HYDROLOGY Impervious Surfaces

What percentage of catchments (small subwatersheds) within each major watershed have 4% or more impervious surface?

Why is this important for hydrology?

Impervious Cover

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Impervious surfaces are roads, buildings, parking lots, and other surfaces that water cannot easily penetrate.  In many natural systems, most rainfall infiltrates into the soil, and slowly moves to streams, springs, or aquifers.  Impervious surfaces prevent infiltration, lead to increased water flow on the surface of the land, and much more rapid flow into streams. Peak floods become higher and dry-season flows lower, as streams become “flashier” (Schoonover et al., 2005).

 (More detail)












Input Data


Calculating the index


Ranking and scoring


Overview of results


Interpreting the results


Relationship to other health components

Scientific literature support


Confidence in index

Future enhancements



perennial streams

Why is this important for hydrology? (more detail)

In many natural systems, most of the rainfall infiltrates into the soil, then slowly moves through saturated soil to streams, springs, or aquifers. This infiltration serves to buffer the speed of stream flow increases during large rain events, and meter out the subsurface flow during dry periods (Ziemer and Lisle, 1998; Poff et al., 2006).

In contrast, impervious surfaces prevent infiltration, lead to increased water flow on the surface of the land, and much more rapid flow into streams. Peak floods become higher and dry-season flows lower, as streams become “flashier” (Schoonover et al., 2005). High flows degrade stream channels by incision or downcutting, increase scour and increase the amount of sediment carried by the stream (White and Greer, 2006). High flows also lead to greater bank erosion, as well as increased upland gully erosion, particularly at pipe outlets. Organic and inorganic pollutants are deposited by vehicles and from the atmosphere onto impervious surfaces where surface runoff often carries them directly to streams. These various impacts lead to subsequent changes in the diversity and abundance of stream flora and fauna (Wang et al., 1997; Wang and Kahehl, 2003; Lyons 2006; Schiff and Benoit, 2007).


Calculating the index

At the major watershed scale, impervious cover was estimated using a classification of Landsat satellite images, circa 2001, analyzed in conjunction with higher-resolution satellite images, aerial photographs, and field visits (Yuan et al., 2005; Yuan and Bauer, 2006). These data were developed by the University of Minnesota Environmental Remote Sensing Center, and are available through the Twin Cities Metropolitan Council. The amount of impervious surface was quantified for the smallest catchment unit delineated, the Hydrologic Unit Code (HUC)-12, which range from 100-3000 acres in size. Those HUC-12 catchments with a level of impervious surfaces shown to impact water quality were identified. A threshold of 4% imperviousness was used because this is generally the level below which stream chemistry, biota, geomorphology, and other stream characteristics are indistinguishable from undisturbed streams (Paul and Meyer, 2001; Morse et al., 2003). All HUC-12 catchments that contained 4% or more impervious cover were identified. The percentage of HUC-12 catchments that met or exceed the 4% threshold within each major watershed was then calculated. The percentage of catchments meeting or exceeding the impervious threshold within a major watershed ranged from 0 to 73%.

At the catchment scale, impervious cover percentages were derived from the National Land Cover Data (NLCD) 2011 impervious data.  Open water areas were masked out of the analysis.  Zonal statistics (mean) values of impervious cover were calculated using the DNR Catchments as zonal features.  A threshold of 4% was also applied at the catchment scale. 


Ranking and scoring

At the watershed scale, the values were ranked into five, equal-interval classes on a 0 – 100 scale. The scores are the inverse of the percent of impacted catchments. The highest score (80 - 100) indicates the least impacted condition with little or no impervious surface present.

At the catchment scale, the score is also the inverse of the percent imperviousness, applying a 4% threshold to represent a score of 0.  Values of 0-4% imperviousness were scaled from 100 (highest score, 0% impervious surface) to 0 (lowest score, 4% or more impervious surface).



Overview of results

Impervious surface values are low for a large majority of the DNR Catchments in the state, with more than 85% of the catchments below the 4% threshold that characterizes detectable impacts. Not surprisingly, lowest scores (greatest amount of impervious surfaces) were concentrated in the Twin Cities metropolitan area, with a notable extension through the highway 10/25-52/94 corridor through St Cloud, and from there north through Brainerd, and west towards Wilmar. The lowest score (27) was found in the Minneapolis/St. Paul area watershed, indicating 73% of the DNR Catchments met or exceeded the 4% threshold for impacts from impervious surfaces. The DNR Catchments in and near Duluth and Rochester are also substantially affected, but the level of development in other regional population centers has also surpassed the threshold in some catchments, e.g., Fargo-Morehead, Bemidji, Grand Rapids, Virginia, Albert Lea, Alexandria, and Mankato. When averaged over the HUC-8 boundaries, these locally high impervious areas reduce scores only slightly, except in the metropolitan area.


