Glacier Ice Thickness Estimation and Future Lake Formation in Swiss Southwestern Alps—The Upper Rhône Catchment: A VOLTA Application

• Published in: Remote sensing (Basel, Switzerland) Vol. 12; no. 20; p. 3443
• Main Authors: Gharehchahi, Saeideh, James, William H. M., Bhardwaj, Anshuman, Jensen, Jennifer L. R., Sam, Lydia, Ballinger, Thomas J., Butler, David R.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.10.2020
• Subjects: Automation; Bedrock; Catchments; Climate change; Datasets; Digital Elevation Models; Error analysis; glacial geomorphology; Glacial lakes; glacier recession; Glaciers; Global climate; ground-penetrating radar (GPR); Ice; Ice cover; Ice thickness; ice thickness distribution; Knowledge management; lake formation; Lakes; Landscape; Mountain regions; Mountains; Parameters; Shear stress; Thickness; Topography; Tourism; Unmanned aerial vehicles; VOLTA; Water management; Water resources; Water resources management; Alps
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs12203443

Glacial lake formations are currently being observed in the majority of glacierized mountains in the world. Given the ongoing climate change and population increase, studying glacier ice thickness and bed topography is a necessity for understanding the erosive power of glacier activity in the past and lake formation in the future. This study uses the available information to predict potential sites for future lake formation in the Upper Rhône catchment located in the Southwestern Swiss Alps. The study integrates the latest available glacier outlines and high-quality digital elevation models (DEMs) into the Volume and Topography Automation (VOLTA) model to estimate ice thickness within the extent of the glaciers. Unlike the previous ice thickness models, VOLTA calculates ice thickness distribution based on automatically-derived centerlines, while optimizing the model by including the valley side drag parameter in the force equation. In this study, a total ice volume of 37.17 ± 12.26 km3 (1σ) was estimated for the Upper Rhône catchment. The comparison of VOLTA performance indicates a stronger relationship between measured and predicted bedrock, confirming the less variability in VOLTA’s results (r2 ≈ 0.92) than Glacier Bed Topography (GlabTop) (r2 ≈ 0.82). Overall, the mean percentage of ice thickness error for all measured profiles in the Upper Rhône catchment is around ±22%, of which 28 out of 42 glaciers are underestimated. By incorporating the vertical accuracy of free-ice DEM, we could identify 171 overdeepenings. Among them, 100 sites have a high potential for future lake formation based on four morphological criteria. The visual evaluation of deglaciated areas also supports the robustness of the presented methodology, as 11 water bodies were already formed within the predicted overdeepenings. In the wake of changing global climate, such results highlight the importance of combined datasets and parameters for projecting the future glacial landscapes. The timely information on future glacial lake formation can equip planners with essential knowledge, not only for managing water resources and hazards, but also for understanding glacier dynamics, catchment ecology, and landscape evolution of high-mountain regions.