Validation of Urban Surface Water Flood Modeling with Multisource Data: Two Case Studies in Baoji and Linyi Cities, China

  • Guizhen Guo
  • , Jie Yin*
  • , Xuesong Yuan
  • , Ziqing Zhu
  • , Mingfu Guan
  • , Dapeng Yu
  • , Nigel Wright
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Urban areas are particularly vulnerable to surface water flooding in a changing environment. A large number of urban surface water flood models have been developed to derive flood inundations and support risk management. However, unlike fluvial and coastal flooding, urban pluvial flooding is often associated with shallow water and thus the model is difficult to validate with traditional monitoring data. In this study, we first developed a full two-dimensional (2D) hydrodynamic model for simulating surface water floods. We further evaluated the model performance with multisource data from flood incidents, including official reports and social media data. The model was tested in the cities of Baoji and Linyi, China, where two surface water flood events recently occurred and caused considerable losses and casualties. In total, 350 localized flooding incidents were obtained for the two cities (220 in Baoji and 130 in Linyi) and 313 reports were retained after data cleaning (202 in Baoji and 111 in Linyi). Over 90% of the reported flood incidents fall in urban areas where water depths are predicted to be higher than 0.15 m. The results demonstrate that the model is able to derive the broad patterns of flood inundation at the city scale. The approach tested here could be applied to other flood-prone cities and future research could include water depth information for more robust model validation.

Original languageEnglish
Pages (from-to)832-842
Number of pages11
JournalInternational Journal of Disaster Risk Science
Volume16
Issue number5
DOIs
StatePublished - Oct 2025

Keywords

  • Model validation
  • Multisource data
  • Surface water flooding
  • Urban flood modeling

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