this area cause the
demand for land to spike, driving up costs. With
land demand rising, why are bioretention
methods the preferred method of treatment?
Since each project it approached
independently, the low operations and
maintenance costs associated with bioretention
trump the potential economies of scale savings
of combing projects. JMU already owning some
of the land that is required to build a BMP
makes land costs only a minor consideration.
Opportunity costs of used land in this paper has
not been analyzed, however studies by Wossink
(2003) used present value calculations to
estimate total economic impacts.
Differences in project type also have a
lot to do with failure to observe economy of
scale cost savings. Topographic differences in
the land require different means of
development, and some areas are limited to
what can be placed there. Different soil types
make areas more or less suitable for practices
such as bioretention. Type C and type D are
made up of clays, making these particular soils
are less efficient at removing pollution and
mitigating flooding. For that reason,
bioretention is not always the best practice to
be prescribed. Acquiring the land needed for
24. 23
bigger bioretention projects is a timely and
costly endeavor that can be replaced with a
more costly, but less land intensive practice.
Competing interests
This has been listed as one of the
biggest inhibitors to project coordination by
multiple stormwater coordinators and
professionals in the field. MS4 permits are
required for JMU, the city of Harrisonburg, and
the local branch of the Virginia Department of
Transportation, yet coordination between these
3 entities is limited. The current wording of
rules and regulations promote smaller projects
rather than large scale joint efforts. Perhaps the
cost savings from economies of scale are not
yet being recognized by those in charge of
writing and amending laws about stormwater
management, otherwise incentives would have
been placed in order to promote working
together towards a lower unit cost.
An interesting lack in coordination
appears when scanning through MS4 program
plans for the city of Harrisonburg. A search of
the City of Harrisonburg MS4 document returns
no references to James Madison University or
its stormwater coordination department.
Assumedly they have slightly different target
audiences, but failing to account for the full
time and part time students as citizens of the
town means missing a large percent of the
population that is undoubtable accountable for
some of the various sorts of pollutants. Having
separate MS4 permits and therefore separate
stormwater management plans and NPDES
permit requirements. This being the case,
different objectives and difference sources of
funding lead to different sorts of projects being
tasked. Having the land that JMU does, it is easy
to install landscaped natural BMPs along with
the manufactured BMPs. This is a different case
for the city as well as VDOT. Limited property
rights and budgeting restrictions mean that
some instances of stormwater runoff can be
jurisdictionally tricky. BMP 3F(2) under the
VDOT MS4 permit annual progress report
identifies goals such as “identifying and
developing and estimation of the area draining
from within VDOT right of way to identified
TMDL waterways” and “implementation of
procedures, reconnaissance and sampling
protocols to identify and address the discharge
of the pollutant identified in the waste load
allocation (WLA) to the MS4. This allocation is
an accurate representation for comparison for
similar waste load allocations for other areas in
VA. In the case of VDOT, WLAs must be
approved by the Soil and Water Conservation
Board. An example of the WLA from the VDOT
MS4 Annual progress report (2014) is given in
Table 3 below:
6 Table 3 VDOT’s WLAs for TMDLs (listed in Attachment 1 of the
VDOT MS4 Annual progress report (2014)
These reductions requirements do not
talk about what is happening in other sectors
that are also assigned WLAs. A further
25. 24
development of the discussion about what is
being done to treat stormwater runoff across
jurisdictional units is needed in order to further
capture potential synergies. Independent WLAs
are needed for accountability reasons, but
promotion or incentivizing cooperation with
other local permit holders could yield a cost
savings where everyone benefits. Building in
costs and empirically valuing nature as an
ecosystem service is a challenge in the lenses of
WLAs and taxes/permit fees that pay for
preserved state of the environment as
demanded by the people. No matter the
method, policies regulating law such as
emission taxes and auctioned permits are likely
subject to competition interests by firms in the
political realm. A study by Milliman and Pierce
(1988) describe how the transfer payments
extracted from the polluters may be useful to
spur innovative activity, but it also may be a
moot point if these payments are blocked by
recalcitrant firms in the political arena.
