Visualizing probabilistic flood forecast information: Expert preferences and perceptions of best practice in uncertainty communication

Florian Pappenberger*, Elisabeth Stephens, Jutta Thielen, Peter Salamon, David Demeritt, Schalk Jan van Andel, Fredrik Wetterhall, Lorenzo Alfieri

*Corresponding author for this work

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

74 Citations (Scopus)

Abstract

The aim of this article is to improve the communication of the probabilistic flood forecasts generated by hydrological ensemble prediction systems (HEPS) by understanding perceptions of different methods of visualizing probabilistic forecast information. This study focuses on interexpert communication and accounts for differences in visualization requirements based on the information content necessary for individual users. The perceptions of the expert group addressed in this study are important because they are the designers and primary users of existing HEPS. Nevertheless, they have sometimes resisted the release of uncertainty information to the general public because of doubts about whether it can be successfully communicated in ways that would be readily understood to nonexperts. In this article, we explore the strengths and weaknesses of existing HEPS visualization methods and thereby formulate some wider recommendations about the best practice for HEPS visualization and communication. We suggest that specific training on probabilistic forecasting would foster use of probabilistic forecasts with a wider range of applications. The result of a case study exercise showed that there is no overarching agreement between experts on how to display probabilistic forecasts and what they consider the essential information that should accompany plots and diagrams. In this article, we propose a list of minimum properties that, if consistently displayed with probabilistic forecasts, would make the products more easily understandable.

Original languageEnglish
Pages (from-to)132-146
Number of pages15
JournalHydrological Processes
Volume27
Issue number1
Early online date23 Apr 2012
DOIs
Publication statusPublished - 1 Jan 2013

Keywords

  • Flood forecasting
  • Hydrological ensemble prediction system
  • Uncertainty
  • Visualising probabilistic information

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