Use of gravel loss prediction models in the design and management of unsealed road pavements

Many countries have large unsealed road networks which are essential for business efficiency, social connectedness, and community safety. These roads are maintained at considerable cost mainly through blading and re-gravelling. The latter is a major component of the maintenance and is determined by gravel loss. Gravel loss prediction models can be used to assess the effect of different wearing courses, which provides useful input into the design and management of unsealed roads. This paper reviews the origins, input parameters, and output of four available gravel loss prediction models, namely, the Transport and Road Research, HDM-4, Australian, and South African models. It was found that the predictive accuracy of the models is in general low and they predict very different gravel loss results. There is also a lack of integration between the design and maintenance, leading to the wearing course properties recommended for design not being directly linked to gravel loss. These findings led to further analysis of the models and the development of re-gravelling frequencies based on traffic, climate (annual rainfall), and material property (plastic factor), which can be used in the selection of the appropriate wearing course material and in the determination of re-gravelling budgets. This presents a simplified approach to the use of existing gravel loss prediction models in the design and management of unsealed roads which mitigates some of the shortcomings in the use of uncalibrated models