Water Film Depth Prediction Model for Chip Seal Surface Drainage


Water film depth (WFD) is an essential factor regarding road traffic safety on the roads due to its direct connection with skid resistance, hydroplaning speed, and the tendency of splash and spray. Increasing the pavement macrotexture is one of the solutions to reduce the WFD. Therefore, chip seal can be a viable option for reducing the WFD. However, the existing models of WFD prediction are not developed based on highly textured surfaces like chip seal. Besides, the rainfall intensity ranges used for developing most of these models do not raise safety issues on chip seal surfaces. To propose a new WFD prediction model, an experimental study was conducted on 154 different combinations of texture depth, surface material type, surface slope, drainage length, and rainfall intensity using a full-scale rainfall simulator. To study the effects of surface material type and also evaluate the newly proposed eco-friendly rubberized chip seal, mineral aggregate and crumb rubber were used as aggregate. Test results through 1,784 WFD readings indicated that the well-known Gallaway and PAVDRN models are not accurate for chip seal surfaces. Hence, two new analytical models were proposed to predict the WFD, which showed a significantly higher correlation between the actual and the predicted WFD compared to the existing models. Besides, the rubberized chip seal performed an enhanced drainage capability compared to conventional chip seal, especially in low slopes, due to the hydrophobic nature of crumb rubber. Accordingly, the proposed model incorporated a term to consider the effect of surface material type.

Meeting Name

Transportation Research Board 100th Annual Meeting (2021: Jan. 5-29, Virtual)


Civil, Architectural and Environmental Engineering

Keywords and Phrases

Chip seals; Crumb rubber; Drainage; Experiments; Highway safety; Paving materials; Predictive models; Surface course (Pavements); Water; Highways

Document Type

Article - Conference proceedings

Document Version


File Type





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Publication Date

29 Jan 2021