Operational and emerging capabilities for surface water flood forecasting

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. This article is categorized under: Engineering Water > Engineering Water

Dynamic Pluvial Flash Flooding Hazard Forecast Using Weather Radar Data

“…Evolving early warning systems for urban areas work with very detailed datawith a spatial resolution of up to 1 square kilometre and a temporal resolution of up to 5 min [34,35]. As input, they use weather radar, rain gauge statins, nowcasting, and a detailed description of the urban environment to prepare predictions using very detailed hydraulic and hydrological models.…”

“…The proposed method uses raw weather radar data only. Nowcasting was not included in the method because it uses weather radar and rain gauge stations, wind profiler, and other weather data and numerical weather prediction models [35]. Thus, if nowcasting is available for the monitored area, more comprehensive tools for flash flooding hazard forecasting will probably be used.…”

“…The estimation of ground precipitation intensity based on radar reflectivity Z measurements is burdened with many uncertainties, increasing with increased distance from the weather radar. The resulting precipitation estimates may, therefore, be significantly overestimated or underestimated [16,35,58]. The analysis, quantification, and impact of these uncertainties on the accuracy of the derived precipitation values have been discussed in numerous publications (e.g., [54,[58][59][60][61]), but research in this area is still running [35].…”

“…The resulting precipitation estimates may, therefore, be significantly overestimated or underestimated [16,35,58]. The analysis, quantification, and impact of these uncertainties on the accuracy of the derived precipitation values have been discussed in numerous publications (e.g., [54,[58][59][60][61]), but research in this area is still running [35].…”

Invited perspectives: challenges and future directions in improving bridge flood resilience

“…Other aspects of flood forecasting, such as surface water flood forecasting (e.g. Speight et al, 2021), and forecasts on longer lead times can also be explored to assess their potential utility and application for bridge resilience. For example, the next generation of forecasts on larger spatial scales, such as the European-wide EFAS flood forecasting system (Wetterhall and Di 450 Giuseppe, 2018), or the global subseasonal-to-seasonal meteorological predictions (White et al, 2017), can be employed to extend existing flood forecast and warning capabilities.…”