Alternative modeling framework for pervious concrete pavement condition analysis

Pervious concrete pavement (PCP) is listed as one of the best stormwater management practices by the Environmental Protection Agency (EPA) due to its capacity to reduce impervious areas, capability to improve water quality, reduce runoff quantity, eliminate the need for detention basins, protect downstream channels, and reduce flooding (save lives and properties). Moreover, it is designated a “Green Asset” since it allows stormwater to seep through pavement to recharge ground water level. PCP may potentially improve skid resistance, reduce noise, decrease heat, and reduce water contamination. However, since PCP must have adequate permeability (porous structure), it can potentially be susceptible to freeze–thaw damage particularly in cold climates. To deploy the PCP in a transportation network, its performance should be thoroughly evaluated. For this purpose, the condition of PCP has to be defined and determined over time. Since PCP has not been widely investigated in cold climates such as Canada, no condition indices have been defined for it. This paper proposes a combined condition index for PCP to ensure that it will perform adequately over time. To develop a combined condition index, both a panel rating approach and objective measurements are employed to assess surface distresses and permeability rates of specific PCP sections. The panel rating method is applied due to the lack of long-term performance data to evaluate PCP sections’ conditions with regards to surface distress (e.g., raveling, spalling, and cracking) and functional performance (i.e., permeability rate). The objective measurements of surface distress and permeability rate (functional performance) of the same PCP sections are performed through the application of the adjusted Ministry of Transportation of Ontario (MTO) protocol and a permeameter, respectively. Regression analysis is used to relate surface objective measurements to the surface panel rating. As a result of statistical analyses, the panel rating method is successfully applied only in surface distress rating. Accordingly, a combined condition index is developed using surface distress ratings and objective functional performance measures.