Behavior of a Fully-Looped Drainage Network and the Corresponding Dendritic Networks

Hydraulic and hydrologic analysis in urban catchments is typically accompanied by a number of uncertainties, such as a lack of required information for modeling purposes or complex loops inside a drainage network. In this article, Gibbs’ stochastic network model is utilized in order to achieve a dendritic network that corresponds to a fully looped network in terms of the peak of the runoff hydrograph at the outlet. A synthetic catchment with a drainage network composed of 8 × 8 grids is introduced to investigate the behavior of a fully looped network for a given rainfall event using the Storm Water Management Model. Dendritic networks are generated from the Gibbsian model for a given value of the parameter, β. The results showed that the shape of the hydrograph and the peak flow of a fully looped network are heavily dependent on the catchment slope. Moreover, the results showed that it is possible to find the corresponding dendritic networks generated by the Gibbsian model that match the fully looped network depending on the catchment slope in terms of peak flows. The results of this study imply the potential improvement of drainage network analysis providing a relationship between the catchment slope of a fully looped network and the corresponding dendritic network generated by the Gibbsian model