ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume VI-4/W2-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VI-4/W2-2020, 9–15, 2020
https://doi.org/10.5194/isprs-annals-VI-4-W2-2020-9-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VI-4/W2-2020, 9–15, 2020
https://doi.org/10.5194/isprs-annals-VI-4-W2-2020-9-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  15 Sep 2020

15 Sep 2020

FLOOD-PREPARED: A NOWCASTING SYSTEM FOR REAL-TIME IMPACT ADAPTION TO SURFACE WATER FLOODING IN CITIES

S. L. Barr1,2,3, S. Johnson4, X. Ming3, M. Peppa3, N. Dong3, Z. Wen5, C. Robson3, L. Smith3, P. James3, D. Wilkinson4, S. Heaps4, Q. Laing6, W. Xiao3, R. Dawson3, and R. Ranjan5 S. L. Barr et al.
  • 1School of Design, University of Melbourne, Australia
  • 2Australian Urban Research Infrastructure Network (AURIN)
  • 3School of Engineering, Newcastle University, UK
  • 4School of Mathematics, Statistics and Physics, Newcastle University, UK
  • 5School of Computing, Newcastle University, UK
  • 6School of Architecture, Building and Civil Engineering, Loughborough University, UK

Keywords: Real-Time Monitoring, Nowcast Modelling, Flood Impacts, Big Data Workflows

Abstract. 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.