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Spatial risk assessment for extreme river flows


  • Caroline Keef
  • Jonathan Tawn
  • Cecilia Svensson


The UK has in recent years experienced a series of fluvial flooding events which have simultaneously affected communities over different parts of the country. For the co-ordination of flood mitigation activities and for the insurance and reinsurance industries, knowledge of the spatial characteristics of fluvial flooding is important. Past research into the spatiotemporal risk of fluvial flooding has largely been restricted to empirical estimates of risk measures. A weakness with such an approach is that there is no basis for extrapolation of these estimates to rarer events, which is required as empirical evidence suggests that larger events tend to be more localized in space. We adopt a model-based approach using the methods of Heffernan and Tawn. However, the large proportion of missing data over a network of sites makes direct application of this method highly inefficient. We therefore propose an extension of the Heffernan and Tawn method which accounts for missing values. Furthermore, as the risk measures are spatiotemporal an extension of the Heffernan and Tawn method is also required to handle temporal dependence. We illustrate the benefits of the procedure with a simulation study and by assessing spatial dependence over four fluvial sites in Scotland. Copyright (c) 2009 Royal Statistical Society.

Suggested Citation

  • Caroline Keef & Jonathan Tawn & Cecilia Svensson, 2009. "Spatial risk assessment for extreme river flows," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(5), pages 601-618.
  • Handle: RePEc:bla:jorssc:v:58:y:2009:i:5:p:601-618

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    References listed on IDEAS

    1. Janet E. Heffernan & Jonathan A. Tawn, 2004. "A conditional approach for multivariate extreme values (with discussion)," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(3), pages 497-546.
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    Cited by:

    1. Marmai, Nadin & Franco Villoria, Maria & Guerzoni, Marco, 2016. "How the Black Swan damages the harvest: statistical modelling of extreme events in weather and crop production in Africa, Asia, and Latin America," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201605, University of Turin.
    2. Keef, Caroline & Papastathopoulos, Ioannis & Tawn, Jonathan A., 2013. "Estimation of the conditional distribution of a multivariate variable given that one of its components is large: Additional constraints for the Heffernan and Tawn model," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 396-404.
    3. Marmai, Nadine, 2016. "Farmers’ investments in innovative technologies in times of precipitation extremes: A statistical analysis for rural Tanzania," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201617, University of Turin.

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