Development and Reliability of
Standard Land Development
Models
Robert Pitt1, Celina Bochis2, and Geosyntec Project Team Members
1Cudworth Professor of Urban Water Systems, University of Alabama, Tuscaloosa
2Former Postdoctoral Researcher, University of Alabama, Tuscaloosa
Land Development Surveys
• Land development characteristics for different land
uses have been collected for many locations
throughout the US as part of stormwater research
projects, stormwater management plans, and model
calibration efforts.
• This information was collated and statistically
evaluated to identify similarities and trends in the
major land use features for different locations in the
country as part of this EPA Standards Development
Process.
• WinSLAMM used this information along with data from
the National Stormwater Quality Database (NSQD) to
develop regional calibrations and to evaluate different
stormwater management alternatives.
Example Field Data Collection for
Development Characteristics for Different
Land Uses in an Area
• Delineation of the watersheds and neighborhoods
• Single land use neighborhood surveys: 6 to 12 per study
area land use to determine the variability of the
development characteristics
• Site Inventory has 2 parts:
– Field data collection
– Aerial photographic measurements of different land
covers
• Each site has at least two photographs taken (now
supplemented with Google Street View):
– one as a general view
– one as a close-up of the street texture and gutter/curb
interface
Field Inventory
Sheet Prepared for Each
Neighborhood
When in the field we look for:
1. Roof types (flat or
pitched) and material
(now supplemented by
small drone cameras)
2. Roof connections
(connected,
disconnected)
3. Pavement conditions
and texture (smooth,
intermediate, rough)
4. Storm drainage type
(grass swales, curb and
gutters, and roof drains)
Village Creek Site (SWMA 002)
Birmingham, AL
Example of 1 m monochromatic aerial photograph (USGS photo)
Example of high resolution color satellite image (Google)
General Land Use Categories (modified based
on local definitions and project needs)
• Residential (separated by development age and veg type)
– High, medium, low density
– Apartments, multi- family units
• Commercial
– Strip commercial, shopping centers
– Office parks, downtown business district
• Industrial
– Manufacturing (power plants, steel mills, cement plants)
– Non-manufacturing (warehouses)
– Medium and Heavy Industrial (lumber yards, junk and auto salvage
yards, storage areas)
• Institutional
– Schools, churches, hospitals, nursing homes
• Open Space
– Parks, cemeteries, golf courses
– Vacant spaces, undeveloped areas
• Freeway
High Density Residential Area, with and without extensive
vegetation
High Rise
Residential
Apartments
Open
Space:
Cemetery
Freeway
Scrap yard and
Storage Area
Light Industrial Area
(Warehouses)
Institutional
School
Strip
Commercial
Little Shades Creek Watershed
Average Land Cover Distribution
High Density Residential (6 houses/acre)
TIA = 25%
DCIA = 15%
TR-55 = 52 - 65%
TIA = 20%
TIA = 61%
DCIA = 15%
DCIA = 60%
TR-55 = 25-52%
TR-55 = 85%
TIA = 10%
DCIA = 6.7%
TR-55 = 20-25%
TIA = 67%
DCIA = 64%
TR-55 = 85%
Little Shades Creek and Jefferson Co.
Drainage Areas: DCIA by Land Use
National Stormwater Quality Database (NSQD)
and Geographical Calibration Areas
North
West
Great Lakes
South
West
East
Coast
Central
South East
17
Number of Events and Land Use Coverage in NSQD ver. 3
TOTAL
EVENTS
PERCENTAGE
Residential
2,979
35
Mixed Residential
Commercial
Mixed Commercial
Institutional
1,245
1,288
525
115
15
15
6
1
887
269
763
10
3
9
404
8,602
5
100
LAND USE
Industrial
Mixed Industrial
Freeway
Open Space
TOTAL
NSQD Data: These grouped
box-whisker plots sort all of the
data by land use. Kruskal-Wallis
analyses indicate that all
constituents have at least one
significantly different category
from the others. Heavy metal
differences are most obvious.
NSQD data: Residential
area concentrations grouped
by EPA rain zones. Zones 14 are east half of country,
zones 5-9 are western half
of country. Zones 3 and 7
are the wettest zones.
Many study areas throughout the US had detailed land
development information and concurrent stormwater
quality data and were organized by geographical area and
land use:
Number of Standard Land Use Files Used for Each Category
Central
East Coast
Great Lakes
(the
USGS/DNR
files)
Northwest
Southeast
Southwest
Total by Land
Use
Commer. Indus. Instit.
Open
Space
Resid.
Freeways/ Total by
Highways Region
4
3
6
2
1
4
4
1
4
1
1
2
5
2
11
3
3
4
19
11
31
2
7
5
27
1
2
1
11
1
3
1
14
1
5
1
11
3
8
2
31
3
4
3
20
11
29
13
11421
22
Rainfall Distribution Modeling for
Different Locations and Land Uses
Can be used to establish treatment goals
for a targeted annual runoff objective:
- About 90% of the annual runoff
corresponds to a rain depth from about
1.5 to 3.5 inches
- About 70% of the annual runoff
corresponds to a rain depth from about
0.75 to 2 inches
Source Area Modeling Identifies Major Sources of Flows and Pollutants for
Critical Events:
- As expected, directly connected impervious areas are the major runoff sources for
up to about 2 inch rains in residential areas, but then landscaped areas are more
important. They are always important in most commercial and industrial areas.
ArcGIS and WinSLAMM
• Typically user might use GIS to develop source
areas and then manually enter values into the
WinSLAMM interface
• Developing databases and tools to automate
that process
• ArcSLAMM tool will produce WinSLAMM
compliant databases per drainage or catchment
area which can then be run in batch mode
through WinSLAMM
Conclusions
• Standard land use information and associated
development characteristics affect stormwater
quality and quantity.
• Surface coverage of different elements in each
land use do not vary as much throughout the
country as does random variations in directly
connected imperviousness.
• Obtaining regional standard land use
information is a good investment, but it requires
field work and evaluation of aerial imaging.
Conclusions (cont.)
• Historical tools used to automate the
collection of this information was found to
result in significant errors.
• Newer high resolution tools (such as 6
inch LiDAR, light detection and ranging)
has been shown to be quite effective in the
collection of most of this data, but field
surveys are still needed for supplemental
information.