The topology of Sanitary Sewer Networks (SSNs) can play an influential role in the occurrence and magnitude of operational failures such as blockages and basements flooding (Reyes-Silva et al., 2020). For example, meshed (grid-like) topologies are reported to be less vulnerable to failures compared to branched (tree-like) topologies (Zhang et al., 2017). However, in reality, most SSNs are reported to have a predominantly branched topology (Reyes-Silva et al., 2020). Therefore, it could be argued that the spatial behaviour of operational failures may be related to the topological properties of SSNs. This study explored this argument by investigating the spatial association between the location of recurrent blockages and the location of influential nodes within the network. Graph theory–centrality measures (Ganesan et al., 2020) and the network cross-K-function (Okabe and Sugihara, 2012) were the methods used. Secondly, the question of which structural, hydraulic or environmental factors may explain the identified spatial associations was also explored using geographically weighted regression (Fotheringham and Charlton, 2009). In lieu of robust properly calibrated hydraulic models, results from centrality measures and network cross k-function can support the discovery of influential locations within the topology of SSNs that may propagate recurrent blockages. Such influential locations may also be inception points for remedial actions such as redesigning, which may be more cost-effective in the long term compared to conventional approaches like flushing. Results from a preliminary application of centrality measures and network cross-function to the SSN of one municipality (total network length 500 km, ≈40 people/km) using its historical blockage data are presented.