Continuous measurements of valley floor width in mountainous landscapes

Abstract

Abstract. Mountainous landscapes often feature alluviated valleys that control both ecosystem diversity and the distribution of human populations. Alluviated, flat valley floors also play a key role in determining flood hazard in these landscapes. Various mechanisms have been proposed to control the spatial distribution and width of valley floors, including climatic, tectonic and lithologic drivers. Attributing one of these drivers to observed valley floor widths has been hindered by a lack of reproducible, automated valley extraction methods that allow continuous measurements of valley floor width at regional scales. Here we present a new method for measuring valley floor width in mountain landscapes from digital elevation models (DEMs). This method first identifies valley floors based on thresholds of slope and elevation compared to the modern channel, and uses these valley floors to extract valley centrelines. It then measures valley floor width orthogonal to the centreline at each pixel along the channel. The result is a continuous measurement of valley floor width at every pixel along the valley, allowing us to constrain how valley floor width changes downstream. We demonstrate the ability of our method to accurately extract valley floor widths by comparing with independent Quaternary fluvial deposit maps from sites in the UK and the USA. We find that our method extracts similar downstream patterns of valley floor width to the independent datasets in each site. The method works best in confined valley settings and will not work in unconfined valleys where the valley walls are not easily distinguished from the valley floor. We then test current models of lateral erosion by exploring the relationship between valley floor width and drainage area in the Appalachian Plateau, USA, selected because of its tectonic quiescence and relatively homogeneous lithology. We find that an exponent relating width and drainage area (cv = 0.3 ± 0.06) is remarkably similar across the region and across spatial scales, suggesting that valley floor width evolution is driven by a combination of both valley wall undercutting and wall erosion in the Appalachian Plateau. Finally, we suggest that, similar to common metrics used to explore vertical incision, our method provides the potential to act as a network-scale metric of lateral fluvial response to external forcing.

Drainage reorganization induces deviations in the scaling between valley width and drainage area

“…Despite the different processes that underlie the widening of channels and valleys, empirical observations suggest that the relation between the valley width and drainage area follows a powerlaw scaling similar to Eq. ( 1) (Beeson et al, 2018;Brocard and van der Beek, 2006;Clubb et al, 2022;Langston and Temme, 2019;Langston and Tucker, 2018;May et al, 2013;Schanz and Montgomery, 2016;Snyder et al, 2003;Tomkin et al, 2003). However, the reported range of the exponent d is significantly wider in valleys, ranging between negative values of −0.13 (Clubb et al, 2022) and positive values as high as 1.18 (Beeson et al, 2018).…”

“…Valley widening occurs when the channel migrates and abuts the valley wall, enabling particles from the channel to erode the valley wall. The effectiveness of valley widening is thus controlled by the frequency at which the channel abuts and erodes the valley wall; this depends on the valley width, channel width, and channel mobility within the valley, which increases with sediment flux (Clubb et al, 2022). Despite the different processes that underlie the widening of channels and valleys, empirical observations suggest that the relation between the valley width and drainage area follows a powerlaw scaling similar to Eq.…”

“…( 1) (Beeson et al, 2018;Brocard and van der Beek, 2006;Clubb et al, 2022;Langston and Temme, 2019;Langston and Tucker, 2018;May et al, 2013;Schanz and Montgomery, 2016;Snyder et al, 2003;Tomkin et al, 2003). However, the reported range of the exponent d is significantly wider in valleys, ranging between negative values of −0.13 (Clubb et al, 2022) and positive values as high as 1.18 (Beeson et al, 2018). Here, too, the exponent range was attributed to differences in the properties of valleybounding rocks (Brocard and van der Beek, 2006;Keen-Zebert et al, 2017;Langston and Temme, 2019;Schanz and Montgomery, 2016) or, in some high-relief landscapes, to the spatial distribution of deep-seated landslides that can cause local recession of the valley walls and, at times, dam the valley and cause upstream aggradation and widening (Beeson et al, 2018;Clubb et al, 2022;May et al, 2013).…”

“…In the undisturbed and beheaded categories, the valley width refers to the flat valley bottom that is fully flooded during formative floods, while in the reversed category the valley width typically includes terraces that preserve former levels of the valley bottom (Harel et al, 2019). Unlike the upstream drainage area and slope, which are derived through relatively simple calculations over the digital elevation model (DEM), defining and extracting the valley width based on a DEM is not straightforward and requires a tailored procedure (Clubb et al, 2017(Clubb et al, , 2022Golly and Turowski, 2017;Hilley et al, 2020;Roux et al, 2015;Rowland et al, 2016;Sechu et al, 2021). Particularly, the location and orientation of valley width measurements require caution because the width is often not well-defined in proximity to side tributaries and valley bends (Beeson et al, 2018;Clubb et al, 2022).…”

“…The central role of valley and channel width across disciplines highlights the value of high-resolution width measurements, which could vary by several orders of magnitude within a single basin as well as across basins and landscapes (Schumm and Ethridge, 1994). Producing high-resolution field-based width measurement of channels and valleys is challenging and time-consuming, and in recent years a growing body of work has focused on developing tools for automatic width extraction based on remotely sensed data (e.g., Clubb et al, 2022;Fisher et al, 2013;Gilbert et al, 2016;Hilley et al, 2020;Monegaglia et al, 2018;Roux et al, 2015;Rowland et al, 2016). Although these tools represent a significant advancement in river research and management, they commonly focus on specific types of river morphology and require parameter calibrations, as well as human supervision (Fryirs et al, 2019;Golly and Turowski, 2017).…”