Articles | Volume 3, issue 2
https://doi.org/10.5194/gc-3-203-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gc-3-203-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
“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
Department of Geography and Environmental Science, University of Reading, Reading, UK
European Centre for Medium-Range Weather Forecasts, Reading, UK
now at: Coldwater Laboratory, University of Saskatchewan, Canmore, Alberta, Canada
Liz Anspoks
Incident Management and Resilience, Environment Agency, Warrington, UK
Susan Manson
Flood and Coastal Risk Management Research, Environment Agency, Beverley, UK
Jessica Neumann
Department of Geography and Environmental Science, University of Reading, Reading, UK
Tim Norton
Incident Management and Resilience, Environment Agency, Addington, UK
Elisabeth Stephens
Department of Geography and Environmental Science, University of Reading, Reading, UK
Louise Wolfenden
Incident Management and Resilience, Environment Agency, Bristol, UK
Hannah Louise Cloke
Department of Geography and Environmental Science, University of Reading, Reading, UK
Department of Meteorology, University of Reading, Reading, UK
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Centre of Natural Hazards and Disaster Science, Uppsala, Sweden
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Hybrid forecasting systems combine data-driven methods with physics-based weather and climate models to improve the accuracy of predictions for meteorological and hydroclimatic events such as rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. We review recent developments in hybrid forecasting and outline key challenges and opportunities in the field.
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Water equivalent of snow cover (SWE) is a key variable for water management, hydrological forecasting and climate monitoring. A new Canadian SWE dataset (CanSWE) is presented in this paper. It compiles data collected by multiple agencies and companies at more than 2500 different locations across Canada over the period 1928–2020. Snow depth and derived bulk snow density are also included when available.
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Geosci. Commun., 1, 35–57, https://doi.org/10.5194/gc-1-35-2018, https://doi.org/10.5194/gc-1-35-2018, 2018
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Seasonal hydrological forecasts (SHF) can predict floods, droughts, and water use in the coming months, but little is known about how SHF are used for decision-making. We asked 11 water sector participants what decisions they would make when faced with a possible flood event in 6 weeks' time. Flood forecasters and groundwater hydrologists responded to the flood risk more than water supply managers. SHF need to be tailored for use and communicated more clearly if they are to aid decision-making.
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Hydrol. Earth Syst. Sci., 22, 2057–2072, https://doi.org/10.5194/hess-22-2057-2018, https://doi.org/10.5194/hess-22-2057-2018, 2018
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This paper presents a new operational forecasting system (driven by atmospheric forecasts), predicting river flow in European rivers for the next 7 months. For the first month only, these river flow forecasts are, on average, better than predictions that do not make use of atmospheric forecasts. Overall, this forecasting system can predict whether abnormally high or low river flows will occur in the next 7 months in many parts of Europe, and could be valuable for various applications.
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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.
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hotspotregions that experience these events.
Louise J. Slater, Louise Arnal, Marie-Amélie Boucher, Annie Y.-Y. Chang, Simon Moulds, Conor Murphy, Grey Nearing, Guy Shalev, Chaopeng Shen, Linda Speight, Gabriele Villarini, Robert L. Wilby, Andrew Wood, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 27, 1865–1889, https://doi.org/10.5194/hess-27-1865-2023, https://doi.org/10.5194/hess-27-1865-2023, 2023
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Hybrid forecasting systems combine data-driven methods with physics-based weather and climate models to improve the accuracy of predictions for meteorological and hydroclimatic events such as rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. We review recent developments in hybrid forecasting and outline key challenges and opportunities in the field.
Shaun Harrigan, Ervin Zsoter, Hannah Cloke, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 27, 1–19, https://doi.org/10.5194/hess-27-1-2023, https://doi.org/10.5194/hess-27-1-2023, 2023
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Real-time river discharge forecasts and reforecasts from the Global Flood Awareness System (GloFAS) have been made publicly available, together with an evaluation of forecast skill at the global scale. Results show that GloFAS is skillful in over 93 % of catchments in the short (1–3 d) and medium range (5–15 d) and skillful in over 80 % of catchments in the extended lead time (16–30 d). Skill is summarised in a new layer on the GloFAS Web Map Viewer to aid decision-making.
Gwyneth Matthews, Christopher Barnard, Hannah Cloke, Sarah L. Dance, Toni Jurlina, Cinzia Mazzetti, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 26, 2939–2968, https://doi.org/10.5194/hess-26-2939-2022, https://doi.org/10.5194/hess-26-2939-2022, 2022
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The European Flood Awareness System creates flood forecasts for up to 15 d in the future for the whole of Europe which are made available to local authorities. These forecasts can be erroneous because the weather forecasts include errors or because the hydrological model used does not represent the flow in the rivers correctly. We found that, by using recent observations and a model trained with past observations and forecasts, the real-time forecast can be corrected, thus becoming more useful.
