Just over a year ago, one of the most destructive
rock-ice avalanches in Indian Himalaya hit a small
township, tragically wiping out more than 200 lives,
several bridges, roads and two hydroelectric power
Known as the Chamoli disaster, it was unique in its
magnitude. Despite consisting of 80% of rock and only
20% of ice, the avalanche mass was able to travel
around 13km downstream before it turned into a debris
flow, causing a flash flood in the Rishiganga and
Our research started with an interesting observation,
also reported by other studies: the Chamoli disaster
site is a hotspot for avalanches. Scanning through past
satellite images from the last 20 years, we identified
two ice avalanches and several snow avalanches in the
Ice avalanches caused by breakage of a hanging glacier
in early 2000 and again in September 2016 were massive,
consisting of approximately 10 million m³ of glacial
ice, filling around 3.5km of the valley floor with
debris deposits that reached heights of up to 50m.
However, because the Chamoli disaster occurred within
4.5 years of the September 2016 ice avalanche, it
makes the whole scenario even more intriguing.
The 2021 disaster was caused by an avalanche which,
although more than 2.5 times more voluminous than the
2016 event, was made of 80% of rocks contrary to the
pure icy composition of 2016’s avalanche.
The sequence of these two massive and constituently
different ice avalanches, originating from the same
elevation and hitting the same valley within a period
of five years, is unique. It offered us an unprecedented
natural testbed to understand how frequent avalanches,
with varying degree of ice content, can vary in terms
of their run-out and destructive power.
Predicting the future
Adopting an integrative approach, we studied both the
pre-event and during-event flow characteristics of the
2016 and 2021 avalanches. We observed short-term and
long-term changes in the rate of surface movement which
reaches up to over around five times the normal values.
The estimation of surface movements has proven effective
in observing the development and trajectory of ice
avalanches in the past. In 1973, movements were measured
for the first time on an unstable hanging glacier in order
to predict its collapse. The success of this field-based
monitoring approach was demonstrated in 2014 by the accurate
prediction of a hanging glacier “break-off” from the
south face of the Grandes Jorasses in Italy, 10 days before
the avalanche happened.
But logistics issues in these high-mountain areas mean
these kinds of field-based efforts are limited. Our
observations, particularly for the 2016 avalanche, highlight
that remote sensing movement estimations not only have
larger coverage, but can also represent a timely, cost-effective
and safer way to monitor hanging glaciers, and possibly
even predict large and dangerous ice avalanches.
But there are uncertainties associated with remote sensing
observations, and any possible future predictability certainly
requires more research to identify statistically significant
trends in surface movements.
Using a thermomechanical model, we simulated the September
2016 event and the maximum pressure exerted by this event
on the valley. We discovered it was 6,000 kilopascal
(a measurement of compressive strength) – big enough to
make visible changes in the valley profile by adding erodible
sediments, which could worsen any future event.
Seasonal snow avalanches also keep this part of the valley
sufficiently lubricated. We then simulated the 2021 event
under two scenarios: the first without specifying the erosion
characteristics of the remaining avalanche deposits from the
past, and the second with the inclusion of defined erosional zones.
The results indicate that the remaining valley deposits
from past ice and snow avalanches likely aided the volume
and flow of the 2021 rock-ice avalanche – which would
explain its exceptional reach to the downstream population.
Although the past ice avalanches of 2000 and 2016 did not
inflict any direct damage to life and property, they are
recurring events in this valley. But it is difficult to
predict their future impact in combination with other
glacial hazards, such as happened in the Chamoli disaster.
As climate change accelerates globally, such life-threatening
scenarios are developing in other mountain regions too,
with greater frequency and uncertainty. With satellites
providing frequently updating images, understanding any
patterns in these high-mountain hazards could help save
many lives and protect expensive infrastructure in future.
Provided by the IKCEST Disaster Risk Reduction Knowledge Service System