Composition, frequency and magnitude of future rain-on-snow floods in Germany

Abstract. In Germany, severe trans-basin winter floods are often generated by rain-on-snow (ROS) phenomena. Under suitable conditions, when rain falls on the snow cover, the snow can melt and produce extreme amounts of runoff. In a warming climate, the frequency of ROS events is expected to change locally depending on elevation and regionally based on the general climate conditions. Consequently, the characteristics of ROS-driven winter floods are also anticipated to change. To investigate these changes, streamflow for multiple gauge stations in Germany was simulated using a deep learning model based on an ensemble of downscaled climate projections. Germany, as a representative mid-latitude country with a considerable portion of historical floods generated by ROS, offers extensive spatial and temporal coverage of hydrological observations spanning long temporal scales, and hence warranting efficient training of the deep learning model. We used explainable artificial intelligence to examine flood-generating processes, focusing primarily on ROS, for every simulated flood peak. Changes in frequency, feature importance, and magnitude of ROS flood events were assessed for individual streamflow gauges and for trans-basin floods across four major river basins in Germany. We found that with regard to the ensemble median, the frequency of ROS floods will decrease at the scale of individual gauges, as well as at the trans-basin scale for the Rhine, Elbe, and Weser River basins but increase in the Danube River basin. For all regions, the snowmelt component during ROS floods becomes less relevant, whereas the contribution of rainfall to these events increases. Interestingly, the severity of both the mean and the most extreme ROS trans-basin floods is projected to increase compared to the historical period in all major river basins in Germany, even though several individual gauges may experience a decrease in magnitude. Despite the overall agreement in the trends of the input features across climate models, the resulting trends in ROS floods are considerably disparate. This discrepancy is primarily attributed to the variations in snow dynamics in different climate models.