The taxonomy used for labeling elements exposed to risk is GED4ALL, which is extended version of the Global Exposure Database for the Global Earthquake Model (Silva et al. 2018, Murnane et al. 2019)

Description of Data Product components

DAMAGE SCALES

– Description of Damage scale:

Damage scale is the ensemble of mutually exclusive and collectively exhaustive damage states (DS_i) used to describe the whole range of possibilities of damage for an exposed asset (Buildings or other structure). Damage levels D_j are the thresholds that separate the different damage states (DS_i).

Figure 1: Table of different damage scales introduced in literature with Graphical representation of damage levels D_j and damage states DS_j, where j=0-N_DS. An example of damage scale with 4 damage level (Paulik et al. 2019).

FRAGILITY CURVES

– Description of fragility curves

The probability of exceeding a given damage level (DS_{j) given a certain Intensity Measure (IM). Fragility curves can be calculated either through structural analysis (analytical approach) or by observing the local damage from a previous tsunami event (empirical approach). ETRiS currently provides empirical fragility curves. These curves are all derived using the software computeFrag Version 2 (see the Tsunami Risk Toolkit page).}

Figure 2 : Fragility curve relation with different variables. The fragility curve defines as the probability of exceeding the a given damage level (DS_{j) given a certain Intensity Measure (IM)}

CONSEQUENCE MODELS

– Description of Consequence model

The conditional probability distribution (e.g., mean, and standard deviation) of a decision variable DV (e.g., fatalities, economic loss) for prescribed damage states.

Figure 3 : Consequence model relation with different variables. table shows examples of consequence models in literature.

VULNERABILITY CURVES

– Description of vulnerability curves

The conditional probability distribution (e.g., mean and standard deviation) of a decision variable DV (e.g., fatalities, economic loss) as a function of the intensity measure IM.

Figure 4 : Vulnerability curve relation with different variables. The vulnerability curve defines as the probability distribution (e.g., mean and standard deviation) of a decision variable DV (e.g., fatalities, economic loss) as a function of the intensity measure IM

Metadata: Vulnerability_Curve_metadata includes building classes for different events, on different damage scales, and using different modeling processes, as well as information about their contributors. Note: the Vulnerability curves provided by ETRiS are all re-postprocessed using the compFrag software version 2. The original papers provide information about the raw data and documentation for the original Vulnerability curves.

LOSS CURVES

– Description of loss curves

Loss curves provide the mean annual rate of exceeding specific thresholds dv for the decision variable DV. ETRiS is currently preparing the loss curves to be shared on the repository.