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PART B OF THE SUPPORTING STATEMENT 

1. QUESTIONNAIRE OBJECTIVES, KEY VARIABLES, AND OTHER 

PRELIMINARIES 

1.1. Survey Objective 

The objective of the survey is to collect information to inform decisions regarding how the 

nation’s stormwater regulations should be strengthened and to support the technical and financial 

feasibility associated with such rulemaking, This Information Collection Request consists of 

several questionnaires to different target populations. EPA would send one questionnaire to 

NPDES permit authorities; two questionnaires (long or short) to owners or developers of new 

and redevelopment projects; two questionnaires to MS4s (one for those currently subject to 

EPA’s Phase I or Phase II stormwater regulations and another for those that are not); and a 

questionnaire to transportation MS4s. The primary objectives of the NPDES and MS4 

questionnaires are to gather information to characterize the current scope, components, and 

implementation of existing local and state stormwater programs and to estimate the burden and 

expenditures to comply with and enforce new requirements on stormwater discharges. The 

primary objectives of the owner/developer questionnaires are to: (1) characterize current building 

and real estate improvement projects including type, location, and size; (2) characterize the 

prevalence and type of stormwater controls implemented at new development and redevelopment 

sites to control long term stormwater discharges; and (3) characterize the operations and 

financial condition of owners and developers that could be subject to revised regulations. 

1.2. Key Variables 

The Owner/Developer Questionnaires request information on the following key variables: 

 Project characteristics (e.g., type, location, duration, size, land cover, discharge 

location and method of stormwater conveyance) 

 Long term stormwater best management practices and controls 

 Stormwater permit and management requirements 

 Firm, establishment, and project level financial information 

The MS4 and Transportation Questionnaires request information on: 

 MS4 characteristics (e.g., Phase I, traditional, State DOT) 

 Stormwater program components (e.g., outreach, recordkeeping, training) 

 Current MS4 stormwater permit and management requirements 

 Long term stormwater best management practices and controls 

 Budget and funding sources 

The NPDES Permitting Authority Questionnaire requests information on: 

 Current state stormwater program components 

 Scope and extent of municipal stormwater program 

 State stormwater municipal permit requirements 

 State industrial and construction stormwater permits and requirements 

 Budget 

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See Part A, Section 4(b) of this ICR for detailed information on the data items for the 

questionnaires. 

1.3. Terminology 

1.3.1. Statistical Definitions 

In describing the statistical approach for the survey, EPA has used several statistical terms. They 

are: 

 Element or Sampling unit is the individual reporting unit from which the 

questionnaire will collect information. For example, the MS4 questionnaire will be 

distributed to MS4s, and thus, each MS4 is an element or sampling unit. 

 Target population consists of every element of interest for the questionnaire. EPA 

will use the questionnaire data to make statistical inferences about the target 

population. Statistical inferences include national estimates of certain characteristics, 

such as estimated number of municipalities with MS4s. Because of the importance of 

the target population in reporting outcomes, a principal task in the development of a 

sample survey design is establishing a clear, concise description of the target 

population for each questionnaire. The definition should identify every element of the 

target population so that all non-population elements can be excluded. 

 Sample is the collective term for the sampling unit selected to receive the 

questionnaire. There are three types: 

o Census is a complete enumeration of all elements in the target population. 

Information about the target population are obtained directly from the reported 

values. In other words, statistical estimates are not necessary because information 

is provided for every element in the population. 

o Statistical sample is a statistically selected subset of the target population. In a 

statistical sample, the elements have a known probability of selection. Statistical 

inferences about the entire target population can be made from the sample data. 

o Judgment sample is an arbitrarily selected subset of the target population. In a 

judgment sample, the elements are selected based upon particular characteristics 

of interest. For example, EPA might select several MS4s because of unique and 

innovative stormwater control programs. Because the data are not statistically 

representative of the target population, they are not used to make statistical 

inferences about the entire population. Instead, they are used to provide 

information about particular aspects of interest. For example, a judgment sample 

might be used as the basis for costs of innovative control programs. In its surveys, 

EPA typically receives a few unsolicited (voluntary) completed questionnaires 

and they are treated as judgment samples. 

 Sample frame is a list or set of procedures for identifying all elements of a target 

population. Sample frames are essential to the quality of surveys because sample 

elements are drawn from them. Sample frames are typically created from one or more 

data sources. In addition to listing population elements, the resulting sample frame 

contains information that will be used to draw statistical samples. This information 

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includes addresses and stratification variables used to draw the samples. Usually, 

each target population is associated with a single sample frame, although EPA is 

considering the statistically valid option of dual frames as explained later in the 

section. 

1.3.2. Population-Related Definitions 

In Part B, EPA has adopted the terminology used by the U.S. Bureau of the Census in describing 

where people live. Except as noted, the following definitions are quotes from the Census Bureau 

publication Geographic Areas Reference Manual (1994, retrieved April 7, 2010 from 

www.census.gov/geo/www/garm.html,): 

 Counties: For most States, counties are the primary administrative divisions. There 

are exceptions, however; Louisiana has parishes, while Alaska has boroughs for the 

organized portion of its territory. Because a large part of Alaska is not in any 

organized borough, the State and the Census Bureau cooperatively have subdivided 

the unorganized portion of Alaska into census areas for the purposes of presenting 

statistical data. Three States (Maryland, Missouri, and Nevada) each have one city 

that is governmentally independent of county organization; Virginia currently has 41 

such cities. For both legal and statistical presentation purposes, these independent 

cities constitute primary administrative divisions of their States. Part of Yellowstone 

National Park in Montana is not within any county, therefore the Census Bureau 

treats it as the statistical equivalent of a county. The District of Columbia has no 

primary administrative divisions; the Census Bureau treats its entire area as the 

statistical equivalent of both a State and a county. (page 4-2)... Rhode Island’s 

counties exist only for the purpose of judicial administration and have no associated 

governmental structure. In 1960, Connecticut abolished its county governments and 

transferred their functions to the State government; however, the State retained the 

former counties for election and judicial purposes. Nevertheless, in both States, the 

Census Bureau continues to report many types of data for these county-type entities, 

in part to retain data comparability with earlier censuses and the data sets of other 

government agencies. (page 4-12) 

 Part B of this ICR supporting statement uses the term “county” to refer only to 

those counties with primary administrative functions. Consequently, it has 

excluded counties in Rhode Island and Connecticut. 