Vincent Vionnet, Colleen Mortimer, Mike Brady, Louise Arnal, and Ross Brown
Earth Syst. Sci. Data, 13, 4603–4619, https://doi.org/10.5194/essd-13-4603-2021, https://doi.org/10.5194/essd-13-4603-2021, 2021
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Water equivalent of snow cover (SWE) is a key variable for water management, hydrological forecasting and climate monitoring. A new Canadian SWE dataset (CanSWE) is presented in this paper. It compiles data collected by multiple agencies and companies at more than 2500 different locations across Canada over the period 1928–2020. Snow depth and derived bulk snow density are also included when available.
Chloe Leach, Tom Coulthard, Andrew Barkwith, Daniel R. Parsons, and Susan Manson
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Numerical models can be used to understand how coastal systems evolve over time, including likely responses to climate change. However, many existing models are aimed at simulating 10- to 100-year time periods do not represent a vertical dimension and are thus unable to include the effect of sea-level rise. The Coastline Evolution Model 2D (CEM2D) presented in this paper is an advance in this field, with the inclusion of the vertical coastal profile against which the water level can be altered.
Chloe Brimicombe, Claudia Di Napoli, Rosalind Cornforth, Florian Pappenberger, Celia Petty, and Hannah L. Cloke
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-242, https://doi.org/10.5194/nhess-2021-242, 2021
Revised manuscript not accepted
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Heatwaves are an increasing risk to African communities. This hazard can have a negative impact on peoples lives and in some cases results in their death. This study shows new information about heatwave characteristics through a list of heatwave events that have been reported for the African continent from 1980 until 2020. Case studies are useful helps to inform the development of early warning systems and forecasting, which is an urgent priority and needs significant improvement.
Jamie Towner, Andrea Ficchí, Hannah L. Cloke, Juan Bazo, Erin Coughlan de Perez, and Elisabeth M. Stephens
Hydrol. Earth Syst. Sci., 25, 3875–3895, https://doi.org/10.5194/hess-25-3875-2021, https://doi.org/10.5194/hess-25-3875-2021, 2021
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We examine whether several climate indices alter the magnitude, timing and duration of floods in the Amazon. We find significant changes in both flood magnitude and duration, particularly in the north-eastern Amazon for negative SST years in the central Pacific Ocean. This response is not repeated when the negative anomaly is positioned further east. These results have important implications for both social and physical sectors working towards the improvement of flood early warning systems.
Sazzad Hossain, Hannah L. Cloke, Andrea Ficchì, Andrew G. Turner, and Elisabeth M. Stephens
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-97, https://doi.org/10.5194/hess-2021-97, 2021
Manuscript not accepted for further review
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Hydrometeorological drivers are investigated to study three different flood types: long duration, rapid rise and high water level of the Brahmaputra river basin in Bangladesh. Our results reveal that long duration floods have been driven by basin-wide rainfall whereas rapid rate of rise due to more localized rainfall. We find that recent record high water levels are not coincident with extreme river flows. Understanding these drivers is key for flood forecasting and early warning.
Shaun Harrigan, Ervin Zsoter, Lorenzo Alfieri, Christel Prudhomme, Peter Salamon, Fredrik Wetterhall, Christopher Barnard, Hannah Cloke, and Florian Pappenberger
Earth Syst. Sci. Data, 12, 2043–2060, https://doi.org/10.5194/essd-12-2043-2020, https://doi.org/10.5194/essd-12-2043-2020, 2020
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A new river discharge reanalysis dataset is produced operationally by coupling ECMWF's latest global atmospheric reanalysis, ERA5, with the hydrological modelling component of the Global Flood Awareness System (GloFAS). The GloFAS-ERA5 reanalysis is a global gridded dataset with a horizontal resolution of 0.1° at a daily time step and is freely available from 1979 until near real time. The evaluation against observations shows that the GloFAS-ERA5 reanalysis was skilful in 86 % of catchments.
Elisabeth M. Stephens, David J. Spiegelhalter, Ken Mylne, and Mark Harrison
Geosci. Commun., 2, 101–116, https://doi.org/10.5194/gc-2-101-2019, https://doi.org/10.5194/gc-2-101-2019, 2019
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The UK Met Office ran an online game to highlight the best methods of communicating uncertainty in their online forecasts and to widen engagement in probabilistic weather forecasting. The game used a randomized design to test different methods of presenting uncertainty and to enable participants to experience being
luckyor
unluckywhen the most likely scenario did not occur. Over 8000 people played the game; we found players made better decisions when provided with forecast uncertainty.
