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Multi-criteria model calibration can lead to a better representation of hydrological processes and reduce parameter uncertainty compared to calibration on streamflow data alone. However, the additional data may be difficult to collect or aggregate into a representative catchment average value that can be used to calibrate a lumped model. Temporary streams are highly dynamic, and their flow state can be observed visually. However, data on the state of temporary streams are still uncommon and rarely used in hydrological catchment modelling. In this study, we used a unique dataset with discrete flow state observations for temporary streams in France and evaluated how informative these data are for calibrating a lumped, bucket-type hydrological model. We calibrated the HBV model for 92 catchments using discharge or stream-level data at different temporal resolutions (daily, one daily value per month, or one daily …