Flood risk analytics for infrastructure debt

The flood exposure of any asset, priced in basis points.

FloodGate screens 42,037 ports, airports and power plants against 689 global flood hazard layers — and translates the hazard into expected damage and probability of default, with peer-reviewed methodology and open data.

Open the tool Watch the demo Free during the pilot · no account needed
7,244 flood-exposed assets, drawn from the FloodGate database · historical baseline <1% expected damage 1–5% 5–15% >15%
The numbers

A global screen, built like a research dataset.

Live example — Port of Delfzijl, Netherlands

Coastal flood depth by return period, historical baseline (undefended hazard)

0 2.2 4.4 m 1-in-2 1-in-50 1-in-1,000 yr 3.9 – 4.2 m Run the full analysis →
Assets covered
42,037
34,936 power plants · 3,297 airports · 3,804 ports
Hazard layers per asset
689
riverine + coastal · 3 scenarios · 5 climate models · to 1-in-1,000 yr
The econometric link
+99 bps
probability of default per 1 s.d. of expected flood damage — estimated on 951 real loans

Climate change deepens and spreads the risk

Mean expected damage among exposed assets

Historical 4.61% RCP 8.5 · 2080 6.87% exposed assets grow from 6,516 to 7,044 over the same horizon
Most exposed sector
Ports
25.2% flood-exposed · airports 19.4% · power 16.2%
Static & auditable
CSV
every number traces to a row in an open, versioned dataset — no black box

Method, end to end

Reproduces the published pipeline exactly — validated against the original research to zero deviation.

Asset location→ WRI Aqueduct flood depths→ JRC damage functions→ Expected damage (Eq. 3)→ ΔPD in basis points

Built on published research

Assab (2025), Journal of Climate Finance — flood damage and infrastructure loan default; Assab (2024), JRFM — pricing climate loss & damage in infrastructure financing.

doi:10.1016/j.jclimf.2025.100066 doi:10.3390/jrfm17040133
How it works

From coordinates to basis points in three steps.

01

Find the asset

Pick a country and asset type, then select from every port, commercial airport and power plant we track there.

02

Set the scenario

Historical baseline or RCP 4.5 / RCP 8.5 out to 2080 — with full control over climate models, coastal settings and damage functions.

03

Read the risk

Flood depth by return period, expected damage as a share of asset value, and the uplift to probability of default in basis points.

Screen your first asset in under a minute.

No installation, no account during the pilot — the tool runs in your browser from a static, auditable dataset.

Open the tool