Abstract
Urban infrastructure resilience is critical for sustainable development in rapidly urbanising regions. However, existing assessments often fail to capture the complex interdependencies between cities, which limits our understanding of topological evolution of resilience networks at the regional scale. This study presents a novel framework that integrates the pressure-state-response model with complex network theory to evaluate the evolution of infrastructure resilience across 41 cities in China’s Yangtze River Delta (YRD) from 2013 to 2022. With the help of ArcGIS and network analysis, considerable spatiotemporal dynamics was uncovered. Key results show that rapid resilience improvements in core cities have exacerbated regional inequalities. The performance in pressure, state and response subsystems exhibited distinct regional patterns. Network analysis indicated an increased cooperation in state and response systems, and the distribution of pressure sources was relatively dispersed. Furthermore, key node cities were most dynamic within the pressure network and remained relatively stable in the state and response networks. These insights offer a valuable decision-support tool for achieving balanced and resilient urban construction in the YRD and similar metropolitan regions.
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Data availability
Data is provided within the supplementary information files. The data of Indicator X4 that support the findings of this study are available from National Meteorological Science Data Center but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of National Meteorological Science Data Center.
References
Feng, X., Zeng, F., Loo, B. P. & Zhong, Y. The evolution of urban ecological resilience: an evaluation framework based on vulnerability, sensitivity and self-organization. Sustainable Cities Soc. 116, 105933 (2024).
Aguilar-Barajas, I., Sisto, N. P., Ramirez, A. I. & Magaña-Rueda, V. Building urban resilience and knowledge co-production in the face of weather hazards: flash floods in the Monterrey metropolitan area (Mexico). Environ. Sci. Policy. 99, 37–47 (2019).
Sun, Y., Chau, P. H., Wong, M. & Woo, J. Place-and age-responsive disaster risk reduction for Hong kong: collaborative place audit and social vulnerability index for elders. Int. J. Disaster Risk Sci. 8, 121–133 (2017).
Rolf, M. et al. Flooding frequency and floodplain topography determine abundance of microplastics in an alluvial rhine soil. Sci. Total Environ. 836, 155141 (2022).
Zhang, X., Song, J., Peng, J. & Wu, J. Landslides-oriented urban disaster resilience assessment—A case study in ShenZhen, China. Sci. Total Environ. 661, 95–106 (2019).
Ayyub, B. M. Systems resilience for multihazard environments: Definition, metrics, and valuation for decision making. Risk Anal. 34, 340–355 (2014).
Dhakal, S. & Zhang, L. A social welfare-based infrastructure resilience assessment framework: toward equitable resilience for infrastructure development. Nat. Hazards Rev. 24, 04022043 (2023).
Hémond, Y. & Robert, B. Evaluation of state of resilience for a critical infrastructure in a context of interdependencies. Int. J. Crit. Infrastruct. 4, 95–106 (2012).
Karamouz, M., Taheri, M., Khalili, P. & Chen, X. Building infrastructure resilience in coastal flood risk management. J. Water Resour. Plan. Manag. 145, 0001043 (2019).
Nogal, M., O’Connor, A., Martinez-Pastor, B. & Caulfield, B. Novel probabilistic resilience assessment framework of transportation networks against extreme weather events. Asce-Asme J. Risk Uncertain. Eng. Syst. Part. a-Civil Eng. 3, 04017003 (2017).
Cutter, S. L., Ash, K. D. & Emrich, C. T. Urban–rural differences in disaster resilience. Annals Am. Association Geographers. 106, 1236–1252 (2016).
Quinlan, A. E., Berbés-Blázquez, M., Haider, L. J. & Peterson, G. D. Measuring and assessing resilience: broadening Understanding through multiple disciplinary perspectives. J. Appl. Ecol. 53, 677–687 (2016).
Huang, W. & Ling, M. System resilience assessment method of urban lifeline system for GIS. Comput. Environ. Urban Syst. 71, 67–80 (2018).
