Impervious surfaces are mainly artificial structures—such as pavements (roads, sidewalks, driveways and parking lots, as well as industrial areas such as airports, ports and logistics and distribution centres, all of which use considerable paved areas) that are covered by water-resistant materials such as asphalt, concrete, brick, stone—and rooftops. Soils compacted by urban development are also highly impervious.
Environmental effects Impervious surfaces are an environmental concern because their construction initiates a chain of events that modifies urban air and water resources:
The pavement materials seal the soil surface, eliminating rainwater infiltration and natural groundwater recharge. This can cause urban flooding. An article in the Seattle Times states that "while urban areas cover only 3 percent of the U.S., it is estimated that their runoff is the primary source of pollution in 13 percent of rivers, 18 percent of lakes and 32 percent of estuaries."Cappiello, Dina. "Report: EPA Failing to stop Sprawl Runoff." Seattle Times, 16 October 2008 Some of these pollutants include excess nutrients from fertilizers; pathogens; pet waste; gasoline, motor oil and heavy metals from vehicles; high sediment loads from stream bed erosion and construction sites; and waste such as cigarette butts, 6-pack holders and plastic bags carried by surges of stormwater. In some cities, the flood waters get into combined sewers, causing them to overflow, flushing their raw sewage into streams. Polluted runoff can have many negative effects on fish, animals, plants and people.
Impervious surfaces collect solar heat in their dense mass. When the heat is released, it raises air temperatures, producing urban "heat islands", and increasing energy consumption in buildings. The warm runoff from impervious surfaces reduces dissolved oxygen in stream water, making life difficult in aquatic ecosystems. Impervious pavements deprive tree roots of aeration, eliminating the "urban forest" and the canopy shade that would otherwise moderate urban climate. Because impervious surfaces displace living vegetation, they reduce ecological productivity, and interrupt atmospheric carbon cycling.
The total coverage by impervious surfaces in an area, such as a municipality or a drainage basin, is usually expressed as a percentage of the total land area. The coverage increases with rising urbanization. In rural areas, impervious cover may only be one or two percent. In residential areas, coverage increases from about 10 percent in low-density subdivisions to over 50 percent in multifamily communities. In industrial and commercial areas, coverage rises above 70 percent. In regional shopping centers and dense urban areas, it is over 90 percent. In the contiguous 48 states of the US, urban impervious cover adds up to . Development adds annually. Typically, two-thirds of the cover is pavements and one-third is building roofs.Schueler, Thomas R. "The Importance of Imperviousness." Reprinted in The Practice of Watershed Protection. 2000. Center for Watershed Protection. Ellicott City, MD.
Mitigation of environmental impacts
Impervious surface coverage can be limited by restricting land use density (such as a number of homes per acre in a subdivision), but this approach causes land elsewhere (outside the subdivision) to be developed, to accommodate the growing population. (See urban sprawl.) Alternatively, urban structures can be built differently to make them function more like naturally pervious soils; examples of such alternative structures are porous pavements, green roofs and infiltration basins.
Rainwater from impervious surfaces can be collected in rainwater tanks and used in place of main water. The island of Catalina located West of the Port of Long Beach has put extensive effort into capturing rainfall to minimize the cost of transportation from the mainland.
Partly in response to recent criticism by municipalities, a number of concrete manufacturers such as CEMEX and Quikrete have begun producing permeable materials which partly mitigate the environmental impact of conventional impervious concrete. These new materials are composed of various combinations of naturally derived solids including fine to coarse-grained rocks and minerals, organic matter (including living organisms), ice, weathered rock and precipitates, liquids (primarily water solutions), and gases.Rosenberg, Carter, 2006, Anti-Impervious Surfaces: The Ecological Impact of Concrete Alternatives, Troy, NY: Luminopf Press. The COVID-19 pandemic gave birth to proposals for radical change in the organisation of the city, being the drastic reduction of the presence of impermeable surfaces and the recovery of the permeability of the soil one of the elements of the Manifesto for the Reorganisation of the city, published in Barcelona by architecture and urban theorist Massimo Paolini and signed by 160 academics and 350 architects.
Percentage imperviousness
The percentage imperviousness, commonly referred to as PIMP in calculations, is an important factor when considering drainage of water. It is calculated by measuring the percentage of a catchment area which is made up of impervious surfaces such as roads, roofs and other paved surfaces. An estimation of PIMP is given by PIMP = 6.4J^0.5 where J is the number of dwellings per hectare (Butler and Davies 2000). For example, woodland has a PIMP value of 10%, whereas dense commercial areas have a PIMP value of 100%. This variable is used in the Flood Estimation Handbook.
