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Richard Williams
Researcher at University of Glasgow
Publications - 50
Citations - 1205
Richard Williams is an academic researcher from University of Glasgow. The author has contributed to research in topics: Bed load & Acoustic Doppler current profiler. The author has an hindex of 15, co-authored 49 publications receiving 903 citations. Previous affiliations of Richard Williams include Aberystwyth University.
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Hyperscale terrain modelling of braided rivers: fusing mobile terrestrial laser scanning and optical bathymetric mapping
TL;DR: In this paper, the authors present a novel survey methodology that combines mobile terrestrial laser scanning and non-metric aerial photography with data reduction and surface modelling techniques to render DEMs from the resulting very high resolution datasets.
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Hydraulic validation of two-dimensional simulations of braided river flow with spatially continuous aDcp data
TL;DR: In this article, high-resolution topographic survey and hydraulic monitoring at a density commensurate with model discretization can be used to advance hydrodynamic simulations in braided rivers.
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Linking the spatial distribution of bed load transport to morphological change during high‐flow events in a shallow braided river
TL;DR: In this paper, the authors provide novel observations linking the connections between spatially distributed bed load transport pathways, hydraulic patterns, and morphological change in a shallow, gravel bed braided river.
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Assessment of a numerical model to reproduce event‐scale erosion and deposition distributions in a braided river
TL;DR: In this paper, a depth-averaged non-uniform sediment model (Delft3D) was used to predict the morphodynamics of a 2.5 km long reach of the braided Rees River, New Zealand, during a single high-flow event.
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Numerical Modelling of Braided River Morphodynamics: Review and Future Challenges
TL;DR: A taxonomy of braided river morphodynamic models is presented in this paper, with a case study of monitoring and modelling, conducted in the Rees River, New Zealand, and compared to high-resolution, multi-temporal morphological data for assessing 2D physics-based morphodynamic model predictions.