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

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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 -

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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.

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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.

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,

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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

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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

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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

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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

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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.

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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

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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

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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

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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).

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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

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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-Square

Model P-Value

lat lEFF

All BMPs single variable

0.2383

1

0.1891

0.0004

All BMPs multiple variable

0.2074

8

-0.30457

0.209

0.0011

Bioretention BMPs single variable

0.6170

6

0.4565

0.0001

Bioretention BMPs multiple variable

0.5538

1

-0.74019

0.4829

0.0001

Manufactured BMPs single variable

0.0950

6

0.0086

0.0509

Manufactured BMPs multiple variable

0.0703

6

-0.38523

0.4117

0.001

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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

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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.

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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

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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

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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

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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.

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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.

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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. O'Neill, R. Raskin, P. Sutton, M. van den Belt. (1997). The value of the world’s ecosystem services and natural capital. Nature, vol 387 pg 253-260

CSO Control Policy. (1994). Federal Register Combined Sewer Overflow Control Policy. Environmental Protection Agency, Vol. 59 No. 75

JMU (1). (2015). Land Disturbing Activities. Retrieved from https://www.jmu.edu/facmgt/sustainability/Stormwater/files/policy-land-distrubing-activities-2015-11.pdf

Line, Daniel E. Jon A. Gregory, D. Jennings, and Jy Wu. (1996). Water Quality of Stormwater Runoff from Ten Industrial Sites. Water Resources Bulletin, American Water Resources Association. Retrieved from http://onlinelibrary.wiley.com/doi/10.1111/j.1752-1688.1996.tb03478.x/epdf

Maher, Michael Davis. (1980). The Economics of Urban Stormwater Management (Ph.D. Dissertation). University Microfilms International. Retrieved from https://scholarship.rice.edu/handle/1911/15564

Martin, C. Y. Ruperd, M. Legret. (2007). Urban stormwater drainage management: The development of a multicriteria decision aid approach for best management practices. European Journal of Operational Research, Vol 181(1), 338-349.

Milliman, Scott. Raymond Prince. (1988). Firm Inventives to Promote Technological Change in Pollution Control. Journal of Environmental Economics and Management 17, 247-265.

National Water Quality Monitoring Council. (2007).Glossary of water-quality monitoring terms: Advisory Committee on Water Information, access date July 1, 2011.

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 (May-Jun., 1995), pp. 260-275.

Service Area Delineation Methodology. (2013). Arlington County MS4 Program Plan Appendix A. Retrieved from http://arlingtonva.s3.amazonaws.com/wp-content/uploads/sites/13/2015/04/App-A_D.pdf

- 27 -

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 Review. Water Resource management, vol (11), 137-164.

U.S. Geological Survey. (2011). Water science glossary of terms: U.S. Geological Survey. Retrieved from http://water.usgs.gov/edu/dictionary.html

VDOT. (2014). MS4 Annual Progress Report July 2013-June2014. VDOT Location and Design Division. Retrieved from http://www.virginiadot.org/business/resources/LocDes/MS4-July2013-June2014_AnnualProgressReport.pdf.

Weiss, P. T., Gulliver, J. S., & Erickson, A. J. (2007). Cost and pollutant removal of storm-water treatment practices. Journal of Water Resources Planning and Management, 133(3), 218-229.

Wossink, G. A. A., & Hunt, B. (2003). The economics of structural stormwater BMPs in North Carolina. Water Resources Research Institute of the University of North Carolina.

US. Bureau of Labor Statistics. (2016). Producer Price Index for All Commodities [PPIACO]. Federal Reserve Bank of St. Louis. Retrieved from https://research.stlouisfed.org/fred2/series/PPIACO

Weiss, Peter T., John S. Gulliver, Andrew J. Erickson. (2005). The Cost and Effectiveness of Stormwater Management Practices. Minnesota Department of Transportation. Retrieved from http://www.lrrb.org/pdf/200523.pdf

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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

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The REG Procedure all BMPs

- 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

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- 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

- 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

- 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

- 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

- 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

- 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

- 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

- 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

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