Development of new composite index on channel sensitivity using AHP, FR and ensemble model and its application on the Mayurakshi river of Eastern India. Issue 4 (2nd October 2022) - Ghosh, Abhishek; Maiti, Ramkrishna
ABSTRACT: The Mayurakshi river is one of the most important rivers in the Geographical Scenario of Eastern India. The river is subject to several morphological alterations due to complex interaction with the natural eco-geomorphological setup and human interferences. Therefore, the present study aims to understand the morphological sensitivity of the Mayurakshi river due to eco-geomorphological variations and haphazard human interferences. The channel sensitivity is combinedly determined by natural geomorphic set-up, anthropogenic interventions and resilience factors. Natural geomorphic setup was assessed through the inception of geological, morphological and cross-sectional characters of the channel. Different types of anthropogenic interferences were selected as the provocative factor and near-bank and in-stream vegetation cover was contemplated as resilience factor. Published maps, Topographical sheets published by Survey of India, Digital Elevation Model and satellite images were used to understand the general geomorphological setup and channel morphological variations. High-resolution Google Earth Image and Global Positioning System were combinedly used to detect different forms of anthropogenic interferences. Besides, near-bank and in-stream vegetation cover was measured using satellite image and field observations. Finally, the channel sensitivity index was prepared using analytical hierarchy process (AHP), frequency ratio (FR) model and ensemble of AHP and FR models. All three models show a high degree of channel sensitivity in lower-middle reaches of the river due to high channel sinuosity, steep bank angle, high channel incision rate and intense human interferences. The efficiency of the three models was verified from field survey using the ROC curve (receiver operating characteristics) and Kappa statistics. The validation results show that the parameters and methods selected for this research are highly effective in assessing the channel sensitivity of Mayurakshi river.