The service
FLOODMAGE provides a comprehensive outlook about the potential economic and financial impacts linked to flood hazard. The outlooks can be provided either at the annual and the seasonal scale, with monthly updates about the estimated risk for the area of interest. This information is key for effective climate adaptation strategies. The service is oriented to a variety of users, including the public administration, river basin authorities, land reclamation boards, asset managers, and insurers. The service responds to different needs depending on the user.
are informed about risk hotspots and forecasted changes in the amount of exposed value and potential losses. This information is key to anticipate the hazard and mitigate the impacts through different actions and strategies, such as: upgrading of flood defences, restoration of wetlands, maintainance of the drainage network, planning of financial resources.
can use our flood maps and damage models to assess risk across the property market, enabling consistent insurance pricing, capital management and portfolio design with high resolution and detail at the local level.
FLOODMAGE is adaptable to different spatial scales and builds upon advanced seasonal meteo-climatic downscaling, high resolution exposure mapping, hydrodynamic and hydrostatic hazard modelling, multi-variable vulnerability assessment, and macro-economic modelling of labour and capital.
Flood Types
Floods can be triggered by different natural phenomena, then exacerbated by local conditions such as terrain morphology, soil imperviousness and artificial barriers.
FLOODMAGE addresses three main types of extreme meteorological events triggering flood hazard:
Coastal floods happen when the sea level rises due to storm surge and strong winds. This can happen due to low pressure and cyclonic activity, in conjunction with extreme tidal level. Land subsidence and sea level rise are both factors affecting the relative sea level, thus the frequency of coastal inundation events. The severity of a coastal flood is determined by several factors, including the height and momentum of the waves, the duration of the event, and the onshore and offshore topography.
Pluvial (or surface) floods are triggered by intense rainfall over a relatively small area, independently from the presence of a water body. Surface floods often happen in urban areas, where the impervious soil has reduced absorption capacity and the drainage system is more vulnerable to saturation from rainfall peaks. They typically arise very quickly (often less than six hours between rain falling and flooding).
Riverine (or fluvial) floods occur when intense water runoff due to heavy rainfall or fast snow melting triggers a peak water discharge that exceeds the river capacity. This can cause the overflow or breach of the embankments and the submersion of surrounding land. The severity of a river flood mostly depends on the volume of the floodwater (and relative depth), the speed of the flow, and the duration of the event.
The approach
A variety of methods are combined together to produce risk estimates from climate timeseries. When developing our approach, we made use of the most innovative tools in this field, achieving a state-of-the-art workflow that allows us to offer a high detail of analysis, whithin the limits of forecasts reliability.
The probability of extreme events is estimated on the basis of long-term historical records and medium-term seasonal forecasts. The downscaling of seasonal forecasts is performed using the climate analogs method: forecasted meteo-climatic conditions are compared with observations from the past to identify similarities with known extreme events.
Advanced hazard modelling is applied to simulate the scenarios of extreme events and the resulting flood hazard features. Each type of flood is simulated using a dedicated model, which accounts for the specific physical processes involved.
The simulations are performed at high-resolution, using the best DTM data available. The output is provided in form of georeferenced features including key indicators for risk assessment such as flood extent, water depth, and duration.
At the stage, hazard mitigation options can be implemented to produce alternative scanrios and evaluate their effectiveness.
Updated inventories of vulnerable asset value and production value are georeferenced at building level to identify the maximum potential economic value exposed to flood damage in relation to the hazard probability scenarios modelled in the previous step. The exposure is identified by land use type, such as residential, industrial, commercial and agricultural.
The last step is the estimation of direct damage and indirect losses inflicted on exposed assets as a result of flooding. To do that, empirically-based vulnerability models are employed. The simulated flood scenarios describing the hazard intensity are spatially combined with the maximuma exposed economic value and translated into direct damage, calculated as a share of the total asset value. Secondly, business interruption is evaluated in terms of production losses over the annual GDP (at regional scale).
Demo application in Rimini (IT)
The service was developed in partnership with the Region Emilia-Romagna, where we identified the pilot case of Rimini to develop and test our methodology.
Rimini is a coastal city located on the North Adriatic coast which suffered consistent damage due to coastal inundations and pluvial floods. For example, in June 2013 a violent rainstorm (123 mm in 1 hour) caused the surface flooding of a large part of the urban area; in February 2015, a severe storm surge event caused the rise of the sea level (1.3 m) and the inundation of large part of the regional coast, triggering almost 1 billion in damage and losses in total.
Coastal inundation from storm surge
Coastal inundations scenarios up to 2100 are produced using historical references of extreme sea level events and accounting for the projected changes in 1) sea level rise; 2) probability of extreme surge events; and 3) ground level due to local vertical land movements.
The characterisation of extreme scenarios includes: event probability, mean sea level, storm surge level and duration, effect of tide, wave dynamic and related runup.
An advanced hydrodynamic model performs the simulation of extreme events and the induced effect in terms of hazard, measured in terms of flood extent, water depth, and duration of submersion. The model runs on recent high-resolution Lidar Digital Terrain Model (1m) and bathymetry. The effect of planned flood mitigation measures is tested for all accounted scenarios.
Current scenario
2050, RP 100 years
"Parco del Mare" scenario
2050, RP 100 years
"Parco del Mare" + Canal barrier
2050, RP 100 years
Surface flood from extreme rainfall
Pluvial flood scenarios are built using historical references of extreme rainfall events (more than 50 mm/day) and downscaling the seasonal forecasts produced monthly by SEAS5 with a maximum leadtime of 6 months.
The extreme pluvial scenarios are modelled using a hydrostatic fill-and-spill approach based on high-resoluion Lidar DTM (1 m) which has been manually verified and corrected.
The characterisation of extreme scenarios includes: event probability on annual and seasonal basis, flood extent and water depth in relation to mm/hour of rainfall.
Hazard and Risk Maps
One of the key outputs of the service consists of:
- Hazard maps, representing the maximum hazard intensity in relation to probability
- Risk maps, representing the economic cost triggered by the hazard
Below, an example of combined hazard+risk map for a coastal inundation event with a probability (return period) of once in 10 years, set in 2050 under RCP 4.5 sea level rise scenario, including land subsidence at present rates and no mitigation action. Damage is expressed as restoration cost for residential buildings at current Eur value.
