Rhiannon Ervin Assignment 6



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Rhiannon Ervin

Assignment 6

April 8, 2011
Introduction
In many towns and cities in the United States, zoning laws were created many years ago and have not been significantly modified since. Consequently, many of the newer ideas of smart growth, low impact development (LID) or watershed management best management practices (BMPs) are not incorporated into zoning ordinances. One way to illustrate the impact of leaving zoning regulations as they are is to conduct a build-out analysis. A build out analysis takes the current zoning regulations and maps the future look of an area if all parcels were built to the maximum extent allowed in the zoning laws. A build-out analysis can also be used to estimate the additional amount of resources required (e.g. water-use) to support build-out. With this knowledge, planners and regulators can discuss what zoning laws and regulations should be added or modified to protect both the natural and the living environment of a particular location.

For my final GIS project, I propose to conduct a build-out analysis of Concord, MA, with a particular focus on stormwater management. First a conventional build-out analysis will be done using current zoning laws. The increase of impervious surface and stormwater flow will be calculated for this scenario. Then the analysis will be conducted again assuming a percentage of impervious surface is reduced using LID technologies. This percentage and the type of LID treatment suggested will be dependent on land use. Additionally soils data and floodplain data will be used to ensure that LID technologies can be used in these areas. The analysis will be general, but will be used to demonstrate the appeal of using GIS to present complicated land use planning and stormwater modeling projects.



Background

Similar analyses have been conducted in the literature. Below are four short summaries of articles that focus on incorporating stormwater management into urban planning. Each focuses on one or more of the key factors of the proposed project: build-out analysis, stormwater analysis, and LID implementation. The first two summaries do a more traditional build-out analysis. They do not incorporate much GIS, though both acknowledge that GIS would be a very good tool to display this information. The second two are more complicated and incorporate decision support system (DSS) models into a GIS analysis to determine the effect of putting specific BMPs in specific locations.

Chester et al. (1996) wrote a review on the idea of using impervious surface as an environmental indicator. As natural surfaces are paved, the natural hydrologic cycle changes in both the way water moves and the way water is stored, which usually degrades the water resources in the area. Previous research had shown that water degradation can be divided into categories, each relating to percent impervious surface in a watershed. The three categories are: protected, < 10% impervious; impacted, 10%-30% impervious; degraded, > 30%. These categories are quite general and are not the perfect criteria for every watershed, but are good for estimating impacts over a broad range of locations. Additionally, the amount of pollutants coming off an impervious surface is dependent upon the use of that specific surface. Therefore, watershed degradation can be tied to both impervious surface and land use. They demonstrated how maps of the current built state of a location and the future build-out state can be used to show stakeholders the degradation of the watershed in both instances. The maps were made using satellite pictures, from which general land-cover categories and estimates of impervious surface were taken. (GIS was not used, though they noted that as GIS becomes more user friendly, it would be the ideal method for performing this type of analysis). The authors then suggested that the maps be used to aid regional and local planning, as well as modify regulations. They suggest that from this rough build-out analysis planners should revisit zoning requirements and emphasize the minimization of impervious surface in future development.

In their 2005 paper, Conway and Lathrop discuss using local scale watershed management to “bridge the gap between land use planning and natural resource management”. They particularly focus on using build-out analysis to examine possible future landscapes, before permanent changes occur. To present the utility of the build-out analysis, the authors use the Bamegat Bay Estuary in New Jersey as a case study. They conducted four build-out scenarios: 1) Current regulations scenario: based on current zoning and environmental regulations; 2) Down zoning scenario: minimum lot size is increased; 3) Large buffer scenario: down zoning with an increased buffer around all freshwater wetlands and streams; 4) Open space scenario: down zoning scenario with a more aggressive plan to protect open space. For each scenario maps were created to show future land use and percent imperviousness. The authors then proposed that these maps be shared with regulators to help them understand the impact of current and future zoning and regulations.


