Abstract
Gravel loss is one of the major issues on unsealed roads which attract large annual maintenance. The continual process of gravel loss makes roads environmentally unsustainable. The unsealed road management faces several challenges which are: inaccuracies in behavior prediction, numerous data gathering requirements and exposure in the level of service and maintenance practices. To address these issues, the modified gravel is used on the unsealed road network in Australia. A case study is conducted to assess the gravel loss of unsealed roads. To monitor gravel loss on good quality, gravel monitoring stations are installed. Geographical information system (GIS) is used for finalizing the gravel monitoring station locations. Roughometer is used for surface assessment longitudinally. Roughness will be measured over two years at an interval of every three months. This paper discusses the gravel loss monitoring approaches, data analyses and improved material specification for gravel.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Martin T, Choummanivong L (2016) The benefits of long-term pavement performance (LTPP) research to funders. Transp Res Procedia 14:2477–2486
Australian RuralRoads Group (2010) Going nowhere: The rural local road crisis Its national significance and proposed reforms. Australian Rural Roads Group, NSW, Australia
Scenic Rim Regional Council (SRRC) (2018) 2018–19 community budget report scenic rim regional council, scenic rim regional council, Beaudesert, Australia
Alzubaidi H, Magnusson R (2002) Deterioration and rating of gravel roads: state of the art. Road Mater Pavement Des 3(3):235–260
McManus KJ (1994) Pavement deterioration models for a local government authority. In: 17th ARRB conference, gold coast, Queensland, 15–19 August 1994; proceedings; volume 17, part 4
Lea JD, Paige-Green P, Jones D (1999) Neural networks for performance prediction on unsealed roads. Road and Transp Res 8(1):57
Linard K (2010) A system dynamics modeling approach to gravel road maintenance management. In: ARRB conference, 24th, 2010ARRB Group Limited
Henning T, Giummarra GJ, Roux DC (2008) The development of gravel deterioration models for adoption in a New Zealand gravel road management system (No. 332)
Henning TF, Flockhart G, Costello SB, Jones V, Rodenburg B (2015) Managing gravel-roads on the basis of fundamental material properties (No. 15-2562)
Paige-Green P (1989) The influence of the geological and geotechnical properties on the performance of materials for gravel roads (Ph.D. Thesis, University of Pretoria, Pretoria)
Jones D, Paige-Green P, Sadzik E (2003) Development of guidelines for unsealed road assessment. Transp Res Rec: J Transp Res BoardBoard 1819:287–296
Uys R (2011) Evaluation of gravel loss deterioration models: case study. Transp Res Rec 2205(1):86–94
Giummarra G (2009) Unsealed roads manual: guidelines to good practice, 2009th edn. Australian Road Research Board, Melbourne, Victoria, Australia
Road Infrastructure Management Support (RIMS) (2015) Unsealed roads tactical asset management guide. RIMS, New Zealand
Mazari M, Rodriguez DD (2016) Prediction of pavement roughness using a hybrid gene expression programming-neural network technique. J Traffic Transp Eng (Engl Ed) 3(5):448–455
Acknowledgements
Authors acknowledge Chris Gray, General Manager, Asset and Environmental Sustainability, from Scenic Rim Regional Council for providing his support for this research project.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Pardeshi, V., Nimbalkar, S., Khabbaz, H. (2020). Theoretical and Experimental Assessment of Gravel Loss on Unsealed Roads in Australia. In: Kanwar, V., Shukla, S. (eds) Sustainable Civil Engineering Practices. Lecture Notes in Civil Engineering, vol 72. Springer, Singapore. https://doi.org/10.1007/978-981-15-3677-9_3
Download citation
DOI: https://doi.org/10.1007/978-981-15-3677-9_3
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-3676-2
Online ISBN: 978-981-15-3677-9
eBook Packages: EngineeringEngineering (R0)