Physically based deterministic rockfall hazard assessment integrating multi-failure modes at large scale: A case study of Tiefeng Township, Chongqing, China

The rise in construction activities within mountainous regions has significantly increased the frequency of rockfalls. Statistical models for rockfall hazard assessment often struggle to achieve high precision on a large scale. This limitation arises primarily from the scarcity of historical rockfall data and the inadequacy of conventional assessment indicators in capturing the physical and structural characteristics of rockfalls. This study proposes a physically based deterministic model designed to accurately quantify rockfall hazards at a large scale. The model accounts for multiple rockfall failure modes and incorporates the key physical and structural parameters of the rock mass. Rockfall hazard is defined as the product of three factors: the rockfall failure probability, the probability of reaching a specific position, and the corresponding impact intensity. The failure probability includes probabilities of formation and instability of rock blocks under different failure modes, modeled based on the combination patterns of slope surfaces and rock discontinuities. The Monte Carlo method is employed to account for the randomness of mechanical and geometric parameters when quantifying instability probabilities. Additionally, the rock trajectories and impact energies simulated using Flow-R software are combined with rockfall failure probability to enable regional rockfall hazard zoning. A case study was conducted in Tiefeng, Chongqing, China, considering four types of rockfall failure modes. Hazard zoning results identified the steep and elevated terrains of the northern and southern anaclinal slopes as areas of highest rockfall hazard. These findings align with observed conditions, providing detailed hazard zoning and validating the effectiveness and potential of the proposed model.