Exploring landscape persistence and erosion dynamics in mountain catchments: A morphometric approach in the Swiss Alps and Blue Ridge Mountains, USA

In recent years, increased theoretical and modelling-based research has explored the persistence of mountain topography and the processes and timescales over which landscapes achieve a stable or ‘steady state’ form. Across various sub-disciplines of geomorphology, amphitheatre or arm-chair-shaped topography has been recognised as a more persistent landscape form, attainable through glacial, periglacial and/or fluvial processes. Once achieved, rates of landscape change may be subdued, or a higher magnitude forcing or event is needed to significantly alter the form. This has yet to be empirically tested in the headwaters of mountain catchments.

This study evaluates the extent to which the morphometrics of catchment headwaters can provide insight into the persistence of mountain landscapes. This is achieved by exploring the dynamic relationships between topographic form and erosion in the Swiss Alps and Blue Ridge Mountains, USA.  We focus on two distinct mountain regions to capture a range of tectonic, climatic, and glacial settings. We use the novel ACME 2.0 GIS tool and high-resolution LiDAR data to characterise the morphometrics (inc. circularity, relief, hilltop curvature, hillslope length) of more than 50 catchments. We introduce a new Headwaters Topographic Form Index (HTFI) derived from these data, which allows us to compare topographic form between diverse mountain environments. To explore the links between form and rates of landscape change, we compare the HTFI and morphometric data with published catchment-averaged erosion rates.

This study aims to explore some of the factors influencing landscape persistence in mountain catchment headwaters, providing new insights into how vulnerable mountain landscapes may respond to ongoing and future climate change. This work has implications for research focused on hillslope stability, mountain hazards (e.g., landsliding), and landscape evolution modelling.