Jamie Towner, Hannah L. Cloke, Ervin Zsoter, Zachary Flamig, Jannis M. Hoch, Juan Bazo, Erin Coughlan de Perez, and Elisabeth M. Stephens
Hydrol. Earth Syst. Sci., 23, 3057–3080, https://doi.org/10.5194/hess-23-3057-2019, https://doi.org/10.5194/hess-23-3057-2019, 2019
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This study presents an intercomparison analysis of eight global hydrological models (GHMs), assessing their ability to simulate peak river flows in the Amazon basin. Results indicate that the meteorological input is the most influential component of the hydrological modelling chain, with the recent ERA-5 reanalysis dataset significantly improving the ability to simulate flood peaks in the Peruvian Amazon. In contrast, calibration of the Lisflood routing model was found to have no impact.
Sazzad Hossain, Hannah L. Cloke, Andrea Ficchì, Andrew G. Turner, and Elisabeth Stephens
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-286, https://doi.org/10.5194/hess-2019-286, 2019
Manuscript not accepted for further review
Jessica L. Neumann, Louise Arnal, Rebecca E. Emerton, Helen Griffith, Stuart Hyslop, Sofia Theofanidi, and Hannah L. Cloke
Geosci. Commun., 1, 35–57, https://doi.org/10.5194/gc-1-35-2018, https://doi.org/10.5194/gc-1-35-2018, 2018
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Seasonal hydrological forecasts (SHF) can predict floods, droughts, and water use in the coming months, but little is known about how SHF are used for decision-making. We asked 11 water sector participants what decisions they would make when faced with a possible flood event in 6 weeks' time. Flood forecasters and groundwater hydrologists responded to the flood risk more than water supply managers. SHF need to be tailored for use and communicated more clearly if they are to aid decision-making.
Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah L. Cloke, Davide Muraro, Christel Prudhomme, Elisabeth M. Stephens, Peter Salamon, and Florian Pappenberger
Geosci. Model Dev., 11, 3327–3346, https://doi.org/10.5194/gmd-11-3327-2018, https://doi.org/10.5194/gmd-11-3327-2018, 2018
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Global overviews of upcoming flood and drought events are key for many applications from agriculture to disaster risk reduction. Seasonal forecasts are designed to provide early indications of such events weeks or even months in advance. This paper introduces GloFAS-Seasonal, the first operational global-scale seasonal hydro-meteorological forecasting system producing openly available forecasts of high and low river flow out to 4 months ahead.
Louise Arnal, Hannah L. Cloke, Elisabeth Stephens, Fredrik Wetterhall, Christel Prudhomme, Jessica Neumann, Blazej Krzeminski, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 22, 2057–2072, https://doi.org/10.5194/hess-22-2057-2018, https://doi.org/10.5194/hess-22-2057-2018, 2018
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This paper presents a new operational forecasting system (driven by atmospheric forecasts), predicting river flow in European rivers for the next 7 months. For the first month only, these river flow forecasts are, on average, better than predictions that do not make use of atmospheric forecasts. Overall, this forecasting system can predict whether abnormally high or low river flows will occur in the next 7 months in many parts of Europe, and could be valuable for various applications.
Erin Coughlan de Perez, Elisabeth Stephens, Konstantinos Bischiniotis, Maarten van Aalst, Bart van den Hurk, Simon Mason, Hannah Nissan, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 21, 4517–4524, https://doi.org/10.5194/hess-21-4517-2017, https://doi.org/10.5194/hess-21-4517-2017, 2017
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Disaster managers would like to use seasonal forecasts to anticipate flooding months in advance. However, current seasonal forecasts give information on rainfall instead of flooding. Here, we find that the number of extreme events, rather than total rainfall, is most related to flooding in different regions of Africa. We recommend several forecast adjustments and research opportunities that would improve flood information at the seasonal timescale in different regions.
Erin Coughlan de Perez, Bart van den Hurk, Maarten K. van Aalst, Irene Amuron, Deus Bamanya, Tristan Hauser, Brenden Jongma, Ana Lopez, Simon Mason, Janot Mendler de Suarez, Florian Pappenberger, Alexandra Rueth, Elisabeth Stephens, Pablo Suarez, Jurjen Wagemaker, and Ervin Zsoter
Hydrol. Earth Syst. Sci., 20, 3549–3560, https://doi.org/10.5194/hess-20-3549-2016, https://doi.org/10.5194/hess-20-3549-2016, 2016
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Many flood disaster impacts could be avoided by preventative action; however, early action is not guaranteed. This article demonstrates the design of a new system of forecast-based financing, which automatically triggers action when a flood forecast arrives, before a potential disaster. We establish "action triggers" for northern Uganda based on a global flood forecasting system, verifying these forecasts and assessing the uncertainties inherent in setting a trigger in a data-scarce location.
