Flood Susceptibility Analysis in Chennai Corporation Using Frequency Ratio Model
Natural disasters like flood are causing massive damages to natural and human resources, especially in coastal areas. In respect to social, economic and environmental perspective, flood is one of the most devastating disasters in Chennai for the recent days. Flood susceptibility mapping using freque...
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Veröffentlicht in: | Journal of the Indian Society of Remote Sensing 2021-07, Vol.49 (7), p.1533-1543 |
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Sprache: | eng |
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Zusammenfassung: | Natural disasters like flood are causing massive damages to natural and human resources, especially in coastal areas. In respect to social, economic and environmental perspective, flood is one of the most devastating disasters in Chennai for the recent days. Flood susceptibility mapping using frequency ratio model was done for the 88 micro watersheds of Adyar, Cooum and Kosasthalaiyar watersheds of Chennai Corporation area. Flood Susceptibility map was generated using frequency ratio model by considering ten different independent variables (landuse/land cover, elevation, slope, topographic wetness index, surface runoff, landform, lithology, distance from the main river, soil texture and soil drainage) through weighted-based bivariate probability values. In total, 123 historic flood reported locations were taken for this study from which 100 locations were used for susceptibility mapping and 23 locations were used for validation. Both the independent variables and historic flood locations were combined together to generate frequency ratio database for flood susceptibility mapping. The developed frequency ratio was varied from 0 to 27.11 and reclassified into five flood vulnerability zones namely, very low (less than 5.0), low (5.0 7.5), moderate (7.5–10.0), high (10.0–12.5) and very high susceptibility (more than 12.5). The result revealed that 10.48 and 38.93 percentage of the land have very high and high vulnerable class, respectively. The frequency ratio model validated using 23 flood locations, where 22 locations are presented in high and very high susceptibility class. This analysis exemplified that prediction was with success rate of 95.6%. The flood susceptibility analysis using this model will be very useful and efficient tool to the local government administrators, researchers and planners for devising flood mitigation plans. |
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ISSN: | 0255-660X 0974-3006 |
DOI: | 10.1007/s12524-021-01331-8 |