Operational and emerging capabilities for surface water flood forecasting

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Speight, Linda J. and Cranston, Michael D. and White, Christopher J. and Kelly, Laura (2021) Operational and emerging capabilities for surface water flood forecasting. Wiley Interdisciplinary Reviews: Water, 8 (3). e1517. ISSN 2049-1948 (https://doi.org/10.1002/wat2.1517)

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Abstract

Surface water (or pluvial) flooding is caused by intense rainfall before it enters rivers or drainage systems. As the climate changes and urban populations grow, the number of people around the world at risk of surface water flooding is increasing. Although it may not be possible to prevent such flooding, reliable and timely flood forecasts can help improve preparedness and recovery. Unlike riverine and coastal flooding where forecasting methods are well established, surface water flood forecasting presents a unique challenge due to the high uncertainties around predicting the location, timing, and impact of what are typically localized events. Over the past 5 years, there has been rapid development of convection-permitting numerical weather prediction models, ensemble forecasting, and computational ability. It is now theoretically feasible to develop operational surface water forecasting systems. This paper identifies three approaches to surface water forecasting utilizing state-of-the-art meteorological forecasts: empirical-based scenarios, hydrological forecasts linked to presimulated impact scenarios, and real-time hydrodynamic simulation. Reviewing operational examples of each approach provides an opportunity to learn from international best practice to develop targeted, impact-based, surface water forecasts to support informed decision-making. Although the emergence of new meteorological and hydrological forecasting capabilities is promising, there remains a scientific limit to the predictability of convective rainfall. To overcome this challenge, we suggest that a rethink of the established role of flood forecasting is needed, alongside the development of interdisciplinary solutions for communicating uncertainty and making the best use of all available data to increase preparedness.

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