Articles | Volume 20, issue 8
Hydrol. Earth Syst. Sci., 20, 3109–3128, 2016
https://doi.org/10.5194/hess-20-3109-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue: Effective Science Communication and Education in Hydrology...
Research article
02 Aug 2016
Research article
| 02 Aug 2016
Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game
Louise Arnal et al.
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Cited
25 citations as recorded by crossref.
- Analyses of community willingness-to-pay and the influencing factors towards restoration of River Malaba floodplains A. Mubialiwo et al. 10.1016/j.envc.2021.100160
- Improved error modelling for streamflow forecasting at hourly time steps by splitting hydrographs into rising and falling limbs M. Li et al. 10.1016/j.jhydrol.2017.10.057
- Editorial: Geoscience Communication – Building bridges, not walls S. Illingworth et al. 10.5194/gc-1-1-2018
- Quantification of the Risks on Dam Preliminary Release Based on Ensemble Rainfall Forecasts and Determination of Operation H. Inomata et al. 10.20965/jdr.2018.p0637
- Improving the Reliability of Probabilistic Multi-Step-Ahead Flood Forecasting by Fusing Unscented Kalman Filter with Recurrent Neural Network Y. Zhou et al. 10.3390/w12020578
- Integrating seasonal forecasts into real-time drought management: Júcar River Basin case study S. Suárez-Almiñana et al. 10.1016/j.ijdrr.2021.102777
- Reliable long-range ensemble streamflow forecasts: Combining calibrated climate forecasts with a conceptual runoff model and a staged error model J. Bennett et al. 10.1002/2016WR019193
- Fuzzy Postprocessing to Advance the Quality of Continental Seasonal Hydrological Forecasts for River Basin Management H. Macian-Sorribes et al. 10.1175/JHM-D-19-0266.1
- How Does Seasonal Forecast Performance Influence Decision-Making? Insights from a Serious Game L. Crochemore et al. 10.1175/BAMS-D-20-0169.1
- The Weather Roulette: A Game to Communicate the Usefulness of Probabilistic Climate Predictions M. Terrado et al. 10.1175/BAMS-D-18-0214.1
- How Suitable is Quantile Mapping For Postprocessing GCM Precipitation Forecasts? T. Zhao et al. 10.1175/JCLI-D-16-0652.1
- Enhanced surface water flood forecasts: User‐led development and testing C. Birch et al. 10.1111/jfr3.12691
- Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. 10.1029/2020WR028392
- Residual uncertainty estimation using instance-based learning with applications to hydrologic forecasting O. Wani et al. 10.5194/hess-21-4021-2017
- Can seasonal hydrological forecasts inform local decisions and actions? A decision-making activity J. Neumann et al. 10.5194/gc-1-35-2018
- Toward Improved Probabilistic Predictions for Flood Forecasts Generated Using Deterministic Models X. Jiang et al. 10.1029/2019WR025477
- Creative practice as a tool to build resilience to natural hazards in the Global South A. Van Loon et al. 10.5194/gc-3-453-2020
- “Are we talking just a bit of water out of bank? Or is it Armageddon?” Front line perspectives on transitioning to probabilistic fluvial flood forecasts in England L. Arnal et al. 10.5194/gc-3-203-2020
- Comparison of different quantile regression methods to estimate predictive hydrological uncertainty in the Upper Chao Phraya River Basin, Thailand S. Acharya et al. 10.1111/jfr3.12585
- Value of Information on Resilience Decision-Making in Repeated Disaster Environments N. Dormady et al. 10.1061/(ASCE)NH.1527-6996.0000415
- Coproducing Sea Ice Predictions with Stakeholders Using Simulation B. Blair et al. 10.1175/WCAS-D-21-0048.1
- Probabilistic forecasting based on ensemble forecasts and EMOS method for TGR inflow Y. Zhong et al. 10.1007/s11707-019-0773-9
- A serious gaming approach to understanding household flood risk mitigation decisions J. Gordon & N. Yiannakoulias 10.1111/jfr3.12648
- A Data-Driven Probabilistic Rainfall-Inundation Model for Flash-Flood Warnings T. Pan et al. 10.3390/w11122534
- <i>Breaking the Silos</i>: an online serious game for multi-risk disaster risk reduction (DRR) management M. de Ruiter et al. 10.5194/gc-4-383-2021
25 citations as recorded by crossref.
