Hydraulic- hydromorphologic analysis as an aid for improving peak flow predictions

Abstract: Conventional hydrological compartmental models have been shown to exhibit a high degree of uncertainty for predictions of peak flows, such as the design floods for design of hydropower infrastructure. One reason for these uncertainties is that conventional models are parameterised using statistical methods based on how catchments have responded in the past. Because the rare occurrence of peak flows, these are underrepresented during the periods used for calibration. This implies that the model has to be extrapolated beyond the discharge intervals where it has been calibrated.In this thesis, hydromechanical approaches are used to investigate the properties of stream networks, reflecting mechanisms including stage dependency, damming effects, interactions between tributaries (network effects) and the topography of the stream network. Further, it is investigated how these properties can be incorporated into the streamflow response functions of compartmental hydrological models.The response of the stream network was shown to vary strongly with stage in a non-linear manner, an effect that is commonly not accounted for in model formulation. The non-linearity is particularly linked to the flooding of stream channels and interactions with the flow on flood-plains.An evaluation of the significance of using physically based response functions on discharge predictions in a few sub-catchments in Southern Sweden show improvements (compared to a conventional model) in discharge predictions – particularly when modelling peak discharges.An additional benefit of replacing statistical parameterisation methods with physical parameterisation methods is the possibility of hydrological modelling during non-stationary conditions, such as the ongoing climate change.