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Higher or Lower Density? What Gives the Best Bang for the Buck for Mitigating the Effects of Development? John Jacob, Ph.d. Ricardo López, M.S. Low Impact Development Vs. Urban Sprawl Low Impact Development (LID) Increase the amount of perviousness in developed areas Smart Growth

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slide1

Higher or Lower Density? What Gives the Best Bang for the Buck for Mitigating the Effects of Development?

John Jacob, Ph.d.

Ricardo López, M.S.

The AWRA 2006 Conference on GIS & Water Resources IV

low impact development vs urban sprawl
Low Impact DevelopmentVs.Urban Sprawl
  • Low Impact Development (LID)
    • Increase the amount of perviousness in developed areas
  • Smart Growth
    • Increase density (and therefore imperviousness), but save more open space overall

The AWRA 2006 Conference on GIS & Water Resources IV

slide3
Goal

Report the results of a modeling effort comparing the two approaches in a hypothetical watershed

The AWRA 2006 Conference on GIS & Water Resources IV

impervious land cover
Impervious land cover
  • Impervious surface features are those that prohibit water from naturally infiltrating the ground (concrete, pavement, etc)
  • Urban Landscapes:
    • Concrete, pavement, rooftops
    • Swimming Pools
  • Impervious Land Cover: essentially the area that is not “green”

The AWRA 2006 Conference on GIS & Water Resources IV

pop density vs impervious land cover

Total Population:

100,000

5,000 Pop/Sq. Mile

10,000 Pop/Sq. Mile

Total Study Area:

50 Sq. Miles

Total Study Area:

50 Sq. Miles

Developed Area:

20 Sq. Miles

Developed Area:

10 Sq. Miles

Pop. Density Vs. Impervious Land Cover

The AWRA 2006 Conference on GIS & Water Resources IV

slide6

Impervious Cover Model

Good

Sensitive

Fair

Stream Quality

Impacted

Urban Drainage

Poor

Non-Supporting

10% 25% 40% 60% 100%

Watershed Impervious Cover

Center for Watershed Protection

The AWRA 2006 Conference on GIS & Water Resources IV

city of league city tx 2002 aerial photo
City of League City, TX2002 Aerial Photo

The AWRA 2006 Conference on GIS & Water Resources IV

slide9

100,000 new residents

The AWRA 2006 Conference on GIS & Water Resources IV

slide10

8.3 sq mi @ 12,000 pop / sq mi

100,000 new residents

The AWRA 2006 Conference on GIS & Water Resources IV

slide11

3.4 sq mi @ 30,000 pop / sq mi

100,000 new residents

The AWRA 2006 Conference on GIS & Water Resources IV

slide12

BOGOTA, COL160 Sq. mi. @ 40,000 pop/sq mi

League CityArea: 53 Sq. MilesPopulation: 50,000 (2000)

BogotaArea: 160 Sq. MilePopulation: 6,500,000 (2000)

The AWRA 2006 Conference on GIS & Water Resources IV

pollutant load calculations

Pollutant Load Calculations

The AWRA 2006 Conference on GIS & Water Resources IV

pollutant load model 1 input lulc vector format arcgis 9 model builder
Pollutant Load Model (1)Input: LULC Vector formatArcGIS 9 Model Builder

The AWRA 2006 Conference on GIS & Water Resources IV

pollutant load model 2 input lulc raster format arcgis 9 model builder
Pollutant Load Model (2)Input: LULC Raster formatArcGIS 9 Model Builder

The AWRA 2006 Conference on GIS & Water Resources IV

pollutant load model
Pollutant Load Model
  • Simplified, GIS-based application
  • Developed in ArcGIS 9.x (Model Builder)
  • Raster data model
  • Estimates total pollutant loads (NPS) in lbs / yr, for any user-specified pollutant
  • Based on the empirical Simple Method developed by Schueler (1987) for estimating pollutant export from small urban watersheds

The AWRA 2006 Conference on GIS & Water Resources IV

model input data
Geo-spatial Data

Watershed Boundaries

Land-Use/Land-Cover (LULC) - Vector or raster

Tabular Data

Event Mean Concentration (EMC) table - Text (csv)

Imperviousness factors table - Text (csv)

Model Input Data

The AWRA 2006 Conference on GIS & Water Resources IV

runoff coefficient rvu
Runoff Coefficient RVU *

RVU = 0.05 + (0.009 * IU)

Where:

  • RVU = Runoff Coefficient for land use type u, inches(runoff) / inches(rainfall)
  • IU = Percent Imperviousness

* Schueler 1987 (Washington D.C.)

The AWRA 2006 Conference on GIS & Water Resources IV

imp imperviousness values
IMP - Imperviousness values(%)

The AWRA 2006 Conference on GIS & Water Resources IV

total pollutant load lb yr
Total Pollutant Load (lb/yr) *

LP = Σ U (P * PJ* RVU * CU* AU * 2.72 / 12)

Where:

  • LP = Pollutant load, lb/yr
  • P = Precipitation, in/yr (assumed 46 for study area)
  • PJ = Ratio of storms producing runoff (default = 0.9)
  • RVU= Runoff Coefficient for land use type u, inches(runoff)/inches(rainfall)
  • CU = EMC for land use type u, mg/l
  • AU = Area of land use type u, in acres

* Schueler 1987 (Washington D.C.)

