Can Continental Models Convey Useful Seasonal Hydrologic Information at the Catchment Scale?

The development and availability of climate forecasting systems have allowed the implementation of seasonal hydroclimatic services at the continental scale. User guidance and quality of the forecast information are key components to ensure user engagement and service uptake, yet forecast quality depends on the hydrologic model setup. Here, we address how seasonal forecasts from continental services can be used to address user needs at the catchment scale. We compare a continentally calibrated process‐based model (E‐HYPE) and a catchment‐specific parsimonious model (GR6J) to forecast streamflow in a set of French catchments. Results show that despite expected high performance from the catchment setup against observed streamflow, the continental setup can, in some catchments, match or even outperform the catchment‐specific setup for 3‐month aggregations and threshold exceedance. Forecast systems can become comparable when looking at statistics relative to model climatology, such as anomalies, and adequate initial conditions are the main source of skill in both systems. We highlight the need for consistency in data used in modeling chains and in tailoring service outputs for use at the catchment scale. Finally, we show that the spread in internal model states varies largely between the two systems, reflecting the differences in their setups and calibration strategies, and highlighting that caution is needed before extracting hydrologic variables other than streamflow. We overall argue that continental hydroclimatic services show potential on addressing needs at the catchment scale, yet guidance is needed to extract, tailor and use the information provided. Plain Language Summary Climatic variations can have a significant impact on a number of water‐related sectors. Managing such variations through accurate predictions is thus crucial. Continental hydroclimate services have recently received attention to address various user needs. However, predictions for months ahead can be limited at catchment scale, highlighting the need for data tailoring. Here, we compare the predictions from two hydrologic setups at catchment scale. One setup (E‐HYPE) is used in a European hydroclimate service, whereas the other (GR6J) is used for local water‐related risk assessment. Our results show that predictions from the continental setup can be as accurate as the predictions from the local model when predicting streamflow averaged over several months and when looking at changes in