EGU23-17458
https://doi.org/10.5194/egusphere-egu23-17458
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Surface water flood forecast-based loss estimation for resilient finance

Dimosthenis Tsaknias1, Andrew Pledger2, Avinoam Baruch2, and Dapeng Yu2,3
Dimosthenis Tsaknias et al.
  • 1Previsico Limited, Loughborough, United Kingdom (dimos.tsaknias@previsico.com)
  • 2Previsico Limited, Loughborough, United Kingdom
  • 3Loughborough University, Geography and Environment, Loughborough, United Kingdom

Hazard warning systems are being increasingly employed globally, though these fail to account for surface water flooding or flooding from ordinary water courses. Thus, Previsico currently delivers to asset owners a warning and forecast service for surface water flooding at 25m resolution using its proprietary live hydrodynamic modelling software. Flood forecasts are generated every three hours and are produced using the latest rainfall nowcasts (6-hour outlook) and forecasts (48-hour outlook). The service issues property-level alerts so assets can be moved to safety, and organisations can improve their flood response capabilities. However, whilst warnings are important for mitigating physical impacts and losses, they – in isolation – are insufficient for coordinating the responses of insurers, re-insurers, and the wider finance sector. Of particular note, the accuracy of catastrophe claim reserves that depends on correct and timely loss estimates can directly affect the solvency and stability of a company. Loss estimation tools combining flood nowcasting and forecasting for perils that are rarely accounted for (e.g. surface water and ordinary water course flooding) are urgently needed to help insurers and reinsurers make reserving decisions with confidence.

We have therefore developed a loss estimation algorithm parameterised using Previsico’s world-leading forecast and nowcast derived flood extent and depth data and asset exposure and vulnerability data to produce near-present views of financial risk. Loss estimates will in turn be delivered to customers via Previsico’s flood dashboard and email alerts and alongside asset alerts and flood tiles, will support improved flood response capabilities for both the financial sector and associated stakeholders, including property owners and managers.     

How to cite: Tsaknias, D., Pledger, A., Baruch, A., and Yu, D.: Surface water flood forecast-based loss estimation for resilient finance, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-17458, https://doi.org/10.5194/egusphere-egu23-17458, 2023.