Sample et al. (2001) demonstrate the utility of combining GIS with water resources decision support systems (DSS) for local scale stormwater management. In general, DSS incorporate hundreds of variables and use complicated algorithms to solve the optimization problem. Sample et al. (2001) state that “the strength of GIS is that it can be used as a common ground between specialists and nonspecialists to help them communicate effectively.” To demonstrate this claim, the authors examine a developed mix use neighborhood to determine what best management practices (BMPs) could be added to the neighborhood to return stormwater characteristics to predevelopment conditions. The analysis used GIS data layers of land use, parcel geometry, storm sewers, manholes, soils, point elevations, street rights-of-way, rooflines, and driveways. They then use the curve number method that assigns different levels of change to the natural hydraulic system depending on land use and impervious surface. Then, the amount of land that should be dedicated to best set aside BMP strategies to make up for the change in the hydraulic system is calculated. At this point, an optimization routine can be run to come up with the best (herein defined as lowest cost) locations to implement BMPs.
In their 2010 paper, Viavattene et al., create a GIS-based BMP model to examine the reduction in stormwater runoff through BMP implementation. They say that one of the strengths of this model is that the GIS interface allows it to be used by “a range of local authority/municipal, federal/state regulatory agencies, drainage engineers/consultants and other interested stakeholders in the development and evaluation of stormwater drainage infrastructure contained within stormwater management plans.” Viavattene et al. (2010) demonstrate the effectiveness of their tool by using a case study of the urban regeneration project in the city of Birmingham, UK. This city was chosen because (as of 2007) a large part of the sewer network surcharged during 5 year rainfall events. The GIS data layers included detailed land use, soils, surface gradients, and the sewer system. The user is able to use the “ADD BMP Tool” to add appropriate BMPs to data layers. Running the model before and after BMP implementation showed that the same number of sewer surcharges occurred, but that the flow of each surcharge was greatly reduced due to the BMPs. The tool showed the user that the specific selection of BMPs helped reduce the magnitude of the problem, but that more modifications would be necessary to completely eradicate the problem.

Methods

Though none of these examples is laid out the exact analysis proposed for this project, methods used in each example will be used to complete the final project. The generalized procedure is as follows:



  1. Evaluate current stormwater conditions using data on buildings and impervious surface using a specific design storm (TBD)



  1. Incorporate zoning laws with zoning, land use, hydrography, open space, contours and parcels data to estimate current build-out conditions



  1. Estimate the amount of additional impervious surface at build-out



  1. Estimate the additional amount of stormwater due to build-out



  1. Use the soils, land use, floodplain, wetland, and hydrography data sets to identify locations for LID implementation



  1. Determine a general criteria for LID application in these areas



  1. Calculate the benefit (reduction of stormwater) due to LID implementation

Data Layers

The following data layers will be used for this analysis.



Data Layer

Source

Source Scale

Year Created

Boundary Polygon

M Drive City of Concord

unknown

2005*

Hydrography Polygon

M Drive City of Concord

unknown

2005*

Land Use Polygon

Mass GIS

1:5,000

2005

Wetlands Polygon

M Drive City of Concord

unknown

2006*

Open Space Polygon

Mass GIS

1:25,000

2005

Flood Plain Polygon

M Drive City of Concord

unknown

2005*

Contours Polygon

M Drive City of Concord

unknown

2005*

Roads Polygon

M Drive City of Concord

unknown

2005*

Buildings Polygon

M Drive City of Concord

unknown

2007*

Easements Polygon

M Drive City of Concord

unknown

2005*

Zoning Polygon

Mass GIS

unknown

2007

Parcels Polygon

M Drive City of Concord

unknown

2006*

Edge of Pavement Polygon

M Drive City of Concord

unknown

2005*

Soils Polygon

M Drive City of Concord

unknown

2005

Impervious Surface Raster

Mass GIS

1 meter

2005

Storm Sewer Lines

M Drive City of Concord

unknown

2005*

Catch Basin Points

M Drive City of Concord

unknown

1995

* Represents year modified. Unable to find year created in meta-date on the m drive.

References

Arnold Jr., Chester L. and Gibbons, C. James. 1996. Impervious Surface Coverage: The Emergence of a Key Environmental Indicator. Journal of the American Planning Association, 62: 2, 243 — 258.

Conway, M. and R.G. Lathrop. 2005. Alternative land use regulations and environmental impacts: assessing future land use in an urbanizing watershed. Landscape and Urban Planning 71: 1–15.

Sample, D.J., Heaney, J.P., Wright, L.T., and R. Koustas. 2001. Geographic Information Systems, Decision Support Systems, and Urban Storm-water Management. Journal of Water Resources Planning and Management, May/June 2001



Viavattene, C., Ellis, J.B., Revitt, D.M., Seiker, H and Peters, C. 2010. The application of a GIS-based BMP selection tool for the evaluation of hydrologic performance and storm flow reduction. Proc. 7th Int.Conf. Sustainable Techniques and Strategies for Urban Water Management; NOVATECH10. 28 June – 1 July 2010. GRAIE, Insa de Lyon. Lyon, France.
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