David Wyncoll
HR Wallingford
15 Papers
54 Citations
David Wyncoll is an academic researcher from HR Wallingford. The author has contributed to research in topics: Flood myth & Extreme value theory. The author has an hindex of 6, co-authored 15 publications. Previous affiliations of David Wyncoll include Smith Institute & Lancaster University.
Chat about Author
Papers
First-order uncertainty analysis using Algorithmic Differentiation of morphodynamic models
TL;DR: An efficient first-order second moment method using Algorithmic Differentiation (FOSM) and a Tangent Linear Model (TLM) which can be applied to quantify uncertainty/sensitivities in morphodynamic models is presented.
25
A Bayesian method for improving probabilistic wave forecasts by weighting ensemble members
TL;DR: This paper outlines an application of the Bayesian statistical methodology which combines probabilistic modelling results, new sources of observational data such as GNSS reflectometry and FerryBoxes, which can be combined with an increased availability of more traditional static sensors.
14
Technical Note: Comparison of methods for threshold selection for extreme sea levels
TL;DR: A new automated method is proposed that mimics the enduringly popular visual inspection method, and five different types of statistical threshold selection and their variants are evaluated by comparison to manually derived thresholds, demonstrating that the new method is a useful, complementary tool.
A generic and practical wave overtopping model that includes uncertainty
Tim Pullen,Y. Liu,P. Otinar Morillas,David Wyncoll,Sajni Malde,Ben Gouldby +5 more
- 20 Dec 2018
TL;DR: This paper introduces the next stage in the development of the next generic meta-modelling overtopping model, which reduces uncertainties and gives clear guidance on the range and validity of the outputs.
Applying emulators for improved flood risk analysis
Sajni Malde,David Wyncoll,Jeremy E. Oakley,Nigel Tozer,Ben Gouldby +4 more
- 01 Jan 2016
TL;DR: This paper presents an analysis of the benefits and performance of using a GPE of the SWAN spectral wave transformation model within the context of a coastal flood risk analysis modelling chain and compares the look-up table approach to the GPE to analyse the performance of both approaches.