Waterlogging Risk Assessment of Airport Airfield Areas Using the Analytic Network Process with Triangular Fuzzy Numbers

Risk assessment is an effective management tool for mitigating waterlogging disasters. In this study, a novel airport waterlogging risk assessment framework based on the analytic network process with triangular fuzzy numbers (TFN-ANP) was developed to evaluate hazard, exposure, vulnerability, and comprehensive risk under different return periods. The proposed framework was compared with the triangular fuzzy analytic hierarchy process (TFN-AHP). The results indicated that water depth, land cover type, and maintenance cost exerted dominant influences on hazard, exposure, and vulnerability, respectively. Compared with TFN-AHP, TFN-ANP produced different global weight distributions and a broader spatial extent of high-risk areas. Under the 50-year return period, TFN-ANP classified 31.65% of the study area as highest-risk, whereas TFN-AHP did not delineate any highest-risk zones and classified 40.05% of the study area as higher risk. A similar pattern was observed under the 100-year return period. TFN-ANP delineated 35.41% of the study area as being at the highest risk under the 100-year return period. By explicitly accounting for interdependencies among risk factors, TFN-ANP generated more differentiated spatial risk patterns. The proposed framework provides an effective decision-support tool for waterlogging risk management in data-scarce airport environments.