The Canterbury earthquake sequence triggered thousands of rockfalls in the Port Hills of Christchurch, New Zealand, with over 6,000 falling on 22 February 2011. Several hundred families were evacuated after about 200 homes were hit. We characterized the rockfalls by boulder-size distribution, runout distance, source-area dimensions, and boulder-production rates over a range of triggering peak ground accelerations. Using these characteristics, a time-varying seismic hazard model for Canterbury, and estimates of residential occupancy rates and resident vulnerability, we estimated annual individual fatality risk from rockfall in the Port Hills. The results demonstrate the Port Hills rockfall risk is time-variable, decreasing as the seismic hazard decreases following the main earthquakes in February and June 2011. This presents a real challenge for formulating robust land-use and reconstruction policy in the Port Hills.

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Abstract. We present a quantitative risk analysis (QRA) case study from the Kā Roimata o Hine Hukatere / Franz Josef Glacier and Te Moeka o Tuawe / Fox Glacier valleys, on the west coast of the South Island, Aotearoa / New Zealand. The glacier valleys are important tourist destinations that are subject to landslide hazards. Both valleys contain actively retreating glaciers; experience high rainfall; and are proximal to the Alpine Fault, which is a major source of seismic hazard on the west coast. We considered the life safety risk from rockfalls, soil/rock avalanches, and flows that either are seismically triggered or occur aseismically. To determine the range in risk values and dominant contributing variables to the risk, we modelled nine different risk scenarios where we incrementally changed the variables used in the risk model to account for the underlying uncertainty. The scenarios represent our central estimate of the risk, e.g. neither optimistic nor conservative, through to our upper estimate of the risk. We include in these estimates the impact time-variable factors, such as a recently reactivated landslide, have had on locally increasing risk and the time-elapsed since the last major earthquake on the nearby Alpine Fault. We disaggregated our risk results to determine the dominant drivers in landslide risk, which highlighted the importance of considering dynamic time-variable risk scenarios and the changing contributions to risk from aseismic versus seismic landslides. A detailed understanding of the drivers of landslide risk in each valley is important to determine the most efficient and appropriate risk management decisions.

Abstract. We present a quantitative risk analysis (QRA) case-study from the Franz Josef and Fox Glacier Valleys, on the West Coast of the South Island, New Zealand. The Glacier Valleys are important tourist destinations that are subject to landslide hazards. Both valleys contain actively retreating glaciers, experience high rainfall, and are proximal to the Alpine Fault, which is a major source of seismic hazard on the West Coast. We considered the life safety risk from rockfalls, soil/rock avalanches and flows that are either seismically triggered or occur aseismically. To determine the range in risk values, and dominant contributing variables on the risk, we modelled nine different risk scenarios where we incrementally changed the variables used in the risk model to account for the underlying uncertainty. The scenarios represent our central estimate of the risk, e.g. neither optimistic nor conservative, through to our upper estimate of the risk. We include in these estimates the impact of time-variable factors, such as a recently reactivated landslide has had on locally increasing risk and the time-elapsed since the last major earthquake on the nearby Alpine Fault. We disaggregated our risk results to determine the dominant drivers in landslide risk, which highlighted importance of considering dynamic time variable risk scenarios and the changing contributions to risk from aseismic versus seismic landslides. A detailed understanding of the drivers of landslide risk in each valley is important to determine the most efficient and appropriate risk management decisions.

No abstract