Using GIS to determine the percentage of Effective Impervious Surface in a Watershed
UEP 232 Introduction to GIS
Yuan (Rose) Wang
Assignment #1
Idea 1:
[Summary]
Impervious surface in urban landscape is often thought to be correlated with non-point source
loadings to surface water bodies. However, recent studies suggest that effective impervious surface,
which is a subset of total impervious surface, is better correlated with water quality variables. Effective
impervious surface areas are connected to urban drainage system. The rainwater falls on them will be
routed directly to rivers through the drains. Rainwater falls onto rooftops whose gutters are not
connected to the stormwater pipes will probably infiltrate through lawns and soil. These rooftop areas
should be excluded from the total impervious area.
The difficult part of this study would be determining the connectivity of the drainage. Some
towns may have required drainage connection on buildings constructed during certain periods. Public
buildings may have more connected drainage than private houses. Some roads may have been designed
with curb and gutters but some may not. All these features decide that connectivity is very site specific.
So, empirical ratio is unlikely to be helpful in predicting percentage of Effective Impervious Surface in
different sites. I plan to look into a subbasin of Mystic River Watershed as a pilot project and hope this
study can provide useful methodology to be upscaled to the whole watershed for pollutants load
estimation.
[Related Journal Articals]
Arnold & Gibbons (1996) illustrated why impervious surface becomes a big problem in water
quality and how planners and local officials can mitigate this problem. In the past, stormwater
management has mostly focusing on how to get the stormwater out of sight fast without considering its
impact on downstream water quality. The large volume of runoff caused by impervious surface,
together with increased efficiency of water conveyance through pipes, gutters, and artificially straight
channels result in increased severity of flooding and decreased water quality downstream.
Hatt, et al, (2004) conducted statistical analysis to examine the impacts of urban density and
drainage connection on water quality of streams. It was the first of such study to consider drainage
connection as one important variable. It shows that effective impervious area (EIA) has a better
correlation to water quality indices than total impervious area (TIA). This suggests the importance of
quantifying EIA.
Alley & Veenhuis (1983) is a well cited paper in this area. They studied the TIA, EIA and their
ratio of EIA/TIA on 19 urban basins. Even though no GIS technique was used in this study, some
interesting patterns were found with regard to land use. For example, for single house families, the ratio
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of EIA/TIA does not vary with lot size. Basins with more multifamily houses have greater EIA/TIA than
basins single family houses. Commercial and industrial land use have high EIA/TIA ratio and have greater
variability among different developments than residential development. This provides me with some
insights in the relationship between land use and EIA/TIA ratio. During my study, I shall first look at land
use map of the Mystic River Watershed to decide a best sub-basin than have a good representation of
the whole basin with regard to land use. If door-to-door interview is necessary, it is also important to
further zone the sub-basin and chooses the areas that can be representative of the whole sub-basin
based on the ratio of property types and land use.
Roy & Shuster (2009) combined the use of GIS data compilation, aerial photo interpretation and
parcel scale field assessment to determine the percentage of EIS in a suburban basin in Cincinnati, Ohio.
The study basically provides a methodology to compute the EIS using combined GIS and field
assessment. The basic GIS layers needed are impervious surface, storm and sewer connection data,
drainage map, and topography layer. The map of the study is shown in Figure 1. An important step
mentioned is the determination of the surface connectivity, which requires door-to-door interview to
property owners. I have concerns on whether it would impose big barriers to this project.
Han & Burian (2009) applied an automated macro in GIS to compute EIA. They applied a GIS
code to geospatially intersect the impervious surface coverage with a fine-scale digital elevation model
(DEM) and a vector dataset identifying locations of stormwater collection infrastructures (e.g., gutters,
inlets, channels). After intersection, the geospatial analysis step traces the water flow path from
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classified impervious pixels until it either enters the drainage system or passes over a pervious area. This
method would require a high resolution layer for water collection system. In addition, coding in GIS
environment is needed, which may not be easily grasped during an intro course.
Another important literature is Dr. Carl Zimmerman’s dissertation (Zimmerman, 2012). He created
an inductive geospatial model to predict EIA in residential areas at hydrologic unit scale. The outcome of
his research is a statistically significant equation to predict parcel level DCIA. The important variables
from this equation are total impervious cover within the parcel, the absence/presence of driveway
drains, and slope direction of the driveway.
Alley, W., & Veenhuis, J. (1983). Effective impervious area in urban runoff modeling. Journal of Hydraulic
Engineering, 109(17669), 313–319. Retrieved from
http://ascelibrary.org/doi/abs/10.1061/(ASCE)0733-9429(1983)109:2(313)
Arnold, C. L., & Gibbons, C. J. (1996). Impervious Surface Coverage: The Emergence of a Key
Environmental Indicator. Journal of the American Planning Association, 62(2), 243–258.
doi:10.1080/01944369608975688
Han, W., & Burian, S. (2009). Determining effective impervious area for urban hydrologic modeling.
Journal of Hydrologic Engineering, (February), 111–120. Retrieved from
http://ascelibrary.org/doi/abs/10.1061/(ASCE)1084-0699(2009)14:2(111)
Hatt, B. E., Fletcher, T. D., Walsh, C. J., & Taylor, S. L. (2004). The influence of urban density and drainage
infrastructure on the concentrations and loads of pollutants in small streams. Environmental
management, 34(1), 112–24. doi:10.1007/s00267-004-0221-8
Roy, A. H., & Shuster, W. D. (2009). Assessing Impervious Surface Connectivity and Applications for
Watershed Management. JAWRA Journal of the American Water Resources Association, 45(1),
198–209. doi:10.1111/j.1752-1688.2008.00271.x
Zimmerman, C. L. (2012). Determining Directly-Connected Impervious Areas in Residential Land Uses.
University of Connecticut. Retrieved from http://search.proquest.com//docview/1033185962
[Data Source with Free Access]
MassGIS impervious surface layer:
http://www.mass.gov/anf/research-and-tech/it-serv-and-support/application-serv/office-of-geographicinformation-massgis/datalayers/impervioussurface.html
MassGIS Land use layer:
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http://www.mass.gov/anf/research-and-tech/it-serv-and-support/application-serv/office-of-geographicinformation-massgis/datalayers/lus2005.html
MassGIS Drainage Sub-basins:
http://www.mass.gov/anf/research-and-tech/it-serv-and-support/application-serv/office-of-geographicinformation-massgis/datalayers/subbas.html
MassGIS Water/Sewer Services areas:
http://www.mass.gov/anf/research-and-tech/it-serv-and-support/application-serv/office-of-geographicinformation-massgis/datalayers/mwraservice.html
MassGIS Building footprints:
http://www.mass.gov/anf/research-and-tech/it-serv-and-support/application-serv/office-of-geographicinformation-massgis/datalayers/lidarbuildingfp2d.html
MassGIS Digital Orthophoto Topographic Breaklines:
http://www.mass.gov/anf/research-and-tech/it-serv-and-support/application-serv/office-of-geographicinformation-massgis/datalayers/l.html
MassGIS Digital Elevation Model (DEM):
http://www.mass.gov/anf/research-and-tech/it-serv-and-support/application-serv/office-of-geographicinformation-massgis/datalayers/imgelev5k.html
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