PSI - Issue 78

Matjaž Dolšek et al. / Procedia Structural Integrity 78 (2026) 1569 – 1576

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The methodology comprises four main steps: STEP 1: Time-based Risk Assessment and Intensity-based Loss Estimation for Residential Buildings, STEP 2: Definition of Earthquake, Flood and Compound Hazard Scenarios, STEP 3: Scenario-based Loss Estimation for Affected Area, STEP 4: Emergency Response System and Emergency Management System’s Performance Assessment at the Municipal Level STEP 1 identifies high-risk urban areas using a time-based risk assessment and detailed exposure models of residential buildings supplemented by intensity-based loss estimates from hazard maps. This helps identify risk-based hotspots and supports strategic risk decisions towards risk reduction. STEP 2 provide specific hazard scenarios — such as earthquakes, floods, or compound events — linked to defined return periods, allowing for an understanding of the impact severity relative to the likelihood of the event. STEP 3 expands the exposure model to include EMS units, estimating scenario-based losses such as building damage, injuries, and fatalities while evaluating EMS operability across affected regions, including cross-border areas. Scenario-based hotspots are also an important result of this step. STEP 4 evaluates a municipal emergency response by modelling critical infrastructure and simulating response strategies within subdivided sectors, culminating in EMS performance assessment and recommendations for resilience improvement. While STEPs 1 and 2 and loss estimation for residential buildings of STEP3 refer to the entire affected area, the loss estimation for EMS units of STEP 3 and the simulations in STEP 4 are limited to the municipality level. 3. Methodology 3.1. Time-based risk assessment and Intensity-based loss estimation for residential buildings The first step of the BORIS2 methodology builds on the framework of the former BORIS project for harmonized single and multi-risk assessment (Polese et al. 2024 , Babič et al., 2025 ), introducing two key innovations aimed at supporting the emergency management planning phase at the local level. First, spatial disaggregation is one of the main enhancements introduced in BORIS2. The original BORIS methodology represented exposure data and seismic hazard at the municipal centroid level (Fig. 1a), while for flood hazard the risk analysis was performed at the building level and subsequently aggregated at the municipal scale. Conversely, BORIS2 emplolys a regular grid cells (e.g. 250x250 m) to perform the analysis and report results (Fig. 1b). This enables more precise identification of critical areas and supports a more realistic integration with local emergency planning strategies. Secondly, the considered assets at risk are residential buildings and population, for which the selected risk metrics such as building damage, economic losses, injured/deaths and displaced population (in the short term or long term). Another key aspect of BORIS2 methodology is that more relevance is given to the impacts on the population that are more relevant to the emergency response phase. The study area may include a single municipality or a group of neighboring municipalities, depending on the extent of the affected area and the expected interdependencies among local EMS. This flexibility makes it possible to support emergency planning at both municipal and cross-border level, depending on the severity of the hazardous event. The hazards considered are the seismic and fluvial flood events in a multi-layer single-risk approach. In this step, they are treated as independent, and only later (see 3.2) compound scenarios with a defined return period can be selected, allowing for comparison in terms of impacts and probability of occurrence. For seismic risk, hazard intensity values (i.e., Peak Ground Acceleration - PGA) at each grid cell centroid are derived from probabilistic seismic hazard models. Soil amplification factors should be applied where local data is available. Losses are then computed using exposure models, vulnerability functions, and appropriate consequence functions (Polese et al., 2024). For flood risk, intensity information is extracted from hazard maps (water depth and flood extent) for specific return periods. The losses are computed at the building level and aggregated to the grid cell centroid using vulnerability functions such as HAZUS (FEMA, 2013), which consider occupancy type and structural characteristics, utilized also