Acknowledgements of Potential
Synergies
The problem now is how well are these
load allocations being followed and what can
cooperation potentially do to help enhance
local water quality. By addressing these issues,
potential synergies exist not only in the realm of
economies of scale, but also in management,
maintenance, field research positions.
Operations and maintenance cost savings based
on cost estimated by Wossink (2003) for specific
BMP practices exist as well as construction costs
serve as the basis for the argument that
synergies could exist that produce cost saving
results in the long run. Manufactured BMPs
according to the results of this study have the
greatest potential for economies of scale, but
Bioretention should not be overlooked as
economies of scale are present in that
segmented model as well.
The other aspect involved in the
potential synergies between permit holders is
one more difficult to quantify. If cost savings are
possible, who is technically responsible for
bearing the burden of pollution reduction and
making the plans to development the required
stormwater management practice? Defining
property rights on runoff is a difficult task that
has been held up by vested government and
private parties that do not want to have to raise
the nutrient reduction or pollution reduction
goals if responsibility is dealt unequally. Below
(Figure 7) is an example of how Arlington
County in their MS4 Service Area Delineation
Methodology (2013) has been used to assign
rights of way in the instances of roadways:
7 Examples of each type of VDOT areas
Rather than assign the right of way as a
way of dealing with jurisdictional issues, service
areas can be managed by a collaborative effort.
This solution if imposed through Va. State laws
would mean a wider range of sollutions that
looked at the issue from a watershed
perspective rather than a jurisdictional one.
26. 25
Larger service areas open up the possibility of
alternative forms of mitigation, ultimately
leading to betterand more efficienct practices
Conclusion
After both a qualitative and quantative
assessment of stormwater management
policies under the rules and regulations that
apply to James Madison University, the
presence of cost saving economies of scale in
BMP implementation is found and reinforced by
the supporting literature review. As a public
good with associated negative externalities,
underproduction can be expected and a skewed
understanding of how consumer preferences
are aggregated is likely. The review of relevant
programs and management plans can be
applied to different areas in Virginia, but it is
unlikely that the same state programs and
names translate to other states. However, it is
not the specific names of the programs that
hold merit in this report. The emphasis of this
analysis was to test for and confirm economies
of scale in production of new BMPs that are
constantly being applied to new areas as they
pass the minimum threshold into being
required to obtain permits and adopt
stormwater management plans.
Results from the statistical analysis of
stormwater BMPs on the campus of James
Madison University found, with high levels of
confidence, that there is a positive relationship
between cost of a BMP and the acres treated,
and this cost increases at a decreasing rate.
Economies of scale were found to be present in
all variations of the model, with some
categories showing stronger decreasing returns
than others. If these cost savings are to be
observed, better cooperation between permit
holders and more flexible funding to allow for the
construction of larger, more cost efficient projects,
must be a targeted goal of policy makers and
enforcers alike. Designed schemes by state and
federal governing bodies that promote cooperation
and incentivize high efficient/low cost projects are
likely going to be a necessary first step in moving
towards higher water quality. Further research is
needed on some of the less quantifiable aspects of
stormwater management in order to improve the fit
of the model. Public education and restrictions are
and will continue to be the most effective way to
limit the amount of pollution to an acceptable level.
The demand of this public good to be clean,
swimmable, and fishable, by individuals locally and
downstream is only going to rise and more and more
waterways are compromised due to pollution.
Mitigating further damage has been a set priority
since the enactment of the CWA and the start of the
EPA; we now are in a position where we can further
efficiency, improve equity, and provide a clean
public good to the citizens at the level they demand.
27. - 26 -
Works Cited
California Environmental Protection Agency. (2013). Storm water Program-Municipal Program. State Water
Resources Control Board. Retrieved from
http://www.waterboards.ca.gov/water_issues/programs/stormwater/municipal.shtml
Chesapeake Bay Preservation Act. (1988). Chesapeake Bay Preservation Area Designation and Management
Regulations enacted by the VA General Assembly. Retrieved From
http://law.lis.virginia.gov/vacodefull/title62.1/chapter3.1/article2.5/
Chestnut, Dale. (2015). James Madison University MS4 Program Plan. Retrieved from
http://www.jmu.edu/facmgt/sustainability/Stormwater/ms4.shtml
Costanza, Robert. R. d'Arge, R. de Groot, S. Farber, M. Grasso, B. Hannon, S. Naeem, K. Limburg, J. Paruelo, R.V.
