Combining your measurements with public data

Knowledge base · July 11, 2026

Most environmental measurements do not live in a vacuum. Water level responds to rainfall, turbidity to run-off, oxygen and blooms to temperature and wind, insect swarming to warmth. That is why your own data only gains full value when set against weather and hydrology - and these are publicly available (see IMGW-PIB data and GIOŚ data).

Why context changes everything

Your measurementPublic contextWhat it explains
water level / dischargerainfallwhether the level is rising after rain, or something unusual is happening
turbidityrainfall / run-offwhere the sudden cloudiness comes from
cyanobacterial bloom / chlorophylltemperature, wind, insolationanticipating the risk
dissolved oxygentemperaturewarm water holds less of it
PM dustweather + a reference stationwhether it is an inversion or a real episode
bark-beetle catchtemperaturewhen swarming starts and intensifies

Without this context it is easy to misinterpret a result - or to overlook that an “anomaly” is simply the outcome of yesterday’s downpour.

Two routes: by hand or automatically

By hand. You download data from the IMGW/GIOŚ portals, match it in time to your measurements and stitch it together in a spreadsheet. It works, but it is laborious and it is easy to make mistakes when matching dates and stations.

Automatically. The data flows in by itself and is immediately “glued” to your measurements on a shared time axis. This solution scales much better, especially with continuous monitoring.

📊 See it live: Global Rivers & Lakes Watch - a public dashboard from three stations in three countries: the Maumee River (Ohio, USA), the river Main in Frankfurt and the LéXPLORE research platform on Lake Geneva. Water temperature, dissolved oxygen, pH, conductivity, turbidity and chlorophyll-a are fetched automatically (USGS Water Services, WSV Pegelonline, Eawag Datalakes), with correlation tiles and a station map. No login.

How LimnoLog does it

Here the connectors in LimnoLog come to the rescue: they can automatically pull in data from public APIs (e.g. rainfall and hydrology from IMGW-PIB, air quality from GIOŚ) and record it alongside your measurements. Thanks to this you see a measurement and its context on a single chart - without manually stitching spreadsheets. The same goes for alerts: a warning threshold on your indicator can be read together with the weather that often explains it.

If you are just starting out, the simplest thing is to begin with your own measurements (see the Method Guide) and add the weather context when you need it.

See it in the LimnoLog app

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