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Figure 2: Channel stability as a function of imperviousness <br />(Booth and Relnelt, 1993) <br />z.5 <br />z.n <br />t.5 <br />1.0 <br />0.5 <br />0.0 <br />o °~; <br />~~ <br />o <br />O STAB LE CI[ANNELS <br />NN(LS <br />° <br />a:,p <br />a; m <br />X UNSTABLE CHA <br />° L1.ROE~I.AKE SUBCATCItMENTS <br />O E'er <br />a~ o <br />°~ <br />: <br />° <br />CENL'R.~tLLYSTA©LE CHANNELS <br />$ o: <br />C>~° p ° 1 0-yr lorested dtscharpe <br />a~x:,~ <br />~ ~ o: ° 2-yr current dtscharpe <br />• <br /> <br />O ~~ x x <br />~ ~~ x X x <br />x x <br />CF.NERAI,L~UNSTAD/.E CHANNELS <br />[0 20 30 40 50 60 <br />PERCENT IMPERV70US AREA IN CATCHMENT <br />years.10•"•Z' Where these tools have been applied to <br />urban streams, they have consistently demonstrated <br />that. a sharp threshold in habitat quality exists at ap- <br />proximately 10 to 15% imperviousness.°•"•'~ Beyond <br />this threshold, urban stream habitat quality is consis- <br />tently classified as poor. <br />Imperviousness and water quality <br />Impervious surfaces collect and accumulate pot lut- <br />ants deposited from the atmosphere, leaked from ve- <br />hicles or derived from other sources. During storms, <br />accumulated pollutants are quickly <br />washed off and rapidly delivered to <br />Habitat assessment tools have aquatic systems. <br />consistently demonstrated that <br />a sharp threshold in habitat Monitoring and modeling studies <br />quality exists at approximately have consistently indicated that urban <br />10 to 15% imperviousness. pollutant loads are directly related to <br />~ watershed imperviousness. Indeed, <br />imperviousness is the key predictive <br />variable in most simulation and empirical models used <br />to estimate pollutant loads. For example, the Simple <br />Method assumes that pollutant loads are a direct func- <br />tion ofwatershed imperviousness'-', as imperviousness <br />is the key independent variable in the equation. <br />Threshold limits for maintai~ting backgrott~td <br />pollutant loads <br />Suppose that watershed runoff drains into a lake <br />that isphosphorus-limited. Also assume that the present <br />background load of phosphorus from a rural land use <br />amounts to 0.5 lbslac/yr. The Simple Method predicts <br />that the postdevelopment phosphorus load will exceed <br />background loads once watershed imperviousness (I) <br />exceeds 20 to 25% (Figure 3j, thereby increasing the <br />risk of nutrient overenrichment in the lake. <br />Urban phosphorus loads can he reduced when <br />urban best management practices (BMPs) arc installed, <br />such as stonnwater ponds, wetlands. filters or infiltra- <br />tion practices. Performance monitoring data indicates <br />that BMPs can reduce phosphorus loads by as much as <br />40 to 60%, depending on the practice selected. The <br />impact of this pollutant reduction on the <br />postdevelopmcnt phosphorus loading rate from the <br />site is shown in Figure 3. The net effect is to raise the <br />phosphorus threshold to about 35%-60% impervious- <br />ness, depending on the performance of tl~e BMP we <br />instal(. Therefore, even when effective practices are <br />widely applied, we eventually cross a threshold of <br />imperviousness, beyond which we cannot maintain <br />predevelopment water quality. <br />Imperviousness and stream warming <br />Impervious surfaces both absorb and reflect heat. <br />During the summer months, impervious areas can have <br />local air and ground temperatures that are 10 to 12 <br />degrees warmer than the fields and forests that they <br />replace. In addition, the trees that could have provided <br />shade to offset the effects of solar radiation are absent. <br />Water temperature in headwaterstreams is strop` ly <br />influenced by local air temperatur::. ~Jalli`' reported <br />that stream temperatures throughout the summer are <br />increased in urban watersheds, and the degree of wann- <br />ingappears to be directly related to the imperviousness <br />of the contributing watershed. He monitored Five head- <br />water streams in the Maryland Piedmont over asix- <br />month period, the streams having differing levels of <br />impervious cover (Figure 4). Each of the urban streams <br />had mean temperatures that were consistently warnler <br />than a forested reference stream, and the size of the <br />increase (referred to as the delta-T) appeared to be a <br />direct function of watershed imperviousness.. Other <br />factors, such as lack of riparian cover and ponds, were <br />also demonstrated to amplify stream warming, but the <br />primary contributing factor appeared to be watershed <br />impervious cover.`' <br />Imperviousness and stream biodiversity <br />The health of the aquatic ecosystem. is a strong <br />environmental indicator of watershed quality. A num- <br />ber of research studies have recently examined tl~e <br />links between imperviousness and the biological di- <br />versity in streams. Some of the key findings are sum- <br />marized in Table 2. <br />Aquatic insects <br />The diversity, richness and composition of the <br />benthic or streambed community has frequently been <br />used to evaluate the quality of urban streams. Not only <br />are aquatic insects a useful environmental indicator, <br />~__a ~...:.. ,.. <br />but They also form the base of the stream ~~~~ ~~_..,,~ ~~~ <br />most regions of the country. <br />102 i 1aYf ~~,~~iL-1~iL~~~7~(~ttaia;i_r~-.aairt~ia}`~, !_; `~l~rl~, lay[~1~:°~`iJ l.•,~1~41~:__~~,_1 <br />