Comprehensive Seismic Risk Analysis for Denizli Province

Strategic Insights -

Researchers from Firat University have conducted a critical study to assess seismic risk in Denizli Province, a region in Turkey known for its industrial and touristic significance. The team utilized a combination of Analytic Hierarchy Process, Random Forest, and Frequency Ratio methods to create detailed susceptibility maps and classify risk levels into five categories. The study's findings highlight the urgency of implementing effective earthquake risk management policies and urban planning strategies in the area.

Key Takeaways:

  • The study integrates multiple analytical approaches, including AHP, Random Forest, and Frequency Ratio methods, to provide a comprehensive seismic risk assessment for Denizli Province.
  • The integrated risk map indicates that 29.3% of the province's total area falls into the 'very low' risk category, while 1.5% is classified as 'very high' risk.
  • The study identifies densely populated districts, such as Pamukkale and Merkezefendi, as being under elevated seismic threat.
  • The research concludes that effective earthquake risk management policies and urban planning strategies are necessary for Denizli Province.
  • The study utilizes geological, topographic, and seismic data to generate seismic susceptibility maps, classifying risk levels into five categories: very low, low, moderate, high, and very high.
  • The study highlights the importance of regional risk-mitigation strategies, particularly in areas prone to frequent earthquakes, such as Acıpayam.

Statistics:

  • 29.3% of Denizli Province's total area falls into the 'very low' risk category.
  • 27.1% falls into the 'low' risk category.
  • 32.6% falls into the 'moderate' risk category.
  • 9.6% falls into the 'high' risk category.
  • 1.5% falls into the 'very high' risk category.
  • 48.21% of the province's residents live within the 'very high' and 'high' risk zones.
  • 29.3% of the province's total area falls into the 'very low' risk category.

Sources:

  • Integrated Seismic Risk Assessment Using Multi-criteria Decision Making, Statistical, and Machine Learning Approaches: a Case Study of Denizli, Turkiye. Natural Hazards, 2025.
  • NewsRx. Findings from Firat University in the Area of Machine Learning Reported (Integrated Seismic Risk Assessment Using Multi-criteria Decision Making, Statistical, and Machine Learning Approaches: a Case Study of Denizli, Turkiye). Journal of Engineering. October 13, 2025; p 652.