 Minor civil divisions (MCD): Minor civil divisions are the primary subcounty 

governmental or administrative units; they have legal boundaries and names as well 

as governmental functions or administrative purposes specified by State law. The 

most familiar types of MCDs are towns and townships, but there are many others ... 

In some situations, the Census Bureau must complete the coverage of subcounty units 

by creating additional entities called unorganized territories (UTs) that it treats as 

being statistically equivalent to MCDs. The Census Bureau has established UTs in 

certain MCD States to account for the part or parts of a county that are not within any 

MCD or MCD equivalent... (page 8-1) 

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 Part B of this ICR supporting statement uses the term “minor civil divisions” to 

refer only to those entities with governmental functions. 

 Incorporated places: Incorporated places are established under the authorization of 

the governments in each of the 50 States. Requirements for incorporation vary widely 

among the States; some States have few specific criteria, while others have 

established population thresholds and occasionally other conditions (for example, 

minimum land area, population density, and distance from other existing incorporated 

places) that must be met for incorporation (see Table 9-1). The Census Bureau 

recognizes incorporated places in all States except Hawaii... Puerto Rico and several 

of the Outlying Areas under United States jurisdiction (Guam, the Northern Mariana 

Islands, and Palau) also have no incorporated places... Different States recognize a 

variety of entities as incorporated places. Usually, the designations city, town, village, 

and borough are most frequent... (page 9-2).

 Part B of this ICR supporting statement uses the term “local governments” to 

refer to incorporated places and MCDs.

2. TARGET POPULATIONS, SAMPLE FRAMES, AND GENERAL 

SAMPLE DESIGNS 

This section describes the target populations, sample frames, and general sample designs for 

each of the questionnaires that EPA is considering in this Information Collection Request (ICR). 

Section 3 provides more information about the different statistical approaches that may be used 

in developing the sample design for each questionnaire. 

2.1. NPDES Authorities 

For the NPDES Authorities Questionnaire, the target population is the permitting authority for 

each state and territory. EPA remains the permitting authority in a few states, territories and on 

most tribal lands, but most states are authorized to implement the NPDES Stormwater Program 

and administer their own stormwater permitting programs. The questionnaire will be sent to the 

stormwater coordinator for each state/territory. 

EPA created its NPDES sample frame using contact lists collected from each EPA Region. The 

sample frame contains a mixture of state/territory contacts and EPA contacts, depending upon 

which entity is responsible for the NPDES permits. For each contact, the sample frame identifies 

the contact name, contact title, mailing address, telephone number, and email address. 

The sample design would be a census, because EPA intends to collect information about every 

state/territory. If any state/territory does not respond after several contacts, EPA staff will 

complete the questionnaire using publicly available information and best professional estimates. 

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2.2. Municipal Separate Stormwater Systems (MS4) 

Municipal Separate Stormwater Systems (MS4) are conveyances or systems of conveyances that 

are: 

 Owned by a state, city, town, village, or other public entity that discharges to waters 

of the U.S.; 

 Designed or used to collect or convey stormwater (including storm drains, pipes, 

ditches); 

 Not a combined sewer; and 

 Not part of a Publicly Owned Treatment Works (sewage treatment plant). 

MS4s may be classified in two categories: 

 Traditional which are MS4s operated by local governments; and 

 Non-traditional which are generally operated by non-local entities such as State 

transportation departments, universities, and hospitals. 

Further, MS4s may be: 

 Federally regulated MS4s if they are currently subject to EPA’s Phase I or Phase II 

stormwater requirements for MS4s; and 

 Non-federally regulated MS4s if they are not subject to EPA’s Phase I and Phase II 

requirements. However, if they discharge into local waterbodies, operators must 

obtain a state or federal permit and develop a stormwater management program. In 

other words, EPA is using the term “federally regulated” to refer only to the Phase I 

and Phase II requirements. 

The following sections describe EPA’s plans for collecting data from traditional federally 

regulated MS4s (2.2.1), non-federally regulated MS4s (2.2.2), transportation MS4s (2.2.3), and 

other non-traditional MS4s (2.2.4). Within each of the MS4 categories, EPA plans to collect 

information from sampling units within all States, all Territories and some Tribes. 

2.2.1. Traditional Federally Regulated MS4s 

For the Federally Regulated MS4 Questionnaire, the target population is the governing body 

(e.g., county, borough, tribal) for the traditional MS4s that are currently subject to EPA’s Phase I 

or Phase II stormwater requirements for MS4s. EPA created its Federally Regulated MS4 sample 

frame using contact lists collected from the stormwater coordinators from each state. For each 

MS4, the sample frame identifies the phase (I or II) and governing body for each MS4. EPA 

compared its contact information to Census Bureau lists of governing bodies: 8% are counties; 

64% incorporated places; and 24% are MCDs. Of the remaining records, 1.1% are from U.S. 

territories (primarily Puerto Rico), and 2.6% (175) are other miscellaneous areas or districts as 

shown in Table 2-1. Other information in the sample frame includes contact information, 

population, and land area. However, some MS4-relevant population and land information was 

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not provided, and will be estimated using information from publicly available sources produced 

by the Census Bureau. 