Chen, T., Chen, L., Shao, Z. & Chai, H. Enhanced resilience in urban stormwater management through model predictive control and optimal layout schemes under extreme rainfall events. J. Environ. Manage. 366, 121767 (2024).
Orencio, P. M. & Fujii, M. A localized disaster-resilience index to assess coastal communities based on an analytic hierarchy process (AHP). Int. J. Disaster Risk Reduct. 3, 62–75 (2013).
Zarei, E., Ramavandi, B., Darabi, A. H. & Omidvar, M. A framework for resilience assessment in process systems using a fuzzy hybrid MCDM model. J. Loss Prev. Process Ind. 69, 104375 (2021).
Jiao, L. et al. An assessment model for urban resilience based on the pressure-state-response framework and BP-GA neural network. Urban Clim. 49, 101543 (2023).
Ge, Y., Jia, W., Zhao, H. & Xiang, P. A framework for urban resilience measurement and enhancement strategies: A case study in Qingdao, China. J. Environ. Manage. 367, 122047 (2024).
Sun, Y. & Cui, Y. Analyzing the coupling coordination among economic, social, and environmental benefits of urban infrastructure: Case study of four Chinese autonomous municipalities. Mathematical Problems in Engineering, 8280328 (2018). (2018).
Rapport, D. Towards a comprehensive framework for environmental statistics: a stress-response approach. Statistics Canada. https://publications.gc.ca/site/eng/9.896799/publication.html (1979).
Khatun, R. & Das, S. Assessment of wetland ecosystem health in Rarh Region, India through PSR (pressure-state-response) model. Sci. Total Environ. 951, 175700 (2024).
Zhao, Y., Zhou, L., Dong, B. & Dai, C. Health assessment for urban rivers based on the pressure, state and response framework—A case study of the Shiwuli river. Ecol. Ind. 99, 324–331 (2019).
Zhang, T., Sun, Y., Zhang, X., Yin, L. & Zhang, B. Potential heterogeneity of urban ecological resilience and urbanization in multiple urban agglomerations from a landscape perspective. J. Environ. Manage. 342, 118129 (2023).
Chen, X. et al. Assessment of flood risk in Jinsha river basin based on land use value and PSR model. Phys. Chem. Earth Parts A/B/C. 141, 104139 (2025).
Jatav, S. S. & Naik, K. Measuring the agricultural sustainability of india: an application of Pressure-State-Response (PSR) model. Reg. Sustain. 4, 218–234 (2023).
Casali, Y., Aydin, N. Y. & Comes, T. A data-driven approach to analyse the co-evolution of urban systems through a resilience lens: A Helsinki case study. Environ. Plann. B: Urban Analytics City Sci. 51, 2074–2091 (2024).
Zhang, R., Li, Y., Li, C. & Chen, T. A complex network approach to quantifying flood resilience in high-density coastal urban areas: A case study of Macau. Int. J. Disaster Risk Reduct. 119, 105335 (2025).
Ashja-Ardalan, S., Alesheikh, A. A., Sharif, M. & Wittowsky, D. Resilience of urban road networks to climate change: a spatial-topological approach. Transp. Res. Part. D: Transp. Environ. 148, 104948 (2025).
Zhang, Y., Song, R., Zhang, K. & Wang, T. The characteristics and modes of urban network evolution in the Yangtze river delta in China from 1990 to 2017. Ieee Access. 9, 5531–5544 (2021).
Zhang, W., Liu, G., Gonella, F., Xu, L. & Yang, Z. Research on collaborative management and optimization of ecological risks in urban agglomeration. J. Clean. Prod. 372, 133735 (2022).
Li, J., Sun, C. & Zheng, X. Assessment of spatio-temporal evolution of regionally ecological risks based on adaptive cycle theory: A case study of Yangtze river delta urban agglomeration. J. Ecol. 41, 2609–2621 (2021).
Zhu, S., Feng, H., Arashpour, M. & Zhang, F. Enhancing urban flood resilience: A coupling coordinated evaluation and geographical factor analysis under SES-PSR framework. Int. J. Disaster Risk Reduct. 101, 104243 (2024).
