Assessing the socio-economic impacts of flash floods for early warning at regional, national, and continental scales

Flash floods are one of the most devastating natural hazards, claiming numerous lives and tremendous economic losses. One of the main reasons for their catastrophic potential is the limited time available for precautionary measures, such as warnings or evacuations. Early warning systems (EWSs) play a key role for emergency managers to react in a timely manner to upcoming floods and effectively mitigate the impacts. This thesis explores possibilities to enhance the methods available for flash flood early warning and thus improve the operational decision support. While a variety of existing methods aims at the prediction of the hazard component of flash floods (e.g. the peak streamflow), an increasing number of EWS developers and end-users have recognised the potential of tools that automatically translate the flash flood hazard forecasts into the expected socio-economic impacts (e.g. the population affected). These so-called impact forecasts enable more objective and rapid decisions, ultimately leading to a more effective flood response. While for fluvial floods, impact forecasts have been available for several years and over various spatial scales, the existing approaches for flash floods have been limited to a small number of prototypes focusing on individual catchments or relatively small regions. These small-scale approaches can be useful for the coordination of local emergency measures, but their potential is limited for supporting the decisions of authorities operating over larger domains (e.g. regional, national, or international civil protection mechanisms). The main goal of this thesis has been to extend the available decision support by applying the concept of flash flood impact forecasting over large spatial scales. Two methods have been developed for estimating the impacts in real time, named ReAFFIRM and ReAFFINE. The two methods take into account that emergency services operating at different spatial scales require different kinds of real-time information to make informed decisions: ReAFFIRM provides detailed impact estimates in high resolution to support regional or national authorities in the coordination of location-specific emergency measures (e.g. evacuations), whereas ReAFFINE generates order-of-magnitude impact estimates with pan-European coverage that can be useful for end-users operating across regions or countries. The application of ReAFFIRM and ReAFFINE for a number of past flood events has demonstrated their capabilities to identify flash flood impacts in real time over the different spatial scales. The developed algorithms have a moderate computational cost and require only datasets that are available throughout the EU, which facilitates the real-time implementation of the methods and their integration into the operational procedures of end-users across Europe. An additional objective of this thesis has been to explore a more integrated perspective of flood early warning. Traditionally, EWSs are designed separately for the different physical processes that lead to flooding (i.e. individual systems for fluvial, pluvial, coastal, and flash floods). This means that the end-users need to monitor a number of separate flood forecasts with potentially even contradicting outputs. Especially during events in which different flood types coincide (so-called compound floods), this can be time-consuming and confusing. The decision support could be significantly simplified by automatically integrating the forecasts of different flood types into an overall compound flood forecast. This idea has been explored through the analysis of a recent catastrophic compound flood, for which the impact estimates from ReAFFIRM have been combined with those from a system designed for fluvial floods. The combined performance of the methods has shown to be superior to the individual performances, clearly demonstrating the potential of such integrated approaches for improving the decision support.Las avenidas torrenciales son una de las amenazas naturales más devastadoras, causando numerosas víctimas y enormes pérdidas económicas. Los sistemas de alerta temprana (SAT) juegan un papel clave para que los servicios de emergencia puedan reaccionar de manera oportuna y mitigar con eficacia los impactos. Esta tesis explora diferentes posibilidades de ampliar los métodos disponibles para la alerta temprana de avenidas torrenciales, con el objetivo de mejorar la toma de decisiones de los servicios de emergencia. Una variedad de métodos se dedica a la predicción del componente de amenaza de las avenidas repentinas (e.g. los caudales máximos instantáneos). No obstante, un número creciente de desarrolladores de SAT y usuarios finales han reconocido el potencial de herramientas que traducen automáticamente estos pronósticos de amenaza en impactos socioeconómicos (e.g. la cantidad de población afectada). Estas predicciones de impacto permiten tomar decisiones más objetivas y rápidas, que conducen a una respuesta más eficaz ante las avenidas y sus consecuencias. Los estudios realizados para la predicción del impacto de avenidas torrenciales han sido limitados a unos pocos prototipos que se enfocan en cuencas individuales o regiones relativamente pequeñas que pueden resultar útiles para la coordinación de medidas de emergencia locales, pero su potencial es limitado para apoyar las decisiones de las autoridades que actúan en dominios más amplios (e.g. autoridades de protección civil regionales, nacionales o europeas). El objetivo principal de esta tesis ha sido extender el apoyo a la toma de decisiones disponible mediante la aplicación del concepto de previsión del impacto de avenidas torrenciales en grandes escalas espaciales. Para ello, se desarrollaron dos métodos para estimar los impactos en tiempo real: ReAFFIRM y ReAFFINE. ReAFFIRM proporciona estimaciones de impacto detalladas y en alta resolución para dar apoyo a las autoridades regionales o nacionales en la coordinación de medidas de emergencia específicas (e.g. evacuaciones), mientras que ReAFFINE genera estimaciones de impacto en órdenes de magnitud con cobertura paneuropea que resultan útiles para los usuarios finales que actúan en grandes dominios espaciales. El uso de ReAFFIRM y ReAFFINE para una serie de inundaciones pasadas ha demostrado su capacidad para identificar los impactos de las avenidas torrenciales en tiempo real y en diferentes escalas espaciales. Los algoritmos desarrollados tienen un coste computacional moderado y solo requieren datos que están disponibles en toda la UE, permitiendo su implementación e integración en los procedimientos operativos de varios usuarios finales en toda Europa. Un objetivo adicional de esta tesis ha sido explorar una perspectiva más integrada de la alerta temprana de inundaciones. Tradicionalmente, los SAT son diseñados por separado para los diferentes procesos físicos que pueden resultar en inundaciones. Esto significa que los usuarios finales deben monitorear una serie de pronósticos de inundaciones por separado con resultados que podrían resultar potencialmente contradictorios, especialmente durante eventos en los que coincidan diferentes tipos de inundaciones (también llamadas inundaciones compuestas). Lo anterior puede alargar los tiempos de respuesta, generar confusión y, en última instancia, impedir una respuesta de emergencia eficaz. El apoyo a la toma de decisiones podría ser simplificada significativamente y de manera automática mediante la integración de los SAT de diferentes tipos de inundaciones en un único pronóstico que las englobe. Esta idea se explora a través de la combinación de las estimaciones de impacto de ReAFFIRM con las de un sistema diseñado para inundaciones fluviales. El rendimiento de ambos métodos combinados ha demostrado ser superior al de cada uno de manera individual, indicando el potencial de combinar el pronóstico de impacto por inundacionesPostprint (published version