Louise Arnal, Maria-Helena Ramos, Erin Coughlan de Perez, Hannah Louise Cloke, Elisabeth Stephens, Fredrik Wetterhall, Schalk Jan van Andel, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 20, 3109–3128, https://doi.org/10.5194/hess-20-3109-2016, https://doi.org/10.5194/hess-20-3109-2016, 2016
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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.
Dave MacLeod, Hannah Cloke, Florian Pappenberger, and Antje Weisheimer
Hydrol. Earth Syst. Sci., 20, 2737–2743, https://doi.org/10.5194/hess-20-2737-2016, https://doi.org/10.5194/hess-20-2737-2016, 2016
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Soil moisture memory is a key aspect of seasonal climate predictions, through feedback between the land surface and the atmosphere. Estimates have been made of the length of soil moisture memory; however, we show here how estimates of memory show large variation with uncertain model parameters. Explicit representation of model uncertainty may then improve the realism of simulations and seasonal climate forecasts.
G. Balsamo, C. Albergel, A. Beljaars, S. Boussetta, E. Brun, H. Cloke, D. Dee, E. Dutra, J. Muñoz-Sabater, F. Pappenberger, P. de Rosnay, T. Stockdale, and F. Vitart
Hydrol. Earth Syst. Sci., 19, 389–407, https://doi.org/10.5194/hess-19-389-2015, https://doi.org/10.5194/hess-19-389-2015, 2015
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ERA-Interim/Land is a global land surface reanalysis covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land includes a number of parameterization improvements in the land surface scheme with respect to the original ERA-Interim and a precipitation bias correction based on GPCP. A selection of verification results show the added value in representing the terrestrial water cycle and its main land surface storages and fluxes.
C. C. Sampson, T. J. Fewtrell, F. O'Loughlin, F. Pappenberger, P. B. Bates, J. E. Freer, and H. L. Cloke
Hydrol. Earth Syst. Sci., 18, 2305–2324, https://doi.org/10.5194/hess-18-2305-2014, https://doi.org/10.5194/hess-18-2305-2014, 2014
F. Wetterhall, F. Pappenberger, L. Alfieri, H. L. Cloke, J. Thielen-del Pozo, S. Balabanova, J. Daňhelka, A. Vogelbacher, P. Salamon, I. Carrasco, A. J. Cabrera-Tordera, M. Corzo-Toscano, M. Garcia-Padilla, R. J. Garcia-Sanchez, C. Ardilouze, S. Jurela, B. Terek, A. Csik, J. Casey, G. Stankūnavičius, V. Ceres, E. Sprokkereef, J. Stam, E. Anghel, D. Vladikovic, C. Alionte Eklund, N. Hjerdt, H. Djerv, F. Holmberg, J. Nilsson, K. Nyström, M. Sušnik, M. Hazlinger, and M. Holubecka
Hydrol. Earth Syst. Sci., 17, 4389–4399, https://doi.org/10.5194/hess-17-4389-2013, https://doi.org/10.5194/hess-17-4389-2013, 2013
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Subject: Geoscience engagement | Keyword: Risk communication
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Geosci. Commun., 7, 195–200, https://doi.org/10.5194/gc-7-195-2024, https://doi.org/10.5194/gc-7-195-2024, 2024
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To allow for more effective use of climate science, this work proposes and evaluates an open-access R code that deploys a measure of how natural hazards (e.g. extreme wind and flooding) co-occur, is obtainable from scientific research and is usable in practice without restricted data (climate or risk) being exposed. The approach can be applied to hazards in various sectors (e.g. road, rail and telecommunications).
Ed Hawkins, Nigel Arnell, Jamie Hannaford, and Rowan Sutton
Geosci. Commun., 7, 161–165, https://doi.org/10.5194/gc-7-161-2024, https://doi.org/10.5194/gc-7-161-2024, 2024
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Climate change can often seem rather remote, especially when the discussion is about global averages which appear to have little relevance to local experiences. But those global changes are already affecting people, even if they do not fully realise it, and effective communication of this issue is critical. We use long observations and well-understood physical principles to visually highlight how global emissions influence local flood risk in one river basin in the UK.
Laura Müller and Petra Döll
Geosci. Commun., 7, 121–144, https://doi.org/10.5194/gc-7-121-2024, https://doi.org/10.5194/gc-7-121-2024, 2024
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To be able to adapt to climate change, stakeholders need to be informed about future uncertain climate change hazards. Using freely available output of global hydrological models, we quantified future local changes in water resources and their uncertainty. To communicate these in participatory processes, we propose using "percentile boxes" to support the development of flexible strategies for climate risk management worldwide, involving stakeholders and scientists.
