Stormwater runoff quality and quantity from asphalt, paver, and crushed stone driveways in Connecticut
ABSTRACT This study compared the quality and quantity of stormwater runoff from replicated asphalt, permeable paver, and crushed-stone driveways. Rainfall was measured on-site and runoff was recorded using tipping buckets. Flow-weighted composite runoff samples were analyzed weekly for total suspended solids, total Kjeldahl nitrogen, nitrate-nitrogen, ammonia-nitrogen, total phosphorus (TP), zinc, lead, and copper. Infiltration rate was determined on each driveway annually. Repeated measures analysis of variance indicated that stormwater runoff was significantly different among each driveway type; the order of decreasing runoff was asphalt> paver> stone. Average infiltration rates were 0, 11.2 and 9.0 cm/h for asphalt, paver, and crushed stone driveways, respectively. Both paver and crushed stone driveways reduced stormwater runoff as compared to asphalt driveways. Runoff from paver driveways contained significantly lower concentrations of all pollutants measured than runoff from asphalt driveways. However, runoff from crushed stone driveways was similar in concentrations to runoff from asphalt driveways, except for TP concentrations, which were lower in runoff from crushed stone driveways than runoff from asphalt driveways. The mass export of measured pollutants followed the relative differences in stormwater runoff, rather than differences in concentrations.
SourceAvailable from: eprints.qut.edu.au
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ABSTRACT: We determined reference hydro-climatic and land use/cover sensitivities of stormwater runoff and quality in the Miami River Basin of Florida by developing a dynamic rainfall-runoff model with the EPA Storm Water Management Model. Potential storm runoff in the complex coastal-urban basin exhibited high and notably different seasonal sensitivities to rainfall; with stronger responses in the drier early winter and wetter late summer months. Basin runoff and pollutant loads showed moderate sensitivities to the hydrologic and land cover parameters; imperviousness and roughness exhibited more dominant influence than slope. Sensitivity to potential changes in land use patterns was relatively low. The changes in runoff and pollutants under simultaneous hydro-climatic or climate-land use perturbations were notably different than the summations of their individual contributions. The quantified sensitivities can be useful for appropriate management of stormwater quantity and quality in complex urban basins under a changing climate, land use/cover, and hydrology around the world.
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ABSTRACT: The Storm Water Management Model was used to simulate runoff and nutrient export from a low impact development (LID) watershed and a watershed using traditional runoff controls. Predictions were compared to observed values. Uncalibrated simulations underpredicted weekly runoff volume and average peak flow rates from the multiple subcatchment LID watershed by over 80%; the single subcatchment traditional watershed had better predictions. Saturated hydraulic conductivity, Manning's n for swales, and initial soil moisture deficit were sensitive parameters. After calibration, prediction of total weekly runoff volume for the LID and traditional watersheds improved to within 12 and 5% of observed values, respectively. For the validation period, predicted total weekly runoff volumes for the LID and traditional watersheds were within 6 and 2% of observed values, respectively. Water quality simulation was less successful, Nash–Sutcliffe coefficients >0.5 for both calibration and validation periods were only achieved for prediction of total nitrogen export from the LID watershed. Simulation of a 100-year, 24-h storm resulted in a runoff coefficient of 0.46 for the LID watershed and 0.59 for the traditional watershed. Results suggest either calibration is needed to improve predictions for LID watersheds or expanded look-up tables for Green–Ampt infiltration parameter values that account for compaction of urban soil and antecedent conditions are needed.JAWRA Journal of the American Water Resources Association 01/2015; DOI:10.1111/jawr.12272 · 2.07 Impact Factor