Multi-criteria decision based geospatial mapping of flood susceptibility and temporal hydro-geomorphic changes in the Subarnarekha basin, India

The Subarnarekha River in east India experiences frequent high magnitude flooding in monsoon season. In this study, we present an in-depth analysis of flood hydrology and GIS-based flood susceptibility mapping of the entire catchment. About 40 years of annual peak discharge data, historical cross-sections of different gauging sites, and 12 flood conditioning factors were considered. Our flood susceptibility mapping followed an expert knowledge-based multi-parametric analytical hierarchy process (AHP) and optimized AHP-VIP methods. Peak hydrology data indicated more than 5 times higher discharge contrasted with the mean streamflow of the peak monsoon month in all hydro-monitoring stations that correspond to possible overbank flooding in the shallow semi-alluvial reaches of the Subarnarekha River. Width-depth ratio revealed continuous changes on the channel cross-sections at decadal scale in all gauging sites. Predicted flood susceptibility map through optimized AHP-VIP method showed a great amount of areas (38%) have a high probability of flooding and demands earnest attention of administrative bodies. The AHP-VIP based flood susceptibility map was theoritically validated through AUC approach and it showed fairly high accuracy (AUC = 0.93). Our study offers an exceptionally cost and time effective solution to the flooding issues in the Subarnarekha basin. (C) 2021 China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

This study conducted an in-depth analysis of flood hydrology and GIS-based flood susceptibility mapping of the entire catchment of the Subarnarekha River in east India. The study found that in the flood season, the river's peak discharge is more than 5 times higher than the mean streamflow, leading to possible overbank flooding. The predicted flood susceptibility map showed that 38% of the areas have a high probability of flooding, requiring urgent attention from administrative bodies.