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Artificial structures such as pavements covered with water tight materials

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.

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. 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.

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. [[File:Graph of Impervious Surfaces Coverage in the US. png|thumb|right|Graph of impervious surface coverage in the US.

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. 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. 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)). Southard (1986) 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) Granato (2010) Granato (2010) Detection of impervious areas using deep learning in conjunction with satellite images has emerged as a transformative method in remote sensing and environmental monitoring. Deep learning algorithms, particularly convolutional neural networks (CNNs), have revolutionized our capacity to identify and quantify impervious surfaces from high resolution satellite imagery. These models can automatically extract intricate spatial and spectral features, enabling them to discriminate between impervious and non impervious surfaces with exceptional accuracy.

Natural impervious areas are defined herein as land covers that can contribute a substantial amount of stormflow during small and large storms, but commonly are classified as pervious areas. provides land cover statistics that can be used as a qualitative measure of the prevalence of different land covers that may act as natural impervious areas. Open water may act as a natural impervious area if direct precipitation is routed through the channel network and arrives as stormflow at the site of interest. Wetlands may act as a natural impervious area during storms when groundwater discharge and saturation overland flow are a substantial proportion of stormflow. Barren ground in riparian areas may act as a natural impervious area during storms because these areas are a source of infiltration excess overland flows. Seemingly pervious areas that have been affected by development activities may act as
impervious areas and generate infiltration excess overland flows. These stormflows may occur even during storms that do not meet precipitation volume or intensity criteria to produce runoff based on nominal infiltration rates. Developed pervious areas may behave like impervious areas because development and subsequent use tends to compact soils and reduce infiltration rates. For example, Felton and Lull (1963) measured infiltration rates for forest soils and lawns to indicate a potential 80 percent reduction in infiltration as a result of development activities. Similarly, Taylor (1982) did infiltrometer tests in areas before and after suburban development and noted that topsoil alteration and compaction by construction activities reduced infiltration rates by more than 77 percent.