Xiao et al. (2026) Flood risk assessment at electrical substations using a risk matrix coupled with a hydrodynamic model

Identification

• Journal: Natural Hazards
• Year: 2026
• Date: 2026-02-01
• Authors: Wei Xiao, Lei Shi, Xiaohua Ren, Wenbin Zang, Xiaoli Hao, Hongping Zhang
• DOI: 10.1007/s11069-025-07944-3

Research Groups

• State Grid Beijing Electric Power Research Institute, Beijing, China
• China Institute of Water Resources and Hydropower Research, Beijing, China

Short Summary

This study developed a methodological framework for facility-specific flood risk assessment of electrical substations by coupling a hydrodynamic model with a risk matrix and Analytic Hierarchy Process (AHP). Applied to 12 substations in the Dashi River Basin, the framework identified that nearly half of them are at risk of flooding, with two facing "particularly significant" risk, providing an actionable "Flood Mitigation Priority Action List" for power grid managers.

Objective

• To develop and apply an integrated framework for assessing the flood risk of electrical substations, combining quantitative flood likelihood (from hydrodynamic simulations) with semi-quantitative consequence severity (evaluated via AHP) through a risk matrix, to provide targeted flood resilience strategies.

Study Configuration

• Spatial Scale: Dashi River Basin, Fangshan District, Beijing, China. The basin has a total length of 129 km and an area of 1280 km². The study focused on 12 specific electrical substations (D1-D12) within this basin. The hydrodynamic model covered a 24.28 km river channel and approximately 267.48 km² of surface area.
• Temporal Scale: The study utilized time-series precipitation records with a 10-minute resolution and simulated flood events corresponding to 10-year, 20-year, 50-year, and 100-year recurrence periods. Model validation was performed using data from the "23·7 catastrophic flood event" (July 2023).

Methodology and Data

• Models used:
  • Risk matrix method (5x5 conversion matrix for possibility and severity).
  • One-dimensional and two-dimensional coupled hydrodynamic model (Saint–Venant equations for river channels, shallow water equations for surface flow).
  • Analytic Hierarchy Process (AHP) for evaluating the severity of inundation consequences.
• Data sources:
  • High-resolution Digital Elevation Model (DEM) with 2 m spatial resolution (Beijing Institute of Surveying and Mapping).
  • Land use map, soil map, and hydrological monitoring data (precipitation records, stage-discharge measurements) (Beijing Hydrological Station).
  • Field measurements of maximum inundation depths and severity indices for substations (State Grid Beijing Electric Power Company).
  • Post-event investigation report of the 23·7 catastrophic flood event for model validation (China Institute of Water Resources and Hydropower Research).
  • Substation ledger lists, flood control inspection lists, and expert scores for AHP indicator weighting.
  • Beijing Hydrological Handbook—Rainstorm Atlas for designed rainstorm data.

Main Results

• The coupled hydrodynamic model demonstrated high accuracy, with simulated maximum inundation depths for substations D9 and D12 differing from measured values by 0.2 m. Overall, 73.3% of 15 flood investigation points had water depth errors within 0.2 m.
• Flood simulations under different recurrence periods showed increasing inundation range and depth. For a 100-year flood, D9 and D12 experienced inundation depths of 4.10 m and 4.65 m, respectively, while D7, D10, and D11 also showed inundation.
• Based on the risk matrix, two substations (D9 and D12) were classified as having a "particularly significant flood risk" (Level IV), with a risk event magnitude of 20, due to very high possibility (Level 5) and high severity (Level 4).
• Three substations (D7, D10, and D11) were categorized as having a "high flood risk" (Level II), with risk magnitudes of 8 or 9.
• The remaining seven substations (D1-D6, D8) were classified as having a "general flood risk" (Level I), with risk magnitudes ranging from 2 to 6.
• The Analytic Hierarchy Process (AHP) determined that the importance level of the substation was the most influential factor in consequence severity (weight 0.434), followed by service life (0.254), engineering/technical protection measures (0.188), and materials/equipment management (0.124).
• The framework successfully generated a "Flood Mitigation Priority Action List," enabling targeted investments in structural reinforcements for high-risk facilities and management improvements for moderate-risk sites.

Contributions

• This study provides a novel integrated framework for facility-specific flood risk assessment of critical infrastructure (electrical substations), addressing a gap in existing literature that often focuses on macro-level regional risk zoning.
• It innovatively couples a physical-mechanism-based hydrodynamic model with a multi-criteria decision-making approach (AHP) and a risk matrix, allowing for a comprehensive and quantitative assessment of both flood likelihood and consequence severity at a micro-level.
• The framework generates actionable outputs, including risk zoning maps and a "Flood Mitigation Priority Action List," which directly supports power grid managers in optimizing disaster prevention budgets, prioritizing interventions (e.g., raising floodwalls, enhancing emergency planning), and improving the resilience of power systems.
• It demonstrates the feasibility and effectiveness of a combined quantitative and semi-quantitative assessment approach, offering a robust methodology for proactive flood risk management in the context of increasing extreme weather events.

Funding

• Science and Technology Project of State Grid Beijing Electric Power Company.
• Project Name: Research and Demonstration Application of Key Technologies for Flood Risk Assessment and Early Warning of Typical Substations (Rooms) in Beijing.
• Project Number: 520223240007.

Citation

@article{Xiao2026Flood,
  author = {Xiao, Wei and Shi, Lei and Ren, Xiaohua and Zang, Wenbin and Hao, Xiaoli and Zhang, Hongping},
  title = {Flood risk assessment at electrical substations using a risk matrix coupled with a hydrodynamic model},
  journal = {Natural Hazards},
  year = {2026},
  doi = {10.1007/s11069-025-07944-3},
  url = {https://doi.org/10.1007/s11069-025-07944-3}
}