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Are your properties located far enough from rivers, sea shorelines or water bodies? If the answer is yes, this does not mean that they are fully safe from flooding.In an era governed by continuous climate instability and unstoppable expansion of cities, the exacerbation of hydrometeorological events is increasing the occurrence of pluvial floods. Pluvial flooding is induced by the combination of two factors: extreme precipitations and the incapability of the ground/drainage systems to effectively handle excessive rainwater.In an urban environment, the runoff generated by localized and intense rainstorms may quickly inundate streets and buildings undermining the safety of people and assets. The characteristic of being hardly predictable has inspired the definition of pluvial flood as an ‘invisible hazard’ and the related damages and losses are increasingly weighing on the budget of municipalities and private citizens.Looking at the upsetting climate projections, experts are resolute in developing comprehensive methodologies and strategies for flood risk assessment and management.In this work, we present the attempt of accomplishing a high-resolution pluvial flood risk assessment at the city scale. The city of Differdange (Luxembourg's third largest city) is used as case study in which the extreme rainfall-related impacts and hazards are analyzed through the implementation of a fully coupled 1D/2D dual drainage model. This type of hydrodynamic model closely mimics the complexity of an urban landscape allowing to simulate all hydraulic phenomena occurring both on the surface and through the sewer network. Despite the digital accuracy of these models, they are rarely implemented due to the vast amount of detailed information required; which are often unavailable.The implementation of the hydraulic model follows two main steps: the bi-dimensional discretization of the surface and the 1D modelling of the whole drainage network.Nowadays, many countries provide open-access high-resolution digital elevation models of their territories (50 cm for Luxembourg) and up-to-date cadastral planimetries from which essential information for the 2D component are extrapolated. Ground data is enriched by land use/cover and soil maps for the estimation of roughness and infiltration parameters.The drainage network contemplates all pipes carrying rainwater, meaning the newer storm-water system and the old combined sewer network. The geometric specifications required are size, shape, elevation, material of pipes, manholes and tanks. Important infrastructures, such as flooding barriers, have been systematically added to the model. The fully-distributed hydrological engine allows operating the rainfall-runoff transformation on each cell of the domain and the exchange of water between the surface and drainage network occurs through the nodes of the network (storm drains and manholes).The model’s outcomes allow for assessing the level of hazard to which each building is exposed, identifying the critical nodes within the drainage network, and proposing mitigation strategies.Furthermore, these insights may help authorities to improve their warning systems and emergency plans.

Traditionally, flood risk maps used by city officials and water resource managers for urban planning, by engineers for adequate flood defence infrastructure design, or by insurers and re-insurers for estimating financial risk exposure are the result of modelling flood hazard of rivers and their associated floodplain lands at different return periods. Often, any of these stakeholders would use the 1:100 return period of fluvial hazard to plan accordingly. However, with the climate crises signals clearly present during recent flood disasters, and especially with the 2021 Europe floods, water managers, cities and the financial risk sector are now starting to plan differently and are recognizing the need not only for better and more frequently updated flood risk analysis, particularly in urban areas, but also need to consider pluvial and flash floods that can happen in any part of a river basin and oftentimes take place in headwater areas or off the main river floodplains. Flash flooding greatly impacts urban areas where the storm drainage infrastructure is becoming largely insufficient due to the increasing duration and higher frequency of extreme intense rainstorms. Therefore, model simulations of flood hazard that account for these rather unprecedented types of extremely destructive events are required, and those need to be integrating the newest data from all types of sensors. At the same time, we observe that sustainable, nature-based solutions are now sought after because these solutions offer an inviting alternative to ever changing flood risk, particularly under the present and future climate crisis. It is stipulated that increasing healthy urban vegetation cover could reduce this risk and is a form of a nature-based solution for urban areas. Here we combine existing methods from the literature and develop a methodology relating time-series of satellite-based vegetation maps, topography and soil permeability to estimate excess runoff from intense precipitation. The runoff coefficient is mapped through the use of a composite curve number method.. The method of looking at the partition between rainfall and runoff is highly correlated to change in land use, and thus changes in vegetation cover. Relying on the NDVI index for green vegetation mapping, the methodology is able to capture the differences in the hydrological response even for seasonal or canopy integrity changes. Looking at different vegetation cover scenarios therefore allows the creation of different runoff responses, and therefore a possible reduction in flood risk.In this paper, we present initial results of this flood risk analysis, the goal of which is to produce runoff change maps at city, urban neighbourhood or city post code level using different scenarios in rainfall amounts from design storms coupled with existing or planned urban vegetation cover scenarios.

