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Lookup NU author(s): Professor Stuart Barr, Dr Stephen Johnson, Dr Xiaodong MingORCiD, Dr Maria-Valasia PeppaORCiD, Dr Na DongORCiD, Dr Zhenyu Wen, Dr Craig Robson, Dr Luke Smith, Professor Philip James, Professor Darren Wilkinson, Dr Sarah Heaps, Dr Wen Xiao, Professor Richard DawsonORCiD, Professor Raj Ranjan
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2020 S. L. Barr et al.Extreme rainfall events pose an ever increasing threat to cities due to the potential for surface water flooding resulting in damage to properties and major disruption of transport systems. Modern sensor networks offer enormous potential for the real-time monitoring of urban systems and potentially allow improved situational awareness of impeding hazards and their impacts such as flooding. However, monitoring in itself is not enough if we are to be able to adapt in in real-time to hazards. Systems are required that allow analytics and models, that feed of real-time observations, to make predictions of impacts and suggest adaption options ahead of the hazard event. The Flood-PREPARED project is developing a system for real-time adaption to surface water flooding. The system comprises of advanced spatiotemporal models of rainfall, surface water flooding and road traffic impacts. These models are linked and orchestrated within into a Big Data workflow that allows events to be simulated using emerging rainfall data recorded by a short range weather radar. This approach allows nowcasting to be undertaken where predictions of surface water inundation and impacts on the road network can be predicted ahead of the rainfall event reaching the city; thus providing the ability for an improved adaptive response to the actual event.
Author(s): Barr SL, Johnson S, Ming X, Peppa M, Dong N, Wen Z, Robson C, Smith L, James P, Wilkinson D, Heaps S, Laing Q, Xiao W, Dawson R, Ranjan R
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 5th International Conference on Smart Data and Smart Cities
Year of Conference: 2020
Pages: 9-15
Online publication date: 15/09/2020
Acceptance date: 02/04/2018
Date deposited: 28/04/2021
ISSN: 2194-9042
Publisher: Copernicus GmbH
URL: https://doi.org/10.5194/isprs-annals-VI-4-W2-2020-9-2020
DOI: 10.5194/isprs-annals-VI-4-W2-2020-9-2020
Series Title: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
