Insights on using flood impact data for evaluating hydrometeorological warnings in Sweden

The accuracy of flood warnings should ideally be evaluated on real impact data, although such data are often difficult to obtain and work with. The Swedish Meteorological and Hydrological Institute (SMHI) has recently acquired records of flood-affected roads and emergencies attended by fire and rescue services in Sweden over the last 25 years. We analysed whether the impacts were covered by flood-related warnings and whether they coincided with hydrometeorological conditions exceeding flood warning thresholds from hindcast data. Here we present our experiences on tackling challenges associated with using the impact dataset, insights into what type of flood events the warning system handles well and how it can be developed further.

The existing SMHI warning methodology explained only 26% of the reported flood impacts, although this proportion increased to 43% after filtering out minor and isolated impacts. Incorporating runoff data from a recently developed sub-daily hydrological model further increased the proportion of explained impacts to 54%. Sub-daily runoff was especially effective in explaining summer flood impacts from cloudbursts in small flashy streams, illustrated through a case study of the Västernorrland flood in September 2025. Notably, total runoff generated in subcatchments was a more important predictor of flood impacts than streamflow, while precipitation did not account for almost any impacts alone without coinciding hydrological causes. Nevertheless, impacts from winter processes, such as urban snowmelt and rain-on-snow floods, remain poorly represented in the warning system. Our findings highlight the importance of filtering impact records prior to evaluation and reveal the benefit of utilising high-resolution hydrological models with outputs beyond streamflow in operational flood warning systems.