Gün et al. (2026) A New Framework for Comprehensive Flood Risk Assessment Under Non-Stationary Conditions Using GIS-Based MCDM Modeling

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Identification

• Journal: Atmosphere
• Year: 2026
• Date: 2026-01-03
• Authors: Reşat Gün, Muhammet Yılmaz
• DOI: 10.3390/atmos17010062

Research Groups

Not explicitly stated in the provided text.

Short Summary

This study integrates multi-criteria decision-making (MCDM) with non-stationary rainfall quantiles to assess and prioritize urban flood risk in Izmir, Türkiye. It finds that under non-stationary conditions, higher rainfall return periods lead to an expansion of high-risk areas and a contraction of low-risk areas.

Objective

• To identify and prioritize flood risk areas in Izmir, Türkiye, by integrating MCDM-based flood hazard mapping techniques with rainfall quantiles calculated for different return periods under non-stationary conditions.

Study Configuration

• Spatial Scale: Izmir, Türkiye, focusing on 165 specific points within the city.
• Temporal Scale: Current flood risk assessment and future flood risk scenarios based on 10-, 20-, 50-, and 100-year rainfall return periods under non-stationary conditions.

Methodology and Data

• Models used: Analytical Hierarchy Process (AHP), VIseKriterijumsa Optimizacija I Kompromisno Resenje (VIKOR), Generalized Additive Models for Location, Scale, and Shape (GAMLSS). Geographic Information System (GIS) was used for integration and mapping.
• Data sources: Rainfall estimates (derived using GAMLSS for non-stationary conditions), Geographic Information System (GIS) data (for spatial analysis and mapping).

Main Results

• For the current flood risk assessment, Buca, Menderes, Bornova, Kemalpaşa, Çeşme, Torbalı, Menemen, Seferihiri, and Çiğli were identified as high-flood-risk areas. The highest-flood-risk points were R91 (Çeşme), R153 (Buca), and R93 (Çeşme).
• As rainfall return periods increase under non-stationary conditions, high-risk areas expand, while low-risk areas shrink.
• Quantitatively, the proportion of very-low-risk areas declined from 15.12% for the 10-year return period to 13.92% for the 100-year return period.
• Conversely, the proportion of very-high-risk areas increased from 6.73% for the 10-year return period to 7.53% for the 100-year return period.
• For the four future scenarios (10-, 20-, 50-, and 100-year return periods), points R55, R56, and R54 in Kemalpaşa consistently showed the highest flood risk.

Contributions

• Addresses a research gap by integrating MCDM-based flood hazard mapping with rainfall quantiles calculated for different return periods under non-stationary conditions within a GIS framework.
• Provides a comprehensive flood risk assessment methodology that accounts for the dynamic nature of rainfall patterns due to climate change.
• Identifies specific high-risk areas and points in Izmir, Türkiye, under both current and future non-stationary rainfall conditions.

Funding

Not explicitly stated in the provided text.

Citation

@article{Gün2026New,
  author = {Gün, Reşat and Yılmaz, Muhammet},
  title = {A New Framework for Comprehensive Flood Risk Assessment Under Non-Stationary Conditions Using GIS-Based MCDM Modeling},
  journal = {Atmosphere},
  year = {2026},
  doi = {10.3390/atmos17010062},
  url = {https://doi.org/10.3390/atmos17010062}
}