In the Sub-Himalayan foothills region of eastern India, floods are considered the most powerful annually occurring natural disaster, which causes severe losses to the socio-economic life of the inhabitants. The present study tested three comprehensive and systematic MCDM techniques such as Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Vise Kriterijumska Optimizacijaik Ompromisno Resenje (VIKOR), and Evaluation Based on Distance from Average Solution (EDAS) in Koch Bihar district for comparative assessment of the flood susceptible zones.The 21 indicators, i.e., elevation, slope, drainage density, geomorphology, rainfall deviation, aspect, curvature, lineament density, lithology, long-term annual rainfall, land use land cover, modified fournier index, modified normalized difference water index, normalized difference vegetation index, roughness, soil, sediment transport index, stream power index, topographic positioning index, terrain ruggedness index, and topographic wetness index were considered as the essential flood conditioning parameters. The multicollinearity statistics were employed to erase the issues regarding highly correlated parameters (i.e., MFI and long-term annual rainfall). The Spearman's rank (πβ) tests among the three models revealed that TOPSIS-EDAS persisted in a high correlation (πβ = 0.714) in contrast to the relationships between VIKOR-EDAS (πβ = 0.651) and TOPSIS-VIKOR (πβ = 0.639). The model's efficiency was statistically judged by applying the Receiver Operating Characteristic-Area Under the Curve (ROC-AUC), Mean Absolute Error (MAE), Mean Square Error (MSE), and Root Mean Square Error (RMSE) techniques to recognize the better-suited models for mapping the flood susceptibility. The performance of all techniques is found good enough (ROC-AUC = >0.700 and MAE, MSE and RMSE = <0.300). However, TOPSIS and VIKOR have manifested an excellent outcome and are highly recommended for identifying flood susceptibility in such active flood-prone areas.
