A network-based framework for identifying potential synchronizations and amplifications of sediment delivery in river basins

Long-term prediction of environmental response to natural and anthropogenic disturbances in a basin becomes highly uncertain using physically based distributed models, particularly when transport time scales range from tens to thousands of years, such as for sediment. Yet, such predictions are needed as changes in one part of a basin now might adversely affect other parts of the basin in years to come. In this paper, we propose a simplified network-based predictive framework of sedimentological response in a basin, which incorporates network topology, channel characteristics, and transport-process dynamics to perform a nonlinear process-based scaling of the river-network width function to a time-response function. We develop the process-scaling formulation for transport of mud, sand, and gravel, using simplifying assumptions including neglecting long-term storage, and apply the methodology to the Minnesota River Basin. We identify a robust bimodal distribution of the sedimentological response for sand of the basin which we attribute to specific source areas, and identify a resonant frequency of sediment supply where the disturbance of one area followed by the disturbance of another area after a certain period of time, may result in amplification of the effects of sediment inputs which would be otherwise difficult to predict. We perform a sensitivity analysis to test the robustness of the proposed formulation to model parameter uncertainty and use observations of suspended sediment at several stations in the basin to diagnose the model. The proposed framework has identified an important vulnerability of the Minnesota River Basin to spatial and temporal structuring of sediment delivery.