Derivation of surface grain size is necessary for a variety of applications in river engineering, geomorphology and river ecology. Yet, characterisation of surface grain-size is notoriously problematic due to patchiness, incompatibility between sampling approaches and operational bias. To improve ecological status (viz. the EU Water Framework Directive) there is a need to advance the understanding of geomorphological, hydrological and ecological functional links. There is a need for adaptive tools, and a key question is whether hydromorphology can be characterised at a spatial scale that truly accounts for instream ecological dynamics. At the micro-habitat scale, water flow level in river channels is moderated by the interaction with the roughness of the surface over which it flows. This is vital for benthic community organisation. The interaction is highly complex and remains poorly understood despite its importance. Here, surface roughness has also been measured using a random field of spatial elevation data. The success of this approach has been tempered by the lack of high-resolution topographic data covering all roughness scales; improved data-point resolution is now achievable however, using terrestrial laser scanning technology. The aim here is to reliably quantify instream hydraulic habitat defined by water surface characteristics using random field terrestrial laser scanner x,y,z data. In addition, we look at the applicability of the technology to reac
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