Geospatial Approach For Assessment Of Vulnerability To Flood In Local Self Governments

Abstract

Recent years have shown a significant increase in the occurrence of flood globally, with impact on habitation and different sectors of the economy. This, in turn, necessitates the use of different flood mitigation strategies, wherein flood vulnerability assessment plays a significant role. The proposed work presents a methodology which combines vulnerability under physiographic and socio-economic domains to assess the overall flood vulnerability at the local self-government level. The methodology was illustrated to the case of Aluva municipality, located on the banks of River Periyar, in Kerala state, India. The spatial variation of hazard inducing factors and population statistics were analysed using GIS tools. The machine learning algorithm, Random Forest, which uses hazard inducing factors as input was implemented for the evaluation of physiographic vulnerability. The social vulnerability of the region was analysed using GIS Multi-criteria decision analysis approach, with criteria weights to incorporate the interests of different stakeholders. The critical combinations of the two domains of vulnerability in the assessment of the vulnerability to flood, to have efficient flood management in local self-government was demonstrated in this study and can be made use of for any flood event.