Flood control is a multifaceted challenge that requires a comprehensive understanding of the physical, social, and economic factors contributing to flood risk. We learned this the hard way… While advancements have been made in hydrological modeling and infrastructure design, the integration of socioeconomic considerations into flood vulnerability and impact assessments remains crucial for developing effective and equitable flood management strategies.
Flood events can arise from a variety of physical processes, including fluvial (river), pluvial (surface water), and coastal flooding. Although numerous risk assessment approaches stress the importance of accounting for potential combinations of flood types (i.e., compound floods), this awareness has not yet been fully reflected in the development of early warning systems. Existing methods for forecasting flood hazards or the corresponding socioeconomic impacts are generally designed for only one type of flooding, limiting their ability to identify overall hazards or impacts during compound flood events.
From the perspective of end-users, such as civil protection authorities, the monitoring of separate flood forecasts with potentially contradictory outputs can be confusing and time-consuming, ultimately impeding an effective emergency response. To enhance decision support, this article proposes the integration of different flood type-specific approaches into a unified compound flood impact forecast.
Flood events regularly result in devastating impacts on human society, claiming lives and causing substantial economic losses. Climate change projections suggest that the frequency and magnitude of floods will increase in many parts of the world, further exacerbating the impacts on populations and infrastructure. The development of early warning systems (EWSs) is a highly cost-effective way to reduce flood impacts, as they support the coordination of emergency response measures, such as warnings to the population, evacuations, and the installation of temporary flood barriers.
To enable an effective emergency response, the warning information needs to be accurate, easily interpretable, and disseminated in a timely manner to end-users. Flood EWSs generally rely on methods that continuously provide end-users with forecasts of upcoming flood hazards or impacts. Typically, these forecasting methods are based on models representing the physical processes that generate floods, which can vary significantly depending on the type of flooding (e.g., fluvial, flash, pluvial, or coastal).
Due to the differences in the governing physical processes, forecasting approaches are traditionally designed separately for the individual flood types. Fluvial floods, for instance, develop over days or weeks in large river basins and are most commonly forecasted by coupling weather observations and numerical weather prediction (NWP) with distributed hydrological models. In contrast, flash floods have a more sudden onset (minutes to a few hours) and typically occur in small- to medium-sized mountainous catchments, requiring a quick computation and dissemination of the warnings to end-users.
At present, the overwhelming majority of flood forecasting approaches focus on the hazard component of floods, providing information on potential flood locations and magnitudes before the onset of the event. To estimate the expected impacts (e.g., the affected number of people), end-users commonly combine hazard forecasts with socioeconomic exposure and vulnerability information in the areas at risk. In current practice, this combination is often done based on personal knowledge and experience or by means of simple GIS-based tools, which can consume valuable time during approaching events and lead to sub-optimal decisions.
For a more effective and faster emergency response, the World Meteorological Organization (WMO) and the United Nations International Strategy for Disaster Reduction (UNISDR) promote the enhancement of existing tools with components that automatically translate forecasted hazards into expected socioeconomic impacts. The general recipe for impact forecasting is similar across flood types: the forecasted flood hazard is automatically combined with vulnerability and exposure layers, such as population density or land use maps.
Several impact forecasting approaches have been developed in recent years for fluvial floods, flash floods, and other flood types. However, these forecasting approaches remain flood type-specific, while in reality, flood events are often the result of a combination of flood types, also referred to as “compound floods.” The Intergovernmental Panel on Climate Change (IPCC) defines compound events as the combination of multiple drivers and/or hazards that contribute to societal or environmental risk.
Previous studies on compound floods have mostly focused on scenario-based hazard assessments, accounting for different combinations of flood types. However, this awareness has not yet been addressed by the developers of EWSs. At present, forecasting approaches remain flood type-specific, and the end-users’ decision-making process is usually based on a number of separate flood forecasts that may even show contradictory outputs.
Systems that predict compound events in an integrated way, especially in terms of socioeconomic impacts, could significantly improve decision support for end-users. This article proposes the development of a framework that automatically integrates flood type-specific forecasting approaches into one compound flood impact forecast.
