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<p>Lokoja, the capital of Kogi State in North Central Nigeria, is considered a high-risk area for flooding due to its inherent flood susceptibility and history of devastating floods. Effective flood susceptibility mapping is crucial for managing such regions. This study proposes a Pentagonal Fuzzy Number Integral Value FuzzyAHP (PFN-FAHP) method combined with geospatial techniques to improve flood susceptibility assessments. Using six key flood causative factors, the generated flood susceptibility map classifies 20.53% of the area as Very High Susceptibility, 18.40% as High Susceptibility, and 16.11% as Moderate Susceptibility. Validation with Sentinel-1 SAR imagery acquired on October 13, 2022, confirms reliability, with high-risk zones aligning closely with actual flood extents. Compared to Triangular Fuzzy Number FAHP (TFN-FAHP) and Trapezoidal Fuzzy Number FAHP (TrFN-FAHP), PFN-FAHP achieves a 13.06% improvement in mapping Very High Susceptibility areas over TFN-FAHP and 0.54% over TrFN-FAHP, driven by its superior uncertainty handling. These improvements demonstrate the superior performance of PFN-FAHP in mapping flood-prone regions, making it a more reliable model for flood susceptibility assessment. These findings establish PFN-FAHP as a valuable tool for flood mitigation strategies in Lokoja and similar regions, offering improved accuracy and proactive flood risk management.</p>

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Flood Susceptibility Mapping for Lokoja Metropolis Using a Pentagonal Integral Value Fuzzy AHP Model and Geospatial Techniques

  • 期刊论文

  • 发表日期：

    2026年1月27日

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  • Abimbola Atijosan,
  • Ibrahim Isa

摘要

Lokoja, the capital of Kogi State in North Central Nigeria, is considered a high-risk area for flooding due to its inherent flood susceptibility and history of devastating floods. Effective flood susceptibility mapping is crucial for managing such regions. This study proposes a Pentagonal Fuzzy Number Integral Value FuzzyAHP (PFN-FAHP) method combined with geospatial techniques to improve flood susceptibility assessments. Using six key flood causative factors, the generated flood susceptibility map classifies 20.53% of the area as Very High Susceptibility, 18.40% as High Susceptibility, and 16.11% as Moderate Susceptibility. Validation with Sentinel-1 SAR imagery acquired on October 13, 2022, confirms reliability, with high-risk zones aligning closely with actual flood extents. Compared to Triangular Fuzzy Number FAHP (TFN-FAHP) and Trapezoidal Fuzzy Number FAHP (TrFN-FAHP), PFN-FAHP achieves a 13.06% improvement in mapping Very High Susceptibility areas over TFN-FAHP and 0.54% over TrFN-FAHP, driven by its superior uncertainty handling. These improvements demonstrate the superior performance of PFN-FAHP in mapping flood-prone regions, making it a more reliable model for flood susceptibility assessment. These findings establish PFN-FAHP as a valuable tool for flood mitigation strategies in Lokoja and similar regions, offering improved accuracy and proactive flood risk management.