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

Abstract

AbstractIn fluvial research, comparisons of laboratory and field data sets are rare or outdated; therefore, future research would benefit from the integration of laboratory and field data sets.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.