To explore the possible advantages and drawbacks of such an integrated system, a severe episode of compound flooding (the 2019 DANA event in south-east Spain) has been analyzed. For this event, a simple real-time-adapted combination of fluvial flood impact simulations from the European Flood Awareness System’s Rapid Risk Assessment (EFAS RRA) and flash flood impact simulations from the ReAFFIRM method has been tested. The resulting simulated compound impacts are compared to impacts reported by satellite images, flood insurers, civil protection authorities, and the media.
This exploratory study allows for identifying potential opportunities and challenges of combining flood type-specific impact forecasting methods and the future developments required to create a full compound flood impact forecast encompassing all common flood types.
The south-eastern part of Spain is characterized by hydrometeorological extremes, experiencing long-lasting droughts as well as torrential rains and floods almost every year. From 11 to 15 September 2019, a weather phenomenon commonly known in Spain as “DANA” or “Gota Fría” affected the region, causing rainfall accumulation of up to 461 mm in 24 h. As a result, devastating floods occurred across eight provinces, with Murcia and Alicante suffering the most severe impacts.
One particularly interesting characteristic of this episode is the high variability in catchment size of the affected streams, representing different flood generation mechanisms: fluvial flooding in the large Segura River basin and flash flooding in smaller tributaries. In addition to fluvial and flash flooding, the DANA event also caused pluvial flooding in several locations, making it a classic example of a compound flood event.
To simulate the compound impacts of the DANA event, the EFAS RRA method has been used to estimate the fluvial flood impacts, and the ReAFFIRM method has been applied to assess the flash flood impacts. EFAS RRA combines weather observations and NWP with the LISFLOOD hydrological model to forecast fluvial flood hazards and automatically translate them into socioeconomic impacts.
ReAFFIRM, on the other hand, uses weather radar data to estimate flash flood hazards and then transforms them into impact assessments, including affected population, economic losses, and critical infrastructure. After introducing the two methods separately, a procedure for combining them to a compound flood impact estimation is presented.
The simulated compound flood extents and impacts are compared to various validation sources, including satellite observations, insurance claim data, and reports from civil protection authorities and the media. This exploratory analysis reveals the potential and limitations of integrating flood type-specific forecasting approaches and provides insights into the future developments required for creating a robust compound flood impact forecast.
One of the key findings is that the combination of the two methods identified the overall compound flood extents and impacts reasonably well, corresponding much better to the observed impacts than the individual methods applied separately. For instance, the simulated economic losses amounted to about €670 million, compared to €425 million of reported insured losses.
However, the compound impact estimates were less accurate at the municipal level, as the uncertainties affecting the individual methods cascaded down to the combined results. Significant overestimations or underestimations of impacts were observed in some municipalities, depending on the specific flood types and their underlying uncertainties.
The results illustrate that integrating flood type-specific impact forecasting methods can improve decision support services during compound flood events. By providing a unified output instead of separate forecasts for different flood types, the end-users’ task of monitoring and interpreting the warning information can be facilitated, enabling a more immediate and effective emergency response.
At the same time, the exploratory analysis highlighted the need for further developments to create a robust compound flood impact forecast. Key aspects include improving the accuracy of the underlying hydrometeorological inputs and flood maps, as well as addressing the challenges of combining forecasting methods with different temporal resolutions and lead times.
Additionally, future efforts should aim at integrating systems designed for other flood types, such as pluvial and coastal floods, to create a comprehensive compound flood impact forecast encompassing all common flood hazards. This would be a significant contribution towards building more resilient societies that can effectively prepare for and respond to natural disasters in the face of a changing climate.
Flood control 2015 is dedicated to providing the latest information and insights on the design, implementation, and maintenance of flood control systems. By integrating socioeconomic considerations into flood vulnerability and impact assessments, this article offers valuable guidance for government agencies, emergency planners, and infrastructure managers in developing effective and equitable flood management strategies.
Example: London Flood Resilience Initiative 2024