Table 2-1 Traditional MS4s: Other Areas and Districts 

Army Housing Community Property Owners Association 

City (HI) Public Utilities Commission 

Community Development District Sanitation & Flood Control District 

Community Services District Sanitation District 

Conservation & Reclamation District Sewer District 

Drainage District Sewer Services 

Flood Control & Water Conservation District Unincorporated 

Flood Control District Utility District 

Improvement District Valley 

Irrigation District Village (GA, MN, NV) 

Levee Improvement District Water Control District 

Metropolitan Agency Water Control/Improvement District 

Metropolitan District Water District 

Metropolitan Stormwater Authority Water Reclamation District 

Municipal Utility District Water Users Association 

Municipality Watershed District 

EPA plans to select a statistical sample that includes MS4s of different population sizes, land 

areas, population densities (surrogate for impervious surfaces),1

 and locations throughout the 

United States. Because the number of local governments varies considerably from state to state, 

EPA intends to control the selection procedure so that states with the most MS4s do not 

dominate the sample. The statistical sample design may be a cluster design (e.g., state is a 

cluster) or a stratified random design. (Section 3 provides more information about the design 

approaches.) 

EPA will consider whether the statistical sample should be supplemented by a judgment sample 

to obtain information from traditional MS4s with unique characteristics. 

2.2.2. Non-Federally Regulated MS4s 

To consider the potential impacts of expanding its municipal stormwater requirements to 

additional traditional MS4s, EPA developed a questionnaire for local governments that are not 

currently subject to Phase I or Phase II stormwater requirements for MS4s (i.e., “non-federally 

regulated MS4s”). The questionnaire is short with relatively few questions. The following 

paragraphs describe the selection approach that EPA is considering for the Non-Federally 

Regulated MS4 Questionnaire. 

 

1

 To verify that population densities is a suitable surrogate for impervious surfaces, EPA intends to compare the 

population densities to impervious surface maps. 

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As it intends for the Federally Regulated MS4 Questionnaire, EPA would obtain information 

from local governments that can reply on the behalf of its community (see discussion of Census 

terms in Section B.1.3.2). For this questionnaire, the target population definition would be local 

governments that met one of the following definitions, or a close variation: 

1. Areas that are not currently subject to Phase I or Phase II stormwater requirements. First, 

EPA would obtain a publicly available list of all local government entities, such as those 

maintained by the Census Bureau (see, for example, 2007 Governments Integrated 

Directory (GID) which is “The master list of all governments in the U.S.”2 From this list, 

EPA would extract the county, municipality, and town/township information for its list of 

local governments. Figure 2-1 provides a map with the number of local governments in 

each state. After identifying the local governments, EPA would exclude local 

governments: 

 Listed in its federally regulated MS4 sample frame. 

 Within counties with a county-level federally regulated MS4, because, presumably, 

the county MS4 would apply to any sub-government (e.g., city) without its own MS4. 

The resulting, smaller, list would be the sample frame of non-federally regulated MS4 entities. If 

EPA used this target population definition, it would obtain information about stormwater 

practices and financial data from a broad spectrum of non-federally regulated MS4s, located both 

in urban and rural locations. 

Figure 2-1: Number of Local Governments by State

 

2

 http://harvester.census.gov/gid/gid_07/options.html, retrieved April 7, 2010 

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2. Areas that, based upon the 2000 Census data, have the following characteristics:3 

a. Are outside urbanized area populations (i.e., would not have been subject to Phase 

I or Phase II stormwater requirements in 2000) 

b. Have a population greater than 10,000 

c. Have a population density of 1,000 people or more per square mile 

3. Areas that, based upon Census data, have been experiencing rapid growth in the last 

decade, and thus, are likely to meet the size requirements of federally regulated MS4s in 

the near future. To select incorporated areas experiencing such growth, EPA would 

probably use one of the following approaches or a similar approach: 

a. A calculator tool such as MABLE developed by the Missouri Data Census Center 

(http://mcdc2.missouri.edu/websas/geocorr2k.html). Because this tool analyzes 

2000 Census block and tract data, it would be possible to identify rapid growth in 

relatively small areas and link them with the appropriate governing body (e.g., 

unincorporated land near a city but governed by a county). 

b. Estimated growth using yearly population estimates from the Census Bureau (see, 

for example, http://www.census.gov/popest/datasets.html). 

c. Coding provided by other government agencies. For example, the Economic 

Research Service (ERS) of the United States Department of Agriculture (USDA) 

categorizes counties using Urban Influence Codes. ERS describes the codes on its 

website (http://ers.usda.gov/Briefing/Rurality/urbaninf/): 

The 2003 Urban Influence Codes divide the 3,141 counties, county 

equivalents, and independent cities in the United States into 12 groups. 

Metro counties are divided into two groups by the size of the metro area—

those in "large" areas with at least 1 million residents and those in "small" 

areas with fewer than 1 million residents. Nonmetro micropolitan counties 

are divided into three groups by their adjacency to metro areas—adjacent 

to a large metro area, adjacent to a small metro area, and not adjacent to a 

metro area. Nonmetro noncore counties are divided into seven groups by 

their adjacency to metro or micro areas and whether or not they have their 

"own town" of at least 2,500 residents. 