ReAFFIRM: Real-time Assessment of Flash Flood Impacts: a Regional high-resolution Method

Flash floods evolve rapidly in time, which poses particular challenges to emergency managers. One way to support decision-making is to complement models that estimate the flash flood hazard (e.g. discharge or return period) with tools that directly translate the hazard into the expected socio-economic impacts. This paper presents a method named ReAFFIRM that uses gridded rainfall estimates to assess in real time the flash flood hazard and translate it into the corresponding impacts. In contrast to other studies that mainly focus on in- dividual river catchments, the approach allows for monitoring entire regions at high resolution. The method consists of the following three components: (i) an already existing hazard module that processes the rainfall into values of exceeded return period in the drainage network, (ii) a flood map module that employs the flood maps created within the EU Floods Directive to convert the return periods into the expected flooded areas and flood depths, and (iii) an impact assessment module that combines the flood depths with several layers of socio- economic exposure and vulnerability. Impacts are estimated in three quantitative categories: population in the flooded area, economic losses, and affected critical infrastructures. The performance of ReAFFIRM is shown by applying it in the region of Catalonia (NE Spain) for three significant flash flood events. The results show that the method is capable of identifying areas where the flash floods caused the highest impacts, while some locations affected by less significant impacts were missed. In the locations where the flood extent corresponded to flood observations, the assessments of the population in the flooded area and affected critical infrastructures seemed to perform reasonably well, whereas the economic losses were systematically overestimated. The effects of different sources of uncertainty have been discussed: from the estimation of the hazard to its translation into impacts, which highly depends on the quality of the employed datasets, and in particular on the quality of the rainfall inputs and the comprehensiveness of the flood maps.Peer ReviewedPostprint (published version

Multiobjective direct policy search using physically based operating rules in multireservoir systems

supplemental_data_wr.1943-5452.0001159_ritter.pdf (492 KB)This study explores the ways to introduce physical interpretability into the process of optimizing operating rules for multireservoir systems with multiple objectives. Prior studies applied the concept of direct policy search (DPS), in which the release policy is expressed as a set of parameterized functions (e.g., neural networks) that are optimized by simulating the performance of different parameter value combinations over a testing period. The problem with this approach is that the operators generally avoid adopting such artificial black-box functions for the direct real-time control of their systems, preferring simpler tools with a clear connection to the system physics. This study addresses this mismatch by replacing the black-box functions in DPS with physically based parameterized operating rules, for example by directly using target levels in dams as decision variables. This leads to results that are physically interpretable and may be more acceptable to operators. The methodology proposed in this work is applied to a network of five reservoirs and four power plants in the Nechi catchment in Colombia, with four interests involved: average energy generation, firm energy generation, flood hazard, and flow regime alteration. The release policy is expressed depending on only 12 parameters, which significantly reduces the computational complexity compared to existing approaches of multiobjective DPS. The resulting four-dimensional Pareto-approximate set offers a variety of operational strategies from which operators may choose one that corresponds best to their preferences. For demonstration purposes, one particular optimized policy is selected and its parameter values are analyzed to illustrate how the physically based operating rules can be directly interpreted by the operators.Peer ReviewedPreprin