- Analyses of community willingness-to-pay and the influencing factors towards restoration of River Malaba floodplains A. Mubialiwo et al. 10.1016/j.envc.2021.100160
- Improved error modelling for streamflow forecasting at hourly time steps by splitting hydrographs into rising and falling limbs M. Li et al. 10.1016/j.jhydrol.2017.10.057
- Editorial: Geoscience Communication – Building bridges, not walls S. Illingworth et al. 10.5194/gc-1-1-2018
- Quantification of the Risks on Dam Preliminary Release Based on Ensemble Rainfall Forecasts and Determination of Operation H. Inomata et al. 10.20965/jdr.2018.p0637
- Improving the Reliability of Probabilistic Multi-Step-Ahead Flood Forecasting by Fusing Unscented Kalman Filter with Recurrent Neural Network Y. Zhou et al. 10.3390/w12020578
- Integrating seasonal forecasts into real-time drought management: Júcar River Basin case study S. Suárez-Almiñana et al. 10.1016/j.ijdrr.2021.102777
- Reliable long-range ensemble streamflow forecasts: Combining calibrated climate forecasts with a conceptual runoff model and a staged error model J. Bennett et al. 10.1002/2016WR019193
- Fuzzy Postprocessing to Advance the Quality of Continental Seasonal Hydrological Forecasts for River Basin Management H. Macian-Sorribes et al. 10.1175/JHM-D-19-0266.1
- How Does Seasonal Forecast Performance Influence Decision-Making? Insights from a Serious Game L. Crochemore et al. 10.1175/BAMS-D-20-0169.1
- The Weather Roulette: A Game to Communicate the Usefulness of Probabilistic Climate Predictions M. Terrado et al. 10.1175/BAMS-D-18-0214.1
- How Suitable is Quantile Mapping For Postprocessing GCM Precipitation Forecasts? T. Zhao et al. 10.1175/JCLI-D-16-0652.1
- Enhanced surface water flood forecasts: User‐led development and testing C. Birch et al. 10.1111/jfr3.12691
- Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. 10.1029/2020WR028392
- Residual uncertainty estimation using instance-based learning with applications to hydrologic forecasting O. Wani et al. 10.5194/hess-21-4021-2017
- Can seasonal hydrological forecasts inform local decisions and actions? A decision-making activity J. Neumann et al. 10.5194/gc-1-35-2018
- Toward Improved Probabilistic Predictions for Flood Forecasts Generated Using Deterministic Models X. Jiang et al. 10.1029/2019WR025477
- Creative practice as a tool to build resilience to natural hazards in the Global South A. Van Loon et al. 10.5194/gc-3-453-2020
- “Are we talking just a bit of water out of bank? Or is it Armageddon?” Front line perspectives on transitioning to probabilistic fluvial flood forecasts in England L. Arnal et al. 10.5194/gc-3-203-2020
- Comparison of different quantile regression methods to estimate predictive hydrological uncertainty in the Upper Chao Phraya River Basin, Thailand S. Acharya et al. 10.1111/jfr3.12585
- Value of Information on Resilience Decision-Making in Repeated Disaster Environments N. Dormady et al. 10.1061/(ASCE)NH.1527-6996.0000415
- Coproducing Sea Ice Predictions with Stakeholders Using Simulation B. Blair et al. 10.1175/WCAS-D-21-0048.1
- Probabilistic forecasting based on ensemble forecasts and EMOS method for TGR inflow Y. Zhong et al. 10.1007/s11707-019-0773-9
- A serious gaming approach to understanding household flood risk mitigation decisions J. Gordon & N. Yiannakoulias 10.1111/jfr3.12648
- A Data-Driven Probabilistic Rainfall-Inundation Model for Flash-Flood Warnings T. Pan et al. 10.3390/w11122534
- <i>Breaking the Silos</i>: an online serious game for multi-risk disaster risk reduction (DRR) management M. de Ruiter et al. 10.5194/gc-4-383-2021
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Latest update: 08 Aug 2022
Short summary
Forecasts are produced as probabilities of occurrence of specific events, which is both an added value and a challenge for users. This paper presents a game on flood protection, "How much are you prepared to pay for a forecast?", which investigated how users perceive the value of forecasts and are willing to pay for them when making decisions. It shows that users are mainly influenced by the perceived quality of the forecasts, their need for the information and their degree of risk tolerance.
Forecasts are produced as probabilities of occurrence of specific events, which is both an added...