Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Quantifying melt dynamics on a debris-covered Himalayan glacier using repeated UAS photogrammetry derived DSM and point cloud differencing

Version 1 : Received: 20 July 2020 / Approved: 23 July 2020 / Online: 23 July 2020 (12:00:27 CEST)

How to cite: Mishra, N.; Chaudhuri, G.; Mainali, K.; Mal, S.; Tiruwa, B.; Singh, P. Quantifying melt dynamics on a debris-covered Himalayan glacier using repeated UAS photogrammetry derived DSM and point cloud differencing . Preprints 2020, 2020070555 (doi: 10.20944/preprints202007.0555.v1). Mishra, N.; Chaudhuri, G.; Mainali, K.; Mal, S.; Tiruwa, B.; Singh, P. Quantifying melt dynamics on a debris-covered Himalayan glacier using repeated UAS photogrammetry derived DSM and point cloud differencing . Preprints 2020, 2020070555 (doi: 10.20944/preprints202007.0555.v1).

Abstract

Debris-covered glaciers are a notable feature in the greater Himalaya, and their ongoing mass loss under changing climate will affect the water resources of over a billion people. The current knowledge of the mass balance of Himalayan glaciers is restricted by the paucity of in-situ measurements of glaciers in both space and time, as well as the resolution of satellite remote sensing imageries. Recently, the use of Unmanned Aerial System (UAS) imagery has shown the potential to bridge this gap by enabling very detailed monitoring of inaccessible glacial areas. UAS imagery-based monitoring of Himalayan glaciers has so far been limited to a single glacier in the entire Himalaya, providing a limited understanding of spatial variability in glacier mass balance and driving factors. In the first UAS based glacial mass change estimation in the trans-Himalaya, we conducted two Unmanned Aerial System (UAS) surveys (May and November 2019) over the debris-covered Annapurna III glacier in the Himalaya. We performed Structure-from-Motion (SfM) analysis and utilized differential GPS field observations to derive geometrically accurate point clouds, ortho-mosaics and digital surface models (DSMs). The glacial volumetric loss was estimated from DSM differencing, and the magnitude and spatial variability of glacier surface change was derived from 3-D differencing of point clouds. Results revealed a heterogeneous glacial melt pattern, with an average elevation loss of 0.89 m during the monitored time period. The majority of the glacial tongue exhibited surface lowering except the area above and around the glacial snout that surprisingly exhibited significant elevation gain. Both the highest magnitude of mass loss and the highest spatial variability in mass change was observed in areas with exposed ice-cliffs and supraglacial ponds. Glacial surface velocity derived from manual feature tracking showed velocity ranging from 0-4.1 m. A detailed evaluation of specific areas allowed an improved understanding of the complex interplay of factors leading to observed surface change. Our findings expand the extent of UAS based monitoring of debris-covered glaciers in the Himalaya and conclude that UAS derived 3D topographic products will become increasingly important for monitoring of thinning debris-covered glaciers.

Subject Areas

UAS, debris-covered glacier, trans-Himalaya, aerial photogrammetry, structure from motion, DSM differencing, point cloud differencing, glacial mass balance, ice-cliffs

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