Predicting physical clogging of porous and permeable pavements

SummaryPorous pavements are easily retrofitted, and effective in improving water quality and hydrology, but prone to clogging. Despite being a major determinant in the lifespan of porous pavements, there is limited information on the physical clogging processes through these systems. The aim of this study was to understand the main physical processes that govern physical clogging and develop a simple black-box model that predicts physical clogging. The key variables that were hypothesised to influence clogging were pavement design and climate characteristics. Two compressed time scale laboratory experiments were conducted over 3 years on three common porous pavement types; monolithic porous asphalt, modular Hydrapave and monolithic Permapave. Pavement design was found to be an important role in clogging. Permapave did not clog even after 26 years of operation in simulated sub-tropical Brisbane (Australia) climate while porous asphalt and Hydrapave clogged after just 12 years, from surface clogging and geotextile clogging, respectively. Each system was tested using two different dosing patterns: (1) continual wetting with no dry periods and (2) variable inflow rates with drying periods (i.e. representing more natural conditions). The latter dosing method approximately doubled the lifespan of all systems suggesting the influence of climate conditions on clogging. Clogging was found to be highly correlated with cumulative volume and flow rate. A simple black-box regression model that predicts physical clogging was developed as a function of cumulative volume and Brisbane climatic conditions. However it is very likely that the shape of this regression is general, and that it could be calibrated for different climates in the future.

► We conducted two laboratory experiments over 3 years on three porous pavement types.
► Continual wetting with no drying, and variable inflow with drying were simulated.
► Variable inflow and drying periods approximately doubled the lifespan of all systems.
► A simple regression model to predict hydraulic resistance (clogging) was developed.
► Hydraulic resistance is an exponential function of cumulative volume and flow rate.