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JMU (1). (2015). Land Disturbing Activities. Retrieved from
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11.pdf
Line, Daniel E. Jon A. Gregory, D. Jennings, and Jy Wu. (1996). Water Quality of Stormwater Runoff from Ten
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Maher, Michael Davis. (1980). The Economics of Urban Stormwater Management (Ph.D. Dissertation). University
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Martin, C. Y. Ruperd, M. Legret. (2007). Urban stormwater drainage management: The development of a
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Milliman, Scott. Raymond Prince. (1988). Firm Inventives to Promote Technological Change in Pollution Control.
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Pitt, Robert. Richard Field, Melinda Lalor, Michael Brown. (1995). Urban Stormwater Toxic Pollutants: Assessment,
Sources, and Treatability. Water Environment Federation. Water Environment Research. Vol. 67, No. 3
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Service Area Delineation Methodology. (2013). Arlington County MS4 Program Plan Appendix A. Retrieved from
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Stormwater Phase II Final Rule. (2000). Small MS4 Stormwater Program Overview Fact Sheet 2.0. Environmental
Protection Agency. Retrieved from https://www3.epa.gov/npdes/pubs/fact2-0.pdf
Tsihrintzis, Vassilios A. Rizwan Hamid. (1995). Modeling and Management of Urban Stormwater Runoff Quality: A
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29. - 28 -
Appendix
The REG Procedure all BMPs
Model: MODEL1
Dependent Variable: lrealcost
Number of Observations Read 88
Number of Observations Used 62
Number of Observations with Missing Values 26
Analysis of Variance
Source DF Sum of
Squares
Mean
Square
F Value Pr > F
Model 1 6.31424 6.31424 13.99 0.0004
Error 60 27.07866 0.45131
Corrected Total 61 33.39289
Root MSE 0.67180 R-Square 0.1891
Dependent Mean 10.24261 Adj R-Sq 0.1756
Coeff Var 6.55884
Parameter Estimates
Variable DF Parameter
Estimate
Standard
Error
t Value Pr > |t| Heteroscedasticity Consistent
Standard
Error
t Value Pr > |t|
Intercept 1 10.23967 0.08532 120.01 <.0001 0.08380 122.20 <.0001
lat 1 0.23831 0.06371 3.74 0.0004 0.06633 3.59 0.0007
31. - 30 -
The REG Procedure all BMPs
Model: MODEL1
Dependent Variable: lrealcost
Number of Observations Read 88
Number of Observations Used 61
Number of Observations with Missing Values 27
Analysis of Variance
Source DF Sum of
Squares
Mean
Square
F Value Pr > F
Model 2 6.65931 3.32965 7.66 0.0011
Error 58 25.20715 0.43461
Corrected Total 60 31.86646
Root MSE 0.65925 R-Square 0.2090
Dependent Mean 10.22252 Adj R-Sq 0.1817
Coeff Var 6.44896
Parameter Estimates
Variable DF Parameter
Estimate
Standard
Error
t Value Pr > |t| Heteroscedasticity Consistent
Standard
Error
t Value Pr > |t|
Intercept 1 10.01182 0.16629 60.21 <.0001 0.15810 63.33 <.0001
lat 1 0.20748 0.06443 3.22 0.0021 0.05873 3.53 0.0008
leff 1 -0.30457 0.20555 -1.48 0.1438 0.12961 -2.35 0.0222
The REG Procedure all BMPs
33. - 32 -
The REG Procedure manufactured BMPs
Model: MODEL1