The AWRA 2006 Conference on GIS & Water Resources IV

event mean concentration emc
Event Mean Concentration (EMC)
  • An EMC is defined as the total constituent mass discharge divided by the total runoff volume (EPA 1983)
  • EMCs were developed by the EPA’s Nationwide Urban Runoff Program (NURP) (1983) to serve as a national measure of the magnitude of urban runoff, specifically pollutant loadings

The AWRA 2006 Conference on GIS & Water Resources IV

emc event mean concentration values for tss bod tn and tp in mg l houston area emc database
EMC - Event Mean Concentration values for TSS, BOD, TN and TP in mg/l(Houston Area EMC Database)

GBNEP – 15March 1992

The AWRA 2006 Conference on GIS & Water Resources IV

scenarios
Scenarios
  • No development
  • Full buildout at 4000 people/mi2 (Status Quo)
  • Same population as full buildout but at 12,000 people/mi2
  • Same population as full buildout but at 30,000 people/mi2
  • Full-buildout scenario at 4000 people/mi2 with the addition of best management practices (BMPs or “LID”) treating 20% of the area with a 65% effectiveness.

The AWRA 2006 Conference on GIS & Water Resources IV

results

Results

The AWRA 2006 Conference on GIS & Water Resources IV

pollutant loads comparison chart lbs year

Total Nitrogen

Total Phosphorus

Biochemical Oxygen Demand

Total Suspended Solids

Pollutant Loads - Comparison Chart(lbs / year)

The AWRA 2006 Conference on GIS & Water Resources IV

conclusions
Conclusions
  • The BMP scenario reduced pollutant loadings from the conventional-density, full-buildout scenario by 13-15%.
  • Holding the population constant and increasing density 3-fold to 12,000 people/mi2, decreased pollutant load overall by 50-75%.
  • Clearly, density should be considered as a BMP in its own right when considering development scenarios.
  • But the LID approach remains valid in the low density developments that are destined to remain with us.

The AWRA 2006 Conference on GIS & Water Resources IV

texas sea grant tx coop extension texas a m university
Texas Sea Grant / Tx. Coop. ExtensionTexas A&M University

www.urban-nature.org

Ricardo A Lopez M.S.

17000 El Camino Real, Suite 301

Houston, TX 77058

(281) 218 0570

E-mail: rilopez@tamu.edu

The AWRA 2006 Conference on GIS & Water Resources IV

appendix

Appendix

The AWRA 2006 Conference on GIS & Water Resources IV

what is urban sprawl
What is Urban Sprawl?
  • To spread out in a way that is not organized.www.inhs.uiuc.edu/chf/pub/virtualbird/glossary.html
  • Haphazard growth or outward extension of a city resulting from uncontrolled or poorly managed development.www.co.monterey.ca.us/gpu/glossary2.htm
  • Current development patterns, where rural land is converted to urban uses more quickly than needed to house new residents and support new businesses, and people become more dependent on automobiles. www.smartgrowth.org/bibliographies/greenlit_search/glossary.html

The AWRA 2006 Conference on GIS & Water Resources IV

basins
BASINS
  • BASINS: Better Assessment Science Integrating Point and Nonpoint Sources – U.S. Environmental Protection Agency (EPA)
    • Multipurpose environmental analysis system designed to perform watershed and water quality-based studies
    • Makes it possible to quickly assess large amounts of point source and non-point source data
    • Geographic Information System (GIS) tool developed as an extension to ArcView software program (Environmental System Research Institute – ESRI)

The AWRA 2006 Conference on GIS & Water Resources IV

watershed boundary
Watershed Boundary
  • Watersheds define the areas for which the pollutant loads are calculated
  • Available from local government agencies in most moderate- to high-density urban areas
  • May be derived using standard GIS or BASINS tools and the United States Geological Survey (USGS) Digital Elevation Model (DEM) data files (See appendix)
  • Dataset must have a code field containing unique identifiers for each watershed
  • Vector format, projected CS, same projection and datum, stored in meters (map units)

The AWRA 2006 Conference on GIS & Water Resources IV

lulc dataset
LULC Dataset
  • Defines Land-Use/Land-Cover types for the study area
  • Dataset must encompass the entire watershed
  • Essential for calculating the pollutant loads.
  • Available from local government agencies in most moderate- to high-density urban areas
  • If available in raster format (grid of cells), must be converted to vector format (polygon spatial features)

The AWRA 2006 Conference on GIS & Water Resources IV

imperviousness emc tables
Imperviousness & EMCTables

DATASET:imp_csv: Imperviousness table

Attributes:

LUCODE: Land use unique identifier

Imperv: Imperviousness factor (Percentage in percent

fraction format)

DATASET: emc_csv: Event mean concentrations table

Attributes:

LUCODE: Land use unique identifier

TN: Total Nitrogen (mg/l)

BOD: Biochemical Oxygen Demand (mg/l)

TSS: Total Suspended Solids (mg/l)

TP: Total Phosphorus (mg/l)

The AWRA 2006 Conference on GIS & Water Resources IV

software references
Software References

P-LOAD (ArcView extension to BASINS (Better Assessment Science Integrating Point & Nonpoint Sources – U.S. Environmental Protection Agency - EPA):

BASINS 3.1 Description:

http://www.epa.gov/waterscience/ftp/basins/system/BASINS3/areadb3.htm

Download BASINS 3.1 program and data:

http://www.epa.gov/waterscience/basins/index.html

The AWRA 2006 Conference on GIS & Water Resources IV