Quantifying the predictability of the timing of jökulhlaups from Merzbacher Lake, Kyrgyzstan

Glacier-dammed lakes can yield subglacial outburst floods (jo¨kulhlaups) repeatedly.
Predicting flood timing is crucial for hazard mitigation, but incomplete understanding of flood-initiation
physics makes this challenging. Here we examine the predictability of the timing of jo¨kulhlaups from
Merzbacher Lake, Kyrgyzstan, using five flood-date prediction models of varying complexity. The
simplest model, which offers a benchmark against which the other models are compared, assumes that
floods occur on the same date each year. The other four models predict flood dates using a floodinitiation
threshold approach and incorporate weather forcing (approximated by the output of two
climate reanalyses) behind the meltwater input to the lake; the most complex of these models accounts
for a moving subglacial water divide beneath the glacier that dams the lake. Each model is optimized
against recorded flood dates to maximize its prediction ability. In terms of their flood prediction ability,
our two best models are those that assume a variable outburst threshold governed by the rate of
meltwater input to the lake and the rate of lake-level rise. They excel over the simplest and most
complex models and correctly predict flood dates to within �20 days 57.4% of the time. We also
quantify the impact of weather uncertainty on prediction success. Our findings can inform practical
flood-forecasting schemes and future investigations of flood-initiation physics.