An Integrated Framework for Pluvial Flooding and Population Vulnerability Assessment Based on agent-based Approach with Urbanization Forecasting at Urban Scale

Xinyi Shu, Chenlei Ye () and Zongxue Xu
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Xinyi Shu: Beijing Normal University
Chenlei Ye: Beijing Normal University
Zongxue Xu: Beijing Normal University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2025, vol. 39, issue 12, No 5, 6093-6119

Abstract: Abstract The combined effects of urbanization and climate change have significantly increased the risk of urban flooding, placing unprecedented pressure on both urban drainage systems and social systems. However, existing studies primarily focus on flood modeling based on current urbanization conditions, often neglecting the dynamic processes of urbanization and their impact on surface runoff and surface inundation, as well as the associated uncertainties. Moreover, population vulnerability, directly influenced by surface flooding, exhibits significant heterogeneity across the social system. This study proposes an innovative framework to assess urban pluvial flooding and population vulnerability with urbanization. The framework consists of three main components: (1) Heuristic algorithms are employed to optimize the parameters of flood models, with the parameter combination of the best-performing algorithm enhancing the generalization capability; (2) The urban expansion patterns were simulated based on future urban area data, enabling flood simulation for future scenarios; and (3) Population vulnerability was analyzed using a bottom-up modeling approach. This framework was applied to Jinan, China. The results indicated that: The simulated 2018 urban built-up area (UBUA) is 231.26 km2, with a relative error of 0.53% compared to remote sensing observations. During the 50-year return period rainfall scenario, the average inundation depth in the UBUA for 2018 and 2038 are 0.30 m and 0.31 m, respectively. In road areas, the low−risk individual (LRI) decreases by 60.88% in 2018 and 62.95% in 2038.

Keywords: Urban Pluvial Flooding; Agent-based Model; Heuristic Algorithm; Urban Expansion Patterns (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11269-025-04242-2

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