John K. Hillier and Michiel van Meeteren
Geosci. Commun., 7, 35–56, https://doi.org/10.5194/gc-7-35-2024, https://doi.org/10.5194/gc-7-35-2024, 2024
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Co-RISK is a workshop-based
toolkitto aid the co-creation of joint projects in various sectors (e.g. insurance, rail, power generation) impacted by natural hazard risks. There is a genuine need to quickly convert the latest insights from environmental research into real-world climate change adaptation strategies, and a gap exists for an accessible (i.e. open access, low tech, zero cost) and practical solution tailored to assist with this.
Chloe Brimicombe
Geosci. Commun., 5, 281–287, https://doi.org/10.5194/gc-5-281-2022, https://doi.org/10.5194/gc-5-281-2022, 2022
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Climate change is increasing the risk of weather hazards (i.e. storms and heatwaves). Using open science methods, it is shown that there is a bias in weather hazard reporting in English-language news media. Storms are the weather hazard with the most articles written over the last 5 years. In comparison, wildfires are mentioned most per individual hazard occurrence with climate change. Science and media collaborations could address the bias and improve reporting.
Cited articles
Arnal, L., Ramos, M.-H., Coughlan de Perez, E., Cloke, H. L., Stephens, E., Wetterhall, F., van Andel, S. J., and Pappenberger, F.: Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game, Hydrol. Earth Syst. Sci., 20, 3109–3128, https://doi.org/10.5194/hess-20-3109-2016, 2016.
Bischiniotis, K., van den Hurk, B., Coughlan de Perez, E., Veldkamp, T.,
Guimarães Nobre, G., and Aerts, J.: Assessing Time, Cost and Quality
Trade-Offs in Forecast-Based Action for Floods, Int. J. Disast. Risk Re.,
40, 101252, https://doi.org/10.1016/j.ijdrr.2019.101252, 2019.
Bruen, M., Krahe, P., Zappa, M., Olsson, J., Vehvilainen, B., Kok, K., and
Daamen, K.: Visualizing Flood Forecasting Uncertainty: Some Current European
EPS Platforms-COST731 Working Group 3, Atmos. Sci. Lett., 11, 92–99,
https://doi.org/10.1002/asl.258, 2010.
Buizza, R.: The Value of Probabilistic Prediction, Atmos. Sci. Lett., 9,
36–42, https://doi.org/10.1002/asl.170, 2008.
Cloke, H. L. and Pappenberger, F.: Ensemble Flood Forecasting: A Review, J. Hydrol., 375, 613–26, https://doi.org/10.1016/j.jhydrol.2009.06.005, 2009.
Cloke, H. L., Thielen, J., Pappenberger, F., Nobert, S., Bálint, G.,
Edlund, C., Koistinen, A., de Saint-Aubin, C., Sprokkereef, E., Viel, C.,
Salamon, P., and Buizza, R.: Progress in the Implementation of Hydrological
Ensemble Prediction Systems (HEPS) in Europe for Operational Flood
Forecasting, ECMWF Newsletter No. 121, Autumn, Reading, UK, 20–24, https://doi.org/10.21957/bn6mx5nxfq, 2009.
Dale, M., Ji, Y., Wicks, J., Mylne, K., Pappenberger, F., and Cloke, H. L.:
Applying Probabilistic Flood Forecasting in Flood Incident Management,
Environment Agency Technical Report, Project No. SC090032, Bristol, UK, 97
pp., 2013.
Dale, M. and Wicks, J.: Decision-making with probabilistic flood forecasts, Illustrative guide for using decision-support methods, Project No. SC090032,
Bristol, UK, 63 pp., 2013.
Dale, M., Wicks, J., Mylne, K., Pappenberger, F., Laeger, S., and Taylor,
S.: Probabilistic Flood Forecasting and Decision-Making: An Innovative
Risk-Based Approach, Nat. Hazards, 70, 159–72,
https://doi.org/10.1007/s11069-012-0483-z, 2012.
Davies, A., Hoggart, K., and Lees, L.: Researching Human Geography, 1st
edition, Routledge, London, UK, 384 pp., 2014.
Demeritt, D., Nobert, S., Cloke, H. L., and Pappenberger, F.: The European
Flood Alert System and the Communication, Perception, and Use of Ensemble
Predictions for Operational Flood Risk Management, Hydrol. Process., 27,
147–57, https://doi.org/10.1002/hyp.9419, 2013.
