Abstract. In active mountain belts with steep terrain, bedrock landsliding
is a major erosional agent. In the Himalayas, landsliding is driven by annual
hydro-meteorological forcing due to the summer monsoon and by rarer,
exceptional events, such as earthquakes. Independent methods yield erosion
rate estimates that appear to increase with sampling time, suggesting that
rare, high-magnitude erosion events dominate the erosional budget.
Nevertheless, until now, neither the contribution of monsoon and earthquakes
to landslide erosion nor the proportion of erosion due to rare, giant
landslides have been quantified in the Himalayas. We address these challenges
by combining and analysing earthquake- and monsoon-induced landslide
inventories across different timescales. With time series of 5 m satellite
images over four main valleys in central Nepal, we comprehensively mapped
landslides caused by the monsoon from 2010 to 2018. We found no clear
correlation between monsoon properties and landsliding and a similar mean
landsliding rate for all valleys, except in 2015, where the valleys affected
by the earthquake featured ∼5–8 times more landsliding than the
pre-earthquake mean rate. The long-term size–frequency distribution of
monsoon-induced landsliding (MIL) was derived from these inventories and from
an inventory of landslides larger than ∼0.1 km2 that occurred
between 1972 and 2014. Using a published landslide inventory for the Gorkha
2015 earthquake, we derive the size–frequency distribution for
earthquake-induced landsliding (EQIL). These two distributions are dominated
by infrequent, large and giant landslides but under-predict an estimated
Holocene frequency of giant landslides (> 1 km3) which we
derived from a literature compilation. This discrepancy can be resolved when
modelling the effect of a full distribution of earthquakes of variable
magnitude and when considering that a shallower earthquake may cause larger
landslides. In this case, EQIL and MIL contribute about equally to a total
long-term erosion of ∼2±0.75 mm yr−1 in agreement with most thermo-chronological data.
Independently of the specific total and relative erosion rates, the
heavy-tailed size–frequency distribution from MIL and EQIL and the very large
maximal landslide size in the Himalayas indicate that mean landslide erosion
rates increase with sampling time, as has been observed for independent
erosion estimates. Further, we find that the sampling timescale required to adequately capture the frequency of the largest landslides, which is
necessary for deriving long-term mean erosion rates, is often much longer
than the averaging time of cosmogenic 10Be methods. This
observation presents a strong caveat when interpreting spatial or temporal
variability in erosion rates from this method. Thus, in areas where a very
large, rare landslide contributes heavily to long-term erosion (as the
Himalayas), we recommend 10Be sample in catchments with source
areas > 10 000 km2 to reduce the method mean bias to below
∼20 % of the long-term erosion.
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