Volume change of tropical Peruvian glaciers from multi-temporal digital elevation models and volume–surface area scaling. Issue 3 (3rd July 2017)

• Record Type: Journal Article
• Authors: Huh, Kyung In; Mark, Bryan G.; Ahn, Yushin; Hopkinson, Chris
• Is Part Of: Geografiska annaler. Volume 99:Issue 3(2017)
• Page Start: 222
• Page End: 239
• Publication Date: 2017-07-03
• Subjects: Tropical glaciers -- glacier volume change -- volume–surface area scaling; Physical geography -- Periodicals; 551.4
• DOI: 10.1080/04353676.2017.1313095
• Languages: English
• ISSNs: 0435-3676

Abstract

ABSTRACT: To estimate hydrological storage and better understand the climatic implications of glacier retreat, the volume of glacial ice is a critical but problematic variable. High-accuracy mapping of glacier surface changes over time can directly estimate volume changes, allowing for explicit testing and refining of scaling relationships between changes in glacier volume and surface area that are necessary for making an inventory of remaining glacier mass with remote imagery. A combination of airborne LiDAR, spaceborne remote sensing imagery, digital photogrammetry, and geospatial techniques is used to assess the changes in volume and surface area of six glaciers in the Cordillera Blanca, Peru, between 1962 and 2008. The loss of glacier surface area ranges from 30.79% to 72.62%, corresponding to individual glacier volume changes ranging from 0.019 to 0.150 km 3 . The volume–surface area scaling is deduced from the change in volume related to the change in surface area by a power relationship quantified from 13 different epoch series. The result shows that there is about 36% more volume loss relative to the loss expected from surface area alone of these individual glaciers in the study area than other glaciers in mid- and high-latitudes from the previous study. Since the error of volume estimation shows a much larger impact on the increase with the size of glaciers, volume–surface area scaling analysis needs to include larger ice masses with regional inventories for a more accurate estimation.