Automatic method of flow direction reasoning for bridging tributaries using adjacency relation. (11th September 2022)

• Record Type: Journal Article
• Authors: Li, Chengming; Wu, Wei; Bai, Xiaofei; Yin, Yong; Wu, Zheng; Zhang, Chengcheng
• Is Part Of: River research and applications. Volume 38:Number 10(2022)
• Page Start: 1803
• Page End: 1814
• Publication Date: 2022-09-11
• Subjects: adjacency relation -- bridging tributaries -- complex river networks -- flow direction reasoning -- Kth‐order adjacency field; Rivers -- Regulation -- Periodicals; Rivers -- Periodicals; 551.483
• DOI: 10.1002/rra.4048
• Languages: English
• ISSNs: 1535-1459

Abstract

Abstract: Determining an accurate flow direction is a prerequisite for hydrographic analysis and river generalization. For river networks with complex spatial structures and little semantic information, it has always been a difficult and interesting problem to automatically and objectively determine the flow direction of all rivers. In a river network with many estuaries, tributaries may either be "simple tributaries" that are associated only with a single main channel or "bridging tributaries" that link multiple main channels. The former is large in number, while the latter is few, but both of them are very important in constructing the hierarchical relationship of the whole river network. Existing studies have concentrated on simple tributaries, and flow direction reasoning for bridging tributaries is ignored, leading to a misunderstanding of the spatial structure of river networks. To address this problem, an automatic method of flow direction reasoning for bridging tributaries using adjacency relation (FDR‐BR method) is proposed. First, in view of the insufficient semantic information in actual river data, the principle of "the minority is subordinate to the majority" is adopted to establish two statistical identification criteria for estuaries, and main channels are extracted by using the good continuity feature between river reaches, that is, stroke feature. Second, the Kth ‐order adjacency fields are constructed for each main channel based on the topological connection relationships between the main channels and tributaries. Finally, the "split river reaches" are detected from the bridging tributaries, and the spatial adjacency relation is used as a constraint to identify the benchmark main channel of each bridging tributary. The FDR‐BR method is validated using a geographical census dataset for a city in China. In the experimental area, simple river networks with independent main channels account for 91.67% of the networks, and complex river networks with multiple main channels account for 8.33%. For the complex river networks, 77.79% of the tributaries are simple tributaries, while 13.27% are bridging tributaries. The experimental results reveal that for all rivers in the simple river networks and the simple tributaries in the complex river networks, the flow direction reasoning results of FDR‐BR method are consistent with the results of the state‐of‐the‐art Schwenk method, with an accuracy of more than 98%; for the bridging tributaries in the complex river networks, the flow direction reasoning accuracy of the Schwenk method is only 59.3%, while the accuracy of FDR‐BR method reaches 98%, and the results are more realistic.