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Multi-hazard probability assessment and mapping in Iran.

Hamid Reza Pourghasemi1, Amiya Gayen2, Mahdi Panahi3

  • 1Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran.

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|July 28, 2019
PubMed
Summary

A new ensemble model combining SWARA, ANFIS, and GWO effectively mapped multi-hazard risks including floods, landslides, and earthquakes in Iran's Lorestan Province. This tool aids sustainable land use and infrastructure planning in hazard-prone regions.

Keywords:
ANFISEnsembles modelsGray wolf approachLandslide, floods, earthquakesMulti-hazard mappingSWARA

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Area of Science:

  • Geosciences
  • Environmental Science
  • Risk Management

Background:

  • Iran's Lorestan Province faces significant risks from multiple natural hazards.
  • Effective risk reduction necessitates understanding individual hazards and their interactions.
  • Previous studies often focus on single hazards, limiting comprehensive management strategies.

Purpose of the Study:

  • To develop a multi-hazard probability map for floods, landslides, and earthquakes in Lorestan Province.
  • To implement and validate a novel ensemble model (SWARA-ANFIS-GWO) for hazard assessment.
  • To provide a tool for informed land use planning and sustainable infrastructure development.

Main Methods:

  • Utilized SWARA (Stepwise Weight Assessment Ratio Analysis) for factor weighting and spatial relationship analysis.
  • Employed ANFIS (Adaptive Neuro-Fuzzy Inference System) integrated with a Gray Wolf Optimizer (GWO) metaheuristic algorithm for susceptibility mapping.
  • Prepared individual hazard maps using occurrence data, terrain/land use factors, and probabilistic seismic hazard analysis (PSHA).

Main Results:

  • The SWARA-ANFIS-GWO model achieved high accuracy in susceptibility mapping, with Area Under the Curve (AUC) values up to 87% for training data and 84% for validation data.
  • Individual flood, landslide, and earthquake susceptibility maps were generated.
  • A comprehensive multi-hazard probability map for Lorestan Province was created by integrating the individual hazard maps.

Conclusions:

  • The developed multi-hazard probability map is a crucial tool for managing natural hazards in Lorestan Province.
  • The SWARA-ANFIS-GWO ensemble model demonstrates strong performance for multi-hazard risk assessment.
  • The findings support sustainable land use planning and infrastructure development in hazard-prone areas.