Articles | Volume 17, issue 7
Research article
13 Jul 2023
Research article |  | 13 Jul 2023

Modelling point mass balance for the glaciers of the Central European Alps using machine learning techniques

Ritu Anilkumar, Rishikesh Bharti, Dibyajyoti Chutia, and Shiv Prasad Aggarwal

Data sets

Fluctuations of Glaciers Database World Glacier Monitoring Service (WGMS)

ERA5-Land hourly data from 1950 to present J. Muñoz Sabater

Short summary
Our analysis demonstrates the capability of machine learning models in estimating glacier mass balance in terms of performance metrics and dataset availability. Feature importance analysis suggests that ablation features are significant. This is in agreement with the predominantly negative mass balance observations. We show that ensemble tree models typically depict the best performance. However, neural network models are preferable for biased inputs and kernel-based models for smaller datasets.