Demeritt, D., Nobert, S., Cloke, H. L., and Pappenberger, F.: Challenges in
Communicating and Using Ensembles in Operational Flood Forecasting,
Meteorol. Appl., 17, 209–22, https://doi.org/10.1002/met.194, 2010.
Department for Environment Food and Rural Affairs: The National
Flood Emergency Framework for England, 1–105, HMSO, London, UK, available at: https://www.gov.uk/government/publications/the-national-flood-emergency-framework-for-england (last access: 10 August 2020), 2014.
Dessai, S. and Hulme, M.: Climate Policy Does Climate Adaptation Policy Need Probabilities? Does Climate Adaptation Policy Need Probabilities?,
Clim. Policy, 4, 107–28, https://doi.org/10.1080/14693062.2004.9685515, 2004.
Duan, Q., Pappenberger, F., Wood, A., Cloke, H. L., and Schaake, J.:
Handbook of Hydrometeorological Ensemble Forecasting, Springer, Berlin,
Heidelberg, 1521 pp., https://doi.org/10.1007/978-3-642-39925-1, 2019.
Environment Agency: Creating a Better Place – Our Ambition to 2020, available at: https://www.gov.uk/government/publications/environment-agency-our-ambition-to-2020 (last access: 10 August 2020),
2018.
Faulkner, H., Parker, D., Green, C., and Beven, K.: Developing a
translational discourse to communicate uncertainty in flood risk between
science and the practitioner, AMBIO: a Journal of the Human Environment, 36,
8, 692–704, https://doi.org/10.1579/0044-7447(2007)36[692:DATDTC]2.0.CO;2, 2007.
FFC (Flood Forecasting Centre): Flood Guidance Statement User Guide, available at: http://www.ffc-environment-agency.metoffice.gov.uk/services/FGS_User_Guide.pdf, last access: 10 August 2020.
Flood and Water Management Act 2010, c. 29, available at: https://www.legislation.gov.uk/ukpga/2010/29/contents (last access: 10 August 2020), 2010.
Flowerdew, J., Horsburgh, K., and Mylne, K.: Ensemble Forecasting of Storm
Surges, Mar. Geod., 32, 91–99, https://doi.org/10.1080/01490410902869151, 2009.
Fundel, V. J., Fleischhut, N., Herzog, S. M., Göber, M., and Hagedorn,
R.: Promoting the use of probabilistic weather forecasts through a dialogue
between scientists, developers and end-users, Q. J. Roy. Meteor. Soc., 145,
210–231, https://doi.org/10.1002/qj.3482, 2019.
Funtowicz, S. O. and Ravetz, J. R.: Science for the Post-Normal Age, Futures, 25, 739–55, https://doi.org/10.1016/0016-3287(93)90022-L, 1993.
Gold, I. and Connolly, S.: Forecasting coastal overtopping: What's the worst that can happen?, 3rd International Conference on Protection
against Overtopping, 6–8 June 2018, Grange-over-Sands, UK, 2018.
Golding, N., Hewitt, C., Zhang, P., Bett, P., Fang, X., Hu, H., and Nobert,
S.: Improving User Engagement and Uptake of Climate Services in China,
Climate Services, 5, 39–45, https://doi.org/10.1016/j.cliser.2017.03.004, 2017.
Handmer, J. and Proudley, B.: Communicating uncertainty via probabilities: The case of weather forecasts, Environ. Hazards, 7, 2, 79–87, https://doi.org/10.1016/j.envhaz.2007.05.002, 2007.
HM Government: National Flood Resilience Review, HMSO, London, UK, available at: https://www.gov.uk/government/publications/national-flood-resilience-review (last access: 10 August 2020), 2016.
House of Commons – Environment Food and Rural Affairs Committee: Future Flood Prevention – Second Report of Session 2016–17, HMSO, London, UK, available at: https://publications.parliament.uk/pa/cm201617/cmselect/cmenvfru/115/115.pdf (last access: 10 August 2020), 2016.
Joslyn, S. and Savelli, S.: Communicating Forecast Uncertainty: Public Perception of Weather Forecast Uncertainty, Meteorol. Appl., 17, 180–95,
https://doi.org/10.1002/met.190, 2010.
Joslyn, S., Savelli, S., and Nadav-Greenberg, L.: Reducing probabilistic
weather forecasts to the worst-case scenario: Anchoring effects, J. Exp.
Psychol.: Applied, 17, 4, 342–353, https://doi.org/10.1037/a0025901, 2011.
McCarthy, S., Tunstall, S., Parker, D., Faulkner, H., and Howe, J.: Risk
communication in emergency response to a simulated extreme flood,
Environ. Hazards, 7, 179–192, https://doi.org/10.1016/j.envhaz.2007.06.003, 2007.
