RESUMEN

Earthquake-triggered landslides show three important characteristics: they are often responsible for a considerable proportion of the damage sustained during mountain region earthquakes, they are non-randomly distributed across space, and they continue to evolve in the years after the earthquake. Despite this, planning for future earthquakes rarely takes into consideration either landslides or their evolution with time. Here we couple a unique timeseries of mapped landslides between 2014-2020 across the area of Nepal impacted by the 2015 Mw 7.8 Gorkha earthquake and a numerical landslide runout model overlain with building locations to examine how the distributions of both evolving landslide hazard and exposure intersect to generate a dynamic threat to buildings. The threat from landslide runout is shown to change in predictable ways after the earthquake, becoming more pronounced at mid- and lower-hillslope positions and remaining in the landscape for multiple years. Using the positions of our mapped landslides as a starting point, we can identify a priori the locations of 78% of buildings that were subsequently impacted by landslide debris. We show that landslide exposure and hazard vary from negligible to high, in relative terms, over lateral distances of as little as 10s of m. Our findings hold important implications for guiding reconstruction and for taking steps to reduce the risks from future earthquakes.

Asunto(s)

RESUMEN

Glacial lake outburst floods (GLOFs) represent a major hazard and can result in significant loss of life. Globally, since 1990, the number and size of glacial lakes has grown rapidly along with downstream population, while socio-economic vulnerability has decreased. Nevertheless, contemporary exposure and vulnerability to GLOFs at the global scale has never been quantified. Here we show that 15 million people globally are exposed to impacts from potential GLOFs. Populations in High Mountains Asia (HMA) are the most exposed and on average live closest to glacial lakes with ~1 million people living within 10 km of a glacial lake. More than half of the globally exposed population are found in just four countries: India, Pakistan, Peru, and China. While HMA has the highest potential for GLOF impacts, we highlight the Andes as a region of concern, with similar potential for GLOF impacts to HMA but comparatively few published research studies.

RESUMEN

The ability to rapidly access optical satellite imagery is now an intrinsic component of managing the disaster response that follows a major earthquake. These images provide synoptic data on the impacts, extent, and intensity of damage, which is essential for mitigating further losses by feeding into the response coordination. However, whilst the efficiency of the response can be hampered when cloud cover limits image availability, spatio-temporal variations in cloud cover have never been considered as part of the design of effective disaster mapping. Here we show how annual variations in cloud cover may affect our capacity to respond rapidly throughout the year and consequently contribute to overall earthquake risk. We find that on a global scale when accounting for cloud, the worst time of year for an earthquake disaster is between June and August. During these months, 40% of the global population at risk from earthquakes are obscured from optical satellite view for >3 consecutive days. Southeastern Asia is particularly strongly affected, accounting for the majority of the population at risk from earthquakes that could be obscured by cloud in every month. Our results demonstrate the importance of the timing of earthquakes in terms of our capacity to respond effectively, highlighting the need for more intelligent design of disaster response that is not overly reliant on optical satellite imagery.

RESUMEN

High death tolls from recent earthquakes show that seismic risk remains high globally. While there has been much focus on seismic hazard, large uncertainties associated with exposure and vulnerability have led to more limited analyses of the potential impacts of future earthquakes. We argue that as both exposure and vulnerability are reducible factors of risk, assessing their importance and variability allows for prioritization of the most effective disaster risk-reduction (DRR) actions. We address this through earthquake ensemble modeling, using the example of Nepal. We model fatalities from 90 different scenario earthquakes and establish whether impacts are specific to certain scenario earthquakes or occur irrespective of the scenario. Our results show that for most districts in Nepal impacts are not specific to the particular characteristics of a single earthquake, and that total modeled impacts are skewed toward the minimum estimate. These results suggest that planning for the worst-case scenario in Nepal may place an unnecessarily large burden on the limited resources available for DRR. We also show that the most at-risk districts are predominantly in rural western Nepal, with ∼9.5 million Nepalis inhabiting districts with higher seismic risk than Kathmandu. Our proposed approach provides a holistic consideration of seismic risk for informing contingency planning and allows the relative importance of the reducible components of risk (exposure and vulnerability) to be estimated, highlighting factors that can be targeted most effectively. We propose this approach for informing contingency planning, especially in locations where information on the likelihood of future earthquakes is inadequate.