- 1University of Canterbury, Faculty of Science, School of Earth and Environment, New Zealand (mathew.darling@pg.canterbury.ac.nz)
- 2Computer Science and Software Engineering, Faculty of Engineering, University of Canterbury, Christchurch New Zealand
- 3Centre for Sustainability, School of Geography, University of Otago, Dunedin New Zealand
Human casualties related to rapid-onset natural hazards are usually proportional to the number of people directly exposed. Yet population mobility makes exposure difficult to assess due to temporal and spatial variability. Population exposure is a crucial dimension of risk, and often the dynamics of exposure are overlooked in disaster risk assessment and subsequent management. Here, we quantify how disaster risk in Aotearoa New Zealand changes across multiple temporal and a highly resolved spatial scales due to dynamic population mobility and observe the significant influence it has on resulting risk.
We present a unique dataset from the highly touristic Piopiotahi Milford Sound in New Zealand using longitudinal data over a 790-day period, including throughout the COVID-19 pandemic. We demonstrate how minute-by-minute population changes of up to 1000-people within 5 minutes can dramatically affect the risk posed by a landslide-triggered tsunami in the fiord. During our study period, the societal risk fluctuated by two to three orders of magnitude, underscoring how dynamic population movement translates to the potential doubling of fatalities in a tsunami. Using an established threshold for acceptable risk, our dynamic approach reveals that the societal risk was only acceptable during the strictest COVID-19 lockdown measures, after which it became increasingly unacceptable as population mobility resumed.
This New Zealand case study demonstrates that integrating high-resolution dynamic population data into disaster risk assessment can significantly improve assessments of risk, particularly in rapidly changing or high population mobility contexts. Understanding these dynamics is essential for developing effective risk reduction strategies and adaptation plans. Our findings show that incorporating longitudinal high-resolution data on dynamic exposure substantially improves assessment accuracy and reduces inherent uncertainty of dynamic disaster risk, especially in popular touristic areas and where population shifts are frequent and significant.
How to cite: Darling, M., Robinson, T., Adams, B., Wilson, T., and Orchiston, C.: Minutes Matter for Risk to Life in Disasters - the experience from Aotearoa, New Zealand, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1744, https://doi.org/10.5194/egusphere-egu25-1744, 2025.