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A large variety of barriers can affect longitudinal connectivity, which leads to shipping blocking and even flood hazard. However, few existing methods can quantify physically the river channel connectivity from the barrier’s details perspective in a watershed. This paper establishes a new model of the River Channel Connectivity Index (RCCI) to quantify the unobstructed degree of river flow in river channels within geographic information system (GIS ) platforms based on the modified concept of time accessibility. A comprehensive classification system of barriers is setup before these barriers are identified by the remote sensing technology. The model is applied to Dashi Watershed in suburban Beijing, China. Results show that submersible bridges and sediment siltation are the main barriers in the watershed. RCCI values in the mountainous areas are generally higher than that of the plains. The assessment results verified by two historical flood events show that the RCCI can reveal where the river channel connectivity is impaired, how serious it is, and what the reason is for managers. Through scenarios’ results, the best restoration measure for each tributary is obtained from the perspective of reducing flood hazards. The new RCCI method not only has methodological significance, but also helps policymakers to enhance river flooding reduction and determine restoration priorities of the river channel.

Barrier-based Longitudinal Connectivity Index for Managing Urban Rivers