PMID- 36180798 OWN - NLM STAT- MEDLINE DCOM- 20230210 LR - 20230210 IS - 1614-7499 (Electronic) IS - 0944-1344 (Linking) VI - 30 IP - 6 DP - 2023 Feb TI - A comparative assessment of flood susceptibility modelling of GIS-based TOPSIS, VIKOR, and EDAS techniques in the Sub-Himalayan foothills region of Eastern India. PG - 16036-16067 LID - 10.1007/s11356-022-23168-5 [doi] AB - In the Sub-Himalayan foothills region of eastern India, floods are considered the most powerful annually occurring natural disaster, which cause severe losses to the socio-economic life of the inhabitants. Therefore, the present study integrated geographic information system (GIS) and three comprehensive and systematic multicriteria decision-making (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 multi-dimensional 21 indicators were considered, and multicollinearity statistics were employed to erase the issues regarding highly correlated parameters (i.e., MFI and long-term annual rainfall). Results of MCDM models depicted that the riparian areas and riverine "chars" (islands) are the most susceptible sectors, accounting for around 40% of the total area. The microlevel assessment revealed that flooding was most susceptible in the Tufanganj-I, Tufanganj-II, and Mathabhanga-I blocks, while Haldibari, Sitalkuchi, and Sitai blocks were less susceptible. Spearman's rank (r(s)) tests among the three MCDM models revealed that TOPSIS-EDAS persisted in a high correlation (r(s) = 0.714) in contrast to the relationships between VIKOR-EDAS (r(s) = 0.651) and TOPSIS-VIKOR (r(s) = 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. Thus, this kind of study addresses the role of GIS in the construction of the flood susceptibility of the region and the performance of the respective models in a very lucid manner. CI - (c) 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. FAU - Mitra, Rajib AU - Mitra R AUID- ORCID: 0000-0002-3018-8935 AD - Department of Geography and Applied Geography, University of North Bengal, PO- North Bengal University, Dist- Darjeeling, 734013, India. FAU - Das, Jayanta AU - Das J AUID- ORCID: 0000-0003-0995-9114 AD - Department of Geography, Rampurhat College, PO- Rampurhat, Dist- Birbhum, 731224, India. jayanta.daas@gmail.com. LA - eng PT - Journal Article DEP - 20220930 PL - Germany TA - Environ Sci Pollut Res Int JT - Environmental science and pollution research international JID - 9441769 SB - IM MH - *Floods MH - *Geographic Information Systems MH - India MH - Area Under Curve OTO - NOTNLM OT - Correlation studies OT - Flood susceptibility mapping OT - GIS OT - Koch Bihar district OT - Multicriteria decision-making EDAT- 2022/10/01 06:00 MHDA- 2023/02/11 06:00 CRDT- 2022/09/30 23:42 PHST- 2022/06/03 00:00 [received] PHST- 2022/09/18 00:00 [accepted] PHST- 2022/10/01 06:00 [pubmed] PHST- 2023/02/11 06:00 [medline] PHST- 2022/09/30 23:42 [entrez] AID - 10.1007/s11356-022-23168-5 [pii] AID - 10.1007/s11356-022-23168-5 [doi] PST - ppublish SO - Environ Sci Pollut Res Int. 2023 Feb;30(6):16036-16067. doi: 10.1007/s11356-022-23168-5. Epub 2022 Sep 30.