Impact and risk

Impact and risk#

In this framework, Risk (R) is calculated as a function of: the hazard occurrence probability and intensity (i.e., physical magnitude) in a particular location (H, for Hazard); the people and physical assets (infrastructure, buildings, crops, etc.) situated in that location and therefore exposed to the hazard (E, for Exposure); and the conditions determined by physical, social, and economic factors which increase the susceptibility of an exposed individual, community, asset or system to the impacts of hazards (V, for Vulnerability).

Risk = Hazard x Exposure x Vulnerability

See also

Disaster risk is expressed as the likelihood of loss of life, injury or destruction and damage from a disaster in a given period of time (UNDRR 2019).

Measures of exposure can include the number of people or types of assets in an area. These can be combined with the specific vulnerability and capacity of the exposed elements to any particular hazard to estimate the quantitative risks associated with that hazard in the area of interest.

UNDRR Risk overview

From these definitions, we understand that the concept of risk is inherently tied to the concept of probability, expressed in terms of frequency (also occurrence rate). In other words:

Risk = Probability x Impact

../_images/risk_impact_rate.png — Fig. 5 Risk as impact - probability combination.#

While historical losses can explain the past, they do not necessarily provide a good guide to the future; most disasters that could happen have not happened yet. Probabilistic risk assessment simulates those future disasters which, based on scientific evidence, are likely to occur. As a result, these risk assessments resolve the problem posed by the limits of historical data. Probabilistic models therefore complement historical records by reproducing the physics and/or the statistics/statistical distribution of the phenomena and recreating the intensity of a large number of synthetic events.

Note

In the context of disaster risk, probability refers to the frequency of occurrence, or return period of impacts associated with an hazard event of given intensity.

Probabilistic risk is the chance of something adverse (impact) occurring. This method assesses the likelihood of an event(s) and it contains the idea of uncertainty because it incorporates the variability between frequent, low impact events and rare, high impact events.

In contrast, a deterministic risk model typically models one scenario representing a real event or an individual, finite risk scenario (e.g. mean, median, worst case), but cannot properly represent the full range of variability around it.

An indicator of mean annual risk: Expected Annual Impact#

When probabilistic hazard scenarios (multiple layers by Return Period) are available to calculate impacts in relation to occurrence frequency, an estimate of the Expected Annual Impact (EAI) over exposed categories can be calculated. This can be done for both the Baseline, refering to the historical period, and for future climate projections.

The EAI is calculated by multiplying the impact from each scenario with its exceedance probability, and then summing up to obtain the mean annual risk considering the whole range of hazard occurrence probabilities. The exceedance frequency curve highlights the relationship between the return period of each hazard and the estimated impact: the area below the curve represents the total annual damage considering all individual scenario probabilities.
In lack of a proper vulnerability function, the EAE is calculated in a similar fashon considering exposure to specific hazard thresholds instead of impacts. (EAE) is then expressed as annual exposure to hazard over a certain threshold.

Lower and Upper bounds#

Due to requests from regional teams, a refined calculation of the integral for probabilistic EAI and EAE includes:

EAI Lower Bound (EAI_LB): calculated as the sum of the area of recangles built below the exceedance probability curve
EAI Upper Bound (EAI_UB): calculated as the sum of the area of recangles built above the exceedance probability curve
EAI: mean between lower and upper bound

../_images/lowerupper.png — Fig. 6 The integral below the curve is calculated as the mean of lower and upper bound rectangles areas (Riemann sum).#

Direct and indirect losses#

Direct disaster losses refer to directly quantifiable losses such as the number of people killed and the damage to buildings, infrastructure and natural resources.
Indirect disaster losses include declines in output or revenue, and impact on wellbeing of people, and generally arise from disruptions to the flow of goods and services as a result of a disaster [GFDRR 2014; UNDRR].

In this specific framework, we are only estimating DIRECT disaster losses in terms of impacts on mortality and built-up damage.

Supported combinations of hazard and exposure#

Based on the available data, the following matrix show the combinations of hazard and exposure for which a vulnerability model is provided, and the type of model, allowing to express the risk either in form of impact (damage) or exposure to hazard classes.

Hazard types	Population [Mortality]	Built-up assets [Physical damage]	Agricultural land [Production losses]
River and Coastal floods Probabilistic [Water extent and depth]	Impact model	Impact model	Impact model
Landslides Deterministic [Landslide hazard index]	Exposure by hazard classes	Exposure by hazard classes
Tropical cyclones (wind) Probabilistic [Cyclone tracks]		Impact model
Agricultural drought Deterministic [Agricultural Stress Index]			Exposure by hazard classes
Heat stress Probabilistic [Heat index]	Exposure by hazard classes
Air pollution Deterministic [PM2.5 concentration]	Exposure by hazard classes