Impervious Surface: Water Quality Index

Framework / Assessment
Summary

Proportion of watershed covered by impenetrable materials such as roads, parking lots, and buildings preventing water from leaching directly into the soil. Water quality is affected by impervious surface development in watersheds. The more impervious surfaces are developed, the greater the chance that water quality will be degraded.

General Information
Sustainability Goal

Goal 4. Improve quality of drinking water, irrigation water, and in-stream flows to protect human and environmental health. Goal 5. Protect and enhance environmental conditions by improving watershed, floodplain, and aquatic condition and processes.

Domain

Water Quality = The chemical and physical quality of water to meet ecosystem and drinking water standards and requirements. Ecosystem Health = The condition of natural system, including terrestrial systems interacting with aquatic systems through runoff pathways

What is it?

Impervious surface is a measure of land cover. Water quality is affected by impervious surface development in watersheds. The more impervious surfaces are developed, the greater the chance that water quality will be degraded. It is derived from the National Land Cover Database using satellite imagery primarily from Landsat. Images are analyzed to reveal 16 land cover classes, including: water, developed, barren, forest, shrubland, herbaceous, planted/cultivated, and wetlands. Each land cover class is assigned a value for percent imperviousness based on a 30*30km resolution raster data set (USGS National Landcover Database). It is important to note that the percent impervious surface measurement is an estimate of imperviousness and not a direct measurement.

This indicator covers a process category and serves as a potential measure of impact of development on water quality.

Why is it important?

Impervious cover is a relatively easily measured metric that is valuable for watershed planners, storm water engineers, water quality regulators, economists, and stream ecologists (Schueler et al. 2009). It also acts as a measure of development and growth.  Direct impacts of impervious surface include changes in land cover, hydrology, geomorphology, and water quality. Indirectly impervious surface impacts stream ecology, species richness, the economy, policy, and social well-being and human health. Bellucci (2007) cites multiple papers documenting the influence of land cover change on stream health, biotic integrity, and runoff; stating that increases in urbanization results in stormwater runoff that contributes to "flashier hydrograph, elevated concentrations of pollutants transported from impervious surfaces to streams, altered channel morphology, and reduced biotic integrity with dominance of more tolerant species."

What can Influence or Stress Condition?

This indicator has a direct connection between stress and percent impervious surface. Therefore, development or conversion of land from "natural" to developed land is the only thing that could alter this condition. Furthermore, as stated previously, changes in land cover can indirectly affect geomorphology, water quality, and ecosystem health in terms of native species richness.

Climate change may influence the resulting scores (RGA, WQI, Etc) from this indicator by altering the timing and amount of precipitation as well as drought. Climate predictions result from a combination of scenarios and climate models that integrate estimates of greenhouse gas emissions and how the climate system will respond to these emissions. Therefore, variation within the predictions may result in different policy implications and actions. Furthermore, we are likely to see variation in the location, amount, and timing of precipitation rather than homogenous responses across the globe.

Basis of Calculation and Use

For the purposes of our analyses, we used impervious surface spatial data from the years 2001 and 2006. Spatial data for 1992 exists, but represents land cover classes, not impervious surface classifications. Methods exist for assigning impervious surface values for these land cover classes, but are location and scale dependent (e.g. Sacramento, San Diego river) and differ in accuracy (McMahon 2007).

One area of interest in the impervious surface indicator is the degree and pace of change over time. Currently data for percent impervious surface is available for 2001 and 2006, with the following important note for comparison between years from the NLCD website: "NLCD2001 Version 2.0 products must be used in any comparison of NLCD2001 and NLCD2006 data products." Furthermore, with regards to analysis using land cover and estimates in impervious surfaces, McMahon (2007) states the importance of resolution in data for informing landcover classes and developing models for impervious surfaces.

Target or Desired Condition

There are many estimates for a threshold of percent impervious surface, beyond which, measurable damage to stream systems is endured. Wang et al. (2003) estimate that between 6-11% impervious area, major changes in stream fish could occur. Fitzgerald et al. (2012) estimate increased sensitivity of stream ecosystems at between 5-10% impervious surface. Hilderbrand et al. (2010) suggest that within their study area, once percent impervious area reaches 15% a loss of nearly 60% of benthic macroinvertebrate taxa could occur. Schiff et al. (2007) calculate that above a critical level of 5% impervious surface, stream health declines. However, Allan (2004) makes the argument that although there is strong influence on stream health and land cover change, direct associations are complex and depend on anthropogenic and natural gradients, scale, nonlinear responses, and the difficulty in parsing out impacts from today and the past.

Thus, modeled predictions that utilize actual monitoring data for regions of interest, the stream indicators of greatest concern, the main land cover type , and represent a range of possible outcomes may be more realistic (Schueler et al. 2009). Furthermore, Schueler et al. (2009) mention several caveats regarding the use of impervious surface as an indicator for stream hydrology and health. These caveats include: consideration of watershed scale, problems with forming relationships between impervious surface and watersheds with major point source pollutant discharge or dams, importance in grouping watersheds within the same physiographic regions, and caution when applying models based on impervious surface when management practices are poor, especially in areas of low impervious cover (Schueler et al. 2009).