Value of water level class observations for parameter set selection in hydrological modelling

Finding suitable parameter sets for a hydrological model usually requires several years of discharge data. As these data are often unavailable, it can be challenging to use hydrological models. It has been shown that alternative data also contain valuable information for lumped bucket-type models. Here, we tested the value of water level class observations by citizen scientists, a limited number of discharge measurements, and an estimate of the mean annual discharge for parameter set selection for the Hydrologiska Byråns Vattenbalansavdelning (HBV) model. We found that water level class observations can improve parameter set selection if they are combined with some information on the discharge volume (a few discharge measurements or an estimate of the mean annual discharge). A rough estimate of the mean annual discharge range is not only informative but even more beneficial than an “exact” estimate. To simulate the discharge dynamics, water level class observations by citizen scientists are sufficient if they are of good quality.