Humankind is currently living in an era governed by continuous climate warm-up and unstoppable urbanization, in which the ongoing climate change is leading to an exacerbation of hydrometeorological events. With an intensification of magnitude and frequency of extreme rainfall events, engineers and scientists are striving to develop methodologies and strategies to effectively defend people and assets from pluvial flooding. Pluvial floods produced by local, intense, and fast rainstorms cause the surcharge of urban drainage systems inducing the inundation of streets and buildings before the runoff reaches the receptor watercourse. Pluvial flood damage has been defined as an ‘invisible hazard’ but it increasingly weighs on the budget of direct flood losses, raising the costs incurred by flood damages. Besides the tangible losses, the costs may be even higher when the intangible share is considered, such as the potential loss of heritage held in ancient towns. For this reason, the inestimable cultural and artistic heritage preserved in historical buildings require a high-level of protection against hazards induced by natural calamities. The present study investigates extreme rainfall-related impacts and hazards threatening the cultural heritage situated in the most vulnerable areas of the Santa Croce district (Florence, Italy). The district hosts some of the most important buildings of the city: the National Central Library of Florence and the Opera di Santa Croce. The geographical location of this monumental complex makes the cultural heritage guarded inside of it dangerously exposed to multiple sources of flood hazard. Firstly, river flooding due to the proximity to the Arno River (this area has been already harshly damaged by the catastrophic flood in 1966). Secondly, flooding by sewage since that the internal drainage network is linked with one of the main sewer conduits of the city. Then, surface runoff flowing down from the headwater. Considering this framework, the pluvial flood hazard assessment is performed using a 1D/2D dual drainage model specifically implemented to simulate all hydraulic phenomena occurring both on the surface and through the sewer network. The analysis comprehends a series of scenarios designed to simulate the impact of hydrometeorological extremes on the study area and each possible concatenation of consequences or failures. The hydraulic model incorporates different layers of information: the high-resolution digital surface model of the area and buildings, the public sewer network, and the internal rainfall collection system of the district. Geometrical features and technical specifications of the sewer network have been retrieved from detailed field surveys and research in historical archives. Model’s outcomes allow identifying the critical nodes within the drainage network, delineating the most vulnerable areas, and prioritizing the rescue efforts in case of severe cloudbursts. Results may help site managers to improve the efficiency of their hazard management and emergency plans. Furthermore, the study intends to propose suitable technical solutions for safeguarding the cultural heritage where designing intrusive engineering works hardly fits within the historical urban context.

During the last 20 years, floods have become a major hazard in West Africa, particularly in the Sahelian belt, affecting livelihoods, infrastructure and production systems, and hence heavily impacting on sustainable development. The Sendai Framework for Disaster Risk Reduction 2015–2030 recognized Climate Services (CS) as a powerful tool for more effective disaster preparedness. The European research and innovation Roadmap for CS expands their contribution, particularly “hydrometeorological services”, to the Sendai Framework. From this convergence, Hydrometeorological Early Warning Systems (EWS) become a strategic target and a building block of preparedness to hydrometeorological risks in developed and developing countries. In West Africa, EWS for floods are in place only for the main rivers and are conceived mainly top-down and hazard centered, lacking links with exposed communities and expected impacts. These gaps reduce the effectiveness of a flood EWS, while engaging local communities since de beginning through a co-production process can improve the effectiveness and ensure better response in case of alert.Our study aims to present the lessons learnt from the set-up of a Community and Impact Based Flood EWS on the Sirba River in Niger. The service was developed with stakeholders at different levels, leveraging on existing resources and knowledge, using simple but effective approaches and integrating state-of-the-art hydro-meteorological science in a decisional scheme of Sahelian rural areas. This mechanism can be replicable in different contexts characterized by knowledge and structural deficits, by creating a better capacity to exchange data and information and by directly connecting available technical capabilities with the local level. The participatory approach allowed the beneficiaries to define the rules of the system, which, in any case, needed to be consistent with the national legislation and internationally recognized best practices.The study suggests that it is not necessary to develop complex forecasting tools, while it can be preferable to enhance those already operating and calibrate them on the local scale through risk thresholds, field observations and potential impacts using flood scenarios. The strength of simplicity also lies in not having to spread complex messages, but simply the reference risk scenario, and finally its color-code (according to the international standards of ISO 22324:2015), which already embeds all other information including potential impacts. The simple and integrated approach illustrated in this case study, bridging the gap between top-down and bottom-up approaches, can inspire Governments, local administrations and development partners to invest in the improvement of existing tools and knowledge and in strengthening cooperation, collaboration and coordination to reduce hazards’ impacts and sustain the development of rural and urban areas.