GLACIAL LAKE EVOLUTION BASED ON REMOTE SENSING TIME SERIES: A CASE STUDY OF TSHO ROLPA IN NEPAL

Abstract

Himalayan glaciers have retreated rapidly in recent years. Resultant glacial lakes in the region pose potential catastrophic threats to downstream communities, especially under a changing climate. The potential for Glacial Lake Outburst Floods (GLOFs) has increased and studies have assessed the risks of those in Nepal and prioritised several glacial lakes for urgent and closer investigation. The risk posed by the Tsho Rolpa Glacial Lake is one of the most serious in Nepal. To investigate the feasibility of high-frequency monitoring of glacial lake evolution by remote sensing, this paper proposes a workflow for automated glacial lake boundary extraction and evolution using a time series of Sentinel optical imagery. The waterbody is segmented and vectorised using bimodal histograms from water indices. The vectorised lake boundary is validated against reference data extracted from rigorous contemporary unmanned aerial vehicle (UAV)-based photogrammetric survey. Lake boundaries were subsequently extracted at four different epochs to evaluate the evolution of the lake, especially at the glacier terminus. The final lake area was estimated at 1.61 km2, significantly larger than the areal extent last formally reported. A 0.99 m/day maximum, and a 0.45 m/day average, horizontal glacier retreat rates were estimated. The reported research has demonstrated the potential of remote sensing time series to monitor glacial lake evolution, which is particularly important for lakes in remote mountain regions that are otherwise difficult to access.