Characteristics of intergovernmental cooperation network for water pollution prevention and control in the Yangtze River Delta urban agglomeration and influencing factors

[Objective] An effective intergovernmental cooperation network and a robust foundation for collaboration are essential for the effective control of transboundary water pollution. This study examined the factors that influence the intergovernmental cooperation network for water pollution prevention and control in the Yangtze River Delta urban agglomeration. The objective was to provide scientific policy recommendations and practical references for the governance of regional water pollution. [Methods] The study used data from water pollution prevention policies and agreements issued by local governments of 27 cities between 2017 and 2023 in the Yangtze River Delta urban agglomeration. It employed social network analysis and GIS spatial analysis to examine the intergovernmental cooperation network for water pollution prevention. Based on this, the quadratic assignment procedure (QAP) model used three primary indicators—economic, geographic, and environmental—and eight secondary indicators to measure their impacts on the intergovernmental cooperation network for water pollution prevention. [Results] (1) The water pollution prevention cooperation network was large, forming three distinct subgroups centered around the Shanghai-Suzhou, Nanjing-Hefei, and Hangzhou-Ningbo urban alliances. (2) The cooperation network was significantly correlated with multiple indicators: economically, it was closely related to total GDP, fiscal autonomy, and the proportion of the secondary industry; geographically, it was influenced by whether cities belong to the same metropolitan area, the same river basin, or are geographically adjacent; environmentally, it was associated with permanent population density and COD emissions. (3) Regression analysis indicated that geographic factors had the greatest impact on the cooperation network, with environmental governance agreements primarily established between geographically proximate cities. Fiscal autonomy among economic factors and COD emissions among environmental factors also influenced cross-boundary cooperative management to some extent. [Conclusion] Currently, the water pollution cooperative management network is passive, based mainly on geographic proximity and metropolitan area affiliation. In the future, more collaborative actions based on holistic watershed management are needed.