Recommendations for improving integration in national end-to-end flood forecasting systems: An overview of the FFIR (Flooding From Intense Rainfall) programme

David L.A. Flack*, Christopher J. Skinner, Lee Hawkness-Smith, Greg O'Donnell, Robert J. Thompson, Joanne A. Waller, Albert S. Chen, Jessica Moloney, Chloé Largeron, Xilin Xia, Stephen Blenkinsop, Adrian J. Champion, Matthew T. Perks, Niall Quinn, Linda J. Speight

*Corresponding author for this work

Research output: Contribution to journalReview article (Academic Journal)peer-review

7 Citations (Scopus)
193 Downloads (Pure)

Abstract

Recent surface-water and flash floods have caused millions of pounds worth of damage in the UK. These events form rapidly and are difficult to predict due to their short-lived and localised nature. The interdisciplinary Flooding From Intense Rainfall (FFIR) programme investigated the feasibility of enhancing the integration of an end-to-end forecasting system for flash and surface-water floods to help increase the lead time for warnings for these events. Here we propose developments to the integration of an operational end-to-end forecasting system based on the findings of the FFIR programme. The suggested developments include methods to improve radar-derived rainfall rates and understanding of the uncertainty in the position of intense rainfall in weather forecasts; the addition of hydraulic modelling components; and novel education techniques to help lead to effective dissemination of flood warnings. We make recommendations for future advances such as research into the propagation of uncertainty throughout the forecast chain. We further propose the creation of closer bonds to the end users to allow for an improved, integrated, end-to-end forecasting system that is easily accessible for users and end users alike, and will ultimately help mitigate the impacts of flooding from intense rainfall by informed and timely action.

Original languageEnglish
Article number725
Number of pages19
JournalWater (Switzerland)
Volume11
Issue number4
DOIs
Publication statusPublished - 8 Apr 2019

Keywords

  • Data assimilation
  • End-to-end forecasting
  • Flooding
  • Hydraulic modelling
  • Intense rainfall
  • Numerical weather prediction
  • Public outreach
  • Radar

Fingerprint Dive into the research topics of 'Recommendations for improving integration in national end-to-end flood forecasting systems: An overview of the FFIR (Flooding From Intense Rainfall) programme'. Together they form a unique fingerprint.

Cite this