How To Use Land Cover Data as a Water Quality Indicator

Data Used

The web-based maps included here were created based on the analysis of NOAA’s 2010 Regional Coastal Change Analysis Program (C-CAP) land cover data.

Learn more about C-CAP Regional Land Cover
Review how data were analyzed to create these maps

  1. Identify Potential Impacts from Impervious Surfaces

    Impervious surfaces and other forms of development reduce the infiltration of water into the ground. Impervious surfaces often contribute to higher storm water runoff, greater sediment yields, and increased pollutant loads, all of which can degrade water quality. Sensitive streams, for instance, can be impacted by as little as 5 to 10 percent impervious surface area, with greater impairments expected when rates exceed 20 to 25 percent.

  2. Identify Potential Effects of Forest Cover

    Forest cover provides interception, absorption, and natural pollutant processing for rainfall and surface water. Urban trees serve as an inexpensive storm water practice, lowering water treatment costs. In areas with lower levels of development, forest cover is often the best indicator of watershed health. Watersheds that are over 65% forested have been found to be protective of a stream’s biological community. A goal of 40% forest cover is recommended in urban areas.

  3. Examine the Relationship of Forest Cover to Impervious Area

    Watersheds are composed of groundwater recharge and storm water runoff generation areas. Forests and impervious surfaces represent the two ends of that continuum, with other land covers falling in between. In general, where impervious surfaces are limited in size and scope, forest cover exerts the most influence on water quality. Once impervious surfaces exceed a threshold, they are the determining factor. Areas noted as sensitive should be explored further in subsequent steps.

  4. Identify Whether Developed Grasses Could be a Factor

    Along with buildings and roads, open urban areas such as parks and lawns factor into the development footprint. While denser development may pose severe localized problems, lower density development spread across a larger area creates more infrastructure costs and impervious cover per capita. Areas of turf and grass can also exhibit the highest concentrations of pollutants such as pesticides and nutrients, but can be pervious and a sink for nutrients when properly managed.

  5. Examine Riparian Buffers

    Riparian buffers can be an important component for stream stability, pollutant removal, and stream health maintenance. Ensuring the integrity of these features, and restoring previous buffers, can have a positive impact on water quality. While a healthy riparian zone cannot totally offset development impacts, riparian buffers can be effective when used in combination with other management strategies.

    What is in your area’s riparian buffers? This map highlights the general land cover within the riparian buffers for each watershed shown. Due to their proximity to water features, these buffers can be very influential in terms of water quality. In addition to runoff from development, agricultural lands are primary sources of nutrient inputs nationwide.

  6. Examine Other Potential Water Quality Factors

    Water quality is determined by many physical, chemical, and biological factors. Land cover data represent only one piece of the puzzle. Nonpoint source pollutants are common and pervasive water quality stressors. These pollutants include sediments, metals, and nutrients. By definition these pollutants can’t be attributed to any specific point location, and due to their distributed nature are quite difficult to manage and mitigate.

    Several investigative tools are available to help identify nonpoint-source pollutants. OpenNSPECT is one such tool. This tool uses land cover data (as well as other data) and helps users analyze potential water quality impacts from past changes, current decisions, and future scenarios.