DISCOVER GLACIERS

MOTIVATION OF THIS WORK

In high mountain environments such as the Andes and the Himalayas, glaciers constitute important water resources and are worshipped by Hindu, Buddhist and Andean cultures as sacred, but they are also causes of disastrous natural hazards such as lake outburst floods, posing threats to local communities living downstream. Particularly, debris-covered glaciers have quickly emerged as one of the ‘hot topics’ in glaciology in the last few years, with respect to their response to climate changes, their contribution to future water resources (runoff, streamflow) and potential hazards associated with the formation of potentially dangerous, fast-growing moraine­dammed lakes. There is high urgency in monitoring surface dynamics of these glaciers in order to identify their potential to trigger glacier-related hazards, to assess future water shortages, and to help develop mitigation strategies. These tasks are particularly critical in light of present climate-induced accelerated glacier melt.  The outcomes of this research will be used to help local communities cope with climate-induced glacier changes in the near future.

THE PROJECT

The ‘Debris-cover on glaciers (DISCOVER GLACIERS): Exploring methods to assess climate-induced glacier changes and their impacts’ project is funded by the European Commission Marie-Curie COFUND scheme (2017 – 2020) and is conducted at Aberystwyth University in the UK by Adina Racoviteanu (Ser Cymru II fellow) and PI Neil Glasser. The goal of the DISCOVER GLACIERS project is to identify rapidly changing glaciers, in particular debris-covered glaciers in the Himalayas using the best available remote sensing techniques (object-oriented mapping), and state-of-the art photogrammetric technology (thermal infrared imagery from unnamed aerial vehicles). This project aims at understanding the evolution of surface features such as exposed ice walls and supraglacial lakes, and their contributions to glacier ice melt and to glacier-related hazards such as Glacier Lake Outburst Flood (GLOF) events. Glacier hazard assessments remain sparse in remote high altitude areas such as those targeted here; combining various techniques techniques will allow us to generate metrics that are needed for hazard assessments.

The project is multi-scale (regional to local and its main objectives are:

  •  Identify regions of the Himalaya where glaciers and associated lakes have been changing rapidly in the last decade: Using remote sensing, we aim at updating regional maps of debris covered glaciers and lake extents based on semi-automated methods applied to recent Landsat 8 (30m) and Sentinel-2 imagery (10 m) surface reflectance. This will guide the choice of local areas where more detailed analysis will be performed, using higher resolution images.

 

  • Quantify local-scale topographic factors (local slope and orientation) and surface features (ice walls, debris mounds and supraglacial lakes) : We aim at extracting surface features in a automated fashion using ENVI Feature detection algorithm, applied to Landsat 8 and Sentinel-2 imagery. We are also testing sub-pixel mapping methods for lake delineation applied to Landsat, on the basis of regions of interest extracted from higher resolution Pleiades imagery and PlanetScope very high resolution daily imagery (0.8 – 5 m) granted through the Planet platform API program[1]. We plan to apply sub-pixel method to Landsat thermal infrared imagery, with surface temperature extracted from field unnamed aerial vehicles. This will yield sub-pixel maps of surface morphology as well as surface temperature.

(above):  Surface features on debris covered glaciers in the Khumbu region in the Nepal Himalaya. Photo credit: A. Racoviteanu

  • Assess the hazard potential of selected glacierized basins using an updated hard ranking scheme:  We are compiling existing glacier lake hazard-ranking schemes and are automating existing schemes tested in the Himalayas. We are using a geographic information system (GIS) on the basis of topographic information coupled with glaciological data generated from the first two objectives. We are using high-resolution imagery to extract moraine characteristics to input in the hazard ranking scheme.

 

[1] https://www.planet.com/