Visual characterization technique for gravel-cobble river bed surface sediments; Validation and environmental applications contribution to the Programme of CIRSA (Centre Interuniversitaire de Recherche sur le Saumon Atlantique)

This paper presents an evaluation of the feasibility and the reliability of a visual characterization technique for gravel-cobble river bed surface su bstrate. Based on principal axis regressions, using phi scale (phi), compar isons of visual estimation and grid sampling techniques show that useful pr edictive relations (R-2 = 0.78-0.88) exist between visual estimates of the surface d(16), d(50) and d(84) and estimates obtained for the same percenti les with the grid sampling technique. Comparisons of visual estimation and the surface-bulk sampling technique also indicate a predictive relation (R- 2 = 0.70) between the d(50) Of the two methods. Trained operators can visua lly estimate gravel-cobble bed surface dib to uncertainties of 41 per cent, d(50) to 15 per cent and d(84) to 11 per cent (for example, there is a 5.5 mm error on a d(84) size of 50 mm). Furthermore, evidence shows that if op erators are properly trained, a calibration relation for each percentile ca n be applied independently of operators. This visual characterization allow s effective detailed mapping of spatial patterns in substrate size distribu tion along extensive reaches of gravel-bed rivers. The technique can be ver y useful in creating terrain models for various geomorphological, hydrologi cal and biological applications such as the determination of entrainment th resholds, hydraulic roughness and substrate suitability for benthic insects or salmonid habitat. Copyright (C) 2001 John Wiley & Sons, Ltd.