Luan et al. (2026) Revealing the relationship between storm surge risks and coastal urbanization characteristics under sea level rise

Identification

• Journal: Ecological Indicators
• Year: 2026
• Date: 2026-01-18
• Authors: Bo Luan, X. X. Ye, Jianing Luo, Shiqi Xie, Chenxi Xia, Yanhong Ning, Mingjian Zhu
• DOI: 10.1016/j.ecolind.2026.114626

Research Groups

• Green Infrastructure Institute, Peking University Shenzhen Institute, Shenzhen, China
• Shenzhen Key Laboratory of Environmental Simulation and Pollution Control, Shenzhen, China
• School of Design, South China University of Technology, Guangzhou, China

Short Summary

This study investigates the relationship between storm surge risks and coastal urbanization characteristics in Shenzhen under sea level rise (SLR) scenarios, revealing that extensive land reclamation and artificial land use significantly exacerbate inundation risks, particularly for critical infrastructure.

Objective

• To assess the exposure risk and map the inundation extent of critical land uses under combined SLR and storm surge scenarios in Shenzhen.
• To quantify the statistical linkages between key urbanization metrics and storm surge impacts, identifying the relative contribution of each factor.
• To propose targeted adaptation strategies for Shenzhen based on the simulation results.

Study Configuration

• Spatial Scale: Shenzhen, China, focusing on its coastal zone (a 1 km inland buffer from the shoreline baseline, covering approximately 336.86 km2 of land area).
• Temporal Scale:
  • Historical typhoon records: 1949–2015 (CMA dataset), 1965–2021 (tropical cyclones near Shenzhen).
  • Land reclamation data: 1988, 1995, 2000, 2005, 2010, and 2024.
  • Land use data: 2018.
  • NDVI data: 2021.
  • Population data: 2020.
  • SLR projections: by 2100 under SSP2-4.5 and SSP5-8.5 scenarios.
  • Typhoon Mangkhut simulation: September 7–17, 2018.

Methodology and Data

• Models used:
  • MIKE 21 hydrodynamic model (for storm surge simulation).
  • Holland model (for wind field configuration).
  • Tidal Analysis and Prediction module (for tidal forcing).
  • Gumbel distribution (Extreme Value Type I) (for 100-year, 200-year, and 1000-year return period typhoon intensity calculation).
  • Univariate and Multiple Linear Regression models (for statistical analysis of urbanization factors).
  • Kriging interpolation method (for generating inundation maps).
• Data sources:
  • Shoreline data: GEODAS-NG software (National Centers for Environmental Information, NCEI).
  • Bathymetric data: ETOPO2022 global relief model.
  • Terrestrial elevation data: Geospatial Data Cloud platform (www.gscloud.cn).
  • Typhoon Mangkhut wind field parameters: Wenzhou Typhoon Network (wztf121.com).
  • Historical tropical cyclone best-track dataset (1949–2015): China Meteorological Administration (CMA).
  • Sea Level Rise (SLR) projections: NASA's Sea Level Projection Tool.
  • Land use data (2018): Shenzhen Municipal Planning and Natural Resources Bureau.
  • Land reclamation areas: Manually identified and delineated from Google Earth Pro satellite imagery (1988, 1995, 2000, 2005, 2010, 2024) using ArcGIS 10.8.
  • Population density data: LandScan Population Dataset (https://landscan.ornl.gov/).
  • Nighttime light data: “Luojia-1” satellite dataset (http://59.175.109.173:8888/index.html).
  • Normalized Difference Vegetation Index (NDVI) data (2021): National Ecological Science Data Center.
  • Tidal gauge observations (for model validation): National Marine Data and Information Service (Shekou Station, Nei Lingding Island Station, September 15–17, 2018).

Main Results

• The maximum inundation extent from a 1000-year typhoon (without SLR) is 106.74 km2 (5.34% of Shenzhen's land area), with a maximum depth of 5.70 m.
• Under the adverse SLR scenario (SSP5-8.5 by 2100), the 1000-year typhoon inundation area increases to 119.50 km2 (5.98% of land area), with a maximum depth of 6.08 m.
• The western coastal zones of Shenzhen (units 11–15) exhibit significantly higher inundation risk, with inundation areas 2.06 to 2.61 times greater than the eastern coast.
• Coastal urbanization characteristics, particularly artificial land use area and reclaimed land area, correlate positively and significantly with storm surge risk. Areas with high economic activities (Nighttime Light Index) and better vegetation coverage (NDVI) show a greater capacity for disaster reduction.
• Land reclamation markedly amplifies risk, with 79.74% (56.68 km2) of Shenzhen's total reclaimed area (71.08 km2) susceptible to storm surge inundation. Artificial land developed on reclaimed terrain faces 1.69 times higher risk than that on original terrain.
• High-density built-up areas and critical infrastructure (e.g., Airports and Ports Land, Transport and Infrastructure Land) experience disproportionately higher exposure. Artificial surfaces are 4.2 times more vulnerable to inundation than green spaces in the coastal zone.

Contributions

• Provides a mechanistic understanding of the complex interactions between anthropogenic urbanization processes (e.g., land reclamation, land-use patterns) and climatic hazards (storm surges, SLR).
• Quantitatively illustrates the statistical linkages between multiple urbanization factors and storm surge risks, identifying the relative importance of each factor.
• Offers a detailed evaluation of the exposure of specific land-use types and critical infrastructure to combined storm surge and SLR threats, highlighting adaptation disparities among green spaces, artificial surfaces, and reclaimed land.
• Delivers a scientific basis for climate adaptation and resilient spatial planning in hyper-urbanized coastal cities like Shenzhen, addressing a critical gap in the evidence base for such regions.

Funding

• General Program of the National Natural Science Foundation of China (grant number: 32271735)
• Shenzhen Science and Technology Program (grant number: KCXST20221021111416039)

Citation

@article{Luan2026Revealing,
  author = {Luan, Bo and Ye, X. X. and Luo, Jianing and Xie, Shiqi and Xia, Chenxi and Ning, Yanhong and Zhu, Mingjian},
  title = {Revealing the relationship between storm surge risks and coastal urbanization characteristics under sea level rise},
  journal = {Ecological Indicators},
  year = {2026},
  doi = {10.1016/j.ecolind.2026.114626},
  url = {https://doi.org/10.1016/j.ecolind.2026.114626}
}