Wang, Z., Wang, L., Xu, R., Huang, H. & Wu, F. GIS and RS based assessment of cultivated land quality of Shandong Province. Procedia Environ. Sci. 12, 823–830 (2012).
Li, J., Pei, W., Li, Y., Liu, S., Chen, Y., Wang, B., … Zhang, J. Evaluating and diagnosing ecosystem health of the three-lake watershed in Yuxi, Yunnan, China from 2010 to 2020 by PSR-KDE. Environmental Research, 258, 119406 (2024).
Sahana, M. et al. Assessing wetland ecosystem health in Sundarban biosphere reserve using pressure-state-response model and Geospatial techniques. Remote Sens. Applications: Soc. Environ. 26, 100754 (2022).
Sun, B., Tang, J., Yu, D., Song, Z. & Wang, P. Ecosystem health assessment: A PSR analysis combining AHP and FCE methods for Jiaozhou Bay, China. Ocean. Coastal. Manage. 168, 41–50 (2019).
Yang, X., Li, H., Zhang, J., Niu, S. & Miao, M. Urban economic resilience within the Yangtze river delta urban agglomeration: exploring Spatially correlated network and Spatial heterogeneity. Sustainable Cities Soc. 103, 105270 (2024).
Hu, X., Ma, C., Huang, P. & Guo, X. Ecological vulnerability assessment based on AHP-PSR method and analysis of its single parameter sensitivity and Spatial autocorrelation for ecological protection–A case of Weifang City, China. Ecol. Ind. 125, 107464 (2021).
Zhu, S., Li, D., Feng, H. & Zhang, N. The influencing factors and mechanisms for urban flood resilience in china: from the perspective of social-economic-natural complex ecosystem. Ecol. Ind. 147, 109959 (2023).
Fernandez, M. A., Bucaram, S. J. & Renteria, W. Assessing local vulnerability to climate change in Ecuador. SpringerPlus 4, 1–20 (2015).
Cutter, S. L., Burton, C. G. & Emrich, C. T. Disaster resilience indicators for benchmarking baseline conditions. J. Homel. Secur. Emerg. Manage. 7, 1–22 (2010).
Hazbavi, Z., Sadeghi, S. H., Gholamalifard, M. & Davudirad, A. A. Watershed health assessment using the pressure–state–response (PSR) framework. Land. Degrad. Dev. 31, 3–19 (2020).
Mou, Y., Luo, Y., Su, Z., Wang, J. & Liu, T. Evaluating the dynamic sustainability and resilience of a hybrid urban system: case of Chengdu, China. J. Clean. Prod. 291, 125719 (2021).
Rezvani, S. M., de Almeida, N. M., Falcao, M. J. & Duarte, M. Enhancing urban resilience evaluation systems through automated rational and consistent decision-making simulations. Sustainable Cities Soc. 78, 103612 (2022).
Zhang, Y. & Shang, K. Cloud model assessment of urban flood resilience based on PSR model and game theory. Int. J. Disaster Risk Reduct. 97, 104050 (2023).
Fenner, R. et al. Achieving urban flood resilience in an uncertain future. Water 11, 1082 (2019).
Lee, D. W. An exploratory assessment of infrastructure resilience to disasters. Int. J. Disaster Resil. Built Environ. 11, 519–533 (2020).
Xu, K., Zhang, X., Bin, L. & Shen, R. An improved global resilience assessment method for urban drainage systems: A case study of Haidian Island, South China. J. Environ. Manage. 360, 121135 (2024).
Guo, Z. et al. Urban agglomeration transportation resilience: evaluation and evolution analysis using a data-driven model. Environ. Sustain. Indic. 26, 100714 (2025).
Chen, M., Jiang, Y., Wang, E., Wang, Y. & Zhang, J. Measuring urban infrastructure resilience via pressure-state-response framework in four Chinese municipalities. Appl. Sci. 12, 2819 (2022).
Xu, W., Cong, J. & Proverbs, D. G. Evaluation of infrastructure resilience. Int. J. Building Pathol. Adaptation. 41, 378–400 (2023).
