Comparing rockfall hazard and risk assessment procedures along roads for different planning purposes

Mineo, Simone

doi:10.1007/s11629-019-5766-3

Cited by 24 publications

(8 citation statements)

References 47 publications

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“…In QRAs, rockfall risk for exposed elements is estimated by including in the analysis each component of risk: the hazard, the exposure and the vulnerability. However, in practice, this quantitative estimation is challenging [13,32,53], so that state-of-the-art methods remain scarce [1,14,43,45]. Notably, risk is always evaluated for already existing buildings and infrastructures only [1,13,54,61].…”

Section: Introductionmentioning

confidence: 99%

Quantile-based individual risk measures for rockfall-prone areas

Farvacque

Eckert

Bourrier

et al. 2021

International Journal of Disaster Risk Reduction

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In mountain environments, precise rockfall risk evaluation is crucial to reduce death tolls and costs. However, to date, existing rockfall risk assessment procedures remain scarce, as they focus only on existing elements at risk and with the damage expectation as sole risk measure. Here, we propose an approach to evaluate the distribution of damages on an individual basis as a continuous function of space. Furthermore, rockfall risk is evaluated through (i) the damage expectation and based on (ii) the value-at-risk (VAR) and (iii) the expected shortfall (ES). VaR and ES risk measures allow better assessing the risk due to extreme events and accounting for various short-term/long-term constraints faced by stakeholders. This procedure is applied to Le Brocey slope (municipality of Crolles, French Alps), frequently affected by rockfall events, illustrating its potential for land-use planning. Notably, obtained individual risk values can be confronted with acceptability thresholds to perform legal zoning on sound basis. Also, they allow comparison of risk management strategies as function of different behaviors towards risk, budgetary constraints and/or temporal horizons. Hence, the approach provides valuable tools for future land-use planning and decision-making. It could easily be transferred to other hazards as a wider contribution to the determination of the best balance between safety and sustainability.

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Section: Introductionmentioning

confidence: 99%

Quantile-based individual risk measures for rockfall-prone areas

Farvacque

Eckert

Bourrier

et al. 2021

International Journal of Disaster Risk Reduction

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“…To gain a deeper understanding of rockfalls aboveground, rockfall disasters under various circumstances have been studied (Curry and Black 2003;Zorlu and Taga 2009;Kumar et al 2017). Infrastructure damage has been investigated (Bunce et al 1997;Budetta 2004;Mignelli et al 2012;Macciotta et al 2016;Mineo 2020). Passive protection structures such as embankments and fences are widely used to protect the infrastructure downhill of steep slopes (Ronco et al 2009;Peila and Ronco 2009;Marchelli et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Risk mitigation for rockfall hazards in steeply dipping coal seam: a case study in Xinjiang, northwestern China

Wang

et al. 2021

Geomatics, Natural Hazards and Risk

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Many recent examples have shown that rockfalls can occur in underground steep coal mines. The stratigraphic circumstances, block formation mechanism, and cumulative damage effects of rockfalls in the longwalls of a steeply dipping coal seam (SDCS) make them detrimental to workplace safety. Therefore, this study examined an approach for mitigating rockfall hazards in SDCSs. A passive mesh system was installed to prevent the propagation of rockfalls, which decreased the number of collisions between the falling rocks and mining equipment. The interactions of the falling rocks and passive mesh were studied using a series of full-scale numerical impact tests. The following conclusions could be drawn. The displacement of the mesh increased with the rockfall kinetic energy, showing the characteristic of strain hardening. The peak stress appeared near the contact area between the rockfall and mesh, and it spread to the mesh edge in an X-shaped pattern. Stress concentrations were likely to occur in areas that were in direct contact with the mesh and mesh edges. The displacement of the mesh increased when the incidence angle increased, and the number of mesh cells entering the plastic state increased significantly. The internal energy ratio increased with an increase in the incidence angle, indicating that a greater incidence angle led to a larger amount of kinetic energy being transferred from the block into the internal energy of the passive mesh. Finally, the method was verified by comparing the numerical test with the on-site damaged equipment. The high replacement frequency of a passive mesh system and the annual fatality rate in the longwalls of SDCS were significantly improved. This study provided the design for a drapery mesh system for rockfall disaster prevention, particularly the mitigation of rockfall hazard risks in underground SDCSs.

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“…Remote sensing (RS)-based data and Geographic Information System (GIS) tools, together with machine-learning approaches, have been popularly used in numerous studies. In recent studies, soft computing, heuristic, statistic, and deterministic models have been used to evaluate rockfall in terms of source identification [8][9][10], kinematic modeling [11][12][13], hazard assessment [1,14,15], and risk assessment [16][17][18]. The numerical modeling predicts either the blocks trajectories using Newtonian mechanics or the rockfall runout zone based on empirical measurements [2].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based and 3D Kinematic Models for Rockfall Hazard Assessment Using LiDAR Data and GIS

et al. 2020

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Rockfall is one of the most hazardous phenomena in mountainous and hilly regions with high and steep terrain. Such incidents can cause massive damage to people, properties, and infrastructure. Therefore, proper rockfall hazard assessment methods are required to save lives and provide a guide for the development of an area. The aim of this research is to develop a method for rockfall hazard assessment at two different scales (regional and local). A high-resolution airborne laser scanning (ALS) technique was utilized to derive an accurate digital terrain model (DTM); next, a terrestrial laser scanner (TLS) was used to capture the topography of the two most critical areas within the study area. A staking machine-learning model based on different classifiers, namely logistic regression (LR), random forest (RF), artificial neural network (ANN), support vector machine (SVM), and k-nearest neighbor (KNN), was optimized and employed to determine rockfall probability by utilizing various rockfall conditioning factors. A developed 3D rockfall kinematic model was used to obtain rockfall trajectories, velocity, frequency, bouncing height, kinetic energy, and impact location. Next, a spatial model combined with a fuzzy analytical hierarchy process (fuzzy-AHP) integrated in the Geographic Information System (GIS) was developed to assess rockfall hazard in two different areas in Ipoh, Malaysia. Additionally, mitigation processes were suggested and assessed to provide a comprehensive information for urban planning management. The results show that, the stacking random forest–k-nearest neighbor (RF-KNN) model is the best hybrid model compared to other tested models with an accuracy of 89%, 86%, and 87% based on training, validation, and cross-validation datasets, respectively. The three-dimension rockfall kinematic model was calibrated with an accuracy of 93% and 95% for the two study areas and subsequently the rockfall trajectories and their characteristics were derived. The assessment of the suggested mitigation processes proves that the proposed methods can reduce or eliminate rockfall hazard in these areas. According to the results, the proposed method can be generalized and applied in other geographical places to provide decision-makers with a comprehensive rockfall hazard assessment.

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Comparing rockfall hazard and risk assessment procedures along roads for different planning purposes

Cited by 24 publications

References 47 publications

Quantile-based individual risk measures for rockfall-prone areas

Quantile-based individual risk measures for rockfall-prone areas

Risk mitigation for rockfall hazards in steeply dipping coal seam: a case study in Xinjiang, northwestern China

Machine Learning-Based and 3D Kinematic Models for Rockfall Hazard Assessment Using LiDAR Data and GIS

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