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Evaluating the Accuracy of Common Runoff Estimation Methods for New Impervious Hot-Mix Asphalt
Citation:
Brown, R. AND Mike Borst. Evaluating the Accuracy of Common Runoff Estimation Methods for New Impervious Hot-Mix Asphalt. Journal of Sustainable Water in the Built Environment. American Society of Civil Engineers (ASCE), New York, NY, 2(2):04015010, (2016).
Impact/Purpose:
Accurately predicting runoff volume from impervious surfaces for water quality design events (e.g., 25 mm) is important for sizing green infrastructure stormwater control measures to meet water quality and infiltration design targets. The objective of this research was to quantify abstraction from a recently paved impervious hot-mix asphalt (HMA) parking lot surface and evaluate the accuracy of the following common runoff estimation methods: the discrete Soil Conservation Service Curve Number (SCS-CN) method, the Simple Method (SM), and the Small Storm Hydrology Method (SSHM).
Description:
Accurately predicting runoff volume from impervious surfaces for water quality design events (e.g., 25.4 mm) is important for sizing green infrastructure stormwater control measures to meet water quality and infiltration design targets. The objective of this research was to quantify abstraction from a recently paved impervious hot-mix asphalt (HMA) parking lot surface and evaluate the accuracy of the following common runoff estimation methods: the discrete Soil Conservation Service Curve Number (SCS-CN) method, the Simple Method (SM), and the Small Storm Hydrology Method (SSHM). The U.S. Environmental Protection Agency constructed a 0.4-ha parking lot in Edison, New Jersey, that incorporated permeable pavement in the parking lanes which were designed to receive run-on from the impervious HMA driving lanes. Twelve lined permeable pavement sections capture all infiltrating water and route it to collection tanks that can fully contain events up to 38 mm. Using a water balance approach on an event basis, the measured infiltrate volume was compared to the rainfall volume across the drainage area to determine the rainfall retained by the HMA surface and in the permeable pavement strata and underlying aggregate. It was assumed that the rainfall retention depth for events with an antecedent dry period (ADP) less than 24 hours (N=16) was completely abstracted in the HMA surface because evaporation from the permeable pavement profile was expected to be negligible for this short ADP. Including measurement uncertainty, the abstraction depth in new, smooth HMA should be in the range of 0.4 to 1.6 mm. In comparing measured retention in the HMA surface to the three methods, the SCS-CN method over-predicted abstraction in the majority of the test sections. While the SM and SSHM under-predicted abstraction in more test sections, the difference in half of the sections was not significant. These results indicate that the current SCS-CN method using a curve number of 98 under-predicted runoff volumes in newly-paved impervious asphalt surfaces that are free of defects and depressions. Based on the measured abstraction depth, the standard curve number selection (98) resulted in under-predicting runoff volume for a 25.4-mm water quality design event by about 15%. Using the SM or SSHM, the predicted abstraction depths were within the range of the measured abstraction depths.