Dependent Variable: lrealcost
Number of Observations Read 34
Number of Observations Used 30
Number of Observations with Missing Values 4
Analysis of Variance
Source DF Sum of
Squares
Mean
Square
F Value Pr > F
Model 1 0.66174 0.66174 3.88 0.0590
Error 28 4.78065 0.17074
Corrected Total 29 5.44239
Root MSE 0.41320 R-Square 0.1216
Dependent Mean 10.18272 Adj R-Sq 0.0902
Coeff Var 4.05789
Parameter Estimates
34. - 33 -
Variable DF Parameter
Estimate
Standard
Error
t Value Pr > |t| Heteroscedasticity Consistent
Standard
Error
t Value Pr > |t|
Intercept 1 10.15452 0.07679 132.24 <.0001 0.07253 140.00 <.0001
lat 1 0.09506 0.04829 1.97 0.0590 0.03363 2.83 0.0086
The REG Procedure manufactured BMPs
35. - 34 -
The REG Procedure manufactured BMPs
Model: MODEL1
Dependent Variable: lrealcost
Number of Observations Read 34
Number of Observations Used 29
Number of Observations with Missing Values 5
Analysis of Variance
Source DF Sum of
Squares
Mean
Square
F Value Pr > F
Model 2 1.53707 0.76854 9.10 0.0010
Error 26 2.19616 0.08447
Corrected Total 28 3.73323
Root MSE 0.29063 R-Square 0.4117
Dependent Mean 10.13840 Adj R-Sq 0.3665
Coeff Var 2.86666
Parameter Estimates
36. - 35 -
Variable DF Parameter
Estimate
Standard
Error
t Value Pr > |t| Heteroscedasticity Consistent
Standard
Error
t Value Pr > |t|
Intercept 1 9.77991 0.10915 89.60 <.0001 0.11378 85.96 <.0001
lat 1 0.07036 0.03426 2.05 0.0502 0.02347 3.00 0.0059
lEFF 1 -0.38523 0.10786 -3.57 0.0014 0.07264 -5.30 <.0001
The REG Procedure manufactured BMPs
37. - 36 -
The REG Procedure bioretention
Model: MODEL1
Dependent Variable: lrealcost
Number of Observations Read 34
Number of Observations Used 32
Number of Observations with Missing Values 2
Analysis of Variance
Source DF Sum of
Squares
Mean
Square
F Value Pr > F
Model 1 12.66512 12.66512 25.20 <.0001
Error 30 15.07691 0.50256
Corrected Total 31 27.74203
Root MSE 0.70892 R-Square 0.4565
Dependent Mean 10.29876 Adj R-Sq 0.4384
Coeff Var 6.88352
Parameter Estimates
38. - 37 -
Variable DF Parameter
Estimate
Standard
Error
t Value Pr > |t| Heteroscedasticity Consistent
Standard
Error
t Value Pr > |t|
Intercept 1 10.45560 0.12916 80.95 <.0001 0.12082 86.54 <.0001
lat 1 0.61706 0.12292 5.02 <.0001 0.11058 5.58 <.0001
The REG Procedure bioretention
Model: MODEL1
Dependent Variable: lrealcost
39. - 38 -
The REG Procedure bioretention
Model: MODEL1
Dependent Variable: lrealcost
Number of Observations Read 34
Number of Observations Used 32
Number of Observations with Missing Values 2
Analysis of Variance
Source DF Sum of
Squares
Mean
Square
F Value Pr > F
Model 2 13.39761 6.69880 13.54 <.0001
Error 29 14.34442 0.49464
Corrected Total 31 27.74203
Root MSE 0.70330 R-Square 0.4829
Dependent Mean 10.29876 Adj R-Sq 0.4473
Coeff Var 6.82901
Parameter Estimates
40. - 39 -
Variable DF Parameter
Estimate
Standard
Error
t Value Pr > |t| Heteroscedasticity Consistent
Standard
Error
t Value Pr > |t|
Intercept 1 10.04832 0.35837 28.04 <.0001 0.29399 34.18 <.0001
lat 1 0.55381 0.13256 4.18 0.0002 0.10745 5.15 <.0001
leff 1 -0.74019 0.60825 -1.22 0.2334 0.36522 -2.03 0.0520
The REG Procedure bioretention
Model: MODEL1
Dependent Variable: lrealcost