With any of these target populations, EPA would select a statistical sample that would contain 

areas with a mixture of population sizes, population densities, land areas, rural-urban continuum 

codes,4

 and geographic locations. To obtain a more balanced mixture of such characteristics, 

EPA might use information in the sample frame to stratify the target population. In addition, 

because the number of local governments can vary considerably from state to state (e.g., Nevada 

has 35; Indiana has 2832), EPA may use statistical approaches, such as cluster sampling, to 

ensure that states with few local governments are appropriately included in the statistical sample. 

In addition to the statistical sample, EPA might select a judgment sample to obtain specific 

 

3

 EPA previously summarized this information for each state and linked the information from 

http://cfpub.epa.gov/npdes/stormwater/urbanmaps.cfm. Using the Census sources directly, EPA has consolidated 

this information for all states. 

4

 The Economic Research Service of the United States Agriculture Department provides a 9-part codification that 

distinguishes metropolitan counties by size and nonmetropolitan counties by degree of urbanization and proximity to 

metro areas. (Description retrieved from http://www.ers.usda.gov/data/RuralUrbanContinuumcodes/, April 7, 2010.) 

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information about unique communities, unique stormwater practices, and/or other unique 

characteristics. 

2.2.3. Transportation MS4s 

For the Transportation MS4 Questionnaire, the target population is the transportation department 

in each state/territory that is currently subject to Phase I or Phase II stormwater requirements for 

MS4s. EPA also is considering an expansion of the target population definition to include similar 

county transportation departments and highway projects. 

EPA created its Transportation MS4 Questionnaire sample frame using contact lists collected 

from each EPA Region and information collected from state/territory websites. For each contact, 

the sample frame identifies the contact name, contact title, mailing address, telephone number, 

and email address. The sample design may be a census, because EPA intends to collect 

information about every state/territory. If any state/territory does not respond after several 

contacts, EPA staff will complete the questionnaire using publicly available information and best 

professional estimates. 

EPA also has a list of federally regulated MS4s that includes county transportation departments 

and highway projects. After evaluating the comments received on the second Federal Register 

Notice for the ICR, EPA will determine whether its transportation target population should be 

expanded to include these county transportation departments and highway projects. EPA also 

will consider whether the county DOTs should be limited to those specifically identified in 

EPA’s records with road projects, or expanded to all county DOTs. Depending on its intended 

use for the data, EPA then will consider whether it should select a statistical sample or a 

judgment sample. For either type of sample, EPA would include counties/projects from various 

locations throughout the United States. 

2.2.4. Other Non-Traditional MS4s (no questionnaire planned) 

Other than transportation MS4s discussed above, EPA has not included non-traditional MS4s in 

the survey effort. As shown in Table 2-2, non-traditional MS4s cover a range of different 

purposes. The summary was created from a list of non-traditional MS4s subject to Phase I or 

Phase II stormwater requirements identified by the stormwater coordinators from each state. For 

each non-traditional MS4, the list identifies the type of MS4 (e.g., hospital, university, federal) 

and contact information. Because the non-traditional MS4s vary in purpose, EPA is considering 

a data collection that will target only a few of the non-federal entities. The transportation MS4s 

will be addressed by the Transportation MS4 Questionnaire and federal entities through interagency consultations. 

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Table 2-2 Types of Non-Traditional MS4s 

Type of Non-Traditional MS4 

Number 

of MS4s 

Identified

Number of 

States With 

This Type 

Agricultural Association 1 1 

Airport 9 7 

Conservancy District 7 2 

Diking Improvement District 1 1 

Exposition Site 1 1 

Highway 130 40 

Hospital 18 8 

Metropark 7 3 

Metropolitan Park District 1 1 

Other 2 2 

Park District 2 1 

Public School District 93 5 

Satellite Tracking Station 1 1 

Stadium 4 3 

State 151 23 

Transit 8 3 

University 271 36 

Water and Sewer Authority 1 1 

2.3. Owners and Developers of New and Redevelopment Projects 

EPA has developed two versions of the Owner/Developer Questionnaire: short and long. The 

short and the long versions include the same basic questions, with additional, more detailed 

questions appearing on the long version. The two versions have the same target population, 

sample frame, and general sample design, and they are discussed in the following sections. 

2.3.1. Target Population 

 The target population is the same for both questionnaires. The target population is owners and 

developers of new and redevelopment projects. Owner is defined as the firm, individual, or 

institution for which the project is being built. Developer is defined as a person, business, or 

partnership that controls project design and/or land development activities associated with a 

project. In some cases, the developer may also be the owner. 

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2.3.2. Sample Frame 

 EPA is considering a statistical approach that will select statistical samples independently from 

two sample frames, or a dual frame. Traditionally, questionnaire surveys are conducted by taking 

a sample from a single sampling frame that lists all known members of a target population. In 

some cases, it may be necessary or useful to sample from multiple sample frames that, as a 

whole, cover the target population. This is the case when it is either difficult to create a single 

sample frame or when there are several different organizations that provide information about 

different subsets of the population. 

Specifically, for the Owner/Developer Questionnaire, EPA is evaluating the use of two data 

sources either to: 1) merge and create a single sample frame; or 2) select samples from each 

frame (dual frame approach). EPA’s preference is to combine the information into a single 

sample frame (#1), but the available information may not allow linkages of the same entities in 

each database to be easily and efficiently determined, making the second approach more 

practical. For example, a company may be listed with slightly different mailing addresses in each 

data source, and thus, appear to be separate entities. The advantage of the dual frame approach is 

that linkage only needs to occur for the members that are selected from each sample frame. This 

is the case because only those members that are selected will be assigned a survey weight for 

purposes of data analysis. The next two sections describe the two data sources. 

