Bridging the lab‐field interface in fluvial morphology at patch‐scale: Using close‐range photogrammetry to assess surface replication and vegetation influence

Abstract

In fluvial research, comparisons of laboratory and field data sets are rare or outdated; therefore, future research would benefit from the integration of laboratory and field data sets. We use close‐range photogrammetry as a tool to help bridge that interface. Close‐range photogrammetry is a technique that is readily applied in both laboratory and field environments to capture submillimetre topographic data of natural and replica surfaces of gravel‐bed rivers. Digital Elevation Models (DEMs) of difference (DoDs) are presented to quantitatively assess the replicability of four surfaces, using the casting process. Replication results with accuracies of <35 mm, including observed localized areas of particle dislodgement, suggest casting is a suitable process to integrate laboratory and field data sets in fluvial morphology, allowing natural surfaces (e.g., from the field) to be analysed in a controlled laboratory environment. This enables the isolation of parameters, such as the microtopography of the surface or water submergence. Further, we highlight the importance of considerations of the wider scale morphology required to contextualize patch‐scale field research using close‐range photogrammetry. We demonstrate this with an example of the influence of vegetation on DEM quality and roughness statistics. These wider morphological features are difficult to simulate in the laboratory, albeit have a control on patch‐scale processes. The successful replication of natural surfaces using casting and the use of tools such as close‐range photogrammetry provide a bridge for future research that requires the integration of laboratory experiments, field experiments, and numerical modelling.

Remote sensing of laboratory rivers

“…For flume and stream table experiments, close‐range photogrammetry is used and typically involves one or two cameras mounted on an instrument cart that moves down the experiment, capturing images at a fixed distance downstream. The approach has been deployed to monitor experiments with braided rivers (Ashmore et al., 2011; Gardner & Ashmore, 2011; Gardner et al., 2018; Leduc et al., 2015; Lindsay & Ashmore, 2002; Stojic et al., 1998), alluvial fans and deltas (van Dijk et al., 2009; van Dijk, Kleinhans, Postma, & Kraal, 2012; Kraal et al., 2008), river meanders (Chandler et al., 2001; Lane et al., 2001), bed structures (Bertin et al., 2015; Butler et al., 2002; Groom & Friedrich, 2018), soil erosion (Heng et al 20102005; Brasington & Smart, 2003; Hancock & Willgoose, 2001a, 2001b; Niemann & Hasbargen, 2005; Rohais et al., 2012; Turowski et al 2006…”

“…While quantifying vegetation size and density itself is important, geomorphologists tend to be more interested in how the experimental riverbed beneath the vegetation is affected by its presence or growth. Field studies using SfM and close‐range photogrammetry found that surface heights were erroneously increased or less accurately measured in the presence of vegetation (Groom & Friedrich, 2018; Woodget et al., 2015). Given the influence of vegetation on the accuracy of SfM and close‐range photogrammetry, laser scanning methods may seem more suited to vegetated experiments.…”

“…For flume and stream table experiments, close-range photogrammetry is used and typically involves one or two cameras mounted on an instrument cart that moves down the experiment, capturing images at a fixed distance downstream. The approach has been deployed to monitor experiments with braided rivers (Ashmore et al, 2011;Gardner et al, 2018;Leduc et al, 2015;Lindsay & Ashmore, 2002;Stojic et al, 1998), alluvial fans and deltas (van Dijk et al, 2009;van Dijk, Kleinhans, Postma, & Kraal, 2012;Kraal et al, 2008), river meanders (Chandler et al, 2001;Lane et al, 2001), bed structures (Bertin et al, 2015;Butler et al, 2002;Groom & Friedrich, 2018), soil erosion (Heng et al2010), and landscape evolution (Babault et al, 2005;Brasington & Smart, 2003;Hancock & Willgoose, 2001a, 2001bNiemann & Hasbargen, 2005;Rohais et al, 2012;Turowski et al2006). Since its first application to experimental fluvial geomorphology by Stojic et al (1998), important developments have included its through-water application by Butler et al (2002), who developed a refraction-correction method, and the work of Han and Endreny (2014), who applied close-range photogrammetry to water surface topography.…”

Human intervention in rivers

“…Hypothetically, detailed velocity measurements around vegetation patches can serve a similar function to estimate flow resistance using GLUE. However, the literature on flow data around real-world vegetation patches are scarce (Naden et al, 2006;Marjoribanks et al, 2017), and comparisons between laboratory and field in general are rare (Huthoff et al, 2013;Groom and Friedrich, 2018).…”