Inferring channel incision in gravel‐bed rivers: Integrating LiDAR data, historical aerial photographs and drone‐based SfM topo‐bathymetry

Abstract

AbstractChannel incision is an evident trend for river evolution in many European rivers and notably the Western Carpathians, whose former braided and multichannel wandering river system is transforming into a single‐thread channel, but it is often difficult to separate drivers and determine if incision is finished or is still ongoing. To overpass these research gaps, this paper presents an innovative approach to assess the multidecadal incision of the Belá River in the Western Carpathians since 1949 by LiDAR‐based analyses of floodplain surfaces above the river channel dated from historical aerial images. Detailed analyses of ongoing incision were also calculated based on DEM of differences (DoD) using Structure‐from‐Motion (SfM) photogrammetry‐derived topo‐bathymetric models. The study applied the BACI (Before‐After‐Control‐Impact) approach that compared pre‐state (Before), post‐state (After) and reach (Control) that is not affected by potential external effects with degraded (impacted) reach to be able to distinguish the driver effects. Floodplain channel surface analyses indicate the maximum incision up to 4 m and incision rate of 5.7 cm/year that occurred in the most degraded reach. Moreover, cross‐section profiles point to accelerated incision of 24.5 cm/year in the last 10 years (2011–2021) by the propagation of incision upstream. Overall, the net changes from the UAV survey pointed to 22 759 m3 of gravel sediments, constituting outwash from the 1.6 km long channel system (2015–2022) by incision, whereas analyses of historical channel surfaces estimated erosion of 573 303 m3 from impacted reaches between 1949 and 2020. Incision evidence is only observed in the downstream part below the control section due to local drivers (channel regulation, comprising embankment and gravel mining that activated a backward erosion of the system with knickpoint migration upstream). This analysis shows the benefits of combining different sources of data to separate long‐term and ongoing channel responses and the BACI‐approach to better target cause–effect relationships in space and time.