Best Young Researcher Award of the PROLOG 2018, The Logistics Institute, University of Hull, UK
During the PROLOG conference a prize is awarded to the best young researcher.
The Best Young Researcher Award of the PROLOG2018, 4th Edition, at The Logistics Institute, University of Hull, Hull, UK was attributed to:
Tianni WANG,
Liverpool Business School, Liverpool John Moores University, UK
Liverpool Logistics, Offshore and Marine Research Institute, Liverpool John Moores University, UK.
Freight & Logistics Department, AECOM (UK) Ltd, UK
Title of the paper
How Can the UK Road System be Adapted to the Impacts Posed by Climate Change? By Creating a Climate Adaptation Framework
Abstract
This paper aims to analyse the impacts of climate change to the current and predicted future situations of road infrastructure in the UK and evaluate the corresponding adaptation plans to cope with them. A conceptual framework for developing long-term climate change adaptation planning in road systems is proposed to ensure the resilience and sustainability of the road transport systems under various climate risks such as flooding and increased temperature. To do so, an advanced Fuzzy Bayesian Reasoning (FBR) model is first employed to evaluate the climate risks in the UK road transport networks. This modelling approach can overcome the high uncertainty in risk data and thus facilitate the development of the climate adaptation framework and its application in the UK road sector. To examine the feasibility of this model, a national wide survey is conducted among stakeholders to analyse the climate risks, in terms of the timeframe of climate hazards, the likelihood of occurrence, the severity of consequences, and infrastructure resilience. Secondly, an Evidential Reasoning (ER) approach is used to select the best adaptation measures by taking into account the risk analysis results from the FBR and the adaptation costs simultaneously. During this process, a qualitative analysis of several national reports regarding the impacts of climate change, risk assessment and adaptation options in the UK road sector is conducted to collect the relevant decision data (i.e. risk and cost). It is also supplemented by an in-depth interview with a senior planner from Highway England. The findings provide road planners and decision makers with useful insights on identifying and prioritising climate hazards and selecting cost- effective climate adaptation measures to make better adaptation planning.
Keywords: Climate change, adaptation measure, risk analysis, road planning, fuzzy set, Bayesian networks, evidential reasoning.
Co-authors: Zhuohua Qu, Timothy Nichol, Zaili Yang, Delia Dimitriu, Geoff Clarke, Daniel Bowden