Development and Reliability of Standard Land Development

Models

Robert Pitt1, Celina Bochis2, and Geosyntec Project Team Members1Cudworth 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 InventorySheet Prepared for EachNeighborhood

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 RiseResidentialApartments

Open Space:Cemetery

Freeway

Light Industrial Area(Warehouses)

Scrap yard andStorage Area

InstitutionalSchool

Strip Commercial

Little Shades Creek WatershedAverage Land Cover DistributionHigh Density Residential (6 houses/acre)

TIA = 25%

DCIA = 15%

TR-55 = 52 - 65%

TIA = 20%

DCIA = 15%

TR-55 = 25-52%

TIA = 10%

DCIA = 6.7%

TR-55 = 20-25%

TIA = 61%

DCIA = 60%

TR-55 = 85%

TIA = 67%

DCIA = 64%

TR-55 = 85%

Little Shades Creek and Jefferson Co. Drainage Areas: DCIA by Land Use

Great Lakes

East Coast

South East

Central

North West

South West

National Stormwater Quality Database (NSQD) and Geographical Calibration Areas

17

 

LAND USE TOTAL EVENTS PERCENTAGE

Residential 2,979 35

Mixed Residential 1,245 15

Commercial 1,288 15

Mixed Commercial 525 6

Institutional 115 1

Industrial 887 10

Mixed Industrial 269 3

Freeway 763 9

Open Space 404 5

TOTAL 8,602 100

Number of Events and Land Use Coverage in NSQD ver. 3

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 1-4 are east half of country, zones 5-9 are western half of country. Zones 3 and 7 are the wettest zones.

  Commer. Indus. Instit. Open Space

Resid. Freeways/Highways

Total by Region

Central 4 2 4 1 5 3 19East Coast 3 1 1 1 2 3 11Great Lakes (the USGS/DNR files)

6 4 4 2 11 4 31

Northwest 2 1 1 1 3 3 11Southeast 7 2 3 5 8 4 29Southwest 5 1 1 1 2 3 13Total by Land Use

27 11 14 11 31 20 114

Number of Standard Land Use Files Used for Each Category

21

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:

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.