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Nigel Wright
Researcher at Nottingham Trent University
Publications - 142
Citations - 6485
Nigel Wright is an academic researcher from Nottingham Trent University. The author has contributed to research in topics: Flood myth & Computational fluid dynamics. The author has an hindex of 35, co-authored 134 publications receiving 5272 citations. Previous affiliations of Nigel Wright include Durham University & University of Nottingham.
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The food waste hierarchy as a framework for the management of food surplus and food waste
TL;DR: In this paper, the authors examine the factors that give rise to food waste throughout the food supply chain, and propose a framework to identify and prioritize the most appropriate options for prevention and management of food waste.
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A flood vulnerability index for coastal cities and its use in assessing climate change impacts
TL;DR: In this article, the authors developed a Coastal City Flood Vulnerability Index (CCFVI) based on exposure, susceptibility and resilience to coastal flooding, which is applied to nine cities around the world, each with different kinds of exposure.
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On the use of the k–ε model in commercial CFD software to model the neutral atmospheric boundary layer
David J. Hargreaves,Nigel Wright +1 more
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Benchmarking 2D hydraulic models for urban flooding
NM Hunter,Paul D. Bates,S. Neelz,Gareth Pender,Ignacio Villanueva,Nigel Wright,Dongfang Liang,Roger Alexander Falconer,BinLiang Lin,SG Waller,A. J. Crossley,David C. Mason +11 more
TL;DR: In this article, the authors describe benchmark testing of six 2D hydraulic models (DIVAST, DIVASTTVD, TUFLOW, JFLOW and TRENT) in terms of their ability to simulate surface flows in a densely urbanised area.
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Flood vulnerability indices at varying spatial scales.
TL;DR: The methodology developed distinguishes different characteristics at each identified spatial scale, thus allowing a more in-depth analysis and interpretation of local indicators, which leads to some interesting observations on how flood vulnerability can be reflected by quantifiable indicators across scales.