Real-time assessment of flash flood impacts at pan-European scale: the ReAFFINE method

The development of early warning systems (EWSs) is a key element for the effective mitigation of flash flood impacts. Emergency managers and other end-users increasingly recognise the benefit of tools that automatically translate the forecasted flash flood hazard (e.g. expressed in terms of peak discharge or return period) into the expected socio-economic impacts (e.g. the affected population). While previous studies aimed at forecasting flash flood impacts at local or regional scales, this paper presents a simple approach for estimating in real time the flash flood impacts at pan-European scale. The proposed method – named ReAFFINE – is designed to be integrated into an EWS for end-users operating over large spatial domains (e.g. across regions or countries). ReAFFINE uses the pan-European flash flood hazard estimates from the ERICHA system to retrieve the potentially flooded areas from the national flood maps (generated in the framework of the EU Floods Directive). By combining the potentially flooded areas with socio-economic exposure information, ReAFFINE estimates in real time the exposed population and critical infrastructures. For two catastrophic flash flood events affecting Europe in recent years, ReAFFINE has demonstrated the capability to identify impacts over large spatial scales. Also at sub-regional level, the method has mostly been able to locate the areas and municipalities where the most important impacts occurred. The results also show that the performance is sensitive to the quality of the rainfall estimates that drive the hazard estimation, and to the comprehensiveness of the employed flood maps.The EU Horizon 2020 project ANYWHERE (H2020-DRS-1-2015-700099) financed the initial period of this work. The study was finalised in the framework of the TAMIR project (UCPM-874435-TAMIR). We would like to express our gratitude to OPERA, WMO and the Spanish State Meteorological Agency (AEMET) for the provision of meteorological data, and the Spanish National Geographic Institute (IGN) and the German Federal Institute of Hydrology (BfG) for access to the national flood maps. Furthermore, we would like to thank OpenStreetMaps, Milan Kalas, and the Joint Research Centre for providing the pan-European exposure datasets, and the European Severe Weather Database (ESWD), the Bavarian Environment Agency (LfU), the Spanish Insurance Compensation Consortium (CCS), the Spanish Directorate-General for Civil Protection and Emergencies (DGPCE), and Jens de Bruijn (Vrije Universiteit Amsterdam) from the Global Flood Monitor for meticulously reporting the impacts of the analysed flood events.Peer ReviewedPostprint (published version

ReAFFIRM: Real-time Assessment of Flash Flood Impacts: a Regional high-resolution Method

Flash floods evolve rapidly in time, which poses particular challenges to emergency managers. One way to support decision-making is to complement models that estimate the flash flood hazard (e.g. discharge or return period) with tools that directly translate the hazard into the expected socio-economic impacts. This paper presents a method named ReAFFIRM that uses gridded rainfall estimates to assess in real time the flash flood hazard and translate it into the corresponding impacts. In contrast to other studies that mainly focus on in- dividual river catchments, the approach allows for monitoring entire regions at high resolution. The method consists of the following three components: (i) an already existing hazard module that processes the rainfall into values of exceeded return period in the drainage network, (ii) a flood map module that employs the flood maps created within the EU Floods Directive to convert the return periods into the expected flooded areas and flood depths, and (iii) an impact assessment module that combines the flood depths with several layers of socio- economic exposure and vulnerability. Impacts are estimated in three quantitative categories: population in the flooded area, economic losses, and affected critical infrastructures. The performance of ReAFFIRM is shown by applying it in the region of Catalonia (NE Spain) for three significant flash flood events. The results show that the method is capable of identifying areas where the flash floods caused the highest impacts, while some locations affected by less significant impacts were missed. In the locations where the flood extent corresponded to flood observations, the assessments of the population in the flooded area and affected critical infrastructures seemed to perform reasonably well, whereas the economic losses were systematically overestimated. The effects of different sources of uncertainty have been discussed: from the estimation of the hazard to its translation into impacts, which highly depends on the quality of the employed datasets, and in particular on the quality of the rainfall inputs and the comprehensiveness of the flood maps.Peer Reviewe