Deciphering streamflow composition during drought – model simulations as benchmark for advanced hydrograph separation

Prediction of hydrological drought requires good process understanding of streamflow generation. It is known that during progressing drought the water availability in rivers is a composition of different delayed contributions from various stores in the catchments. However, the composition of delayed contributions often differs a lot across landscapes and hydrogeological settings. Solutes or isotope data sets are often limited to separate different contributions only during the campaign period in a specific catchment. Hydrological models incorporate delayed contribution typically with different soil and groundwater storages to simulate total streamflow. Here we analyzed the output from different storages of the water balance model LARSIM which is a well-established operational river forecasting model in Southern Germany. We hypothesized that the different storages' contributions can also be estimated by an advanced hydrograph separation method splitting total streamflow in four delayed contributions (i.e., storm flow, fast and slow interflow and baseflow). We used the Delayed Flow Index (DFI) for hydrograph separation as, compared to a BFI index, it estimates multiple storage-outflow components. Though not entirely similar in their results, the combined analysis of model simulations and DFI hydrograph has the potential to inform water management and forecasters about relevant time scales of different streamflow contributions and drought severity. The information of streamflow storage states and contributions may help hydrological drought prediction of time periods outside the model calibration period and also for periods when faster delayed contributions consecutively cease to sustain streamflow.