PalaeoIce: An automated method to reconstruct palaeoglaciers using geomorphic evidence and digital elevation models.

Reconstructing three-dimensional palaeoglacier surface, thickness, and volume provides useful information for quantifying palaeo-climate conditions during glacial stages and assessing the impact of glacier change on water resources. A glacial flowline model has been implemented in Excel and ArcGIS to reconstruct palaeoglaciers based on digital elevation models and geomorphic constraints, such as moraines and trimlines that represent the margins and local heights of palaeoglaciers, respectively. However, significant efforts are still needed in using these tools for palaeoglacier reconstruction, such as digitizing flowlines, adjusting shear stress, and deriving shape factors. This paper presents an automated method, PalaeoIce, to reconstruct palaeoglaciers using geomorphic constraints. Coded in python, PalaeoIce is an ArcGIS toolbox with a set of tools to generate glacial flowlines, optimize shear stress, derive shape factors, calculate ice thickness values along flowlines, and interpolate palaeo ice surfaces based on geomorphic constraints. The use of PalaeoIce is demonstrated using extant glaciers with measured thickness values and moraines/trimlines of the Little Ice Age (LIA) and Marine Isotope Stage (MIS) 2 in the eastern Tian Shan, China. The reconstructed ice thickness values of Glacier No. 1 in this area show a reasonable agreement with field measurements with 1.4 % and 5.4 % differences between measured and reconstructed mean ice thickness values using the two methods included in PalaeoIce: a revised ice thickness model for extant glaciers and a palaeoglacier reconstruction method based on glacier outlines, respectively. Two approaches are then illustrated for palaeoglacier reconstructions using two sets of geomorphic constraints: one with the fully reconstructed glacier outlines during the LIA, and the other with just the terminal moraine and limited trimlines during MIS 2. PalaeoIce can significantly improve the efficiency of palaeoglacier reconstructions and the understanding of the impact of glacier change on water resources. • An automated method, PalaeoIce, is presented for palaeoglacier reconstruction. • Tools are developed to create flowlines, modify DEM, and reconstruct palaeoglaciers. • Reconstructed ice thickness data are validated by field measurements in Tian Shan. • Target geomorphic features are of importance for palaeoglacier reconstruction. [ABSTRACT FROM AUTHOR]