# SaferPlaces

### Description

SaferPlaces is an advanced flood risk model combining geospatial, satellite imagery, climate data and AI-based models to provide information about urban flood risks (Bagli, et al., 2022). It can be used to assess pluvial, fluvial and coastal flood hazards and risk in consideration of both historical, current and future climate scenarios.

### Model Specifications

| Model Specifications          | Description                                                                                                                                                                                                                                                                                                                                                                                      |
| ----------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| Model type                    | Can deliver both deterministic and AI-based data driven flood modelling. Uses innovative algorithms to simulate specific events such as storm scenarios (pluvial, fluvial and coastal).                                                                                                                                                                                                          |
| Associated Probability Method | The platform utilises damage models based on flood-depth damage functions (JRC, FEMA)                                                                                                                                                                                                                                                                                                            |
| Spatial Resolution            | Varies depending on the quality and availability of DTM input data – has been used to provide estimates with a spatial resolution down to 1–5 meters (Mediero et al., 2020). Also, available in 5-10 and 10-30m resolution.                                                                                                                                                                      |
| Intensity Parameters          | <p>Flood water depth/velocity, flood extent, economic damage per building<br>The intensity parameters are generated for each scenario (Return Period, Climate Scenario)</p>                                                                                                                                                                                                                      |
| Other Inputs                  | Digital Terrain Models (DTMs), land use and land cover data (including urban infrastructure, vegetation), OpenStreetMap, Earth Observation Data (EOD), building footprints and characteristics, drainage, and sewer networks. It also has a functionality to simulate the effects of mitigation measures to flood risks such as physical barriers, water tanks, soil infiltration capacity, NBS. |
| Calibration and Validation    | Validation can be done using a combination of historical data and advanced statistical techniques, benchmarking model outputs against past events (including the use of insurance records to refine and validate damage estimations).                                                                                                                                                            |
| Effects of Climate Change     | The platform can incorporate SSPs to assess how climate change can influence flood risks in urban areas.                                                                                                                                                                                                                                                                                         |

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