Stations within 5 km of Sheffield Hackspace
URLs:
- https://check-for-flooding.service.gov.uk/station/8248
- https://environment.data.gov.uk/flood-monitoring/doc/reference
- https://environment.data.gov.uk/flood-monitoring/id/stations?lat=53.369771&long=-1.474261&dist=5
- https://environment.data.gov.uk/flood-monitoring/id/stations/L0691
- https://environment.data.gov.uk/flood-monitoring/id/stations/F0402/readings?_sorted
# save
curl "https://environment.data.gov.uk/flood-monitoring/id/stations?lat=53.369771&long=-1.474261&dist=5" \
> stations.json
$ cat stations.json | jq -r '.items | length | tostring + " total stations"'
14 total stations
# print results nicely
$ cat stations.json | jq -r '.items | .[] | ("\(.RLOIid) (\(.label)) measures " + (.measures|length|tostring) + " quantities\n opened \(.dateOpened) at \(.lat) \(.long)\n and is in \(.riverName), \(.town)")'
8339 (Sheffield Oakbrook Road) measures 1 quantities
opened 2005-12-09 at 53.367798 -1.521432
and is in Porter Brook, Sheffield
8308 (Sheffield Centenary Works) measures 1 quantities
opened 1998-01-16 at 53.351517 -1.484072
and is in River Sheaf, Sheffield
…
# save as CSV
cat stations.json | jq -r '.items | .[] |= (.measures = (.measures|length))' | jq -r '(map(keys) | add | unique) as $cols | map(. as $row | $cols | map($row[.])) as $rows | $cols, $rows[] | @csv' | csvtool paste - \
> stations.csv
# turn CSV to geojson
# rename headers "lat" to "latitude" first and use code from https://blog.alifeee.co.uk/notes/making-a-geojson-file-from-a-csv/
cat stations.csv | sed '1s+,lat,+,latitude,+;1s+,long,+,longitude,+' | jq -Rn '(input|split(",")) as $headers | ($headers|[index("longitude"), index("latitude")]) as $indices | {"type": "FeatureCollection", "features": [inputs|split(",") | {"type": "Feature", "properties": ([($headers), .] | transpose | map( { "key": .[0], "value": .[1] } ) | from_entries | del(.latitude, .longitude)), "geometry": {"type": "Point", "coordinates": [(.[$indices[0]]|tonumber), (.[$indices[1]]|tonumber)]}}]}' \
> stations.geojson
# single station data
$ curl "https://environment.data.gov.uk/flood-monitoring/id/stations/F0402/readings?_sorted" \
> F0402.json
$ cat F0402.json | jq -r '.items | min_by(.dateTime | fromdate) | ("\(.value) on \(.dateTime)")'
0.198 on 2025-09-17T05:45:00Z
$ cat F0402.json | jq -r '.items | max_by(.dateTime | fromdate) | ("\(.value) on \(.dateTime)")'
0.216 on 2025-09-22T10:30:00Z
# plot
cat F0402.json \
| jq -r '.items | .[] | (.dateTime | fromdate|tostring) + "\t" + (.value|tostring)' \
| eplot -t "Level"
data can be plotted on Grafana using the Infinity datasource to load JSON.
