Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3133
Title: A GIS-Based Comparative Analysis of Frequency Ratio and Statistical Index Models for Flood Susceptibility Mapping in the Upper Krishna Basin, India
Authors: Pawar, U
Suppawimut, W
Muttil, N
Rathnayake, U
Keywords: Upper Krishna Basin
flood susceptibility mapping
frequency ratio
statistical index models
precipitation
Issue Date: 20-Nov-2022
Publisher: MDPI
Citation: Pawar, U.; Suppawimut, W.; Muttil, N.; Rathnayake, U. A GIS-Based Comparative Analysis of Frequency Ratio and Statistical Index Models for Flood Susceptibility Mapping in the Upper Krishna Basin, India. Water 2022, 14, 3771. https://doi.org/10.3390/w14223771
Series/Report no.: Water (Switzerland);Volume 14, Issue 22
Abstract: The Upper Krishna Basin in Maharashtra (India) is highly vulnerable to floods. This study aimed to generate a flood susceptibility map for the basin using Frequency Ratio and Statistical Index models of flood analysis. The flood hazard inventory map was created by 370 flood locations in the Upper Krishna Basin and plotted using ArcGIS 10.1 software. The 259 flood locations (70%) were selected randomly as training samples for analysis of the flood models, and for validation purposes, the remaining 111 flood locations (30%) were used. Flood susceptibility analyses were performed based on 12 flood conditioning factors. These were elevation, slope, aspect, curvature, Topographic Wetness Index, Stream Power Index, rainfall, distance from the river, stream density, soil types, land use, and distance from the road. The Statistical Index model revealed that 38% of the area of the Upper Krishna Basin is in the high- to very-high-flood-susceptibility class. The precision of the flood susceptibility map was confirmed using the receiver operating characteristic and the area under the curve value method. The area under the curve showed a 66.89% success rate and a 68% prediction rate for the Frequency Ratio model. However, the Statistical Index model provided an 82.85% success rate and 83.23% prediction rate. The comparative analysis of the Frequency Ratio and Statistical Index models revealed that the Statistical Index model was the most suitable for flood susceptibility analysis and mapping flood-prone areas in the Upper Krishna Basin. The results obtained from this research can be helpful in flood disaster mitigation and hazard preparedness in the Upper Krishna Basin.
URI: https://rda.sliit.lk/handle/123456789/3133
ISSN: 20734441
Appears in Collections:Department of Civil Engineering

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