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Areas with the greatest scarcity in hydrological data are typically also those that suffer the greatest impacts from adverse hydrological conditions. These areas can potentially benefit greatly from simple hydrological data collection methods, such as those obtained by citizen scientists. Streamflow can be estimated by anyone without specialized equipment, but these estimates are potentially too inaccurate to be useful for hydrological model calibration. In the CrowdWater project, we assess the requirements of streamflow data in terms of frequency and accuracy for their use in the calibration of bucket-type hydrological models. We asked passersby to estimate the streamflow for different rivers in Switzerland. A comparison of the people's estimates with the measured streamflow data suggested a lognormal error distribution. We applied this error distribution to a year of measured hourly streamflow data to obtain synthetic …