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Urban inundation mapping by coupling 1D − 2D models and model comparison

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Abstract

Urban inundation mapping is important for early warning, management, and drainage network planning. Urban flood simulations typically utilize a 1D model focused on pipe nodes, whereas 2D simulations are required over a land area. In this paper, our focus is on their coupling, so that a dynamic 1D-2D model is obtained. We couple the Storm Water Management Model (SWMM), a widely utilized urban drainage model, with 2D models to simulate urban inundation. The 1D-2D coupled inundation model uses the 1D model output, which represents the overflow volume of sparsely distributed pipe nodes. After coupling, surface inundation distribution maps are obtained. We developed a physically-based 2D overflow diffusion model (2D-DM) and compared it with two geostatistical models: Ordinary co-kriging (OCK) and Regression Kriging (RK). The study area is the central area of Haining City in China, where a severe storm occurred on August 3, 2018. The 2D-DM performed best (RMSE = 0.232), followed by RK (RMSE = 0.286), and OCK (RMSE = 0.361), but did not provide uncertainty measures, in contrast to the geostatistical models. We conclude that 1D-2D coupling was done successfully, with the different 2D models showing different qualities. To enhance urban inundation mapping, it is suggested to couple the 1D model with both physical and statistically based 2D models for a more comprehensive assessment of potential inundation areas and depths.

Original languageEnglish
Article number103869
Number of pages10
JournalInternational Journal of Applied Earth Observation and Geoinformation
Volume130
Early online date1 May 2024
DOIs
Publication statusPublished - Jun 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • UT-Gold-D
  • Spatial statistical models
  • SWMM
  • Urban inundation mapping
  • 1D-2D Coupled model

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