Abstract
Floods are one of the natural disasters that occur most frequently in the Brahmani River of Eastern India. Frequent floods in the area, results from anthropogenic activities, climate change, unpredictable weather, and heavy rainfall cause loss of life, property, and resources. Flood hazard susceptibility maps will help in identifying risk-prone locations, which aids in flood management and the decision-making process. The main objective of this study is to evaluate the performance of bivariate statistical and hybrid models such as Frequency ratio, Weight of Evidence (WoE), Evidential Belief Function (EBF), Index of Entropy, Analytical Hierarchy Process (AHP), AHP–TOPSIS and AHP VIKOR to prepare flood susceptibility maps of the Brahmani River basin, India. The flood conditioning factor includes Slope, Aspect, Elevation, Curvature, Geology, Geomorphology, Topographic Wetness Index, Topographic Ruggedness Index, Distance from Streams, Distance from Roads, Rainfall, Normalized Difference Vegetation Index (NDVI), Stream Power Index, Soil, Drainage Density, and Land use Land cover. The flood inventory was prepared using various atlas and news reports. Multicollinearity among all the causative parameters is measured using the Variance Inflation factor (VIF) and Tolerance (TOL). The collection of a spatial database and flood inventory from various sources is used to prepare flood susceptibility maps. The flood susceptibility map is categorised into very high, high, moderate, low, and very low classes using the natural break method. The models are validated using flood training (70%) and testing (30%) points. The accuracy of flood susceptibility maps is determined using Area Under Receiver Operating Characteristics (AUROC) curves and Seed Cell Area Index (SCAI) values. The success rate of Frequency ratio (AUC 0.91), EBF (AUC 0.90) and WoE (AUC 0.86) show the highest accuracy among all other models in AUC. WoE, IoE, and FR gave reliable results in the SCAI validation process. The susceptibility maps will help in identifying hazard-prone areas, which will help policy makers better assessment of natural hazards.
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Anand, A.K., Pradhan, S.P. Evaluation of bivariate statistical and hybrid models for the preparation of flood hazard susceptibility maps in the Brahmani River Basin, India. Environ Earth Sci 82, 389 (2023). https://doi.org/10.1007/s12665-023-11069-w
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DOI: https://doi.org/10.1007/s12665-023-11069-w