Monitoring and modelling particle and reach-scale morphological change in gravel-bed rivers: Applications and challenges

This paper focuses on developments in topographic data acquisition, including airborne remote sensing, digital photogrammetry, differential GPS, and laser profiling (e.g. LiDAR) technologies that allow rapid acquisition of high resolution and high precision topographic data sets over a range of spatial scales. These developments have offered new opportunities for investigating spatial and temporal patterns of morphological change in gravel-bed rivers and have contributed to revitalization in three key areas: (1) morphometric estimates of sediment transport and sediment budgeting; (2) boundary conditions for numerical models, including computational fluid dynamics and cellular modelling; (3) three dimensional characterisation of morphology that is independent of flow stage. The potential is clear but there remain a number of significant challenges, including quality control and the effects of error on specific applications and morphologies. This paper presents results from two investigations, representing field and laboratory analyses of gravel-bed river morphology at different spatial scales and for different applications. Case study 1 is concerned with monitoring and modelling morphological change in a large, braided gravel-bed river, using ground-based GPS survey and digital photogrammetry derived from airborne imagery. Case study 2 is an investigation of the mechanisms for infiltration of fine sediment into gravel-bed rivers, which applies close range laser altimetry in flume experiments to derive very high resolution digital elevation models (DEMs) that are used to quantify and analyse changes in bed texture. These case studies highlight the strengths and weaknesses of specific technologies and approaches to analysis of channel and floodplain morphology and change, and suggest key areas that remain to be fully resolved. In particular, the critical need to define a specific threshold level of detection associated with each acquisition method, and for different fluvial settings (e.g. bar surface, sub-aqueous zone), is emphasised.