Abstract
AbstractSurface 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.This article is categorized under: Engineering Water > Engineering Water
Highlights
Surface water flooding, or pluvial flooding, is defined as “flooding as a result of rainfall when water ponds or flows over the ground before it enters a natural or man-made drainage system or watercourse, or when it cannot enter because the system is already full to capacity” (SEPA, 2009)
The United Kingdom as a whole is relatively unique in its flood risk management approach as they consider surface water flooding separately to flash flooding in steep small catchments; other countries forecast these events on a continuous scale using the same system
We suggest that the adoption of new approaches will require rethinking of established fluvial and coastal flood forecasting practices to deal with short lead times and uncertainty in surface water decision-making
Summary
Pluvial flooding, is defined as “flooding as a result of rainfall when water ponds or flows over the ground before it enters a natural or man-made drainage system or watercourse, or when it cannot enter because the system is already full to capacity” (SEPA, 2009). Understanding the limits of predictability of convection-permitting NWP enables hydrometeorologists to make informed assessments of forecast skill in different weather situations As concluded by Clark et al (2016, p178) “the current state of the art [of convection-permitting NWP] represents a beginning, not a conclusion, and it is anticipated that many advances in various directions will be possible in the future.” In their scoping review of potential options for surface water flood forecasting and warning for the United Kingdom, Priest et al (2011) presented a spectrum of possible approaches ranging from simple rainfall-based alerts at large scales to more complex and targeted impact-based flood warnings at local scales. Based on Henonin, Russo, Mark, and Gourbesville (2013) who classified available approaches based on the use (or not) of hydraulic models, our review is structured using a three-type classification of real-time flood forecasting systems as follows: 1. Empirical-based scenarios: Surface water flood forecasting based on observed or forecast rainfall scenarios, typically based on historical data and evidence of pluvial flooding
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