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Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game

Arnal, L., Ramos, M.-H., Coughlan de Perez, E., Cloke, H. ORCID:, Stephens, E., Wetterhall, F., van Andel, S.-J. and Pappenberger, F. (2016) Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game. Hydrology and Earth System Sciences, 20 (8). pp. 3109-3128. ISSN 1027-5606

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To link to this item DOI: 10.5194/hess-20-3109-2016


Probabilistic hydro-meteorological forecasts have over the last decades been used more frequently to communicate forecastuncertainty. This uncertainty is twofold, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic over deterministic forecasts across the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty to transform the probability of occurrence of an event into a binary decision. This paper presents the results of a risk-based decision-making game on the topic of flood protection mitigation, called “How much are you prepared to pay for a forecast?”. The game was played at several workshops in 2015, which were attended by operational forecasters and academics working in the field of hydrometeorology. The aim of this game was to better understand the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants’ willingness-to-pay for a forecast, the results of the game show that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers.

Item Type:Article
Divisions:Interdisciplinary Research Centres (IDRCs) > Walker Institute
Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:65762


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