Interpretation of results

 As expected, greatest proportions of impervious surfaces are in the primary population centers of the Twin Cities Metropolitan Area, with secondary levels found surrounding Duluth, Rochester, and St. Cloud, and transportation corridors connecting them.


Relationship to other health components 

Water quality

Increased impervious surface leads to increased inputs of organic and inorganic pollutants through overland transport, and increased bank and near-stream erosion due to increased peak flows. Turbidity and sediment concentrations increase during storm events.


Impervious surfaces change surface vs. sub-surface flows, and reduce biological connectivity in two ways. Vegetation is absent from the impervious surface areas, hence altering or eliminating migration corridors or near-stream refugia. In addition, impervious surfaces in riparian areas preclude trees and decrease shading, which may alter temperature regimes and connectivity of cool-stream habitat. In cases where groundwater is significantly impacted, lower summer flows may reduce stream connectivity or increase intermittency in streams.


Increased discharge, bank erosion, and sediment transport change stream geomorphology, largely due to increased erosion of streambanks and the streambed. Streams may become more incised (deeper).


Altered flow regimes and geomorphology may alter stream biota, favoring species that are mobile and species able to tolerate higher temperature, higher flow variability and peak flow volumes.  Impervious surfaces such as highways may  bisect important terrestrial habitat; interrupting and degrading large habitat patches, travel corridors and migration pathways.


Scientific literature support 

Mapping impervious surface from satellites has been shown to be accurate across a range of conditions and satellite platforms (Yuan and Bauer, 2007), with high accuracies reported at the watershed scale, and further work has shown high correlation between levels of satellite-estimated impervious surface and declines in stream quality (Slonecker et al., 2001; Snyder et al., 2005). High flows related to impervious areas result in bank erosion and can significantly change the mean bankfull depth and width of a stream (Goldstein et al. 2007). The width and depth of steam channels adjust in response to long-term changes in sediment supply and flow regime (Walsh et al. 2005). Increased imperviousness generally results in channel widening (Montgomery and Buffington 1998), regardless of the presence of a forested riparian buffer (Hesson et al. 2003).

Reduction in channel complexity and instream habitat is a universal symptom of urbanization. For example, McBride and Booth (2005) found that physical stream condition improved with decreasing urbanization for channel size, retention of large woody debris, bank stability, complexity of habitats, and embeddedness. Similarly, Shoonover et al. (2005) found that the streambed of urban channels eroded approximately 20 cm every 6 months, whereas streams from other land uses remained stable or redistributed and stored sediments within their cross-sections. This rapidly changing stream morphology was due to increased runoff and erosion encouraged by urban development. Streambank and streambed erosion reportedly occurs between 10-20% impervious cover (Gergel et al. 2002), however geomorphic changes, such as channel widening, can occur with as little as 2-10% impervious area (Booth and Jackson 1997).  Roaded areas accentuate surface erosion and have even greater erosion rates than previously forested clear-cut landscapes (Beechie et al. 2005). Roads act as conduits for sediment transport to nearby lakes and streams and their presence is a good indicator of suspended sediment in the water (Coats et al. 2008). Impervious surface areas have been shown to affect stream invertebrate and fish communities (Paul and Meyer, 2001; Morse et al., 2003; Wang et al., 2003), and increased impervious surface has been associated with decreased quality of hydrologic, chemical, and biotic characteristics of streams (Townsend et al., 1997; Weller et al., 1998; Wang et al., 2001).


Confidence in index

 This metric is strongly supported, resting on a well-developed theoretical foundation, with strong theoretical support in the technical processes of generating the base data and index and empirical tests of its application. There is a broad set of studies connecting changes in ecological, chemical, and physical characteristics of water bodies as a function of impervious surface, across the world, in North America, the upper Midwest, and within Minnesota.

Data quality in forming the metric is very high, with relatively recent, high resolution data used to develop a map of impervious surfaces.


Future enhancements

The approach used for creating catchment scale results from NLCD Impervious data (2011) has been successfully implemented.  The catchment scores will be "reupscaled" to create watershed scores based on the same data.  New NLCD data (released May 2014) allowed calculation of trends over time based on comparable 2001, 2006 and 2011 NLCD Imperviousness values. The calculation of impervious trend data over this time period has been completed and will be delivered through the online map for the catchment scale.  It is currently available as GIS data format by downloading WHAF data from the MNGeo Data Commons