McEwen, L. J., Krause, F., Jones, O., and Garde Hansen, J.: Sustainable
Flood Memories, Informal Knowledge and the Development of Community
Resilience to Future Flood Risk, WIT Trans. Ecol. Envir., 159, 253–64,
https://doi.org/10.2495/FRIAR120211, 2012.
Michaels, S.: Probabilistic Forecasting and the Reshaping of Flood Risk
Management, Journal of Natural Resources Policy Research, 7, 41–51,
https://doi.org/10.1080/19390459.2014.970800, 2014.
Morss, R. E., Wilhelmi, O. V., Downton, M. W., and Gruntfest, E.: Flood
Risk, Uncertainty, and Scientific Information for Decision Making: Lessons
from an Interdisciplinary Project, B. Am. Meteorol. Soc., 86, 1593–1602,
https://doi.org/10.1175/BAMS-86-11-1593, 2005.
Mu, D., Kaplan, T. R., and Dankers, R.: Decision making with risk-based
weather warnings, Int. J. Disast. Risk Re., 30, 59–73, https://doi.org/10.1016/j.ijdrr.2018.03.030, 2018.
Mulder, K. J., Lickiss, M., Harvey, N., Black, A., Charlton-Perez, A.,
Dacre, H., and McCloy, R.: Visualizing Volcanic Ash Forecasts: Scientist and
Stakeholder Decisions Using Different Graphical Representations and
Conflicting Forecasts, Weather Clim. Soc., 9, 333–48,
https://doi.org/10.1175/WCAS-D-16-0062.1, 2017.
Neumann, J. L., Arnal, L., Emerton, R. E., Griffith, H., Hyslop, S., Theofanidi, S., and Cloke, H. L.: Can seasonal hydrological forecasts inform local decisions and actions? A decision-making activity, Geosci. Commun., 1, 35–57, https://doi.org/10.5194/gc-1-35-2018, 2018.
New, M., Lopez, A., Dessai, S., and Wilby, R.: Challenges in Using
Probabilistic Climate Change Information for Impact Assessments: An Example
from the Water Sector, Philos. T. Roy. Soc. A, 365, 2117–31,
https://doi.org/10.1098/rsta.2007.2080, 2007.
Nobert, S., Demeritt, D., and Cloke, H. L.: Informing Operational Flood
Management with Ensemble Predictions: Lessons from Sweden, J. Flood Risk
Manag., 3, 72–79, https://doi.org/10.1111/j.1753-318X.2009.01056.x, 2010.
Orr, P. and Twigger-Ross, C.: Communicating Risk and Uncertainty in Flood Warnings: A Review of Defra/Environment Agency FCERM Literature, Environment
Agency Science Report, Project No. SC070060/SR2, Bristol, UK, 60 pp., 2009.
Pagano, T. C., Hartmann, H. C., and Sorooshian, S.: Seasonal Forecasts and
Water Management in Arizona: A Case Study of the 1997–98 El Niño Event,
29th Annual Water Resources Planning and Management Conference, 21, 1–11,
https://doi.org/10.1061/40430(1999)227, 2004.
Pappenberger, F., Stephens, E., Thielen, J., Salamon, P., Demeritt, D., van
Andel, S. J., Wetterhall, F., and Alfieri, L.: Visualizing Probabilistic
Flood Forecast Information: Expert Preferences and Perceptions of Best
Practice in Uncertainty Communication, Hydrol. Process., 27, 132–46,
https://doi.org/10.1002/hyp.9253, 2013.
Parker, D. J., Priest, S. J., and Tapsell, S. M.: Understanding and
Enhancing the Public's Behavioural Response to Flood Warning Information,
Meteorol. Appl., 114, 103–14, https://doi.org/10.1002/met.119, 2009.
Pidgeon, N. and Fischhoff, B.: The role of social and decision sciences in communicating uncertain climate risks, Nat. Clim. Change, 1, 1, 35–41,
https://doi.org/10.1038/NCLIMATE1080, 2011.
Pielke, R. A. Jr.: Asking the Right Questions: Atmospheric Sciences Research
and Societal Needs, B. Am. Meteorol. Soc., 78, 255–255,
https://doi.org/10.1175/1520-0477(1997)078<0255:ATRQAS>2.0.CO;2, 1997.
Pilling, C., Dodds, V., Cranston, M., Price, D., Harrison, T., and How, A.:
Chapter 9 – Flood Forecasting – A National Overview for Great Britain,
Flood Forecasting – A Global Perspective, edited by: Adams III, T. E., and
Pagano, T. C., Academic Press, 201–47,
https://doi.org/10.1016/B978-0-12-801884-2.00009-8, 2016.
