Abstract
Cost-benefit analyses are conducted to evaluate the cost efficiency of road slope stabilisation measures to aid road planning, design, maintenance, and repair. Most cost analyses are based on a statistical framework that requires a database of slope failures. However, databases can be costly to compile, and they tend to compare options that satisfy the same global factor of safety or partial factors of safety (e.g. EC-7) neglecting the fact that each measure reduces the risk of slope failure by a different extent. Here, we present a novel methodology to evaluate the cost efficiency of different road slope stabilisation measures based on direct costs and a rigorous but parsimonious mechanistic and probabilistic geotechnical slope stability assessment. Unlike other cost analyses for slope stability, our methodology accounts for uncertainty in slope geomaterial characteristics, as well as for hillslope hydrology. Probabilistic slope stability analyses accounting for the effect of time-varying slope seepage are performed using the CUTSTAB-P methodology to estimate the frequency of slope failure. The methodology is demonstrated on a cut slope in Nepal, assessing four different road slope stabilisation measures that are implemented in Nepal: (1) the cut slope with no additional support; (2) reprofiling to a shallower inclination; (3) a mortared masonry wall; and (4) an anchoring system. We find that an anchoring system is the most cost-efficient road slope stabilisation measure for this cut slope, and that a mortared masonry wall is least cost-efficient. This is despite the mortared masonry wall having much lower initial investment costs than the anchoring system. Mortared masonry walls are hugely common along roads in Nepal. We also make an approximation of indirect costs. With this addition, we find that the anchoring system remains the most cost-efficient method.
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Robson, E. B., Milledge, D. G., Utili, S., & Bründl, M. (2024). Cost-benefit methodology for road slope stabilisation. Transportation Geotechnics, 48. https://doi.org/10.1016/j.trgeo.2024.101282
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