Uncertainty in three dimensions: the challenges of communicating probabilistic flood forecast maps

<p>Real-time operational flood forecasting most often concentrates on issuing streamflow predictions at specific points along the rivers of a watershed. However, we are now witnessing an increasing number of studies aimed at also including flood mapping as part of the forecasting system. While...

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Main Authors: V. Jean, M.-A. Boucher, A. Frini, D. Roussel
Format: Article
Language:English
Published: Copernicus Publications 2023-09-01
Series:Hydrology and Earth System Sciences
Online Access:https://hess.copernicus.org/articles/27/3351/2023/hess-27-3351-2023.pdf
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author V. Jean
M.-A. Boucher
A. Frini
D. Roussel
author_facet V. Jean
M.-A. Boucher
A. Frini
D. Roussel
author_sort V. Jean
collection DOAJ
description <p>Real-time operational flood forecasting most often concentrates on issuing streamflow predictions at specific points along the rivers of a watershed. However, we are now witnessing an increasing number of studies aimed at also including flood mapping as part of the forecasting system. While this additional new information (flood extent, depth, velocity, etc.) can potentially be useful for decision-makers, it could also be overwhelming. This is especially true for probabilistic and ensemble forecasting systems. While ensemble streamflow forecasts for a given point in space can be visualized relatively easily, the visualization and communication of probabilistic forecasts for water depth and extent pose additional challenges. Confusion typically arises from too much information, counterintuitive interpretation, or simply too much complexity in the representation of the forecast. The communication and visualization of probabilistic streamflow forecasts has been studied in the past, but this is not the case for the probabilistic flood forecast map, which is still an emerging product. In this paper, we synthesize the results of a large-scale survey (28 government representatives, 52 municipalities, 9 organizations, and 38 citizens and farmers, for a total of 140 people) regarding the users' preferences in terms of visualizing probabilistic flood forecasts over an entire river reach. The survey was performed through interviews, during which the interviewees were asked about their needs in terms of hydrological forecasting. We also presented the interviewees with four prototypes representing alternative visualizations of the same probabilistic forecast in order to understand their preferences in terms of colour maps, wording, and the representation of uncertainty. Our results highlight several issues related to the understanding of probabilities in the specific context of visualizing forecasted flood maps. We propose several suggestions for visualizing probabilistic flood maps and also describe potential adaptations for different categories of end users. This study is the first to investigate the visualization of probabilistic flood maps, which are gaining popularity. Given that the interview questions were not tied to a specific geographical location, our findings are applicable outside of the study area and, therefore, to other operational centres interested in providing probabilistic flood forecast maps to decision-making organizations and citizens.</p>
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spelling doaj.art-db85de4b5aba4c5494b860252f76f8742023-09-21T10:04:07ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382023-09-01273351337310.5194/hess-27-3351-2023Uncertainty in three dimensions: the challenges of communicating probabilistic flood forecast mapsV. Jean0M.-A. Boucher1A. Frini2D. Roussel3Unité départementale des sciences de la gestion, Université du Québec à Rimouski, Lévis, CanadaDepartment of Civil and Building Engineering, Université de Sherbrooke, Sherbrooke, CanadaUnité départementale des sciences de la gestion, Université du Québec à Rimouski, Lévis, CanadaQuebec Ministère de l’Environnement et de la Lutte contre les Changements Climatiques, Québec, Canada<p>Real-time operational flood forecasting most often concentrates on issuing streamflow predictions at specific points along the rivers of a watershed. However, we are now witnessing an increasing number of studies aimed at also including flood mapping as part of the forecasting system. While this additional new information (flood extent, depth, velocity, etc.) can potentially be useful for decision-makers, it could also be overwhelming. This is especially true for probabilistic and ensemble forecasting systems. While ensemble streamflow forecasts for a given point in space can be visualized relatively easily, the visualization and communication of probabilistic forecasts for water depth and extent pose additional challenges. Confusion typically arises from too much information, counterintuitive interpretation, or simply too much complexity in the representation of the forecast. The communication and visualization of probabilistic streamflow forecasts has been studied in the past, but this is not the case for the probabilistic flood forecast map, which is still an emerging product. In this paper, we synthesize the results of a large-scale survey (28 government representatives, 52 municipalities, 9 organizations, and 38 citizens and farmers, for a total of 140 people) regarding the users' preferences in terms of visualizing probabilistic flood forecasts over an entire river reach. The survey was performed through interviews, during which the interviewees were asked about their needs in terms of hydrological forecasting. We also presented the interviewees with four prototypes representing alternative visualizations of the same probabilistic forecast in order to understand their preferences in terms of colour maps, wording, and the representation of uncertainty. Our results highlight several issues related to the understanding of probabilities in the specific context of visualizing forecasted flood maps. We propose several suggestions for visualizing probabilistic flood maps and also describe potential adaptations for different categories of end users. This study is the first to investigate the visualization of probabilistic flood maps, which are gaining popularity. Given that the interview questions were not tied to a specific geographical location, our findings are applicable outside of the study area and, therefore, to other operational centres interested in providing probabilistic flood forecast maps to decision-making organizations and citizens.</p>https://hess.copernicus.org/articles/27/3351/2023/hess-27-3351-2023.pdf
spellingShingle V. Jean
M.-A. Boucher
A. Frini
D. Roussel
Uncertainty in three dimensions: the challenges of communicating probabilistic flood forecast maps
Hydrology and Earth System Sciences
title Uncertainty in three dimensions: the challenges of communicating probabilistic flood forecast maps
title_full Uncertainty in three dimensions: the challenges of communicating probabilistic flood forecast maps
title_fullStr Uncertainty in three dimensions: the challenges of communicating probabilistic flood forecast maps
title_full_unstemmed Uncertainty in three dimensions: the challenges of communicating probabilistic flood forecast maps
title_short Uncertainty in three dimensions: the challenges of communicating probabilistic flood forecast maps
title_sort uncertainty in three dimensions the challenges of communicating probabilistic flood forecast maps
url https://hess.copernicus.org/articles/27/3351/2023/hess-27-3351-2023.pdf
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