Gao, X., Yuan, Z., Liu, X., Liu, F. & Kou, C. Achieving urban ecosystem resilience: static and dynamic attack simulation and cascading failure analysis of urban blue-green infrastructure networks. Ecol. Ind. 179, 114205 (2025).
Lai, S. et al. Evaluation of ecological security and ecological maintenance based on pressure-state-response (PSR) model, case study: Fuzhou city, China. Hum. Ecol. Risk Assessment: Int. J. 28, 734–761 (2022).
Yao, J., Chen, G., Yao, B. & Wu, J. Urban resilience assessment matrix considering Spatiotemporal processes: model proposal and application. Sustainable Cities Soc. 135, 106988 (2025).
Luthar, S. S., Cicchetti, D. & Becker, B. The construct of resilience: A critical evaluation and guidelines for future work. Child Dev. 71, 543–562 (2000).
Xu, W. & Tianyan, W. Resilience assessment of urban emergency management for emergencies. E3S Web of Conferences, 276, 02015 (2021).
Zhang, C., Zhou, Y. & Yin, S. Interaction mechanisms of urban ecosystem resilience based on pressure-state-response framework: A case study of the Yangtze river delta. Ecol. Ind. 166, 112263 (2024).
Cutter, S. L. et al. A place-based model for Understanding community resilience to natural disasters. Global Environ. Change-Human Policy Dimensions. 18, 598–606 (2008).
Huang, G., Li, D., Zhu, X. & Zhu, J. Influencing factors and their influencing mechanisms on urban resilience in China. Sustainable Cities Soc. 74, 103210 (2021).
Hwang, C. L., Lai, Y. J. & Liu, T. Y. A new approach for multiple objective decision making. Computers Oper. Res. 20, 889–899 (1993).
Zavadskas, E. K., Mardani, A., Turskis, Z., Jusoh, A. & Nor, K. M. D. Development of TOPSIS method to solve complicated Decision-Making problems: an overview on developments from 2000 to 2015. Int. J. Inform. Technol. Decis. Mak. 15, 645–682 (2016).
Xun, X. & Yuan, Y. Research on the urban resilience evaluation with hybrid multiple attribute TOPSIS method: an example in China. Nat. Hazards. 103, 557–577 (2020).
Peng, Y., Zheng, R., Yuan, T., Cheng, L. & You, J. Evaluating perception of community resilience to typhoon disasters in China based on grey relational TOPSIS model. Int. J. Disaster Risk Reduct. 84, 103468 (2023).
Wen, G. & Ji, F. Flood resilience assessment of region based on TOPSIS-BOA-RF integrated model. Ecol. Ind. 169, 112901 (2024).
Lv, B. et al. Evaluation of the water resource carrying capacity in Heilongjiang, Eastern China, based on the improved TOPSIS model. Ecol. Ind. 150, 110208 (2023).
Marzouk, M. & Sabbah, M. AHP-TOPSIS social sustainability approach for selecting supplier in construction supply chain. Clean. Environ. Syst. 2, 100034 (2021).
Zhang, X., Zhang, Q., Sun, T., Zou, Y. & Chen, H. Evaluation of urban public transport priority performance based on the improved TOPSIS method: A case study of Wuhan. Sustainable Cities Soc. 43, 357–365 (2018).
Beskese, A., Demir, H. H., Ozcan, H. K. & Okten, H. E. Landfill site selection using fuzzy AHP and fuzzy TOPSIS: a case study for Istanbul. Environ. Earth Sci. 73, 3513–3521 (2015).
Singh, N., Krishnaswamy, V. & Zhang, J. Z. Intellectual structure of cybersecurity research in enterprise information systems. Enterp. Inform. Syst. 17, 2025545 (2023).
Zhu, Z., Zheng, Y. & Xiang, P. Deciphering the Spatial and Temporal evolution of urban anthropogenic resilience within the Yangtze river delta urban agglomeration. Sustainable Cities Soc. 88, 104274 (2023).
