Natural hazards & risk

Floods, fires, earthquakes and landslides as data: return periods, severity and shaking, who is exposed, and the arithmetic that turns the three into a risk figure.

Three nested flood scenarios over the same row of houses, with the share of expected annual damage each band contributes. the rare scenario does the most damage and contributes the least1-in-1075% of expected damage1-in-10021%1-in-5003%Expected annual damage integrates over every scenario, so the frequent shallow ones dominate

A hazard map answers "how deep, how hard, how hot, and how often". A risk map answers "how much does that cost", and getting from one to the other needs two more terms: who and what is in the way, and how badly they fare. Most maps labelled risk are a single scenario of the hazard term with a red ramp on it.

Each hazard arrives with its own data and its own traps. Flood maps come per return period and nest inside each other, so their exposure counts cannot be added. Earthquake catalogues record what the network could detect, so counts rise when the instruments do. Burn severity is a change index that cannot tell a harvest from a fire. Susceptibility is a weighted overlay whose weights are opinion until an inventory tests them. And the exposure step is the one that turns a defensible map into an indefensible headline, because every apportionment rule gives a different number.

The concepts below fix the vocabulary — hazard, exposure, vulnerability, return period, severity, susceptibility; the how-to guides work through real catalogues, ShakeMaps, gauge records, perimeters, imagery and census blocks to a published expected annual damage; and the fixes are the five ways these numbers go wrong in public.

Learning paths run through this topic too — see the end of this page.

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