2.3.2.1 Dun and Bradstreet 

 “MarketPlace Pro,” formerly known as the Duns Market Identifiers (DMI) register, is 

maintained by Dun & Bradstreet (D&B) and covers the entire United States economy. DMI is a 

file produced by D&B, Inc., that contains basic company data, executive names and titles, 

mailing and location addresses, corporate linkages, employment and sales data on over 10 

million U.S. business establishment locations, including public, private, and government 

organizations. DMI is the only comprehensive publicly available database to provide coverage of 

business establishments. DMI is updated monthly and its coverage of the target population is 

relatively complete, but often contains out-of-date entries that can introduce inefficiencies in the 

sample design. 

DMI provides the option of choosing alternative organizational levels. DMI defines a 

headquarters as a business establishment that has branches or divisions reporting to it, and is 

financially responsible for those branches or divisions. The headquarters record provides the 

total number of employees for the company, including the employees in the branches. Another 

corporate family linkage relationship provided by DMI is the subsidiary to parent linkage. A 

subsidiary is a corporation with more than 50 percent of its capital stock owned by another 

corporation and will have a different legal business name from its parent company. 

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Based on both primary and secondary NAICS codes (secondary NAICS codes for a specific 

entity may include up to 5 NAICS codes other than primary), EPA obtained approximately 

740,000 records, screened for duplicates, from the D&B database. The following NAICS codes 

were used for selection: 

 236115 Single-family Builders, 236116 Multi-family Builders, 236117 Operative 

Builders, and any business with only a four digit NAICS code and listed as 2361 (i.e., 

all businesses in 2361 except 236118) 

 236210 Industrial Builders, 236220 (2362) Commercial and Institutional Builders 

 237210 (2372) Land Subdivision 

 237310 (2373) Highway, Street, and Bridge Construction 

 237990 (2379) Heavy and Civil Engineering Construction 

2.3.2.2 Reed Connect 

EPA also obtained detailed project and firm information from Reed Connect, a product of Reed 

Construction Data.5

 Reed Connect provides information about nonresidual and multifamily 

residential projects. Projects tend to be relatively large, requiring subcontractor support. Project 

data reported by Reed that are relevant to this analysis include project categorization, project 

location, company contact information, company categorization, project value, and several 

building characteristics (e.g., site size and constructed square footage). 

2.3.3. General Sample Design 

As explained in Section 2.6.2, EPA is considering a dual frame approach to the statistical sample

design for the owner/developer questionnaire. In this type of design, samples are statistically 

selected independently from each of two frames (i.e., Reed and D&B). Because the project-level 

information in the Reed database can better identify which firms meet the target population 

definition, EPA is considering selecting firms in the Reed database with a higher probability for 

the long questionnaire than those in the D&B database. It is possible that firms in the Reed 

database will only receive a long questionnaire if selected, instead of a short questionnaire. Firms 

in the D&B database will receive either the short or the long questionnaire. EPA also will 

consider whether the statistical sample from either sample frame should be supplemented by a 

judgment sample to obtain information from owners/developers with unique characteristics. 

Because some firms might have many projects, EPA is considering an approach to minimize the 

burden associated with reporting project-level information. Instead of reporting for an extended 

period or a specified number of projects, EPA is considering an alternative that will request each 

firm to report about its projects that were active on a specified date that EPA will randomly 

select for each questionnaire. In this manner, EPA would obtain statistically representative data 

about projects that could be extrapolated to the entire population. 

5 http://www.reedconstructiondata.com/construction-project-leads/reed-connect/ 

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3. CONSIDERATIONS IN SAMPLE SELECTION 

This section provides more information about the general sample designs identified in the 

previous section. It describes the precision targets and statistical approaches to selecting the 

sample. 

3.1. Precision 

Precision is the sampling error (variability) associated with estimates calculated from the sample 

data and extrapolated to the larger target population. One measure of precision is the width of the 

confidence interval for the estimate. Confidence intervals provide a range of values for a 

particular estimate that would be likely if the study were repeated an infinite number of times 

(because, by statistical theory, our sample is only one of many possible samples that could have 

been selected). Thus, when using 95 percent confidence intervals, 95 percent of such intervals 

would include the true value, if we could take an infinite number of samples. The precision of 

the estimates depends on both the sample design and the sample size, that is, the number of 

elements in the sample. 

Because EPA is developing a national rule, it is primarily concerned with the precision of the 

overall estimates. Consequently, in estimating the overall sample size, EPA intends to impose 

more stringent requirements for overall estimates than any subpopulation. First, EPA would 

assume that the sample (unadjusted for nonresponse) would be expected, with a certain 

confidence level (e.g., 90 or 95 percent), to yield sufficient data to estimate the value of an 

unknown proportion. EPA is considering a precision target of 90 percent which provides 

reasonable precision. If EPA were to use a more stringent precision target, such as 95 percent, it 

would need to collect more data which would increase the burden to the target populations. 

Once it determines the overall precision target, EPA then allocates the sample among the 

different strata. EPA typically requires that each stratum meet a basic level of precision. For 

example, if the binomial distribution were used, a stratum sample might be selected so that it 

would be expected, with 90 percent confidence, to yield sufficient data to estimate the value of 

an unknown proportion to within ±0.15 of its true value for the target population. 

3.2. Statistical Approaches 

This section describes the statistical approaches that EPA is considering for selecting samples for 

each questionnaire. Depending on the target population characteristics, it is possible that EPA 

may use a different sample design for each questionnaire. For each design, EPA may use the 

following approaches, either individually or in combination. 

