Revising supraglacial rock avalanche magnitudes and frequencies in Glacier Bay National Park, Alaska

The frequency of large supraglacial landslides (rock avalanches) occurring in glacial environments is thought to be increasing due to feedbacks with climate warming and permafrost degradation. However, it is difficult to (i) test this; (ii) establish cause-effect relationships; and (iii) determine associated lag-times, due to both temporal and spatial biases in detection rates. Here we applied the Google Earth Engine supraglacial debris input detector (GERALDINE) to Glacier Bay National Park & Preserve (GLBA), Alaska. We find that the number of rock ava-lanches (RAs) has previously been underestimated by 53 %, with a bias in past detections towards large area RAs. In total, GLBA experienced 69 RAs during 1984-2020, with the highest frequency in the last three years. Of these, 58 % were deposited into the accumulation zone and then sequestered into the ice within two years. RA sources clustered spatially at high elevations and around certain peaks and ridges, predominantly at the boundary of modelled permafrost likelihood. They also clustered temporally, occurring mainly between May and September when air temperatures were high enough to initiate rock-permafrost degradation mechanisms. There was a chronic background debris supply from RAs, with at least one RA occurring in all but nine years; however, a debris rich period during 2012-2016 was driven by three large RAs delivering 44 % of all (1984-2020) debris (by area). Comparable investigation of slope-failures in other remote currently glaciated regions is lacking. If RA rates are similar elsewhere, especially the bias towards emplacement onto/into accumulation zones, their contribution to glacial sediment budgets has been globally underestimated.

Automated summary

The frequency of large supraglacial landslides in glacial environments is increasing due to climate warming and permafrost degradation. However, detection biases make it difficult to test, establish cause-effect relationships, and determine lag-times. In this study, the Google Earth Engine was used to analyze Glacier Bay National Park & Preserve in Alaska, revealing an underestimation of rock avalanches (RAs) by 53% and a bias towards large area RAs. RA sources clustered spatially at high elevations and temporally between May and September, when air temperatures were high enough to initiate rock-permafrost degradation mechanisms. Understanding the global contribution of RAs to glacial sediment budgets requires further investigation in other glaciated regions.