Homer and others (2007) indicate that about 76 percent of the conterminous United States is classified as having less than 1 percent impervious cover, 11 percent with impervious cover of 1 to 10 percent, 4 percent with an estimated impervious cover of 11 to 20 percent, 4.4 percent with an estimated impervious cover of 21 to 40 percent, and about 4.4 percent with an estimated impervious cover greater than 40 percent.Homer, C., Dewitz, J., Fry, J., Coan, M., Hossain, N., Larson, C., Herold, N., McKerrow, A., VanDriel, J.N., and Wickham, J., 2007, Completion of the 2001 National land cover database for the conterminous United States: Photogrammetric Engineering and Remote Sensing, v. 73, no. 4, p. 337-341.Granato, G.E., 2010, Overview of Methods Used to Estimate Imperviousness in a Drainage Basin Appendix 6 in Methods for development of planning-level estimates of stormflow at unmonitored sites in the conterminous United States: Federal Highway Administration, FHWA-HEP-09-005 "Available on-line."
Total impervious area The total impervious area (TIA), commonly referred to as impervious cover (IC) in calculations, can be expressed as a fraction (from zero to one) or a percentage. There are many methods for estimating TIA, including the use of the National Land Cover Data Set (NLCD) with a Geographic information system (GIS), land-use categories with categorical TIA estimates, a generalized percent developed area, and relations between population density and TIA.
The U.S. NLCD impervious surface data set may provide a high-quality nationally consistent land cover data set in a GIS-ready format that can be used to estimate TIA value. The NLCD consistently quantifies the percent anthropogenic TIA for the NLCD at a 30-meter (a 900 m2) pixel resolution throughout the Nation. Within the data set, each pixel is quantified as having a TIA value that ranges from 0 to 100 percent. TIA estimates made with the NLCD impervious surface data set represent an aggregated TIA value for each pixel rather than a TIA value for an individual impervious feature. For example, a two lane road in a grassy field has a TIA value of 100 percent, but the pixel containing the road would have a TIA value of 26 percent. If the road (equally) straddles the boundary of two pixels, each pixel would have a TIA value of 13 percent. The Data-quality analysis of the NLCD 2001 data set with manually delimited TIA sample areas indicates that the average error of predicted versus actual TIA may range from 8.8 to 11.4 percent.
TIA estimates from land use are made by identifying land use categories for large blocks of land, summing the total area of each category, and multiplying each area by a characteristic TIA coefficient. Land use categories commonly are used to estimate TIA because areas with a common land use can be identified from field studies, from maps, from planning and zoning information, and from remote imagery. Land use coefficient methods commonly are used because planning and zoning maps that identify similar areas are, increasingly, available in GIS formats. Also, land use methods are selected to estimate potential effects of future development on TIA with planning maps that quantify projected changes in land use.Cappiella, K., and Brown, K., 2001, Land use and impervious cover in the Chesapeake Bay region: Watershed Protection Techniques, v. 3, no. 4, p. 835-840. There are substantial differences in actual and estimated TIA estimates from different studies in the literature. Terms like low density and high density may differ in different areas.Hitt, K.J., 1994, Refining 1970's land use data with 1990 population data to indicate new residential development: U.S. Geological Survey Water-Resources Investigations Report 94-4250, 15 p. A residential density of one-half acre per house may be classified as high density in a rural area, medium density in a suburban area, and low density in an urban area. Granato (2010) provides a table with TIA values for different land-use categories from 30 studies in the literature.
The percent developed area (PDA) is commonly used to estimate TIA manually by using maps. The Multi-Resolution Land Characteristics Consortium (MRLCC) defines a developed area as being covered by at least 30 percent of constructed materialsU.S. Environmental Protection Agency, 2009, National Land Cover Data (NLCD) Classification Schemes "Available on-line"). Southard (1986)Southard, R.E., 1986, An alternative basin characteristic for use in estimating impervious area in urban Missouri basins: U.S. Geological Survey Water-Resources Investigations Report 86-4362, 21 p. defined non-developed areas as natural, agricultural, or scattered residential development. He developed a regression equation to predict TIA using percent developed area (table 6–1). He developed his equation using logarithmic power function with data from 23 basins in Missouri. He noted that this method was advantageous because large basins could quickly be delineated and TIA estimated manually from available maps. Granato (2010) developed a regression equation by using data from 262 stream basins in 10 metropolitan areas of the conterminous United States with drainage areas ranging from 0.35 to 216 square miles and PDA values ranging from 0.16 to 99.06 percent.