In any sample design, if a stratum has a sample size of less than 10, EPA intends to sample all 

elements within the stratum. 

3.2.1. Binomial Distribution 

The binomial distribution is often used as the basis of sample designs, and can be used to 

estimate precision. The binomial distribution applies to situations where there are only two 

outcomes (yes or no) to a dichotomous question such as “Were stormwater post construction 

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controls that retain stormwater onsite implemented on this project?” The presence or absence of 

the attribute for a particular project is a dichotomous, or binary, variable. The binomial 

distribution models these data, based on the notion of obtaining national estimates of the 

percentage or proportion of projects in the target population (or a subset of the target population) 

that have a particular attribute. The binomial distribution also provides estimates of the variance 

that is used to calculate the confidence intervals. Because a proportion of 0.5 (or 50 percent) 

results in the largest possible variance for the binomial distribution, if EPA uses this approach, it 

would assume that the probability of one outcome would be 0.5 (e.g., stormwater postconstruction controls that retain stormwater onsite were implemented by 50 percent of the 

respondents). In other words, if the population value is any value other than 50 percent, the 

survey estimate will be more precise – in statistical expectation – than it would be if the 

population value is 50 percent. 

3.2.2. Stratified Sampling 

For a stratified sample design, stratification is performed by selecting one or more characteristics 

of interest provided in the sample frame and dividing the members of the population into the 

strata based on those characteristics. Stratified sampling consists of selecting a sample from 

within each stratum, then combining them to constitute the total sample. There are several 

benefits that result from stratifying the population, including: 

o Ensuring that the sample contains representatives from every stratum; 

o Improving the precision of parameter estimates; 

o Allowing important parameters to be estimated at the stratum level; and 

o Allowing certain subpopulations of particular interest to be sampled at a greater 

rate than others. 

Classifying the target population by all of the stratification variables leads to a number of cells 

that increases quickly by multiples of the strata categories. For a simple example, see Table 2-3 

with six total cells for two gender and three age classifications. 

Table 2-3 Simple Example of Two Stratification Variables 

Producing Six Cells 

Male Infant Male Child Male Adult 

Female Infant Female Child Female Adult 

Cells with small population sizes are statistically inefficient, so EPA intends to classify each of 

the stratification variables into relatively few categories. 

EPA is considering the following variables as stratification variables, but may consider others if 

appropriate: 

 Location information for all questionnaires: 

o Ecological regions: EPA is considering the Level 1 ecological regions established 

for North America 

(www.epa.gov/wed/pages/ecoregions/na_eco.htm#Level%20I). EPA also 

considered evapotranspiration, precipitation, and other environmental factors, but 

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considers the ecological regions to best categorize the United States for the 

purpose of the stormwater survey. To minimize the number of strata categories 

due to the number of regions, EPA intends to combine the smallest regions with 

another region in the same general location and/or climatic conditions. EPA also 

is considering a modification that would designate the Chesapeake Bay as a 

separate region to address Agency initiatives related to the Bay. 

o Population density: EPA is considering the use of population density as a 

surrogate for impervious surfaces. EPA intends to compare the results to recent 

research on the impact of impervious surfaces on watersheds.6

 

o Location Relative to Federally Regulated MS4s: EPA is considering several 

approaches to identifying areas that are adjacent to federally regulated MS4s 

and/or growing to a size that may require the MS4 to comply with Phase I or 

Phase II stormwater requirements. EPA is considering the following approaches: 

 Census Population Data: The Census Bureau provides information 

(www.census.gov/popest/cities/cities.html) about annual population 

estimates for states, counties, MCDs, and incorporated places for the years 

2000 through 2008. These estimates can be used to classify growth 

patterns. 

 Rural-Urban Continuum Codes: USDA/ERS has assigned one of nine 

Rural-Urban Continuum Codes to each U.S. county (or county 

equivalent). Metropolitan counties are assigned one of three codes 

according to the population of the associated metropolitan area in which 

they are located. Non-metropolitan counties are assigned one of six codes 

according to the size of their urban population and whether or not they are 

“adjacent” to a metropolitan area. (The term “adjacent” means that they 

are physically adjoining at least one metropolitan area, and at least two 

percent of their working population commutes to and from a central 

county within the adjoining metropolitan area.) 

 Urban Influence Codes: USDA/ERS also has assigned one of 12 Urban 

Influence Codes to counties (and county equivalents). Table 2-4 provides 

the definitions used for the codes. Metropolitan counties are assigned one 

of three codes. Among non-metropolitan counties, three codes are used to 

distinguish micropolitan counties by whether or not they are adjacent to a 

metropolitan area, and if so, if this metropolitan area has a population of at 

least one million. Seven additional codes are used to distinguish non-core 

counties by whether they are adjacent to a metropolitan area (and if so, 

whether this area has at least one million people), a micropolitan area, or 

neither.. 

 

6

 For example, “Watersheds at Risk to Increased Impervious Surface Cover in the Conterminous United States,” 

David M. Theobald, et al, Journal of Hydrologic Engineering, April 2009, pages 362-368, retrieved from 

http://www.whrc.org/resources/published_literature/pdf/Theobaldetal.JHydrolEng.09.pdf on April 22, 2010. 

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Table 2-4 USDA/ERS Definitions Used for Urban Influence Codes 

Metropolitan 

counties 

(1,089 counties) 

Counties located within a metropolitan area. 

(Metropolitan areas consist of a “central” county 

having at least one urbanized area1 with population at 

least 50,000, and adjoining counties for which at least 

25% of its population commutes to work in the central 

county, or at least 25% of its employment consists of 

workers from the central county.) 