Pitt, M.: Learning Lessons from the 2007 Floods, The Pitt Review,
Cabinet Office, London, UK, 1–205, 2008.
Ramos, M.-H., Mathevet, T., Thielen, J., and Pappenberger, F.: Communicating
Uncertainty in Hydro-Meteorological Forecasts: Mission Impossible?,
Meteorol. Appl., 17, 223–35, https://doi.org/10.1002/met.202, 2010.
Ramos, M. H., van Andel, S. J., and Pappenberger, F.: Do probabilistic forecasts lead to better decisions?, Hydrol. Earth Syst. Sci., 17, 2219–2232, https://doi.org/10.5194/hess-17-2219-2013, 2013.
Rowley, J.: Conducting research interviews, Management Research Review, 35,
3/4, 260–271, https://doi.org/10.1108/01409171211210154, 2012.
Schoenberger, E.: The Corporate Interview as a Research Method in Economic
Geography, Prof. Geogr., 43, 180–89, https://doi.org/10.1111/j.0033-0124.1991.00180.x, 1991.
Sene, K., Huband, M., Chen, Y., and Darch, G.: Probabilistic Flood
Forecasting Scoping Study, R&D Technical Report, Joint Defra/EA Flood and
Coastal Erosion Risk Risk Management R&D Programme, Project No.
FD2901/TR, London, UK, 216 pp., 2007.
Sene, K., Weerts, A., Beven, K., Moore, R. J., Whitlow, C., and Young P.:
Risk-Based Probabilistic Fluvial Flood Forecasting for Integrated Catchment
Models – Phase 1 Report, Environment Agency Science Report, Project No. SC080030/SR1, Bristol, UK, 179 pp., 2009.
Sene, K., Weerts, A., Beven, K., Moore, R. J., and Whitlow, C.: Risk-based
Probabilistic Fluvial Flood Forecasting for Integrated Catchment Models – Phase 3 Implementation Plan, Environment Agency Science Report, Project No.
SR SC080030, Bristol, UK, 35 pp., 2010.
Sivle, A. D., Kolstø, S. D., Hansen, P. J. K., and Kristiansen, J.: How
Do Laypeople Evaluate the Degree of Certainty in a Weather Report? A Case
Study of the Use of the Web Service yr.no., Weather Clim. Soc., 6, 399–412, https://doi.org/10.1175/WCAS-D-12-00054.1, 2014.
Smith, K. A., Wilby, R. L., Broderick, C., Prudhomme, C., Matthews, T.,
Harrigan, S., and Murphy, C.: Navigating Cascades of Uncertainty – As Easy
as ABC? Not Quite..., Journal of Extreme Events, 5, 1850007, https://doi.org/10.1142/S2345737618500070, 2018.
Stephens, E. and Cloke, H. L.: Improving Flood Forecasts for Better Flood Preparedness in the UK (and Beyond), Geogr. J., 180, 310–16,
https://doi.org/10.1111/geoj.12103, 2014.
Stephens, E. M., Edwards, T. L., and Demeritt, D.: Communicating
Probabilistic Information from Climate Model Ensembles-Lessons from
Numerical Weather Prediction, WIREs Clim. Change, 3, 409–26,
https://doi.org/10.1002/wcc.187, 2012.
Thielen, J., Bartholmes, J., Ramos, M.-H., and de Roo, A.: The European Flood Alert System – Part 1: Concept and development, Hydrol. Earth Syst. Sci., 13, 125–140, https://doi.org/10.5194/hess-13-125-2009, 2009.
Thielen, J., Bartholmes, J., and Ramos, M.-H.: The Benefit of Probabilistic
Flood Forecasting on European Scale – Results of the European Flood Alert
System for 2005/2006, European Commission, Ispra, Italy, 99 pp., 2006.
Verkade, J. S. and Werner, M. G. F.: Estimating the benefits of single value and probability forecasting for flood warning, Hydrol. Earth Syst. Sci., 15, 3751–3765, https://doi.org/10.5194/hess-15-3751-2011, 2011.
Werner, M., Cranston, M., Harrison, T., Whitfield, D., and Schellekens, J.:
Recent Developments in Operational Flood Forecasting in England, Wales and
Scotland, Meteorol. Appl., 16, 13–22, https://doi.org/10.1002/met.124, 2009.
Short summary
The Environment Agency (EA), responsible for flood risk management in England, is moving towards the use of probabilistic river flood forecasts. By showing the likelihood of future floods, they can allow earlier anticipation. But making decisions on probabilistic information is complex and interviews with EA decision-makers highlight the practical challenges and opportunities of this transition. We make recommendations to support a successful transition for flood early warning in England.
The Environment Agency (EA), responsible for flood risk management in England, is moving towards...
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