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Install EuroFlood, run your first flood query, and download a depth map — end to end, against the published index (no data build required). Prefer runnable notebooks? The Tutorials cover all of this in depth.

Install

pip install "euroflood[viz]"   # core + plotting (recommended)

uv add "euroflood[viz]"

EuroFlood works out of the box: the published index is read remotely and cached on first use (~14 MB of tables), so there is nothing to download or configure first.

Your first query

floods(...) returns a FloodFrame — a geopandas.GeoDataFrame, one row per historic flood event. It's cheap: it streams a small window of the index and downloads no rasters.

import euroflood as ef

cat = ef.floods("Zutphen, Netherlands")
cat

EuroFlood catalogue: 25 flood events · 2015-01-12 … 2024-02-05 · 51.6 km² total

Because it is a GeoDataFrame, filter and plot it as usual — then .download() the depth rasters for the events you keep and .stats() them (no network after the download):

recent = cat[cat["date"] >= "2021-01-01"]    # any pandas / geopandas operation
recent.plot()                                 # recurrence heatmap — still no download
dl = recent.download("out/")                  # fetch + crop only these events' rasters
dl.stats()                                    # max/mean/p95 depth (m), area (km²), volume

Ways to specify a region

A place name is geocoded; a bbox, point + radius_m, or shapefile skip geocoding. Administrative boundaries can be awkward (they often follow a river), so shape="bbox" / "hull" gives a cleaner ROI, and buffer_m grows it:

ef.floods("Zutphen, Netherlands", buffer_m=1000)
ef.floods("Zutphen, Netherlands", shape="bbox")   # a clean bounding-box ROI
ef.floods(bbox=(6.14, 52.09, 6.27, 52.17))
ef.floods(point=(52.14, 6.20), radius_m=6000)     # point is (lat, lon)

Modelled hazard

The same API queries the global CEMS-GLOFAS flood-hazard maps by return period:

haz = ef.hazard("Zutphen, Netherlands", return_period=[100, 500]).download("hazard/")
haz.stats()

Offline & HPC

Everything above streams the index. For fully offline / cluster use, mirror the full ~130 MB bundle once, then read it locally:

export EUROFLOOD_GEOCODER_BACKEND=local   # resolve names from the offline NUTS dataset
euroflood mirror-index                    # pull the whole bundle, then query with no network

Next steps

  • Tutorials

    The guided path — from a first query to hazard maps and quantitative analysis.

    Start the tutorials

  • Concepts

    How the index works — the one page that makes everything else click.

    Read Concepts

  • API reference

    Every public function, class, and EUROFLOOD_* setting.

    Browse the API