Micropolitan 

counties 

(675 counties) 

Counties located within a micropolitan area, but not a 

metropolitan area. (Micropolitan areas consist of a 

central county having at least one urban cluster2

 of at 

least 10,000 but less than 50,000, and adjoining 

counties for which at least 25% of its population 

commutes to work in the central county, or at least 25% 

of its employment consists of workers from the central 

county.) 

Non-core counties 

(1,377 counties) 

Counties not located within a metropolitan or 

micropolitan area. 

1

 “Urbanized areas” are areas having an urban nucleus of at least 50,000 people and a core with population density of at least 

1,000 people per square mile. 

2

 “Urban clusters” are areas with populations between 2,500 and 50,000 people, and having the same population density 

requirements as urbanized areas. 

 Owner/Developer Questionnaires: 

o Industry Sector would be determined by the primary business as identified by the 

primary NAICS code. 

o Size would be determined by business volume such as sales or revenue. 

 MS4 Questionnaires: 

o Population 

o Land area 

o Phase I or Phase II (traditionally regulated MS4s only) 

3.2.3. Cluster Sampling 

A cluster sample is a probability sample in which each sampling unit is a collection, or cluster, of 

elements from the target population. For example, EPA might consider each state to be a cluster 

which is comprised of a collection of federally regulated MS4s. If EPA uses this design approach 

for any of its target population, it would send the questionnaire to a sample of elements within 

each cluster (e.g., a sample of federally regulated MS4s in each state). 

3.2.4. Probability Proportional to Size 

The probability proportional to size (PPS) sample design uses size as a factor in selecting the 

sample. In this design, the sample would include most of the largest elements and fewer of the 

smaller ones. Size can be defined in a number of different ways, such as population or revenue. 

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3.2.5. Spatial Sampling 

In simplest terms, spatial context is the information required to locate a sample point on the 

landscape, for example, latitude and longitude. For our purposes, there might be benefits to 

selecting elements in a manner that would cover the entire country and be selected from different 

watersheds. Although any random sample could accomplish this in a sense, there might be 

advantages to placing some spatial constraints on the sample so that the spatial distribution of the 

sample closely matches the spatial distribution of the population. Although EPA could 

approximate the latitude and longitude for element, other approaches such as systematic 

sampling within ecoregions may be simpler and easier to implement. 

3.2.6. Systematic Sampling 

Instead of stratifying by ecoregions, EPA is considering systematic sampling to incorporate some 

spatial context into the sample designs. Systematic sampling involves selecting every k

th facility 

where k is determined by the selection rate. For example, for federally regulated MS4s within 

each ecoregion, EPA might sort the MS4 sample frame by state name, and then zip code within 

each state, and finally randomly sort the MS4 names within zip code. The next step would be to 

draw a systematic sample from the sorted list for each ecoregion. In this manner, the sample 

would be reasonably diverse from a geographical perspective. 

4. SOURCES OF ERROR, INCLUDING NONRESPONSE 

In developing the final sample design, EPA will consider the precision targets for data collected 

from the target populations. EPA also will consider potential error that could be associated with 

estimates calculated from the collected data, due to sources of error associated with sampling, 

such as response rates, as well as non-sampling sources of error, such as processing error. The 

following sections describe approaches that EPA may consider to minimize error in data 

collected using the final design. 

4.1. Response Rates 

In developing the sample design, EPA will consider both unit (questionnaire) and item (question) 

nonresponse. Response rates compare the number of completed questionnaires to the number 

that were distributed. EPA expects that the unit response rate would be 80 percent or better for 

this mandatory survey effort. 

The survey would be conducted under the authority of the Clean Water Act. The cover letters 

and instructions would explain the legal authority, responsibility to respond, reasons for the 

questionnaire, and penalty for nonresponse. EPA would use reminder letters and/or telephone 

calls to remind respondents of the duty to respond under authority of the Clean Water Act. If 

possible, EPA would seek the endorsement of the major trade associations, which would be 

expected to increase the response rate from its members. EPA recognizes that some nonresponse 

is unavoidable, and in past survey efforts, EPA has waived the duty to respond in extreme and 

rare cases (e.g., natural disasters) which also might occur for this survey effort. To ensure that it 

receives enough completed questionnaires to meet its precision targets, EPA intends to adjust the 

sample sizes upward by 20 percent. In addition, EPA intends to further adjust the sample sizes 

upward to account for out-of-scope elements (including out-of-business). For example, a 

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particular county may administer all of the stormwater programs in its county, and thus, all of the 

local governments (towns, etc.) located in that county would be considered “out-of-scope” for 

the questionnaire because they do not administer any stormwater programs. 

Table 2-5 Sampled Populations: Out-of-Scope Assumptions 

Questionnaire Out-of-Scope 

Assumptions 

Federally 

Regulated and 

Transportation 

MS4 

0% 

Non-Federally 

Regulated MS4 25% 

Owner/Developer 

– Short 30% 

Owner/Developer 

– Long 15% 

Prior to distributing the detailed questionnaires (units), EPA would probably adjust the initial 

sample sizes to help ensure that the effective sample sizes (i.e., respondents) would be sufficient 

for precision requirements. For this reason, EPA would adjust the statistical sample size upwards 

to account for an estimated nonresponse rate of 20 percent. Nonresponse can result from a 

number of factors, including undeliverable addresses; out-of-business establishments for which 

nobody is available to respond; out-of-scope establishments that were incorrectly included in the 

sample frame; and refusals. EPA typically evaluates each of these components and adjusts its 

statistical estimates accordingly. 

