Crowdsourcing hydrological data
Can citizens observe what hydrological models need?
1. Stream level class data from citizen scientists provide sufficient information to calibrate hydrological models.
2. Qualitative data (e.g. soil moisture and water level class estimates) can be useful for hydrological model calibration.
The CrowdWater project examines the potential of crowdsourced hydrological information for hydrological model calibration and forecasts.
Water level, streamflow and soil moisture data are collected with an app and the value of this data for improving hydrological models is evaluated. The adopted “geocaching” approach means that users can create virtual measuring stations at any location and add their observations to the time series of other stations. Surveys and information boards at various location help us to improve our methodology and enable us to assess the quality of the data.
Anyone can contribute to the CrowdWater project. Citizens can set up their own virtual stations and create their own time series for water level, streamflow and soil moisture and thereby learn a lot about how these parameters change in response to weather and seasonal changes.
Department of Geography, Hydrology and Climate Group, University of Zurich
Barbara Strobl, Simon Etter, Dr. Ilja van Meerveld, Prof. Dr. Jan Seibert, Dr. Tracy Ewen