Individual Importance Classification of Urban Stormwater Channel Networks: A Novel Approach Based on Permutation and Algebraic Graph Theory

The frequency and intensity of urban flooding continuously increase due to the dual influences of climate change and urbanization. Conducting individual importance classification of urban stormwater channel networks (USCNs) is of significant importance for alleviating urban flooding and facilitating targeted stormwater management implementation. However, a quantitative classification method is lacking for trellis networks, which are a common type of USCN. This study proposed a novel importance classification methodology for channel segments in most types of USCNs, especially suitable for trellis networks, based on permutation and algebraic graph theory. The concept of permutation was integrated into the methodology to measure the importance of each channel segment to the USCN. Algebraic graph theory was employed to quantify the topological structure and hydraulic characteristics of the USCN. To verify the applicability and rationality of the proposed methodology, a real-world city with trellis USCNs in China (i.e., Huai’an) was selected as the study area. Seventy channel segments in the USCN were efficiently classified into three categories based on individual importance. This study provided a decision-support methodology from the perspective of individual importance classification in the USCN and offered valuable reference for urban flooding managers.