In addition to increasing the initial sample size, EPA would strive to improve the response rate 

by sending reminder letters and/or telephone calls. Furthermore, after receiving the responses, 

EPA intends to adjust the questionnaire weights for any nonresponse. 

If the nonresponse rate is greater than 20 percent for any questionnaire, EPA will evaluate 

whether non-respondents appear to have different characteristics than respondents. EPA would 

examine these characteristics both for the entire industry and for subgroups in the analyses as 

recommended in the OMB guidance of January 20, 2006 

(www.whitehouse.gov/omb/inforeg/pmc_survey_guidance_2006.pdf). For any differences, EPA 

intends to determine the major causes, and to incorporate appropriate adjustments for bias. (Bias 

is the difference between the expected value of an estimate and the true value of a parameter or 

quantity being estimated. If the data collection process generates estimates that are consistently 

(or on average) above or below the true value, the data collection process is biased.) 

To minimize item nonresponse, EPA’s subject matter experts have worked closely with MS4s, 

owners/developers, and states to develop questions that would be easy to understand with clearly 

defined and familiar terms; are formatted in a logical sequence; and would request data that are 

readily available. In this manner, EPA expects to minimize inaccurate or incomplete response of 

the questions that can occur due to misunderstanding or misinterpretation of questions and the 

unintentional skipping of questions by respondents. Additionally, EPA would operate an e-mail 

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helpline and website to assist respondents with the questionnaires. If necessary, EPA would 

impute responses to key questions in our analyses. 

4.2. Processing Errors 

Processing errors can occur when questionnaire responses are coded, edited, and entered into the 

database. The design and implementation of the questionnaire database would employ a number 

of quality assurance techniques to reduce the frequency of such errors. These techniques may 

include the following: 

 Investigate whether web surveys are practical for any of the questionnaires, which 

would minimize transcription errors from paper copies 

 Double-entry keypunch verification on critical questions 

 Computerized comparison of selected responses to detect inconsistencies and illogical 

responses 

 Computerized analyses to screen for out-of-range and inconsistent numerical values 

 Computerized analyses to detect missing numerical data and missing units 

5. PRETESTS AND PILOT TESTS 

EPA does not intend to pre-test the questionnaire. For more than 30 years, EPA’s Engineering 

and Analysis Division has conducted surveys of numerous sectors to collect information to 

support regulation development activities in the effluent guidelines program. In past years, EPA 

has relied predominantly on active participation by trade groups in reviewing the questionnaires. 

In EPA’s experience, such collaboration generally tends to better reflect the sectors at large than 

pre-tests. For this reason, EPA considers additional review through the pre-test process to be 

unnecessary for this survey. 

6. COLLECTION METHODS AND FOLLOWUP 

Please See Part A, Section 5(b) of this ICR for this information. 

7. DATA PREPARATION AND ANALYSIS 

7.1. Data Processing Errors 

As explained in Section 6 of Part A of this support statement, EPA may distribute the 

questionnaires in paper form, electronic PDF, through a letter with a link to the questionnaire for 

completion online, or some combination. Upon receipt of completed questionnaires, EPA would 

download the electronic or web responses directly to a database or prepare written responses for 

data entry. Concurrently, EPA and its contractors would review the questionnaires for 

completeness and accuracy. As necessary, EPA would perform follow-up calls to clarify 

inconsistencies in responses. Once the data are entered into a database, numerous manual and 

electronic QA activities would likely be performed and the results would be provided to 

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engineering and economic staff for further resolution and documentation. This database would 

then be used to perform data analyses. 

7.2. Analysis 

The data collected through these questionnaires will provide EPA with information to 

characterize current building, transportation, and real estate improvement projects (i.e., new and 

redevelopment); long term stormwater controls and best management practices (BMPs) being 

installed at newly developed and redeveloped projects; state and local long term stormwater 

programs and requirements (including retrofit of existing development) and the areas covered by 

these requirements; the current capacity and expenditures by NPDES Permitting Authorities and 

local authorities to implement, enforce, and maintain long term stormwater programs and 

controls; and technical, financial, and environmental data needed to quantify the incremental 

pollutant removals, compliance costs, impacts, and benefits for various regulatory options that 

EPA might consider in this rulemaking. Ultimately, EPA would use the information to inform 

whether to expand its national stormwater program and how to best reduce long-term stormwater 

discharges from new and redevelopment and the built environment. 

The objectives of the each questionnaire would be achieved by the statistically-designed sample 

survey because the resulting inferences and analyses would be as statistically unbiased and as 

precise as is practicable. EPA would apply sample weights derived from the statistical sample 

design and adjust for nonresponse to the data during statistical analysis. Weighting the data 

would allow inferences to be made about the entire target population, including those that did not 

respond to the questionnaires. Another advantage is that weighted estimates would have smaller 

variances than unweighted estimates. EPA would use accepted statistical methods for survey 

statistics, such as those described in Sampling Techniques (Cochran, 1977) and Survey Sampling

(Kish, 1965). EPA would use the data from the judgment sample separately in a qualitative 

manner. 

See Part A, Section 2(b) of this Information Collection Request for a detailed discussion of the 

technical and economic analyses. 

8. REFERENCES 

Cochran, W.G. (1977). Sampling Techniques. New York: Wiley. 

Dillman, D. (2000). Mail and Internet Surveys: The Tailored Design Method. New York: 

Wiley. 

Israel, G. (1992) "Sampling Issues: Nonresponse," University of Florida, IFAS Extension 

Electronic Document. Available at: http://edis.ifas.ufl.edu/PD006. 

Kish, L. (1965). Survey Sampling. New York: Wiley.