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Probabilistic geotechnical modeling of the seismic resilience of bioengineered slopes
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DOI：10.1016/j.ecoleng.2026.108063.png)
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Abstract
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The geotechnical analysis of bioengineered slopes is inherently complex due to the temporal endogenous processes affecting their natural components and the difficulty in forecasting exogenous actions such as climate-induced phenomena and earthquakes. Resilience, understood as the capacity of a system to attain and maintain functionality over time, offers a suitable paradigm for the engineering analysis and management of such bioengineered systems, as it accounts explicitly for the temporal evolution of performance and for recovery following disturbance. Because the seismic loading, the calculated factor of safety, the adopted performance criteria, and the functionality model are all uncertain, a deterministic analysis is inadequate, and these uncertainties must be propagated explicitly. This paper proposes a probabilistic framework that couples stochastic simulation of local seismicity, geotechnical slope stability analysis, time-dependent modeling of root reinforcement and wooden-element degradation, and a functionality metric calibrated consistently with established geotechnical design practice; a resilience index is obtained as the time-integrated, control-period-normalized measure of functionality. The framework is demonstrated on a real slope in Tuscany (Italy), comparing conventional, nature-based, and combined green–gray stabilization scenarios. Both nature-based scenarios markedly outperform the conventional one, with the combined solution ranking highest across the full range of outcomes: the time-invariant structural reinforcement provides a uniform resilience gain, the time-variant root contribution governs recovery, and worst-case performance reflects the timing of severe disturbances rather than the adequacy of reinforcement. The resilience index thus offers ecological engineers a decision-support metric for ranking and timing green, gray, and hybrid stabilization strategies under uncertainty.
Keywords:
Resilience
Geotechnical engineering
Slope stability
Earthquakes
Nature-based solutions
Probability
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