This study aims to utilize complex network theory and network immune strategies to identify relevant risks in urban river ecological governance projects and develop corresponding risk response strategies. By constructing a risk evolution network with 53 nodes and 255 edges, we analyzed the network’s degree centrality, betweenness centrality, closeness centrality, and composite value parameters, confirming the network’s scale-free characteristics. Based on this, we used network global efficiency as a metric to assess the network’s robustness under random and targeted attacks. The results revealed that under targeted attack scenarios, the degree value attack immune strategy performed optimally, while random immune strategies were less effective than targeted immune strategies. Moreover, this model offers various advantages in early risk response decision-making and establishing a forward-looking risk warning framework, providing an effective tool for risk management in urban river ecological governance projects.
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