Articles | Volume 18, issue 6
https://doi.org/10.5194/hess-18-2305-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-18-2305-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
23 Jun 2014
Research article |
| 23 Jun 2014
The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model
C. C. Sampson
School of Geographical Sciences, University of Bristol, BS8 1SS, UK
T. J. Fewtrell
Willis Global Analytics, Willis Group, 51 Lime Street, London, EC3M 7DQ, UK
F. O'Loughlin
School of Geographical Sciences, University of Bristol, BS8 1SS, UK
F. Pappenberger
European Centre for Medium-Range Weather Forecasts, Reading, RG2 9AX, UK
P. B. Bates
School of Geographical Sciences, University of Bristol, BS8 1SS, UK
J. E. Freer
School of Geographical Sciences, University of Bristol, BS8 1SS, UK
H. L. Cloke
Department of Geography and Environmental Science, University of Reading, RG6 6DW, UK
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- Development of Flood Damage Regression Models by Rainfall Identification Reflecting Landscape Features in Gangwon Province, the Republic of Korea H. Choi 10.3390/land10020123
- Toward Global Stochastic River Flood Modeling O. Wing et al. 10.1029/2020WR027692
- Review: Sources of Hydrological Model Uncertainties and Advances in Their Analysis E. Moges et al. 10.3390/w13010028
- The impact of intense rainfall on insurance losses in two Swedish cities B. Blumenthal & L. Nyberg 10.1111/jfr3.12504
- On s-convex bounds for Beta-unimodal distributions with applications to basis risk assessment C. Lefèvre et al. 10.1080/03461238.2020.1852596
- Challenges, Opportunities, and Pitfalls for Global Coupled Hydrologic‐Hydraulic Modeling of Floods S. Grimaldi et al. 10.1029/2018WR024289
- Application of re/insurance models to estimate increases in flood risk due to climate change J. Thistlethwaite et al. 10.1186/s40677-018-0101-9
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- What are the hydro-meteorological controls on flood characteristics? M. Nied et al. 10.1016/j.jhydrol.2016.12.003
- The relationship between precipitation and insurance data for floods in a Mediterranean region (northeast Spain) M. Cortès et al. 10.5194/nhess-18-857-2018
- Predictability of state-level flood damage in the conterminous United States: the role of hazard, exposure and vulnerability Q. Zhou et al. 10.1038/s41598-017-05773-4
- Large‐Sample Evaluation of Radar Rainfall Nowcasting for Flood Early Warning R. Imhoff et al. 10.1029/2021WR031591
- Analysis of large flood events: Based on flood data during 1985–2016 in Australia and India M. Halgamuge & A. Nirmalathas 10.1016/j.ijdrr.2017.05.011
- Extending coupled hydrological-hydraulic model chains with a surrogate model for the estimation of flood losses A. Zischg et al. 10.1016/j.envsoft.2018.08.009
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- Basis risk management and randomly scaled uncertainty M. Mercè Claramunt et al. 10.1016/j.insmatheco.2022.08.005
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- Uncertainty analysis of 100-year flood maps under climate change scenarios S. Alipour et al. 10.1016/j.jhydrol.2023.130502
- Subseasonal variability of mesoscale convective systems over the tropical northeastern Pacific S. Berthet et al. 10.1002/qj.2992
- Effects of variability in probable maximum precipitation patterns on flood losses A. Zischg et al. 10.5194/hess-22-2759-2018
- Reading in the dark: Shifting governmentalities and the spatial dimensions of legible U.S. flood risk T. Brundidge 10.1177/0308518X241232528
- A high-resolution global flood hazard model C. Sampson et al. 10.1002/2015WR016954
46 citations as recorded by crossref.
- A tropical cyclone risk prediction framework using flood susceptibility and tree-based machine learning models: County-level direct economic loss prediction in Guangdong Province J. Yang et al. 10.1016/j.ijdrr.2024.104955
- Intercomparison of global reanalysis precipitation for flood risk modelling F. McClean et al. 10.5194/hess-27-331-2023
- Quantifying the importance of spatial resolution and other factors through global sensitivity analysis of a flood inundation model J. Thomas Steven Savage et al. 10.1002/2015WR018198
- Comprehensive climatic variability analysis and its significance on flood occurrences in the Middle Ganga Plain, India A. Arora et al. 10.1007/s44288-024-00050-0
- Development of Flood Damage Regression Models by Rainfall Identification Reflecting Landscape Features in Gangwon Province, the Republic of Korea H. Choi 10.3390/land10020123
- Toward Global Stochastic River Flood Modeling O. Wing et al. 10.1029/2020WR027692
- Review: Sources of Hydrological Model Uncertainties and Advances in Their Analysis E. Moges et al. 10.3390/w13010028
- The impact of intense rainfall on insurance losses in two Swedish cities B. Blumenthal & L. Nyberg 10.1111/jfr3.12504
- On s-convex bounds for Beta-unimodal distributions with applications to basis risk assessment C. Lefèvre et al. 10.1080/03461238.2020.1852596
- Challenges, Opportunities, and Pitfalls for Global Coupled Hydrologic‐Hydraulic Modeling of Floods S. Grimaldi et al. 10.1029/2018WR024289