Hu, P., Huang, Y., He, Q. & Zhang, G. Can urban agglomeration policies promote regional economic agglomeration? Evidence from the Yangtze river economic belt in China. Environ. Plann. B: Urban Analytics City Sci. 52, 1335–1352 (2025).
Cao, Z., Derudder, B. & Peng, Z. Comparing the physical, functional and knowledge integration of the Yangtze river delta city-region through the lens of inter-city networks. Cities 82, 119–126 (2018).
Zhang, W., Derudder, B., Wang, J. & Shen, W. Regionalization in the Yangtze river Delta, China, from the perspective of inter-city daily mobility. Reg. Stud. 52, 528–541 (2018).
Fujita, M. & Thisse, J. F. Does geographical agglomeration foster economic growth? And who gains and loses from it? Japanese Economic Rev. 54, 121–145 (2003).
Gu, Y., Shi, R., Zhuang, Y., Li, Q. & Yue, Y. How to determine City hierarchies and Spatial structure of a megaregion? Geo-spatial Inform. Sci. 27, 276–288 (2024).
Krugman, P. Increasing returns and economic geography. J. Polit. Econ. 99, 483–499 (1991).
Cohen, W. M. & Levinthal, D. A. Absorptive capacity: A new perspective on learning and innovation. Adm. Sci. Q. 35, 128–152 (1990).
Boschma, R. & Iammarino, S. Related variety, trade linkages, and regional growth in Italy. Econ. Geogr. 85, 289–311 (2009).
Li, S. & Wu, L. Can regional integration promote industrial green transformation? Empirical evidence from Yangtze river delta urban agglomeration. J. Environ. Stud. Sci. 14, 117–134 (2024).
Gallopín, G. C. Linkages between vulnerability, resilience, and adaptive capacity. Glob. Environ. Change. 16, 293–303 (2006).
Folke, C., Hahn, T., Olsson, P. & Norberg, J. Adaptive governance of social-ecological systems. Annu. Rev. Environ. Resour. 30, 441–473 (2005).
Satterthwaite, D. The political underpinnings of cities’ accumulated resilience to climate change. Environ. Urbanization. 25, 381–391 (2013).
Yu, Y. & Lyu, L. Spatial pattern of knowledge innovation function among Chinese cities and its influencing factors. J. Geog. Sci. 33, 1161–1184 (2023).
Wang, Y., Wang, G. & Chen, G. Network externalities of the innovation network in china’s five urban agglomerations: based on buzz-and-pipeline theory. Humanit. Social Sci. Commun. 12, 1–20 (2025).
Namatame, A. & Tran, H. A. Q. Enhancing the resilience of networked agents through risk sharing. Adv. Complex. Syst. 16, 1350006 (2013).
Wang, D. & Chen, S. Synergistic action on mitigation and adaptation pilot policies to enhance low-carbon resilience of Chinese cities. Nat. Cities. 2, 812–824 (2025).
Reggiani, A. The architecture of connectivity: a key to network vulnerability, complexity and resilience. Networks Spat. Econ. 22, 415–437 (2022).
Lu, H., Lu, X., Jiao, L. & Zhang, Y. Evaluating urban agglomeration resilience to disaster in the Yangtze delta City group in China. Sustainable Cities Soc. 76, 103464 (2022).
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This work is funded by the National Natural Science Foundation of China (Grant No. 72471214) and the Fundamental Research Funds for the Central Universities of Ministry of Education of China: the Youth Innovation Fund of University of Science and Technology of China (WK2040250137).
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Xihui Wang, Mei Sun and Minlian Wu wrote the main manuscript, and Mei Sun and Minlian Wu prepared all figures. All authors reviewed the manuscript.
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Wang, X., Sun, M. & Wu, M. Recognizing resilience evolution and connectivity in the Yangtze River Delta urban agglomeration. Sci Rep (2026). https://doi.org/10.1038/s41598-025-34716-7
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DOI: https://doi.org/10.1038/s41598-025-34716-7


