<p>Flood susceptibility mapping requires methods capable of capturing uncertainty in expert judgment and environmental variability. This study proposes a Pentagonal Interval Type-2 Fuzzy Analytic Hierarchy Process (PIT2FAHP) to enhance flood susceptibility assessment in Asaba, Nigeria. PIT2FAHP extends conventional fuzzy AHP by employing interval Type-2 fuzzy sets with pentagonal membership structures, providing a richer representation of higher-order uncertainty. Five conditioning factors, distance to active drainage channels, rainfall, elevation, slope, and land use, were selected based on their dominant hydrological influence on urban flooding in riverine environments, widespread use in prior studies, and data availability constraints in a data-scarce setting, while ensuring model parsimony. Validation against the October 2022 flood event using Sentinel-1 SAR imagery showed strong spatial agreement. PIT2FAHP captured 94.33% (41.30&#xa0;km²) of the observed flood extent within the “Very High” susceptibility class, compared with 91.92% and 89.25% for the triangular interval Type-2 FAHP and triangular Type-1 FAHP models, respectively, demonstrating the best performance among the evaluated models. The strong dominance of the “Very High” class (&gt; 90% of the flood extent) reflects the low-lying floodplain geomorphology of Asaba and its proximity to the River Niger. PIT2FAHP performance was evaluated using the consistency ratio (CR = 0.0396, below  0.1), entropy (0.9033), and variance (0.015954), demonstrating improved decision consistency and class separability compared with the triangular interval Type-2 FAHP and triangular Type-1 FAHP models. These results indicate that PIT2FAHP provides a more reliable framework for flood-prone zone identification, supporting flood mitigation and planning in rapidly urbanizing riverine environments.</p>