- Application of re/insurance models to estimate increases in flood risk due to climate change J. Thistlethwaite et al. 10.1186/s40677-018-0101-9
- Satellite-driven downscaling of global reanalysis precipitation products for hydrological applications H. Seyyedi et al. 10.5194/hess-18-5077-2014
- What are the hydro-meteorological controls on flood characteristics? M. Nied et al. 10.1016/j.jhydrol.2016.12.003
- The relationship between precipitation and insurance data for floods in a Mediterranean region (northeast Spain) M. Cortès et al. 10.5194/nhess-18-857-2018
- Predictability of state-level flood damage in the conterminous United States: the role of hazard, exposure and vulnerability Q. Zhou et al. 10.1038/s41598-017-05773-4
- Large‐Sample Evaluation of Radar Rainfall Nowcasting for Flood Early Warning R. Imhoff et al. 10.1029/2021WR031591
- Analysis of large flood events: Based on flood data during 1985–2016 in Australia and India M. Halgamuge & A. Nirmalathas 10.1016/j.ijdrr.2017.05.011
- Extending coupled hydrological-hydraulic model chains with a surrogate model for the estimation of flood losses A. Zischg et al. 10.1016/j.envsoft.2018.08.009
- Spatiotemporal characteristics and hydrological implications of downscaled hourly precipitation climate scenarios for South Korea T. Lee et al. 10.1002/joc.7300
- Regional flood frequency analysis at the global scale A. Smith et al. 10.1002/2014WR015814
- Economic indicators of hydrologic drought insurance under water demand and climate change scenarios in a Brazilian context G. Mohor & E. Mendiondo 10.1016/j.ecolecon.2017.04.014
- Basis risk management and randomly scaled uncertainty M. Mercè Claramunt et al. 10.1016/j.insmatheco.2022.08.005
- Modulation of Economic Losses From European Floods by the North Atlantic Oscillation S. Zanardo et al. 10.1029/2019GL081956
- Quantification of Uncertainty in Spatial Return Levels of Urban Precipitation Extremes C. Rupa & P. Mujumdar 10.1061/(ASCE)HE.1943-5584.0001583
- South Asia river-flow projections and their implications for water resources C. Mathison et al. 10.5194/hess-19-4783-2015
- A comprehensive assessment of precipitation products: Temporal and spatial analyses over terrestrial biomes in Northeastern Brazil J. de Andrade et al. 10.1016/j.rsase.2022.100842
- Can Atmospheric Reanalysis Data Sets Be Used to Reproduce Flooding Over Large Scales? K. Andreadis et al. 10.1002/2017GL075502
- A deep-learning-technique-based data-driven model for accurate and rapid flood predictions in temporal and spatial dimensions Q. Zhou et al. 10.5194/hess-27-1791-2023
- Quantifying compound flood event uncertainties in a wave and tidally dominated coastal region: The impacts of copula selection, sampling, record length, and precipitation gauge selection J. Lucey & T. Gallien 10.1111/jfr3.12984
- A hybrid approach to improvement of watershed water quality modeling by coupling process–based and deep learning models D. Jeong et al. 10.1002/wer.11079
- Examining the utility of river restoration approaches for flood mitigation and channel stability enhancement: a recent review S. Mondal & P. Patel 10.1007/s12665-018-7381-y
- Calibration of the Global Flood Awareness System (GloFAS) using daily streamflow data F. Hirpa et al. 10.1016/j.jhydrol.2018.09.052
- Guidance on field survey programme design for basement flooding assessment A. Jiang et al. 10.1080/02626667.2020.1782412
- Sensitivity of flood loss estimates to building representation and flow depth attribution methods in micro-scale flood modelling M. Bermúdez & A. Zischg 10.1007/s11069-018-3270-7
- Extreme multi-basin flooding linked with extra-tropical cyclones P. De Luca et al. 10.1088/1748-9326/aa868e
- Flood Indices for Java Island Using Global Satellite Mapping of Precipitation A. Rojali et al. 10.1088/1757-899X/453/1/012072
- The monetary benefit of early flood warnings in Europe F. Pappenberger et al. 10.1016/j.envsci.2015.04.016
- Trace selection method for a best representative in stochastic downscaling of precipitation T. Lee et al. 10.1007/s00704-019-03021-5
- Data quality and uncertainty issues in flood prediction: a systematic review J. Yu et al. 10.1080/17538947.2025.2495738
- Are 2D shallow-water solvers fast enough for early flood warning? A comparative assessment on the 2021 Ahr valley flood event S. Khosh Bin Ghomash et al. 10.5194/nhess-24-2857-2024
- Assessing water options trading willingness in irrigation areas with heterogeneous resource endowments X. Cai et al. 10.1016/j.jhydrol.2022.128471
- Optimizing flood resilience in China’s mountainous areas: Design flood estimation using advanced machine learning techniques X. Wang et al. 10.1016/j.ejrh.2025.102345
- Uncertainty analysis of 100-year flood maps under climate change scenarios S. Alipour et al. 10.1016/j.jhydrol.2023.130502
- Subseasonal variability of mesoscale convective systems over the tropical northeastern Pacific S. Berthet et al. 10.1002/qj.2992
- Effects of variability in probable maximum precipitation patterns on flood losses A. Zischg et al. 10.5194/hess-22-2759-2018
- Reading in the dark: Shifting governmentalities and the spatial dimensions of legible U.S. flood risk T. Brundidge 10.1177/0308518X241232528
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