To address the challenges of "typhoon-burst storm surge" compound rainwater disasters in coastal cities under global climate change, this study focuses on Lianyungang City to develop a resilience assessment framework encompassing four dimensions: natural geography, infrastructure, socioeconomic conditions, and emergency management. The research employs a hybrid approach combining Analytic Hierarchy Process (AHP) and entropy weighting to determine indicator weights, followed by fuzzy comprehensive evaluation for quantitative resilience assessment. Four resilience zones are delineated: high, moderately high, moderately low, and low. Results indicate that Lianyungang's overall rainwater disaster resilience is moderately low, with natural geography demonstrating relatively better performance while infrastructure and emergency management remain critical weaknesses. High-resilience zones are concentrated in the new urban area, whereas low-resilience zones are predominantly located in the old urban area and coastal low-lying regions. These findings aim to provide scientific basis for Lianyungang's territorial spatial planning, disaster prevention and mitigation engineering, and optimization of emergency management systems.

Zhang Xingxing, Lu Mingxing, Zhou Yu. Research on the Influencing Factors and Evaluation System of Urban Resilience in Lianyungang under Rain and Flood Disasters. Academic Journal of Environment & Earth Science (2026), Vol. 8, Issue 1: 57-67. https://doi.org/10.25236/AJEE.2026.080109.

[1] Shen Y ,Goodall L J ,Chase B S .Condition State–Based Civil Infrastructure Deterioration Model on a Structure System Level[J].Journal of Infrastructure Systems,2019,25(1)

[2] Wang, L., Bian, L., Leon, S.A., et  al. Integrating  Policy  Instruments   for  Enhanced  Urban Resilience: A Machine Learning and IoT-Based Approach to Flood Mitigation[J].Water,2024, 16(23)

[3] Behzad Jamali, Roland Löwe, Peter M. Bach, Christian Urich, Karsten Arnbjerg-Nielsen, Ana Deletic. A  rapid  urban  flood  inundation  and  damage  assessment  model[J].Journal  of Hydrology, 2018,564

[4] Apreda C ,D ’Ambrosio V ,Martino D F .A climate vulnerability and impact assessment model for complex urban systems[J].Environmental Science and Policy,2019,93:11-26.

[5] Estelaji F, Zahedi R, Gitifar A, et al. Integrating HEC-RAS,GIS, and LISREL for assessing and enhancing  urban  building  resilience  against  flood  threats: Comprehensive  model  and analysis[J]. Heliyon,2024, 10(20)

[6] Shang Lei, Zhang Youzhi, Zhang Dongyin, Zhong Yuan. Assessment of Disaster Resilience in Old Communities under the Perspective of Flood Disasters: An Empirical Study Based on PSR Model and BPNN [J]. Science and Technology in Engineering, 2023,23(26):11338-11348.

[7] Shang Lei. Assessment and Enhancement Strategies of Disaster Resilience in Urban Old Communities under Flood Scenarios [D]. Jiangsu University of Science and Technology, 2023.

[8] Shang Cuyu. Assessment of Urban Flood Risk and Resilience under Rainstorm Flood Scenarios [D]. Beijing University of Civil Engineering and Architecture, 2023.

[9] Dong Hanru. Assessment of Drainage Capacity and Flood Risk Simulation in Typical New Urban Areas of North China [D]. North China University of Water Resources and Electric Power, 2023.

[10] Xu H. Risk assessment of urban flooding in the old urban area of Yingtan City [D]. Guangxi University, 2023.

[11] He Xianzhi, Zhai Guofang. Resilient Response to Urban Flood Disasters [J]. Disaster Prevention Expo, 2024, (04):4-9.

[12] Luan Chunfeng, Shi Zhaohui, Zhao Renjing, Cui Yiwen. Risk assessment of rainwater and flood disasters in mountainous small towns based on GIS technology [J]. People's Yellow River, 2024, 46(05):56-62+67.

[13] Wang BK. Assessment Methods and Planning Strategies for Rainwater Flood Resilience in Small Towns of Hanzhong Basin [D]. Xi'an University of Architecture and Technology, 2024.

[14] Li Ziyang. Environmental Sensitivity Assessment and Smart Development of Traditional Villages in Central Henan Region under Flood Disaster Context [D]. Henan Polytechnic University, 2023.

[15] Song Qinyuan, Zhang Boxiang, Ma Donghui, et al. A comprehensive review of quantitative assessment methods for community flood resilience [J]. Disaster Science, 2024,39(02):212-219.

[16] Chen Junfei, Ding Jiamin, Deng Menghua. Research progress on risk assessment and management of urban rainstorm disasters [J]. Disaster Science, 2020,35(02):154-159+166.

[17] Chen CK, Chen YQ, Shi B, et al. Urban resilience assessment model under rainstorm disaster scenarios [J]. China Journal of Safety Science, 2018,28(04):1-6.

[18] Wang Shuangling, Xu Na, Hu Yuting, Li Xiangyu, Yang Jiaqi, Yuan Yue. Review on Simulation and Early Warning Technology of Urban Rainwater Flood Disaster[J]. Project Management Technology, 2023,21(11):55-61.

[19] Fan Chenxi. Morphological Resilience Assessment of Historic Urban Areas from the Perspective of Flood Disaster Prevention [D]. South China University of Technology, 2023.

[20] Zhao Dongyue, Chen Changkun, Yi Liang, et al. Research on a Multi-factor Comprehensive Evaluation Model for Urban Resilience [J]. China Safety Science and Technology, 2022,18(05):54-59.

[21] Chen Shengda, Feng Yijun, Zheng Wenxin, et al. Urban resilience evaluation model and application from the perspective of rainwater resilience-Taking Hangzhou as an example [C]// China Urban Planning Society, Hefei Municipal People's Government. Beautiful China, co-building, co-governing, and sharing-Proceedings of the 2024 China Urban Planning Annual Conference (02 Urban Safety and Disaster Prevention Planning). Hangzhou Urban Planning and Design Research Institute; 2024:445-452.

[22] SAATY T L , VA R GAS L G . Models , methods , concepts and applications of the analytic hierarchy process [J]. International , 2012,7( 2): 159-172.